service innovation in consumer-centric …file/...service innovation in consumer-centric information...

Service Innovation in Consumer-Centric Information Systems:

A Socio-Technical Perspective

DISSERTATION

of the University of St. Gallen,

School of Management,

Economics, Law, Social Sciences

and International Affairs

to obtain the title of

Doctor of Philosophy in Management

submitted by

Benjamin Spottke

from

Germany

Approved on the application of

Prof. Dr. Walter Brenner

and

Prof. Dr. Jan vom Brocke

Dissertation no. 4803

Digitaldruckhaus GmbH, Konstanz 2018

The University of St. Gallen, School of Management, Economics, Law, Social Sciences

and International Affairs hereby consents to the printing of the present dissertation,

without hereby expressing any opinion on the views herein expressed.

St. Gallen, May 22, 2018

The President:

Prof. Dr. Thomas Bieger

Acknowledgements I

Acknowledgements

This thesis is the result of my journey at the Institute of Information Management at

University of St.Gallen in Switzerland, which started end of 2014. In these years of

intense studying many people contributed substantially to make this thesis happen.

First and foremost, I thank Prof. Dr. Walter Brenner for his personal support, his

supervision of my thesis, and for providing the great working environment that made

this research possible. I also thank Prof. Dr. Jan vom Brocke for his willingness to co-

supervise my thesis, as well as his encouragement and inspiration in doctoral seminars

and personal exchanges in St. Gallen and Vaduz. I would like to express my special

appreciation to Dr. Jochen Wulf, senior lecturer and research fellow at the Institute of

Information Management, for our stimulating and rewarding collaboration, and for his

guidance and engagement in our joint research projects.

For their untiring organizational advice and support, I would like to thank Barbara

Rohner, Dr. Jochen Müller, Dr. Peter Gut and Susanne Gmünder. With the help of these

colleagues, I could safely navigate through the organizational matters and traditions that

shape the unique culture of our Institute. Much of my research was inspired by the close

collaboration with industry partners. I am especially grateful to Andi Maier and Fiorenzo

Maletta from AXA Winterthur, and Wolfgang Zimmermann from Migros

Genossenschaftsbund. These partners have constantly challenged my assumptions and

provided vital feedback to progress my research.

I feel privileged to have worked with fantastic colleagues at our Institute. My special

thanks go to Alexander Eck, who inspired and challenged much of my research into

productive directions. Many others have helped me finding my way through the process.

In particular, I would like to express my gratitude to Prof. Dr. Robert Winter, and Prof.

Dr. Kazem Haki for their advice and for reliably pointing to areas of improvement in

my research. Much of my experience was shaped by my fellow PhD students. I am

especially grateful to Dr. Rieke Bärenfänger, Dr. Sabine Berghaus, Christian Dremel,

Tuomo Eloranta, Jennifer Hehn, Manuel Holler, and Emanuel Stöckli for the countless

constructive and encouraging discussions.

Finally, I wish to thank my family and friends for encouraging and supporting me

throughout this dissertation and, of course, Renske van Giffen, who has motivated and

helped me in ways I could never have imagined.

St.Gallen, January 2018 Benjamin Spottke

Table of contents III

Table of contents

Acknowledgements ........................................................................................................ i

Table of contents .......................................................................................................... iii

List of abbreviations ................................................................................................... vii

List of figures ................................................................................................................ ix

List of tables .................................................................................................................. xi

Abstract ....................................................................................................................... xiii

Kurzfassung ................................................................................................................. xv

Part A ............................................................................................................................. 1

1 Introduction ............................................................................................................. 1

2 Thesis structure and research results ................................................................... 3

3 Discussion and future research .............................................................................. 9

4 Reference overview of articles in this thesis ....................................................... 13

4.1 Consumer-Centric Information Systems: A Literature Review and Avenues

for Further Research ....................................................................................... 13

4.2 A Socio-Technical Approach to Study Consumer-Centric Information

Systems .......................................................................................................... 14

4.3 What Companies Can Learn from the Videogame Industry for the Design of

the Digital Customer Experience: An Analysis of the Platform Steam ......... 15

4.4 Service Innovation in Social Networking Services: A Resource Integration

Perspective on Facebook ................................................................................ 16

Part B ........................................................................................................................... 17

I Consumer-Centric Information Systems: A Literature Review and Avenues

for Further Research ............................................................................................ 17

I.1 Introduction .................................................................................................... 18

I.2 Foundational theory ....................................................................................... 20

I.3 Research methodology ................................................................................... 22

I.4 Organizational objectives of customer centricity .......................................... 23

I.5 Characteristics and antecedents of CCIS ....................................................... 27

IV Table of contents

I.6 Conclusion and further research .................................................................... 30

II A Socio-Technical Approach to Study Consumer-Centric Information

Systems ................................................................................................................... 31

II.1 Introduction .................................................................................................... 32

II.2 Theoretical foundation ................................................................................... 34

II.3 Methodology .................................................................................................. 38

II.4 The case of Steam: illustration of research model and research design ........ 42

II.5 Acknowledgements ........................................................................................ 45

III What Companies Can Learn from the Videogame Industry for the Design of

the Digital Customer Experience: An Analysis of the Platform Steam ........... 47

III.1 Einleitung und Motivation ............................................................................. 48

III.2 Steam als führende Plattform der Videospieleindustrie ................................ 50

III.3 Datenerhebung und Analyse .......................................................................... 51

III.4 Gestaltungsebenen digitaler Plattformen und ihre Bedeutung für die Digital

Customer Experience bei Steam .................................................................... 52

III.5 Illustration der Handlungsempfehlungen in Automobil-, Unterhaltungs- und

Versicherungsbranche .................................................................................... 59

III.6 Zusammenfassung und Ausblick ................................................................... 62

III.7 Danksagung .................................................................................................... 62

IV Service Innovation in Social Networking Services: A Resource Integration

Perspective on Facebook ...................................................................................... 63

IV.1 Introduction .................................................................................................... 64

IV.2 Related research and conceptual basis ........................................................... 67

IV.3 Methodology .................................................................................................. 73

IV.4 Facebook case findings .................................................................................. 82

IV.5 Task-centered service innovation................................................................... 83

IV.6 Technology-centered service innovation ....................................................... 89

IV.7 Structure-centered service innovation ............................................................ 95

IV.8 Discussion ...................................................................................................... 99

IV.9 Conclusion ................................................................................................... 104

Table of contents V

IV.10 Appendix 1: Chronology of the Facebook Newsfeed ................................ 105

IV.11 Appendix 2: Typologies of resources ......................................................... 109

References .................................................................................................................. 111

Publication list of the author .................................................................................... xvii

Curriculum vitae ........................................................................................................ xix

List of abbreviations VII

List of abbreviations

CCIS Consumer-Centric Information System

HMD HMD Praxis der Wirtschaftsinformatik

ICIS International Conference on Information Systems

IS Information systems

IT Information technology

IWI-HSG Institute of Information Management, University of St. Gallen

PhD Doctor of Philosophy

RQ Research question

S-D Service-dominant

SNS Social Networking Service

S-T Socio-Technical

List of figures IX

List of figures

Figure 1. Overview of thesis structure and constitutive articles ................................... 3

Figure 2. Research model of a consumer-centric IS ..................................................... 5

Figure 3. Components and interrelationships of socio-technical systems .................. 20

Figure 4. Characteristics and antecedents of CCIS..................................................... 27

Figure 5. Research model of a consumer-centric IS ................................................... 36

Figure 6. Chronology of key events in the history of Steam ...................................... 43

Figure 7. Entwicklung aktiver Accounts und verfügbarer Spiele auf Steam ............. 50

Figure 8. Resource integration model and main theoretical constructs ...................... 70

Figure 9. Newsfeed and exemplary features ............................................................... 79

Figure 10. Data-driven innovation mechanism............................................................. 87

Figure 11. Technology propulsion mechanism ............................................................ 92

Figure 12. Social debugging mechanism ...................................................................... 97

List of tables XI

List of tables

Table 1. Bibliographic information for Article I ....................................................... 13

Table 2. Bibliographic information for Article II ...................................................... 14

Table 3. Bibliographic information for Article III .................................................... 15

Table 4. Bibliographic information for Article IV .................................................... 16

Table 5. Bibliographic information for Article I ....................................................... 17

Table 6. Results of the literature search .................................................................... 23

Table 7. Organizational objectives of consumer centricity ....................................... 24

Table 8. Bibliographic information for Article II ...................................................... 31

Table 9. Steps in within-case analysis ....................................................................... 41

Table 10. Illustrative results of within-case Analysis ................................................. 44

Table 11. Bibliographic information for Article III .................................................... 47

Table 12. Overview of results ..................................................................................... 58

Table 13. Bibliographic information for Article IV .................................................... 63

Table 14. Data analysis ................................................................................................ 77

Table 15. Coding of involved resources on feature level ............................................ 81

Table 16. Task-centered service innovations in the Newsfeed ................................. 105

Table 17. Technology-centered service innovations in the Newsfeed ...................... 107

Table 18. Structure-centered service innovations in the Newsfeed .......................... 108

Table 19. Typology of resources involved in task-centered innovations .................. 109

Table 20. Typology of resources involved in technology-centered innovations ...... 110

Table 21. Typology of resources involved in structure-centered innovations .......... 110

Table 22. Comprehensive publication list with participation of the author .............. xvii

Abstract XIII

Abstract

In the past two decades, a number of powerful technology giants created consumer-

centric information systems (CCIS), which provide services that are integral to our

everyday life. The well-known providers, amongst them Facebook, Alphabet, Amazon,

or Steam, to name a few, share an important characteristic: they put the individual

consumer and her needs at the center of all undertakings; that is, they promote the

paradigm of consumer centricity. While an emerging body of literature recognizes CCIS

as a novel type of information system (IS), and increasing attention is paid to the nascent

stream of service innovation in the digital age, we know little about how to conceptualize

consumer centricity in IS, and how service innovations in these IS are generated.

This thesis, which consists of four articles, studies service innovation in CCIS. The first

article draws on the marketing and IS literature to operationalize consumer centricity. It

conceptualizes socio-technical system alignment as antecedent of consumer centricity

in IS. The second article advances a CCIS model by conceiving consumer centricity of

an IS as a latent trait that is reflected by three indicators (need orientation, value

cocreation, relationship orientation). It also includes a short case study and traces three

mechanisms to enhance consumer centricity. The third article investigates the video-

gaming platform Steam, and develops recommendations for the analysis and design of

CCIS. The results emphasize the importance of consumer resources in CCIS. The fourth

article, an in-depth case study of Facebook, proposes the resource integration model as

an empirically-grounded, theoretical model to explain how resource integration of

consumers and provider is generative of service innovation and accounts for the

dynamic and emergent nature of service innovation in the digital world. Its application

in the case context uncovers three service innovation mechanisms: data-driven

innovation, technology propulsion, and social debugging. The results suggest that

service innovation in CCIS relies significantly on a provider’s ability to engage,

facilitate, and leverage the resources and resource integration of its consumers.

This thesis contributes to theory by (1) providing a socio-technical model of CCIS, (2)

uncovering mechanisms that enhance consumer centricity, and (3) by explaining how

service innovations are generated in CCIS. It explicitly considers the role of consumers

in generating innovations and, thereby, it contributes to (4) ongoing research on digital

innovation and digital ecosystems. For practicioners, the thesis holds implications on

the analysis and design of CCIS, and how to think about service innovation in the digital

age.

Kurzfassung XV

Kurzfassung

In den letzten zwei Dekaden haben einige Technologiegiganten konsumentenzentrische

Informationssysteme (CCIS) geschaffen, die integraler Bestandteil unseres Alltags sind.

Bekannte Anbieter wie Facebook, Alphabet, Amazon, oder Steam, um Einige zu

nennen, haben eine Gemeinsamkeit: Sie stellen den Konsumenten und seine Bedürfnisse

in den Mittelpunkt aller Unternehmungen, d.h. sie folgen dem Paradigma der

Konsumentenzentrizität. Obwohl die wissenschaftliche Literatur CCIS als neuen Typ

Informationssystem (IS) anerkennt und auch Forschung um Serviceinnovation im

digitalen Zeitalter verstärkt beachtet wird, wissen wir wenig wie Konsumentenzentrizi-

tät in IS zu verstehen ist und wie Serviceinnovationen in diesen Systemen entstehen.

Diese Dissertation untersucht Serviceinnovation in CCIS. Artikel I operationalisiert

Konsumentenzentrizität auf Basis der Marketing- und IS Literatur. Die Ausrichtung

sozio-technischer Systemkomponenten wird als Voraussetzung für Konsu-

mentenzentrizität in IS konzeptualisiert. Artikel II entwickelt ein CCIS Modell, das

Konsumentenzentrizität als Eigenschaft eines IS versteht und durch drei Indikatoren

erfasst. In einer kurzen Fallstudie der Videospiel-Plattform Steam werden drei

Mechanismen identifiziert, die Konsumentenzentrizität erhöhen. Artikel III untersucht

Steam detaillierter und erarbeitet Empfehlungen für die Analyse und Gestaltung von

CCIS. Die Erkenntnisse heben die Bedeutung von Konsumentenressourcen in CCIS

hervor. Artikel IV schlägt das Ressourcenintegrationsmodell als ein empirisch

begründetes, theoretisches Modell vor, welches erklärt wie Serviceinnovationen durch

Ressourcenintegration von Konsument und Anbieter generiert werden. Hierdurch wird

das dynamische und emergente Wesen von Serviceinnovationen im digitalen Zeitalter

erfasst. Die empirische Anwendung des Modells identifiziert drei Serviceinnovations-

Mechanismen (Datengetriebene Innovation, Technologievortrieb und Soziale

Fehlerbehebung). Die Ergebnisse zeigen, dass Serviceinnovation in CCIS signifikant

von der Fähigkeit eines Anbieters abhängt, Konsumenten und deren Ressourcen

einzubringen, zu befähigen und zu nutzen.

Die Dissertation trägt zur Theorie bei, indem sie (1) ein sozio-technisches CCIS Modell

entwickelt, (2) Mechanismen identifiziert um Konsumentenzentrizität zu erhöhen und

(3) erklärt, wie Serviceinnovationen in CCIS generiert werden. Die Arbeit expliziert die

Rolle des Konsumenten für Serviceinnovationen und trägt dadurch (4) zur Forschung

an digitaler Innovation und digitalen Ökosystemen bei. Für Praktiker enthält die Arbeit

Hinweise für die Analyse und Gestaltung von CCIS und liefert Denkanstösse zur

Serviceinnovation im digitalen Zeitalter.

Part A: Introduction 1

Part A

1 Introduction

Research motivation

In the past two decades, a number of powerful technology giants created consumer-

centric information systems (CCIS) which provide services that became integral to our

life. For example, Facebook has evolved from an organized collection of personal

profile pages of a few hundred students to the world’s most popular social networking

service. As of January 2018 over 2 billion active consumers and ranges amongst the

most valuable firms in the world. There are many more examples of information systems

that attract vast numbers of consumers and that have tremendously changed our

everyday life, e.g., how we socialize (Facebook, Snapchat, Instagram), communicate

with others (WhatsApp, WeChat, Facebook Messenger), search for news and

information (Google, Wikipedia), consume music and video content (Spotify,

YouTube), purchase video games (Steam), or other goods (Alibaba, Amazon).

The firms behind these prime examples share an important characteristic: they put the

individual consumer and her needs at the center of all undertakings, that is they promote

the paradigm of consumer centricity (Shah et al. 2006).1 Following this organizational

approach, they develop consumer-centric information systems by aligning the systems’

main components to satisfy consumer needs, e.g., through on-demand configuration and

personalization of provided services (Liang and Tanniru 2006).

The emergence of CCIS, as a new type of information system (IS), poses a novel socio-

technical phenomenon that challenges the existing body of knowledge in many new

ways, of which three are outlined here.

First, consumers, as focal actors in CCIS, differ from organizational IS users. They adopt

systems voluntary and their system use is guided by individual will and emotion

(Tuunanen et al. 2008). Consumers choose their activities, roles and relationships freely

and are not only driven by economic considerations (Wagner and Majchrzak 2006).

While the idea of consumer centricity in IS is commonplace, its conceptualization is

1 The term consumer centricity is employed throughout this thesis to narrow the discussion towards a certain type of customer, namely an individual human being in her private surroundings.

2 Part A: Introduction

often vague (Alter 2008, p. 461). Extant IS literature describes characteristics of IS

associated with consumer centricity (Huang and Rust 2013; Liang and Tanniru 2006;

Pan and Pan 2006; Reich and Benbasat 1990; Tuunanen et al. 2008; Tuunanen et al.

2010), but there is a paucity of research about the antecedents of consumer centricity,

which limits our ability to understand these information systems.

Second, CCIS challenge our thinking about service innovation and how value is

generated in consumers’ personal social contexts. The digitized consumer, his data trace

and technology resources are the starting point, and not the end, for novel configurations

of the value chain (Brenner et al. 2014, p. 56). This becomes even more important when

considering that consumers nowadays operate powerful personal information and

communication technologies which are critical resources in CCIS (Baskerville 2011;

Yoo 2010). Thus, research on how providers leverage those consumer resources is

valuable to advance our understanding of service innovation in CCIS.

Third, CCIS providers need to constantly seek to innovate their services as the default

mode of operation, not as the exception (Mesaglio and Hotle 2012). Consumers not only

expect providers to adapt services to their ever-changing needs, but when interacting

digitally, they often create new data, which has recently been labelled as the most

valuable resource in the world (The Economist 2017). The constant generation of data

creates new potentials for innovation (Yoo et al. 2012). This demands new contributions

that theorize service innovation as a dynamic process in which actors constantly

contribute and integrate their resources to create value and to generate novel resources,

as opposed to conceiving service innovation as a one-time process with clear beginning

and end (Barrett et al. 2015; Lusch and Nambisan 2015; Nambisan et al. 2017).

Research objective

Given these challenges, the motivation of this thesis is then to explore service innovation

in CCIS as a novel socio-technical phenomenon. To frame this work the overall research

goal is formulated as follows:

This research aims to conceptualize consumer centricity in information systems and to

explain how service innovations in these systems are generated on the basis of

consumers’ and provider’s resource integration.

The thesis is particularly focused on enhancing our understanding of CCIS and how

service innovations are generated through resource integration. Thus, it contributes to

the knowledge base on CCIS and service innovation in the digitial age.

Part A: Thesis structure and research results 3

2 Thesis structure and research results

The research objective is addressed through four research questions of which each is

addressed in a dedicated article (cf. Figure 1). To accommodate for the research process

and the novelty of the phenomenon, the thesis comprises conceptual and empirical work.

Figure 1. Overview of thesis structure and constitutive articles

RQ1: How can consumer centricity be operationalized as characteristics of information systems and which antecedents lead to consumer centricity of IS?

TitleConsumer-Centric Information Systems: A Literature Review and Avenues for Further Research (ICIS 2015).

Method Conceptual literature review of #21 marketing publications on consumer centricity.

ResultOperationalization of three generic objectives of consumer centricity in IS;IS model of socio-technical component alignment; six hypotheses as antecedents.

Article I

RQ2: What mechanisms align the socio-technical components of an IS towards consumer centricity?

TitleA Socio-Technical Approach to Study Consumer-Centric Information Systems(ICIS 2016).

Method Case study research.

ResultImproved IS model of socio-technical component alignment. Case study research design, including identification of three cases (Steam, Facebook, YouTube). 3 mechanisms socio-technical component alignment.

Article II

RQ 3: What can companies learn from the video game industry for the design of the digtial customer experience?

TitleWhat Companies Can Learn from the Videogame Industry for the Design of the Digital Customer Experience: An Analysis of the Platform Steam (HMD 2017, in German)

MethodCase study analysis of Steam video-gaming platform. Analysis of six major changes in the development of Steam between 2003 and 2016.

ResultNine recommendations for designing of the digital customer experience in consumer-centric IS. Illustrative application within three settings: automobile industry, TV streaming, and a digital platform for car repairs.

Article III

RQ 4: How do provider and consumers integrate their respective resources in social networking services to generate service innovations?

TitleService Innovation in Social Networking Services: A Resource Integration Perspective on Facebook (paper aiming at top IS journal).

MethodExploratory, interpretative case study of Facebook. In-depth analysis of 51 service innovations generated between 2004 and 2017.

ResultThe resource integration model to explain service innovation in SNS;Three service innovation mechanisms: data-driven innovation, technology propulsion, and social debugging.

Article IV

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4 Part A: Thesis structure and research results

This thesis embraces socio-technical (S-T) system theory (Bostrom and Heinen 1977)

as a reference framework. It provides a comprehensive foundation to describe socio-

technical systems which is simple, extensive, sufficiently well-defined, anchored in

extant theory, and that can be easily extended with other categories to obtain rich

vocabulary (Lyytinen and Newman 2008). As such, the S-T framework allows to

capture CCIS from a holistic, inclusive and nuanced perspective that appears useful for

the structuring and analysis of selected IS and the innovation of services they enable.

The first part of the research project conceptualizes consumer centricity in information

systems (RQ 1), and develops the theoretical foundation upon which further research

can be conducted (RQ 2). Following the review and synthesis of the knowledge base,

the empirical research focuses on exploring how the S-T framework could inform the

analysis and design of CCIS (RQ 3), and how service innovations are generated based

on the integration of social and technical resources of consumer and provider (RQ 4).

The following research summary is structured along the four research questions.

RQ 1: How can consumer centricity be operationalized as characteristics of information

systems and which antecedents lead to consumer centricity of information systems?

The first research question aims to provide a conceptual foundation for this thesis. To

this end, Article I presents a literature review that examines how the concept of

consumer centricity in marketing can be built upon to operationalize consumer centricity

in information systems. Turning to the marketing discipline makes sense, because

scholars of the domain have debated the objectives and transformational activities

related to consumer centricity for decades (Kumar 2015; Levitt 1960). The review

focuses on literature that defines consumer centricity with the goal to understand the

“phenomenon as a whole, its meaning and its relationships” (Rowe 2014, p. 243). The

data collection and analysis follows a systematic process in which 21 publications are

identified, selected and analyzed (Webster and Watson 2002). Following an iterative

process of open, axial and selective coding (Glaser and Strauss 1967; Strauss and Corbin

1990), three generic objectives of consumer centricity are identified and labelled as need

orientation, value cocreation, and relationship orientation.

In the next step, a model of a consumer-centric IS is developed based on the socio-

technical framework. It suggests that the four constitutive system components – task,

technology, structure and actor – can be aligned towards a specific goal (Bostrom and

Heinen 1977; Hester 2014; Leavitt 1964a; Lyytinen and Newman 2008; Orlikowski

2000), which is consumer centricity in this research. The objectives of customer


centricity from marketing are then generalized as characteristics towards which the

components of a consumer-centric IS are aligned and six hypotheses are derived on

alignment capabilities as antecedents of consumer centricity.

Within the thesis, Article I provides an initial operationalization of consumer centricity

in IS and it offers a theoretical foundation of socio-technical component alignment for

further studying consumer-centric information systems.

RQ 2: What mechanisms align the socio-technical components of an IS towards

consumer centricity?

The second research question seeks to identify mechanisms that are designed into IS

with the purpose to increase consumer centricity. To this end, Article II elaborates a

socio-technical approach to study consumer-centric IS and advances the theoretical

model proposed in Article I. Figure 2 indicates four social and technical system

components, their alignment relationships, and consumer centricity as the outcome of

component alignment. The model focuses on the consumer as single most relevant actor

and conceives consumer centricity as a latent trait of an IS. Consumer centricity is then

evaluated against three reflective indicators, i.e., the degree of need orientation, value

cocreation and relationship orientation.

Figure 2. Research model of a consumer-centric IS

Article II proposes an exploratory, multiple case study design to identify mechanisms

and to test hypotheses on the alignment of task-consumer, technology-consumer, and

structure-consumer relationship. Based on theory-informed criteria, the paper identifies

three extreme cases which are useful for identifying causal relationships and theory

building (Yin 2013). The cases vary in their domain, i.e., video gaming (Steam), social

networking (Facebook), and video sharing (YouTube), they are similar in their success,


and they are information rich, which makes an in-depth analysis of the case contexts and

mechanisms within these IS possible.

The application of the research model and research design is then illustrated through an

analysis of Steam, the leading platform for digital video game distribution. The case

vignette analyzes the implementation of Steam Greenlight, Steam’s Hardware and

Software Survey, and Steam’s Anti-Cheat Client. The analysis yields evidence for three

mechanisms that increase consumer centricity, namely consumer-driven collective

selection of video games, increase of transparency about consumer technology, and the

enforcement of norms.

In this dissertation, Article II paves the way for further research. First, it puts forth the

concept of a consumer-centric IS as a socio-technical system. Second, it provides an

empirical research design that offers a case selection strategy and that aims to study

mechanisms that align a system towards consumer centricity. Finally, it offers a case

vignette that laid the ground for the subsequent in-depth case studies of Steam (Article

III) and Facebook (Article IV).

RQ 3: What can companies learn from the video game industry for the design of the

digital customer experience?

The third research question aims to explore and demonstrate how the socio-technical

framework can inform the analysis and design of CCIS, with a particular focus on the

digital customer experience. To this end, Article III, employs the socio-technical

framework to investigate the leading video gaming platform Steam, and to generalize

recommendations for the design of the digital customer experience.

The research in Article III employs the case study method to scrutinize six major

changes in the development of Steam between 2003 and 2016. The case analysis focuses

on how Valve, the firm behind Steam, defines and manages the task, technology and

structure components within the IS. Consistent with Articles 1 and 2, the rationale is that

system components constitute the interfacing resources by which consumers interact

digitally and experience the CCIS. In consequence, the analysis distinguishes three

layers and focuses on how Valve defines services and service portfolio (task

component), manages consumer technology (technology component), and how it

secures consumers’ trust and loyalty by embedding values and norms into the IS

(structure component).


The analysis of the Steam platform resulted in nine recommendations by which Valve

has shaped the digital customer experience within the consumer-centric IS. The

application of these recommendations is then discussed for three settings (automobile

industry, TV streaming, and a digital platform for car repairs). This illustration

demonstrates how a prime example in the video game industry can inform the design of

CCIS in other, perhaps more traditional industries.

As part of this thesis, Article III builds on the socio-technical foundation provided in

Articles I and II and establishes an empirical understanding of how digital leaders design

consumer-centric IS. The results emphasize the importance of recognizing and

integrating consumer resources, e.g., knowledge, data, and technology, as important

components of consumer-centric IS.

RQ 4: How do provider and consumers integrate their respective resources in social

networking services to generate service innovations?

The fourth research question aims to explain service innovation in social networking

services (SNS), as a particularly relevant type of CCIS. The objective of this research is

to develop an empirically based understanding of resource integration, and to explore

how the resource integration of consumers and provider in SNS is linked to the

generation of service innovations. To this end, Article IV proposes the resource

integration model as a theoretical framework with which to make sense of the activities

and reciprocal dynamics of resource integration that are emphasized in service-dominant

logic (Vargo and Lusch 2004, 2008). The model depicts two resource integrating actors,

i.e., provider and consumer, and suggests that their resource integration is generative of

service innovations (Lusch and Nambisan 2015, p. 168).

The research in Article IV adopts socio-technical (S-T) system theory (Bostrom and

Heinen 1977) as a reference framework to structure the analysis of service innovations,

as well as the involved social and technical resources of consumers and provider.

Specifically, the task, technology and structure component are employed as lenses that

flesh out three “centers of gravity” of service innovations which are labelled accordingly

as task-centered, technology-centered, and structure-centered service innovations.

The resource integration model is then applied to an explorative, interpretive case study

of Facebook with a detailed analysis of 51 service innovations generated between 2004

and 2017. The case analysis, which followed an iterative process of sensemaking, data

gathering, and gradual generalization (Klein and Myers 1999), uncovered three service

innovation mechanisms: data-driven innovation, technology propulsion, and social


debugging. Each mechanism provides insights about the social and technical resources

of consumer and provider, and how their resource integration dynamics have been

generative of service innovations in the case context. The three empirically identified

mechanisms demonstrate that service innovation in SNS relies significantly on the

provider’s ability to successfully engage, facilitate, and leverage the resources and

resource integration of consumers.

The results presented in Article IV are the outcome focused research and represent the

central result of the dissertation project. The preceding research Articles I-III were

important prerequisites for conducting this research: Articles I and II were essential for

understanding and identifying socio-technical theory and service-dominant logic as

conceptual foundation, and for identifying and justifying Facebook as a CCIS on which

rich and interesting data exists. Conducting the research in Article III helped to gain

experience in case study method and, eventually, informed the systematic collection and

analysis of data, to trace Facebook’s service innovations, and to identify and code the

involved resources and their integration. In that regard, Article IV empirically explores

service innovation in consumer-centric information systems through an in-depth case

study.

Part A: Discussion and future research 9

3 Discussion and future research

Theoretical contributions

This thesis contributes to our knowledge on service innovation in consumer-centric IS.

It establishes a socio-technical (S-T) view of consumer-centric IS, and it explains how

resource integration of consumers and provider is generative of service innovations. The

thesis makes four important contributions.

First, the CCIS model contributes an intellectual structure which puts the consumer into

the foreground of our thinking (Brenner et al. 2014) and, thereby, might be useful to

overcome the prevailing “centricity of the business-enterprise, the organization, or the

society […]” in current IS research (Baskerville 2011, p. 253). This shift is encouraged

by employing the S-T framework and by operationalizing need orientation, value

cocreation, and relationship orientation as generic objectives of consumer centricity in

IS (cf. Articles I and II). The notion of S-T component alignment also provides a novel

lens to identify mechanisms that are built into IS to increase consumer centricity. To this

end, the CCIS model can serve further empirical studies. It might also serve as a

framework to integrate related knowledge in the nascent stream of research on CCIS (cf.

Rowe 2014, p. 244).

Second, the resource integration model provides a structure with which to make sense

of resource integration as the underlying process of value cocreation and service

innovation (Lusch and Nambisan 2015, p. 168), and it accounts for the dynamic and

emergent nature of service innovation in the digital world (Yoo et al. 2012). By

embracing interfacing resources that mediate digital interactions, e.g., features,

technology, or data, the model captures how novel resources are generated and how they

manifest as innovations that are beneficial to some actor (Lusch and Nambisan 2015, p.

161). The model enhances transparency on service innovation in the digital world, which

is increasingly difficult to bound in terms of time, space, beginning, end and agency

(Nambisan et al. 2017). To summarize, the resource integration model enhances our

understanding and theorizing of value cocreation and service innovation, which

increasingly develops into a narrative of “resource-integrating, reciprocal-service

providing actors […]” (Vargo and Lusch 2016, p. 7).

Third, the research contributes three service innovation mechanisms, namely data-

driven innovation, technology propulsion, and social debugging. The mechanisms result

from blending the S-T framework into the resource integration model, which enabled a

10 Part A: Discussion and future research

nuanced understanding of innovation by differentiating task-centered, technology-

centered, and structure-centered service innovations. The mechanisms suggest that

service innovation in CCIS relies significantly on a provider’s ability to successfully

engage, facilitate, and leverage the resources and resource integration activities of its

consumers. The mechanisms might not only be useful for identifying and theorizing

about different types of service innovation, but also to sensitize research for different

types of social and technical resources.

Finally, this thesis contributes to the ongoing research on digital innovation (Yoo et al.

2010; Yoo et al. 2012) and digital ecosystems (Henfridsson and Bygstad 2013; Reuver

et al. 2017; Tilson et al. 2010; Tiwana et al. 2010) by examining and specifying

resources that are essential for innovating digital services for and with consumers. More

specifically, this thesis complements research that studied the resources and innovations

generated and integrated by providers and third-party developers (Eaton et al. 2015;

Ghazawneh and Henfridsson 2013; Gnyawali et al. 2010), by explicitly accounting for

the consumer, who is often not only a beneficiary, but also a contributor of essential

resources for service innovation.

Practical implications

This thesis also holds implications relevant for managers and practitioners.

First, the CCIS model provokes a consumer-centric view and, as such, it can be useful

to challenge a business-centric, inside-out perspective of firms who design consumer-

facing systems. The proposed model (Article II) and the analysis of the Steam platform

(Article III) demonstrate how CCIS can be analyzed based on their constitutive S-T

components. The results show how different mechanisms enhance consumer centricity

in real-world systems, e.g., by involving consumers in the collective selection and

definition of services and service portfolio, by monitoring and responding to deployed

consumer technology, or by implementing mechanisms that enact and enforce accepted

social practices. The suggestion to managers is then to think strategically about the

social and technical implications when designing IS for consumers.

Second, the Steam case analysis (Article III) and the resource integration model (Article

IV) stimulate managers to think in nuanced ways about service innovation in CCIS.

Managers should consider the resources that initially consumers provide and also those

that they continuously generate as sources of service innovation. The dynamic and

emergent perspective offered here underlines the importance to recognize service

innovation in CCIS as an incremental, continuous effort to improve, adapt and invent

Part A: Discussion and future research 11

new services to satisfy consumers’ ever-changing needs. This thinking is probably best

illustrated in the three service innovation mechanisms: data-driven innovation suggests

that managers conceive consumers' service interactions as data-generating activity upon

which service innovations can be generated. Technology propulsion suggests that

managers focus not only on the firm’s digital infrastructure, but also appraise and

facilitate consumers' abilities to integrate their technology as foundation of service

innovation. Social debugging suggests that managers reflect on the normative and

behavioral expectations of consumers and implement resources to innovate the social

structure in CCIS. The social implications of service innovations are often subtle and

difficult to assess and require a long-term strategy to align with consumers’ value and

norm expectations.

