H200819 Open innovation in SMES Trends, motives and management challenges Vareska van de Vrande Jeroen P. J. de Jong Wim Vanhaverbeke Maurice de Rochemont Zoetermeer, November 2008 1 This report is published under the SCALES-initiative (SCIENTIFIC Analysis of Entrepreneurship and SMES), as part of the'SMES and Entrepreneurship programme 'financed by The netherlands Ministry of Economic Affairs Most recent EIM reports and much more on SMES and Entrepreneurship can be found at www. entrepreneurship-sme. eu The responsibility for the contents of this report lies with EIM bv. Quoting numbers or text in papers, essays and books is permitted only when the source is mentioned clearly. No part of this publication may be copied and/or published in any form or by any means, or stored in a retrieval system, without the prior written permission of EIM bv. EIM bv does not accept responsibility for printing errors and/or other imperfections 2 Open innovation in SMES Trends, motives and management challenges Vareska van de Vrande *RSM Erasmus University E-mail: vvrande@rsm. nl Jeroen P. J. De Jong EIM Business and Policy Research E-mail: jjo@eim. nl Wim Vanhaverbeke Hasselt University, Faculty of business Studies E-mail: wim. vanhaverbeke@uhasselt. be Maurice de Rochemont Eindhoven University of Technology E-mail: m d. rochemont@tm. tue. nl February 2008 *Corresponding author Vareska van de Vrande RSM Erasmus University Department of Strategic Management and Business Environment Room T7-33 P o box 1738,3000 DR Rotterdam, The netherlands T:++31 10 408 2208, F:++31 10 408 9013 E-mail: vvrande@rsm. nl Working paper: Please do not quote or cite without the authors†permission 3 Abstract Although evidence for open innovation practices has been provided for large MNES they have not yet been analyzed systematically for SMES. This paper presents the results of a survey among 605 Dutch innovating SMES. The results show that SMES are increasingly adapting open innovation practices. Moreover, they indicate a difference in the adaption to open innovation between manufacturing and services firms, and between larger and smaller SMES. Larger SMES adapting more quickly and in a more structured and professionalized way to open innovation than smaller ones The survey furthermore shows that SMES generally pursue an open innovation strategy to realize market-related objectives such as meeting customer demands, or keeping up with competitors. In addition, the results show that the most important barriers respondents face are related to the organizational and cultural differences when cooperating with other partners. Other serious barriers are administrative burdens, financing and knowledge transfer problems Keywords Open innovation, SMES, motives for and barriers to cooperation 4 Open innovation in SMES Trends, motives and management challenges 1. INTRODUCTION Companies consider innovations as a major engine to enhance their performance and to strengthen their competitive position in the market. Many firms have paid most of their management attention to a greater focus on internal efficiencies of the development process, team structures, decision making and cross functional interaction. However, as more and more companies bring innovation straight to the heart of their corporate strategies, developing internal innovation capabilities is no longer sufficient to gain and sustain competitive advantage. Since innovation strategies look increasingly similar and commoditized, more and more organizations try to further improve their innovation performance through intensifying collaboration across industry networks and partnerships, opening up their innovation processes in line with the open innovation framework (Chesbrough 2003,2006; EIRMA, 2004 Traditionally, open innovation has been analyzed mainly within the context of large, multinational, technology firms (Chesbrough, 2003. Although Chesbrough et al. (2006) argue that large firms could differ from small firms in their adoption of open innovation, only a small number of studies on open innovation within smaller firms exist. For instance, Henkel (2006) examines both small and large firms, but focuses only on companies that develop open source software. Lecocq & Demil 2006) study the U s. tabletop role-playing game industry, which is a highly fragmented industry with SMES as the main players. Furthermore, Christensen et al 2005) illustrate the role of small companies over the life cycle of the technology They also show that firm size does influence the innovation strategy and value 5 capturing ability of firms on new technology. Nevertheless, prior studies have not yet systematically analyzed the notion of open innovation in SMES. Hence, it still remains to a large extend an unanswered question how small firms adopt to open innovation This paper addresses this gap by focusing on the open innovation practices in SMES Based on an exploratory survey among SMES in The netherlands, we intend to formulate an answer on the following questions: Is open innovation different for small firms as compared to large ones? Do we find homogeneous results for all SMES or can we make a distinction between different types of open innovation-strategies in different categories of SMES, such as services and manufacturing firms? What are the most important drivers for SMES to start open innovation practices? What are the major barriers? SMES do not have internal R&d labs and cannot rely on entrenched technological competences. They have to make systematic use of the competences of suppliers, customers, complementors (Nalebuff and Brandenburger, 1996) and other actors in the value system. Moreover, many SMES are active in medium-or low-tech industries and do not have formalized R&d-activities The paper intends to contribute to the literature in several ways. First, this study is the first one to investigate the use of open innovation practices in SMES in a systematic way and to identify the motives that drive firms to get involved in