Research Paper
Open Innovation in Small and Medium-Sized Enterprises (SMEs): External Knowledge Sourcing Strategies and Internal Organizational Facilitators by Sabine Brunswicker and Wim Vanhaverbeke
In this paper we explore how small and medium-sized enterprises (SMEs) engage in external knowledge sourcing, a form of inbound open innovation. We draw upon a sample of 1,411 SMEs and empirically conceptualize a typology of strategic types of external knowledge sourcing, namely minimal, supply-chain, technology-oriented, application-oriented, and full-scope sourcing. Each strategy reflects the nature of external interactions and is linked to a distinct mixture of four internal practices for managing innovation. Both full-scope and application-oriented sourcing offer performance benefits and are associated with a stronger focus on managing innovation. However, they differ in their managerial focus on strategic and operational aspects.
Introduction The burgeoning literature on open innova-
tion highlights the role of external sources of knowledge. Scholars agree that sourcing of external knowledge for innovation is a critical process of a firm’s inbound open innovation activities, where external knowledge flows into the organization (Chesbrough, Vanhaverbeke, and West 2006; Dahlander and Gann 2010). Early qualitative case study contributions show how large firms such as P&G, IBM, and Xerox moved away from relying solely on their internal research and development (R&D) and purpo- sively source external knowledge for innovation (Chesbrough 2003; Dodgson, Gann, and Salter 2006). Quantitative empirical studies on exter- nal knowledge sourcing provide evidence that involving a large number of external sources of
knowledge in innovation is a promising choice for large firms (Lakhani et al. 2007; Laursen and Salter 2006). Open innovation scholars also agree that external sourcing of knowledge does not replace in-house R&D and highlight the importance of “absorptive capacity,” which allows firms to identify, absorb, and make use of external knowledge (Cohen and Levinthal 1990; Dahlander and Gann 2010).
Despite its relevance, the literature also has many gaps. First, small and medium-sized enter- prises (SMEs) are excluded from the mainstream discussion on open innovation (exceptions are Lee et al. 2010; Parida, Westerberg, and Frishammar 2012; van de Vrande et al. 2009) even though scholars agree that SMEs play a growing role in innovation (Chesbrough, Vanhaverbeke, and West 2006). Furthermore, earlier work on SMEs indicates that by nature,
Sabine Brunswicker is associate professor of Innovation and director of the Research Center for Open Digital Innovation (RCODI) at Purdue University. She is also affiliated with ESADE Business School (Spain) and Queensland University of Technology (QUT, Australia).
Wim Vanhaverbeke is professor of Strategy and Innovation Management in the Faculty BEW at Hasselt University (Belgium). He is also visiting professor at ESADE Business School (Spain) and the National University of Singapore.
Address correspondence to: S. Brunswicker, Purdue University, Discovery Park, West Lafayette, IN 47907. E-mail: sbrunswi@purdue.edu.
Journal of Small Business Management 2015 53(4), pp. 1241–1263
doi: 10.1111/jsbm.12120
BRUNSWICKER AND VANHAVERBEKE 1241
innovation in such firms has an external focus and is often strongly embedded in social and personal ties (Baum, Calabrese, and Silverman 2000; Ceci and Iubatti 2012; Edwards, Delbridge, and Munday 2005). However, researchers have hardly explored how SMEs can purposively make use of these ties to source ideas and knowledge for innovation. Second, existing empirical quan- titative contributions scarcely address the fact that not all sources may be of equal value for innovating firms. Thus, the nature of external knowledge sourcing represents a critical but poorly explored aspect of open innovation; espe- cially in SMEs. Thus, we argue that the nature of openness, describing how SMEs purposively source external knowledge in innovation, holds a central role in conceptualizing openness. Third, there is little understanding of the internal com- ponent of openness in SMEs. Such firms rarely engage in formal R&D as large firms do (Vossen 1998), and may have difficulties in build- ing absorptive capacity. Furthermore, external knowledge sourcing requires internal capabilities for managing innovation in order to (1) integrate inflows of knowledge with internal innovation activities, (2) successfully apply knowledge from internal and external sources, and (3) direct inno- vation actions (Adams, Bessant, and Phelps 2006; Lichtenthaler 2011; Lichtenthaler and Lichtenthaler 2009; Robertson, Casali, and Jacobson 2012). So far, little is known about the role of such integrative managerial practices for innovation in external knowledge sourcing in SMEs.
This paper investigates external knowledge sourcing in SMEs and focuses on the nature of external knowledge sourcing and the facilitat- ing role of internal practices for managing inno- vation. It empirically conceptualizes a typology of external knowledge sourcing. This typology describes distinct strategic types of openness, which give SMEs the opportunity to improve their innovation performance and relate to a distinct set of internal practices for managing innovation.
The paper is organized as follows: The next section briefly introduces open innovation and external knowledge sourcing and also reflects on internal organizational “facilitators.” Afterward, we present the analytical framework of our empirical conceptual study. Then we provide details of the sample, the data, and measures before furnishing the results of our empirical analyses drawing upon 1,411 firm-level data sets of SMEs in Europe. In the final section, we discuss
theoretical contributions of our research to the literature, avenues that future research may take and the limitations of our study.
Conceptual Background and Literature Review Open Innovation and External Knowledge Sourcing
Open innovation describes a cognitive frame- work for a firm’s strategy to profit from innova- tion (Chesbrough, Vanhaverbeke, and West 2006). It proposes that firms should purposively use inflows and outflows of knowledge to accel- erate internal innovation, and to expand markets for external use of innovation, respec- tively (Chesbrough 2006b, p. 1). Most research on open innovation differentiates between two concepts of open innovation: inbound where new ideas flow into an organization and outbound where internally developed technolo- gies and ideas can be acquired by external organizations with business models that are better suited to commercialize a given technol- ogy or idea (Chesbrough 2003). In so-called nonpecuniary modes of open innovation there is no immediate financial reward associated with a knowledge flow across organizational boundar- ies whereas in the pecuniary mode there is an immediate monetary compensation related to a knowledge flow (Dahlander and Gann 2010).
A firm’s external knowledge sourcing repre- sents an important nonpecuniary mode of inbound open innovation. It refers to how firms can use external sources of knowledge in a nonpecuniary way. Empirical studies on exter- nal knowledge sourcing regularly define open- ness as the number of external sources of knowledge that each firm draws upon in its innovation activities (Laursen and Salter 2004, 2006). In their influential study, Laursen and Salter (2006) provide empirical evidence that openness, measured as the number of external sources, positively affects a firm’s financial innovation performance. Their measure of openness—referred to as search breadth— inspired further studies on open innovation (Chen, Chen, and Vanhaverbeke 2011; Parida, Westerberg, and Frishammar 2012). However, a volume-oriented perspective ignores the fact that not all potential sources are of equal value for all innovating firms and that there are differ- ences in the strengths of interaction. For example, R&D sources such as universities, research labs, or suppliers seem to be highly
JOURNAL OF SMALL BUSINESS MANAGEMENT1242
relevant sources for a pioneering high-tech entrepreneurial firm but less so for a demand- oriented SME that mainly interacts with custom- ers and users (Gans and Stern 2003). Thus, it is important to concentrate on the particular nature and the distinct mix of interactions with external innovation partners in a firm’s sourcing strategy to enrich our understanding of open- ness in SMEs (Dahlander and Gann 2010; Gassmann 2006).
