Managing International Networks for

Emerging Technologies

– Teaching Materials –

Dr Tomás S. Harrington, Dr Jagjit Singh Srai, Dr David A. Kirkwood

Introduction

This report provides a summary of MIN II research and provides teaching material for the dissemination of academic outputs. One of the challenges concerning emerging industries (EIs) is that there is no defined strategy that a firm can follow. The lack of certainty in the environment and on the consumer needs forces the entrepreneur to experiment with supply chain strategies through a process described as “effectuation” (Sarasvathy, 2001, Winter & Szulanksi, 2001). This process can be very time consuming and will increase the time to market. Furthermore, this process makes it difficult to maintain a “first mover advantage.” Many authors in the literature suggest that in order to successfully grow a firm from the nascent to mature stages, various dimensions of the supply network (SN) such as resources, partners, supplier, customers, etc. must all be coordinated (Leibold et al., 2002; Sarasvathy & Dew, 2005; Voelpel et al., 2004). In particular, manufacturing value networks are a central part of building an effective business model (Simchi-Levi, 2010; Hills & Sarin, 2003; Jaworski, 2000). The aim of value network design and analysis, in the context of international networks, is to construct insights on the industry and develop mapping techniques for a more effective management of the supply chain and industry network. Hence, a supply network approach can provide a set of techniques that can offer insight on the interaction between various stages of the manufacturing value chain and allow entrepreneurs to manage their resources through effective supply chain strategies.

The research has informed development of approaches to the mapping and analysis of value creation and capture in complex industrial networks and methods to support the configuration of appropriate networks for the commercialisation of CIKC technologies

Research Outputs

Generic Industrial Systems Mapping Approach

Network Configuration Framework for Nascent, Emergent and Mature Industries (NEM Framework)

Conceptual Framework linking technology evolution, network configuration and product evolution (i.e. cube model)

Supply Network Stages/Modes of Emergence

Generic Industrial Systems Mapping Approach

This approach provides an initial overview of industrial system structure: identifying the key players including institutional, sector specialists and the principal supply chain actors. The approach can also be used to capture key linkages between industrial players and to identify firms involved in supporting major product categories. A review of the literature on international industrial networks specifically on historical approaches to industrial network/value chain mapping and analysis was conducted, is summarised in table 1, and was used to construct the final industrial system mapping process.

Table 1. Summary of key industrial network/value chain mapping and analysis literature by type,

objective and emphasis

Emerging Industry Supply Network (EI SN) case studies were selected based on industrial systems that exhibited different types of disruptive innovation as categorised in the literature review. The following industrial systems were examined:

• Emergence of product-service models within Defence Aerospace

• The transition of a Maritime cluster into a niche high-specification product supply

• The early evolution of firms supporting sustainable Built-Environments

• Technology Platform development in the UK Industrial Biotechnology industry (IB)

• Product generation changes in global Photovoltaics (PV)

• New routes to market within Last Mile Logistics

These cases include a mix of industrial systems that demonstrate new markets, technology platforms, new routes to market, and new product/service delivery models. In some cases, where there were multiple product categories (e.g. IB) or co-existing product-generations (e.g. PV) within the chosen

industrial system, at least one focal-firm from each product category/generation was used to capture the category-specific elements of industrial emergence. These mapping activities informed the creation of the industrial ecosystem maps to be used in subsequent analysis. Relevant focal Firm, Government and country specific advantages were captured to capture the context in which emergence was taking place. In summary, the final methodology involved the:

Identification of sector institutional players and secondary stakeholders e.g. research, industry development, specialist firms etc

Development of a Value Chain Process Map e.g. production processes and unit operations etc

Identification of the industry actors e.g. supply chain actors, organisational types, linkages between organisations, material, potential information and value flows etc

Technology process and product types e.g. Identification of substrates, process technologies etc The process (in the context of CIKC) was then used to map the UK plastic electronics sector (see also practice guidelines document) and is presented in Appendix I.

