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Organizing to Gain from User Interaction: The Role of Organizational Practices for Absorptive
and Innovative Capacities
Nicolai J Foss Center for Strategic Management and Globalization
Porcelainshaven 24; 2000 Frederiksberg; Denmark; [email protected]
Keld Laursen
DRUID, Department of Industrial Economics and Strategy Copenhagen Business School
Solbjergvej 3; 2000 Frederiksberg Denmark; [email protected]
Torben Pedersen
Center for Strategic Management and Globalization Porcelainshaven 24; 2000 Frederiksberg;
Denmark; [email protected]
First draft; very preliminary, please don’t cite or quote Word count, main body: 5150
2 October 2005
Keywords Absorptive capacity, user innovation, knowledge sharing, strategic HRM practices. JEL Codes L2, O31, 032 Paper prepared for the workshop “Organizing the Search for Technological Innovation” to be held at the Copenhagen Business School, Friday October 7th, 2005
Organizing to Gain from User Interaction: The Role of Organizational Practices for Absorptive
and Innovative Capacities
Abstract We address how organizational practices may leverage the knowledge absorption from users in the context of innovation. We focus on practices that enhance communication and knowledge sharing between management and employees and between departments, and on pecuniary rewards for engaging in knowledge sharing. Such practices leverage knowledge absorption and lead to higher innovative capacity. Thus, we identify some of the organizational dimensions of absorptive capacity that are needed to benefit from the “user innovation model” and provide quantitative support for the propositions put forward. The paper draws on a survey of 169 Danish private firms. The survey was implemented in 2001 among a sample of the 1000 largest Danish manufacturing and service firms.
I. Introduction The ability of firms to innovate is a central component in gaining, renewing and sustaining
competitive advantage. Empirical studies demonstrate that innovative firms tend to have
higher rates of profits, greater market value, better credit ratings and stronger chances of
surviving in the market (Geroski, Machin and van Reenen, 1993; Hall, 2000; Cefis and
Marsili, 2003; Czarnitzki and Kraft, 2004). In addition, the notion that interaction with users
matter crucially for product and process innovations in a large number of industries has been
well recognized for more than three decades. Early important contributions, such as Linder
(1961), Freeman (1968), Rothwell et al.(1974), von Hippel (1976) and Rosenberg (1982) all
ascribe central roles to users in interacting with producers in order to improve given products
or processes, either by providing important knowledge and information to the producer or by
directly participating in making innovations. Subsequently, a large literature has emerged
that analyzes key benefits and obstacles to user involvement in the innovation process (see
for instance, Henkel and von Hippel, 2005, for an overview). Nevertheless, despite the
substantial attention paid to the role of users in the innovation process, little effort has been
devoted to understanding how (producer) firms need to adjust their internal organization to
be better able to benefit from interaction with users.1
Taking Cohen and Levinthal’s (1989; 1990) celebrated notion of “absorptive capacity”
as the point of departure, we examine how firms should adjust their internal organization so
as to be better able to gain from working with users. The contribution of the paper is two-
fold. The first main contribution is to place absorptive capacity in a novel setting, namely
that of “user innovation,” as described above. Second, we take an approach to explaining
absorptive capacity that differs from the literature by addressing the intra-firm,
organizational antecedents of absorptive capacity. Although the pioneering Cohen and
Levinthal (1989; 1990) contributions explicitly mention intra-organizational antecedents,
they have been neglected in the literature which has mainly taken a knowledge-based
approach, stressing firm-level knowledge as the critical antecedent of absorptive capacity.
Relatedly, we believe our approach is more micro-analytic than is usually the case in
the literature by looking into how aspects of internal organization impacts absorptive
capacity. Thus, we address how organizational practices may leverage the knowledge
absorption from suppliers and, in particular, users. In particular, we hypothesize that 1 In contrast, there is a substantial literature on how user firms should adapt their organizations in response to
the adoption of innovations (see for instance, Leonard-Barton and Sinha, 1993; Bresnahan, Brynjolfsson and Hitt, 2002).