Internal Organizational Practices for Innovation as Facilitators of Openness
Both scholars and practitioners of open innovation agree that openness poses mana- gerial challenges and has an internal comple- ment (Chesbrough 2006a; Chiaroni, Chiesa, and Frattini 2011; Huston and Sakkab 2006; Lichtenthaler 2011). To successfully benefit from inbound open innovation, a firm requires some higher-order management capa- bilities to align inbound knowledge flows with the firm’s in-house innovation activities. Research on such internal organizational capacities for innovation discusses a range of practices and routines for managing innova- tion at strategic and operational levels (Bessant et al. 2010; Ernst 2002; Freeman and Engel 2007; van de Meer 2007; Pavitt 1998, 2002). Such managerial capabilities ensure that knowledge is successfully organized, mobilized, and applied in order to effectively and efficiently achieve a firm’s organizational goals for innovation (Robertson, Casali, and Jacobson 2012). Thus, organizational practices for managing innovation within the firm’s boundaries are facilitators of external knowl- edge sourcing activities as they aim for suc- cessful mobilization and application of knowledge from external and internal sources (Cohen and Levinthal 1990; Huizingh 2011). They complement a firm’s ability to absorb external knowledge and represent a kind of a master capacity to align a firm’s external knowledge sourcing activities with a firm’s innovation objectives (Cohen and Levinthal 1990; Lenox and King 2004; Robertson, Casali, and Jacobson 2012; Todorova and Durisin 2007; Vanhaverbeke, Cloodt, and van de Vrande 2008). Given their role in facilitating internal managerial practices for innovation, we argue the need to consider the interrela- tion between these activities and external knowledge sourcing.
The Analytical Framework: External Knowledge Sourcing in SMEs
Departing from the literature, the following section presents an analytical framework of external knowledge sourcing in innovation in SMEs. To do so, we first briefly discuss the specifics of open innovation in SMEs.
The Specifics of Open Innovation in SMEs
SMEs are an important source of innovation. SMEs have the capacity for radical, new-to-the- world innovation (Acs and Audretsch 1987). However, their innovation models and activi- ties differ from those of large firms. Although SMEs are usually more flexible, less formalized, and quicker to make decisions, their financial resources for internal R&D are limited (Bessant 1999; Lee et al. 2010; Vossen 1998; van de Vrande et al. 2009). Due to their smallness and resource constraints, they cannot cover all the innovation activities required to success- fully realize an innovation. As noted in earlier work on alliances and networks in SMEs, inno- vation in SMEs almost always has an interorganizational and boundary-spanning component. In fact, strategic and multi-actor alliances are critical drivers of innovation and help them access critical resources, extend their technological competencies, and build legiti- macy and reputation (Baum, Calabrese, and Silverman 2000; Lee et al. 2010). However, SMEs regularly struggle with making purpo- sively good use of external relationships for innovation (van de Vrande et al. 2009).
First studies on the adoption of open inno- vation in SMEs indicate that even though large firms seems to be more open, SMEs appear to have a greater concentration of open innovation than large firms (Spithoven et al. 2013). They indicate that SMEs have increased their activity in open innovation with inbound open innovation being far more diffused than outbound open innovation (van de Vrande et al. 2009). Considering the resource con- straints of SMEs and the role of informal interorganizational relationships in innovation in SMEs, research indicates that SMEs prefer nonmonetary activities such as networking and informal knowledge sourcing over pecuniary and complex transaction-based ones, such as acquisitions and in-licensing. The latter are resource intensive and also require expertise
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and control over a number of elements in a firm’s innovation network, which SMEs regu- larly lack (Dahlander and Gann 2010). Thus, we suggest that purposive external knowledge sourcing as nonpecuniary inbound is an impor- tant strategic dimension of openness in SMEs. As not all sources are of equal value to inno- vating SMEs, we assume that there are different sourcing strategies among SMEs that allow them to boost innovation performance and are linked to organizational and managerial capa- bilities for innovation.
Characteristics of External Knowledge Sourcing in SMEs
External knowledge sourcing may span various kinds of external innovation partners, who relate to different knowledge flows and can provide access to widely differing knowl- edge domains such as science, technology, design, societal trends, customer insights and product-market trends (von Hippel 1988; Sidhu, Volberda, and Commandeur 2004). We emphasize that external knowledge sourcing implies nonpecuniary direct interactions with external actors rather than passive search along knowledge trajectories. SMEs may exhibit varying patterns of sourcing given that access to each innovation source and the value expected in each case can differ significantly. Thus, the diversity and combination of innova- tion sources rather than their total number is crucial for the success of a firm’s sourcing strat- egy. Further in this paper, we discuss key sources and directions of external knowledge sourcing in SMEs.
Interactions with Direct and Indirect Customers. Sourcing along the traditional value chain might be a valuable approach for SMEs. SMEs might search downstream to access “sticky information” on customer needs, customer context, and customer experience. Such infor- mation is tacit and difficult to articulate (von Hippel and von Krogh 2006; Reichwald and Piller 2006). The involvement of indirect customers/users (e.g., drivers rather than manufacturers of car parts) may provide new insights into new business opportunities beyond existing products and markets (Enkel, Kausch, and Gassmann 2005).
Interactions with Suppliers. SMEs may also search upstream along the traditional value chain to benefit from suppliers expertise
(usually technological) with a view to involving them in their new product development (NPD). Suppliers can provide ideas for enhancing tech- nological solutions or process innovations (Tsai 2009). SMEs may consider suppliers as a rel- evant source as they concentrate on solutions and commercial value in the short term (Chesbrough and Prencipe 2008; Dyer, Cho, and Chu 1998).
Interactions with Universities and Research Organizations. For SMEs, both universities and research organizations are a relevant source for inventive and preindustrial knowl- edge as science may significantly alter the search for inventions (Fabrizio 2006; Fleming and Sorenson 2004; Shinn and Lamy 2006; Tsai 2009). University linkages also offer more timely access to inventive trends (Fabrizio 2009). However, there are a range of barriers to external knowledge sourcing in university– industry relationships, such as, for example, cultural differences, long-term scientific research versus exploitation-oriented research of industrial organizations and incompatible rewards systems—with universities focusing on publishing and firms protecting results (Harryson, Kliknaite, and Dudkowski 2008).
Interaction with Experts on Intellectual Prop- erty Rights (IPR). To access technological knowledge, SMEs may rely on intermediate service providers. Experts on IPR can provide crucial information services that help to bridge the gap between a technological opportunity and its successful commercialization (Bessant and Rush 1995). They may support a search for technological trends and ideas outside the firm’s boundary services or ideas on how to appropriate value from a firm’s knowledge assets (Bader 2006; Bennett and Robson 2005; Bessant 1999; Turok and Rako 2000; Vega-Jurado et al. 2008). However, the involve- ment of IPR experts is costly and also requires SMEs to deal with complex regulations and drawn-out patent protection procedures. Thus, it may make it more difficult to quickly move an idea to the commercialization stage (Hurmelinna-Laukkanen, Kyläheiko, and Jauhiainen 2007).
Interaction with Network Partners. Relation- ships with network partners are usually long- term and aim to create joint value creation rather than efficient transactions. They build
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upon trust and are characterized by mutual understanding among partners (Nooteboom et al. 2007). At the same time, network partners offer SMEs access to complementary innovation assets and also operational complementary assets such as manufacturing, marketing, and access channels (Christensen, Olesen, and Kjær 2005; Teece 1986); such resources normally take years to build (Baum, Calabrese, and Silverman 2000). Due to the synergetic nature of interactions, network relationships make it easier to identify, access, and absorb external ideas. Network partners and other sources just discussed are not mutually exclusive but may coexist. Considering the driving role of network ties in innovation for SMEs, network partners can be an important source for new ideas if SMEs use them purposively.
SMEs differ in terms of dependencies from network partners, customer insights, and their position in the value chain. Thus, we also expect them to shape their external knowledge searching strategies in different ways differ- ently to best assimilate the external knowledge they need for innovation.