Network Configuration Framework for Nascent, Emergent and Mature Industries (NEM Framework) A second mapping tool (previously used extensively in configuring networks in more mature industries), was adapted and tested in the context of nascent and emergent industries. The term ‘network configuration’ is mainly used to describe the current “state” of a supply chain, its influence in the ecosystem and is often used to study value creation in emerging markets and understand firm strategy and innovation developments. It also highlights interdependent characteristics of the supply chain which is the basis for understanding possible strategies and types of organisations. The ‘selection’ of an appropriate Supply Network for an Emerging Industry is expected to be one of the keys in determining success. Companies which are the most successful in the immature phase of emergence are those which are fastest to market, whether through being able to attract early stage funding, or by being differentiated in technology or mode of delivery . However, a lack of understanding of the entire value chain and its supporting Supply Network will see these companies fail to exploit their potential as the industry matures. The network configuration approach used focuses on establishing patterns or profiles. According to configuration theory, the alignment of strategy, systems or practice is reflected in the patterns observed in practice. Firm-based configuration concepts are widely recognized in the strategic management and organisational structure literature. Strategic management literature has identified different types of configurations with distinguishable strategic objectives, target markets, critical resources, and operational behaviors (Chandler 1962; Khandwalla 1970; Rumelt 1974; Miles et al, 1978; Mintzberg 1979; Miller 1996). Firm configurations are usually described by the characteristics of organisational structures and coordination mechanisms (Chandler 1962; Mintzberg 1979; Miller 1996). Mintzberg (1979) considered configuration as a combination of certain characteristics of structure and situation which organisations naturally fall into. Organisations will not function effectively when such

characteristics are mismatched. Organisational elements should be logically configured into internally consistent groupings because they are usually interrelated in complex and integral ways (Miller 1986). Firms may be driven towards common configurations to achieve internal harmony among elements of strategy, structure and context (Miller 1986). Cohesive configurations are composed of tight constellations of complementary and mutually reinforcing elements, which could be predicatively useful because the number of possible ways in which constructional elements are combined is reduced. With this viewpoint, configuration can be viewed as a constellation of organisation elements that are pulled together by a unifying theme. The description of configuration includes a firm’s core mission and its fundamental means to accomplish the mission in a certain market, and the systems, processes, and structures to support the core operations.

In the recent years, business activities are increasingly dispersed across geography and ownership boundaries. There is a growing research community working on network configurations, especially in operations management and strategic management (Shi et al, 1998; Bozarth et al, 1998; Oltra et al, 2005; Zhang et al, 2007; Srai et al, 2008). Shi et al (1998) contended that the dispersion and coordination of manufacturing networks require different international manufacturing capabilities from the perspectives of efficiency, mobility, resource accessibility and learning ability. The dispersion dimension refers to the structure of a network; and the coordination dimension emphasises on the relationship between network members. Zhang et al (2007) identify four types of contextual environments of global engineering networks; capturing the core capabilities of engineering networks in each context and demonstrated the organisational features to deliver the capabilities. Engineering network configuration has been described from the perspectives of network structure, governance and coordination, and support infrastructure. The research introduces two new dimensions - governance system and support infrastructure, which have strong relationships with the capability and context of engineering networks. Srai et al (2008) describe the configuration of supply networks from the perspectives of network structure, flow of information and material between/within operation units; relationships between network partners; and product structure. The research highlights the importance of relationship with internal and external partners. Although different type of ‘products’ demand different network capabilities, and hence the network configuration to deliver the capability, products themselves should not be a part of supply networks.

The literature demonstrates the incremental process in understanding the organisational features of different types of networks, including intra-firm and inter-firm operations for manufacturing, engineering and service supply chain functions. For a network involving multiple players, these individual research strand inputs can be usefully integrated as:

Structure: to describe the geography footprint of a network, including the dispersion of network units and their interdependence, characterised by the degree of dispersion (dispersed v. concentrated), and the interdependence between engineering centres (independent v. interdependent).

Network Dynamics: to describe the operational processes adopted by network members, characterised by their degree of standardization (standard v. tailored /bespoke).

Governance and Coordination: to describe the governance system and coordination mechanism of a network, characterised by their degree of centralization.