Finally, this thesis (Articles I-IV) emphasizes that leading CCIS generate data and

insights from every consumer interaction. Practitioners who are involved in the

innovation and provisioning of services in CCIS should design interfacing resources,

e.g. features, websites, or applications, in ways that drive the generatino of multifaceted

data which, e.g., can be processed, measured, and recombined for service innovation.

Limitations and future research

This thesis presents CCIS as a relevant field of IS research. The included publications

contribute knowledge and insights to conceptualize consumer-centric IS, and to explain

how service innovations are generated in these systems. Given the novelty of the

phenomenon and the early stage of extant research, this thesis has limitations that should

be addressed in future research.

First, the thesis focused on Facebook and Steam as two highly relevant consumer-centric

IS. While both cases represent rich and dynamic settings to study service innovation,

future research should consider other systems. This would add further empirical

grounding to the CCIS model, and it could strengthen the generalizability of the resource

integration model, as well as the service innovation mechanisms into other contexts. It

is reasonable to expect similar mechanisms and in other contexts. Potentially valuable

cases could stem from personalizing music and video services (e.g., Spotify, YouTube,

Netflix), promoting consumer hardware to innovate new services (e.g., Amazon’s

Alexa, Google Echo, or Virtual Reality devices), or seeking to understand how novel

services can regulate disputes and tensions between actors (e.g., Twitter, Snapchat).

Second, this thesis focuses exclusively on consumers and provider as actors in CCIS.

Future research could apply, or extend, the proposed resource integration model to study

12 Part A: Discussion and future research

the role of other actors, e.g., third-party developers, for generating service innovations

in CCIS. Such research could provide valuable insights on how the resources and

resource integration activities of these actors are generative of service innovation in

CCIS. At the same time, it could complement extant research on boundary resources

(Eaton et al. 2015; Ghazawneh and Henfridsson 2013) as it would focus on the active

resources (e.g., knowledge, skills, or capabilities) that third parties integrate in CCIS (cf.

Sarker et al. (2012) for an exemplary case study in a B2B setting).

Finally, the mechanisms identified in this thesis are at a relatively abstract level. This

suggests that nested causal paths for increasing consumer centricity and for generating

service innovations through resource integration have not been identified. Thus, the

thesis cannot claim exhaustiveness regarding the identification of mechanisms that

increase consumer centricity of an IS and that are generative of service innovation.

Future research should aim at identifying further mechanisms, e.g., by carefully

examining other CCIS, as indicated above, or by lowering the level of abstraction at

which mechanisms are studied.

Part A: Reference overview of articles in this thesis 13

4 Reference overview of articles in this thesis

This section provides the full bibliographical information of the articles included in this

thesis. They jointly address the formulated research objective and form the core part of

the thesis. Articles I to IV are presented in full in Part B.

4.1 Consumer-Centric Information Systems: A Literature Review

and Avenues for Further Research

Table 1. Bibliographic information for Article I

Title Consumer-Centric Information Systems: A Literature Review and Avenues for Further Research

Authors Benjamin Spottke, Jochen Wulf, Walter Brenner

Outlet ICIS 2015 Proceedings

Year 2015

Status Published

Abstract. While consumer centricity has been extensively discussed as a concept of

organizational transformation in the marketing domain, there is little research on its

operationalization as a characteristic of information systems and associated antecedents.

We review the marketing literature to understand generic organizational objectives of

consumer centricity which are then generalized as characteristics of consumer-centric

information systems. In a second step, we draw on socio-technical theory to

conceptualize antecedents of consumer centricity as capabilities to align social and

technical system components.

Our research contributes to the body of knowledge by theoretically deriving an

operationalization and antecedents of consumer centricity in IS research. This paper lays

the foundation for a structured review of IS literature to theorize on component

alignment capabilities as antecedents of consumer centricity. It further is the basis for

case study research to construct a nomological network for consumer-centric

information systems.

Keywords: Human-computer interaction, Information systems, IS models, IS research,

IS research agenda, IS theory, Socio-technical approach

14 Part A: Reference overview of articles in this thesis

4.2 A Socio-Technical Approach to Study Consumer-Centric

Information Systems

Table 2. Bibliographic information for Article II

Title A Socio-Technical Approach to Study Consumer-Centric Information Systems

Authors Benjamin Spottke, Alexander Eck, Jochen Wulf


Year 2016

Status Published

Abstract. Given the unprecedented role of digital service platforms in private life, this

research sets out to identify the mechanisms that are designed into information systems

with the purpose to increase consumer centricity. We evaluate the consumer centricity

of an information system against three reflective indicators, that is the degree of need

orientation, value cocreation and relationship orientation and conceptualize consumer

centricity as the ability to align social and technical information system components.

We employ a positivist, explanatory case study approach to test three hypotheses on

system component alignment in cases from three domains (gaming, social networking,

and video sharing). We found preliminary evidence for three alignment mechanisms that

increase consumer centricity.

With this research, we plan to contribute to the literature on consumer-centric

information systems by elaborating and empirically grounding a socio-technical

approach to study mechanisms and their joint application to increase consumer

centricity in information systems.

Keywords: Human behavior in IS, Human-computer interaction, Information systems,

IS models, IS research, Socio-technical approach, Case Study Research

Part A: Reference overview of articles in this thesis 15

4.3 What Companies Can Learn from the Videogame Industry for

the Design of the Digital Customer Experience: An Analysis of the

Platform Steam

Table 3. Bibliographic information for Article III

Title What Companies Can Learn from the Videogame Industry for the Design of the Digital Customer Experience: An Analysis of the Platform Steam

Authors Benjamin Spottke

Outlet HMD Praxis der Wirtschaftsinformatik (317), Springer.

Year 2017

Status Published

Abstract. In the age of digitization the successful management of customer interactions

in the sense of a holistic digital customer experience is becoming increasingly valuable.

Technology leaders like Amazon, Apple, Facebook and Google, but also Valve as the

provider of the leading video gaming platform Steam are well known for their ability to

organize and design digital interactions between users, third parties and other actors.

This article employs the case study method to investigate the Steam platform. Based on

the analysis of Steam, recommendations for the design of the digital customer

experience are generalized. These recommendations can be applied by companies in

other industries. The study focuses on (1) the definition of services and service portfolio,

(2) the management of consumer technology, and (3) the development of trust and

loyalty by embedding values and norms within a digital platform. The elaborated

recommendations are then illustratively discussed within three settings, i.e. automobile

industry, TV streaming and a digital platform for car repairs.

This article aims to inform managers in IT service development and IT service design,

IT strategists and business architects who are responsible for the design of digital

customer experiences enabled by information systems and corresponding digital

platforms. This article contributes to theory by establishing a socio-technical lens on the

design of the digital customer experience.

Keywords: Digital Customer Experience, Digital Platforms, Service Design, Case

Study Research

16 Part A: Reference overview of articles in this thesis

4.4 Service Innovation in Social Networking Services: A Resource

Integration Perspective on Facebook

Table 4. Bibliographic information for Article IV

Title Service Innovation in Social Networking Services: A Resource Integration Perspective on Facebook


Outlet Research aiming at a paper in a top IS journal (e.g., Information Systems Journal)

Year 2018

Status Working paper (IWI-HSG)

Abstract. This paper explores how Facebook, the world’s largest and most successful

social networking service (SNS) provider, and its consumers generated service

innovations through resource integration. While prior research emphasizes the

importance of third-party developers, little is known about how consumers and their

resources are leveraged for generating service innovations in SNS. To this end, this

paper proposes the resource integration model as a theoretical framework that is rooted

in service-dominant logic, and that conceptualizes resource integration as the process

underlying service innovation. We apply the model to an explorative, interpretive case

study of Facebook with a detailed analysis of 51 service innovations generated between

2004 and 2017. Our analysis uncovered three service innovation mechanisms: data-

driven innovation, technology propulsion, and social debugging. Each mechanism

provides insights about the resources and resource integration dynamics of consumer

and provider, and how these have been generative of service innovations. Our findings

suggest that service innovation in SNS relies significantly on the provider’s ability to

successfully engage, facilitate, and leverage the resources and resource integration of

consumers. While the mechanisms can be used to examine service innovations in

specific contexts, the model can be specialized for studying diverse aspects of service

innovation and resource integration, which we exemplified by blending the socio-

technical framework into the case analysis. Our research offers a novel perspective on

service innovation and enhances previous research on SNS, as well as service innovation

in the digital age.

Key words: service innovation, digital innovation, social networking services, service-

dominant logic, Facebook, case study, mechanism

Part B: Consumer-Centric Information Systems: A Literature Review and Avenues for Further Research 17

Part B

I Consumer-Centric Information Systems: A Literature

Review and Avenues for Further Research

Table 5. Bibliographic information for Article I

Title Consumer-Centric Information Systems: A Literature Review and Avenues for Further Research

Authors Benjamin Spottke, Jochen Wulf, Walter Brenner


Year 2015

Status Published

Abstract. While consumer centricity has been extensively discussed as a concept of

organizational transformation in the marketing domain, there is little research on its

operationalization as a characteristic of information systems and associated antecedents.

We review the marketing literature to understand generic organizational objectives of

consumer centricity which are then generalized as characteristics of consumer-centric

information systems. In a second step, we draw on socio-technical theory to

conceptualize antecedents of consumer centricity as capabilities to align social and

technical system components.

Our research contributes to the body of knowledge by theoretically deriving an

operationalization and antecedents of consumer centricity in IS research. This paper lays

the foundation for a structured review of IS literature to theorize on component

alignment capabilities as antecedents of consumer centricity. It further is the basis for

case study research to construct a nomological network for consumer-centric

information systems.

Keywords: Human-computer interaction, Information systems, IS models, IS research,

IS research agenda, IS theory, Socio-technical approach

18 Part B: Consumer-Centric Information Systems: A Literature Review and Avenues for Further Research

I.1 Introduction

The increasing adoption of consumer technology and the proliferation of ubiquitous

systems is transforming the interaction between organizations and consumers. As

consumers are seek personalized experiences (Prahalad and Ramaswamy 2004),

interaction is increasingly considered as the locus of value creation (Vargo and Lusch

2004). Without doubt, consumer interactions are strongly facilitated by information

systems and technology (Jayachandran et al. 2005; Saarijärvi et al. 2013).

Consumer-facing systems pose novel organizational challenges with regard to system

development and provisioning. For example, Gartner (2012) distinguishes information

systems by their degree of consumer engagement (low to high) and associated pace of

change (low to high) and deduce different so-called “pace-layered” application

management strategies. A focus on intra-organizational IS users does not cover

consumers, who design their individual information systems for their various purposes

(Baskerville 2011) and within their specific contexts (Lamb and Kling 2003). IS

researchers and practitioners have developed an extensive body of knowledge on intra-

organizational systems, e.g., regarding development (e.g., waterfall model, scrum) and

IT service management (ITIL). The transferability of such practices to the management

of systems with a high consumer engagement, however, is only limited (Liang and

Tanniru 2006).

The concept of customer centricity has been developed in the marketing literature and

applies to the marketing function itself (Kumar 2015; Sheth et al. 2000) or to

organizations as a whole (Shah et al. 2006). Customer centricity is often understood as

a set of transformational activities (e.g., organizational alignment or cultural change

(Shah et al. 2006)) or as organizational objectives (e.g., customer need orientation

(Lamberti 2013) or intensifying customer relationships (Kumar 2015)).

Within the IS literature customer centricity mostly refers to commercial relationships

between private customers and suppliers (Alter 2008; Pan and Pan 2006). IS research

views consumer-centric information system (CCIS) as organizational IS which “link a

company to its customers.” (Reich and Benbasat 1990). Such a perspective does not

cover the emergence of systems which are owned and operated by consumers for non-

commercial purposes (Baskerville 2011). To include such systems into our analysis of

consumer centricity, we adopt a broader definition and consider consumers as private


users of information systems, which may or may not engage with a commercial

organization through IS.1

Advancements in consumer technologies are considered as an enabler for increased

customer centricity (Kumar 2015). Alter (2008) associates customer centricity with an

ability to „respond to customer needs“ and notes that the “idea of customer-centricity

has become commonplace, but is often vague”. Prior literature on CCIS discusses

characteristics of information systems associated with consumer centricity (Huang and

Rust 2013; Liang and Tanniru 2006; Pan and Pan 2006; Reich and Benbasat 1990;

Tuunanen et al. 2008; Tuunanen et al. 2010). This literature, however, provides little

theory on antecedents of consumer centricity and their relation to IS characteristics.

The IS research literature acknowledges the importance to analyze the individual

consumer and her active role in defining and using an information system around her

needs. Baskerville (2011), for example, speaks of “centricity of the business-enterprise”

and is questioning if IS research has “failed to notice the individuation of IS” which are

“certainly socially constructed”. Alter (2008) also emphasizes the need to evaluate and

adjust elements of work systems to “attain the right degree of customer-centricity” and

calls for further research in this area.

To address this call, we pose the following research questions: 1) How can consumer

centricity be operationalized as characteristics of information systems? 2) Which

antecedents lead to consumer centricity of information systems? The first research

question seeks to understand consumer centricity and its meaning in the context of

information systems. The second research question aims at the derivation of the internal

capabilities a CCIS must possess.

We use the literature review method (Rowe 2014) to deduce consumer centricity

characteristics from the marketing literature. We then base our argumentation on socio-

technical theory (Bostrom and Heinen 1977; Hester 2014; Leavitt 1964b; Lyytinen and

Newman 2008; Orlikowski 2000) to regard capabilities for system component

adjustments as antecedents of consumer centricity.

1 We regularly use the term customer centricity to comply with the original terms used by cited authors. Since we imply the transferability of customer centricity concepts to the concept of consumer centricity, we use the term customer as a synonym for consumer unless stated otherwise.


I.2 Foundational theory

Information systems are socio-technical systems and consist of a technical as well as a

social subsystem (Alter 2008; Bostrom and Heinen 1977). The technical subsystem

includes a technology component, i.e. all hardware and software used for information

processing, and a tasks component, which represents the goals of a system as well as the

way information processing is carried out (Hester 2014). The social subsystem

encompasses a structure component and the actors. Structure describes the values and

norms as well as general patterns of behavior, which govern the application of

information systems (Hester 2014). Actors include all participants within the

information system which “carry out or influence the work” (Hester 2014). The

individual components are closely interrelated as, for example, task design has an impact

on the working relationships and interpersonal behavior of actors (Bostrom and Heinen

1977). Figure 3 summarizes the components and interrelationships of socio-technical

systems.

Figure 3. Components and interrelationships of socio-technical systems

Structuration theory emphasizes the duality of structure in social systems: “Structure is

both medium and outcome of reproduction of practices. Structure enters simultaneously

into the constitution of the agent and social practices, and 'exists' in the generating

moments of this constitution.” (Giddens 1979) Orlikowski (2000) applies this thought

to the interactions of social and technical subsystems. The interactions between social

entities and technology are inherently recursive, as “users shape the technology structure

that shapes their use” (Orlikowski 2000). The neglecting of these recursive

interrelationships and the focus on the technical subsystem, in system development, is a

major source of failures in information system design (Bostrom and Heinen 1977). As

a consequence, the knowledge of how to mutually align the components of socio-

technical systems is an important precondition for information systems success.


Lyytinen and Newman (2008) further develop the notion of component alignment in

socio-technical systems to analyze change in organizational information systems.

Misalignment between socio-technical components introduce gaps into a system which

are defined as situations that will deteriorate or threaten the system’s performance

(Lyytinen and Newman 2008). Components of the socio-technical system become

incompatible through so called critical incidents, such as changing user behavior and

requirements, which CCIS are continuously exposed to (Moore 2011). A system’s state

of “alignment” or “equilibrium” is predominantly characterized through the absence of

gaps and misalignments. However, components of the socio-technical system must be

aligned towards a goal or purpose in order to valuate the system’s “performance”.

Prior research on CCIS mainly focusses on describing system characteristics.

Exemplary characteristics include cocreation enablement (Huang and Rust 2013),

“focusing on customers” (Pan and Pan 2006), “link a company to its customers” (Reich

and Benbasat 1990), and “provide consumers with services” (Tuunanen et al. 2008).

Tuunanen et al. (2010) identify three consumer value drivers: consumer participation,

service process experience, and goals and outcomes. Consumer participation refers to

the integration of consumers to enable value cocreation. Service process experience is

associated with providing a high degree of customer engagement. A focus on customer

goals and outcomes highlight the importance to regard different types of consumer

utility. The notion of component alignment capability as an antecedent for consumer

centricity has been scarcely addressed by literature on CCIS. As an exception, Liang

and Tanniru (2006) define a customer-centric IS as “one that is able to configure four

major components - customer, process, technology, and product/service - to satisfy a

customer need.” Configuration, according to Liang and Tanniru (2006), includes the

capturing of customer needs, an on-demand configuration of service processes, and the

customization of services. However, it remains unanswered how these configuration

capabilities contribute to customer centricity.

It is the goal of this article to theoretically derive hypotheses on antecedents of CCIS.

We draw on the model of Lyytinen and Newman (2008) and combine several ideas: (1)

Applying the idea of socio-technical system component (mis)alignment towards a goal,

which is consumer centricity in our case. (2) Transferring the idea of alignment to the

context of CCIS. (3) Utilizing the established vocabulary and descriptive elements

(components, properties and gaps) of Lyytinen and Newman.


I.3 Research methodology

The present paper investigates how the notion of customer centricity, i.e. a concept for

organizational transformation in marketing research, can be built upon to operationalize

consumer centricity in IS research. In terms of Rowe’s (2014) typology for literature

reviews we strive to generate a deeper understanding of the concept of customer

centricity by deducing its core objectives. This review therefore focuses on articles that

define customer centricity in marketing research with the goal to understand the

“phenomenon as a whole, its meaning and its relationships” (Rowe 2014). The guiding

question is: Which organizational objectives are associated with the concept of customer

centricity within the marketing literature? The identified organizational objectives are

later generalized as characteristics of CCIS, on the basis of which antecedents of

consumer centricity are proposed.

Rowe (2014) suggests to define breadth and systematicity for literature reviews that seek

general understanding as well as the identification of gaps and future research directions.

With regard to breadth, we draw a “purposive sample” that ensures “good coverage of

topic” (Rowe 2014) but do not aim for an exhaustive review of the marketing discipline

(Vom Brocke et al. 2009). We initially searched in high ranked marketing journals that

conceptualize and explain the fundamental objectives and organizational activities of

customer centricity, as proposed by (Webster and Watson 2002). In a systematic

process, marketing journals have been searched full text for "customer centricity",

"consumer centricity", "customer orientation" and "consumer orientation" which

resulted in four relevant articles. Publications which either only enumerate or mention

consumer/customer centricity as a term amongst others, often without context or relation

to the publication itself, have been excluded from further review. This applies also to

articles that did neither conceptualize, nor define the term consumer/customer centricity.

Furthermore forward and backward searches have been conducted on the articles as

indicated in Table 6. Articles identified in this stage did not have to be published in high

ranked marketing journals but needed to meet inclusion and exclusion criteria. This

process has led to a total of 21 relevant articles which are included in the review.

Conceptual components of customer centricity have been extracted from the sample

literature through open coding (Glaser and Strauss 1967; Strauss and Corbin 1990). This

led to a first set of codes such as ‘leadership commitment’, ‘organizational re-alignment’

or ‘consumer need’. An aggregation of these codes resulted in five superordinate

categories (axial coding). Three of them were considered as organizational objectives

(consumer need orientation, value cocreation and relationship orientation) and two as


transformational activities which enable customer centricity within an organization

(usage of consumer knowledge and the alignment of the organization). In a third step,

we used these five categories to code the selected literature in a second iteration

(selective coding). The codes were independently allocated by a second researcher with

an inter-coder reliability of kappa=.84, which according to Viera and Garrett (2005)

corresponds to an almost perfect agreement.

Table 6. Results of the literature search

Outlet Hits Relevant References

J. of Marketing 7 1 (Kumar 2015)

J. of Consumer Research 1 0 n/a

J.of Marketing Research 1 0 n/a

J. of the Academy of Marketing Science

8 3 (Etgar 2008; Gummesson 2008b; Payne et al. 2008)

J. of Service Research 2 1 (Shah et al. 2006)

J. of Product Innovation Management

7 0 n/a

Marketing Science, J. of Applied Psychology, International J. of Research in Marketing, J. of Retailing

0 0 n/a

1st search iteration total 26 5 All above

Forward search on the identified articles in Google Scholar and Web of Science

n/a 5 (Kumar et al. 2008; Lamberti 2013; Lee et al. 2014; Tax et al. 2013; Verhoef and Lemon 2013)

Backward search on all identified articles

n/a 11 (Boulding et al. 2005; Day 2003, Gummesson 2008a, 2008b; Jayachandran et al. 2005; Payne et al. 2008; Peppers et al. 1999; Prahalad and Ramaswamy 2004; Sheth et al. 2000; Vargo and Lusch 2004; Womack and Jones 2005)

Total sample n/a 21 All above

The identified organizational objectives can be considered as generic characteristics of

customer centricity, regardless of whether they describe an organization or an

information system. Transformational activities, in contrast, directly refer to

organizational design and cannot be transferred to the information systems context.

I.4 Organizational objectives of customer centricity

The identified marketing literature conceptualizes customer centricity as activities of

organizational change and as organizational objectives related to its customer


relationships. Exemplary organizational change activities are introducing leadership

commitment and a culture of sharing information (Shah et al. 2006), supply chain

integration (Lamberti 2013) and business unit alignment (Lee et al. 2014). These

activities are specific for organizational change and not transferrable to a general IS

context. Lee et al. (2014) exclusively focuses on activities of organizational change,

therefore no codes for organizational objectives could be assigned. A structural analysis

of the organizational objectives mentioned in the analyzed articles resulted in three

overarching objectives (see Table 7). In the following, the main themes are synthesized

and contextualized within general marketing research.

Table 7. Organizational objectives of consumer centricity

Organizational objectives

Bou

ldin

g et

al.

2005

Day

200

3

Gum

mes

son

2008

a

Gum

mes

son

2008

b

Jaya

chan

dran

et a

l. 20

05

John

son

& B

hara

dwaj

,

Kum

ar 2

015

Kum

ar e

t al.

2008

Lam

bert

i 201

3

Lee

et a

l. 20

14

Pay

ne a

nd F

row

200

5

Pay

ne e

t al.

2008

Pep

pers

et a

l. 19

99

Pra

hala

d &

Ram

asw

amy

Saa

rijä

rvi e

t al.

2013

Sha

h et

al.

2006

She

th e

t al.

2000

Tax

et a

l. 20

13

Var

go a

nd L

usch

200

4

Ver

hoef

and

Lem

on 2

013

Wom

ack

and

Jone

s 20

05

TO

TA

L

Customer Need Orientation

X X X X X X X X X X X X 12

Value Cocreation X X X X X X X X X X X X X 13

Relationship Orientation

X X X X X X X X X X X X X X 14

An organizational objective often mentioned is the satisfaction of customer needs. While

the literature on consumer centricity revolves around the core idea of adjusting value

propositions to consumer needs (Shah et al. 2006; Sheth et al. 2000), the concept of

experiential marketing underlines that consumers are human beings who want to fulfill

not only functional needs, but also pursue pleasurable experiences (Brakus et al. 2009;

Hirschman and Holbrook 1982, 1986; Schmitt 1999). Consequently, need fulfillment is

experienced not only in cognitive, rational terms, but within a complex, interrelated

system of thoughts, emotions, activities and value which are highly subjective and

idiosyncratic dimensions (Hirschman and Holbrook 1986). Firms which take on a

customer-centric perspective focus on how products and services address these

multidimensional customer’s needs. A product centric view, in contrast, focusses on

product profitability and market share (Kumar 2015). Several authors emphasize that

needs must be addressed on a small segment or even on an individual level. For example,

this means that product benefits are presented to meet individual needs (Shah et al. 2006;

Sheth et al. 2000), or that products and services are customized to increase the likelihood


of customer loyalty (Johnson and Bharadwaj 2005; Peppers et al. 1999; Prahalad and

Ramaswamy 2004). This paradigm demands firms to understand the need of individual

customers and the ability to activate resources and develop solutions to satisfy those

needs (Lamberti 2013), while allowing the customers to define the what, when and

where value is provided (Gummesson 2008a; Womack and Jones 2005).

The second objective of customer centricity is the notion of value cocreation (Boulding

et al. 2005; Gummesson 2008a, 2008b; Shah et al. 2006). Value cocreation is the

foundation of the service dominant logic (Vargo and Lusch 2004, 2008), a concept

which has received significant attention in marketing and service science over the last

decade. The core assumption of value cocreation is that different entities (e.g., firms,

consumers, societies) jointly integrate their operant resources (e.g., knowledge, skills

and technology) within a collaborative process (e.g., within a service offering) to

generate value (Grönroos 2008; Vargo and Lusch 2004, 2008). Value cocreation may

equally take place within service/product production (co-production), and during service

usage, the phase in which consumers perceive and ultimatively determine the value in-

use within their specific context (Etgar 2008; Vargo and Lusch 2008). In this sense value

determination is experiential, i.e. not entirely “rationalistic” (Schmitt 1999; Vargo and

Lusch 2008) and includes humanistic objectives like pleasure, joy or esthetics (Grönroos

2008; Holbrook and Hirschman 1982).

The identified literature on consumer centricity builds on this fundamental idea and

emphasizes the involvement of customers in value generation and points to the practices

of interaction and exchange within customer supplier encounters (Payne et al. 2008;

Payne and Frow 2005; Tax et al. 2013). From a marketing function perspective this

entails an involvement of customers in marketing and innovation processes, e.g., new

product development or marketing decision making (Lamberti 2013; Sheth et al. 2000).

More generally, cocreation is characterized through a collaborative dialogue that creates

personalized experiences in which the customer is allowed to co-construct the

experience according to his context (Prahalad and Ramaswamy 2004). Co-creation of

value does not necessarily happen between a customer and a firm, but might occur

within a service delivery network, i.e., multiple service providers co-create value with a

customer along his journey (Tax et al. 2013). Through the recognition and fulfilment of

customer needs, value is simultaneously created for the customer and the provider

(Boulding et al. 2005; Kumar et al. 2008; Vargo and Lusch 2004; Verhoef and Lemon

2013). If a product or service is appreciated by the customer, it is (usually) reflected in

his willingness to pay (Boulding et al. 2005; Prahalad and Ramaswamy 2004).


The third organizational objective of customer centricity is the emphasis on relationship

orientation. Relationship orientation is addressed in relationship marketing theory

which aims at establishing, developing and maintaining long-term relationships between

customers and firms (Berry 1995; Morgan and Hunt 1994). Trust is considered as

prerequisite and foundation of relationships and it is built upon shared values, associated

behavioral norms, through social bonds between partners as well as successful past

interactions (Bendapudi and Berry 1997; Berry 1995; Day 2000; Morgan and Hunt

1994; Sheth and Parvatlyar 1995). Developed relationships significantly increase

consumers’ willingness for cooperation (Bendapudi and Berry 1997; Morgan and Hunt

1994), their loyalty and retention (Hennig-Thurau et al. 2002; Verhoef 2003; Wulf et al.

2001) and the chance of ‘word-of-mouth’ referrals (Hennig-Thurau et al. 2002).

Consumers on the other hand may enjoy more convenience and reduced risk, as well as

social benefits (e.g., feeling of familiarity) or special treatments (e.g., faster service,

discounts) (Hennig-Thurau et al. 2002).

With regard to consumer centricity relationship orientation manifests in the processes

and practices of interaction and exchange within the customer supplier relationship

which enable to identify and create further opportunities for co-creating value (Payne et

al. 2008; Payne and Frow 2005) as well as to further developing and sustaining the

relationship itself (Boulding et al. 2005; Day 2003). Lamberti (2013) remarks that

relationships need to be “mutually satisfactory” for both parties. This comes along with

a focus on relationship development, rather than individual transactions (Kumar 2015;

Shah et al. 2006). The underlying assumption is that well developed relationships

between firms and customers correlate with increased loyalty which in turn is associated

with greater profitability (Johnson and Bharadwaj 2005; Shah et al. 2006, 2006; Sheth

et al. 2000). The relations and interactions between customer and firm are the locus of

value creation and subject to the creation of a personalized consumer experience

(Peppers et al. 1999; Prahalad and Ramaswamy 2004).


I.5 Characteristics and antecedents of CCIS

In the following section, the organizational objectives of customer centricity in

marketing are generalized as characteristics of CCIS. The socio-technical system model

is built upon to derive hypotheses on the role of alignment capabilities as antecedents of

consumer centricity (cf. Figure 4).

Figure 4. Characteristics and antecedents of CCIS

I.5.1 Need orientation

A CCIS is need oriented when its purpose and goals (task) are aligned with the needs of

(individual) consumers. This requires consumers to skillfully apply the system to fulfill

their needs by executing tasks and conversely it requires ensuring that the CCIS defines

tasks which fulfill needs. We therefore propose H1a and H1b:

H1a (consumer-task): Enabling consumers to execute tasks and to understand their

underlying value propositions increases the consumer centricity of an IS.

Consumers need to be enabled to understand how specific tasks contribute to the

fulfilment of their needs. They further need to be capable of executing the task itself

(Lee et al. 1995). For example, training tutorials can help consumers to learn how tasks

are performed while at the same time indicating how the result of the task is linked

towards their goals.

H1b (task-consumer): Specifying tasks that aim to support the fulfilment of consumer

needs increases the consumer centricity of an IS.

The specification of tasks within CCIS refer to the definition of what a system does and

how it fulfills consumer needs (Hester 2014). The socio-technical perspective allows to

focus on instrumental and humanistic objectives (Sarker et al. 2013) which is in line

with the introduced multidimensional and holistic lens on consumer needs provided by

experiential marketing (Hirschman and Holbrook 1986). As a consequence, the


alignment between consumers and tasks requires elicitation of needs and their

translation into actionable tasks. CCIS require interaction mechanisms through, e.g.,

social media to constantly monitor consumer needs and specify tasks accordingly

(Tuunanen et al. 2008).

I.5.2 Value Co-creation

Value cocreation is regularly facilitated by technology and therefore closely linked to

the alignment of the CCIS components consumer and technology. From a socio-

technical system perspective technology refers to the tools within an information system

(Hester 2014). From a value cocreation perspective, technology represents operant

resources that different entities (consumers, firms) integrate into the value cocreation

process (Grönroos 2008; Vargo and Lusch 2004, 2008). If consumers cannot integrate

their value foundation (e.g., technology), value cocreation becomes impossible

(Grönroos 2008). Indeed, consumers (and potentially providers) integrate technology to

perform operations that fulfill their individual needs. This can occur as contribution to

the development of an IS (co-production of an offering) or within the actual usage of an

IS (Lempinen and Rajala 2014). We therefore propose H2a and H2b:

H2a (consumer-technology): Enabling consumers to integrate technology to actively

co-create value increases the consumer centricity of an IS.

Consumers must be enabled to integrate their technology resources into the CCIS in

order to contribute to the joint value creation process. This also requires consumers to

understand, operate and accept the consumer technology and potentially other consumer

facing technology (Lyytinen and Newman 2008) relevant for value cocreation at

encounter processes. For example, a consumer must be capable to establish a secure

connection with his smartphone and use a mobile banking app to interact with his bank

(Siau et al. 2001).

H2b (technology-consumer): Ensuring adaptability to and compatibility with the

technological environment of the consumer increases the consumer centricity of an IS.

While adaptability refers to an IS’ capability to adjust an installed technological base to

new or emerging technologies, compatibility ensures that different technological

combinations work together (Hanseth and Lyytinen 2010). The technology component

as enabler for dual value creation requires that the technology component is adaptable

to and compatible with the consumers’ technological environment which might change

over time. A lack of such alignment capabilities may result in unreliable, inefficient or


functionally limited technologies, inadequate to support the required processes

(Lyytinen and Newman 2008). For example, the provisioning of a smartphone

messaging application on a specific mobile operating system, e.g., Apple’s iOS, will

prevent Google’s Android users from value cocreation (exchange of messages) within

the CCIS (Joorabchi et al. 2013).

I.5.3 Relationship orientation

The literature on consumer centricity has characterized relationship orientation by

sustainability, mutual satisfaction, loyalty and cocreation of opportunities in the long

term. Relationships constitute the “social” foundation in which consumers engage and

which enable collaborative creation and exchange of value. While values refer to shared

beliefs and ideals, norms specify the associated behavioral practices. These shared

values and norms are the antecedents for successful relationship orientation as they

foster trust and consumers’ willingness for cooperation (Bendapudi and Berry 1997;

Berry 1995; Day 2000; Morgan and Hunt 1994; Sheth and Parvatlyar 1995). Through

the socio-technical lens values and norms are represented by structure, which defines

the principles of behavior that consumers act upon and influence in the interaction with

or through a CCIS. Structure refers to the systems of communication, authority and

workflow (Lyytinen and Newman 2008) and is an important element in the development

of relationships. The objective of relationship orientation within a CCIS can be

addressed through the alignment of consumers and structure. We therefore propose H3a

and H3b:

H3a (consumer-structure): Ensuring consumers’ identification with the values and

norms of a system increases the consumer centricity of an IS.