Internal Organizational Facilitators of Openness in SMEs
External knowledge sourcing implies an internal component that goes beyond formal R&D (Chesbrough 2006a; Chiaroni, Chiesa, and Frattini 2011; Cohen and Levinthal 1990; Huston and Sakkab 2006; Lichtenthaler 2011). As SMEs hardly engage in formal R&D, it is particularly important to study the facilitating role of integrative managerial practices, which lay the foundations that enable a firm to benefit from external sources of innovation (Nelson and Winter 1977; Robertson, Casali, and Jacobson 2012; Teece, Pisano, and Shuen 1997). As already discussed, they imply strate- gic as well as operational components for effec- tive, efficient attainment of organizational innovation goals (Adams, Bessant, and Phelps 2006; Robertson, Casali, and Jacobson 2012). Thus, these integrative organizational practices come into play at different phases of the inno- vation process and relate to different stages of external knowledge sourcing. In the early stages, they organize the identification of future innovation areas and support activities for iden- tifying and accessing external knowledge; in the later stages they enable firms to launch individual innovation projects and exploit knowledge integrating internal and external
knowledge flows. We argue that there are four internal organizational practices for innovation that help support and enable external knowl- edge sourcing and alignment and that direct external knowledge sourcing at strategic and operational levels: They are (1) long-term investment activities, (2) innovation strategy processes, (3) innovation development pro- cesses, and (4) innovation project control.
Long-Term Innovation Investment. From a resource-based view, financial innovation assets are crucial assets as they provide resource slack and allow the firm to experiment and engage in riskier innovation projects (Barney 1991; Teece, Pisano, and Shuen 1997; Wiklund, Patzelt, and Shepherd 2009). A firm’s spending on innovation also gives a rough idea about its internal learning activities and desire to explore (Laursen and Salter 2006). Innova- tion management may direct a firm’s innovation efforts toward longer-term innovation. Such innovation activities focus on projects whose purpose is to build long-term knowledge rather than yield short-term results. The management focus on investment in long-term innovation shapes internal innovation activities and indi- viduals’ exploration of new knowledge. We assume that a firm’s long-term investment is an important organizational facilitator for external knowledge sourcing. It enables SMEs to build sufficient internal knowledge and may motivate firms to open up to external sources of knowl- edge (Cohen and Levinthal 1990).
Innovation Strategy Processes. An innovation strategy supports the identification of future business opportunities and the exploration of new technologies, solution principles or market functions (Adams, Bessant, and Phelps 2006; March 1991). The development of an innova- tion strategy implies strategic processes and managerial action. Semi-procedural routines for identifying future business opportunities and mapping them to internal competencies and capabilities are essential for innovation strategy making (Goffin and Mitchell 2005; Mintzberg 1991; Mintzberg, Quinn, and Ghoshal 1995; Pfeiffer 1971; Wong and Chin 2007). Innovation strategy processes help to identify and recog- nize the value of new external information and knowledge and direct internal innovation activities such as idea management and inno- vation project management related to it (Nelson and Winter 1982).
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Innovation Development Processes. Formal systems and procedures for NPD, such as stage- gate models, have become crucial in innovation management. Here, the benefits of systematic processes have been well documented in NPD research (Brown and Eisenhardt 1995; Bullinger and Engel 2006; Cooper 2008; Cooper and Kleinschmidt 1987). Such systems help managers coordinate and integrate the devel- opment of innovations in a structured manner (Christiansen and Varnes 2009). Development processes and routines are organizational ante- cedents to the assimilation and transformation of new knowledge (Tidd 2001). Just as absorp- tive capacity helps in assimilating technological knowledge, support development facilitates the coordination of external and internal innova- tion activities.
Innovation Project Control. To turn their inno- vation potential into value-creating outcomes, firms need to measure and manage innovation projects and processes in an efficient, goal- oriented manner. Clearly defined measures and targets for timing, resources, and ensuring the quality of individual innovation projects are essential (Brown and Eisenhardt 1995; Ernst 2002; Hauschildt 2004; Schewe 1994). Setting operational targets for innovation projects is vital when launching innovations (Adams, Bessant, and Phelps 2006). Innovation project control helps firms to reconfigure activities (Benner 2009; Goffin and Mitchell 2005) and ensures that innovation measures are carried out within budget, on schedule and at a satisfactory level of performance (Robertson, Casali, and Jacobson 2012). Thus, innovation project con- trol facilitates external knowledge sourcing as it controls operational activities and the exploita- tion of both external and internal knowledge.
The Empirical Study: Data and Measures Data
This research draws upon a coherent set of firm-level data of one benchmarking database on innovation management in SMEs. The
database was built up as part of a European initiative aiming at improving innovation man- agement in SMEs.1 The aim of the data collec- tion was to thoroughly analyze innovation management in SMEs and to compare the capa- bilities and performance of individual firms at a European level. An analytical tool was devel- oped for this purpose given that there were none available. The benchmarking database provides richer information than existing databases—such as the Community Innovation Survey (CIS)—as it covers organizational and firm-level aspects of innovation management in more detail. It also includes measures of exter- nal knowledge sourcing and open innovation. Various pretests and pilots were executed to ensure the interpretability, reliability, and valid- ity of the measurement instrument (Engel, Diedrichs, and Brunswicker 2008).
The benchmarking data was collected between April 2007 and August 2009 with the support of trained personnel in various Euro- pean countries. Data were collected in an administered manner and based on a structured process. In the preparation phase, the assess- ment objectives were introduced, and key con- cepts and terminologies were explained. During the assessment phase, the benchmarking instru- ment was filled in with the help of trained coaches. In the final feedback phase, each firm received an individual analysis report. The results were discussed during an on-site visit. Key informants of SMEs were the main source of information. The SME’s owner or CEO com- pleted the benchmarking questionnaire (Hair et al. 1998; Sidhu, Volberda, and Commandeur 2004).
To collect the data, over 30,000 SMEs from seven industry groups across Europe were con- tacted using mixed method sampling. The industry groups were selected based on Euro- pean NACE code classification scheme and the contribution the groups made to the gross domestic product of the European country con- cerned. Both high-tech and low-tech sectors were included. Firms that were younger than 2 years and with under 5 and over 1,000 employ- ees were not included in the sample.2
1The so-called IMP3rove initiative was financially supported by the European Commission. 2Referring to the official definition of SMEs suggested in the European Commission Recommendations 2003/361/EC, they employ under 250 employees. We extended the Commission’s definition of SMEs given that some countries have adapted their national classification schemes and classify firms with over 250 employees as SMEs (European Commission 2003; Aschoff et al. 2006).
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The sampling was not restricted to innova- tive firms. To contact the SMEs via e-mail or phone and to invite them to participate in the benchmarking process, we accessed SME data- bases via national contact points (e.g., Chamber of Commerce). In addition, SMEs could apply online to take part in the benchmarking. If they met the minimum participation criteria in terms of size, age, and industry group, they were contacted to start the benchmarking phase: SMEs needed to be in business for at least 2 years, had to employ between 5 and 999 people, and come from one of the seven indus- try groups selected for the study (as we further explain in the following section). Approxi- mately 3,000 SMEs participated in the bench- marking: 2,212 of them successfully completed the benchmarking questionnaire and 1,680 were visited on-site after the benchmarking to discuss the results.
The Sample and Its Characteristics We used a subset of the firms completing the
benchmarking questionnaire for the study.
Firms that we were unable to visit after comple- tion of the benchmarking questionnaire were not included in the analysis. Out of those 1,680 firms, 1,489 met a set of basic validation criteria linked to the research question.3 Furthermore, 78 firms had missing values on external knowl- edge sourcing items and were thus also excluded from the sample. A sample of 1,411 firms was used to develop an empirical typol- ogy of external knowledge sourcing strategies in SMEs.