Support infrastructure: to describe support infrastructures of a network, including IT systems, resources, people, and cultures, characterised by their degree of unification (uniform v. customised) and globalization (global v. local).

Relationships: to describe the linkage between network members, e.g. customers, suppliers and users, characterised by their strategic importance (strategic vs. tactical), degree of trust (trust vs. transactional), and scope (global v. local).

In addition, Table 2 summarises the different approaches to classifying stages of industrial emergence in the literature, particularly relevant to understanding potential SN dimensions of industry evolution. Most studies have traditionally been product or technology focused, with concepts of stage/gate processes dominating. Although there are some which pertain to the network in terms of its business structure and organisation, few have considered the role of the SN and the evolutionary phases through which they must pass as the industry itself transitions from emergence to a state of maturity. A common element of the models is the concept of phases of emergence. Some models go for three, (e.g. Hartigh), whereas at the other extreme as many as nine phases are reported. Sufficient level of granularity and discrimination will only be understood following multiple cross sector in depth case studies with a range of actors in industries at different levels of maturity.

As part of this study, it is postulated that within technological commercialisation, supply networks may be considered in three distinct phases:

Nascent - ‘embryonic, fragmented’ (weak, initial product focus and definition)

Emergent - ‘formation, expansion, stabilisation’ (alpha product development)

Mature -‘established networks with multiple archetypal forms’ (e.g. highly centralised networks focused on standardization, dispersed networks providing tailored solutions etc).

Within the context of the above framework, the Nascent and Emerging stages and parameters were considered in more detail based on the literature from table 2 and subsequent case studies, leading to the proposition that from the perspective of the supply network configuration technological/industrial emergence can be considered in five sub-phases:

Embryonic: ‘Chaotic’ phase with little or no structure. Weak, non-existent product definition

Fragmented: Phase describing increasing ‘order’ within the network; emerging commercial strategy and potential for partnering arrangements

Formation: This creation phase broadly covers the transition from viable pilot production of a new technology or delivery platform to a completed value chain with an end-user in the form of an early adopter. Characteristics include trust building, selection processes etc.

Expansion: At this point multiple customers begin to develop and competitive technologies emerge. The network elements undergo rapid and continual change as the value chain evolves

Stabilisation: The network here starts to cohere into the form it will take for a mature, viable industrial system. Clusters of network actors start to form, as collaborative models begin to gain traction over competitive technologically differentiated approaches

Table 2 – Stages of Emergence

The network configuration (NEM) framework (see Appendix II), adapted and tested as part of this research, can be used to visualise characteristics of nascent, emerging and mature technology supply chains at different stages of network evolution, in terms of these network configuration dimensions1.

1 Based on specific firm interests, three additional sub-dimensions (Production line, performance measure,

partnership-complementary product supplier) and an additional dimension (Intellectual property) were added to the framework as a means of preliminary investigation – still in progress.

Perspective Phases Reported Source Insight

Business Network Structure Innovation; Adaption; Market

Stabilisation

Hartigh et al. (2010) Links TLC to Network

Structure

Organizational Complexity Variation; Ferment; Selection;

Incremental Change

Tushman and

Rosenkopf (1992)

Links Organization

complexity to tech

change

Technology Life Cycle Invention; Introduction; Industrial

Production

Ortt and Schoormans

(2004)

Links tech readiness to

production volume

Competing Technologies R&D Build Up; Technical Feasibility;

Market Creation; Decisive Battle; Post-

Suarez (2004) Links tech readiness to

competitive forces

Innovation readiness lifecycle Concept; Components; Completion;

Chasm; Competition; Closedown

Tao, Probert & Phaal

(2010)

Links Tech readiness to

Market evolution

Technology Readiness Levels 9 Levels - Basic Principles to Actual

system proven

Mankins (1995) Focussed on Tech

Development

Stage Gate Approach Scoping; Build Business Case;

Development; Testing and Validation;

Cooper (1993) Product readiness

Product Lifecycle Innovation; Growth; Maturation; Decline Levitt (1965) Product readiness