Identification is defined as the “perception of similarity of values, membership and

loyalty” (Kankanhalli et al. 2005). The communication and acceptance of shared values

is significantly increasing the alignment of consumer and structure within a socio-

technical system (Hester 2014). An example for communicating shared values and

developing a consumer relationship is Google’s value statement “don’t be evil”. As a

second example, the usage of consumer data might not be accepted due to privacy

concerns if consumers do not identify with the values embodied in a system. A potential

alignment activity could be to create transparency on the usage of consumer data as well

as its benefits that are valuable for the consumer (Li and Unger 2012).

H3b (structure-consumer): Embedding values and norms in a system that consumers

identify with increases the consumer centricity of an IS.


The normative and behavioral dimension of structure must be aligned with the values

and norms of consumers (Venkatesh et al. 2003). Systems of communication, workflow

and authority, together with norms, values and behavioral patterns (e.g., duties, roles

expectations) regulate collaboration and exchange which are the basis for developing

long term relationships. As an example, instant messaging groups on smart phones can

be created ad-hoc and allow consumers to reflect their social norms such a group

openness.

I.6 Conclusion and further research

While consumer centricity has been extensively discussed as a concept of organizational

transformation in the marketing domain, there is little research on its operationalization

as a characteristic of information systems and associated antecedents. We reviewed the

marketing literature to understand generic organizational objectives of consumer

centricity which were generalized as characteristics of CCIS. In a second step, we draw

on socio-technical theory to conceptualize antecedents of consumer centricity as

capabilities to align social and technical system components.

Alter (2008) calls for further research with regard to the “dimensions of customer-

centricity to respond to customer needs”. Our research contributes to the body of

knowledge by theoretically deriving an operationalization and antecedents of consumer

centricity in IS research.

Due to its preliminarily, this research has two limitations which we will address in our

further research: IS literature on consumer centricity needs to be included in more detail

and the theoretically derived hypotheses need to be empirically validated. We plan to

carry out an in-depth review of further IS literature to theorize on component alignment

capabilities as antecedents of consumer centricity. For example, technology acceptance

literature (such as Lee et al. (1995)) potentially provides implications on how to align

consumers and tasks (H1a) through training and education. As a second example, agile

systems development literature (Abrahamsson et al. 2009; Dingsøyr et al. 2012) might

explain the alignment of tasks to consumer needs (H1b).

We further plan to apply case study research and include different organizational and

individual information systems in a cross-case analysis (Yin 2013). The overall

objective is to validate the hypotheses on antecedents of CCIS and to construct a

nomological network for CCIS.

Part B: A Socio-Technical Approach to Study Consumer-Centric Information Systems 31

II A Socio-Technical Approach to Study Consumer-Centric

Information Systems

Table 8. Bibliographic information for Article II

Title A Socio-Technical Approach to Study Consumer-Centric Information Systems



Year 2016

Status Published

Abstract. Given the unprecedented role of digital service platforms in private life, this

research sets out to identify the mechanisms that are designed into information systems

with the purpose to increase consumer centricity. We evaluate the consumer centricity

of an information system against three reflective indicators, that is the degree of need

orientation, value cocreation and relationship orientation and conceptualize consumer

centricity as the ability to align social and technical information system components.

We employ a positivist, explanatory case study approach to test three hypotheses on

system component alignment in cases from three domains (gaming, social networking,

and video sharing). We found preliminary evidence for three alignment mechanisms that

increase consumer centricity.

With this research, we plan to contribute to the literature on consumer-centric

information systems by elaborating and empirically grounding a socio-technical

approach to study mechanisms and their joint application to increase consumer

centricity in information systems.

Keywords: Human behavior in IS, Human-computer interaction, Information systems,

IS models, IS research, Socio-technical approach, Case Study Research

32 Part B: A Socio-Technical Approach to Study Consumer-Centric Information Systems

II.1 Introduction

Enjoying Internet-based services is an integral part of our everyday life. We socialize

on Facebook, play games via Steam, and watch videos on YouTube. Today, these digital

service platforms (Lusch and Nambisan 2015) attract a large number of private users, or

consumers, who engage voluntarily and develop an emotional bond with these platforms

(Sas et al. 2009). The mentioned examples are well-crafted digital artifacts embedded

in a compatible social context: they cater to utilitarian and social needs of individual

consumers; they create a forum for collaborative dialogue; and they become more

beneficial and appealing through continued engagement. These qualities make socio-

technical systems consumer-centric (Spottke et al. 2015).

Information systems (IS) research is rooted in the workplace. Thus, systems have

traditionally been examined for their utilitarian value (Sarker et al. 2013). The

overarching question has usually been how to extract most business value from

investments in digital technologies (Agarwal and Lucas 2005). This inclination has

made IS scholars predominantly root with organizations and the people they employ,

whereas the consumer who simply wants to have a good time often has been either

ignored or marginalized (Yoo 2010). In this regard, Consumer-centric information

systems differ from organizational information systems and represent a new type of IS

(Liang and Tanniru 2006).

In this paper we propose a novel vista on the systems and companies that control these

consumer-centric information systems. Specifically, the objective of this research is to

identify mechanisms that are designed into information systems with the purpose to

increase consumer centricity. We regard consumer-centric mechanisms as interacting

processes that align socio-technical components of an information system with the

individual consumer and that cause the information system to be consumer-centric, or

organized around the consumer. The notion of socio-technical component alignment has

its roots in organizational settings (Bostrom and Heinen 1977; Hester 2014; Leavitt

1965; Lyytinen and Newman 2008; Sarker et al. 2013) but to the best of our knowledge,

it has not been applied to consumer-centric IS.

Focusing on mechanisms that foster system component alignment with the consumer

enhances existing research and has two advantages: First, it directs our attention towards

those outcomes that consumers care about, as opposed to economically relevant

outcomes for service providers. Hence, our work complements research on digital

platforms and digital infrastructures which, for example, focuses on the nature of such


digital artifacts (Kallinikos et al. 2013; Yoo 2013), on explaining how digital platforms

evolve (Hanseth and Lyytinen 2010; Henfridsson and Bygstad 2013), or on how tensions

between providers and developers are resolved (Eaton et al. 2015). Second, focusing on

mechanisms offers an analytical lens that integrates the social and technological

components. So far, research on consumer-centric IS has largely neglected the interplay

of socio-technical components. However, several publications on consumer-centric IS

have identified design activities, that we regard as mechanisms, e.g., the alignment of

service offerings toward consumer needs through personalization (Albert et al. 2004),

the modularization of technology and service architectures to align a provider’s

technology base to the consumer and her technology (Liang and Tanniru 2006;

Tuunanen et al. 2011), and the adaptation to emerging social structures within an IS to

comply with the values and norms of consumers (Wagner and Majchrzak 2006) (Pan

and Pan 2006; Wagner and Majchrzak 2006). While these authors discuss individual

mechanisms, the socio-technical model offers a lens to examine the joint application of

such mechanisms, which is at the root of consumer centricity. To frame our research,

we pose the following question: What mechanisms align the socio-technical components

of an IS towards consumer centricity?

Such a research is necessary, because the existing body of knowledge is conspicuously

silent on the specifics of consumers – and not organizational users – as actors of socio-

technical systems (Yoo 2010). To this end, we propose a research model and a case

study approach in this research-in-progress article which is suitable for identifying the

sought-for mechanisms and assessing them. With the research presented here, we

contribute to the literature on consumer centricity in socio-technical systems by

elaborating an empirical approach to identify mechanisms that increase consumer

centricity through socio-technical component alignment. To this end, (1) we apply

socio-technical systems theory to put forth the concept of a consumer-centric

information system; (2) we propose an empirical research design that aims to reveal

alignment mechanisms and their effects on consumer centricity; and (3) on a case

vignette we illustrate how the proposed model and methodological approach will help

us answering the formulated research question.

The remainder of this manuscript is structured along these lines. It concludes with a brief

reflection of main limitations and an outlook on future research.


II.2 Theoretical foundation

II.2.1 Consumer centricity and customer centricity

Customer centricity has come to be known as a synonym to “literally organize around

the customer” (Galbraith 2005 p.14). With such a vague definition in place, the term is

amenable to a broad range of interpretations and variations (Alter 2008; Shah et al.

2006). To increase clarity of the concept, we briefly introduce three main dimensions of

customer centricity commonly discussed in the marketing and IS literature, based on a

recent review of the knowledge base (Spottke et al. 2015). Turning to the marketing

discipline makes sense, because scholars of strategy and marketing have been debating

this concept for over five decades (Kumar 2015; Levitt 1960).

Moreover, we will employ the term of consumer centricity throughout this paper to

narrow the discussion towards a certain type of customer, namely an individual human

being in her private surroundings. The discussion laid out below leads us to evaluate the

consumer centricity of an IS against three reflective indicators, that is the degree of need

orientation, value cocreation and relationship orientation of an IS.

Recognizing and satisfying consumer needs is a key dimension within the consumer-

centric paradigm (Shah et al. 2006; Sheth et al. 2000). Need orientation is typically

based on information and knowledge about the preferences of individual consumers

(Peppers et al. 1999). Consumer needs are multi-dimensional and heterogeneous, that is

they encompass individual utilitarian, hedonic and social needs (Albert et al. 2004;

Schmitt 1999). In addition, they are not only experienced in cognitive, rationale terms,

but also through thoughts, emotions and activities, which are harder to detect

(Hirschman and Holbrook 1986). The degree of need orientation depends on a socio-

technical system’s ability to recognize and satisfy the multidimensional needs that are

experienced by individual consumers as part of the system.

The concept of value cocreation emphasizes the active role of consumers in value-

generating service processes (Vargo and Lusch 2004, 2008). Value is not passively

delivered to the consumer. It rather results from collaborative interactions in which

consumers and providers integrate their resources, such as skills and technologies

(Payne et al. 2008; Payne and Frow 2005). Hence, consumers are co-creators of their

experience (Prahalad and Ramaswamy 2004), their beneficiaries, and the ultimate causal

factor for any created value (Etgar 2008; Vargo and Lusch 2008). The degree of value

cocreation is reflected in how consumers are involved in the service process, e.g., the


level of resource integration and the amount of influence consumers have on service

activities (Sarker et al. 2012).

A third crucial element of consumer centricity is establishing, developing and

maintaining relationships among consumers and providers (Berry 1995; Morgan and

Hunt 1994). In order for sustainable relationships to develop, they need to be beneficial

for both parties in the long run (Lamberti 2013). Trust is regarded as the foundation of

long-term relationships, and it is built upon successful interactions, shared values and

norms, and compatible behavioral practices (Hennig-Thurau et al. 2002; Morgan and

Hunt 1994). Thus, the degree of relationship orientation depends on a system’s ability

to foster trust among participating consumers and providers, and in the continued

creation of mutual benefits through repeated interactions.

This conceptualization of consumer centricity emerged from a systematic literature

review and coding process (Spottke et al. 2016). The identified indicators are

interrelated, i.e. they can re-inforce each other, and they can occur simultaneously. For

example, personalization mechanisms aim at increasing the degree of need orientation

by adjusting a service to specific consumer preferences, thereby making interactions

more successful and, as a consequence, it deepens relationships (Huang and Rust 2013).

II.2.2 Consumer-centric information systems

Recent publications in the IS field have suggested to expand the scope of inquiry to

computing in everyday life and to the supporting artifacts and infrastructures (Yoo

2010), to account for the individuation of IT (Baskerville 2011), and to conceptualize

users as actors in their social context to better understand their technology adoption and

use (Lamb and Kling 2003; Venkatesh et al. 2012). Private users, or consumers, differ

from organizational users in important ways. Not only is system adoption voluntary and

system use guided by individual will (Tuunanen et al. 2008). Compared with

organizational users, consumers are free to choose their activities, roles and relationships

which depend on their private, individual and social contexts, i.e. they are not primarily

driven by economic considerations (Wagner and Majchrzak 2006).

An emerging body of IS literature specifies characteristics of consumer-centric

information systems and provides methodological support about how to design this type

of IS (Huang and Rust 2013; Pan and Pan 2006; Tuunanen et al. 2010; Tuunanen et al.

2011). Several studies emphasize the importance to modularize IT and service

architectures to enable flexible adaptation and reconfiguration of services (Liang and

Tanniru 2006; Tuunanen et al. 2011). For example, Albert et al. (2004) propose a


personalization process to dynamically adapt and configure a website based on

identified visitor segments. Research on consumer-centric Wikis clearly indicates the

importance of being aware of and respond to (emergent) social structures that are shaped

and enacted through practices of technology-enabled consumer collaboration (Wagner

and Majchrzak 2006). Consumer-centric IS can easily fail without mechanisms that

define, e.g., the standards and norms for collaboration, or the roles that consumers can

take, or the mechanisms for moderating social interactions (Pan and Pan 2006; Wagner

and Majchrzak 2006).

Figure 5. Research model of a consumer-centric IS

We conceptualize consumer centricity as a latent trait of an information system, the roots

of which we find in socio-technical system design. Socio-technical theory attributes a

system’s performance to the mutual alignment of four logically separated components

(Bostrom and Heinen 1977; Leavitt 1965). The research model in Figure 5 and the

hypotheses presented below are based on a previous literature review (Spottke et al.

2016) and show the system components, their alignment relationships, and the desired

outcomes of alignment. It is worth noticing that this model emphasizes the consumer as

single most relevant actor. Here, we deviate from the canonical socio-technical model

that considers all actors involved in system design and usage, such as providers,

developers, and consumers (Leavitt 1965). We regard consumer-centric mechanisms as

interacting processes that align socio-technical components of an information system

with the individual consumer and that cause the information system to be consumer-

centric, or organized around the consumer. Although extant research on consumer-

centric IS does not explicitly conceptualize socio-technical alignment mechanisms, it

suggests that personalization, modularization of architectures, and adaptation of social

structures towards consumers’ preferences, technology base and value system represent

important mechanisms to enhancing consumer centricity. In this context, the socio-


technical model offers a lens to examine the joint application of such mechanisms,

which is at the root of consumer centricity. We assume that consumer centricity is

primarily determined by those relationships in which the consumer is directly involved

(first-order effects, black arrows in Figure 5). These direct relationships are the most

pertinent ones to examine, because second-order effects affect the consumer, and thus

consumer centricity, via indirect causal changes. We therefore exclude such second-

order effects from this study.

Consumers are private individuals who perform activities (or tasks) to fulfill their

hedonic and utilitarian needs. Consumers use systems voluntarily and select their

activities freely (Wagner and Majchrzak 2006). The task-consumer relationship reflects

the capacity of system tasks to fulfill consumer needs, to enable value cocreation, and

to facilitate relationships. We argue that the task component can be aligned towards the

consumer, e.g. by implementing mechanisms that enable consumers to execute tasks or

that enable consumers to influence the task itself. Such a mechanism would for example,

enhance a system’s ability to recognize and satisfy consumer needs, or offer new

opportunities for value cocreation. We therefore hypothesize: (H1) Implementing

mechanisms that capacitate consumers to influence task design and performance

increases consumer centricity of an IS.

Technology consists of the hardware and software artifacts used within the socio-

technical system (Lyytinen and Newman 2008). In a consumer-centric IS, these

elements include consumer-controlled technology such as their private computers,

smartphones, and wearables (Liang and Tanniru 2006; Pan and Pan 2006; Tuunanen et

al. 2010). Thus, the technology-consumer relationship reflects the capacity of a system

to fulfill the technological prerequisites to integrate consumers’ technology resources,

thereby enabling them to actively co-create value, to fulfill their needs, or to build

technology-mediated relationships, e.g., by implementing mechanisms that ensure

compatibility with or adapt to consumers’ technology base. In this sense technological

adaptability refers the capability to adjust an installed technological base to new or

emerging technologies, and compatibility ensures that different technological

combinations work together (Hanseth and Lyytinen 2010). We therefore propose: (H2)

Ensuring adaptability to and compatibility with the technological environment of the

consumer increases consumer centricity of an IS.

Social structure refers to shared values and norms, as well as to behavioral practices that

govern the interactions within systems (Lyytinen and Newman 2008). For example,

existing privacy settings such as the permission to use pseudonyms, enacts certain values


and enforces specific norms within a system (Pan and Pan 2006). The consumer-

structure relationship refers to the capacity of a system to foster consumers’

identification, that is the “perception of similarity of values, membership and loyalty”

(Kankanhalli et al. 2005), with the social structure embedded in a system. We argue that

implementing mechanisms that enhance consumers’ identification fosters trust within

the relationship, and thus nurtures consumers’ willingness to collaborate in cocreation

activities. Therefore, we hypothesize: (H3) Embedding values and norms in a system

that consumers identify with increases consumer centricity of an IS.

II.3 Methodology

II.3.1 Research design

With this research we aim to identify alignment mechanisms that increase consumer

centricity within information systems. Therefore, this study involves the analysis of

socio-technical alignment activities. More specifically, we test how well the formulated

hypotheses explain mechanisms of system component alignment observed in empirical

settings.

Theory testing is often performed through quantitative research methods such as survey

instruments. However, a quantitative approach would be impractical for our purposes

because there is no unified understanding of key terms. For example, the terms

“structure”, “task” or “alignment” are not generally recognized in the context of

consumer centricity in information systems. Also, the theoretical basis to operationalize

and measure the influence of alignment mechanisms on consumer centricity is not yet

established sufficiently, and hence a qualitative research approach is favored (Benbasat

et al. 1987).

We adopt a positivist, explanatory case study approach, and do so for three fundamental

reasons. First, case studies are suitable to study context-rich socio-technical systems,

such as consumer-centric IS (Yin 2013). Second, the approach is appropriate to

understand which mechanisms are implemented and how they impact consumer

centricity (Yin 2013). Third, due to their strengths in taking context and temporal

sequence into account, case studies are useful to identify causal relationships and

thereby to test hypotheses (Dubé and Paré 2003). We study three consumer-centric

information systems in a multiple holistic case design (Yin 2013) to provide sufficient

empirical grounding and to strengthen generalizability (Benbasat et al. 1987). We

employ the proposed research model to specify the unit of analysis, namely a consumer-


centric information system, and the boundaries of our inquiry. The model also provides

a single theory approach to hypothesize on the alignment of system components

(Benbasat et al. 1987). For this study we select the leading digital video game

distribution platform (Steam), the leading social network service (Facebook) and the

leading digital video sharing platform (YouTube). Despite differing case contexts, we

expect that findings can be reproduced from case to case, that is we implement a literal

replication strategy (Yin 2013).

The case selection process is based on the principles of similarity & variation, and

information richness. The cases are similar in their exceptional success across a range

of consumer-related performance indicators. We suppose that high adoption, an

abundance of consumer-generated content, and high frequency of use, are sensible

proxies for detecting consumer centricity of an IS. For example, Steam has 125 million

active accounts, and typically 8-12 million consumers are playing video games

simultaneously every day (Valve 2016b, 2016c). Analogously, Facebook registers over

1 billion consumers per day who generate 4.3 billion “likes” (Facebook 2007). YouTube

also counts over 1 billion active consumers per day, who upload over 300 hours of video

content every minute (YouTube 2016). Consumers spend huge amounts of their time as

part of these systems in order to fulfill social and hedonic needs, such as play, social

exchange, and entertainment. They integrate their skills and technology to use the

offered services, and to engage in interactions with other consumers and with the

provider – exemplified by activities such as generating content, chatting, and rating.

According to these data, we infer the selected systems possess a high degree of consumer

centricity.

We explicitly seek for variation between cases to increase generalizability of findings.

First, the selected systems differ in their domains, namely gaming, social networking,

and video sharing. Furthermore, the socio-technical components of each system vary

with their primary purposes. For example, consumers engage with Steam to play games,

while Facebook centers around social exchange. Similarly, technology differs: in the

case of steam, consumers tend to use their gaming PCs, while Facebook and YouTube

depend much more on smartphones. As a result, we expect to empirically investigate a

broad variety of alignment mechanisms against which the hypotheses of our research

model can be tested.

Lastly, the selected cases are information rich, which allows thorough data collection

and analysis (Paré 2004). We apply four a priori criteria to assess information richness.

First, much information is published about each case and it can be obtained from


multiple sources. Second, the available data is appropriate to triangulate the perspectives

of the consumer, the provider and potentially of third parties who are involved in the

system. Third, sufficient historical data is available to study the development of the

system over time. Finally, the dimensions of consumer centricity can be described and

captured. For instance, Steam, Facebook, and YouTube enjoy extensive media

coverage, and the digital leaders controlling these systems (Valve Corp., Facebook Inc.,

Alphabet Inc.) frequently release information on crucial changes they implemented or

plan to implement. Therefore, plenty of data is available for describing key events in the

history of each system and to operationalize the dimensions of consumer centricity for

each case context.

II.3.2 Data collection and analysis

The research model guides our data collection protocol (Yin 2013). The hypotheses lead

us to focus on alignment mechanisms, the impacted socio-technical components, and

resulting changes in consumer centricity. In order to ensure quality and consistency of

obtained data and to limit the risk of bias, three researchers are engaged in data

collection. Furthermore, a case study database is established where all evidences and

their sources are filed. We collect descriptions of the system components of Steam,

Facebook and YouTube and changes of each system. These changes often affect how

consumers perceive and engage with the system, and hence are regarded to influence

component alignment. The subsequent efforts concentrate on gathering data about these

changes by drawing on multiple sources. We obtain evidence from system providers,

from public media, e.g., journals and blogs, and from engaging with the systems directly.

First, we collect data from providers which publish system and service descriptions,

help sections that explain functionality, and usage statistics. We also identified

subscriber and developer policies and system change histories as useful sources. For

example, the “Facebook Newsroom” (Facebook 2007) provides detailed descriptions of

system changes as well as (claimed) outcomes for consumers. Second, we obtain data

from publications of knowledgeable industry experts and analysts who are familiar with

one or more of the cases. This allows not only a critical assessment of provider

information, but also to understand how specific changes have been reported to impact

consumers. Exemplary sources are Harvard Business Review, Forbes.com, The

Economist, but also smaller news journals, blog entries and social media sites. These

sources help to generate and enrich the understanding of system changes, and often

include statements from consumers and provider representatives. Third, once we have

sufficient overview of each case context, we review and document how consumers


engage with the respective system, by making screenshots of relevant aspects, for

example the Steam client application and the various workflows embedded in it. We

continue with the data collection process until we are able to comprehensively describe

system changes based on multiple sources. Another criterion for ending data collection

is when information about a case consistently repeats, that is when saturation has been

reached. The collected materials are used to interpret the events during the data analysis

phase.

The purpose of data analysis is to test if the research hypotheses can explain the

empirically identified mechanisms and their outcome on consumer centricity. The

analysis follows a systematic process, separated in a within-case analysis and a cross-

case analysis phase (Yin 2013). The individual within-case analysis consists of five steps

which are summarized Table 9 and illustrated in the following section.

Table 9. Steps in within-case analysis

Steps Tasks Output

1. Define system components and explicate indicators of consumer centricity

(a) Specify relevant system components;

(b) Specify indicators of consumer centricity

IS overview, description of system components and specified indicators of consumer centricity

2. Identification of changes to the information system and their underlying forces

(a) Identify changes to the IS

(b) Develop overview of changes

(c) Assess underlying forces / drivers changes

Overview of changes and the underlying reasons why changes were performed

3. Identify impacted system components, alignment dimension and specify alignment mechanism

(a) Code data based on research model;

(b) Describe change, affected system components, mechanism and outcome for consumers

Detailed understanding of changes, mechanisms and impact on consumers’ system usage / experience

4. Identify and describe the impact of alignment mechanisms on consumer centricity

Analyze data on how alignment mechanisms impacts consumer centricity

Assessment of the causal relation between alignment mechanisms and consumer centricity

5. Test hypotheses on alignment mechanisms against results from empirical investigation

(a) Match results from empirical analysis with hypotheses derived from theory

Tested hypotheses

First, we describe the system components for each case based on a review of the

collected data and also define how the reflective indicators of consumer centricity can

be assessed in the specific case context. In the second step, we draw on multiple data

sources to develop an overview system changes. We regard system changes as the


adaptation of one or several system components (cf. Lyytinen and Newman 2008). To

gain richer insights, we also analyze the data about the circumstances and underlying

forces for each change. In the third step the elements of the research model are used to

code data, that is affected system components, alignment relations, implemented

mechanisms, and outcomes for consumers. As a result, we obtain rich descriptions of

implemented changes. In the fourth step, data are revisited to infer to which extent the

identified alignment mechanisms affects any of the three consumer centricity

dimensions before and after the implementation.

As this process includes interpretation, assessments are performed by at least two

researchers; furthermore, we require multiple supporting sources to warrant inclusion in

the analysis. Finally, in the fifth step, we test the research hypotheses against the results

from the empirical case investigation through pattern matching (Paré 2004).

Specifically, we test if the empirically studied alignment mechanisms outcomes can be

explained with the conceptually derived hypotheses of the research model.

After completion of the individual cases we perform a cross-case analysis to deepen our

understanding and to evaluate the explanatory strength of the research model by

analyzing similarities and differences between cases (Paré 2004). As we move forward

with data collection and gain an understanding of the potential similarities and

differences across the case contexts, the exact cross-case analysis procedure will be

defined in more detail.

II.4 The case of Steam: illustration of research model and research

design

We illustrate the application of the research design with an explicitly non-exhaustive

account of Steam. We apply the research model to the case vignette, summarize data

collection, and demonstrate the analysis process. We analyze the implementation of

Steam Greenlight, the Hardware and Software Survey and the Anti-Cheat Client. For

the analysis, we reviewed the Steam client update history and service descriptions to

develop the change overview, to identify alignment mechanisms and to assess their

outcomes for consumers. We corroborated these insights with media articles and

assessed the impact of changes on the dimensions of consumer centricity. The steps of

the analysis are in indicated in brackets [1]-[5].

[1a] Steam is a leading platform for digital video game distribution; it is operated by

Valve Corporation (Valve). Consumers interact with the Steam platform, as well as with


other consumers in their private realm, to play various kinds of games. The task

component describes activities such as purchasing, downloading and organizing video

games, starting game sessions, and using community functions. Technology comprises

the digital infrastructure and the Steam client software (provider technology), as well as

consumers’ gaming computers and applications (consumer technology). Structure refers

to values and norms, and behavioral mechanisms that govern the interaction between

consumers and the platform. For example, a key value in gaming is ‘fair play’, and

automated anti-cheat detection is a means to enforce this value. [1b] In the case of

Steam, an increased degree of need orientation is achieved when consumers’ demand

for new games or social features are recognized and satisfied. An increased degree of

value cocreation is achieved when consumers integrate their resources (skills and

technology) with those of the provider to enable, sustain, or enhance opportunities for

value cocreation. An increased degree of relationship orientation is achieved when

component alignment activities enhance trust among consumers, or when measures are

taken to ensure successful consumer interactions when playing games or when using

Steam.

Figure 6. Chronology of key events in the history of Steam

[2] In the second step of the analysis key events in the history of Steam are identified.

Based on the available data a chronology of key events is developed, as indicated in

Figure 6. We discuss the steps [3] to [5] for each mechanism and provide a summary of

preliminary findings in Table 10.

[3] With the introduction of Steam Greenlight, Valve replaced a slow, manual curation

process for adding new game titles to the catalog. Greenlight is a collective selection

mechanism wherein consumers vote for unpublished games, which are then approved

for publication. As Greenlight facilitates how the game catalog is expanded on Steam,

it relates to the consumer-task dimension. [4] The reviewed data suggests that Greenlight

supports need orientation, because consumers steer the system towards their

preferences. For example, on average only 15-20 games have been released per month

to the Steam catalog. After the implementation of Greenlight, the mechanism has been

used intensely and 50-100 new games are released for publication every month, leading

to a total of ~3,300 released titles between 2012 and 2016. [5] This consumer-driven


collective selection process is explained by hypothesis H1, as it capacitates consumers

to influence the task component to fulfill their needs.

[3] Valve implemented an automated Hardware and Software Survey to better

understand the variety of consumer technology configurations, and to share this

information with any interested party. On Steam, a wide range of data points and

analyses are published every month, including information on which CPUs, graphic

cards, and operating systems are popular among consumers. Implementing such survey

functionality affects alignment along the consumer-technology dimension. [4] The

survey supports value cocreation because Valve uses these insights to decide on

technology investments and to improve compatibility with consumer technologies.

Game developers use the survey to assess compatibility and performance of their games

on consumers’ PCs. [5] The survey mechanism can be explained with H2: It creates

transparency about technology and is used to ensure adaptability of the platform and

compatibility of games with consumers’ technology.

Table 10. Illustrative results of within-case Analysis

Step 5 Steps 1/2 Step 3 Step 4 Step 5

Hypo- thesis

IS change

Consumer outcome

Indication of impact on consumer centricity

Identified mechanism

Exemplary sources

Result

H1 Steam Greenlight

Consumers steer portfolio of games towards their preferences.

Need orientation.

(release of games) Collective selection

(Forbes 2012b, 2014a; Valve 2012, 2013),

(+)

H2 Hardware/ Software Survey

Enhanced compatibility of consumer technology with the platform and new games.

Value cocreation.

(support of technology related decision making)

Technology transparency

(Hoffman 2016; Hughes 2010; Valve 2016a; YouTube 2016)

(+)

H3 Anti-Cheat Client

Cheating in online games is prevented

Relationship orientation (foster trust among consumers

Norm enforcement

(Forbes 2014b; Newell 2014; SteamDB 2016; Valve 2017)

(+)

[3] Valve introduced an Anti-Cheat Client to prevent players from cheating in

multiplayer games. The Anti-Cheat Client encompasses both sophisticated heuristics to

automatically detect cheating, and a comfortable way for consumers to report potential

cheaters. Online gaming is an inherently social activity in which consumer interactions


are mediated by technology and also regulated through social structure. Hence, the Anti-

Cheat Client relates to the consumer-structure dimension. [4] The examined data

indicates that this change was implemented with the intention to foster trust among

consumers, to ensure successful gaming interactions and hence, to support relationship

orientation. The Anti-Cheat Client proved very effective: The average number of

banned players (cheaters) has constantly increased from 1.000-5.000 in 2004 to

150.000-175.000 in 2016, which indicates an increasing adoption of the feature. As of

early 2016, 2.8 million accounts have been blocked for cheating. [5] The introduction

of the Anti-Cheat Client is an evidence for H3: The prevention of cheating embeds the

value fair play and enforces the norm that cheaters are not allowed to participate in

gaming. Concluding remarks, limitations and further research

Our interest is to learn how mechanisms can align socio-technical systems towards

higher levels of consumer centricity. In this paper we developed a research model and

demonstrated its application illustratively. We found preliminary evidence for three

mechanisms that increase consumer centricity, namely consumer-driven collective

selection, increase of transparency about consumer technology, and enforcement of

norms. With the overall research program we aim to devise and empirically test a

concept of socio-technical alignment for consumer centricity and thereby offer a lens

that has been largely neglected in research on consumer-centric IS. We also aim to

provide knowledge for researchers on digital platforms and infrastructures who have

rarely focused on consumer outcomes. Our empirical study of consumer-centric IS

provides an artifact-oriented approach to examine the mechanisms that influence

consumers individual outcomes when using an IS. It further includes consumer

technology, that is the technology owned and operated by consumers. The research

presented here is clearly limited by its early stage. As for the final results, we expect two

major limitations. First, we need to be cautious in generalizing our results to other types

of IS. We will do so by critically reflecting potential contingencies. We also

acknowledge that we do not have direct access to non-published internal case material.

Nonetheless, we are confident to identify sufficiently information rich cases through our

case selection approach.

II.5 Acknowledgements

This research is funded by AXA Research Fund (Joint Research Initiative Program). We

thank Andreas Maier and Fiorenzo Maletta of AXA Winterthur for the constructive

exchange on the application of our model. We also thank the associate editor and the


two anonymous reviewers for their valuable and constructive feedback on the previous

version of this article.

Part B: What Companies Can Learn from the Videogame Industry for the Design of the Digital Customer Experience: An Analysis of the Platform Steam

47

III What Companies Can Learn from the Videogame

Industry for the Design of the Digital Customer

Experience: An Analysis of the Platform Steam

Table 11. Bibliographic information for Article III

Title What Companies Can Learn from the Videogame Industry for the Design of the Digital Customer Experience: An Analysis of the Platform Steam

Authors Benjamin Spottke

Outlet HMD Praxis der Wirtschaftsinformatik (317), Springer.

Year 2017

Status Published

Abstract. In the age of digitization the successful management of customer interactions

in the sense of a holistic digital customer experience is becoming increasingly valuable.

Technology leaders like Amazon, Apple, Facebook and Google, but also Valve as the

provider of the leading video gaming platform Steam are well known for their ability to

organize and design digital interactions between users, third parties and other actors.