The sample consists of fairly small, young firms, which reflects the dominance of such companies in Europe (Wymenga et al. 2012). The median enterprise employed 23 people (employees as head counts on payroll) and had been in business for 14 years. Table 1 shows the data set characteristics in terms of industry, size, and age class.4
Measures and Variables To empirically conceptualize strategic types
of openness in innovation in SMEs, we used three kinds of measures. The first kind captured
3Validation criteria related to completeness of information on employment and financial income data covering the last few years and the consistency of data bearing on innovation performance. For example, if respondents stated that they had not completed an innovation project within the last 4 years but that they had earned income from products or services that were younger than 3 years, we excluded the firm from the sample. 4It is worth noting that we relied on a mixed method sampling technique and thus we could not perform a non-response bias test. This test shows that there is no cognitive bias in the answers and that the statistical power of the sample size is close to the 50:1 suggested as desirable by Hair et al. (1998).
Table 1 Sample Characteristics in Terms of Industry Class, Size, and Agea
No. Industry Group No. of Firms
Age in Years (Median)
S.D. of Age
Size in No. of
Employees (Median)
S.D. of Size
1 Biotechnology 137 20 31.31 26 128.82 2 Food/Beverages 72 17 35.00 50 237.56 3 ICT/Electrical/Optical 305 11 22.66 18 133.11 4 Knowledge Intensive Services 412 8 18.39 12 101.37 5 Machinery/Equipment 357 23 31.15 40 143.11 6 Space/Aeronautics/Automotive 89 18 28.05 55 149.16 7 Textile 39 23 45.84 54 74.35
Total 1,411 15 28.05 23 136.23
aS.D., standard deviation.
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1 5
0 .0
4 2
0 .0
8 0 **
0 .1
0 7 **
0 .1
0 9 **
−0 .0
5 2
0 .0
4 4
−0 .2
2 9 **
0 .0
4 7
0 .1
6 7 **
0 .1
7 9 **
0 .1
3 1 **
0 .5
3 1 **
1 5
E x p e n d it u re
s fo
r In
n o v at
io n
0 .1
4 2
0 .3
1 8
0 .1
0 0 **
0 .0
4 5
−0 .0
0 9
0 .1
2 8 **
0 .1
2 3 **
0 .1
2 0 **
−0 .0
1 9
0 .3
1 2 **
0 .1
1 4 **
0 .1
1 7 **
0 .0
5 4 *
0 .1
5 0 **
−0 .2
7 0 **
−0 .1
9 6 **
a S .D
., st
an d ar
d d e v ia
ti o n .
* =
p <
0 .0
5 ;
** =
p <
0 .0
1 .
JOURNAL OF SMALL BUSINESS MANAGEMENT1248
a firm’s external knowledge sourcing, the second addressed innovation performance, and the third covered internal organizational and the managerial dimension of innovation. Table 2 gives the descriptive analysis and corre- lations for all measures used in our empirical analyses.
Capturing SME’s External Knowledge Sourc- ing. We concentrated on external knowledge sourcing, a form of nonpecuniary inbound open innovation to characterize SME’s open- ness in innovation management. We measured such sourcing activities over the last few years as regular interactions with each of the follow- ing six types of innovation partners: (1) direct customers, (2) indirect customers, (3) suppliers, (4) universities/research organizations, (5) IPR experts, and (6) network partners. The inten- sity of interaction with the respective source to search for new ideas is measured on a 7-point Likert scale where 1 denoted “not at all” and 7 denoted “regularly.” If access to a specific source was not available, answers were labeled as “not applicable.”
Measuring Innovation Performance. To examine the performance potential of different sourcing strategies, we concentrated on two dimensions of innovation performance, namely innovation success and income from innovation.
Innovation Success. This variable measured firms’ success in launching their innovations in terms of the percentage of projects meeting launch targets. By definition, it ranged from 0 to 100. Data of firms that did not specify targets were considered as missing values and thus the 308 data sets with missing values were excluded from the respective empirical analyses.
Income from Innovation Last Year. The vari- able captured a firm’s innovation performance over the last year as a share of income from new products/services that were not older than three years. This operationalization is in line with the Oslo Manual (OECD/European Communities 2005). Forty-two firms failed to provide data for this variable and hence were excluded from the analysis.
Measuring Internal Organizational Practices for Innovation. In our empirical conceptual- ization, we also examined how sourcing was linked to four internal organizational practices for innovation. In fact, there is no generally accepted measurement framework for such managerial practices. Departing from our theo- retical discussion, we constructed four mea- sures for four internal organizational practices for innovation that were instrumental in sup- porting the integration of external knowledge flows with internal innovation activities in the quest for external knowledge. They related to different stages in the innovation and sourcing process.
Long-Term Innovation Investment. To mea- sure a firm’s direction of innovation efforts toward long-term innovation projects, we relied on measure with a scale from 0 to 100 per cent. The measure captures investment in long-term innovation projects5 as a proportion of total innovation efforts.
Innovation Strategy Processes. To measure a firm’s organizational practices for innovation strategy and planning, we constructed a variable from seven items capturing various attributes of a firm’s innovation strategy. Each of the follow- ing items was coded as a binary variable, 0 as “not applicable” and 1 as “applicable”:
(1) The innovation strategy results from an analysis of potential businesses areas for future innovation activities.
(2) The innovation strategy sets clear targets for innovation management activities.
(3) The innovation strategy guides idea man- agement activities.
(4) The innovation strategy sets the objectives for project management in each innova- tion project.
(5) The innovation strategy guides improve- ment of the current product/service or process development.
(6) The innovation strategy provides the basis for organizational change and business model development.
(7) The innovation strategy focuses on the development of a firm’s capacity for innovation.
5Long-term projects are estimated based on their overall length; projects with a time frame of more than the average time-to-profit within the industry classify as long-term.
BRUNSWICKER AND VANHAVERBEKE 1249
Subsequently, the seven items were added up so that the firm got a score of “0” if no item applied and “7” if all items applied. In other words, it was assumed that if the innovation strategy fulfilled more of the attributes just stated, firms had more elaborated practices for innovation strategy. Although our variable was a relatively simple construct, it had a high degree of internal consistency (Cronbach’s alpha coefficient = 0.80).
Innovation Development Processes. The measure for a firm’s innovation development processes was constructed as a composite measure from five indicators to reveal formal innovation development processes for different innovation types. The existence of formal pro- cesses (including stage-gates and milestones) for product, service, process, organizational, and business model innovation is coded on a scale from 1 (not at all) to 7 (fully in place). We calculated the average score (mean values) to come up with an overall score for “innovation development processes.” The composite measure had a high internal consistency (Cronbach’s alpha = 0.87).
Innovation Project Control. The variable mea- sures a firm’s routines and practices for man- aging innovation projects in an efficient and goal-oriented manner when setting project targets. We used three indicators to construct the measure of innovation project control: (1) the percentage of innovation projects with clear targets in terms of time and duration, (2) the percentage of projects with clear targets in terms of budget, and (3) the percent- age of projects with clear targets in terms of quality. All three indicators covered the last three years and used a scale from 0 to 100. Calculating the average score, the overall measure showed high internal consistency (Cronbach’s alpha = 0.87).
Control Variables. Following prior research, we controlled for firm size by the natural loga- rithm of number of employees as well as for the firm’s age by the natural logarithm of the years passed since foundation.6 We also included a measure of innovation effort, measured as
average spending on innovation over the last four years divided by total income over the same period.7 In addition, we included industry dummies to control for industry effects (see, e.g., Laursen and Salter 2006).
Results: A Typology of External Knowledge Sourcing in SMEs
In the following sections, we present the results of our empirical conceptualization of external knowledge sourcing in SMEs. First, we identify homogeneous groups of external knowledge sourcing strategies and introduce an empirical typology of external knowledge sourcing. Then we also examine the perfor- mance impact of each sourcing strategy. Finally, we look at the internal dimension of openness and how different sourcing strategies relate to different internal organizational prac- tices for innovation.