open innovation and the barriers that they face when pursuing a more open approach towards innovation. Second, the results of our study are based on a survey that operationalizes open innovation practices into different, measurable dimensions Third, most prior research on open innovation is based based on US firms (e g Chesbrough, 2003; Chesbrough and Crowther, 2006; Lecocq and Demil, 2006) and research about open innovation practices in Europe have been scarce. This paper 6 contributes to fill that void by analyzing open innovation behavior in small and medium sized companies in The netherlands The remainder of the paper is structured as follows. The next section discusses the concept of open innovation and the different dimensions that can be used to describe open innovation practices in firms. Next, we develop some theoretical arguments about the differences in adoption of open innovation between manufacturing and service firms, and between different size categories of SMES Furthermore, we analyze the motives that drive SMES to get engaged in open innovation and the barriers the experience when implementing it. Thereafter, we describe the survey and sample selection, followed by an analysis of trends in open innovation practices. Next, we explore what motivates firms to start open innovation practices and what type of barriers they experience when they implement open innovation. Finally, we draw some conclusions from the survey results and develop ideas for future research 2. OPEN INNOVATION Traditionally, large firms relied on internal R&d to create new products. In many industries, large internal R&d labs were a strategic asset and represent a considerable barrier to entry for potential entrants. As a result, large firms with extended R&d capabilities and complementary assets could outperform smaller rivals (Teece, 1986 This process in which large firms discover, develop and commercialize technologies internally has been labeled as'closed innovation'(Chesbrough, 2003. For a long time closed innovation has been a very successful way used by companies to sustain a competitive advantage in their different businesses. However, the innovation landscape has changed considerably: good ideas are widely distributed with no firm 7 having a monopoly, venture capital is abundant nowadays and the acceleration of the product life cycle has turned intellectual property (IP) into an increasingly perishable asset. As a result, a growing number of large MNES have been moving from an internally focused innovation process to one that is more †openâ€. In this new era of 'open innovation',firms use both internal and external pathways to exploit technologies and, concurrently, they scout different external sources of technology that can accelerate their innovation process (Chesbrough, 2003. In addition to internal R&d, established companies need to get access to external knowledge, such as startups, universities, suppliers, or even competitors to stay competitive in the long run Open innovation is thus a broad concept, which encompasses different dimensions. First of all, there is the inside-out movement, or technology exploitation in which existing technological capabilities are leveraged outside the boundaries of the firm. Next, there is an outside-in movement, also referred to as technology exploration, in which external sources of innovation are used to enhance current technological developments. In a fully open setting, companies combine both technology exploitation and technology exploration in order to create maximum value from their technological capabilities or other competencies 2. 1 Technology exploitation Firms can implement various strategies to commercialize technologies via external pathways, such as creating and spinning out new ventures, and the licensing of intellectual property to external parties (Chesbrough, 2003. Previous research on open innovation has discussed the spin off process of large firms (e g. Chesbrough 2003; Lord et al. 2002); ) several large high-tech companies spin off new ventures 8 because the business idea does not fit into the existing business model. The potential for these spin off companies is enormous; Chesbrough (2003) illustrates that the total market value of 11 projects which turned into new ventures exceeded that of their parent company, Xerox, by a factor of two In addition, firms can also profit from their own, unused IP when other firms with different business models find profitable, external paths to the market for an idea Chesbrough, 2006. However, the ability of firms to be successfully trade IP depends also on the appropriability conditions (West, 2003. If the appropriation regime is weak (Teece, 1986), outgoing knowledge spillovers allow competitors to imitate innovations and capture its value at the cost of the innovating firm. Thus, firms have to use different intellectual property rights strategies to prevent such situations 2. 2 Technology exploration On the other hand, there are also numerous ways in which a firm can get access to external sources of knowledge. Customers, employees and other firms are the most common sources of new ideas, but the use of venture capital, outsourcing of R&d and the licensing of other firms†IP are also becoming more common nowadays First of all, firms may benefit from user-initiated innovations by decreasing the need to generate and evaluate ideas or concepts, by reducing R&d and commercialization costs and by accelerating involving customers into the product development and commercialization process (Gales and Mansour-Cole, 1995. Failure to consider users'constrains and requirements in the design of innovation, often leads to difficulties in commercialization (Cooper and Kleinschmidt, 1995; Lettl et al 2006). ) Hence, for successful adoption, the entire innovation process requires"mutual adaptation"(Leonard-Barton, 1988), mutually beneficial collaboration between 9 producer and user (Foxall and Johnston, 1987), and successful conflict resolution