This article employs the case study method to investigate the Steam platform. Based on

the analysis of Steam, recommendations for the design of the digital customer

experience are generalized. These recommendations can be applied by companies in

other industries. The study focuses on (1) the definition of services and service portfolio,

(2) the management of consumer technology, and (3) the development of trust and

loyalty by embedding values and norms within a digital platform. The elaborated

recommendations are then illustratively discussed within three settings, i.e. automobile

industry, TV streaming and a digital platform for car repairs.

This article aims to inform managers in IT service development and IT service design,

IT strategists and business architects who are responsible for the design of digital

customer experiences enabled by information systems and corresponding digital

platforms. This article contributes to theory by establishing a socio-technical lens on the

design of the digital customer experience.

Keywords: Digital Customer Experience, Digital Platforms, Service Design, Case

Study Research

48 Part B: What Companies Can Learn from the Videogame Industry for the Design of the Digital Customer Experience: An Analysis of the Platform Steam

III.1 Einleitung und Motivation

Die Gestaltung und das erfolgreiche Management der digitalen Schnittstelle zum

Kunden wird zunehmend wertvoller. Kunden und Nutzer richten viel Zeit und

Aufmerksamkeit auf digitale Plattformen und zugrundeliegende Informationssysteme

(IS), um ihren Alltag zu organisieren, um digitale Inhalte zu konsumieren und um

Bedürfnisse nach Spaß und Freude zu befriedigen. Technologieführer wie Amazon,

Apple, Facebook und Google, aber insbesondere auch Valve Corporation (nachfolgend

Valve) mit seiner Videospieleplattform Steam setzen ihre digitalen Plattformen

erfolgreich ein, um IS-gestützte Interaktionen zwischen Nutzern, Drittanbietern und

weiteren Akteuren zu organisieren (Goldbach and Benlian 2015; Lusch and Nambisan

2015). Der Begriff der Digital Customer Experience bezieht sich hierbei auf alle Phasen

des Kauf- bzw. Konsumprozesses und bezeichnet die ganzheitliche Erfahrung eines

Kunden in den digital gestützten Interaktionen mit einem oder mehreren Anbietern

(Verhoef et al. 2009). Obwohl die genannten Unternehmen unterschiedliche

Geschäftsmodelle verfolgen, wie die Platzierung von Werbeinhalten, den Verkauf und

Verleih von digitalen Produkten und Medien oder das Betreiben von digitalen

Marktplätzen, verstehen sie das erfolgreiche Management der Digital Customer

Experience als wesentlichen Erfolgstreiber für das eigene Unternehmen (Prahalad and

Ramaswamy 2004).

Die Gestaltung der Digital Customer Experience wird für Unternehmen in traditionellen

Branchen, wie z.B. der Automobil-, Finanz- oder auch Versicherungswirtschaft vor

allem aus drei Gründen relevant: Erstens erfolgen Innovationen heute vor allem auf

Ebene digitaler Produkte und Services. Deshalb ist es für Unternehmen wichtig, die

digitale Kundenerfahrung als integralen Bestandteil von Produkt- und

Serviceinnovation zu verstehen. Zweitens werden im Zuge der Digitalisierung

Kundeninteraktionen stärker durch den Einsatz von Konsumententechnologie geprägt.

Dies ist zum einen darauf zurückzuführen, dass sich Kundenerwartungen und -

präferenzen und in der Folge auch das Verhalten hin zu digitalen Interaktionen

verschiebt. Zum anderen erhöht sich auch die Verfügbarkeit und Durchdringung von

Konsumententechnologie im persönlichen Umfeld. Folglich müssen auch etablierte

Unternehmen lernen, mit einer Vielzahl von neuen Konsumententechnologie-

Konfigurationen auf Kundenseite umzugehen. Drittens werden vermehrt Drittparteien

in die Leistungserbringung und Kundeninteraktion eingebunden. Unternehmen werden

zukünftig also häufiger die Digital Customer Experience über ein


49

Leistungserbringungesnetzwerk gestalten müssen anstatt sich lediglich auf die eigene

Organisation zu konzentrieren.

Die Videospieleindustrie geht mit diesen Herausforderungen seit Jahren erfolgreich um.

Die digitale Nutzererfahrung geht über das reine Spielen hinaus und umfasst Aktivitäten

wie Strategie-Diskussionen in Foren, Streamen von Spiele-Sessions auf YouTube und

Twitch, Zusammenschluss in e-Sports-Teams und -Vereinen oder auch die Modifikation

bestehender Spieleinhalte durch Fans. Videospieler stellen also eine Kundengruppe dar,

die sich bewusst und gewünscht in digitalen sozialen Interaktionen engagiert. Weiterhin

gelten Videospieler als besonders technologieaffin, nicht zuletzt da Videospiele

regelmäßig hohe Anforderungen an die eigene Hardware stellen. Vor diesem

Hintergrund stellt die Videospieleindustrie ein geeignetes Umfeld für die Untersuchung

der Digital Customer Experience dar.

Das amerikanische Unternehmen Valve ist in der Videospieleindustrie führend und hat

die Distribution von Videospielen mit der Entwicklung der Plattform Steam

revolutioniert. Steam ist seit der Gründung im Jahr 2003 zu einer hochprofitablen

Community mit über 150 Millionen Spielern herangewachsen (Forbes 2012a; Valve

2016d). Valve ist nicht nur für seine kundenorientierte Entwicklung der Plattform,

sondern auch als ein herausragendes Beispiel für die Gestaltung der Digital Customer

Experience in diesem technologisch anspruchsvollen Umfeld bekannt (Wired 2010a).

Vor diesem Hintergrund bietet die Untersuchung von Steam reichhaltige

Lernmöglichkeiten für Unternehmen. Dieser Artikel analysiert zum einen die

unmittelbare Gestaltung der Digital Customer Experience durch Valve. Zum anderen

wird aufgezeigt, wie Drittanbieter (z.B. Spieleentwickler) mit der Steam-Community

zusammengeführt werden, um das Plattformangebot besser auf die Bedürfnisse der

Kunden abzustimmen. In diesem Sinn können Unternehmen aus anderen Bereichen von

der Videospieleindustrie über die Gestaltung der Digital Customer Experience lernen.

Nachfolgend wird zunächst Steam als führende Plattform in der Videospielindustrie

vorgestellt. Nach Erläuterung der methodischen Vorgehensweise werden die sozialen

und technischen Gestaltungsebenen digitaler Plattformen, deren Bedeutung für die

Digital Customer Experience, sowie konkrete Handlungsempfehlungen vorgestellt.

Anschließend wird die Anwendung der Handlungsempfehlungen in drei anderen

Branchen beispielhaft diskutiert.


III.2 Steam als führende Plattform der Videospieleindustrie

Seit der Einführung im Jahr 2003 hat sich Steam als weltweit führende Plattform in der

Videospieleindustrie etabliert. Drei Akteure sind für Entwicklung und Betrieb der

Plattform von besonderer Bedeutung: Konsumenten von Videospielen (Spieler), Valve

als Betreiber der Plattform sowie Spieleentwickler bzw. Herausgeber von Videospielen

(Entwickler). Spieler installieren den von Valve bereitgestellten kostenlosen Steam-

Client (Client) auf ihren PCs und erhalten dadurch Zugang zum Steam-Store, der Steam-

Community und weiteren Plattform-Services. Mit dem Steam-Client können Spieler

neue Spiele einkaufen und in einer persönlichen Spielebibliothek verwalten. Darüber

hinaus können sie mit dem Client ihre Spiele starten und konfigurieren sowie weitere

Community-Funktionen nutzen. Spieleentwickler veröffentlichen ihre Videospiele im

Steam Store und können darüber hinaus Valves Application Programming Interfaces

(APIs) und Software Development Kits (SDK) nutzen, um in ihren Spielen Community-

Funktionen wie Chats oder Matchmaking anzubieten. Valve betreibt die digitale

Infrastruktur und legt den institutionellen Rahmen für die involvierten Akteure fest.

Valve definiert vor allem Governance-Mechanismen (z.B. Richtlinien, Rollenkonzepte,

Autorisierungsverfahren und Standards), legt aber auch Preismodelle und Regeln zum

Revenue Sharing fest.

Figure 7. Entwicklung aktiver Accounts und verfügbarer Spiele auf Steam

Steam hat die Gestaltung der Digital Customer Experience in der Videospieleindustrie

neu definiert. Über Steam können Entwickler interessierte Spieler einfacher als zuvor

aktiv in die Entwicklung neuer Spiele einbinden. Dies ist vor allem Valves

konsumentenzentrierter Gestaltung der Digital Customer Experience geschuldet, welche


51

sich konsequent an den Bedürfnissen der Spieler-Community orientiert. Dies führt zu

einer hohen Identifikation und Loyalität der Spieler, die ihre Begeisterung für Steam

regelmäßig in Diskussionsforen oder Blogs mittteilen. Die Anzahl aktiver Spieler-

Accounts hat sich von 15 Mio. Spielern im Jahr 2008 auf über 150 Mio. im Jahr 2016

vervielfacht. Ähnlich hat sich das Angebot der auf Steam verfügbaren Spiele entwickelt.

So ist die Anzahl der angebotenen Spiele im Zeitraum vom 2009 bis 2016 von 1,000 auf

über 12,000 angestiegen (vgl. Figure 7).

Beide Kennzahlen spiegeln die erfolgreiche Entwicklung der Steam-Plattform wider

und sind nach Aussage von Gabe Newell, Gründer und Geschäftsführer von Valve,

direkt auf die Einführung von neuen Features und Services der Plattform

zurückzuführen (Wired 2010b). Weiterhin wurde festgestellt, dass Valve die Akzeptanz

und den Erfolg neuer Funktionen in Bezug auf die Digital Customer Experience

regelmässig misst und bewertet. Valve gestaltet also die Digital Customer Experience

auf Steam durch Services und Features. Diese sind Gegenstand der vorliegenden

Untersuchung und werden nachfolgend zusammengefasst.

III.3 Datenerhebung und Analyse

Die Zielsetzung der Arbeit besteht in der Identifikation, Strukturierung und

Generalisierung von Gestaltungsaspekten der Digital Customer Experience in der

Videospieleindustrie. Die vorgestellten Ergebnisse basieren auf einer Analyse der

Videospieleplattform Steam. Datenerhebung und Analyse folgen der

Einzelfallstudienmethodik nach Yin (2013). Im Rahmen der Datenerhebung wurde die

Entwicklung von Steam zwischen 2003 und 2016, d.h. die Implementierung von

Features und Services sowie die Entwicklung von Nutzerzahlen erfasst. Zudem wurden

öffentlich zugängliche Unternehmensinformationen erhoben und Publikationen von

Experten in der Spieleindustrie recherchiert. Schliesslich wurde ergänzend der Steam-

Client installiert und einzelne Features untersucht.

Die Analyse der Gestaltung digitaler Plattformen für die Kundeninteraktion folgt der

sozio-technischen Systemtheorie welche sowohl eine technische als auch eine soziale

Perspektive auf Steam ermöglicht. In der sozio-technischen Systemtheorie werden

neben den beteiligten Akteuren (z.B. Spieler, Entwickler und Valve) auch die

bereitgestellten Services, die eingesetzten Technologien sowie die handlungsleitenden

sozialen Strukturen, z.B. Werte und Normen, berücksichtigt (Bostrom and Heinen

1977). Aus der Synthese der zugrundeliegenden wissenschaftlichen Literatur ergeben

sich drei Gestaltungebenen und deren Kernfragen (Bostrom and Heinen 1977; Lyytinen


and Newman 2008), die nachfolgend eingeführt und in Bezug auf die Digital Customer

Experience vorgestellt werden. Auf Basis dieses theoretischen Rahmens werden

anschließend die Ergebnisse der Analyse von Steam präsentiert.

III.4 Gestaltungsebenen digitaler Plattformen und ihre Bedeutung

für die Digital Customer Experience bei Steam

III.4.1 Gestaltung von Services und Serviceportfolio

Die Ebene der Services bezieht sich auf die Festlegung des Serviceportfolios sowie die

Ausgestaltung der angebotenen Services. Diese Entscheidungen haben unmittelbaren

Einfluss auf die Digital Customer Experience und sollten so erfolgen, dass die

unterschiedlichen, vielseitigen und veränderlichen Kundenbedürfnisse erfüllt werden.

Dementsprechend sind Kernfragen dieser Gestaltungebene:

F1: Welche digitalen Produkte und Services sollen auf einer Plattform angeboten

werden?

F2: Wie sollen digitale Produkte und Services ausgestaltet werden?

In Bezug auf die Digital Customer Experience von Videospielern besteht eine

Schwierigkeit in der Zusammenstellung eines attraktiven Spieleportfolios. Eine weitere

Herausforderung besteht darin, Spiele so zu entwickeln, dass Spieler eine positive

digitale Erfahrung beim Spielen erleben (z.B. durch soziale Anerkennung oder Freude

am Spiel).

Dem Paradigma der kundenorientierten Gestaltung der Digital Customer Experience

folgend hat Valve hierzu Steam Greenlight implementiert. Mit Greenlight können

Entwickler Konzepte, Ideen und Vorversionen von Spielen vorstellen und zum

Ausprobieren verfügbar machen. Auf diese Weise gewinnen Entwickler Feedback von

der Zielgruppe, z.B. durch In-Game Analytics und Spieler-Kommentare, das in der

weiteren Ausgestaltung eines Spiels berücksichtigt wird. Beispielsweise enthielt eine

Vorversion des Titels “Left 4 Dead - Episode Two” detaillierte

Reportingfunktionalitäten um das Gameplay, d.h. einen wesentlichen Teil der Digital

Customer Experience, besser zu verstehen und beobachtete Probleme bereits während

der Spieleentwicklung zu berücksichtigen. Weiterhin wurde mit der Einführung von

Greenlight die manuelle und aufwendige Zusammenstellung des Spielekataloges durch

Valve durch einen kollektiven Auswahlprozess ersetzt. Spieler konnten nun für die


53

Veröffentlichung eines Spiels stimmen und dadurch direkten Einfluss auf das Angebot

der Steam-Plattform nehmen.

Für Entscheider, die mit der Gestaltung der Digital Customer Experience auf

Plattformen betraut sind, ergeben sich mehrere Implikationen für die Gestaltung von

Services und des Serviceportfolios. Erstens sollten Kunden durch intelligente

Mechanismen in die Festlegung des Serviceportfolios eingebunden werden. Hierdurch

kann sichergestellt werden, dass sich das Serviceportfolio an tatsächlichen

Kundenbedürfnissen orientiert. Zweitens sollten Servicedesign und -

entwicklungsprozesse konkrete Kundenpräferenzen erfassen und durch geeignete

Feedbackmechanismen eine kundenzentrierte Serviceentwicklung ermöglichen. Zum

Beispiel ist es wichtig zu erfassen auf welche Weise bereitgestellte Services oder

bestimmte Features tatsächlich genutzt werden, um die Digital Customer Experience in

nachfolgenden Entwicklungsphasen näher an den Bedürfnissen bzw. der konkreten

Nutzung zu orientieren. Drittens verdeutlicht die Implementierung von Steam

Greenlight eine wichtige Aufgabe des Plattformanbieters. Dieser fokussiert im

Fallbeispiel auf die Bereitstellung von Mechanismen, welche den Austausch zwischen

Konsumenten und Drittparteien fördern, um die Digital Customer Experience sowohl

auf Ebene einzelner Services (Spiele), als auch der Plattformnutzung im Allgemeinen

(Steam-Plattform) am Kundenbedürfnis zu orientieren.

III.4.2 Gestaltung der Technologie

Technologie ist ein Enabler für digitale Kundeninteraktionen. Gestaltungsgegenstand

der Technologieebene sind deshalb die Hardware- und Softwarekomponenten von

Endkunden, des Plattformbetreibers oder von Drittparteien, sofern sie für die

Erbringung der angebotenen Services erforderlich sind. Diese Sicht auf Technologie ist

für die Digital Customer Experience relevant, da das Zusammenspiel der IT

Infrastruktur eines Anbieters mit vielen unterschiedlichen Konsumententechnologie-

Konfigurationen ermöglicht werden muss. Vor diesem Hintergrund sind Kernfragen der

technologischen Gestaltungebene:

F3: Wie kann Transparenz über die eingesetzte Konsumententechnologie erhöht

werden?

F4: Welche Mechanismen sind geeignet, um eine Plattform für eine Vielzahl von

Konsumententechnologie-Konfigurationen zu öffnen?

F5: Wie kann Kompatibilität und Anpassungsfähigkeit der beteiligten

technologischen Komponenten – auch langfristig – sichergestellt werden?


Bei Videospielen zeigt sich diese Problematik wenn Kompatibilität mit und zwischen

hochgradig individualisierten PC-Konfigurationen von Spielern sichergestellt sein

muss, damit diese digital interagieren können. Dies gilt zum einen für die Videospiele-

Software selbst, zum anderen ist in Multiplayer-Spielen meist eine digitale Infrastruktur

erforderlich, um Spiele zwischen unterschiedlichen Spielern zu koordinieren oder um

bestimmte Dienste zentral bereit zu stellen. Dies erfolgt entweder durch einen

Plattformbetreiber oder durch Drittparteien und wirft neben der Frage der Kompatibilität

auch die Frage der Anpassungsfähigkeit auf sich wandelnde technologische

Rahmenbedingungen auf.

Im Kontext von Steam beinhaltet Technologie auf Seite von Valve die Frontend- und

Backend-Plattform-Infrastruktur für den Betrieb von Steam. Die

Konsumententechnologie der Spieler beinhaltet u.a. den Steam-Client, Videospiele,

sowie PCs mit Betriebssystem und Netzwerkinfrastruktur. Valve hat drei Mechanismen

bzw. Maßnahmen im Client implementiert, um Anpassungsfähigkeit und Kompatibilität

der genannten technologischen Komponenten sicherzustellen: Automatisierte Patches

und Updates, die Hardware und Software Survey sowie Client-Software für

verschiedene Betriebssysteme. Der Client ermöglicht das vollautomatisierte Patchen

und Updaten per Steam von auf dem PC installierten Spielen. Mit Einführung dieser

Funktionalität stellt Valve sicher, dass Konsumenten stets die neueste Version eines

Spiels auf ihrem PC installiert haben. Darüber hinaus hat Valve eine Hardware und

Software Survey im Client implementiert und veröffentlicht eine monatliche Übersicht

über eingesetzte Konsumententechnologie (Valve 2016d). Hierbei werden detaillierte

Informationen beispielsweise zu Betriebssystem, Prozessor, Grafikkarte, Speicher,

Monitorauflösung und angeschlossener Hardware sowie Informationen zur

Softwarekonfiguration erhoben. Die Teilnahme ist anonym, freiwillig und stellt eine

wichtige Brancheninformation in der Videospieleindustrie dar. Die Ergebnisse werden

nicht nur in Valves Technologieplanung berücksichtigt, sondern informieren auch

Spieler und besonders Entwickler, die ihre Spiele auf eingesetzte Technologien bzw.

Trends abstimmen können. Nach der Einführung des Steam-Clients für Windows in

2003 hat Valve die Client Software sukzessive für Mac OS (2010), Linux (2013) und

schliesslich auch ein eigenes Linux-basiertes Steam OS veröffentlicht. Durch diese

technologische Öffnung der Plattform hat Valve digitale Interaktionsmöglichkeiten mit

Kundengruppen erschlossen, die zuvor eine nicht mit Steam kompatible technologische

Basis verwendeten.


55

Die Analyse verdeutlicht, wie wichtig die Berücksichtigung von

Konsumententechnologie für die Gestaltung digitaler Interaktionen und damit auch der

Digital Customer Experience aus Sicht eines Plattformproviders ist. Hieraus folgen

mehrere Implikationen für Entscheider: Auf konzeptioneller Ebene sollten Provider

Konsumententechnologie als Ressourcen begreifen, die Kunden aktiv in die

Servicenutzung einbringen. Aus Sicht des Plattformproviders ist somit sicherzustellen,

dass Kunden ihre Technologien vor dem Hintergrund sich wandelnder

Kompatibilitätsanforderungen möglichst einfach einbringen können. Auf operativer

Ebene gilt es, die Konsumententechnologie-Konfigurationen zu verstehen und wichtige

Entwicklungen zu antizipieren. Dementsprechend können Plattformanbieter durch die

Implementierung von Monitoring-Mechanismen wie z.B. Steams Hardware und

Software Survey konkrete Erkenntnisse über die eingesetzte Technologie gewinnen und

auch in der eigenen Technologieplanung berücksichtigen. Weiterhin sollten Service-

bzw. Plattformanbieter Technologiekomponenten, auf die Kunden im Rahmen der

Servicenutzung zurückgreifen und welche im Einflussbereich des Anbieters liegen (z.B.

Apps, Websites, Client-Software, ROMs oder auch Endgeräte) so gestalten, dass diese

möglichst einfach und kostengünstig an sich wandelnde technologische

Rahmenbedingungen angepasst werden können, um digitale Interaktionen langfristig zu

ermöglichen.

III.4.3 Gestaltung sozialer Strukturen

Soziale Strukturen beschreiben die handlungsleitenden Werte und Normen

einschließlich der akzeptierten und erwarteten Verhaltensmuster und stellen damit den

institutionalisierten sozialen Rahmen, in dem sich Akteure bewegen. Bei der

Beeinflussung sozialer Strukturen geht es im Kern darum, digitale Interaktionen auf

einer Plattform so zu gestalten, dass das Verhalten der involvierten Akteure im Einklang

mit dem geltenden gemeinsamen Werte- und Normensystem steht (Lyytinen and

Newman 2008). Die Verankerung sozialer Strukturen auf einer Plattform ist zentral für

die Digital Customer Experience, da geteilte Werte und Normen als Voraussetzung für

die Entwicklung von Vertrauen und Loyalität gelten. Zentrale Fragestellungen dieser

Gestaltungsebene sind:

F6: Wie und mit welchen Instrumenten können Werte und Normen auf einer

digitalen Plattform verankert werden?

F7: Wie kann ein Anbieter auf emergente Werte und Normen eingehen?


In vielen Situationen in denen Akteure in Wettbewerbs-, Kooperations-, oder anderen

Austauschbeziehungen stehen, z.B. auch in Videospielen, sind Normen wie „Gleiche

Regeln für alle“ oder „Fair Play“ das Fundament für erfolgreiche soziale Interaktionen.

Die Vernachlässigung dieser sozialen Ebene führt leicht zu Vertrauensverlust und

schließlich zur Ablehnung eines Angebots. Dies gilt nicht nur für Interaktionen

zwischen Kunden, sondern besonders auch für Interaktionen zwischen Kunden und

einem Anbieter.

In der Analyse von Steam sind in diesem Zusammenhang vor allem die Funktionen Anti-

Cheat und Family Sharing relevant. Steam bietet Spieleentwicklern Instrumente an, um

Spielbetrug (Cheating) zu verhindern. Digitale spielerische Interaktionen werden zwar

durch Technologie ermöglicht, sind jedoch stets auch in sozialen Strukturen verankert.

Cheating wird typischerweise nicht in Situationen akzeptiert, in denen Konsumenten

mit- bzw. gegeneinander spielen. In den Nutzungsbedingungen der Steam-Plattform

etabliert Valve den institutionellen Rahmen für die Plattformnutzung und definiert

Cheaten allgemein als „Modifikationen am Spiel, deren Ziel es ist, einem Spieler einen

Vorteil zu verschaffen“ (Valve 2017). Die konkrete Umsetzung von Fair Play erfolgt

durch mehrere Maßnahmen. Erstens erfordert das Mitspielen die Akzeptanz der Steam-

Nutzungsbedingungen, durch die sich Spieler verpflichten nicht zu Cheaten oder die

Anti-Cheat Software zu manipulieren (Valve 2017). Die Nutzungsbedingungen weisen

auch auf mögliche Sanktionen hin, die, je nach Einschätzung des Schweregrades durch

Valve, von der zeitlichen Sperrung für ein Spiel bis hin zur permanenten Sperrung eines

Spieleraccounts auf der Plattform reichen. Zweitens implementiert Valve technische

Funktionen um Cheater zu identifizieren und zu sanktionieren. Hierfür wird zum einen

Valves Anti-Cheat-Software auf Spieleservern installiert, zum anderen ist der Anti-

Cheat-Client als Komponente der Client-Software auf den PCs der Spieler installiert.

Der Anti-Cheat-Client wertet Browsing-Daten und den DNS Cache auf Spieler-PCs aus,

um Auffälligkeiten zu identifizieren und im Falle eines Alarms an das Anti-Cheat-Team

von Steam zu berichten. Hierzu merkt Valves Gründer und Geschäftsführer Gabe

Newell an: „Wir arbeiten wirklich hart daran Euer [Anm.: der Spieler] Vertrauen zu

gewinnen und zu behalten“ (Forbes 2014b). Drittens können Spieler auch sowohl Cheat-

Programme als auch vermutete bzw. nachweisliche Cheater an Steams Anti-Cheat-

Team melden, welches solchen Fällen nachgeht.

Die Analyse zeigt nicht nur auf, dass die Gestaltung sozialer Strukturen wichtig für

Kundenvertrauen in digitalen Interaktionen ist, sondern weist auch auf die Vielseitigkeit

der Gestaltungsmöglichkeiten eines Providers hin. Im Fall von Steam werden mehrere


57

Instrumente für die Verankerung geteilter Werte wie Ehrlichkeit und Fairness

eingesetzt: Kommunikation und Richtlinien (z.B. Nutzungsbedingungen),

technologische Maßnahmen (z.B. Anti-Cheat Software) und schließlich die Community

selbst (Selbstkontrolle). Entscheider sollten sich darüber bewusst sein, dass erstens die

Verankerung von Werten und Normen grossen Einfluss auf die Digital Customer

Experience auf einer Plattform haben kann und zweitens sehr unterschiedliche

Maßnahmen dazu in Frage kommen.

Ein weiteres Beispiel für die Gestaltung sozialer Strukturen ist die Funktion Family

Sharing. Mit Family Sharing können einzelne Spiele oder die gesamte persönliche

Spielesammlung mit Freunden und Familienmitgliedern geteilt werden. Die

Begünstigten können damit Spiele des Freundes per Steam-Client auf ihrem eigenen PC

nutzen als hätten sie sie selbst gekauft. Wie bei dem physischen Verleih von Spielen

können jedoch nicht mehrere Instanzen eines Spieles gleichzeitig genutzt werden. Die

Implementierung von Family Sharing ist eine direkte Reaktion auf das geäusserte

Kundenbedürfnis Spiele mit Freunden und Familienmitgliedern zu teilen.

Bei der Gestaltung sozialer Strukturen sollten Plattformbetreiber aufmerksam auf

Kundenbedürfnisse reagieren, die auf bestehende oder aufkommende sozialen Praktiken

zurückzuführen sind. Im Beispiel von Family Sharing standen Valves Mitarbeiter in

engem Austausch mit der Spieler-Community und konnten so das Bedürfnis, Spiele mit

nahestehenden Personen zu teilen, auf der Plattform verankern.

III.4.4 Zusammenfassung der Handlungsempfehlungen

Nachfolgend werden die Ergebnisse der Fallstudie sowie die resultierenden

Handlungsempfehlungen für Entscheider aus den Abschnitten 4.1 bis 4.3

zusammengefasst (vgl. Table 12).


Table 12. Overview of results

Gestaltungsebenen und Fragestellungen

Handlungsempfehlungen aus der Fallstudie

4.1 Services und Serviceportfolio Ziel: Services orientieren sich an Kundenbedürfnissen

F1: Welche digitalen Produkte und Services sollen auf einer Plattform angeboten werden?

F2: Wie sollen digitalen Produkte und Services ausgestaltet werden?

H1: Provider etabliert Mechanismen wie z.B. kollaboratives Filtern und Abstimmungen, um Kunden in die Definition des Serviceportfolios einzubeziehen.

H2: Kundenpräferenzen und -bedürfnisse werden durch Analyse- und Feedbackmechanismen erfasst und in Servicedesign und Serviceentwicklung berücksichtigt.

H3: Provider stellt Mechanismen bereit, um Zusammenarbeit/Austausch von Entwicklern mit Kunden zu fördern, so dass Produkt- und Serviceentwicklung am Kundenbedürfnis orientiert werden kann.

Fallstudienbeispiel: Steam Greenlight.

4.2 Technologie Ziel: Technologie ist Enabler für digitale Kundeninteraktionen

F3: Wie kann Transparenz über eingesetzte Konsumententechnologie erhöht werden?

F4: Welche Mechanismen sind geeignet, um eine Plattform für eine Vielzahl von Konsumententechnologie-Konfigurationen zu öffnen?

F5: Wie kann Kompatibilität und Anpassungsfähigkeit der beteiligten technologischen Komponenten sichergestellt werden?

H4: Provider ergreift Maßnahmen, um bestehende und zukünftige Konsumententechnologien zu erfassen und zu verstehen, z.B. durch das Monitoring von Nutzer-/Kunden-Clients.

H5: Provider stellt durch Update-Mechanismen sicher, dass Kunden ihre Technologiekomponenten dauerhaft in Service-Interaktionen einbringen können.

H6: Provider gestaltet Technologiekomponenten wie z.B. Client-Software oder Apps so, dass ein großer Anteil relevanter Konsumententechnologie-Konfigurationen kompatibel untereinander bzw. mit der Plattform sind.

Fallstudienbeispiel: Automatisierte Patches und Updates, Hardware und Software Survey, Steam Client Software.

4.3 Soziale Strukturen Ziel: Vertrauen und Loyalität durch gemeinsame Werte und Normen

F6: Wie und mit welchen Instrumenten können Werte und Normen auf einer digitalen Plattform verankert werden?

F7: Wie kann ein Anbieter auf emergente Werte und Normen eingehen?

H7: Provider versteht die Verankerung von Werten und Normen in der Servicestrategie als ein Gestaltungselement der Digital Customer Experience.

H8: Provider nutzt verschiedene Instrumente, um Werte und Normen in Serviceinteraktionen zu verankern. Hierzu zählen z.B. Richtlinien, technologisch-analytische Maßnahmen und Kontrollmechanismen durch Kunden.

H9: Provider verfolgt im digitalen Austausch mit seinen Kunden aufmerksam bestehende und aufkommende soziale Praktiken und erkennt zugrundeliegende Kundenbedürfnisse, um Services danach zu entwickeln.

Fallstudienbeispiel: Anti-Cheat Funktionalität, Family Sharing.


59

III.5 Illustration der Handlungsempfehlungen in Automobil-,

Unterhaltungs- und Versicherungsbranche

Die Umsetzung der erarbeiteten Handlungsempfehlungen wird nachfolgend anhand von

typischen Problemstellungen in drei Branchen beispielhaft diskutiert: Der Automobil-,

der Unterhaltungs- und der Versicherungsbranche. Grundsätzlich können die neun

Handlungsempfehlungen vollständig in unterschiedliche Anwendungsfelder übertragen

werden. Jedes der drei Beispiele zeigt für eine ausgewählte Gestaltungsebene wie auch

andere Branchen von den erfolgreichen Praktiken der Videospieleindustrie profitieren

können. In der Diskussion werden jeweils die relevanten Handlungsempfehlungen mit

den in Tabelle 1 dargestellten Abkürzungen (H1-H9) referenziert.

III.5.1 Das Auto als digitale Plattform

Digitalisierung ist derzeit das zentrale Thema der Automobilindustrie. Nahezu alle

großen Hersteller versuchen ihre Fahrzeuge als digitale Plattform zu etablieren, um

Kunden neue digitale Services anzubieten die über reine Fahrzeugmobilität

hinausgehen. Initiativen wie „Audi Connect“, „BMW Connected Drive“ oder

„Mercedes Me“ versprechen unter anderem digitale Services zur Fahrzeugsteuerung,

Routenführung, Versicherung, für Notfallsituationen oder zur Unterhaltung.

Verglichen mit dem traditionellen Serviceportfolio eines Automobilherstellers wird

schnell deutlich, dass die Auswahl und Ausarbeitung der angebotenen Services zu einer

wesentlichen Gestaltungsaufgabe wird. Zudem ist es unwahrscheinlich, dass

traditionelle Unternehmen wie Audi, BMW oder Mercedes die nötigen Entwicklungs-

und Produktionskapazitäten besitzen, um alle Services selbst zu entwickeln bzw.

anzubieten. Eine sinnvolle Strategie für sie wird es deshalb sein, sich als

Plattformanbieter zu etablieren und stark auf die ganzheitliche Gestaltung der Digital

Customer Experience zu fokussieren.

Automobilhersteller können auf der Gestaltungsebene der Services von der

Videospielindustrie lernen. Entsprechend sollten Kunden aktiv in Auswahl und

Ausarbeitung der angebotenen Services eingebunden werden. Denkbar wäre es zum

Beispiel, Mechanismen zu implementieren, durch die Hersteller und Drittparteien ihre

Services vorstellen und Kunden über die Weiterentwicklung mitbestimmen oder sich

als Testnutzer anmelden können (vgl. H1, H2). Darüber hinaus ist die Sammlung und

Analyse von Service-Nutzungsdaten ratsam, da diese eine wertvolle Informationsquelle


über die tatsächliche Nutzung und damit die Relevanz der angebotenen Services darstellt

(H3).