Empirical Conceptualization of Strategic Sourcing Types
To empirically conceptualize external knowledge sourcing in SMEs, we used cluster analysis to sort firms applying similar innova- tion sourcing strategies into homogenous groups (Hair et al. 1998). We applied hierarchi- cal and nonhierarchical cluster analysis tech- niques in a sequential manner. This helped produce a more robust taxonomy. We chose Ward’s method and the squared Euclidian dis- tance measure. The hierarchical cluster analysis allows for an effective identification of a rea- sonable range of the cluster numbers and potential cluster seeds (Ketchen and Shook 1996). Based on an inspection of the agglom- eration coefficient plotted over the number of clusters, we took the “five-cluster,” “four- cluster,” and “three-cluster” solution into con- sideration for the second analysis phase. Here, we applied a K-means cluster analysis to deter- mine the final cluster profiles. We then used the results of the hierarchical cluster analysis as cluster seeds (Punj and Stewart 1983). K-means analysis revealed the consistency of all three cluster solutions. Thus, we decided to further examine the conceptually preferred five-cluster solution. As suggested by several authors, we
6The nature of the distribution of the variable suggested a transformation. 7As 44 firms had missing values for this variable, the sample size for the regression was lower than the sample with no missing values on the dependent variables.
JOURNAL OF SMALL BUSINESS MANAGEMENT1250
chose a random subsample, carried out cluster- ing and compared results with those based on the overall sample (Hair et al. 1998; Punj and Stewart 1983). This confirmed that the five- cluster solution is robust.
Table 3 presents five clusters resulting from our statistical analysis and reports the average scores of each cluster for each cluster variable, measuring the interaction with individual inno- vation sources. These cluster solutions give an indication about how SMEs engage in knowl- edge sourcing and how they combine different types of interactions with innovation partners to access external ideas. On the basis of these scores, we labeled the five groups to character- ize their knowledge sourcing: (1) minimal searcher, (2) supply-chain searcher, (3) technology-oriented searcher, (4) application- oriented searcher, and (5) full-scope searcher. As illustrated in the following discussion, these strategies are distinct in nature:
Minimal Searcher (Type 1). Type 1 does not actively interact with external sources to combine internal and external innovation potentials. Neither do they rely on inputs from actors of their value chain (customers or sup- pliers) nor do they involve trusted network partners to identify new innovation opportuni- ties. In addition, they do not draw upon scien- tific and pre-commercial knowledge from universities or research organizations. IPR experts are also not an attractive innovation source. They are reluctant to open up their innovation activities to outside influences.
Supply-chain Searcher (Type 2). Firms in Cluster 2 are characterized by relatively intense interactions with direct customers and suppli- ers in comparison to other external sources. Taking a closer look into the relative weight of the respective sources, the data revealed that these SMEs rely heavily on “traditional” supply- chain linkages. Their innovation activities do not rely on input from sources generating pre- commercial and science-based knowledge such as universities and research organizations. Existing and well-established network relation- ships with network partners are not an impor- tant innovation source either.
Technology-oriented Searcher (Type 3). Firms in Cluster 3 are characterized by a relatively high degree of interaction with universities, research organizations, and IPR experts. This
indicates that these SMEs are interested in accessing inventive trends as early as possible and in sourcing external technological and pre- commercial knowledge. These firms tackle the challenges of university–industry relationships such as cultural differences and incompatible reward systems. They also heavily rely on inputs from innovation network partners with which they have established trustworthy rela- tionships. These relationships offer important complementary resources to further develop a technological idea. However, they do not stress the innovation inputs of actors along the tradi- tional supply-chain, such as suppliers and cus- tomers. Indeed, technology-oriented searchers hardly interact with downstream partners (direct customers and indirect customers). This suggests that they follow a technology-push innovation strategy and scarcely involve actors positioned at the end of the value chain in the early phases of innovation activities.
Application-oriented Searcher (Type 4). SMEs of type 4 are application-oriented and demand- driven innovation searchers. Such SMEs regu- larly interact with value chain actors (for instance customers and suppliers) to get access to new ideas. Network partners also play an important role in finding new ideas. These firms rank highest in the active involvement of indirect customers. They consider indirect cus- tomers and users (which are not direct custom- ers) as the most important input source in relation to other sources. Apparently, they per- ceive consumers as “value generators” rather than “value receivers” and apply knowledge sourcing to get access to “sticky information” on customer needs. Technological knowledge and inventive trends are of little relevance if SMEs engage in application-oriented search strategies. These firms rank low in terms of interaction with universities, research organiza- tions, and IPR experts.
Full-scope Searcher (Type 5). Firms in Cluster 5 are heavily involved in knowledge sourcing, show a strong interest in external ideas from various innovation sources and have built an innovation ecosystem for new ideas. They aim for high diversity when sourcing external ideas and cover different knowledge domains such as market, technology, and scientific knowledge. Indeed, they heavily interact with all six inno- vation sources to get access to new ideas and new knowledge. Considering the absolute
BRUNSWICKER AND VANHAVERBEKE 1251
T a b le
3 R
e su
lt s
o f
C lu
st e r
A n a ly
se s—
S tr
a te
g ic
T y p e s
o f
E x te
rn a l
K n o w
le d g e
S o u rc
in g
a
C lu
st e r
V a ri
a b le
s M
e a n
V a lu
e s
(B a se
d o n
a 7 -L
ik e rt
S ca
le )
F T e st
(d f
= 4 )
In te
n si
ty o f
E x te
rn a l
K n o w
le d g e
S o u rc
in g
T o ta
l S a m
p le
M in
im a l
S e a rc
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S u p p ly
-c h a in
S e a rc
h e r
T e ch
n o lo
g y -
o ri
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d S e a rc
h e r
A p p li ca
ti o n -
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e n te
d S e a rc
h e r
F u ll -s
co p e
S e a rc
h e r
D ir
e ct
C u st
o m
e rs
4 .6
9 2 .3
0 5 .4
8 4 .4
7 5 .4
8 5 .8
7 3 1 3 .4
3 **
In d ir
e ct
C u st
o m
e rs
3 .8
1 2 .4
7 1 .8
4 3 .3
7 5 .6
1 5 .3
4 3 8 8 .7
8 **
S u p p li e rs
3 .8
2 1 .9
4 4 .2
6 2 .9
3 4 .5
8 5 .4
1 2 2 3 .9
8 **
IP R
E x p e rt
s 2 .4
6 1 .3
7 1 .4
3 2 .7
4 1 .5
3 5 .2
1 5 0 4 .0
6 **
U n iv
e rs
it ie
s/ R e se
ar ch
O rg
. 3 .0
6 1 .5
2 1 .7
5 5 .0
6 1 .7
6 5 .3
6 7 3 8 .1
9 **
N e tw
o rk
P ar
tn e rs
3 .8
7 2 .2
5 2 .9
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5 4 .1
9 5 .5
0 1 5 7 .9
5 **
N u m
b e r
o f
F ir
m s
1 ,4
1 1
2 7 9
2 8 6
2 7 5
3 0 0
2 7 1
a M e th
o d s:
F ir
st W
ar d ;
A ft e rw
ar d
K -M
e an
s w
it h
W ar
d R e su
lt s
as S ta
rt in
g P o in
t. * =
p <
0 .0
5 ;
** =
p <
0 .0
1 .
JOURNAL OF SMALL BUSINESS MANAGEMENT1252
T a b le
4 T o b it
R e g re
ss io
n s
o n
In co
m e
fr o m
In n o v a ti
o n
a n d
In n o v a ti
o n
S u cc
e ss
a
In co
m e
fr o m
In n o v a ti
o n
In n o v a ti
o n
S u cc
e ss
M o d e l
1 a
M o d e l
1 b
M o d e l
2 a
M o d e l
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C o e f.