Innovation Diffusion Innovators; Early Adopters; Early

Majority; Late Majority; Laggards

Rogers (1995) Business model link to

customer base

Network Maturity Basic Practices; Managed Processes;

Defined processes; Measured Processes;

Continuously Improved Processes

Capone et al. (1998) Applying process quality

descriptors to IT

networks

Innovation chain Generation; Conversion; Diffusion Hansen & Birkinshaw

(2007)

Links conversion of

ideas into revenue

Stages / Emergence Model Literature

Conceptual Framework linking technology evolution, network configuration and product evolution (i.e. cube model)

Previous academic research has described a well understood linkage between technology platforms and final product innovations. However, limited attention has been paid to the industrial system that ‘connects’ technology developments to final products. The frameworks adapted and tested in this research can provide a basis for understanding current and future Supply Network configurations, the industrial system in which it takes place and the interconnections between actors that need to take place to enable industry evolution. Appendix III identifies the industrial value chain, and how it re-configures to provide a linkage between technologies and technology options to product iterations. It runs orthogonal to the standard technology or product roadmaps and can be used to identify the industrial challenges in reconfiguring the industrial chain to new and emerging industries. The conceptual framework demonstrates the linkages between supply network ‘states’ or reconfiguration paths; linking industry structure (back-plate) and how the manufacturing value chain evolves from (1) an initial technology development, to (2) the formation of a supply network, to (3) a SN re-configuration process that supports new products and services.

Supply Network Modes of Emergence

The increasing focus on Emerging Industries with their inherent uncertainties is in some ways compounded by changes in the industrial landscape for mature sectors - arising from the twin impacts of globalisation and the dissolution of vertically integrated value chains. The importance of the evolution of Supply Networks (SNs) as an enabling element of industrial development has been identified in many studies, linking SN structure and configuration to innovation capability, for example, in terms of complexity (Choi and Krause, 2006), production dynamics (Kamath and Roy, 2007) and network configuration (Srai and Gregory, 2008).

The ‘selection’ of an appropriate Supply Network for an Emerging Industry is expected to be one of the keys in determining success (Sebastiao et al, 2008). Companies which are the most successful in the immature phase of emergence are those which are fastest to market, whether through being able to attract early stage funding, or by being differentiated in technology or mode of delivery . However, a lack of understanding of the entire value chain and its supporting Supply Network will see these companies fail to exploit their potential as the industry matures (Simchi-Levi, 2010). In response to changes in global industrial dynamics, new forms of Supply Network have emerged to ameliorate the growing uncertainty in supply and demand (Srai and Gregory 2008). These network types include: Network Integrators; Mass Customisation models; and global scale Single Product clusters. These network types provide new testing grounds for the ability of SN configuration to be linked to industrial emergence (Srai, 2007). Examples identified include;

production systems involving ‘system integrators’ that orchestrate the manufacture and

coordination of production and logistics enabling ‘fabless manufacturing’

global production networks, involving global scale production systems often located in new

centres of production and supply

new routes to market, involving web-facilitated delivery models that enable increasingly

customised delivery solutions providing more choice and flexibility

servitisation models involving integrated after-sales services to manufactured goods; these

service packages far from being ‘tagged on’ extras often generate the dominant revenue stream

or source of value capture

novel business models that provide unique products or services.

In this research, existing SN configuration analysis tools have been adapted and tested in an emerging industry context, in order to understand the impact of broader institutional, industrial and SN actors on industrial transition. Future work will examine the ways in which the configurations of these elements are linked to the relative performance of the firms involved, across a range of industrial sectors.