III.5.2 TV Streaming auf Smart TV, mobile Geräte und Spielekonsolen

TV- und Radioinhalte werden zunehmend digital übertragen und Anbieter wie Zattoo,

Amazon oder Netflix haben sich darauf spezialisiert, Inhalte ausschließlich über das

Internet zu senden. Der Unterschied zu traditionellem Radio und Fernsehen liegt jedoch

nicht nur im Übertragungsmedium, sondern auch in der Vielzahl relevanter

Konsumententechnologien wie Smart TVs, mobile Geräte und Spielekonsolen. Hinzu

kommen neue Services wie digitales Ausleihen von Medieninhalten oder Video on

Demand.

Streaming Anbieter sollten die Gestaltung der Technologieebene als Voraussetzung für

digitale Kundeninteraktionen verstehen und besonders Konsumententechnologien als

wichtigen Einflussfaktor der Digital Customer Experience erkennen. Die in der

Fallstudie identifizierten Handlungsempfehlungen zeigen auf, wie Provider

Konsumentenendgeräte beobachten und beeinflussen können und sind auf den Kontext

von TV-Streaming unmittelbar anwendbar. Streaming Anbieter sollten die Architektur

ihrer Plattformen, insbesondere Clients und Apps, die auf Konsumentengeräten

installiert werden, mit entsprechenden Monitoring-Funktionalitäten ausstatten (H4). So

sind Informationen wie z.B. Bildschirmauflösung, tatsächliche

Datenübertragungsbandbreite und Latenzzeiten, aber auch Modellinformationen oder

Betriebssysteme kritisch für die Übertragung von Medieninhalten. Streaming

Dienstleister sind nicht nur wandelnden Kundenanforderungen an Services unterworfen,

sondern müssen sich auch auf verändernde technische Anforderungen und

Möglichkeiten auf Kundenseite einstellen. Ein Beispiel hierfür ist die Veränderung von

Bildschirmauflösungen von HD zu Full HD und derzeit 4K. Serviceanbieter sollten

neben der Erfassung also auch entsprechende Funktionalitäten zur

Softwareaktualisierung und auch zur Dokumentation von auftretenden Fehlern

implementieren, um z.B. Inkompatibilitäten von Service und eingesetzter Technologie

zu identifizieren bzw. zu beheben (H5, H6).

III.5.3 Die Plattform eines Versicherungsunternehmens für die Vermittlung von

Autoreparaturen

Die Kundeninteraktion in der Versicherungsindustrie verschiebt sich von Offline- zu

Onlinekanälen. Dementsprechend sind viele Interaktionen mit Versicherungen heute

schon vollständig digital möglich. Darüber hinaus besteht ein hoher Druck auf


61

Versicherungen neue Services zu entwickeln, die über das traditionelle

Leistungsangebot hinausgehen.

Exemplarisch für diese Entwicklung steht die digitale Plattform einer Versicherung,

welche Reparaturen zwischen Autofahrern und Werkstätten vermittelt. Kunden

spezifizieren bestimmte Reparatur- oder Wartungsaufgaben und Autowerkstätten

können auf dieser Basis ein Angebot für die entsprechende Arbeit erstellen. Kunden

können dann eines der Angebote auswählen und die Werkstatt mit der Arbeit

beauftragen. Eine wesentliche Herausforderung in dem Kontext ist die Schaffung von

Vertrauen in Preisgestaltung und Qualität der zu erbringenden Serviceleistung. Diese

sind ex-ante, also vor einer Reparatur, für Kunden kaum oder gar nicht einschätzbar.

Dies birgt stets das Risiko für eine negative Kundenerfahrung, z.B. durch höhere als

ursprünglich angegebene Kosten, unvorhergesehene Aufwendungen oder schlecht

durchgeführte Reparaturen. Eine negative Kundenerfahrung schadet nicht nur dem

eigentlichen Serviceerbringer (der Werkstatt), sondern auch der Reputation des

Plattformanbieters.

Anbieter solcher digitalen Plattformen können aus dem dargestellten Fallbeispiel aus

der Spieleindustrie nützliche Erkenntnisse für die Gestaltung sozialer Strukturen

gewinnen. Zum einen sollten Anbieter Werte wie Zuverlässigkeit und Transparenz

bezogen auf Preis- und Servicequalität als wichtige Gestaltungskomponente in der

Servicestrategie definieren (H7). Hierfür bietet sich z.B. ein Bewertungssystem an.

Weiterhin sollte der Plattformanbieter mit geeigneten Instrumenten Werte und Normen

in den Serviceinteraktionen verankern (H8). Analog zur Anti-Cheat-Funktionalität bei

Steam wären mögliche Maßnahmen z.B. die Einführung einer Richtlinie, in der sich

Werkstätten beispielsweise dazu verpflichten, Kunden keine unverhältnismäßigen oder

marktunüblichen Offerten einzugeben. Eine datenorientierte Maßnahme wäre z.B. die

Erfassung von Angebotsdaten, insbesondere Preis und Umfang der angebotenen

Reparatur und ex-post die Erfassung und Berechnung der Preistreue der Werkstatt.

Schließlich ist auch ein System denkbar, mit dem Kunden gebuchte Werkstätten

bewerten oder negative Serviceinteraktionen melden können. Darüber hinaus sollte der

Plattformanbieter den Austausch mit seinen Kunden in Chats, Telefonaten oder auch

Befragungen suchen und aufmerksam für geäußerte Bedürfnisse oder

vertrauensverhindernde Funktionalitäten sein, um entsprechende Instrumente der

Wertverankerung zielgerichtet implementieren zu können (H9).


III.6 Zusammenfassung und Ausblick

In diesem Artikel wurde ein sozio-technischer Rahmen vorgestellt, mit dem

Plattformanbieter drei Gestaltungsebenen der Digital Customer Experience analysieren

und planen können. Die Spieleplattform Steam wurde mit der Fallstudienmethode

untersucht, sodass Handlungsempfehlungen zur Gestaltung der Digital Customer

Experience abgeleitet werden konnten. Die Anwendung der Handlungsempfehlungen

wurden anschließend im Kontext von Automobilbranche, TV-Streaming Anbietern und

anhand einer Plattform für Autoreparaturen beispielhaft diskutiert.

Die Ergebnisse der Arbeit richten sich an verantwortliche Entscheider im IT-Service-

Development und IT-Service-Design, IT-Strategen und Business Architekten, die ihre

Informationssysteme und digitalen Plattformen in Hinblick auf die Gestaltung der

Digital Customer Experience entwickeln und bewerten wollen. Erstens zeigen die

erarbeiteten inhaltlichen Erkenntnisse erprobte Möglichkeiten auf, die Digital Customer

Experience erfolgreich zu gestalten. Sie folgen aus der Fallstudie und stellen eine gute

Grundlage für die Übertragung in weitere Unternehmenskontexte dar. Zweitens liefern

die vorgestellten Gestaltungsebenen einen Rahmen zur Strukturierung. Im Rahmen der

Fallstudie hat sich zum Beispiel gezeigt, dass insbesondere die Gestaltung der sozialen

Ebene, d.h. „Werte und Normen“, häufig vernachlässigt wird und größere

Aufmerksamkeit erfordert. Das Modell kann die Analyse und Planung der eigenen

Digital Customer Experience unterstützen, da es die Aufmerksamkeit des Entscheiders

nicht nur auf service- und technologiebezogene Fragestellungen lenkt, sondern auch die

Gestaltung digitaler sozialer Interaktionen hinterfragt.

III.7 Danksagung

Der Autor dankt dem AXA Research Fund Paris für die Förderung dieser Arbeit im Rahmen des Förderungsprogramms Joint Research Initiative Agile Application Management.

Part B: Service Innovation in Social Networking Services 63

IV Service Innovation in Social Networking Services: A

Resource Integration Perspective on Facebook

Table 13. Bibliographic information for Article IV

Title Service Innovation in Social Networking Services: A Resource Integration Perspective on Facebook


Outlet Research aiming at a paper in a top IS journal (e.g., Information Systems Journal)

Year 2018

Status Working paper (IWI-HSG)

Abstract. This paper explores how Facebook, the world’s largest and most successful

social networking service (SNS) provider, and its consumers generated service

innovations through resource integration. While prior research emphasizes the

importance of third-party developers, little is known about how consumers and their

resources are leveraged for generating service innovations in SNS. To this end, this

paper proposes the resource integration model as a theoretical framework that is rooted

in service-dominant logic, and that conceptualizes resource integration as the process

underlying service innovation. We apply the model to an explorative, interpretive case

study of Facebook with a detailed analysis of 51 service innovations generated between

2004 and 2017. Our analysis uncovered three service innovation mechanisms: data-

driven innovation, technology propulsion, and social debugging. Each mechanism

provides insights about the resources and resource integration dynamics of consumer

and provider, and how these have been generative of service innovations. Our findings

suggest that service innovation in SNS relies significantly on the provider’s ability to

successfully engage, facilitate, and leverage the resources and resource integration of

consumers. While the mechanisms can be used to examine service innovations in

specific contexts, the model can be specialized for studying diverse aspects of service

innovation and resource integration, which we exemplified by blending the socio-

technical framework into the case analysis. Our research offers a novel perspective on

service innovation and enhances previous research on SNS, as well as service innovation

in the digital age.

Key words: service innovation, digital innovation, social networking services, service-

dominant logic, Facebook, case study, mechanism

64 Part B: Service Innovation in Social Networking Services

IV.1 Introduction

Over the past decade, we have witnessed the proliferation of social networking services

(SNS) into everyday life. Consumers engage deeply and voluntarily with these services

by sharing private and public messages, photos, videos and other content (Sas et al.

2009). SNS attract billions of consumers who network and communicate with friends

and organizations. SNS providers generate profits from online advertising, based on

their in-depth knowledge of consumers’ preferences, worldviews, and technological

abilities (Gnyawali et al. 2010). While some SNS have continued to thrive over the

years, e.g., Facebook, Twitter, and YouTube, to name a few, others have forfeited

consumers’ interest, e.g., Myspace or Friendster, and eventually sunk into oblivion. SNS

providers’ insatiable hunger for growth and consumer attention, combined with a highly

competitive environment, makes service innovation a strategic imperative and

continuous obligation (Gnyawali et al. 2010).

At the same time, research on service innovation underwent a fundamental paradigmatic

shift in the digital age. Service innovation is less often viewed as the result of a single

firm that generates new offerings. Increasingly, it is understood as a collaborative

process, in which actors within an ecosystem contribute and integrate their resources to

produce something valuable (Grönroos 2008; Payne et al. 2008; Prahalad and

Ramaswamy 2004; Vargo and Lusch 2004, 2008). To this end, we adopt service-

dominant (S-D) logic and refer to service innovation as the “rebundling of diverse

resources that create novel resources that are beneficial (i.e., value experiencing) to

some actors in a given context” (Lusch and Nambisan 2015, p. 161). Consistent with

this definition, we refer to resources as anything an actor can draw on for support, e.g.,

knowledge and skills, or other physical and digital resources (Vargo and Lusch 2004).

While service innovation can be viewed from different theoretical angles (cf. Barrett et

al. 2015), S-D logic offers a conceptual foundation that centralizes on actors and

resource integration, which represents the very process of value cocreation and service

innovation (Lusch and Nambisan 2015, p. 168).

To date, there is a paucity of empirically grounded, theoretical knowledge that explains

how providers and consumers integrate their resources to generate service innovations.

Prior research has theorized how digital technologies are generative of product and

service innovations based on the recombination of resources (Yoo et al. 2012), and how

digital infrastructures are generative of innovation by enhancing availability of

resources to diverse actors (Henfridsson and Bygstad 2013; Tilson et al. 2010). The

scholarly discourse on platform ecosystems (Tiwana et al. 2010) focuses on how skilled


third-party developers can be leveraged to generate innovations (Eaton et al. 2015;

Ghazawneh and Henfridsson 2013). Recent IS publications have empirically studied

service innovation and value cocreation in the context of enterprise systems (Ceccagnoli

et al. 2012; Lempinen and Rajala 2014; Sarker et al. 2012), inter-organizational IS (Rai

et al. 2012), and innovation alliances between firms (Han et al. 2012). These

publications suggest the importance of resource integration for service innovation. They

focus, however, on B2B environments and do not consider resource integration of

consumers. That is, little research has explicitly focused on how service innovations are

generated through resource integration, and in particular how consumers’ resource

integration is linked to it.

In SNS consumers contribute not only operational capacity and skills, but also social

and technical resources (Singaraju et al. 2016). Consumers’ role in service innovation

is also likely to be more subtle, as opposed to third party developers who invent new

applications or features. When consumers interact with SNS features, they often create

new resources, in particular data, knowledge, and skills, that can be drawn on to generate

service innovations. For example, consumers create personal data and content (Alaimo

and Kallinikos 2017; Zeng and Wei 2013), which has recently been labelled as the “most

valuable resource in the world” (The Economist 2017). Consumers also operate personal

information technology (Baskerville 2011; Yoo 2010) which, together with consumers’

operational capacity, represent resources upon which novel services can be developed.

Above all, consumers’ activities might not simply be regarded as operational, technical

resources; they also enact values and norms which contribute to the social structure

underlying collaborative relationships (Wagner and Majchrzak 2006). Consumers might

not be willing to provide their resources under all circumstances, as regular outcries

about data use, personal privacy and privacy controls in SNS suggest (Cavusoglu et al.

2016; Hoadley et al. 2010; TechCrunch 2009). Few studies account for the social and

technical resources of consumers (Arnould et al. 2006; Baron and Harris 2008;

Baskerville 2011), and research on SNS innovation emphasizes the role of SNS provider

and third-party developers (Gnyawali et al. 2010). As a result, consumer resources and

resource integration have not been linked to the generation of service innovations in

SNS. This is surprising, since SNS innovations are primarily targeted at consumers, and

conversely, the resources generated by consumers are essential for the generation of

innovations in SNS.

To address these challenges, the objective of this research is to develop an empirically

based understanding of service innovation in SNS, with a particular focus on how


consumer and provider integrate their resources to generate service innovations. To

frame our work, we pose the following research question: How do provider and

consumers integrate their respective resources in social networking services to generate

service innovations?

We attempt to accomplish the research objective through an explorative, interpretive

case study design in the context of Facebook, the world’s largest and most successful

SNS. Facebook has a track record of service innovations and exhibits resource

integration with consumers in an extreme fashion. To capture the interactions between

consumer and provider, we propose a resource integration model that is rooted in S-D

logic (Vargo and Lusch 2004, 2008). We further employ socio-technical system theory

as a structuring framework to categorize service innovations, and accordingly, the

involved resources of consumer and provider. On this conceptual basis, we trace

Facebook’s service innovations history, analyze the involved consumer and provider

resources, and identify the resource integration processes by which service innovations

were generated in the case context. Following a process of gradual abstraction and

generalization, we identify three service innovation mechanisms, namely data-driven

innovation, technology propulsion, and social debugging. We comprehend these

mechanisms as causal structures by which consumers and provider generate service

innovations.

This article provides four contributions. First, it provides a empirically grounded,

theoretical understanding of how resource integration is generative of service

innovation. Second, it accounts for consumer resources involved in the generation of

service innovation. Thereby, we complement studies that focus on how third-party

developers generate service innovations in platform ecosystems. Third, by blending the

socio-technical framework into the model, we develop three mechanisms that add a

refined and nuanced understanding of service innovation that adds to the SNS literature.

Finally, the findings contribute to research on digital innovation and digital ecosystems

by specifying resources essential for innovating digital services for consumers. In this

regard, we respond to Lusch and Nambisan (2015) who indicated the need for

mechanisms that support the respective roles and processes related to resource

integration, as well as other IS scholars who call for more grounded research on service

innovation in the digital age (Barrett et al. 2015; Nambisan et al. 2017).

This article is organized as follows. First, we discuss related work on service innovation

and resource integration with a particular focus on SNS. We then synthesize a resource

integration model from the literature which summarizes our literature-based


understanding to guide our empirical investigation. This is followed by a presentation

of Facebook, the selected case, and a discussion of the methodology employed in this

study. Based on our findings from data analysis, we present three mechanisms that

explain how service innovations are generated through resource integration in SNS. The

paper concludes with a discussion of findings, a reflection on contributions, limitations,

and an outlook on future research.

IV.2 Related research and conceptual basis

IV.2.1 Service innovation and resource integration

There is little doubt that information and communication technologies have a substantial

role as resources in service innovation (Barrett et al. 2015; Vargo and Lusch 2004,

2008). Prior research has theorized how digital technologies, which separate digital

content (e.g., data and information) from its physical medium (Yoo et al. 2010), enable

the generation of innovations based on the recombination of digital resources (Yoo et

al. 2012). IS researchers have also focused on digital infrastructures, which enhance the

availability of digital resources to the actors involved in service innovation (Henfridsson

and Bygstad 2013; Tilson et al. 2010). Attention has also been paid to the design and

development of platform ecosystems (Tiwana et al. 2010), and associated with it, the

capacity to leverage third-parties for service innovation through the management of

boundary resources (Eaton et al. 2015; Ghazawneh and Henfridsson 2013). In this

regard, extant IS research on service innovation theorizes on the organization of actors,

in particular platform owners and third party developers, as well as the digital

infrastructures and digital platforms, which enable the generation of service innovations.

Recent publications underlined the need for novel theorizing on service innovation in

the digital age (Barrett et al. 2015; Lusch and Nambisan 2015; Nambisan et al. 2017).

For example, Nambisan et al. (2017) notice more distributed and shifting agency in

innovation processes, because digital innovations occur increasingly through emergent

and dynamic processes which involve multiple actors (cf. Zittrain 2006; Zittrain 2008).

Innovation processes in the digital world are also less bounded in terms of time and

space (Nambisan et al. 2017). For example, the generation and availability of data

resources, combined with analytical capacity of an actor can create a plethora of

innovation opportunities (cf. Huang et al. (2016) for an example). This makes it difficult

to determine as to when a particular innovation process phase starts and/or ends

(Nambisan et al. 2017, p. 225).


In their recent synthesis of the literature, Lusch and Nambisan (2015) offered a

broadened view of service innovation in the digital age, which is grounded in S-D logic.

S-D logic originates in marketing and service research and re-conceptualizes service as

the basis of all social and economic exchange (Vargo and Lusch 2004, 2008, 2016).

Service is defined as the “application of specialized competences (knowledge and skills)

through deeds, processes, and performances for the benefit of another actor or the actor

itself” (Vargo and Lusch 2004, p. 2). In that regard, service refers to the application of

resources (e.g., knowledge and skill) to create something beneficial for and in

conjunction with other actors (Vargo and Lusch 2008). S-D logic differentiates between

operant and operand resources. Key to the performance and exchange of services are

operant resources, e.g., knowledge and skills, which are capable of acting upon other

resources. Operand resources are passive and tangible resources upon which an act is

performed to produce something (Vargo and Lusch 2008). S-D logic regards all actors

as resource integrators (Vargo and Lusch 2004, 2008, 2016). This means, the process of

integrating resources is not only performed by a provider, but also by the beneficiary,

e.g., a consumer. In that sense, value is a result of reciprocal service exchange and based

on the resource integration of diverse actors with different roles (Grönroos and Voima

2013; Prahalad and Ramaswamy 2004; Vargo and Lusch 2004, 2008). Löbler and Lusch

(2014) provide a practical example of how a word processing software can be seen from

a service perspective. A software programmer applies his skills and knowledge (operant

resources) to generate the software (operand resource). Then, a user employs her skills

(operant resources) to use the program (operand resource), thereby generating value in

her context. From this example, it becomes clear, that services are not only exchanged

through direct interactions, but also indirectly, through operand resources, which are

conceived as distribution mechanisms (Vargo and Lusch 2004). In this regard, we define

resources that serve as the interface through which resource integration activities of

consumer and provider are mediated as interfacing operand resources. This is

particularly relevant for conceptualizing resource integration in digital services where

interactions occur through interfacing websites, software applications, or more general,

data and technology.

IV.2.2 Service innovation in social networking services

Previous research in the marketing, strategic management and the IS discipline

demonstrated the importance of service innovations in SNS (Aral et al. 2013; Gnyawali

et al. 2010; Singaraju et al. 2016). In their empirical study of 52 SNS, Gnyawali et al.

(2010) showed that providers continuously engage with consumers and third-parties to


develop and release new features. The generation of new features represents the primary

activity of SNS providers to attract and retain users, and to stay competitive in their

market (Gnyawali et al. 2010). Following the S-D logic perspective, we conceive service

innovation in SNS as the rebundling of resources, created through resource integration

of consumer and provider. For example, consumers draw on SNS features and apply

their knowledge and skills when using it. During this activity, new data is produced that

the provider can draw on when producing a new or change an existing feature that is

then made available to consumers.

Extant research on SNS focused on the generation of social data and content by

consumers (Alaimo and Kallinikos 2017; Zeng and Wei 2013). Other studies

highlighted conditions under which consumers’ self-disclose personal information

(Chen and Sharma 2013; Tow et al. 2010), for which privacy features play a particular

role (Cavusoglu et al. 2016). Another nascent stream of research focuses on consumers’

motivation, adoption and (discontinued) use of social networks (Cheung et al. 2011;

Maier et al. 2015; Ross et al. 2009). Some publications centralized on how value is

cocreated by multiple actors (Singaraju et al. 2016), and how it might be monetized by

firms through novel revenue and business models (Enders et al. 2008; Ketonen-Oksi et

al. 2016). Very few publications provide knowledge about how new features are

developed. Such publications have remained either conceptual (Xiao and Wang 2014),

or reported on the internal processes of an SNS provider from an practitioner viewpoint

(Feitelson et al. 2013).

To date, there is a paucity of empirically grounded, theoretical knowledge that explains

how provider and consumers integrate their resources in SNS to generate service

innovations. We contend that the reciprocity and relatedness of service exchange and

resource integration, as underlined in S-D logic (Vargo and Lusch 2004, 2008), is not

explicated in the literature. By drawing on the S-T framework we explicitly account for

the social and technical resources that consumer and provider possess, which we explain

in the next section, together with the theoretical model that guided this research. The

objective of our research is then to identify and understand the causal structures, i.e.,

mechanisms, by which consumer and provider generate service innovations through

resource integration.

IV.2.3 The model of resource integration in social networking services

We propose a model of resource integration to explore mechanisms by which service

innovations are generated in SNS. Even though the importance of service innovations


has been highlighted in prior SNS research (Aral et al. 2013; Gnyawali et al. 2010;

Singaraju et al. 2016), little attention has been paid to how resource integration of

consumer and provider is generative of service innovations. We contend that not only

the provider, but also consumers contribute resources that are essential for service

innovation.

Service innovation: The “rebundling of diverse resources that create novel resources that are beneficial (i.e., value experiencing) to some actors in a given context” (Lusch and Nambisan 2015, p. 161).

Resource integration: The processes and activities in which involved actors (e.g., consumers and poviders) employ their resources to co-create value and to generate service innovations.

Interfacing operand resources: Resources upon which an act is performed to produce an effect (Vargo and Lusch 2008) and which serve as the interface through which resource integration activities of consumer and provider are mediated (Vargo and Lusch 2004, 2008).

Operant resources: Resources that are capable of acting upon other resources to create value (Vargo and Lusch 2008). These types of resources are often intangible and active and therefore appear as actors or initiators (Lusch and Nambisan 2015).

Figure 8. Resource integration model and main theoretical constructs

Figure 8 provides definitions of the main theoretical constructs and their relationships

within the resource integration model. The model depicts resource integration as a

process in which each actor draws on interfacing operand resources to which he applies

operant resources, to produce some effect upon the interfacing operand resource. The

symmetry of the model reflects a fundamental premise of S-D logic, i.e., all actors are

resource integrators (Vargo and Lusch 2008), but does not suggest that the actors are

identical. Instead, provider and consumer perform different resource integration

activities, based on their distinct resource base.


Against this background, we view, consistent with Lusch and Nambisan (2015, p. 168),

the activities underlying resource integration as the very process of (value cocreation

and) service innovation. Service innovation refers to the process of rebundling resources

to create novel resources. Novel resources then create new opportunities for resource

integration. The rebundling process itself, however, also occurs through resource

integration, which accords with Löbler and Lusch (2014, p. 7), who underline that “when

actors integrate resources, they often arrive at novel combinations that result in

innovative ways of doing.” That is, resource integration reflects the process by which

actors produce new resources, e.g., a new feature, that other actors can then draw on to

generate value (by integrating their resources). It is important to note that rebundling

involves diverse competences and capabilities, which we view, consistent with

Madhavaram and Hunt (2008, p. 69), as operant resources. This conceptualization of

service innovation, as a result of rebundling resources through resource integration, is

grounded in S-D logic and directs our attention at the interfacing operand resources, as

well as the operant resources of consumer and provider.

Interfacing operand resources mediate the resource integration of consumer and

provider. As such, the consumer makes use of resources generated by the provider, and

vice versa, the provider make use of resources generated by the consumer. To explore

service innovation in SNS, we contend that (new) features represent interfacing operand

resources that enable (new) social networking activities. This view is consistent with

prior publications that regard features, e.g., a personal profile, online groups, comments,

or features for sharing user created content and managing personal privacy as the

constitutive building blocks of SNS (Aral et al. 2013; Cavusoglu et al. 2016; Kietzmann

et al. 2011; Kim et al. 2010; Turel et al. 2010). While new features are typically

generated through the rebundling activities of the provider, we argue that consumers

also provide resources that contribute to the generation of service innovations. For

example, when consumers integrate resources they generate vast amounts and varieties

of data and user generated content (Alaimo and Kallinikos 2017; Zeng and Wei 2013),

and they provide personal information and communication technology (Baskerville

2011) that mediate consumers’ resource integration (Baron and Harris 2008). That is,

data and consumer technology also represent interfacing operand resources provided for

using and innovating (new) features.

Operant resources are capable of acting upon other resources to produce an effect

(Vargo and Lusch 2008). These resources are often intangible and active and therefore

appear as actors or initiators in resource integration (Vargo and Lusch 2008). Operant


resources hold transformational capacity and ultimately, are essential for creating new

resources (Madhavaram and Hunt 2008; Moeller et al. 2013). Typical operant resources

are human beings with their specialized skills and knowledge, including the knowledge

to operate technology, as well as physical and mental skills (Lusch and Nambisan 2015).

In SNS, operant resources include the knowledge, skills, and competences that

consumer and provider possess and integrate with other resources. Extant literature has

suggested that consumers, for example, integrate not only physical and material, but also

social, cultural and physical operant resources such as relationships, sensimotor

endowment, energy, and knowledge about shared values and beliefs (Arnould et al.

2006; Baron and Harris 2008). Similarly, Maglio and Spohrer (2008) distinguish people,

technology, organizations, and information as four resource categories, and emphasize

the importance of socially constructed resources, e.g., relationships, identity and

reputation (Spohrer and Maglio 2010, p. 159). With regard to the resource integration

model and the study of service innovation in SNS, operant resources are broadly

conceptualized and sensitize this research on the knowledge, skills, and competences of

consumer and provider, involved in the generation of interfacing operand resources.

Social networking services are socio-technical systems. They offer a variety of social

activities that are enabled by information and communication technology. We therefore

adopt socio-technical (S-T) system theory (Bostrom and Heinen 1977) as a reference

framework to structure our analysis of how consumer and provider integrate their social

and technical resources to generate service innovations.

The S-T framework is an appropriate meta-framework for our purpose. It provides a

comprehensive foundation to describe socio-technical systems which is simple,

extensive, sufficiently well defined, anchored in extant theory, and it can be easily

extended with other categories to obtain richer vocabulary (Lyytinen and Newman

2008). The S-T framework extends the conceptualization of resources by providing

distinct lenses onto the phenomenon of interest.

The S-T framework recognizes four constitutive social and technical components, i.e.,

actor, task, technology, and structure (Hester 2014). Actor refers to the participants that

are involved in the system and that carry out and influence the work. Task refers to the

goals and activities of a system, and the way information is processed.

Technology refers to the hardware and software components that are used to process

information. Structure refers to systems of authority, workflow and communication, and

includes the normative and behavioral dimension of values, norms and role expectations

(Hester 2014; Lyytinen and Newman 2008).


This paper focuses on consumer and provider as two resource-integrating actors. Their

resource integration is essential to the generation and analysis of service innovations,

and thus their activities are ingrained in the resource integration model. We employ the

remaining three S-T components, i.e., task, technology and structure as three distinct

lenses to flesh out the “center of gravity” of each service innovation. Accordingly, we

distinguish service innovations as task-centered, technology-centered, and structure-

centered.

In task-centered service innovations, interfacing operand resources are generated to

support new, or altered social networking activities, and the way how information is

processed and displayed. This applies, for example, to features that innovate the news

displayed to consumers, or how consumers can interact with news from their personal

network. This still involves actors (who perform a task), enabling technology, and social

structure, but the task is central to this perspective. In technology-centered service

innovations, interfacing operand resources are generated on the basis of new or altered

technology resources. For example, service innovations that leverage the emergence of

smartphones or virtual reality technology, fall into this category. This still involves

actors who perform a task, as well as social structure, but the technology is central to

this perspective. In structure-centered service innovations, interfacing operand resources

are generated that support new ways to govern interactions within the SNS, based on

norms, values, or expectations of involved actors. For example, privacy and security

features, or the implementation of group features, fall into this category. This still

involves actors who perform a task, enabling technology, but social structure is central

to this perspective.

The resource integration model provides a genuine theoretical frame and potentially a

useful vocabulary to address our research objective. It should be noted, however, that

the objective was not to establish and deductively test a theoretical framework, but to

enhance our theoretical understanding, and to sensitize our data collection and

subsequent analysis.

IV.3 Methodology

IV.3.1 Research design

The objective of this research is to develop an empirically based understanding of

resource integration, and to explore how resource integration of SNS consumer and

provider is linked to the generation of service innovations. To this end, we adopted a S-


D logic perspective for studying resource integration and service innovation in the case

of Facebook.

We performed case study research (George and Bennett 2005; Gerring 2017; Klein and

Myers 1999) that involved the collection and analysis of qualitative data covering the

period from Facebook’s inception in 2004 until 2017. Based on multiple data sources,

we adopted Corbin and Strauss' (2014) approach for qualitative data analysis to

concretize consumer and provider resources, and to make sense of their resource

integration activities. Following a process of gradual generalization we establish three

service innovation mechanisms that rely on resource integration of consumer and

provider.

On the basis of the resource integration model, we view novel SNS features, i.e.,

interfacing operand resources, as the natural starting point of our case analysis. Viewing

SNS features as novel resources that result from resource integration has three

advantages for our study: First, features are visible and systematically identifiable. A

social networking page, for example, can be broken down into individual features, e.g.,

a profile picture, name and status information, personal posts, etc. This is a particularly

useful characteristic, because it directs our attention on consumers’ interaction with the

SNS (Aral et al. 2013, p. 5), and it allows us to evaluate the integrated consumer

resources involved in the feature. Second, features are functionally identical across the

consumer base. Although individual consumers use different subsets of features, the

basic functionality of a feature is stable between consumers. Finally, much of the

published information on service innovation in SNS reports on new features, how they

were intended by the provider, and how they were perceived by consumers. This helps

to identify the resources and resource integration activites of the provider involved in

the feature.

IV.3.2 Case selection

With the selection of Facebook as the single case of our empricial investigation we

follow an extreme case selection strategy. This strategy is useful for theory building,

because extreme cases are information rich and represent a paradigmatic manifestation

of the phenomenon of interest (Gerring 2017). Facebook is suitable for this type of

theorizing for three main reasons. First, Facebook exhibits an extreme case of ever-

present resource integration of an SNS provider and the involved consumers. In fact,

without consumers’ application of services and resources, Facebook would effectively

not produce any value. Second, Facebook has an exceptionally successful history of


generating service innovations, which documents how the social network transitioned

from a simple website intended to connect college students, to the world’s largest SNS.

Today, Facebook consists of numerous, well-crafted features that are used by billions

of consumers every day. Third, the selection of Facebook was favored due to the rich

information that can be obtained about the case context. Facebook receives extensive

media coverage and releases information on new and existing features frequently. The

amount of publicly available information is well-suited to triangulate data sources and

to reflect the perspectives of different actors. Furthermore, sufficient historical data is

available to study the case over time, thereby making this detailed study possible.

IV.3.3 Data collection and analysis

In this study, three researchers engaged in collecting data from multiple sources, thereby

ensuring consistency of the process and limiting the risk of bias. While most data was

obtained from secondary sources, we collected first hand insights from studying and

analyzing Facebook’s website. This provided us with the opportunity to continuously

validate our understanding of Facebook’s overall structure and features in its real-world

setting. This approach was particularly useful for linking insights about Facebook’s

features and its development directly to the interfacing operand resource, which is the

locus where consumer and provider engage in resource integration.

It should be noted, that we performed data collection and analysis in the sense of a

hermeneutic process that involved going back and forth between sensemaking by the

researchers and the subsequent, iterative gathering of data (Klein and Myers 1999). This

data collection process allowed us to build a rich historical database of features and

events through which we could assess the case context, and resource integration

processes that laid the ground for generating service innovations. This contextualization

was an important step in the interpretation of collected data (Klein and Myers 1999).

Our research was informed by five data sources. The data sources included (1)

Facebook’s press releases and announcements; (2) Facebook’s communication to

investors and external developers; (3) an extensive engagement and review of the SNS

by the researchers; (4) online articles; and (5) several filings of the US Federal Trade

Commission.