Newman and Noble, 1990. Firms can involve customer information using different tactics in their innovation process; market research can be done to find out if customers prefer possible future characteristics of products. However, conventional market research methods may not work well in the instance of many industrial goods and services (Herstatt & Von Hippel, 1992. More recently, firms stimulate users to co-develop products or technologies, such as in the open source software (Henkel 2004; Hienerth, 2006. This practice is also becoming fashionable in other industries such as car design, electronic games, or sports equipment (e g. Franke and Shah 2003; Von Hippel, 2005. Henkel (2004) argues that firms (adopting open source strategies) may make their technology available to the public in order to elicit development collaboration, but without any contractual guarantees of obtaining it Not only customers but also firms'employees can contribute to a firm's overall innovative performance. Both in closed and open innovation paradigms, individual employees play a crucial but different role. Thus, a firm should foster a culture in which these knowledge workers are motivated to continuously search for new ideas In addition, firms that embark on open innovation should stimulate inter -organizational networking between employees of different firms. Several case studies illustrate that informal ties of employees with employees of other organizations or institutions are crucial to understand how new products are created and commercialized (Chesbrough et al. 2006). ) Morgan (1993) observed in the early nineties already that the role of formal reporting structures and detailed work processes had diminished a role in favor of informal networks of employees. These networks were in many cases cross-boundary linking employees of (locally bounded 10 networks of firms. The strength and dynamics of these connected groups of employees has a significant impact on firms'knowledge creating capability. 1 Another important dimension of technology exploration is inter-organizational networking. For instance, R&d alliances between noncompeting firms have become a popular vehicle for acquiring and leveraging technological capabilities (Gomes -Casseres, 1997. In addition, firms increasingly team up with competitors to share R&d costs and associated risks. Because of the fact that firms can get locked in innovation networks, it is important to search for optimal network configurations Rowley et al. 2000), which could also imply that they have to innovate in collaboration with competitors. In addition, more and more SME firms are entering into research collaborations with universities (e g. George et al. 2002). ) Without academic research outcomes many innovations could not have been realized or would have come much later (Fontana et al. 2006). ) Scientific results brought about increased sales and higher research productivity and patenting activity for firms Cohen et al. 1998). ) Additionally, interaction with suppliers & customers can provide missing external inputs into the learning process which the firm itself cannot (easily provide (Romijn and Albaladejo, 2002; Von Hippel, 2005. Users in the form of economic markets inform the design of technology and may even initiate the development by others of desired innovations (Gales and Mansour-Cole, 1995 Predictions of sources of innovation can be based on whether users or developers are most likely to receive the greatest economic benefit (von Hippel, 1988. Moreover Romijn and Albaladejo (2002) illustrate that firms may also use financial institutions 1 Academics and practitioners have analyzed the benefits of networked governance structures such as joint ventures, partnerships, strategic alliances and R&d consortia on the effective creation and integration of knowledge across organizations. However, there has been much less attention paid to how informal networks of employees in networked organizations may facilitate (or hamper knowledge creating and integration 11 banks, venture capitalists) as drivers for the development of new or improved products and or services Inter-organizational networking might also take the specific form of participation in new or existing companies, for instance through minority holdings or corporate venture capital investments (Chesbrough, 2002; Dushnitsky and Lenox 2005a; Ernst et al. 2005). ) Through these kinds of equity investments, firms gain a â€oewindow†on new technological developments (Keil, 2002. Moreover, the equity investment might serve as the creation of an option to further increase collaboration with the partner firm in case the technology provides to be valuable for the investing firm (Van de Vrande et al. 2006). ) Prior studies have shown already that corporate venture capital investments have a positive effect on the innovative performance of firms (Dushnitsky and Lenox, 2005b; Wadhwa & Kotha, 2006 Next, firms can engage in outsourcing of R&d or in-licensing of IP. By outsourcing we mean that firms enter arms-length agreements with third parties concerning the development of a new technology. In a world of closed innovation, the technologically complex parts of innovation should be done in-house, while the simpler parts could be outsourced. In an open innovation paradigm, other organizational forms to maximize the value caption effect could be in place; for instance Prencipe (2000) finds that aircraft engine manufacturers are able to retain knowledge about components whose production is outsourced. One specific engine maker was able to develop capabilities outside of the production, more focused on the integration of new technologies. This is in line with the role of a"network Orchestrator"(Lorenzoni and Baden-Fuller, 1995 Finally IP plays a crucial role in open innovation as a result of the in-and outflows of ideas,(Arora, 2002; Chesbrough, 2003,2006; Lichtenthaler, 2007. In 12 closed innovation, firms controlled their IP so that competitors could not