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. C
o e f.
S .E
. C
o e f.
S .E
. C
o e f.
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.
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rc e p t
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0 .4
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3 4 .4
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4 .8
5 9
So u
rc in
g St
ra te
g ie
s (D
u m
m ie
s) S u p p ly
-c h ai
n S e ar
ch e r
0 .0
6 9
0 .0
3 7
0 .0
5 1
0 .0
3 6
1 .1
6 8
3 .9
5 0
−1 .4
6 8
3 .8
1 1
T e ch
n o lo
g y -o
ri e n te
d S e ar
ch e r
0 .0
6 1
0 .0
3 7
0 .0
1 9
0 .0
3 8
−2 .8
6 5
3 .8
2 9
−6 .0
7 4
3 .7
7 9
A p p li ca
ti o n -o
ri e n te
d S e ar
ch e r
0 .0
4 2
0 .0
3 6
−0 .0
0 3
0 .0
3 6
1 2 .3
2 0 **
3 .7
1 9
8 .1
4 1 *
3 .6
5 3
F u ll -s
co p e
S e ar
ch e r
0 .1
4 3 **
0 .0
3 7
0 .0
7 8 *
0 .0
3 9
9 .9
7 3 **
3 .7
5 5
4 .3
0 8
3 .8
6 0
In te
rn a
l O
rg a
n iz
a ti
o n
a l
P ra
ct ic
es fo
r In
n o va
ti o n
L o n g -t e rm
In n o v at
io n
In v e st
m e n t
−0 .0
0 1
0 .0
0 0
−0 .0
4 6
0 .0
4 3
In n o v at
io n
S tr
at e g y
P ro
ce ss
e s
0 .1
3 6 *
0 .0
0 6
−0 .3
8 0
0 .5
5 8
In n o v at
io n
D e v e lo
p m
e n t
P ro
ce ss
e s
0 .0
0 2
0 .0
0 8
1 .8
6 6 *
0 .7
7 6
In n o v at
io n
P ro
je ct
C o n tr
o l
0 .0
0 2 **
0 .0
0 0
0 .3
1 6 **
0 .0
3 8
C o n
tr o l
V a
ri a
b le
s A
g e
(l n )
−0 .0
6 1 **
0 .0
1 3
−0 .0
5 2 **
0 .0
1 3
0 .3
9 9
1 .3
6 5
0 .8
0 0
1 .3
1 0
S iz
e (l
n )
−0 .0
2 3 *
0 .0
1 1
−0 .0
9 4 **
0 .0
1 1
−0 .2
6 3
1 .0
7 2
−1 .3
7 8
1 .0
5 0
E x p e n d it u re
s fo
r In
n o v at
io n
0 .3
7 5 **
0 .0
4 2
0 .3
3 4 **
0 .0
4 1
−0 .6
0 4
3 .6
1 0
−3 .4
3 1
3 .5
0 9
In d u st
ry D
u m
m ie
s (R
e p o rt
e d
if S ig
n ifi
ca n t)
B io
te ch
n o lo
g y
−0 .1
2 0 **
0 .0
4 4
−0 .1
1 5 **
0 .0
4 3
L o g -L
ik e li h o o d
−8 7 2 .2
0 0
−8 4 5 .9
8 −4
,5 6 4 .2
1 0
−4 ,5
2 5 .6
3 0
C h i- S q u ar
e (W
al d )
2 3 1 .0
2 **
2 8 3 .2
3 3 **
3 4 .4
0 **
1 1 1 .5
6 **
P se
u d o
R 2
ap p li e d
0 .1
2 0
0 .1
4 0
0 .0
0 4
0 .0
1 2
N 1 ,3
4 1
1 ,3
4 1
1 ,0
6 8
1 ,0
6 8
a O n e
T ai
l T -t e st
A p p li e d .
R e fe
re n ce
G ro
u p
o f
S o u rc
in g
S tr
at e g ie
s: M
in im
al S e ar
ch e r;
R e fe
re n ce
G ro
u p
o f
In d u st
ry D
u m
m ie
s: K
n o w
le d g e
In te
n si
v e
S e rv
ic e s
(K IS
). * =
p <
.0 5 ;
** =
p <
.0 1 .
BRUNSWICKER AND VANHAVERBEKE 1253
average score of each external source, “Type 5” SMEs interact intensely with universities and research organizations. This indicates their strong interest in inventive trends and pre- commercial knowledge. At the same time, they also rely more heavily on IPR experts than other SMEs. Full-scope searchers deliberately use their network of trusted contacts and part- ners to find new ideas and have not become dependent upon them (average score 5.5). Fur- thermore, they regularly assess the demand and market potential of new ideas as they rank very high in direct customer involvement.
As suggested in prior literature, we exam- ined whether there were significant differences between the five strategic sourcing types in the variables we used for clustering SMEs. One-way analyses of variance for each individual vari- able confirms significant differences between the five cluster solutions in all clustering vari- ables (F-test p < .01 for all cluster variables). Consequently, our typology meets basic requirements for high quality cluster solutions.
Strategic Types of Openness and Innovation Performance
To investigate the effect of the sourcing choice on innovation performance, we ran regression analyses to refine our understanding of the potential performance impact of each sourcing strategy respectively. To estimate the effect of each sourcing strategy on firms’ inno- vation performance, we made use of categori- cal variables describing the firm’s sourcing strategy as independent variables (resulting from our cluster analysis). We chose the minimal searcher as a reference group and relied on indicator coding assigning a value of “0” to the reference group as suggested by Fox (2008). We applied Tobit regression analyses to account for the specifics of the two dependent variables, innovation success and innovation performance last year (Tobin 1958; Wooldridge 2002). As a standard practice in studying this type of data, we applied censored regression modeling and estimated Tobit models to account for the qualitative difference between
limited observations (zeros) and noncensored continuous observations (see e.g., Wooldridge 2002).
As shown in Table 4 we estimated the Tobit regression models for two dependent and cen- sored measures of innovation performance relating to two performance dimensions—the SME’s success in launching innovation projects and the financial income from new products and services.8 In both regressions, we con- trolled for additional factors describing organi- zational and industry characteristics, namely age, size, innovation efforts, and industry groups. As we had to choose a reference group for our dummy variables to control for industry effects, we chose the KIS group as a reference group and included six industry dummies.9 We estimated the performance effect in two stages. First, we entered the control variables and the sourcing variables (Models 1a/2a). Subse- quently, we entered the measures of organiza- tional facilitators for innovation (Models 1b/2b). In all three regressions, the intercept represents the unexplained level of the depen- dent variable for the minimal searching group.
In the regression on income from innovation (Model 1a and 1b), the results indicate the performance potential of full-scope sourcing over a minimal sourcing strategy on income from innovation. Table 4 shows that we identi- fied significant effects for full-scope sourcing activities in Model 1 (c = 0.143, p < .01 in Model 1a; and c = 0.078 in Model 1b). The dummy variables for supply-chain sourcing and technology-oriented sourcing are only signifi- cant at the level p < .1 in Model 1a, and thus, we cannot claim that they affect a firm’s ability to financial benefit from innovation. Application-oriented sourcing does not show a significant effect and, thus, cannot be consid- ered as critical strategy for improving a firm’s innovation performance.
When entering the variables for the organi- zational practices in Model 1b, full-scope sourcing remains significant. This indicates that full-scope sourcing may have significant positive performance implications indepen-
8Two measures for income from innovation allow testing the robustness of our results. 9In the control model for the dependent variable innovation success, we find a weak positive of the industry dummy space. In the control models for both dependent variables related to income from innovation we found three significant effects: Firm age negatively effects firm performance, and expenditures for innovation positive effects income from innovation; in addition, there is a positive loading for firms from biotech industry in both models.