First, we reviewed press releases and announcements that were published in the

“Facebook Newsroom” between February 2004 and April 2017 (Facebook 2007). This

source is directed at consumers and the general public. Besides publishing company

information and statistics, it provides extensive coverage of service-related news and


events, and Facebook in general. For example, the “Products” page explains key features

such as profile, newsfeed, photo and video. Another source for our study was

Facebook’s “History” page which documents the implementation of new features with

a detailed description in chronological order. One important objective of collecting this

extensive amount of data was to elaborate a chronology of service innovations that

served as backbone for further data collection and to structure our analysis.

Second, we collected documentation that Facebook provides to investors and third-

party developers. For example, annual and quarterly reports document financial metrics

and give insights about Facebook’s current and future service strategy. We also collected

data from the “Facebook Developer Blog”, presentations of Facebook’s annual

developer conference “F8”, as well as developer policies, guidelines, and tools

documentation. Our objective was to attain a comprehensive understanding of the case

context, and to thoroughly document how Facebook approaches the development of new

features. For example, we found several video presentations in which Facebook

representatives explain the design process for new features, how Facebook approaches

new technologies, e.g., photo and video (Facebook 2017b), and how features like the

newsfeed and reactions have been developed (Facebook 2017c, 2017d).

Third, we collected data by engaging with Facebook’s social networking service. We

used an existing consumer account to review how consumers can use specific features.

For example, activities such as publishing a profile picture, or posting messages and

photos on a profile, and interacting with the newsfeed through reading, liking, reporting

or sharing are activities that are frequently performed by consumers. Our goal was to

document how the service and its most essential features function from a consumer

perspective. We also collected information from service descriptions and help sections

that explain how features work. By carefully studying the interfacing operand resources

through which consumer and provider interact, we enhanced our understanding about

what resources consumers are expected to integrate.

Fourth, we collected over 130 online articles from respected news outlets, including The

Economist, Wall Street Journal, Forbes; major technology news websites, e.g.,

TechCrunch.com, Hacker News, Wired, Crunchbase, as well as other blogs and

websites. These articles further contributed to a comprehensive understanding of the

case context and were particularly useful to provide different interpretations of key

events and features. This data supported us in identifying features that consumers

strongly resonate with. For example, consumers spend most of their time on Facebook

with photo and video functionality and newsfeed interactions. Similarly, many articles


discussed privacy and security related questions, and have frequently criticized

Facebook for their use of consumer data. A strength of this data source was access to

experts. While Facebook does not publicly explain many details of how their most

important algorithms work, several technology outlets had the chance to speak with

Facebook employees and subject matter experts to obtain insights that otherwise would

have been impossible to gather. For example, TechCrunch regularly updates a report

that provides detailed insights about how the newsfeed algorithm works, e.g., which

parameters are incorporated to calculate the personal relevance of news stories for

consumers (TechCrunch 2016). The supporting data has been collected during

interviews with Facebook employees and was a valuable source for our interpretation of

specific, highly relevant features.

Lastly, we collected several complaints against Facebook that were filed by the US

Federal Trade Commission. This data sensitized us for the importance of privacy and

security in the context of Facebook. The publication and utilization of consumers’

personal data proved to be highly relevant for generating service innovations that

changed how social interactions were governed.

The combination of these data sources, including our in-depth engagement with

Facebook’s social networking features allowed us to gain a comprehensive

understanding of the case. We continued with data collection until we could

comprehensively describe the SNS. Another criterion for ending data collection was

when collected data consistently repeated.

We adopted Corbin and Strauss' (2014) approach for qualitative data analysis to study

the collected materials. This method provides a systematic approach to analyzing the

comprehensive, interesting, and historical data existing on the Facebook case. The

analysis followed a four-step process (cf. Table 14) which involved the identification

and typification of service innovations, consumer and provider resources and their

integration, as well as theorizing on service innovation mechanisms that are then used

to explain service innovation in the case context.

Table 14. Data analysis

Steps Tasks Output

1. Identify service innovations in case context

(a) Extract data from the five data sources

(b) Identify service innovations (new features, changes and events related to Newsfeed)

Research database

In-depth understanding of

case context


Steps Tasks Output

(c) Create timeline of service innovations for each socio-technical perspective

Three chronologies (Appendix 1)

2. Identify involved resources and generate resource integration narratives

(a) Open and axial coding of resources using key constructs

(b) Generate narratives of resource integration to explain service innovation by using typologies of resources

Typologies of resources

(Appendix 2)

Coded instances of resource integration processes

3. Identify service innovation mechanisms

(a) Theorize on mechanisms based on axial coding of narratives

(b) Corroborate findings with case evidence and resource integration model

Three mechanisms, including visualized process models, and explanation of causal structure

4. Use mechanisms to explain service innovation in case context

(a) Use chronologies of service innovations and case evidence to sensitize mechanisms in their historical context

(b) Explain service innovations in the case context

Case findings and

presentation of mechanisms

In the first step, the objective was to identify service innovations and to develop an in-

depth understanding of the case context. As a result of an extensive analysis, we were

able to identify new, or altered features and time-stamped 142 associated events between

2014 to 2017. On this basis, we analyzed Facebook’s website to understand how

individual features work, and to generate an initial understanding of how features are

related with each other. For example, the like button is presented below every photo,

video, and comment displayed to consumers. It was important for us to understand how

features affected other features, e.g., how clicking the like button influences the

information that is displayed in the newsfeed of another consumer. We also analyzed

online articles and statistics about consumers’ use of Facebook to identify the most

popular consumer activities, i.e., clicking the like button, watching videos, and reading

news articles, and to identify consumers main reasons to use Facebook, e.g., staying in

touch with what friends are doing, staying up to date with news and current events, and

sharing photos and videos with others (Statista 2016). These activities provided a

comprehensive understanding of the case context.

At this stage, we narrowed the analysis to the newsfeed and its closely associated

features. The newsfeed is located on a consumer’s homepage and displays information

and news (e.g., photos, videos and news stories) that other consumers have shared.

Consumers, in turn, can use associated features, e.g., the Like button, reactions, or filters

to interact with and configure the content they want to see. Figure 9 illustrates exemplary


features that are related with the Newsfeed. For example, the publisher, a feature at the

top of the newsfeed, enables consumers to post photos and videos, or 360° videos. Other

features relate to privacy and security, and include the configuration of sharing and

visibility settings of personal content in the newsfeed of other consumers.

This reduction was not done arbitrarily. Instead, it emerged from an iterative process of

data analysis and sensemaking. Multiple criteria were considered to warrant an

investigation of the most important service innovations and their underlying resource

integration processes. One argument was the proportion of time that consumers’ spent

using certain features within Facebook. We aimed to include features that consumers

use the most and that could confidently be regarded as highly relevant. Another

important aspect was the availability of rich data from a variety of sources that would

allow us to carefully and systematically analyze the innovation of new features in a

coherent way. We also paid attention that the development of examined features had a

sufficient history, so that they could be studied in relation to other features. Lastly, we

aimed for an operational definition of aspects relevant to the question at hand. That is,

we structured our analysis and materials so that we could capture the resources,

activities, and causal structures that generated service innovations in the case context.

This step reduced our list of features and change events to 51, which we identified to be

the most relevant service innovations in Facebook’s history.

Figure 9. Newsfeed and exemplary features

We then categorized each service innovation according to the perspectives derived from

the S-T framework. That is, we categorized the identified 51 features and events as (1)


task-centered service innovation (22 entries, mostly relevant to the personalization of

news and information), (2) technology-centered service innovation (15 entries, mostly

relevant to photo and video features), or (3) structure-centered service innovation (14

entries, mostly relevant to privacy and security). The application of the S-T framework

increased our sensitivity to less obvious innovations, e.g., changing policies and

community standards, or introducing new privacy features. On this basis, we created

three chronologies that documented 51 service innovations related to Facebook’s

Newsfeed. Each entry in the chronology provides a brief description of the event, and it

indicates the involved feature(s) for each entry (cf. Appendix 1).

In the second step, we identified consumer and provider resources through open and

axial coding. To this end, we used the constructs of the resource integration model to

identify, generate, and categorize concepts from open coding (Corbin and Strauss 2014).

Specifically, we focused on depicting the operant and interfacing operand resources of

consumer and provider that were involved in each service innovation. The feature, i.e.

an interfacing operand resource, and the information about its generation by the provider

was the starting point for the coding process. For example, Facebook employed its

knowledge and skills (operant resources) to develop the like button (operand resource).

Consumers, on the other hand, employed their knowledge about personal preferences

and operational skills (operant resources) to click the like button, thereby generating

preferential data (operand resource) that is made available to the provider. Table 15

illustrates the initial coding of the like button.

We then performed axial coding to abstract the resources involved in each service

innovation. That is, we generated a typology of resources involved task-centered,

technology-centered, and structure-centered service innovation (cf. Appendix 2). This

was an important step in the case analysis, as it provided an empirically grounded

understanding and vocabulary of the resources that were integrated Three researchers

were involved in the coding. To ensure trustworthiness and reliability of this process,

we performed four iterations of open and axial coding. We also maintained a list of

disputes that was jointly reviewed and used to clarify our understanding of the involved

resources. The final step, i.e., the selective coding of resources has been performed by

two researchers who coded each service innovation independently. The research team

was confident to proceed with the further analysis after following this systematic

approach.


Table 15. Coding of involved resources on feature level

Facebook’s resource integration Consumer’s resource integration

Operant resources Interfacing

operand resourcesOperant resources Interfacing

operand resources

Textual description of involved resources (from memo on Like Button feature)

Facebook employs knowledge and skills to develop and implement Like Button (new feature)

New feature: Like Button) through which preferences are expressed

Consumer employs knowledge and skills to use Like Button as an expression of his preferences

Preferential data from clicking the like button

Initial set of codes

Skill to develop novel feature

Novel feature to perform activity

Knowledge of own preferences

Operational knowledge for using novel feature

Preferential data

Next, we created narratives to explain the resource integration process that generated

each service innovation. Specifically, we used the three resource typologies and the

sequential process logic depicted in the model to generate a narrative of the resource

integration process that underlaid each service innovation. In total, we generated 51

narratives which we corroborated and enriched with the materials collected.

In the third step of the analysis, we traced three service innovation mechanisms, which

we define as causal structures by which actors generate service innovations through

resource integration. Specifically, we aimed to uncover how Facebook, as the provider,

and its consumers integrated their resources to generate service innovations. This step

of the analysis followed the principle of axial coding (Corbin and Strauss 2014). We

aggregated the identified resources and resource integration activities to further abstract

the concepts emergent to our analysis. At this stage, we were particularly attentive to

view resource integration processes in their entirety, that is, we focused on the interplay

of consumer and provider resource integration to uncover the recursive patterns that

generated service innovations in the case context. To this end, we scrutinized the 51

resource integration narratives in view of the case evidence and related theoretical work

as suggested in the resource integration model. For example, we drew on video

presentations and developer keynotes recorded by Facebook to further understand how

specific service innovations have been generated (cf. “How we shipped reactions”

(Facebook 2017c), or “What’s new with the newsfeed?” (Facebook 2017d)). We also

drew on multiple sources to sensitize the role of consumers’ in generating service

innovations. This was useful to reflect on how consumers’ activities and resources have


triggered and enabled the generation of service innovations. This iterative process of

emerging sensemaking and analyzing the case evidence surfaced that Facebook’s ability

to generate service innovations depended on consumers’ use of the social networking

service, its constitutive features, and their contribution of feedback and personal

technology. Through this systematic process of gradual generalization we traced three

service innovation mechanisms which we termed data-driven innovation, technology

propulsion, and social debugging. Each mechanism includes a visualization, a

definition, and it explains a distinct causal structure by which different types of service

innovations have been generated.

In the final step of the analysis, we sought to examine how the three theorized

mechanisms can explain the generation of service innovations. We built on the findings

from the previous stages, in particular the three chronologies of service innovations and

the case evidence to sensitize the three mechanisms in their timely context to explain

the case findings. The three mechanisms have in common that they are generative of

service innovations. Due to the differentiation offered by the S-T framework, they differ

in their focus. Each mechanism points to distinct activities, resources, and service

innovations. In the following section, we first present the case overview, and then

illustrate for each mechanism its empirical context, followed by the presentation of the

respective service innovation mechanism.

IV.4 Facebook case findings

Since its inception in 2004 Facebook has increased the number of active consumers from

a few hundred to over 2 billion in 2017. With an employee-to-consumer ratio of

approximately 1 to 100.000 and a market capitalization of over $500 billion US-Dollars

(Wall Street Journal 2018), Facebook has become one of the worlds most valuable

companies (The Economist 2016b). Facebook generates 97 percent of its revenues from

displaying social advertisements (Facebook 2017a) and it has increased the average

annual revenue per US consumer from below $10 Dollars in 2010 to over $40 Dollars

in 2016 (The Economist 2016a). Globally, consumers spent an average time of 20

minutes per day, and in the United states, 40 minutes per day, on Facebook. Facebook

confirmed in 2016, that consumers watched 100 million hours of video every day, and

that 1 billion users are members of at least one group on Facebook. The event feature

was used by 500 million consumers who created 123 million events in 2015. Such

figures demonstrate consumers’ massive engagment in the service and also the

importance of continuously innovating new features.


Facebook’s provisioning and consumers use of social networking features represents

processes and activities in which both actors employ their resources to produce an

outcome. Facebook, for example, draws on its competence to design and implement

novel features, as well as technology resources, such as databases, servers, and its

knowledge to shape the inherent social structure, that is the values, norms, and behaviors

that regulate interactions. Consumers, on the other hand, employ a variety of resources

which include, for example, the ability to operate and configure the SNS according to

personal preferences, the knowledge and skills to generate, consume, and interact with

feautures, e.g., news, photos and videos that they like, share, block, or comment on.

Consumers provide, configure and operate personal technology infrastructures that

evolve and consist of personal computers, smartphones, and related applications. When

using the service, consumers enact and shape the social structures that enables and

constrain the digitally mediated interactions within the social network.

For example, Facebook invented a feature called minifeed in 2004, which it developed

into the newsfeed in 2006. Initially, the newsfeed displayed news about a consumer’s

personal social network. Over time, and enabled through vast amounts of accumulated

data and knowledge about consumers’ preferences, Facebook transformed the newsfeed

into a highly personalized, rich stream of information that is fed from multiple data

sources and that consumers can customize and interact with to tailor the SNS to their

individual preferences. It is through mutual and reciprocal application of service and the

exchange of resources that characterizes the very nature of resource integration in the

newsfeed and its related features.

Our analysis of the Newsfeed focused on how Facebook generated service innovations

from resource integration with consumers. The chronological analysis was structured

along three socio-technical perspectives on service innovation. This surfaced three

mechanisms (data-driven innovation, technology propulsion, and social debugging) that

explain how Facebook generated service innovations based on the processing of data,

the utilization of consumer technology, and from analyzing the normative and

behavioral expectations of consumers.

IV.5 Task-centered service innovation

IV.5.1 Personalized news and information on Facebook

Early on, Facebook recognized that consumers were mostly interested in presenting a

personal profile, and to share and read news of their personal social network. Thus, the


objective of Facebook’s innovation efforts was to gear the the service, and in particular

the newsfeed, towards the interests and preferences of each individual consumer. This

was particularly achieved by implementing novel features that generated and utilized

data from consumers’ interactions as resources, and that enabled Facebook to

personalize news and features accordingly.

When Facebook introduced the minifeed in 2004, and two years later the newsfeed,

Facebook took its first step to implement a central feature that personalized the

information displayed to each individual. Thirteen years later, in 2017, the Newsfeed

consisted of a highly modular section on the Facebook website that showed a rich,

personalized feed of stories, posts, pictures and videos. Following years of evolutionary

development, the presentation of news was then determined by an algorithm that drew

on more than 100,000 data parameters to calculate the relevance of each news element

for evey individual consumer.

In 2008, Facebook implemented the publisher, a feature that consumers could draw on

to publish comments, photos, and videos. The publisher, and other changes, which

fostered the generation of user generated content, increased the amount of data resources

that were re-bundled to personalize the newsfeed, and to innovate new features. When

Facebook introduced the like button, subscriptions, and reactions, for example, it

provided novel opportunties for consumers to express themselves, and to interact with

digital content. In turn, the use of these features generated rich, preferential data that

enabled Facebook to step-wise improve the personalization of the newsfeed.

The like button, which was implemented in 2009, enabled consumers to interact with

content that has been published by others. After a consumer “liked” a specific news

element, it was indicated in the Newsfeeds of this consumer’s friends. The like button

was a simple, yet effective feature that stimulated consumers’ interactions with digital

content, and it allowed Facebook to draw on data for tracing and predicting the relevance

of specific content for each consumer. The subscribe button, which was implemented in

2011, allowed consumers to follow profile changes and news updates of other persons,

even without becoming friends on the social network. Once consumers have expressed

their interest by subscribing, Facebook’s personalization algorithm would present future

updates and news in the Newsfeed of the subscriber.

The data that resulted from consumers’ likes and subscriptions, enabled Facebook to

innovate two entirely new personalized features. The Newsticker, introduced in 2011,

displayed real-time information about friends’ social networking activities on a side bar


of the Facebook website. This feature was data-driven and personalized, as it utilized

data from likes and subscriptions that was generated during interactions within a

consumer’s personal social network. Similarly, like and subscription data laid the

ground for the data-driven personalization of profile sections, which was implemented

in 2013. Facebook enhanced the modular structure of the profile page and implemented

a new personalization algorithm to generate individualized profile sections based on the

likes and subscriptions of each individual.

For several years, after implementing the Like button, consumers demanded more fine-

grained and simple functionalities to express themselves. Following a global research

initiative that included focus groups, surveys, and experiments, Facebook invented the

reactions feature in 2016. Reactions enhanced the like button and enabled consumers to

interact with content by selecting emoticons that express “Like”, “Love”, “Haha”,

“Wow”, “Sad”, and “Angry”.

Facebook did not only use consumer-generated data to innovate novel features such as

the newsticker and personalized profile sections. Such data was also extensively used to

trace consumer preferences, and to improve personalization of the Newsfeed. In fact,

the majority of change events in the newsfeed history included refining its

personalization algorithm: In 2006, the newsfeed algorithm ingested consumer data

from personal profiles and presented this data in the Newsfeed of other consumers

(2006). Due to consumers’ active use of the like Button (2009) and subscriptions (2011),

and the subsequent availability of consumer-generated content and preferential data,

Facebook was able to change its algorithm in 2011 to display news not in reverse-

chronological order, but according to their popularity within the social network. In a

series of change events between 2013 and 2017, Facebook tweaked the newsfeed

algorithm to prioritize consumers’ recent interactions (2013), to account for consumer-

driven prioritization of news, e.g., through filtering and reporting mechanisms (2015),

as well as to reduce promotional content (2014), “click-baits” (2014), and “false news”

(2015). Following the implementation of reactions in 2016, and together with this, the

generation of more differentiating usage data, Facebook altered the newsfeed algorithm

to rank presented news stories according to their “engagement probability” (in 2016),

and to weigh reactions higher than likes (in 2017).

These service innovations were not independent one-time change events. Instead, they

followed an evolutionary, re-inforcing pattern that was rooted in consumers’ generation

and sharing of data and, conversely, on Facebook’s ability to utilize this data for


personalizing displayed news and features. Then again, this personalization spurred

generation of more data by consumers.

IV.5.2 The data-driven innovation mechanism

Our data analysis surfaced Facebook’s ability to generate innovations based on the

processing of data, which was used to progress personalization. The backbone of such

innovation was the variety and vast amounts of consumer-generated usage data, and the

ability to analyze and process this data. This mechanism was used to produce entirely

new, and to improve already existing personalized features. We refer to this mechanism

as data-driven innovation. It depicts the resource integration process by which the

provider generates service innovations from collecting, analyzing, processing and

algorithmically re-combining data resources generated by consumers to produce

personalized features.

This mechanism addressed Facebook’s never-ending challenge of providing personally

relevant information to every individual consumer. It was used to expand the set of

offered features, to attract new consumers, and to innovate possible service experiences.

Data-driven service innovation results from resource integration performed by the

provider (labelled service personalization) and the consumer (labelled interaction and

self-expression), and it involves usage data and personalized features as interfacing

operand resources, through which these interactions manifest (cf. Figure 10).

Service personalization refers to resource integration in which the provider draws on

usage data that is generated by consumers’ interactions and it involves at least three

types of data-driven activities.


Figure 10. Data-driven innovation mechanism

First, generation of data-driven personalized features. These features provide modular

structures and facilitate the dynamic recombination and presentation of data resources.

Facebook’s core elements, i.e., the homepage, including the newsfeed, and personal

profile page, consist of modular structures that enable the recombination of data

resources that are displayed to consumers. These features are not only data-driven

because of their data use; the interactions they enable also drive data generation. For

example, features for reading news, sharing and evaluating content, or connecting with

other consumers, are all designed to generate new and diverse types of data. They secure

an ongoing accumulation of usage data, thereby spurring further innovation

opportunities.

Second, the generation of personalization algorithms provides a programmed logic and

data-driven approach to recombine data resources. Personalization algorithms automate

resource bundling activities for the provider as they craft information bundles optimized

for personal relevancy. The application of personalization algorithms within Facebook

was regularly refined and expanded. Refinement aimed to increase the relevance of

displayed data at the individual consumer level. For example, Facebook, performed

changes to the newsfeed algorithm to improve the logic according to which data

resources are bundled and presented. Such refinements drew on data that represented

consumer preferences as parameters of the personalization logic. This data was

generated either explicitly, e.g., through consumers’ interactions with features (e.g.,

liking or subscribing), or implicitly, by inferring from log data of networking

interactions or consumed media content (e.g., intractions with friends or watched

videos). Another source of data parameters resulted from analysis of collective levels,

e.g., consumers from a specific country, language, or within a consumers’ personal

social network. Expansion of personalization refers to an increase of the scope and

application areas of personalization. Facebook has increased the amount of personalized

features, e.g, the Newsticker and Personalized profile sections, and it has expanded the

amount and variety of usage data that was drawn upon to personalize the service.

Third, data-driven management of service innovation refers to knowledge building and

decision making in the development and implementation of new personalized features.

This iterative process involved data-driven activities that are particularly employed for

sourcing innovation opportunities, and for testing consumers’ acceptance of new

personalized featues. Facebook’s data-driven management of service innovations

typically involved multiple prototypical implementations and extensive data-collection


and analysis to inform the final design of novel features. For example, Facebook

employed various research methods, e.g., user-experiments, A/B-testing, and analysis

of usage data to validate assumptions over adoption and use of service innovations. The

reported methods were broadly applied to Facebook’s site structure, its elements, as well

as individual features. This data-driven approach did not necessarily involve consumers

to consciously giving feedback. Feedback was often inferred from large amounts of data

that resulted from consumers’ configuration and log data, which were produced while

using the social networking service. In addition, dedicated instruments, e.g., surveys and

feedback forms, were employed to explicitly collect consumer feedback, and to steer

service innovation efforts. In one instance, for example, Facebook reduced the amount

of promotional content that was displayed in the newsfeed due to results from consumer

surveys. These data-driven activities generated personalized features that enabled new

interactions for consumers.

Interaction and self-expression refers to activities in which consumers draw on

personalized features to express themselves. These interactions produced extensive

volumes and varieties of usage data which were integral for data-driven innovation and

involve at least two activities.

First, consumers’ employ their cognitive, creative and operational skills to generate and

publish content, and to interact with content generated by other consumers. For

example, consumers draw on the publisher to generate content, or interact with content

displayed in the newsfeed through likes, subscriptions, or reactions.

Second, Interaction and self-expression involves activities in which consumers

articulate their personal needs and preferences through surveys, feedback instruments,

and by configuring the SNS. Such configuration activities, for example, adapt the layout,

site structure, or displayed features to the personal preferences of an individual.

Consumers can take on an active/conscious, or a passive/unconscious role in providing

preferential and feedback data. When consumers chose to join a beta-test group,

participate in a survey, or to use an alternative experimental homepage, for example,

they took on an active role in which they actively and consciously applied their

competences to articulate how new features should be designed. Consumers who remain

passive, and who do not volunteer to provide feedback, do still generate preferential data

that is derived from indicators such as frequency of use, or (non-)adoption of specific

features.


Inherent to consumers’ activities is the continuous production and accumulation of

usage data, that can be drawn on to enhance service personalization. In the case analysis,

five types of usage data were identified. First, feedback data that was collected through

experiments, tests, or surveys. Second, personal data that described and represented a

consumers’ virtual identity and personal social network, e.g., name, profile picture, job

information, or list of friends. User generated content referred to data that consumers

created, shared, and distributed within their personal social network, e.g., photos,

videos, or comments. Configuration data was actively created by defining privacy and

securtiy settings, customizing SNS features, or by explicating personal interests and

preferences through filters, ratings, or similar features. Log data was generated from

consumers’ feature use and collected by the provider. Log data included, for example,

timestamps of consumer actions (e.g., recently uploaded or viewed content). This

classification of usage data is not exhaustive; instead, it represents an empirically-

grounded vignette that indicates the variety and richness of data that providers can draw

upon to spur service personalization and data-driven innovation.

IV.6 Technology-centered service innovation

IV.6.1 Photo and video features an Facebook

In its short, but successful history, Facebook leveraged consumers’ adoption of

technology to generate service innovations. Many of these innovations generated new

photo and video features that relied on consumers’ personal computers, mobile phones,

digital cameras, and associated software. New photo and video features were important

to support Facebook’s strategy of growth and innovation. These innovations increased

the range of possible service experiences, prolonged consumers’service use, and, most

importantly, they ensured ongoing generation of data and interesting content that was

presented in the Newsfeed.

At the launch of Facebook in 2004, consumers could upload a profile picture to their

personal page. Seeing the profile picture of a friend defined the “magic moment” at

which consumers started to bond with the SNS, as stated by Alex Schultz, Facebook’s

Vice President of Growth. Since then, photo and video features have been a key area of

innovation for Facebook and the consumption of photos and videos ranges amonst the

most popular and frequent social networking activities of consumers.

As part of its expansion, Facebook launched two basic features, photos in 2005, and

videos in 2007, which enabled consumers to share photos and videos, and to tag friends


within their social network. These features were primarily enabled because consumers

aquired digital cameras and camera-equipped mobile devices that increasingly pervaded

everyday life. It was exactly around this time when Apple introduced the iPhone, and

other technology companies started to offer more advanced smartphones, when a

Facebook engineer, who was responsible for developing the video feature, stated in a

company announcement:

„Now that consumer mobile phones and digital cameras are perfectly capable of

taking good quality video, we knew that it was time to build a video application

[…]” (Facebook 2007).

Facebook became increasingly alert to spot innovation opportunities that relied on

consumers’ technology resources, since consumers adopted more advanced technology,

e.g., smartphones, faster internet connectivity, and personal computers with built-in

webcams. Consumers, however, operated their technology indepentently of Facebook.

It was therefore important for Facebook to ensure that consumers could easily employ

their technology for using new photo and video features.

The implementation of the video calling feature in 2011, for example, required

consumers to operate a video camera, and to install a software-plugin to their internet

browser. The installation was a technical prerequisite for connecting consumers’

personal computers to the networking infrastructure that enabled video calling.

Facebook created different installation routines, one for each operating system and

browser combination, to accommodate for different consumer technology

configurations, and to minimize consumers’ configuration efforts. The design of the

video calling interface also promoted consumers use of video technology. It indicated

the message: “Try restarting your browser if you’re having trouble with your camera or

microphone”, and a “Help” button, that led to a step-by-step guide, on how to use

consumer devices for making video calls.

The introduction of 360° videos in 2015, and 360° photos in 2016, were milestones in

the development of photo and video functionality. Both features built on considerably

advanced technology, in particular motions sensors, that were built into the newest

mobile devices and virtual reality (VR) headsets. The production of 360° videos relied

on a set of specifically arranged cameras which recorded all 360 degrees of a scene

simultaneously. Similiarly, 360° pictures could be taken with smartphones that

possessed motion sensors. Consumers could use their mobile phones or virtual reality


(VR) headsets to view these materials and to dynamically choose the angle of a scene

by turning the device into the desired direction.

These features relied on consumers adoption of VR technology and smartphones, as well

as consumers ability to employ their devices for generating and watching 360° photos

and videos. Accordingly, Facebook aimed to facilitate consumers’ use of personal

technology for these purposes. In nearly all instances the presentations and

announcements of new features by Facebook’s included information about technology

requirements, and instructions about how to setup and configure consumer devices.

Facebook published screenshots, demonstration videos and textual descriptions to

promote knowledge that consumers required to employ their technology. Key

information included compatible (or required) internet browsers, operating systems, and

schedules according to which new features were made available on different operating

systems. In addition, announcements of new features that involved advanced consumer

technology, e.g., 360° Photo and Video, was very detailed and included illustrative

content. For example, the presentation of 360° Video included a basic description of a

360° camera system, a demonstration video of the feature itself, and a description of

how such videos are watched with different consumer technology configurations.

Facebook also generated service innovations from recombining existing resources,

including consumer technology and related competences. The features high-quality

pictures (2012), animated pictures (GIF) (2015), collages (2015), profile and intro video

(2015) represented innovations that leveraged consumer’s cameras and even more their

existing competence to upload and share pictures and videos on Facebook. These

innovations were modest enhancements and recombinations of existing features that

consumers were familiar with. Facebook’s announcements of these innovations often

included screenshots or brief videos to explain how these new technology-enabled

features were intended to be used.

Technology-enabled service innovations were driven by consumers’ adoption of new

photo and video technology, and their ability to integrate new technology resources.

Facebook, on the other hand, harnessed advancements in consumer technology by

innovating new features that relied on consumers’ ability to integrate their technology

successfully.

IV.6.2 The technology propulsion mechanism

The case analysis revealed how Facebook utilized advancements in consumer

technology to generate service innovations. The driver of these technology-centered


service innovations was the availability of new consumer technologies, in particular

mobile phones, that have been widely adopted by consumers and that rapidly pervaded

consumers’ everyday life. Facebook repeatedly leveraged consumers’ adoption of such

technologies to propel service innovations, that is innovating new and altering existing

features. We refer to this mechanism as technology propulsion. It depicts the resource

integration process by the provider generates service innovations from promoting new

technologies that are adopted by consumers. This mechanism produces technology-

enabled features which are based on novel consumer technology configurations.

The technology propulsion mechanism enabled Facebook to harness the rapid

advancements and pervasiveness of consumer technologies and, vice versa, it enhanced

consumers’ utilization of technology resources. This is particularly important, because

functioning consumer technology resources, are, to large degrees, not controlled by the

provider. Their utilization, however, is a prerequisite for innovations that depend on

consumers’ ability to configure and operate their technology resources. Technology

propulsion results from resource integration activities performed by the provider

(labelled technology promotion) and the consumer (labelled technology adoption), and

it involves consumer technology and technology-enabled features, as interfacing

operand resources (cf. Figure 11).

Figure 11. Technology propulsion mechanism

Technology promotion refers to resource integration activities in which the provider

draws on technology that is operated and configured by consumers to generate service

innovations. Technology promotion involves at least three types of activities:

First, identifying service innovation opportunities, that are enabled by new consumer

technologies. This includes monitoring of and learning about available consumer


technology, such as mobile technologies or virtual reality, and subsequently, the

development of strategies to utilize new technological affordances.

Second, innovating new technology-enabled features. This refers to the invention of new

features that utilize consumers’ technology resources, e.g., photo and video cameras in

mobile devices, (mobile) network connectivity, or internet browsers. Facebook, for

example, invented new photo and video features, video calling, 360° photo and video,

as well as live video broadcasting functionality on the basis of advancing consumer

technology.

Third, technology promotion includes the creation of features that facilitate consumers’

technology integration. These features were either integrated within new features, e.g.,

as in-product-education elements or tutorial videos, or they complemented new

technology-enabled features, e.g., in the form of help pages, product announcements, or

question and answer videos with software developers who explain new features. The

case evidence showed that Facebook simplified installation and configuration routines,

and enforced adherence to design guidelines, in order to promote consumers’

technology-related competence development. These activities produced new social

networking features, that were enabled by consumers’ adoption of new technology.

Technology adoption refers to activities by which the consumer employs personal

technology and draws on technology-enabled features for using new social networking

features. Technology adoption involves two consumer activities, i.e., technology

acquisition and technology integration.

First, consumers aquire new technology resources that become available due to

technological evolution. This includes, for example, advancements in mobile devices,

networking infrastructure, or software. Technology acquisition describes consumers’

general utilization of new technology resources and includes selecting, purchasing,

configuring, and operating these resources within a personal technology infrastructure.

This acquisition of technology might be partly influenced by a social networking

provider, but in general, it is controlled by the consumer.

Second, technology integration refers to activities by which the consumer develops

required competences and integrates personal technology resources to use new

technology-enabled features. In the case of Facebook, consumers’ technology

integration required the navigation and use of user interfaces and work flows, and to

understanding how new features function, e.g., through public announcements of new

features. As a result, consumers could effectively adopt personal technology and


integrate it in a way that produced functioning technology configurations, which

eventually enabled new SNS features.