profit from ideas. In open innovation, firms manage IP in a different way: they need to access external IP to fuel their own business model and to speed up and nurture their own research engine. This can be done by licensing-in other firms†IP to serve as a valuable add-on to the current business model of firms To conclude, open innovation in firms can take many different forms. It can be argued that the extent to which innovation processes in SMES reflect these different dimensions depends on their size and the type of firm under study. This will be discussed in the next section 3. INNOVATION IN SMALL AND MEDIUM-SIZED FIRMS As the traditional scale advantages of large, internal R&d labs in established companies erode, open innovation recognizes that smaller firms take a more prominent role in the contemporary innovation landscape. Chesbrough (2003 provides evidence that small firms (firms with less than 1000 employees) continually increased their share of total industrial R&d spending in the US during the last two decades. More specifically, small firms account for around 24%of all US industry spending in 2005 †compared to 4%in 1981. The larger firms with more than 25.000 employees were still responsible for 38%of total industry R&d spending in 2005 compared to 71%in 1981 (National Science Foundation, 2006. Hence, although large companies are still playing a prominent role in innovation, smaller firms are becoming increasingly important for industry R&d and thus for economic growth 13 3. 1 Type of industry SMES can be divided in different ways but an interesting segmentation is the division between services and manufacturing firms. Prior studies have acknowledged the fact that services and manufacturing firms are fundamentally different. According to Atuahene-Gima (1996) services differ from products in terms of intangibility inseparability, heterogeneity, and perishability. Intangibility refers to the fact that services can be regarded as experiences which makes it more difficult to assess their value before purchase. Inseparability highlights the role of the customer in the simultaneous production and consumption of the service. Heterogeneity and perishability point towards the variability in the quality of services and the inability to store services when supply exceeds demand. Their study shows how factors affecting the innovation potential differ greatly between these two groups of firms. Hence, one can expect that different dimensions of open innovation also will vary between services and manufacturing firms Traditionally, the importance of closed innovation was highlighted primarily for industrial firms. These firms were able to benefit from closed innovation because the in-house development and commercialization of their products was the only way to ensure that they would benefit from the inventions as well. However, the increasing technological complexity to produce new products, the short product life cycles, the mobility of engineers and the rise of the venture capital industry have forced these firms to open up their innovation processes. With products being more separable and homogenous, it is much easier to outsource parts of the R&d process or to in-source new ideas and technologies that fit the current business line. Moreover, in-en out -licensing of intellectual property is more an issue in firms where the use and development of intellectual property is at the heart of the innovation strategy, which is 14 the case in manufacturing firms. Although service firms, on the other hand, will be inclined to use networks and customer and employee involvement in the innovation process, we expect to find that in general manufacturing firms are involved more in open innovation than service firms. Moreover, we expect that the increase in open innovation practices is stronger in manufacturing firms than in service firms since open innovation has been documented for manufacturing companies. Part of current movement towards open innovation is related to a different approach of universities research labs and companies vis-Ã-vis technology and IP. We expect that the increase in use of open innovation practices has been more prominent in manufacturing companies since new technological developments are on average more important for manufacturing firms compared to service firms 3. 2 Size classes Aside from the fact that SMES are services or manufacturing firms, they also differ significantly in size. SMES are defined as firms with up to 500 employees. However there is still great difference in the innovation strategies of small firms (up to 100 employees) and medium sized enterprises (100-499 employees. The innovation processes of larger firms are structured typically more and professionalized, and larger firms typically have more resources than small firms. This has important implications for the use of open innovation in these firms. Although the use of inter -organizational networks, the involvement of employees and that of customers in the innovation processes seems to be equally feasible for both small and large SMES, the extent to which SME companies establish new ventures as a part of their open innovation strategy is likely to depend on firm size. Outsourcing of R&d and the spinning out of new ventures requires a structured and well organized innovation 15 process. Moreover, participation in other firms also calls for a certain amount of equity ERROR-Flatefilter: stop reading corrupt stream due to a Dataformatexception which can be used to make high-risk investments with uncertain return on investment. Larger firms typically have more financial resources to engage in these kinds of investments. The same holds for the in-and out-licensing of intellectual property rights; in-licensing of IP requires financial slack, whereas out-licensing of IP requires the structure and processes to formalize such agreements. Moreover licensing technology is not possible without patent righting skills. As a result, we expect that open innovation in general is used more commonly by large SMES and that for this size class, the increase in open innovation is stronger than for their smaller counterparts 3. 