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practices that are conducive to intra-firm knowledge sharing, including practices enhancing
communication and knowledge sharing between management and employees and between
departments, but also pecuniary rewards for engaging in knowledge sharing, will leverage
knowledge absorption and lead to higher innovative capacity. The empirical part of the paper
draws on a survey of 169 Danish private firms. The survey was implemented in 2001 among
a sample of the 1000 largest Danish manufacturing and service firms.
In sum, the contribution of this paper is to identify some of the organizational
dimensions of absorptive capacity that are needed to benefit from the “user innovation
model” and to provide quantitative support for the propositions put forward.
II. Absorbing External Knowledge:
The Role of Organizational Practices The Role of Users in Product Innovation
The notion that users can play an important role in the innovative process is hardly a new
one. Thus, Linder (1961) noted, in the context of the “home market” theory of international
trade, that “[i]f, for some odd reason, an entrepreneur decided to cater for a demand which
did not exist at home, he would probably be unsuccessful as he would not have easy access
to crucial information which much be funneled back and forth between producers and
consumers. The trial-and-error period which a new product almost inevitably must go
through on the market will be more embarrassing costwise, the less intimate knowledge the
producer has of the conditions under which the product will be used” (1961: 89). Von Hippel
(1976) documented that more than 80 per cent of innovations in the scientific instrument
industry were invented, prototyped and first field-tested by users of instruments rather than
by an instrument manufacturer. Subsequently, von Hippel and colleagues focused their
research on the idea of lead users (see for instance, Urban and von Hippel, 1988). More
recently, Chesbrough’s (2003a; 2003b) work on the “Open Innovation” model has increased
the attention paid to the role of external sources (including users) in the innovation process,
in business as well as in academic circles. Even more recently, researchers have turned their
attention towards the benefits firms can achieve through the interaction with user
communities established by users themselves (see for instance, Lüthje, 2004) or by firms
(see for instance, Jeppesen, 2005).
The explanation for why users contribute sometimes by investing large amounts of
money and other resources to the innovation process is two-fold. First, users may in many
cases be the main beneficiaries of the innovation (von Hippel, 1988). For instance, an airline
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may gain competitive advantage by being the first adopter of a newly developed fuel-
efficient airplane. In such a situation the airline has an incentive to co-develop the airplane
with the producer (see Rosenberg, 1982, for a historical analysis of the role of users in
aircraft development). Second, users often posses difficult-to-transfer local knowledge or
knowledge that is “sticky” (von Hippel, 1998). Stickiness may be caused by various
attributes of knowledge itself, such as the way it is encoded (in the form of tacit or codified
knowledge) or it may be caused by the attributes of the agents seeking or providing
knowledge (e.g., their cognitive and motivational capacities). As an example, the airline may
possess knowledge about the performance and operating characteristics of the plane that may
turn out to be an essential input in the modification of the airplane knowledge that the
producer will not have access to without direct collaboration with the airline (Rosenberg,
1982: 124). It is a common recognition in the user-innovation literature that firms and user
firms need to hone their capabilities of cooperating, typically through long-term
collaborative efforts. In more recent parlance, such cooperation improves the capacity of the
user firm to transmit knowledge that may be useful in the innovation process and it improves
the capacity of the innovator firm to absorb such knowledge.
Absorptive Capacity
Pioneered by Cohen and Levinthal (1989, 1990), the notion of absorptive capacity has been
not only very influential, but also much debated with respect to its reach (e.g., on which
organizational levels does absorptive capacity exist?), nature and implications (e.g. Zahra
and George, 2002; Bosch, van Wijk and Volberda, 2003). A key attraction of the notion is
that it directs attention to the mechanisms that lie between external knowledge and firm-level
innovation performance. We follow Cohen and Levinthal in arguing that the ability to
exploit external knowledge is a critical component of innovative performance (1990: 128).