Conclusions and Future Work

An Industrial Ecosystem mapping methodology has been extended to and tested within the CIKC context. The approach combines and extends value chain footprint analysis with supply network configuration mapping. Using this methodology in a consistent manner provided a basis for the mapping of emerging industrial systems and an initial basis for cross-case analysis. This exploratory research examined six industrial systems using this methodology in order to better understand generic supply network dimensions of industrial emergence and their enabling network configurations. These industrial systems were selected on the basis of representing alternative and novel evolution paths that might provide an initial understanding of the key characteristics of emerging industry supply networks. Cross-case analysis suggests several generic aspects to EI SNs, including the blurring of industry boundaries, and the critical requirement to manage uncertainty in selective elements of the value chain. Alternative forms of EI SNs have been observed, in some product areas often co-existing. In the case of platform technologies that support multiple product categories, these are often ‘disconnected’ from their end-user markets. From a SN structure perspective the importance of particular SN actors in EI that provide ‘network integration’ and supply/demand balancing capabilities to actively manage supply and demand-side uncertainties are observed and include System integrators, Technology developers, Resource capturers, Asset diversifiers and material/information Consolidators each supporting particular EI evolution paths.

Five stages of industrial emergence from a supply network perspective are identified and suggest particular configurations (and capabilities) exist for each of these stages, themselves promoting specific emergence models. Furthermore, industry context is a critical enabler for EI supply networks, and these can be usefully captured as firm, country and government specific advantages and remain critical features of EI development.

Future Research

This work describes approaches and frameworks for assessing the ways in which supply networks can influence and shape emerging industries. Future research opportunities include further development of the conceptual framework linking technology evolution, network configuration and product evolution i.e. cube model (Appendix III), by integrating supply network and value chain configuration concepts, with product technology road-mapping frameworks, and/or scenario planning tools. The current study is limited by a small sample size of sector studies, and further industrial system case studies will be used to test and validate initial conclusions.

Acknowledgements

The authors would like to acknowledge the financial assistance provided by CIKC, and the industrial collaborators who provided access to organisations, supply network, industrial and institutional partners.

References Bartlett, C. A., Ghoshal, S., (1989) "Managing Across Borders: The Transnational Solution". Boston,

Massachusetts, USA: Harvard Business Press

Bozarth, C., McDermott, C., (1998),”Configurations in manufacturing strategy: a review and directions

for future research”, Journal of Operations Management, 16(4), 427-39.

Blumberg, D.F. (1999), “Strategic examination of reverse logistics and repair service requirements,

needs, market size, and opportunities'', Journal of Business Logistics, Vol. 20 No. 2, pp. 141-59

Chandler, A.D., (1962) “Strategy and Structure: Chapters in the History of the Industrial Enterprise”, MIT

Press, Cambridge, MA.

Choi, T. , Hong, Y., (2002) “Unveiling the structure of supply networks: case studies in Honda, Acura, and

DaimlerChrysler”, Journal of Operations Management, 20(5), 469-493.

Choi, T.Y. and Krause, D.R. (2006), “The supply base and its complexity: implications for transaction

costs, risks, responsiveness, and innovation”, Journal of Operations Management, 24/25, 637-652.

Fine, C., (1998). Clockspeed - Winning Industry Control in the Age of Temporary Advantage. New York:

Perseus Books.

Hartigh, E. D., & Asseldonk, T. V. (2004). Business ecosystems : A research framework for investigating

the relation between network structure , firm strategy , and the pattern of innovation diffusion. ECCON,

1-38.

Hills, S.B., Sarin, S., (2003),”From Market Driven to Market Driving: An Alternative Paradigm for

Marketing in High Technology Industries”, Journal of Marketing Theory & Practice, 11(3), 13-24

Hines, P., Rich, N., (1997) “The seven value stream mapping tools”. International Journal of Operations &

Production Management, 17(1), 46-64.

Jacobides, M.G. and Winter, S.G., (2007), "Entrepreneurship and Firm Boundaries: The Theory of A

Firm", Journal of Management Studies, Special Issue on Entrepreneurship and the Entrepreneurship of

the Firm, 44, 1213-1241.

Jagdev, H,S., Thoben, K.D., (2001) Anatomy of enterprise collaboration, Production Planning & Control,

12 (5) 437-51

Jaworski, B., Kohli, A.K., Sahay, A., (2000), “Market-Driven Versus Driving Markets”. Journal of the

Academy of Marketing Science, 28(1), 45-54

Kamath, N.B. and Roy, R. (2007), “Capacity augmentation of a supply chain for a short lifecycle product:

a system dynamics framework”, European Journal of Operational Research, 179, 2, 334-351.