IV.7 Structure-centered service innovation

IV.7.1 Privacy and security features on Facebook

On September 5th, 2006, when Facebook released the newsfeed, consumers instantly

protested against the automated publication of their activities and personal information

within the social network. Consumers created several groups on Facebook, one reached

a membership of over 280,000 within hours, to complain about the intrusiveness of the

newsfeed on their privacy. Mark Zuckerberg, the CEO of Facebook, responded

immediately with an announcement that was titled “Calm down. Breathe. We hear

you.”. Zuckerberg emphasized that Facebook understood consumers’ concerns and that

it appreciated the feedback provided. Three days after the incident, on Sepember 8th,

2006, Facebook announced more granular data privacy controls and an open letter from

Mark Zuckerberg was published in which he stated:

“We really messed this one up. When we launched News Feed […] we did a bad

job of explaining what the new features were and an even worse job of giving you

control of them. I'd like to try to correct those errors now.” […] Somehow we

missed this point […] and we didn't build in the proper privacy controls right

away. This was a big mistake on our part, and I'm sorry for it. But apologizing

isn't enough. I wanted to make sure we did something about it, and quickly.”

In December 2009, with a consumer base of 350 million, Facebook altered its Publisher

feature to let consumers control case-by-case were and to whom their content was

displayed. In addition to expanding its privacy settings, Facebook introduced the

transition tool, a feature that guided consumers through a review of their privacy

settings. Facebook presented the transition tool as an innovation in response to consumer

requests who have urged the company to implement simpler and more effective privacy

options. Despite the company’s positive portrayal, consumers and advocate groups

criticized Facebook harshly for promoting visibility of personal data to “Everyone” in

the configuration process, thereby hoping to nudge consumers into sharing personal data

more freely.

Only 5 Months later, in May 2010, Facebook once again announced a redesign of its

privacy settings. In the corresponding communication Facebook CEO Mark Zuckerberg

stated:


“Over the past few weeks, the number one thing we’ve heard is that many users

want a simpler way to control their information. Today we’re starting to roll out

changes that will make our controls simpler and easier.”

The announcement provided operational principles that defined how Facebook would

handle consumer data. These principles affirmed, for example, that consumers had

control over how their information is shared, and that no personal information was

shared without consumers’ consent. Facebook also layed out that it performed several

iterations of testing with consumers, and that it consolidated the privacy settings that

were needed to restrict the sharing of personal data.

In 2011, the US Federal Trade Commission (FTC) filed a complaint in which it alleged

Facebook of not having implemented effective privacy controls, and that consumers’

choice not to share personal data was undermined through deceptive practices. Shortly

after settling the charge with the FTC, Facebook’s CEO, Mark Zuckerberg, stated in an

announcement that his company was respecting consumers’ privacy and that he regarded

Facebook as “the leader in transparency and control around privacy” (Facebook 2011).

Between 2012 and 2015, Facebook responded to the privacy concerns of its consumers.

This was reflected in new and altered privacy features. In 2012, for example, Facebook

added shortcuts to untag consumers in photos, and installed in-product education and

in-context reminders to guide consumers’ behaviour in managing privacy settings.

Facebook also implemented a support dashboard to provide status information to

consumers who have reported violations to Facebook’s data policy or community

standards. In 2014, Facebook updated its data policy and terms of service to accomodate

for location based services (check-in and nearby friends), which track and publish a

consumer’s location. In the announcement, Facebook asked consumers to vote and

comment on these policy changes with the aim to build consumers’ trust into its SNS.


IV.7.2 The social debugging mechanism

The case analyis surfaced several disputes over how personal data was used and shared

within the social network. Such disputes often resulted from new features that

consumers perceived as privacy-violating. Consumers were less concerned with the

(technical) task that a new feature afforded, but protested severely about its social

implications and practices. Facebook did repeatedly demonstrate its ability to debug

underlying “defective” practices and created features that would alter or complement

other features to, at least some extent, meet consumers’ expectations. We refer to this

mechanism as social debugging. It depicts the resource integration process by which the

provider generates service innovations from shaping social structure to improve

compliance with the normative and behavioral expectations of consumers. This

mechanism produces structure-carrying features that govern social interactions, and it is

aimed to resolve malfunctions within these interactions.

Figure 12. Social debugging mechanism

Social debugging results from resource integration activities performed by the provider

(labelled shaping of social structure) and the consumer (labelled value and norm guided

behaviour). It manifests in value and norm exposing data, and structure-carrying

features as interfacing operand resources (cf. Figure 12).

Shaping of social structure refers to resource integration activities in which the provider

draws on data that exposes consumers’ values and norms. This process involves at least

two types of activities.

First, the monitoring and analysis of data that, explicitly or implicitly, exposes

consumers’ normative and behavioral expectations This data improved the provider’s

understanding of consumers normative and behavioral expectations and included, for


example, feedback data, public outcries in the media, or the formation of discussion

groups, which often triggered the innovation of new features.

Second, the provider generates structure-carrying features, which we termed according

to their characteristical properties, as governance instruments, value communication and

articulation instruments, and regulation and enforcement instruments. Governance

instruments include policies and guidelines that hold information about general

assumptions and beliefs, and they communicate expected roles and behavioral standards

of actors involved. Facebook, for example, installed a data policy that specifies its use

of consumer data and how third-parties can access such data. It also published

community standards and guidelines for sharing content to guide consumer behavior.

Value communication and articulation instruments include news, announcements, press

releases, and discussion forums. These features document how specifc interactions,

features, and workflows are envisioned to be used and often provide background

information about intended social interactions. However, such instruments facilitate not

only a one-directional communication to consumers, they also provide a venue for

exchanging structure-related feedback with consumers. Regulation and enforcement

instruments provide workflows, controls and tools that enable and constrain consumers’

behavior. These instruments include, for example, privacy and security settings (e.g.,

revealing or deceiving personal data), and related tools, e.g., tutorials, dashboards, or in-

product advice, as well as features to enforce certain behaviors, e.g., for reporting

inapproprate content or behavior. Facebook, for example, developed features that

enabled consumers to report, block, and flag content that they regarded as being

inappropriate, e.g., content that violated community standards, that was faked, or that

conflicted with personal values. The provider’s shaping of social structure manifests in

the identfied features which do not represent social structure as such. Structure is

enacted and constituted in practice. Accordingly, we contend these features to be

structure-carrying; they enable and constrain possible actions, and thereby, carry

normative and behavioral assumptions and beliefs.

Value and norm guided behavior refers to activities in which the consumer draws on

structure-carrying features to enact and communicate normative and behavioral

expectations. These activities are guided by consumers’ values and norms and generate

a digital trace that exposes values and norms to the provider. Such behavior resides in

consumer’s cognitive and operational abilities, and includes the ability to act upon

personal values and norms. The analysis revealed at least two activities that expose

consumers’ values and norms to the provider. First, consumers use of communication


instruments to articulate normative and behavioral expectations. This includes, for

example, the use of discussion groups, feedback, or messages that are directed at the

provider. Such communication is reflective of consumers’ worldview and exposes her

values and norms. Thus, it provides merely explicit and conscious indications of

conflicts over how social practices are enabled by new features. Second, consumers use

of features to regulate and enforce social practices. This includes consumers’

configuration of features and associated workflows to comply with personal values and

norms. It also involves the reporting of inacceptable practices, inappropriate content, or

violation of a shared code of conduct, as well as flagging or blocking of other entities.

In essence, consumers integrate their social structure-related resources through activities

that are guided by and reflective of their personal values and norms. In this process,

consumers generate value and norm exposing data, that is used by the provider for

shaping social structure.

IV.8 Discussion

In this paper, we adopted a S-D logic perspective to enhance our understanding of

service innovation in social networking services. In particular, it has highlighted the

importance of resource integration for generating service innovations. SNS providers

innovate most often for consumers, and hence, understanding the resource integration

of consumer and provider is of critical importance.

This paper proposes the resource integration model as a theoretical framework with

which to make sense of the underlying activities and reciprocal dynamics of resource

integration that are emphasized in S-D logic (Vargo and Lusch 2004, 2008). The model

distinguishes between operant and interfacing operand resources, and depicts two

resource integrating actors, i.e., provider and consumer. The model suggests that

resource integration of both actors is generative of service innovations in SNS. We argue

that the model is useful for explaining service innovations, because it provides a

coherent understanding for examining the resource integration of consumer and provider

on the premises of S-D logic.

We employed the resource integration model to analyze the historical development

process of Facebook’s Newsfeed. Our analysis uncovered three service innovation

mechanisms: data-driven innovation, technology propulsion, and social debugging.

Each mechanism provides insights about the resources and resource integration

dynamics of consumer and provider, and how these dynamics have been generative of


service innovations in the case context. These mechanisms suggest that service

innovation in SNS relies significantly on a provider’s ability to successfully engage,

facilitate, and leverage the resources and resource integration of its consumers.

Data-driven innovation depicts the mechanism by which a provider generates service

innovations from collecting, analyzing, processing and algorithmically re-combining

data resources generated by the consumer to produce personalized features. This

mechanism may be useful to comprehend consumers’ resource integration as a data

generating activity upon which new personalized services may be generated. It might

also be useful to analyze the degree to which (new) features, or more general, interfacing

operand resources, are driven by consumer data and also, wether they facilitate the

generation of novel data resources that spur further innovations.

Technology propulsion depicts the mechanism by which actors generate service

innovations from promoting and adopting new technologies. This mechanism produces

new technology-enabled features, which are based on consumer technology

configurations. It offers an explanation for how providers can harness advancements in

consumer technology to generate service innovations. It comprehends consumer

technology as resources upon which services can be innovated, and it might be useful to

appraise consumers’ abilities to utilize technology as a foundation of succesful

innovation. It might also be useful to study features that support consumers adoption of

technology for specific services, e.g., in-product education materials or learning

tutorials.

Social debugging depicts the mechanism by which a provider generates service

innovations from shaping social structure to improve compliance with the normative

and behavioral expectations of consumers. This mechanism produces structure-carrying

features that govern social interactions, and it is aimed to resolve malfunctions within

these interactions. This mechanism may be useful to study how tensions and conflicts

are addressed in digital services in the course of time. It might be particularly useful to

examine how features can be adapted to comply with consumers normative and

behavioral expectations. This also turned out to be an important measure to retain

consumers’ acceptance, trust, and to ensure continued use of SNS. The social debugging

mechanism offers an alternative, critical explanation that stands in contrast to the

favorable self-portrait that the provider in the case context drew about privacy and the

usage of data. While the social debugging mechanism does not suggest how to shape

social structure in SNS, it might be useful to sensitize for the social implications of

service innovations which are often subtle and difficult to assess.


The insights derived from the resource integration model and the three service

innovation mechanisms enhance previous research on service innovation in the digital

age (Barrett et al. 2015; Lusch and Nambisan 2015; Nambisan et al. 2017), and extant

research on SNS (Aral et al. 2013; Gnyawali et al. 2010; Singaraju et al. 2016).

First, it provides a theoretical account of how provider and consumer integrate their

resources in SNS. The model incorporates the key resources and activities defined in S-

D logic into a coherent model of resource integration. This is important to advance our

understanding of and theorizing about value cocreation and service innovation, which

are both based on the activities that underlie resource integration of different actors, and

that needed more theoretical and empirical foundation (Lusch and Nambisan 2015, p.

168). Our work also suggests to direct attention to SNS features and data, which we

conceptualized as interfacing operand resources. These resources mediate service

exchange and often represent the locus where innovations manifest. That is, they

represent novel resources that result from the rebundling of resources. Resource

integration, as depicted in the resource integration model, provides opportunities for

studying the resources and activities taken by consumer and provider in generating

service innovations. In this regard, our work complements research that studied the

resources and innovations generated by providers and third-party developers (Eaton et

al. 2015; Ghazawneh and Henfridsson 2013; Gnyawali et al. 2010), by explicitly

accounting for the consumer, who is often not only a beneficiary, but also a contibutor

of essential resources for service innovation.

Second, the model views resource integration as a generic process that allows studying

service innovation from a dynamic and emergent perspective. The case analysis has

demonstrated that reciprocity and relatedness are critical to understand how service

innovations are generated on the basis of repeated resource integration activities. These

dynamics are captured in the three identified mechanisms. Data-driven innovation relies

on consumers’ repeated generation of usage data and the ability of the provider to draw

on and process this data. Technology propulsion relies on consumers’ acquisition and

repeated ability to integrate technology, and the ability of the provider to promote and

harness advancements in consumer technology. Social debugging relies on value and

norm exposing data that is repeatedly generated by consumers, and the ability of the

provider to draw on such data to innovate the governance of social interactions. Our

research indicates that these interactions are reciprocal, dynamic and emergent over

time, and they represent the common denominator of the identified service innovation

mechanisms.


The resource integration model challenges extant contributions that model linear,

onetime processes in which actors apply their resources either in parallel (Lusch and

Nambisan 2015; Payne et al. 2008), or consecutively (Grönroos and Voima 2013) to

cocreate value. Although such linear visualizations are often employed for simplicity

(ibid, p. 136), and despite researchers’ emphasis on the relational nature of S-D logic

(Vargo and Lusch 2008), only recently value generating activities have been theorized

as a repeated process of resource integration (Vargo and Lusch 2016). The proposed

resource integration model provides an intellectual structure that brings together the

underlying activities of value cocreation and service innovation, as postulated by (Lusch

and Nambisan 2015). Consumers derive value from drawing on interfacing resources;

At the same time, they often generate new resources, e.g., usage data and technology

configurations, that serve as resources for service innovation. We argue that this

theoretically grounded, empirically-based conceptualization of resource integration

addresses the challenge of studying innovation in the digital world, which has been

identified as being increasingly less bound in terms of time and space (Nambisan et al.

2017).

Third, as demonstrated in our empirical analysis, the resource integration model can be

specialized for studying specific aspects of service innovation and resource integration.

The application of the S-T framework, for example, offered a novel vista on service

innovation and resource integration in SNS. For one thing, we could derive different

centers of gravity, which we termed task-centered, technology-centered, and structure-

centered service innovations. Secondly, we could enrich our coding of resources and

resource integration by extending the generic distinction of operand and operant

resources offered by S-D logic. As a result, each service innovation mechanism

specializes on a different center of gravity of service innovation. This facilitates a

refined and nuanced understanding of service innovation in SNS that was particularly

valuable for identifying and theorizing about how disputes over social structure where

attenuated through the social debugging mechanism. In this regard, we uncovered novel

aspects of service innovation and complement extant literature, which has employed a

variety of theories, e.g., complexity theory (Xiao and Wang 2014), task-technology fit,

long-tail concept, or resource-based view (Enders et al. 2008; Ketonen-Oksi et al. 2016)

to study SNS.

Finally, our work contributes to the ongoing research on digital innovation (Yoo et al.

2010; Yoo et al. 2012) and digital ecosystems (Henfridsson and Bygstad 2013; Reuver


et al. 2017; Tilson et al. 2010; Tiwana et al. 2010) by examining and specifying

resources that are essential for innovating digital services for and with consumers.

This research also holds implications for managers. We demonstrated that Facebook

leveraged consumer resources to generate service innovations through resource

integration. We hope that our work stimulates managers to think in more nuanced ways

about how to invent and design novel features by considering consumers’ social and

technical resources as sources for future service innovations. The dynamic and emergent

perspective offered in the three mechanisms underlines the importance to comprehend

innovation in consumer services as an incremental, continuous effort to improve and

adapt to the ever changing needs of consumers.

Future studies could address the limitations of our work. First, this paper focused on the

single case of Facebook, which exhibits the phenomenon of interest extremely. While

extreme cases are a fertile ground for theory-building, future research could study

service innovation in different empirical settings. We deem it plausible to find similar

dynamics and service innovation mechanisms in other types of consumer-centric

systems. Potential exemplary success cases for future research are personalized music

and video playlists (cf. Spotify, YouTube, Netflix), the promotion of consumer

hardware to innovate new services (cf. Amazon’s Alexa, or Virtual Reality devices), or

the implementation of anti-cheat functionality in video-gaming (cf. Steam gaming

platform). The study of failed digital consumer services, potentially beyond SNS, could

challenge the resource integration model, and the respective mechanisms. Such future

research would add further empiricial grounding to S-D logic, which is increasingly

becoming a narrative of resoure integration (Vargo and Lusch 2016). It would also

increase our knowledge about how firms generate service innovations by leveraging

consumer resources over time and potentially help to identify further service innovation

mechanisms. Second, our research focused exclusively on the resource integration of

consumer and provider. Consequently, it did not account for the resource integration of

other actors. Future research could apply, or extend, the resource integration model to

examine resource integration of other stakeholders, e.g., third-party developers. This

could employ extant research on boundary resources (Eaton et al. 2015; Ghazawneh and

Henfridsson 2013), and extend the scope of research to investigate the resources of third-

party developers, and the interfacing resources that are provided to consumers by third-

party developers (cf. Sarker et al. (2012) for case study in a B2B-ERP environment).

Finally, we acknowledge that there are implicit interactions between the three service

innovation mechanisms. For example, a novel virtual reality feature, i.e., a technology-


centered service innovation, might subsequently enable a task-centered service

innovation, e.g., displaying news on a virtual reality device. Studying these interactions

are beyond the scope of this article and would require further research.

IV.9 Conclusion

In this paper, we contribute a model that captures the dynamic interactions by which

consumer and provider generate service innovations in social networking services. The

model depicts resource integration as a process in which actors draw on interfacing

resources to which they apply their competences to produce an effect that manifests in

interfacing resources. Service innovation, which we understand as the rebundling of

resources that creates novel resources, result from these resource integration activities.

In social networking services, new features represent such novel resources.

The application of the resource integration model uncovered three service innovation

mechanisms: data-driven innovation, technology propulsion, and social debugging. Our

findings suggest that service innovation in social networking services relies significantly

on a provider’s ability to successfully engage, facilitate, and leverage the resources and

resource integration of its consumers. Each mechanism underlines that service

innovations are generated on the basis of consumer-provider interactions. Their

interactions that are reciprocal, dynamic and emergent over time. The logic inherent to

the mechanisms can be used to examine the generation of service innovations in specific

research contexts.

The model itself can be specialized for studying diverse aspects of service innovation

and resource integration, which we exemplified by blending the socio-technical

framework into our model. Thereby we created a novel vista on service innovation and

resource integration in social networking services.

We would like to note, that service-dominant logic and the underlying concept of

resource integration has received increasing attention in recent publications on service

innovation (Barrett et al. 2015; Lusch and Nambisan 2015; Nambisan et al. 2017). We

agree with others that this paradigmatic shift provides excellent opportunities for new,

innovative IS research. In so far, our work sketches a path for future research on service

innovation in the digital age.


IV.10 Appendix 1: Chronology of the Facebook Newsfeed

Table 16. Task-centered service innovations in the Newsfeed

Year Description Involved feature

2004 Launch of Facebook including profile page and the Wall. The profile serves as central element of the Facebook website and indicates a picture and personal information of consumers. The profile also includes “the Wall”, an element where consumers can post information and content.

Profile page, the wall

2006 Introduction of Newsfeed and Mini-Feed: Newsfeed is included on a consumers’ homepages as an aggregator to indicate news about people and activities within personal social network. The Mini-Feed is located at the profile page and indicates changes and updates to consumers’ profile pages.

Newsfeed

2006 Privacy control over Newsfeed: Consumers receive granular control of how information is integrated into Newsfeed. Consumers can block information and prevent content from being published on the newsfeed of other consumers. Change was a response to consumer feedback.

Newsfeed settings

2007 Facebook adopts a modular site structure and distinguishes between core elements, (profile and newsfeed), and (modular) applications, e.g. photos and groups. Consumers can add, remove and reorder applications in the navigation panel.

Modular site structure, profile

2008 New design of Facebook site (Tabbed profile and Publisher). Profile pages are split into tabs such as wall, info, and photos. To include further applications, more tabs can be added to the profile page. The Publisher is introduced as a universal function to publish content. These changes have been based on user previews, user tests, and the analysis of more than 100,000 suggestions of consumers.

Tabbed profile, the wall, publisher

2008 Update to Facebook site implements technological enhancements to feed more current and pertinent information about consumers and their social network into the newsfeed. The updated is based on user previews, tests and a collection and analysis of more than 100,000 suggestions of consumers on layout and features.

Newsfeed algorithm, feedback instrument

2009 The Like Button is introduced. Consumers can react on content that has been published within the social network by expressing “I like this” via a single button.

Like button

2009 Newsfeed is updated and includes, amongst other changes to the homepage, filters to control information listed within the Newsfeed. “As more and more is shared, we want you to be able to [...] shape the stream of information most relevant to you.” Functioning is illustrated within a “product tour”. Facebook received 30.000 emails feedback on the design of the homepage / newsfeed.

Newsfeed filters, consumer feedback

2011 Combined Newsfeed and popular post prioritization: As part of a facelift of the Homepage the sections “Highlights” and “News Feed” were consolidated into one single News Feed. Algorithm is updated to indicate top stories are listed at the top of the feed. That is, the algorithm ranks presented posts in new order. Instead of reverse chronological order, posts are presented based on their popularity (quantified by engagement of a post).

Newsfeed algorithm

2011 Implementation of subscribe button enables consumers to choose what to see from friends in Newsfeed, hear from others that are not within personal network (if subscribed), and let others hear from them (even if they are not connected).

Subscribe button

2013 Profile sections. The profile page is updated to differentiate sections for e.g., videos, music, books, etc. Profile sections organize content and profile information that consumers have added by using the like button.

Profile sections



2013 Newsfeed is updated to increase consumer engagement by including more information feeds, e.g., friends, photos, music, followed pages of each consumer (extending data that feeds into the algorithm). Introduction of automated video play in Newsfeed: Videos start playing silently when it they are indicated to the consumer.

Newsfeed, algorithm, photos, videos, pages, List of friends

2013 New ranking algorithm indicates (selected) posts that have not been seen by consumer a second time. Also, more weight is given to consumers recent interactions on the SNS.

Newsfeed algorithm, log data

2014 Reduction of click-baiting headlines in Newsfeed. Newsfeed algorithm

2014 Less promotional posts. Based on insights from a survey, the number of promotional page posts is reduced. Instead Newsfeed shows less promotional content and more stories from friends and pages associated with consumers preferences and personal network.

Newsfeed algorithm, consumer feedback, list of friends

2015 Fewer hoaxes (reporting of false news). Facebooks implements means to reduce number of hoax news within the Newsfeed. On the one hand posts are algorithmically evaluated, on the other hand, consumers can report questionable posts as “false news story”. Distribution of a post will be reduced if many consumers report a news story.

Newsfeed algorithm, reporting function

2015 Prioritization of news on and about friends. Newsfeed algorithm is updated to prioritize the indication of posts from (close) friends over pages consumers follow.

Newsfeed algorithm, friend list

2015 See first. Consumers can specify their Newsfeed preferences to prioritize specific friend’s and other pages (e.g., news to see first or to hide in Newsfeed).

Newsfeed algorithm, filter configuration

2016 Reactions are introduced as an extension of the Like button. Consumers can react to content by selecting emoticons that comprise Like, Love, Haha, Wow, Sad, and Angry. This change was a result of global research initiative and included focus groups and surveys.

Reactions

2016 Ranking of posts based on engagement probability. News that are likely to stimulate consumers’ interaction (e.g., rating, sharing, liking) are displayed at the top of the Newsfeed.

Newsfeed algorithm, rating, sharing, liking functionality

2017 Ranking of videos in the Newsfeed is (partly) based on the “percent completion”, that is for how long a video is watched, respectively if it is completely watched by many consumers.

Newsfeed algorithm, log data

2017 Ranking of posts. Newsfeed algorithm is updated to weigh “reactions” more than “likes”

Newsfeed algorithm, Likes, Reactions


Table 17. Technology-centered service innovations in the Newsfeed


2004 Launch of Facebook. Facebook launches its social networking services by providing a profile page for every consumer. Consumers can provide personal information and upload a profile picture.

Photos, camera, PC, Profile page

2005 Facebooks launches application “Photos”. Consumers are enabled to upload digital photos from their personal computer to a Facebook photo album.

Photos, camera, PC

2007 Facebook introduces application “Video”. Consumers can store and distribute videos to friends. Facebook built the application because “now (..) consumer mobile phones and digital cameras are perfectly capable of taking good quality video”.

Videos

2008 “Publisher” is introduced as central / universal feature to simplify publication of photos and videos within the SNS.

Publisher

2011 Video calling. In collaboration with Skype, consumers can make video calls directly from the chat function.

Chat, (Skype), Video camera

2012 High resolution pictures. Photo viewing application allows high-resolution photos and full screen viewing for Firefox and Chrome.

Browser, PC, , Photo viewer,

2014 Video view counts are indicated below published videos. Publisher, Newsfeed

2015 Consumers are enabled to publish animated pictures (GIFs) in their Newsfeed. Publisher, Newsfeed,

2015 Facebook allows upload of 360° videos. A set of specially configured cameras record all 360° of a scene simultaneously. Consumers can dynamically choose the angle of a scene by dragging the video with the finger, or by turning the device into a desired direction. This functionality is enabled by a gyroscope that is built into consumers’ mobile phone.

Recording: 360° video camera; Viewing: Mobile phone with gyroscope

2015 Consumers can build collages from photos and videos, that is consumers can group photos and videos into a movie collage.

Collage

2015 Video broadcasts can be shared live. Consumers can use the “live video” function to broadcast a video in real time. During a live session, number and name of viewers is indicated to the broadcaster. At the same time, viewers can post real-time comments that are indicated in real time below the video stream.

Network connection

2015 Profile page can include enhanced photos and video footage. Consumers can upload a video and a photo series on the personal profile page (“Intro”). In addition, consumers are enabled to set a temporary profile picture that expires after a specified time.

Profile page, mobile phone/ camera with video

2016 Implementation of 360° photos and virtual reality. Consumers can use their mobile phones with gyroscope to record all 360° in one photo. These photos can be viewed with mobile phones, with virtual reality (VR) headsets, or within a browser.

Mobile phone or camera with gyroscope, VR headset

2016 Live video functionality is enhanced. Facebook indicates videos that are currently broadcasted on a map of the world. Consumers can also express their feelings by using “reactions” in live videos. Also, consumers can broadcast live videos from events that are organized with Facebook’s event function. Similarly, consumers can broadcast live videos within Facebook groups.

Mobile phone or camera GPS, network connection, events, groups, reactions, filters


Table 18. Structure-centered service innovations in the Newsfeed


2006 Introduction of privacy page to control information displayed in newsfeed as a result of user feedback (and consumer protests organized by using Facebook groups). Implementation is a result of re-design of Newsfeed and Mini-Feed. Facebook CEO apologizes in open letter.

Privacy settings, Newsfeed, Groups

2007 Privacy controls for applications in conjunction with platform. Selective configuration of data access, reporting and blocking of applications.

Privacy settings,

2008 New design of the site design, including privacy page. Cleaner and simpler; Facebook declares it has no impact on previously selected privacy settings.

Privacy settings

2009 Update of privacy controls. Facebook calls consumers to review and update privacy settings. Implementation of new privacy features: granular control of over shared content (“publisher” privacy control, simplified privacy settings, expansion of education materials (on e.g., privacy center, guideline for sharing). Facebook declares that this implementation is a response to “requests from both users and experts”.

Privacy settings, transition tool, publisher, website

2010 Update of privacy settings and introduction of privacy dashboard to define and indicate information that third party applications can access from individual consumer profile.

Privacy settings

2010 Redesign of privacy settings. Simplification of user interface, (e.g., reduction from nearly 50 to 15 settings), reduction of information that is publicly available by default, increase of control about information shared with applications and websites. Change of privacy controls reflect feedback from various stakeholder groups (e.g., Facebook consumers, political institutions, consumer advocacy groups). Explicit communication of privacy operational principles.

Privacy settings

2011 Facebook settles Federal Trade Commission charges for deceiving consumers about the management of consumers private data. Facebook CEO announces commitment to privacy and two new roles Chief Privacy Officer, Policy and Chief Privacy Officer, Products.

Event

2012 Implementation of additional and update of existing privacy tools. Privacy shortcuts, activity log, control/remove tags in photos. In addition, implementation of “in-product education” and “in-context reminder” functions to guide consumers in managing privacy and security.

Privacy settings, security settings, photos

2012 Implementation of a support dashboard to feedback status information reports consumers have submitted on e.g., violations of policies (e.g., community standards).

Reporting; Com-munity policy

2013 Default privacy for teens. New accounts for teens (age 13-17 ) start with privacy settings that display shared content by default to “friends”. In addition, implementation of inline reminders and in-product education.

Privacy settings

2014 Implementation of “privacy checkup”. A tool to support consumers in reviewing and controlling information that is shared within the SNS. Also default audience for first posts of new accounts is “friends” instead of “public”.

Privacy settings

2014 Implementation of “privacy basics”. Interactive guides and information about how consumers can control information and data on Facebook with regard to, e.g., tagging, friending, blocking.

Privacy settings

2014 Update to terms and policies to accommodate for location based services (e.g., check-in, nearby friends), changes in policies regarding consumer data use, advertisements and third-party developers.

Policy, (Nearby, Friends, check-in)

2015 Implementation of “security checkup”. A tool to support finding and using security controls. For example, consumers are reminded to log out from devices that haven’t been used for a certain time, receive login alerts, and advice for secure passwords.

Security settings, login


IV.11 Appendix 2: Typologies of resources

Table 19. Typology of resources involved in task-centered innovations

Operant resources of provider

Interfacing operand resources from provider

Operant resources of consumer

Interfacing operand resources from consumer

Application of an iterative service design and development process.

Application of quantitative and qualitative research methods and implementation of feedback mechanisms to enhance knowledge about customer needs, wants and de-facto SNS use.

Knowledge of consumer needs, wants and SNS use enables data-driven analysis and decision making in system development.

Ability to identify and realize consumer-driven customization opportunities within the interfacing operand resource.

Ability to develop, refine and expand the application of data-driven personalization algorithms.

Ability to develop, implement and maintain the interfacing operand resources and additional functionality in support of these features.

Features related to service design and development, e.g., surveys, experiments, testing and various consumer feedback systems.

Features related to service use enable the primary functions of the SNS, e.g., profiles or homepages. These IS artifacts are highly customizable by consumers and integrate personalized information.

Operand resources related to personalization include recommendation algorithms that draw on various sources of data, e.g., user generated content, configuration and log data. The application of personalization algorithms is regularly refined and expanded within the SNS.

Consumers’ knowledge about their general needs in their use of a SNS as well as the ability to articulate those preferences through feedback instruments.

Consumers’ cognitive, creative and operational skills to create user generated content (e.g., photos, videos, tags, comments) and to evaluate content of other consumers (e.g., ratings or subscriptions).

Consumers’ knowledge about personal preferences in the use of a SNS and the ability to customize IS resources accordingly (e.g., layout, design, site structure and elements).

Consumers’ ability to communicate and interact with other consumers within through comments, messages, ratings.

Feedback data is collected through feedback mechanisms, e.g., experiments, tests, or surveys.

Personal data includes publicly shared and private information to describe and represent a consumers’ virtual identity and associated personal social network. Examples: name, profile picture, job information, list of friends.

User generated content include digital information such as photos, videos, or comments that consumers typically create, share, and distribute within the SNS.

Configuration data is actively created by consumers, e.g. by defining privacy and security settings, customizing features, or by explicating personal interests and preferences through filters, ratings, or similar features.

Log data is passively created and collected by the provider. It is based on consumers system use. Log data includes, for example, timestamps of consumer actions (e.g., recently uploaded or viewed content).


Table 20. Typology of resources involved in technology-centered innovations





Application of an iterative service innovation process

Ability to develop and operate the SNS technology infrastructure

Knowledge of consumer technology and consumers’ technology capabilities, e.g. through beta-user communities

Ability to develop and implement features that facilitate consumer learning

SNS technology infrastructure

Information and exchange to teach and educate consumers, e.g., announcements, introduction videos, Q&A and exchange with engineers, feedback sessions

Features to foster consumer competence development, e.g., in-product education, tutorial videos, help sections

Features that adhere to standard and consistent digital interfaces

Consumers’ knowledge and skills to configure and operate personal technology infrastructure

Consumers’ knowledge and understanding of relevant provider technology resources and skill to integrate personal technology

Functioning technology configuration, i.e. configured personal infrastructure, that enable (new) feature

Consumer hardware (e.g., phones, cameras, personal computer, network connection)

Consumer software (e.g., operating system, browser, mobile apps

Table 21. Typology of resources involved in structure-centered innovations





Knowledge & skills

Knowledge about providers’ and consumers’ values and norms.

Development of governance instruments.

Development of value-reflecting communication and articulation instruments.

Development of regulation and enforcement instruments.

Governance instruments

Policies (data policy, third party developers, community standards)

Guidelines (for sharing con

tent)

Default settings (“private”)

Value communication and articulation instruments

Discussion forums

Q&A sessions

Groups function

Press releases

Regulation and enforcement instruments

Privacy and security settings

Privacy and security tools (e.g., tutorials dashboards, in-product education, password advice)

Enforcement mechanisms (reporting, blocking, flagging, connect)

Knowledge & skills

Knowledge about own worldview and ability to act upon underlying values and norms

Operational skills to define settings according to personal preferences

Ability to utilize functionalities to communicate and articulate own values

Value & norm exposing data

Privacy and security configuration (data)

Value articulation data (flags, blocks)

Feedback data

References 111

References

Abrahamsson, P., Conboy, K., and Wang, X. 2009. “‘Lots done, more to do’: the

current state of agile systems development research,” European Journal of

Information Systems (18:4), pp. 281–284.