However, in spite of the size and richness of the literature on absorptive capacity, the notion
itself remains a label for a complex interaction of behaviors, organizational practices and
knowledge bases in firms, much of which is not well understood. We seek to better
understand the role that organizational practices play in the process. Moreover, whereas
Cohen and Levinthal examine the absorptive capacity needed for acquiring external
knowledge in general, we specifically analyze the role of costumers as sources of knowledge
and information for the innovative performance of firms, when compared to their main
competitors and how the internal organization needs to function in order to reap the potential
fruits from user-involvement in the innovation process. We argue that an important part of
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absorptive capacity is constituted by (complementary) human resource management
practices, and that therefore, such practices are key mediators of the relation between
external knowledge sources in particular users and firm-level innovation performance.
Intra-Firm Knowledge Transfer and Sharing
Sticky knowledge is knowledge that is difficult to transfer between and within organizations.
In an influential paper, Kogut and Zander (1992) argue that what firms do better than
markets is the sharing and transfer of knowledge of individuals and groups within an
organization. Following Schumpeter (1912/1934), Kogut and Zander go on to argue that
innovations are the product of a firm’s “combinatory capabilities” to generate new
applications from existing knowledge. In this view, firms gain competitive advantage by
being able to create and transfer knowledge more efficiently than competitors.
One stream within the knowledge transfer/sharing literature looks at product innovation
and examines the impediments to knowledge transfer among subunits within the firm
(Leonard-Barton and Sinha, 1993; Henderson and Cockburn, 1994; Szulanski, 1996). It is
argued that close and frequent interactions between R&D and other functions, teams and
other subunits leads to superior performance because such interactions lead to better
integration and coordination of different bodies of knowledge. Another stream of literature
examines the (possible) positive effects of knowledge sharing within firms. Within this
stream, Tsai and Ghoshal (1998) follow Kogut and Zander in asserting that innovations are
created through new combinations of resources and that knowledge sharing is one
mechanism for recombining existing resources. They proceed to empirically demonstrating
that intra-organizational knowledge sharing affects business unit product innovation
positively. Building on Granovetter (1973) and Winter (1987), Hansen (1999) argues and
empirically substantiates that intra-organizational knowledge sharing affects project
completion time. An important argument is that although weakly tied project teams have an
advantage in terms of their search ability, such teams have a problem transferring highly
complex knowledge, because they are likely to incur transfer problems due to poor
interaction with the source unit.
Yet another stream of literature examines the role of networks for knowledge sharing.
Tsai (2001) argues that if organizational units occupy a more central network position, they
perform better in terms of innovation. Social networks facilitate new knowledge creation
within organizations. Hansen (2002) develops a concept of “knowledge networks” to explain
why some business units are able to take advantage of knowledge that resides in other parts
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of the organization while other unit may not be. The key of the concept is that an
understanding of effective inter-unit knowledge sharing in a multi-unit firm needs the
consideration of relatedness in knowledge among business units and that a network of
horizontal inter-unit connections that may enable units to retrieve related knowledge.
In a later paper, Tsai (2002) investigates the effectiveness of coordination mechanisms
on knowledge sharing in intra-organizational networks in various part of the organization. It
is argued that social interaction allows individual units to accumulate social capital that can
help them gain access to new knowledge or new information and that the flows of
information or knowledge through inter-unit networks require social interaction to promote
trust. The findings indicate that formal hierarchical structure, in the form of centralization,
has a significant negative effect on knowledge sharing. In contrast, informal lateral relations,
in the form of social interaction, have a significant positive effect on knowledge sharing.
However, no matter knowledge sharing is best promoted, such sharing practices are
perhaps best viewed as one component of a set of complementary organizational practices.
We will discuss this view in the following.