Khandwalla, P.N., (1970) “The Effect of the Environment on the Organisational Structure of the Firm”,

Carnegie-Mellon University, Pittsburgh, PA.

Lambert, D. M., J. R. Stock, et al. (1998). Fundamentals of Logistics Management. Boston; London,

Irwin/McGraw-Hill.

Leibold, M., Probst, G., & Gibbert, M. (2002). Strategic Management in the Knowledge Economy: New

Approaches and Business Applications. New York.

Miles, R.E., Snow, C.C., (1978), “Organisational Strategy, Structure and Process”, McGraw-Hill, New York.

Miller, D., (1986),”Configurations of strategy and structure: towards a synthesis”, Strategic Management

Journal, 7, 233-49.

Miller, D., (1996),”Configurations revisited”, Strategic Management Journal, 17, 505-512.

Mintzberg, H., (1979), “The Structuring of Organisations: A Synthesis of the Research”, Prentice-Hall,

Englewood Cliffs, NJ.

New, S.J., Payne P., (1995),” Research frameworks in logistics: three models, seven dinners and a

survey”, International Journal of Physical Distribution and Logistics Management, 25 (10), 60-77

Oltra, M.J., Maroto, C., Segura, B., (2005),”Operations strategy configurations in project process firms”,

International Journal of Operations & Production Management, 25(5), 429-448.

Porter, M., (1986) “Changing patterns of International Competition”, California Management Review, 28

(2) 9-40.

Rother, M., Shook, J., (1999) Learning to See: Value Stream Mapping to Add Value and Eliminate Muda,

Lean Enterprise Institute, Brookline, MA

Rumelt, R.P., (1974), “Strategy, Structure, and Economic Performance”, Harvard Business School, Press,

Boston, MA.

Sarasvathy, S.D., (2001),"Causation and Effectuation: Toward a Theoretical Shift from Economic

Inevitability to Entrepreneurial Contingency". Academy of Management Review, 26(2), 243-263

Sarasvathy, S.D., & Dew, N., (2005), "New Market Creation through Transformation", Journal of

Evolutionary Economics, 15, 533-565.

Sebastiao, H.J., et al, (2008),” Supply Chain Strategy for Nascent Firms in Emerging Technology Markets”,

J. Business Logistics, 29(1) 75-91

Shi, Y., Gregory, M., (1998),”International manufacturing networks: to develop global competitive

capabilities”, JOPM, 16, 195-214

Simchi-Levi, D. and Fine, C.H. (2010) “Your next supply chain”, MIT Sloan Management Review, 51, 2, 17-

25.

Slack, N. et al, (1995), Operations Management, Pitman Publishing, London

Slack, N. (2005) Patterns of Servitization: Beyond Products and Service, Cambridge: Institute for

Manufacturing, Cambridge University.

Srai, J. (2007) “Global Solutions”, Manufacturing, 86, 5, 32-35.

Srai, J.S. & Gregory, M. (2008) “A supply network configuration perspective on international supply chain

development”, International Journal of Operations & Production Management, 28(5), 386 – 411.

Sturgeon, T., Gereffi, G., (2008) “Value Chains, Networks, and Clusters: Reframing the Global Automotive

Industry,” Journal of Economic Geography, 8(3), 297-321.

Suarez, F.F., (2004), "Battles for technological dominance: an integrative framework", Research Policy,

33(2), 271-286

Tushman, Michael and Philip Anderson. (1986). “Technological discontinuities and organisational

environments”. Administrative Science Quarterly, 31: 439-465.

Voelpel, S.C., Leibold, M., & Eden, B.T. (2004). The Wheel of Business Model Reinvention: How to

Reshape Your Business Model to Leapfrog Competitors. Journal of Change Management, 4(3), 259-276.

Winter, S. G., Szulanski, G., (2001),” Replication as strategy”. Organisation Science, 12(6), 730-743

Zhang, Y., Gregory, M., Shi, Y., (2007),”Global Engineering Networks (GEN): The Integrating Framework

and Key Patterns”, Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering

Manufacture, 221, 1269-1283.