3 Motives and barriers Finally, we are interested in the motives and barriers that are involved with choosing a more open approach towards innovation. A large-scale study by EIRMA (2003 shows that the main motives for R&d managers in large corporations to participate in venturing activities is embedded in market-related arguments such as meeting customer demand, but also in collecting new ideas and knowledge, improving innovative performance, continuous growth and financial motives. In addition, Jacobs and Waalkens (2001) found that the main determinants to change the role of innovation within companies can be found in the improved capabilities for corporate renewal, shortening time-to-market, and better utilization of internal creativity. Hence we expect the motives for firms to undertake open innovation activities to be related to market considerations and the creation of knowledge As far as potential barriers to open innovation are concerned, prior studies about cooperation between firms have mentioned frequently that organizational 16 structure and culture are very important problems related to innovation and knowledge transfer. According to Meschi (1997), most of the organizational difficulties in international joint ventures are rooted in cultural distance, be it national or organizational. Moreover, Simonin (1999) finds that both cultural and organizational distances are related to ambiguity, which in turn negatively affects knowledge transfer. A study developed by a selected group of European R&d managers EIRMA (2003) furthermore shows that the management of different organizational cultures is a key factor in inter-firm cooperation. Companies that follow a more open approach to innovation will need to organize the way in which they manage inter-organizational relationships and network management. For many companies, this is a challenging managing task:''It has become essential to master the network'(EIRMA, 2004: iv). ) As a result, it is likely that barriers to open innovation are rooted in similar causes, including cultural and organizational problems as the most important items 4. DATA AND METHODS 4. 1 Survey description To analyze trends, motives and management challenges related to open innovation we used a dataset that was collected in 2005 by EIM, a research institute for business and policy research in The netherlands. Because the survey's target was to explore open innovation trends in SMES, it started with a number of screening questions First, firms had to be labeled as †active innovatorsâ€, i e. firms which have implemented at least one innovation during the period 2003-2005 and who claim that continuous renewal is part of their corporate strategy. In addition, the responding SMES had to be established at least seven years ago and respondents had to work at 17 least 7 years at the firm to ensure that they were able to give an accurate judgment concerning the development of open innovation in their companies The sample was stratified disproportionally across both manufacturing and service industries and across the two size classes. Potential respondents were randomly drawn from the population of all small and medium-sized firms in the Netherlands, defined as all firms with no more than 500 employees. Firms with less than 10 employees (i e. micro-firms) were excluded from the sample, because in general they have no or very limited in-house R&d activities. Besides, the population of micro-firms contains a relatively high share of start-ups. Such firms would not satisfy the criterion of SMES that have to be in operation for at least seven years The population of firms was derived from a database of the Chambers of Commerce, containing data on all Dutch firms. The data were collected in December 2005, over a period of three weeks, by means of computer assisted telephone interviewing (CATI. All respondents were small business owners or managers and innovation decision-makers. Attempts to contact reference persons were made five times before considering persons as non-respondents. In total 2, 230 respondents were contacted, of which 1, 206 (54%)were willing to participate in our survey. To check for non-response bias, the distribution of respondents and non-respondents across type of industry and size class were compared. The chi-square-tests contrasting these groups revealed no significant differences at the 5%level (p=0. 23 for type of industry and p=0. 55 for size classes), indicating that non-response bias was not a serious problem After our screening questions 605 respondents satisfied both criteria (active innovator and long tenure), which corresponds with a final sampling rate of 27 %18 Table 1 shows how respondents are distributed according to their type of industry and size class Table 1. Distribution of respondents across type of industry and size class Size class Type of industry 10-99 employees 100-499 employees total Manufacturing †food and beverages (NACE codes 15-16) 40 21 †chemicals, rubber and plastics (NACE codes 23-25) 54 22 †machinery and equipment (NACE codes 29-34) 19 32 †other manufacturers (NACE codes 17-22; 26-28; 35-36) 47 53 160 128 288 Services †IT (NACE code 72) 53 17 †business services (NACE code 74) 59 24 †other services (NACE codes 50-71; 92-93) 104 60 216 101 317 Total 376 229 605 4. 2 Operationalizing open innovation Open innovation was operationalized according to the different dimensions mentioned earlier in this paper2 4. 2. 1 Technology exploitation To measure the extent to which firms were involved in technology exploitation, we use variables measuring if firms had spun ever out new ventures, or licensed-out their own intellectual property in the period 2003-2005 In addition, respondents were asked to judge whether the use of these innovation strategies had increased, remained unchanged, or whether it had decreased in the period 2003-2005. Next, in case respondents had increased their usage of 2 An overview of the questions is available from the authors upon request 19 innovation strategies, they were invited to elaborate on their motives and perceived challenges in doing so 4. 