Hypotheses
Complementary organizational practices. During the last decade increasing use has been
made in economics and management of the notion of Edgeworth complementarities
(Milgrom and Roberts, 1990; Milgrom, Qian and Roberts, 1991; Aoki and Dore, 1994;
Holmström and Milgrom, 1994 ; Milgrom and Roberts, 1995; Holmström and Roberts,
1998; Baron and Kreps, 1999). As Milgrom and Roberts define it, complementarity between
activities obtains if “… doing more of one thing increases the returns to doing (more of) the
others” (Milgrom and Roberts, 1995: 181).
This literature has been paralleled (in some cases followed) by a very substantial in
both economics as well as in management research empirical literature, examining the
performance implications of “new” complementary human resource practices within firms
(see for instance, Huselid, 1995; Ichniowski, Shaw and Prennushi, 1997; Whittington et al.,
1999; Mendelson, 2000; Capelli and Neumark, 2001; Laursen and Foss, 2003; Michie and
Sheehan, 2003; Galia and Legros, 2004; Datta, Guthrie and Wright, 2005).2 In this paper, we
focus on practices that are conducive to knowledge sharing in general, including practices
2 Another stream of literature has examined the complementarity of HRM practices on the one hand and
information technology on the other (see for instance, Brynjolfsson and Hitt, 2000; Bresnahan, Brynjolfsson and Hitt, 2002). In this paper we focus solely on complementarities among different HRM practices.
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that enhance communication and knowledge sharing between management and employees
and between departments, as well as pecuniary rewards for engaging in knowledge sharing.
Such practices can be conducive to innovative capacity for a number of reasons. With
respect to process innovations/improvements, one notable feature of many new
organizational practices/HRM practices is that they increase de-centralization in the sense
that problem-solving rights are increasingly delegated to the shopfloor. Accomplished in the
right way, this amounts to delegating rights in such a way that they are co-located with
relevant knowledge, much of which may be highly sticky (and thus require decentralization
for its efficient use). In other words, increased delegation may better allow for the discovery
and utilization of local knowledge in the organization, particularly when there are incentives
in place that foster such discovery (Hayek, 1948; Jensen and Meckling, 1992). Thus, much
of the ability of Japanese firms to engage in ongoing, incremental process innovation has
often been ascribed to a successful co-location of problem rights and localized knowledge
combined with appropriate pecuniary and non-pecuniary incentives (Aoki and Dore, 1994).
Relatedly, the increased use of knowledge sharing practices that is an important
component in the package of new HRM practices also means that better use can be made of
local knowledge, leading to improvements in processes and perhaps also to minor product
improvements. However, different individuals sharing knowledge can do something more,
since such sharing often involves different human resource inputs. This may imply that
individuals or groups bring together knowledge that hitherto existed separately, potentially
resulting in non-trivial process improvements or “new combinations” that lead to novel
products (Schumpeter, 1912/1934; Kogut and Zander, 1992; Tsai and Ghoshal, 1998).
Generally, increased knowledge sharing, for example, through job rotation, and increased
information dissemination, for example through IT, may also be expected to provide a
positive contribution to the firm’s innovation performance, for rather obvious reasons. In
sum, we propose the following hypothesis:
H1 Increased knowledge sharing within the focal firm leads to an increased
innovative capacity of that firm.
The implementation of new organizational practices, such as knowledge sharing, will often
be associated with extra effort or with disutility of changing to new routines and procedures.
Employees will have to be somehow compensated. Thus, we would expect many new
organizational practices to work well (in terms of both profits and innovation performance)
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only if accompanied by some form of remuneration schemes.3 Recent empirical evidence
supports the claim that many new HRM practices work well only if accompanied by new
incentive-based rewards (Ichniowski, Shaw and Prennushi, 1997; Gittleman, Horrigan and
Joyce, 1998; Laursen and Foss, 2003). In sum, the preceding discussion leads us to offer the
following two hypotheses:
H2 Firms that make use of delegation will also make pay more dependent on
knowledge sharing.
H3 Simultaneous use of delegation of responsibility and salaries linked to knowledge
sharing lead to increased knowledge sharing within firms.