JOURNAL OF SMALL BUSINESS MANAGEMENT1254
dently of the firm’s internal capacity for man- aging innovation. We identify two significant effects for the organizational practices for innovation in Model 1b. Innovation strategy processes (c = 0.136, p < .05) and innovation project control (0.002, p < .01) have a direct positive effect on a firm’s income from inno- vation. This indicates that a firm’s internal capacity for managing innovation at a strategic and operational level has a direct positive impact on performance. As the direct effect of full-scope sourcing is smaller in Model 1b, we assume that there are some mediating effects at work through which the effect of external sourcing unfolds (Baron and Kenny 1986; Urban and Mayerl 2008). The effect of full- scope sourcing seems to be partially mediated. Internal strategy processes and project man- agement may facilitate the performance improvement through full-scope sourcing. As we will perform a more detailed analysis of the association between the organizational practices and a firm’s sourcing activities in the following section, we may further support this assumption.
In the regressions on innovation success (Model 2a and Model 2b) two sourcing strategies show a positive performance effect over a minimal sourcing strategy, namely application- oriented sourcing and full-scope sourcing. Table 4 shows that both strategies have a signifi- cant positive effect on a firm’s innovation success in Model 2a. Application-oriented sourc- ing (c = 12.320, p < .01) has a stronger effect than full-scope sourcing (c = 9.973, p < .01) in this model; it indicates the role of interactions with distant value chain partners to ensure the success of individual innovation projects and innovation launch. Supply-chain sourcing and technology-oriented sourcing are not driving success in launching innovation. When entering the variables for organizational practices, the effect of application-oriented sourcing activities remains significant. This suggests that application-oriented sourcing improves a firm’s success in launching innovation independently of its internal capacity for innovation. The effect of full-scope sourcing is not sustained in Model 2b. We identified two significant effects among the internal organizational practices for innova- tion: Innovation development processes (c = 1.866, p < .05) and innovation project control (c = 0.316, p < .001) have a direct posi- tive effect on the success of innovation launch. These operational capabilities are instrumental
in directing and controlling innovation activities for a successful launch. Again, the effect of application-oriented sourcing is smaller in Model 2b than in Model 2a and the effect of full-scope sourcing completely disappears. There might be the potential for some mediating effects (Baron and Kenny 1986). Our results suggest that innovation development processes and project control partially mediate the positive effect of application-oriented sourcing, and fully mediate the positive effect of full-scope sourcing on innovation success.
Overall, our regression analyses indicate that each sourcing strategy represents a distinct mix of interactions with external sources of innova- tion giving SMEs the chance to improve their innovation performance. If SMEs move away from a minimal sourcing strategy the “mix” may give SMEs the opportunity to improve their innovation performance: A full-scope sourcing approach seems to be a highly valuable strate- gic choice over a minimal sourcing strategy to improve innovation performance. The financial innovation benefits are independent from a firm’s internal capacity for innovation. In con- trast, application-oriented search is a major driver of innovation success and represents a smart alternative sourcing approach to full- scope sourcing. The performance implications are independent from the firm’s internal profi- ciency in managing innovation. To conclude, our results indicate that full-scope sourcing as well as application-oriented sourcing are prom- ising strategies.
Openness and Internal Organizational Practices for Innovation
As already discussed, there is an internal managerial dimension of external knowledge sourcing. To investigate the relation between external knowledge sourcing and internal orga- nizational practices for innovation thoroughly, we estimated the effect of the four internal organizational practices for innovation on a firm’s sourcing strategy. These strategies choices represent categorical outcomes, and thus, we chose a multinomial logistic regres- sion (MNL) approach. It allowed us to investi- gate the effect of independent variables on more than two groups of unordered nominal dependent variables, in our case the different sourcing strategies (Freese and Long 2006). Again, we had to choose a reference group for the dependent variables, which forms the basis for calculating the changes in the other groups.
BRUNSWICKER AND VANHAVERBEKE 1255
This is taken into account when interpreting the results. To test the significance of each independent variable a Wald test was applied. In these regressions we took the “minimal searcher” category as the default category.
As shown in Table 5, the multinomial logistic regressions provide a more detailed picture of our empirical typology of external knowledge sourcing. We first estimated a control model, with the control variables (firm age, firm size, industry dummies, and expenditures for innova- tion).10 In a second step, we entered the mea- sures for organizational practices to see how a firm’s internal managerial capacity for innova- tion is linked to a firm’s decision to choose one of the four sourcing strategies over a minimal sourcing strategy. Overall, we found significant effects for all four sourcing strategies.
Table 5 illustrates the increasing role of inter- nal practices the greater the variety and intensity of sourcing. A widely diversified sourcing strat- egy is linked to greater proficiency in managing innovation throughout the innovation value chain—from the inception of the idea through to its successful commercialization—and in differ- ent dimensions such as strategy, operational development processes, and innovation project control. High reliance on internal management proficiency implies that companies also invest time and money in these organizational capa- bilities. On the one hand, they may gain through improved innovation performance. On the other hand, they invest a great deal in organizational practices to get that far. Openness seems to pay off for innovating companies but may also be the price paid to get the benefits. In contrast, minimal searchers and supply-chain searchers gain less from their innovations but also have to worry less about the professionalization of their internal innovation management.
It is worth pointing out that we found sig- nificant variations among the sourcing clusters in terms of the role of different practices. Apparently, each sourcing strategy is linked to a distinct mixture of internal managerial prac- tices and capabilities respectively. Supply-chain sourcing is positively associated with a SME’s focus on strategic practices for innovation (c = 0.094, p < .05). Technology-oriented sourc- ing is associated with a mixture of three prac-
tices: innovation strategy processes (c = 0.197, p < .01), innovation development processes (c = 0.354, p < .01), and innovation project control (c = 0.006; p < .01). For application- oriented sourcing the mix is different. Only operational practices such as innovation devel- opment processes (c = 0.467, p < .01) and inno- vation project control (c = 0.009; p < .01) are relevant, but innovation strategy does not come into play. A full-scope sourcing is strongly linked to a balanced mix of all practices: long- term investment (c = 0.011, p < .05), innovation strategy processes (c = 0.240; p < .01), innova- tion development processes (c = 0.551; p < .01), and innovation project control (c = 0.012; p < .01).
When jointly interpreting the results of Table 5 and Table 4, we find evidence of the mediating functions of internal organizational practices through which the positive performance effect of openness unfolds (Baron and Kenny 1986). The effects in Table 5 suggest a positive association between full-scope sourcing, innovation devel- opment process, innovation strategy, and inno- vation project control respectively. Thus, we conclude that the effect of full-scope sourcing on income from innovation is partially mediated through innovation strategy and project control innovation (see Table 4). These two practices seem to strengthen a firm’s ability to financially benefit from full-scope sourcing. In addition, data also suggests that the performance effect of full- scope sourcing on innovation success is fully mediated by a firm’s development processes and project control (see Table 4). These practices are the prerequisite for a full-scope sourcing strategy to shape a firm’s innovation success. Results also suggest a positive association between application-oriented sourcing and development processes and project control respectively (see Table 5). Thus, we conclude that the effect of application-oriented sourcing on innovation success is partially mediated by these two practices.
Conclusions Openness in SMEs represents an exciting
research topic: Even though most SMEs depend on interorganizational relationships for innova- tion, they often lack the ability to purposively
10We used the same control variables as in the Tobit regressions; we did not include spending on innovation as this variable is included in one of the factors for measuring a firm’s internal organizational practices for innovation.