2. 2 Technology exploration In similar vein, we included a number of questions on the use of technology exploration strategies. To address the role of customers, respondents were asked to which degree customers were involved in the innovation process, for instance by doing active market research, deploying new products which were specified by customers themselves, or producing new products based upon inventions by customers of users. The survey data contained a summary variable indicating customer involvement, i e. a dummy coded 1 if firms used input from their customers in recent innovation processes To measure the role of employees, respondents had to indicate to which degree employees were stimulated to contribute to innovation processes, e g. by investing in employees†ideas and initiatives, creating autonomous teams with own budgets to carry out innovations, or stimulating employees†external work contacts in order to enhance opportunity exploration. The survey data allowed distinguishing between employees that belong to the R&d department and those that are coming from other organizational parts of the company Furthermore, the survey also investigated whether firms collaborated with the different types of partners as described above, including complementors, competitors public knowledge centers (e g. universities), customers, suppliers, and investors (e g banks, venture capital firms 20 Finally, we looked at the degree firms participate by equity investments in new or existing companies, we asked whether respondents had ever outsourced R&d in the period 2003-2005, and to what extent the firm licensed IP from other firms For each type of technology exploration, respondents were asked to indicate whether the use of this particular type had increased, decreased or whether it remained unchanged in the period 2003-2005. In addition, respondents were given again the opportunity to elaborate on their motives and perceived challenges for each of these technology exploration mechanisms by means of open-ended questions 5. RESULTS A summary of the key open innovation practices in the Dutch SMES is presented in Table 2. The table shows the number of respondents that are involved actively in several open innovation practices and the perceptual change of these practices in the period 2003-2005 Table 2. Open innovation practices and their perceived change over time (n=605 Perceived change open innovation indicator Use increase no change decrease Technology exploitation Venturing 29%14%85%2 %License IP to other firms 10%3%95%1 %Technology exploitation Customer involvement 97%38%61%1 %Employee involvement 93%42%57%1 %Network usage in innovation processes 94%29%67%4 %Participation in other firms 32%16%84%1 %Outsourcing R&d 50%22%73%5 %License IP from other firms 20%5%93%2 %Table 2 clearly shows that network usage in innovation processes and the involvement of network partners, customers and employees in innovation processes is fairly 21 common among Dutch SMES. Licensing IP, venturing and participation in other firms are open innovation practices that are explored only by a minority if the respondents The most striking result is that the share of respondents who perceive an intensification of the use of these open innovation practices is substantially larger than those who experience a decrease. This is the case for all indicators in Table 2 Especially employee involvement, customer involvement, the use of network partners and (to a lesser extent) outsourcing of R&d have experienced a substantial increase in popularity in the last three years 5. 1 Type of industry Table 3 shows the share of manufacturing and service SMES using open innovation practices. Customer involvement, employee involvement, and the usage of networks in the innovation process appear to be the main types of open innovation practices used by both manufacturing and services firms. Oneway analysis of variance furthermore demonstrates that outsourcing R&d is done more frequently by manufacturers. The same applies to licensing IP from other firms. In contrast, the results show that venturing is more popular among services firms compared to manufacturing firms service SMES spin out new ventures more often. Thus, although manufacturing firms are involved to a larger extent in outsourcing of R&d and the licensing of IP from third parties, the results also show no difference between manufacturing firms and services firms for the other types of open innovation 22 Table 3. Open innovation practices and perceived change in manufacturing and service SMES Use Perceived change (1 Open innovation indicator Manufacturing n=288 Services n=317 F -value Manufacturing n=288 Services n=317 F -value Technology exploitation Venturing 24%33%5, 8 0. 09 0. 15 3, 8 License IP to other firms 11%8%1, 5 0. 02 0. 02 0, 1 Technology exploration Customer involvement 98%97%0, 7 0. 34 0. 40 2, 2 Employee involvement 94%93%0, 4 0. 41 0. 41 0, 1 Network usage in innovation processes 95%94%0, 3 0. 24 0. 26 0, 3 Participation in other firms 29%34%1, 5 0. 14 0. 15 0, 1 Outsourcing R&d 59%43%16,7**0. 23 0. 13 5, 9 License IP from other firms 25%15%10,7*0. 04 0. 03 0, 4 1) Mean score with increase coded 1, no change coded 0 and decrease coded-1 **p<0. 001,*p<0. 01, p<0. 05 Table 3 also not only shows whether manufacturers and service firms deploy open innovation practices in a different way but also whether they perceive changes in popularity of these practices in a different way. Respondents from both manufacturing and service companies indicate that on average open innovation practices have been increasingly used in the last three years (as mean scores are positive for both types of firms). ) Oneway analysis of variance furthermore shows that manufacturers have experienced a stronger shift towards more outsourcing of R&d, while services firms experienced a stronger increase in new venturing. There are no statistical differences between the services and manufacturing SMES for the other items 5. 