The demands of interaction with users. While the previous section highlighted the
sometimes very strong positive effects for producers from interacting with users of a new
product, there are also effects on the internal organization of the producer firm, since the
organization has to be aligned so that it is in position to absorb the benefits from
collaborating with users. In other words, firms need to get its organizational “absorptive
capacity” right in terms of the internal human resource practices it applies. As pointed out
above, interaction with users in the context of product or process innovation involves the
transfer or exchange of, often, large amounts of knowledge and information. In such an
environment, it is crucial that the knowledge or information transferred into the firm is
distributed to other relevant parts of the firm. Accordingly, we submit:
H4 Interaction with users leads to a higher degree of knowledge sharing within
firms.
Firms often apply “gatekeepers” (Allen, 1977) to connect a research team with external
sources of knowledge, while also filtering out unnecessary noise. In this context, it is
imperative that gatekeepers have both mechanisms and incentives to share the knowledge
with the rest of the relevant part of the organization (such as a research team). Such
mechanisms and incentives are provided by “new” human resource management practices, 3 The opposite point can also be made; not only are incentives needed to make knowledge-sharing work
other practices are also needed to make incentives work. For instance, Kandel and Lazear (1992) show that introducing a profit-sharing plan for all workers in a firm may have little or no impact on productivity unless it is linked with other practices that address the inherent free rider problem associated with corporate wide profit sharing plans.
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including knowledge sharing, delegation of responsibility and performance pay linked to
knowledge sharing. One such rather straightforward incentive for knowledge sharing is the
attempt to link salaries to successful knowledge sharing. One important mechanism for
knowledge sharing is delegation of responsibility. Delegation of responsibility is important
when processing and absorbing knowledge and information from users, because in such
information-rich environments, gatekeepers and other staff working with users (often
through gatekeepers) need to be granted decision rights with respect to the direction of
the innovation project, since they are the ones who are best able to implement and govern the
inputs from users. In other words, the reason for delegating to employees working with users
is that such employees can be said to have superior knowledge when compared to the firm’s
formal management team.
Nevertheless, knowledge sharing organizational practices (and other complementary
organizational practices) may not only diffuse “user-knowledge” within the organization, it
may also help hinder conflicts of the “Not Invented Here” (NIH) syndrome type (Katz and
Allen, 1982). Katz and Allen (1982: 7) define the NIH syndrome as “...the tendency of a
project group of stable composition to believe that it possesses a monopoly of knowledge in
its field, which leads it to reject new ideas from outsiders to the detriment of its
performance.” The NIH syndrome suggests that greater attention to external sources of
knowledge may meet with internal resistance from at least some of the company’s technical
staff. Accordingly, to the extent that the resistance to external solutions is due to the lack of
in-depth knowledge of the possible external(ly assisted or developed) solution, knowledge
sharing may also help to legitimize the application of external knowledge and information.
In sum, we propose:
H5 The application of delegation of responsibility and salaries linked to knowledge
sharing is leveraged by knowledge interaction with users.
Taken together, the five above hypotheses constitute an interlinked structural equation model
(see Figure 1 below). However, before the empirical relevance of the model can be
examined, it needs to be operationalized.
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III. Data and Analysis Sampling and Data
Our sampling frame is Danish firms and the data collection was conducted as a survey
among the largest firms in Denmark. Specifically, the questionnaire was submitted to the
1.000 largest firms in Denmark, covering a wide spectrum of Danish industry including
manufacturing as well as service firms. In the context of the present paper, focusing on
largest firms makes particular sense because it is arguable that such firms are
disproportionately more engaged in innovation activities and are similarly more likely to
have explicitly formulated organizational policies relating to knowledge sharing, delegation
and incentive pay.
