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; njf.smg@cbs.dk

Keld Laursen

DRUID, Department of Industrial Economics and Strategy Copenhagen Business School

Solbjergvej 3; 2000 Frederiksberg Denmark; kl.ivs@cbs.dk

Torben Pedersen

Center for Strategic Management and Globalization Porcelainshaven 24; 2000 Frederiksberg;

Denmark; tp.int@cbs.dk

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.”

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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.

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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