2 Size classes SMES are not a homogenous group of firms. SMES of different firm sizes are expected to deploy open innovation practices in different ways. As SMES grow and reach a critical size, they organize the company in a more formal way, they hire specialists for a broad range of particular job functions and they formalize the firm's 23 strategy in order to ensure market positions against large (r) and international competitors. In many SMES that reach a critical size, formal R&d and innovation practices start to play a critical role in developing and sustaining competitive advantages. At that point, firms are also thinking in a more deliberate way than smaller SMES how to improve these innovating activities. Hence, since larger SMES have formalized more) internal R&d and innovation practices, we expect that the range of possibilities that open innovation practices offers is larger for large SMES than for small ones. For the same reasons, we also expect that open innovation practices have been embraced more rapidly by larger SME as they have more to win from it Table 4 shows that larger SMES (100-499 employees) are on average much stronger involved in outsourcing R&d, participation in other firms and in-and out -licensing, as compared to the small SMES(<100 employees. Both size categories show no significant differences with respect to customer and employee involvement networking with partners because these are practices that have no discriminating power since all firms are involved actively in them. Only a minority of small and large SMES is involved in venturing but there is no clear relation with firm size 24 Table 4. Open innovation practices and perceived change across size classes Use Perceived change (1 Open innovation indicator 10-99 employees n=376 100-499 employees n=229 F-value 10-99 employees n=376 100-499 employees n=229 F-value Technology exploitation Venturing 27%32%1, 9 0. 11 0. 14 1, 5 License IP to other firms 6%16%18,9**0. 01 0. 04 2, 1 Technology exploration Customer involvement 97%98%1, 2 0. 30 0. 50 22,8 **Employee involvement 92%96%3, 0 0. 37 0. 48 7, 5 *Network usage in innovation processes 94%95%0, 2 0. 20 0. 33 8, 8 *Participation in other firms 24%44%28,0**0. 13 0. 18 3, 9 Outsourcing R&d 42%64%27,3**0. 14 0. 24 5, 7 License IP from other firms 14%29%23,1**0. 02 0. 07 4, 8 1) Mean score with increase coded 1, no change coded 0 and decrease coded-1 **p<0. 001,*p<0. 01, p<0. 05 There is a substantial difference between small and large SMES in their adaptation rate of open innovation practices. All values in the two columns are higher for the larger SMES indicating that they adopted open innovation practices more quickly than smaller firms. These differences in adoption rate are all significant with the exception of venturing and licensing IP to other companies, showing that overall, larger SMES experience a stronger increase in the use of open innovation practices compared to smaller SMES. The results indicate that there might be a growing differentiation between small and larger SMES in adapting open innovation because larger SMES are relatively more involved in open innovation and they experience stronger growth in adapting open innovation practices than their smaller counterparts 5. 3 Clusters To explore patterns of open innovation among SMES we relied on cluster analysis techniques. These are sensitive to the selection of the variables used, since the addition of irrelevant variables can have a serious effect on the results of the 25 clustering (Milligan and Cooper, 1987. Cluster variables should also be representative for the typology one wants to present (Everitt, 1993. Here, we selected Table 2†s indicators to explore whether the SME population contained any homogeneous groups of firms with similar use of open innovation practices Our analysis consists of three steps. We started with a principal component analysis to reduce the number of dimensions in our indicators. Next, we applied cluster analysis techniques to explore patterns of open innovation practices among SMES. Finally, we used oneway analysis of variance to validate the taxonomy Several studies that perform taxonomies of innovation patterns use Principal Component Analysis (PCA), as a way to reduce the number of dimensions to be used in the clustering. In general, PCA reduces the risk that single indicators dominate a cluster solution, and helps to prevent the inclusion of irrelevant (non-discriminative variables (Everitt, 1993; Hair et al. 1998). ) Another advantage is that the factors obtained from a PCA are uncorrelated and therefore no variable would implicitly be weighted more heavily in the clustering and thus dominate the cluster solution (Hair et al.,, 1998, p. 491. We first tested if our data were suitable for a component analysis by calculating Measures of Sampling Adequacy (MSA) for the individual variables Hair et al. 1998). ) All the variables had satisfactory values(>0. 57) and were suitable candidates for a PCA. In addition, KMO and Bartlett†s test of sphericity met common standards (KMO=0. 61 and p (Bartlett)< 0. 