In 2001, all Danish firms with a turnover in excess of US $ 1 mio. (in 2000) received a
questionnaire. After two reminders, a total of 207 firms responded to the survey providing a
response rate of 21 percent. However, as important questions were missing in some of the
questionnaires, only 169 responses were usable for statistical analysis. The questionnaire
was submitted to the CEO of the firm. Although the CEO responded in most cases, in some
cases the HRM-manager or other managers have responded. The average number of
employees in the 169 firms included in the data set is 1.811 employees, with a large
variation between some very large firms in one end and a number of medium sized firms
with approx. 350 employees in the other end. Therefore, the survey mainly covers large and
medium sized firms in Denmark, and not the small firms. The firms are on average
generating 28 percent of their turnover abroad, which indicates that they are highly
internationally oriented with substantial sales abroad.
Construct Analysis
The hypotheses are tested in a LISREL model that allow for simultaneous formation of
underlying constructs (the measurement model) and test of structural relationships among
these constructs (the structural model). The validity of LISREL models is estimated by the
validity of the entire model, i.e., by the nomological validity. But before estimating the
nomological validity of the model, with the causal relations specified, it is important to judge
the convergent validity, i.e., the homogeneity of the constructs included in the model, and
the discriminant validity, i.e., to what extent the constructs are independent. First, however,
we describe the operationalization of the constructs included and, and we then evaluate the
different forms of validity.
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Interaction with customers. This construct mirrors the extent to which the focal firm is
involving costumers in its innovation activities. It includes two items measured on a 7-point
Likert-type scale from 1 (not at all) to 7 (to a very large extent). We asked managers to what
extent are you 1) involving customers in development projects, and 2) communicate
extensively with customers. The responses indicate the degree of openness towards
involvement of customers in innovation activities.
Delegation. Delegation reflects the extent to which responsibilities are delegated to
employees in the firm. The construct is based on three items all measured on a 7-point
Likert-type scale (1= not at all and 7 = to a very large extent). We asked to what extent 1) do
employees influence their own job, 2) are suggestions from employees realized, and 3) is
communication between management and employees smoothly. Taken together these three
items are forming a construct for the level of delegation in the firm.
Salary and knowledge sharing. This construct is measuring to what extent the salary is
associated with knowledge sharing, i.e., to what extent the salary is used to create incentives
for knowledge sharing. It is based on two items, where managers are asked to indicate on a
7-point Likert-type scale (1= not at all and 7 = to a very large extent) the extent to which 1)
the salary is associated with ability and willingness to share knowledge, and 2) the salary is
determined by the willingness to improve skills and upgrade knowledge.
Knowledge sharing. Knowledge sharing is a measure of the extent to which knowledge
is shared in the focal firm both among employees and between management and employees.
Two items is making up the construct, where respondents are asked 1) to what extent is
employees sharing information across departments, and 2) the smoothness of communication
between management and employees (both on a 7-point scale going from 1 = not at all to 7 =
to a very large extent).
Innovation capacity. Reflects the level of innovativeness in the focal firm. The
construct consists of two items, where managers are asked 1) to rate the innovativeness of
the focal firm compared to the competitions (on a 7-point scale going from 1 = far below
average to 7 = far above average), and 2) the extent to which the focal firm’s strategy is to
create knowledge and intellectual capital (on a 7-point scale going from 1 = not at all to 7 =
to a very large extent).
A measurement model is created in order to assess convergent and discriminant
validity. In Table 1, convergent validity is judged by the R2-values measuring the strength of
the linear relationships, the t-values, a significance test of each relationship in the model, and
the factor loading for each indicator (Jöreskog and Sörbom, 1993). The constructs in this
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LISREL model all have good convergent validity, i.e., they are homogeneous constructs. As
can be seen from Table 1, the strength of the linearity in relations between constructs and
items is in most cases relatively strong. For two of the items, the relation is somewhat
weaker, with R2-values of 0.29, but clearly above the usual threshold of 0.20 for the R2-
value. Although the R2-values of these items are lower, they are nevertheless highly
significant judging from their t-values (6.58 and 4.50, respectively). This and the fact that
the items together constitute an important dimension of the construct from a theoretical point
of view are the reasons for keeping it as an item in the model. From Table 1 we can also
conclude that the t-values for all items are highly significant (all above 3.84) and that their
(standardized) factors loadings are strong (all above 0.42).