JOURNAL OF SMALL BUSINESS MANAGEMENT1256
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BRUNSWICKER AND VANHAVERBEKE 1257
make use of these ties as sources for new ideas and knowledge in innovation (Baum, Calabrese, and Silverman 2000; Ceci and Iubatti 2012; Edwards, Delbridge, and Munday 2005). With this paper, we deepen our conceptual understanding on SMEs’ external knowledge sourcing strategies for innovation. It presents an empirical typology of external knowledge sourcing in SMEs and contributes two perspec- tives to the literature.
Contributions to Literature on Open Innovation and External Knowledge Sourcing
Our results suggest that SMEs engage in purposive external knowledge sourcing for innovation and that there are SMEs that move away from strategies with limited external inter- actions for innovation. Our analyses show that there are different kinds of external knowledge sourcing strategies in SMEs; We empirically identified five strategies of sourcing: (1) minimal searchers, (2) supply-chain searchers, (3) technology-oriented searchers, (4) application- oriented searchers, and (5) full-scope searchers. Each sourcing strategy represents a distinct mix of interactions with the following external sources of innovation: (1) direct customers, (2) indirect customers, (3) suppliers, (4) universities/research organizations, (5) IPR experts, and (6) network partners. Indeed, openness is not a binary concept—open versus closed—but rather represents a distinct mixture of external interactions.
Our results indicate that engaging in external knowledge sourcing is a sensible move for SMEs as it offers performance benefits and can improve innovation performance in two dimen- sions, namely the success of launching an inno- vation and the appropriation of financial value from new products and services. We identified two sourcing strategies that offer direct perfor- mance benefits in these two dimensions, inde- pendently of a firm’s internal managerial capabilities for innovation. A full-scope sourcing strategy, leveraging the overall ecosystems for new ideas, offers the greatest opportunities to increase the income from innovation over a minimal sourcing strategy. Application-oriented sourcing (which heavily relies on distant part- ners along the value chain, such as indirect customers) can significantly improve the success in commercializing individual innovation proj- ects, and is superior to a full-scope sourcing approach. Although both strategies, full-scope
sourcing and application-oriented sourcing, offer direct performance benefits, these perfor- mance benefits are slightly different. This indicates that the nature of sourcing and the sought-after performance improvement matter when theorizing on openness in SMEs. Thus, our results complement earlier studies on exter- nal knowledge sourcing, which mainly take a “volume-based” approach and focus on the number of sources in a firm’s external knowl- edge sourcing strategy (Laursen and Salter 2006). Application-oriented sourcing is an alter- native “smart” move to enhance innovation success. Whereas full-scope sourcing empha- sizes very deep, synergetic interactions with a diverse set of sources, an application-oriented approach is more selective. Application-oriented searchers do not increase interactions in all directions but instead stress interactions with distant partners along the value chain when moving beyond interactions with direct custom- ers and suppliers.
Contributions to the Literature on Firm-internal Capabilities for Open Innovation
Our research also contributes to our under- standing of the internal managerial component of openness and the role of internal organiza- tional practices for innovation. In particular, we explore the interrelationship with integrative organizational practices for managing innova- tion that direct and control innovation activities at a strategic and operational level. Such prac- tices include capabilities for operationalization, such as process as well as project management, making sure that a firm’s innovation activities are directed toward organizational goals (Robertson, Casali, and Jacobson 2012). Our research makes three important contributions to the internal component of openness: First, our analyses indicate that those sourcing strategies that are associated with a higher degree and variety of external interactions are linked to greater stress on managing innovation internally. Openness seems to pay off for innovating companies as full-scope sourcing and application-oriented sourcing offer perfor- mance benefits; however, there is also an internal component that may spur firms to open up.
Second, our results suggest that there are mediating effects at work. Internal organiza- tional practices for managing innovation support the performance impact of openness.
JOURNAL OF SMALL BUSINESS MANAGEMENT1258
Internal organizational capabilities partially mediate the effect of full-scope sourcing on income from innovation, and also the effect of application-oriented sourcing on innovation success respectively (Baron and Kenny 1986). Without internal practices, the effect of these two strategies would be lower. In addition, the effect of full-scope sourcing on innovation success is fully mediated by the SME’s internal practices for managing innovation. Without internal proficiency this strategy would have no effect. [Correction added on 23 October 2014, after first online publication: the text in lines 7–12 has been updated.] It represents a prereq- uisite for application-oriented search to unfold its potential in driving innovation success.
Third, our results suggest that the nature of sourcing matters given that each strategy is linked to a particular mix of internal organiza- tional practices. We found that not all dimen- sions are equally important for each sourcing type. For example, full-scope searchers empha- size strategic as well as operational aspects. In contrast, application-oriented searchers put their efforts mostly in operational aspects such as innovation project management.
In a nutshell, our conceptualization suggests that it is not just about “more external sources are linked to a higher intensity of managing innovation internally.” It is also the distinct mix of practices that is linked to a particular sourc- ing strategy.
Limitations and Future Research Directions
The current paper presents a new empirical conceptualization of openness in SMEs and examines the interrelation between different types of external sourcing and internal prac- tices for managing innovation. Despite the sig- nificance of the results, there are limitations that pose further questions to be addressed.
First, our study focused on the analysis of patterns of knowledge sourcing. To empirically compose our sourcing strategy, we relied on six major directions of sourcing and measured whether SMEs purposively interact with these sources in innovation. These sources related to different types of external knowledge (Sidhu, Volberda, and Commandeur 2004) and capture critical value creation relationships (Nalebuff and Brandenburger 1996). However, future research may use a more fine-grained list of sources to conceptualize external knowledge sourcing. Even though the CIS survey does not capture
whether SMEs purposively interact with external sources for new ideas, it lists a range of additional sources which may be considered in future new surveys (e.g. Laursen and Salter 2006).
Second, our analysis explores associations between different types of external knowledge sourcing and innovation performance, and internal practices for innovation and external knowledge sourcing respectively. Unfortu- nately, our results do not allow us to make the claim of causality as we rely on cross-sectional data. Thus, we suggest that future research takes a longitudinal perspective to investigate the causal-effect relationships more rigidly.
Third, we assume that external knowledge sourcing is a strategic choice. However, a firm’s sourcing strategy may be bounded by other factors. Considering the liabilities represented by SMEs’ smallness and lack of resources, future research should consider in more detail how organizational and also industry factors help or hinder a firm’s decision to open up to external knowledge sources. Indeed, openness requires SMEs to reveal some knowledge to outsiders. However, this results in a conflict with the SME’s interest in protecting its intellectual property (IP) and their preference for informal protection mechanism (Leiponen and Byma 2009). Thus, future research may investigate the interrelation between boundary conditions and a firm’s nature of openness.
Fourth, our research indicates that internal managerial practices for innovation play a crucial role in openness in SMEs. However, we were not able to investigate them in a fine- grained manner. Further research may examine in more detail how SMEs establish such higher order managerial practices. Such research should also pay particular attention to the micro-foundations of these managerial prac- tices and, specifically, the underlying inten- tional actions, preferences, and skills of individuals (Felin and Foss 2009).
Acknowledgment The research was performed in collaboration
with the Europe INNOVA initiative IMP3rove. Sabine Brunswicker would like to explicitly thank Reinhard Büscher, Head of Innovation Policy Unit, DG Enterprise and Industry, at the European Commission for permitting this sci- entific work. We are grateful for the permission to use the benchmarking data. The usual dis- claimer apply. The authors also wish to thank for very valuable comments from Johann Peter
BRUNSWICKER AND VANHAVERBEKE 1259
Murmann, UNSW, Sydney, Dirk Czarnitzki, K.U. Leuven, Brussels, Larissa Scheiffele, Fraunhofer Institute for Industrial Engineering, Stuttgart and the anonymous referees of this paper.
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