Agarwal, R., and Lucas, H. C. 2005. “The information systems identity crisis:

Focusing on high-visibility and high-impact research,” MIS Quarterly, pp. 381–

398.

Alaimo, C., and Kallinikos, J. 2017. “Computing the everyday: Social media as data

platforms,” The Information Society (33:4), pp. 175–191.

Albert, T. C., Goes, P. B., and Gupta, A. 2004. “GIST: a model for design and

management of content and interactivity of customer-centric web sites,” MIS

Quarterly, pp. 161–182.

Alter, S. 2008. “Defining information systems as work systems: implications for the IS

field,” European Journal of Information Systems (17:5), pp. 448–469.

Aral, S., Dellarocas, C., and Godes, D. 2013. “Introduction to the Special Issue—

Social Media and Business Transformation: A Framework for Research,”

Information Systems Research (24:1), pp. 3–13.

Arnould, E. J., Price, L. L., and Malshe, A. 2006. “Toward a cultural resource-based

theory of the customer,” The service-dominant logic of marketing: Dialog, debate

and directions, pp. 320–333.

Baron, S., and Harris, K. 2008. “Consumers as resource integrators,” Journal of

Marketing Management (24:1-2), pp. 113–130.

Barrett, M., Davidson, E., Prabhu, J., and Vargo, S. L. 2015. “Service innovation in

the digital age: key contributions and future directions,” MIS Quarterly (39:1), pp.

135–154.

Baskerville, R. 2011. “Individual information systems as a research arena,” European

Journal of Information Systems (20:3), pp. 251–254.

Benbasat, I., Goldstein, D. K., and Mead, M. 1987. “The case research strategy in

studies of information systems,” MIS Quarterly, pp. 369–386.

Bendapudi, N., and Berry, L. L. 1997. “Customers' motivations for maintaining

relationships with service providers,” Journal of Retailing (73:1), pp. 15–37.

Berry, L. L. 1995. “Relationship marketing of services—growing interest, emerging

perspectives,” Journal of the Academy of Marketing Science (23:4), pp. 236–245.

Bostrom, R. P., and Heinen, J. S. 1977. “MIS problems and failures: a socio-technical

perspective, part I: the causes,” MIS Quarterly (1:3), pp. 17–32.

112 References

Boulding, W., Staelin, R., Ehret, M., and Johnston, W. J. 2005. “A customer

relationship management roadmap: What is known, potential pitfalls, and where to

go,” Journal of Marketing (69:4), pp. 155–166.

Brakus, J. J., Schmitt, B. H., and Zarantonello, L. 2009. “Brand Experience: What is

it? How is it Measured? Does it Affect Loyalty?” Journal of Marketing (73:3), pp.

52–68.

Brenner, W., Karagiannis, D., Kolbe, L., Krüger, D.-K. J., Leifer, L., Lamberti, H.-J.,

Leimeister, J. M., Österle, H., Petrie, C., and Plattner, H. 2014. “User, use & utility

research,” Business & Information Systems Engineering (6:1), pp. 55–61.

Cavusoglu, H., Phan, T. Q., Cavusoglu, H., and Airoldi, E. M. 2016. “Assessing the

impact of granular privacy controls on content sharing and disclosure on

Facebook,” Information Systems Research (27:4), pp. 848–879.

Ceccagnoli, M., Forman, C., Huang, P., and Wu, D. J. 2012. “Co-creation of value in a

platform ecosystem: The case of enterprise software,” MIS Quarterly (36:1).

Chen, R., and Sharma, S. K. 2013. “Learning and self-disclosure behavior on social

networking sites: The case of Facebook users,” European Journal of Information

Systems (24:1), pp. 93–106.

Cheung, C. M.K., Chiu, P.-Y., and Lee, M. K.O. 2011. “Online social networks: Why

do students use facebook?” Computers in Human Behavior (27:4), pp. 1337–1343.

Corbin, J., and Strauss, A. 2014. Basics of qualitative research: Sage.

Day, G. S. 2000. “Managing Market Relationships,” Journal of the Academy of

Marketing Science (28:1), pp. 24–30.

Day, G. S. 2003. “Creating a Superior Customer-Relating Capability,” MIT Sloan

management review (44:3), pp. 77–82.

Dingsøyr, T., Nerur, S., Balijepally, V., and Moe, N. B. 2012. “A decade of agile

methodologies: Towards explaining agile software development,” Journal of

Systems and Software (85:6), pp. 1213–1221.

Dubé, L., and Paré, G. 2003. “Rigor in information systems positivist case research:

current practices, trends, and recommendations,” MIS Quarterly, pp. 597–636.

Eaton, B., Elaluf-Calderwood, S., Sørensen, C., and Yoo, Y. 2015. “Distributed

Tuning of Boundary Resources: The Case of Apple’s iOS Service System,” MIS

Quarterly (39:1), pp. 217–243.

Eisenhardt, K. M. 1989. “Building theories from case study research,” Academy of

Management Review (14:4), pp. 532–550.

References 113

Enders, A., Hungenberg, H., Denker, H.-P., and Mauch, S. 2008. “The long tail of

social networking.: Revenue models of social networking sites,” European

Management Journal (26:3), pp. 199–211.

Etgar, M. 2008. “A descriptive model of the consumer co-production process,”

Journal of the Academy of Marketing Science (36:1), pp. 97–108.

Facebook. 2007. Video is here. https://www.facebook.com/notes/facebook/video-is-

here/2500237130.

Facebook. 2011. Our Commitment to the Facebook Community.

https://newsroom.fb.com/news/2011/11/our-commitment-to-the-facebook-

community/.

Facebook. 2017a. “Annual Report 2016,”

Facebook. 2017b. Facebook's new tech at F8 2017.

https://code.facebook.com/posts/1309213412492639/facebook-s-new-tech-at-f8-

2017/.

Facebook. 2017c. How We Shipped Reactions.

https://developers.facebook.com/videos/f8-2017/how-we-shipped-reactions/.

Facebook. 2017d. What's New with News Feed.

https://developers.facebook.com/videos/f8-2017/whats-new-with-news-feed/.

Feitelson, D. G., Frachtenberg, E., and Beck, K. L. 2013. “Development and

Deployment at Facebook,” IEEE Internet Computing (17:4), pp. 8–17.

Forbes. 2012a. The Numbers Behind Steam's Success.

https://www.forbes.com/sites/insertcoin/2012/02/16/the-numbers-behind-steams-

success/#60293ccb470f. Accessed 3 April 2017.

Forbes. 2012b. Valve's Gabe Newell Is The Newest Video Game Billionaire.

http://www.forbes.com/sites/davidewalt/2012/03/07/valve-gabe-newell-

billionaire/#4ce71831c49d.

Forbes. 2014a. Steam Greenlight Passes 50 Games, 'Depression Quest' First Twine

Game Lined Up For Steam Launch.

http://www.forbes.com/sites/danielnyegriffiths/2014/01/08/steam-greenlight-

passes-50-games-depression-quest-first-twine-game-lined-up-for-steam-

launch/#2c6fc8083d92.

Forbes. 2014b. Valve's Social Engineering Campaign Against Cheaters is Out of

Bounds. http://www.forbes.com/sites/michaelthomsen/2014/03/04/valves-social-

engineering-campaign-against-cheaters-is-out-of-bounds/#503f2adc5dc1. Accessed

3 April 2017.

114 References

Galbraith, J. R. 2005. Designing the customer-centric organization: A guide to

strategy, structure, and process: John Wiley & Sons.

George, A. L., and Bennett, A. 2005. Case studies and theory development in the

social sciences, Cambridge, UK: MIT press.

Gerring, J. 2017. Case study research: Principles and practices, Cambridge, UK:

Cambridge University Press.

Ghazawneh, A., and Henfridsson, O. 2013. “Balancing platform control and external

contribution in third-party development: the boundary resources model,”

Information Systems Journal (23:2), pp. 173–192.

Giddens, A. 1979. Central problems in social theory: Action, structure, and

contradiction in social analysis, Berkeley: University of California Press.

Glaser, B. G., and Strauss, A. L. 1967. “The discovery of grounded theory: strategies

for qualitative research,” .

Gnyawali, D. R., Fan, W., and Penner, J. 2010. “Competitive actions and dynamics in

the digital age: an empirical investigation of social networking firms,” Information

Systems Research (21:3), pp. 594–613.

Goldbach, T., and Benlian, A. 2015. “Kontrollmechanismen auf Software-

Plattformen,” HMD Praxis der Wirtschaftsinformatik (52:3), pp. 347–357.

Grönroos, C. 2008. “Service logic revisited: who creates value? And who co-creates?”

European Business Review (20:4), pp. 298–314.

Grönroos, C., and Voima, P. 2013. “Critical service logic: making sense of value

creation and cocreation,” Journal of the Academy of Marketing Science (41:2), pp.

133–150.

Gummesson, E. 2008a. “Customer centricity: reality or a wild goose chase?”

European Business Review (20:4), pp. 315–330.

Gummesson, E. 2008b. “Extending the service-dominant logic: from customer

centricity to balanced centricity,” Journal of the Academy of Marketing Science

(36:1), pp. 15–17.

Han, K., Oh, W., Im, K. S., Chang, R. M., Oh, H., and Pinsonneault, A. 2012. “Value

cocreation and wealth spillover in open innovation alliances,” MIS Quarterly

(36:1), pp. 291–325.

Hanseth, O., and Lyytinen, K. 2010. “Design theory for dynamic complexity in

information infrastructures: the case of building internet,” Journal of Information

Technology (25:1), pp. 1–19.

Henfridsson, O., and Bygstad, B. 2013. “The Generative Mechanisms of Digital

Infrastructure Evolution,” MIS Quarterly (37:3), pp. 907–931.

References 115

Hennig-Thurau, T., Gwinner, K. P., and Gremler, D. D. 2002. “Understanding

Relationship Marketing Outcomes: An Integration of Relational Benefits and

Relationship Quality,” Journal of Service Research (4:3), pp. 230–247.

Hester, A. J. 2014. “Socio-technical systems theory as a diagnostic tool for examining

underutilization of wiki technology,” The Learning Organization (21:1), pp. 48–68.

Hirschman, E. C., and Holbrook, M. B. 1982. “Hedonic consumption: emerging

concepts, methods and propositions,” The Journal of Marketing, pp. 92–101.

Hirschman, E. C., and Holbrook, M. B. 1986. “Expanding the ontology and

methodology of research on the consumption experience,” in Perspectives on

methodology in consumer research: Springer, pp. 213–251.

Hoadley, C. M., Xu, H., Lee, J. J., and Rosson, M. B. 2010. “Privacy as information

access and illusory control: The case of the Facebook News Feed privacy outcry,”

Electronic Commerce Research and Applications (9:1), pp. 50–60.

Hoffman, C. 2016. Linux gaming is much healthier than Steam's Hardware Survey

implies. http://www.pcworld.com/article/3045249/linux/linux-gaming-is-much-

healthier-than-steams-hardware-survey-implies.html.

Holbrook, M. B., and Hirschman, E. C. 1982. “The experiential aspects of

consumption: Consumer fantasies, feelings, and fun,” Journal of consumer

research, pp. 132–140.

Huang, J., Henfridsson, O., Liu, M., and Newell, S. 2016. “Growing on steroids:

rapidly scaling the user base in digital ventures through digital innovation,” MIS

Quarterly .

Huang, M.-H., and Rust, R. T. 2013. “IT-Related Service A Multidisciplinary

Perspective,” Journal of Service Research (16:3), pp. 251–258.

Hughes, N. 2010. Steam survey finds more than 8% of gamers use Apple's Mac OS X.

http://appleinsider.com/articles/10/06/05/steam_survey_finds_more_than_8_of_ga

mers_use_apples_mac_os_x.

Jayachandran, S., Sharma, S., Kaufman, P., and Raman, P. 2005. “The role of

relational information processes and technology use in customer relationship

management,” Journal of Marketing (69:4), pp. 177–192.

Johnson, D. S., and Bharadwaj, S. 2005. “Digitization of selling activity and sales

force performance: An empirical investigation,” Journal of the Academy of

Marketing Science (33:1), pp. 3–18.

Joorabchi, M. E., Mesbah, A., and Kruchten, P. 2013. “Real Challenges in Mobile App

Development,” in 2013 ACM/IEEE International Symposium on Empirical

Software Engineering and Measurement (ESEM), Baltimore, Maryland, pp. 15–24.

116 References

Kallinikos, J., Aaltonen, A., and Marton, A. 2013. “The Ambivalent Ontology of

Digital Artifacts,” MIS Quarterly (37:2), pp. 357–370.

Kankanhalli, A., Tan, B. C. Y., and Wei, K.-K. 2005. “Contributing knowledge to

electronic knowledge repositories: an empirical investigation,” MIS Quarterly, pp.

113–143.

Ketonen-Oksi, S., Jussila, J. J., and Kärkkäinen, H. 2016. “Social media based value

creation and business models,” Industrial Management & Data Systems (116:8),

pp. 1820–1838.

Kietzmann, J. H., Hermkens, K., McCarthy, I. P., and Silvestre, B. S. 2011. “Social

media? Get serious! Understanding the functional building blocks of social media,”

Business Horizons (54:3), pp. 241–251.

Kim, W., Jeong, O.-R., and Lee, S.-W. 2010. “On social Web sites,” Information

Systems (35:2), pp. 215–236.

Klein, H. K., and Myers, M. D. 1999. “A Set of Principles for Conducting and

Evaluating Interpretive Field Studies in Information Systems,” MIS Quarterly

(23:1), pp. 67–93.

Kumar, V. 2015. “Evolution of Marketing as a Discipline: What Has Happened and

What to Look Out For,” Journal of Marketing (79:1), pp. 1–9.

Kumar, V., Venkatesan, R., and Reinartz, W. 2008. “Performance implications of

adopting a customer-focused sales campaign,” Journal of Marketing (72:5), pp. 50–

68.

Lamb, R., and Kling, R. 2003. “Reconceptualizing users as social actors in information

systems research,” MIS Quarterly, pp. 197–236.

Lamberti, L. 2013. “Customer centricity: the construct and the operational

antecedents,” Journal of Strategic Marketing (21:7), pp. 588–612.

Leavitt, H. 1964a. “Applied Organisation Change in Industry: Structural, Technical

and Human Approaches,” New Perspectives in Organisational Research, John

Wiley, pp. 1144–1170.

Leavitt, H. J. 1964b. “Applied organization change in industry: structural, technical

and human approaches,” New Perspectives in Organizational Research, pp. 55–71.

Leavitt, H. J. 1965. “Applied organizational change in industry: Structural,

technological and humanistic approaches,” Handbook of organizations (1144), p.

1170.

Lee, J.-Y., Sridhar, S., Henderson, C. M., and Palmatier, R. W. 2014. “Effect of

customer-centric structure on long-term financial performance,” Marketing Science

.

References 117

Lee, S. M., Kim, Y. R., and Lee, J. 1995. “An Empirical Study of the Relationships

among End-User Information Systems Acceptance, Training, and Effectiveness,”

Journal of Management Information Systems (12:2), pp. 189–202.

Lempinen, H., and Rajala, R. 2014. “Exploring multi-actor value creation in IT service

processes,” Journal of Information Technology (29:2), pp. 170–185.

Levitt, T. 1960. Marketing myopia.

Li, T., and Unger, T. 2012. “Willing to pay for quality personalization? Trade-off

between quality and privacy,” European Journal of Information Systems (21:6), pp.

621–642.

Liang, T.-P., and Tanniru, M. 2006. “Special Section: Customer-Centric Information

Systems,” Journal of Management Information Systems (23:3), pp. 9–15.

Löbler, H., and Lusch, R. F. 2014. “Signs and Practices as Resources in IT-Related

Service Innovation,” Service Science (6:3), pp. 190–205.

Lusch, R. F., and Nambisan, S. 2015. “Service Innovation: A Service-Dominant Logic

Perspective,” MIS Quarterly (39:1), pp. 155–175.

Lyytinen, K., and Newman, M. 2008. “Explaining information systems change: a

punctuated socio-technical change model,” European Journal of Information

Systems (17:6), pp. 589–613.

Madhavaram, S., and Hunt, S. D. 2008. “The service-dominant logic and a hierarchy

of operant resources: developing masterful operant resources and implications for

marketing strategy,” Journal of the Academy of Marketing Science (36:1), pp. 67–

82.

Maglio, P. P., and Spohrer, J. 2008. “Fundamentals of service science,” Journal of the

Academy of Marketing Science (36:1), pp. 18–20.

Maier, C., Laumer, S., Eckhardt, A., and Weitzel, T. 2015. “Giving too much social

support: social overload on social networking sites,” European Journal of

Information Systems (24:5), pp. 447–464.

Mesaglio, M., and Hotle, M. 2012. Pace-Layered Application Strategy and IT

Organizational Design: How to Structure the Application Team for Success.

Gartner Research Note.

Moeller, S., Ciuchita, R., Mahr, D., Odekerken-Schröder, G., and Fassnacht, M. 2013.

“Uncovering collaborative value creation patterns and establishing corresponding

customer roles,” Journal of Service Research (16:4), pp. 471–487.

Moore, G. 2011. “Systems of engagement and the future of enterprise IT-a sea change

in enterprise it,” AIIM, Silver Spring, Maryland .

118 References

Morgan, R. M., and Hunt, S. D. 1994. “The Commitment-Trust Theory of

Relationship Marketing,” Journal of Marketing (58:3), p. 20.

Nambisan, S., Lyytinen, K., Majchrzak, A., and Song, M. 2017. “Digital innovation

management: Reinventing innovation management research in a digital world,”

Management Information Systems Quarterly (41:1), pp. 223–238.

Newell, G. 2014. Valve, VAC, and trust.

https://www.reddit.com/r/gaming/comments/1y70ej/valve_vac_and_trust/.

Orlikowski, W. J. 2000. “Using technology and constituting structures: A practice lens

for studying technology in organizations,” Organization science (11:4), pp. 404–

428.

Pan, S. L., and Pan, G. 2006. “Customer-centric IS application development: lessons

from a case of developing an online auction site,” Communications of the

Association for Information Systems (18:1), p. 18.

Paré, G. 2004. “Investigating information systems with positivist case research,” The

Communications of the Association for Information Systems (13:1), p. 57.

Payne, A., and Frow, P. 2005. “A Strategic Framework for Customer Relationship

Management,” Journal of Marketing (69:4), pp. 167–176.

Payne, A. F., Storbacka, K., and Frow, P. 2008. “Managing the cocreation of value,”

Journal of the Academy of Marketing Science (36:1), pp. 83–96.

Peppers, D., Rogers, M., and Dorf, B. 1999. “Is your company ready for one-to-one

marketing,” Harvard Business Review (77:1), pp. 151–160.

Prahalad, C. K., and Ramaswamy, V. 2004. “Co-creation experiences: The next

practice in value creation,” Journal of Interactive Marketing (18:3), pp. 5–14.

Rai, A., Pavlou, P. A., Im, G., and Du, S. 2012. “Interfirm IT capability profiles and

communications for cocreating relational value: evidence from the logistics

industry,” MIS Quarterly (36:1), pp. 233–262.

Reich, B. H., and Benbasat, I. 1990. “An empirical investigation of factors influencing

the success of customer-oriented strategic systems,” Information Systems Research

(1:3), pp. 325–347.

Reuver, M. de, Sørensen, C., and Basole, R. C. 2017. “The digital platform: A research

agenda,” Journal of Information Technology .

Ross, C., Orr, E. S., Sisic, M., Arseneault, J. M., Simmering, M. G., and Orr, R. R.

2009. “Personality and motivations associated with Facebook use,” Computers in

Human Behavior (25:2), pp. 578–586.

Rowe, F. 2014. “What literature review is not: diversity, boundaries and

recommendations,” European Journal of Information Systems (23:3), pp. 241–255.

References 119

Saarijärvi, H., Karjaluoto, H., and Kuusela, H. 2013. “Extending customer relationship

management: from empowering firms to empowering customers,” Journal of

Systems and Information Technology (15:2), pp. 140–158.

Sarker, S., Chatterjee, S., and Xiao, X. 2013. “How “sociotechnical” is our IS

research? An assessment and possible ways forward,” Thirty Fourth International

Conference on Information Systems, Milan .

Sarker, S., Sarker, S., Sahaym, A., and Bjørn-Andersen, N. 2012. “Exploring value

cocreation in relationships between an ERP vendor and its partners: a revelatory

case study,” MIS Quarterly (36:1), pp. 317–338.

Sas, C., Dix, A., Hart, J., and Su, R. (eds.). 2009. Dramaturgical capitalization of

positive emotions: the answer for Facebook success? British Computer Society.

Schmitt, B. 1999. “Experiential Marketing,” Journal of Marketing Management (15:1-

3), pp. 53–67.

Shah, D., Rust, R. T., Parasuraman, A., Staelin, R., and Day, G. S. 2006. “The path to

customer centricity,” Journal of Service Research (9:2), pp. 113–124.

Sheth, J. N., and Parvatlyar, A. 1995. “Relationship Marketing in Consumer Markets:

Antecedents and Consequences,” Journal of the Academy of Marketing Science

(23:4), pp. 255–271.

Sheth, J. N., Sisodia, R. S., and Sharma, A. 2000. “The antecedents and consequences

of customer-centric marketing,” Journal of the Academy of Marketing Science

(28:1), pp. 55–66.

Siau, K., Lim, E.-P., and Shen, Z. 2001. “Mobile commerce: Promises, challenges and

research agenda,” Journal of Database Management (JDM) (12:3), pp. 4–13.

Singaraju, S. P., Nguyen, Q. A., Niininen, O., and Sullivan-Mort, G. 2016. “Social

media and value cocreation in multi-stakeholder systems: A resource integration

approach,” Industrial Marketing Management (54), pp. 44–55.

Spohrer, J. C., and Maglio, P. P. 2010. “Towards a Science of Service Systems. Value

and Symbols,” Handbook of Service Science (Service Science: Research and

Innovations in the Service Economy), pp. 157–195.

Spottke, B., Eck, A., and Wulf, J. 2016. “A Socio-Technical Approach to Study

Consumer-Centric Information Systems,” Proceedings of the 37th International

Conference on Information Systems (ICIS), Dublin (Ireland), December 11-14,

2016. .

Spottke, B., Wulf, J., and Brenner, W. 2015. “Consumer-Centric Information Systems:

A Literature Review and Avenues for Further Research,” Proceedings of the 36th

120 References

International Conference on Information Systems (ICIS), Fort Worth (USA),

December 13-16, 2015. .

Statista. 2016. Facebook Dossier. https://www.statista.com/study/9711/facebook-

statista-dossier/. Accessed January, 5th, 2018.

SteamDB. 2016. Latest Game & VAC Bans. https://steamdb.info/stats/bans/. Accessed

3 August 2016.

Strauss, A., and Corbin, J. M. 1990. Basics of qualitative research: Grounded theory

procedures and techniques: Sage Publications, Inc.

Tax, S. S., McCutcheon, D., and Wilkinson, I. F. 2013. “The service delivery network

(SDN) a customer-centric perspective of the customer journey,” Journal of Service

Research (16:4), pp. 454–470.

TechCrunch. 2009. The Facebook Privacy Fiasco Begins.

https://techcrunch.com/2009/12/09/facebook-privacy/. Accessed January, 7th,

2018.

TechCrunch. 2016. How Facebook News Feed Works.

https://techcrunch.com/2016/09/06/ultimate-guide-to-the-news-feed/. Accessed

August, 7th, 2017.

The Economist. 2016a. Facebook, the world’s most addictive drug. Accessed April,

7th 2016.

The Economist. 2016b. “Imperial ambitions,” .

The Economist. 2017. The world's most valuable resource is no longer oil, but data.

Accessed Jan, 5th 2018.

Tilson, D., Lyytinen, K., and Sørensen, C. 2010. “Research commentary-digital

infrastructures: the missing IS research agenda,” Information Systems Research

(21:4), pp. 748–759.

Tiwana, A., Konsynski, B., and Bush, A. A. 2010. “Research commentary-Platform

evolution: Coevolution of platform architecture, governance, and environmental

dynamics,” Information Systems Research (21:4), pp. 675–687.

Tow, W. N.-F. H., Dell, P., and Venable, J. 2010. “Understanding information

disclosure behaviour in Australian Facebook users,” Journal of Information

Technology (25:2), pp. 126–136.

Turel, O., Serenko, A., and Bontis, N. 2010. “User acceptance of hedonic digital

artifacts: A theory of consumption values perspective,” Information &

Management (47:1), pp. 53–59.

References 121

Tuunanen, T., Gardner, L. A., and Bastek, M. 2011. “Consumer Information Systems

as Service Modules: Case Study of IPTV Services,” Service Science (3:3), pp. 264–

279.

Tuunanen, T., Myers, M., and Cassab, H. 2010. “A conceptual framework for

consumer information systems development,” Pacific Asia Journal of the


Tuunanen, T., Myers, M. D., and Cassab, H. 2008. “Challenges of consumer

information systems development: The case of interactive television services,” in

Advances in information systems research, education and practice: Springer, pp.

89–100.

Valve. 2012. Press Release: Valve Announces Steam Greenlight.

http://store.steampowered.com/news/?feed=steam_press.

Valve. 2013. Press Release: Greenlight's first anniversary.


Valve. 2016a. Client Updates.

http://store.steampowered.com/news/?feed=steam_client.

Valve. 2016b. Press Releases.


Valve. 2016c. Steam & Game Stats. http://store.steampowered.com/stats/.

Valve. 2016d. Steam Store. http://store.steampowered.com/. Accessed 10 July 2017.

Valve. 2017. Steam Subscriber Agreement.

http://store.steampowered.com/subscriber_agreement/. Accessed 10 July 2017.

Vargo, S. L., and Lusch, R. F. 2004. “Evolving to a New Dominant Logic for

Marketing,” Journal of Marketing (68:1), pp. 1–17.

Vargo, S. L., and Lusch, R. F. 2008. “Service-dominant logic: continuing the

evolution,” Journal of the Academy of Marketing Science (36:1), pp. 1–10.

Vargo, S. L., and Lusch, R. F. 2016. “Institutions and axioms: an extension and update

of service-dominant logic,” Journal of the Academy of Marketing Science (44:1),

pp. 5–23.

Venkatesh, V., Morris, M. G., Gordon B. Davis, and Davis, F. D. 2003. “User

Acceptance of Information Technology: Toward a Unified View,” MIS Quarterly

(27:3), pp. 425–478.

Venkatesh, V., Thong, J. Y. L., and Xu, X. 2012. “Consumer acceptance and use of

information technology: extending the unified theory of acceptance and use of

technology,” MIS Quarterly (36:1), pp. 157–178.

122 References

Verhoef, P. C. 2003. “Understanding the Effect of Customer Relationship

Management Efforts on Customer Retention and Customer Share Development,”

Journal of Marketing (67:4), pp. 30–45.

Verhoef, P. C., and Lemon, K. N. 2013. “Successful customer value management: Key

lessons and emerging trends,” European Management Journal (31:1), pp. 1–15.

Verhoef, P. C., Lemon, K. N., Parasuraman, A., Roggeveen, A., Tsiros, M., and

Schlesinger, L. A. 2009. “Customer Experience Creation: Determinants, Dynamics

and Management Strategies,” Journal of Retailing (85:1), pp. 31–41.

Viera, A. J., and Garrett, J. M. 2005. “Understanding interobserver agreement: the

kappa statistic,” Fam Med (37:5), pp. 360–363.

Vom Brocke, J., Simons, A., Niehaves, B., Niehaves, B., Reimer, K., Plattfaut, R., and

Cleven, A. 2009. “Reconstructing the giant: on the importance of rigour in

documenting the literature search process,” .

Wagner, C., and Majchrzak, A. 2006. “Enabling customer-centricity using wikis and

the wiki way,” Journal of Management Information Systems (23:3), pp. 17–43.

Wall Street Journal. 2018. FB Stockprice & News. http://quotes.wsj.com/FB. Accessed

January 5th, 2018.

Webster, J., and Watson, R. T. 2002. “Analyzing the past to prepare for the future:

Writing a literature review,” Management Information Systems Quarterly (26:2), p.

3.

Wired. 2010a. Valve Brings Hit Games, Steam Service to Mac.

https://www.wired.com/2010/03/steam-mac/. Accessed 8 May 2017.

Wired. 2010b. Valve Says Downloads Picked Up Steam in 2009.

https://www.wired.com/2010/01/steam-growth/. Accessed 8 May 2017.

Womack, J. P., and Jones, D. T. 2005. “Lean consumption,” Harvard Business Review

(83:3), p. 5868.

Wulf, K. D., Odekerken-Schröder, G., and Iacobucci, D. 2001. “Investments in

Consumer Relationships: A Cross-Country and Cross-Industry Exploration,”

Journal of Marketing (65:4), pp. 33–50.

Xiao, X., and Wang, T.-n. (eds.). 2014. Social networking sites' feature development

from a complexity theory perspective, IEEE.

Yin, R. K. 2013. Case study research: Design and methods: Sage Publications Ltd.

Yoo, Y. 2010. “Computing in Everyday Life: A Call for Research on Experiential

Computing,” MIS Quarterly (34:2), pp. 213–231.

References 123

Yoo, Y. 2013. “The tables have turned: how can the information systems field

contribute to technology and innovation management research,” Journal of the


Yoo, Y., Boland Jr, R. J., Lyytinen, K., and Majchrzak, A. 2012. “Organizing for

innovation in the digitized world,” Organization science (23:5), pp. 1398–1408.

Yoo, Y., Henfridsson, O., and Lyytinen, K. 2010. “Research Commentary —The New

Organizing Logic of Digital Innovation: An Agenda for Information Systems

Research,” Information Systems Research (21:4), pp. 724–735.

YouTube. 2016. Statistics. https://www.youtube.com/yt/press/en-GB/statistics.html.

Zeng, X., and Wei, L. 2013. “Social Ties and User Content Generation: Evidence from

Flickr,” Information Systems Research (24:1), pp. 71–87.

Zittrain, J. 2008. The future of the internet--and how to stop it: Yale University Press.

Zittrain, J. L. 2006. “The generative internet,” Harvard Law Review, pp. 1974–2040.

Publication list of the author XVII

Publication list of the author

The full list of publications to which the author contributed during his dissertation

process are indicated in Table 22.

Table 22. Comprehensive publication list with participation of the author

# Title Outlet Authors

1 Consumer-Centric Information Systems: A Literature Review and Avenues for Further Research

ICIS 2015 Proceedings (Thesis article)

Benjamin Spottke, Jochen Wulf, Walter Brenner

2 A Socio-Technical Approach to Study Consumer-Centric Information Systems

ICIS 2016 Proceedings (Thesis article)

Benjamin Spottke, Alexander Eck, Jochen Wulf

3 Explaining Value Cocreation in Social Networking Services: Towards a Process Model of Resource Integration (presentation)

Social Study of IT Open Research Forum 2017

Benjamin Spottke, Alexander Eck

4 Project Report Joint Research Initiative Agile Application Management:

IWI-HSG, University of St. Gallen

Benjamin Spottke, Jochen Wulf, Fiorenzo Maletta

5 What Companies Can Learn from the Videogame Industry for the Design of the Digital Customer Experience: An Analysis of the Platform Steam

HMD Praxis der Wirtschaftsinformatik (HMD best paper award 2017) (Thesis article)

Benjamin Spottke

6 Actualizing Affordances: A Socio-Technical Perspective on Big Data Analytics in the Automotive Sector.

ICIS 2017 Proceedings Christian Dremel, Matthias Herterich, Jochen Wulf, Benjamin Spottke

7 Bootstrapping a Digital Ecosystem. (presentation)

European Workshop on Software Ecosystems, Darmstadt (Best Presentation Award)

Alexander Eck, Benjamin Spottke,

8 Service Innovation in Social Networking Services: A Resource Integration Perspective on Facebook

Working paper (IWI-HSG) 2018 aiming at a top IS journal

(Thesis article)

Benjamin Spottke, Alexander Eck, Jochen Wulf

Curriculum vitae XIX

Curriculum vitae

Personal information

Name Benjamin Spottke

Date of birth 22 December 1981

Place of birth Koblenz

Nationality German

Education

2014 – 2018 University of St. Gallen, Switzerland

PhD Program in Management (Business Innovation)

2001 – 2007 RWTH-Aachen, Germany

Dipl.-Kfm. in Business Administration

1995 – 2004 Gymnasium im Kannenbäckerland, Höhr-Grenzhausen

Abitur (University Entrance Diploma)

Work experience

2014 – 2018 Research Associate

Institute of Information Management

University of St. Gallen, Switzerland

2012 – 2014 Manager Sales & Supply Planning Europe

West Pharmaceutical Services GmbH & Co. KG

2010 – 2012 Specialist Sales & Supply Planning Europe


2007 – 2010 System Validation & Project Management Office Analyst Europe &

Asia Pacific


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