The second step in the analytical process is to form the structural model by specifying
the causal relations in accordance with the hypotheses. We test single causal relations with t-
values and factor loadings between the constructs in the model. We assess the entire model
by chi-squares (normal theory weighted least squares) and degrees of freedom and a
probability estimate (p-value), which is a test of a non-significant distance between data and
model, i.e., nomological validity (Jöreskog and Sörbom, 1993).
[Table 1, just about here]
Results
Through repeated iterations, a LISREL analysis proceeds with the fine-tuning of the model
to obtain a more coherent representation of the empirical data. The purpose of the LISREL
analysis is to arrive at and confirm a model consisting of specified causal relations. Thus, in
the test, we generate a structural model that contains significant relationships in accordance
with the stipulated hypotheses (see Figure 1, for a graphical representation of our model).
The presented model is highly significant with, X2(d.f. 21) = 26.29, p = 0.20 in the sense that
the test of significant distance between data and the model is rejected, indicating that the
model gives a good representation of the data. The Goodness of fit index (GFI) is 0.97. The
figures given are standardized factor loadings of causal relations with t-values in parentheses
(those in bold relate to the structural model).
[Figure 1, just about here]
With respect to Hypothesis 1 (“Increased knowledge sharing within the focal firm
leads to an increased innovative capacity of that firm”) it can be seen from Figure 1 that the
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results are consistent with the hypothesis, since the parameter estimate for the effect of
knowledge sharing on innovation capacity is positive and highly significant (t-value of 4.48).
We also find support for Hypothesis 2 (“Firms that make use of delegation will also
make pay more dependent on knowledge sharing”), as our model exhibits a strong
covariance between the use of delegation on the one hand, and the use of salaries linked to
knowledge sharing, on the other.
Relatedly, we find evidence supporting H3 (“Simultaneous use of delegation of
responsibility and salaries linked to knowledge sharing leads to increased knowledge sharing
within firms”), since first, salaries linked to knowledge sharing and delegation are strongly
linked (as noted in Hypothesis 3), and, second, because they jointly lead to increased
knowledge sharing within the organization. It should be noted, however, that the effect of
delegation on knowledge sharing is stronger (coefficient estimate of 0.72) than the effect of
incentives in terms of salaries linked to knowledge sharing (coefficient of 0.36).
The evidence is not strictly consistent with Hypothesis 4 (“Interaction with users leads
to a higher degree of knowledge sharing within firms”), since, although the parameter for the
direct effect has the expected positive sign, it is insignificant. In other words, it seems that
the positive effect on knowledge sharing from interacting with users is not a direct one
(nevertheless, we detect an indirect effect; see below). In contrast, we find support for the
conjecture made in Hypothesis 5 (“The application of delegation of responsibility and
salaries linked to knowledge sharing is leveraged by knowledge interaction with users”), as
interaction with users appears to induce both the use of salaries based on knowledge sharing
(a significant coefficient of 0.52) and delegation of responsibility (a significant coefficient of
0.39). Accordingly, while we do not find evidence supporting a direct effect on knowledge
sharing from interacting with costumers, we find that interaction with consumers does
influence knowledge sharing but indirectly so through the effect on the use of salaries
linked knowledge sharing and through the effect on delegation (Hypothesis 5) practices
which in turn both affect knowledge sharing (Hypothesis 3). Consequently, we find some
support for Hypothesis 4, although the direct effect was too weak to be supported by our
empirical analysis.
IV. Concluding Discussion Contribution to Existing Theory
A prevalent theme in the strategic management and innovation literatures is that firms
increasingly need to rely on external knowledge sources to build, renew and sustain
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competitive advantages. However, how well firms can undertake such sourcing of external
knowledge depends on their level of absorptive capacity.
The contribution of this work has been to take steps towards opening the black box of
absorptive capacity, specifically exploring how organizational practices influence the link
from user knowledge to firm innovative capacity. This is a neglected perspective in the
absorptive capacity literature, although Cohen and Levinthal (1989; 1990) were quite
explicit that the organizational dimension is important. To be sure, some work exists on how
organizational factors impact absorptive capacity (or related constructs). However, most of it
is either focused on product development function (see for instance, Cockburn and
Henderson, 1998; Negassi, 2004; Leiponen, 2005; Penner-Hahn and Shaver, 2005) or take a
sociological, network approach where the role of social links in leveraging information is
central (see for instance, Tsai, 2001; Reagans and McEvily, 2003). In contrast, the present
work considers organizational practices more broadly and is not limited to product
development. Specifically, we have developed hypotheses that relate to the organizational
practices of knowledge sharing, delegation, and performance pay. Our results strongly
support the basic notion that indeed such organizational practices influence how external
“user knowledge” is leveraged into innovative capacity.
Limitations and Future Work
This paper has addressed the issue of how the use of costumers’ knowledge affects the
organizational practices used by an organization, and how such practices help diffusing
external knowledge to the benefit of the organization’s capacity to innovate. However,
costumers are not the only source of external knowledge that influences a producer firm’s
ability to innovate. Indeed, recent work by Chesbrough (2003a; 2003b) claims that
innovative firms are increasingly changing their sourcing of new knowledge to an “open
innovation” model that implies the use of a wide range of external actors and sources to help
them achieve and sustain innovation. Also the earlier notion of “distributed innovation” (von
Hippel, 1988) suggests that external knowledge can be obtained from several external
sources. Moreover, Baum, Calabrese and Silverman (2000), show that within biotechnology,
innovators rarely innovate alone, while Laursen and Salter (2006) empirically demonstrate
that a firm’s ability to produce product innovations is strongly influenced by the openness of
the firm’s external search strategy in terms of the number of external sources of knowledge
applied by the firm. Accordingly, the present study is limited to dealing with the effects of
user interaction, mediated by organizational absorptive capacity in the form of organizational
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practices related to knowledge sharing. Future research should be expanded to deal with the
appropriate organizational response to a much wider range of external knowledge inputs
included in the “open innovation model.”
14
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18
Table 1: Constructs and items
Constructs and items Factor loading*
t-value R2-value
Interaction with customers Are customers involved in development projects? 0.55 6.44 0.30 Are you communicating extensively with customers? 0.89 8.46 0.80 Delegation Do employees have influence on their own job? 0.73 4.72 0.53 Are suggestions from employees are realized? 0.42 3.84 0.27 Salary and knowledge sharing Is the salary associated with the ability and willingness to share
knowledge? 0.80 10.99 0.64
Is the salary determined by the willingness to improve skills and upgrade knowledge?
0.79 10.76 0.62
Knowledge sharing Sharing of information among employees is very common 0.54 6.58 0.29 Is communication between management and employees
smoothly? 0.73 6.33 0.53
Innovation capacity The innovativeness of the focal firm compared to the competitions 0.44 4.50 0.29 Firm strategy to create knowledge and intellectual capital 0.67 5.91 0.45
* all factor loadings are highly significant at p < 0.01 with t-value above 3.84.
19
Figure 1: The Model
Knowledge sharing
Smooth communication
Innovativeness 0.54 (6.58)
0.73 (6.33)
Innovation capacity
0.67 (5.91)
0.44 (4.50)
0.71 (4.48)
Create intellectual capital
0.39 (3.51)
Salary linked to knowledge
sharing
Willingness to improve skills
Ability to share
Delegation
Interaction with costumers 0.14 (0.77)
0.79 (4.23)
0.36 (1.89)
0.72 (4.30)
0.52 (4.17) Involved in deve-lopment projects
0.55 (6.44)
0.89 (8.46) Communicating with consumers
0.80 (10.99) 0.79 (10.76)
Sharing of information among employees
0.73 (4.72)
Influence on own job
0.42 (3.84)
Suggestions realized