001)( Hair et al. 1998). ) In performing the principal component analysis, we used the extraction technique with varimax rotation and, for the selection of the number of factors, we applied the latent root criterion requiring that the eigenvalues are greater than one. As result, we obtained a three -26 dimensional solution explaining 57%of the variance. Since we used the PCA in order to reduce the number of dimensions the output is presented not here3 In the cluster analysis we combined hierarchical and nonhierarchical techniques. This helps to obtain more stable and robust taxonomies (Milligan and Sokol, 1980; Punj and Stewart, 1983. We first carried out a hierarchical analysis to group SMES into homogeneous clusters, by using the Ward†s method based on squared Euclidian distances. Homogeneous groups are built so as to minimize the distance in scores of firms within a single cluster and to maximize the distance in scores between companies from the various clusters. Next, nonhierarchical cluster analyses were carried out to improve the initial solutions and to select the number of clusters for the taxonomy. At first, a visual inspection of the dendogram, plotting the initial solutions of the hierarchical analysis, suggested that a taxonomy with either three of four clusters could be feasible. For a better assessment of robustness we considered a range of initial solutions from the hierarchical analysis, going from two up to five clusters. For each number of clusters (k), we perform a k-means †non -hierarchical†cluster analysis, in which SMES were divided iteratively into clusters based on their distance to some initial starting points of dimension k. While some k -means methods use randomly selected starting points, we employed the centroids of our initial hierarchical solutions for this purpose (cf. Milligan and Sokol, 1980; Punj and Stewart, 1983. To assess which solution should be preferred we computed Kappa, the chance corrected coefficient of agreement (Singh, 1990), between each initial and final solution. The three-cluster solution appeared to have the highest value of Kappa (k=0. 95, while k<0. 94 for the other solutions 3 The results can be obtained from the authors 27 As a basic validity requirement we checked for significant differences on the variables used to develop our taxonomy (Milligan and Cooper, 1987. One-way analyses of variance for each variable confirmed this (see Table 5 Table 5. Open innovation practices across three clusters cluster1 (n=133) cluster2 (n=411) cluster3 (n=61) F-value Technology exploitation Venturing 40%27%15%7, 4 **License IP to other firms 44%1%0%181,6 **Technology exploration Customer involvement 98%99%77%66,5 **Employee involvement 98%99%38%388,9 **Network usage in innovation processes 99%100%44%317,7 **Participation in other firms 44%31%11%10,5 **Outsourcing R&d 70%48%21%22,2 **License IP from other firms 86%0%5%351,5 ***p<0. 001,*p<0. 01, p<0. 05 Firms in cluster 1 are involved strongly in all types of open innovation practices. They use a broad set of these practices to improve their innovation performance and are on average larger and more based in manufacturing compared to the other two clusters see Table 6). Cluster 2 is the largest group. The firms in this cluster rely mainly on the involvement of network partners, customers and employees in their innovation processes. Some of them also rely on outsourcing of R&d, venturing and/or participation in other firms. Almost none of them trade in intellectual property Cluster 3 includes innovative firms that only rely on customer involvement and networking with partners. Most of them are involved not in relatively complex and formalized transaction forms of open innovation activities such as venturing, IP -trading, outsourcing of R&d and participation in other firms To further explore the distinction between the three clusters, Table 6 reveals how respondents think about the changes that took place in the period 2003-2005. We added the information about firm size and share of manufacturing firms per cluster 28 Cluster1 are the most important adopters of open innovation practices. Differences with the other clusters are significant on basically all open innovation indicators. They are involved in more complex and formalized open innovation activities. Their involvement in IP-sharing indicates that these firms also have a more technology based open innovation network. Firms in cluster 3 are poor adopters of open innovation practices. This is a relatively small group of companies that mainly rely on customer involvement and to a minor extent on employee involvement and network partners. This is, of course, a (too) narrow interpretation of open innovation Table 6. Perceived change (1) of open innovation practices, type of industry and size distributions across three open innovation clusters cluster1 (n=133) cluster2 (n=411) cluster3 (n=61) F-value Perceived change Technology exploitation Venturing 0. 17 0. 11 0. 05 3, 5 License IP to other firms 0. 11 0. 00 0. 00 13,0 **Technology exploration Customer involvement 0. 52 0. 38 0. 05 19,5 **Employee involvement 0. 53 0. 43 0. 07 18,2 **Network usage in innovation processes 0. 29 0. 27 0. 05 5, 1 *Participation in other firms 0. 23 0. 14 0. 02 7, 4 **Outsourcing R&d 0. 21 0. 18 0. 07 1, 9 License IP from other firms 0. 17 0. 00-0. 03 24,4 **Sector and size distributions Share of manufacturing firms (versus service firms) 58%45%43%3, 7 Share of firms with 100-499 employees (vs. 10-99 empl. 55%34%25%12,0 **1) Mean score with increase coded 1, no change coded 0 and decrease coded-1 **p<0. 001,*p<0. 01, p<0. 05 How are open innovation practices evolving over time within the three SME-clusters Table 6 indicates that the three clusters evolved in the direction of an intensified use of open innovation practices (there is only a small decrease in in-licensing in clusters 3). However, there are huge differences in the adaptation rate of the three clusters Firms in cluster 1, which are strongly embracing open innovating, also intensified the 29 use of open innovation practices the most in the last three years. The opposite is true for the poor open innovation adopters in cluster 3. In other words, the differences between the three clusters are growing over time. The sector and size distributions are in line with our expectations. Cluster 1, consisting of firms which strongly embrace open innovation, includes the largest share of large SMES (55%)and manufacturing firms (58 %5. 4 Motives for open innovation in SMES SMES clearly have taken up a more open approach towards innovation. An important question in this respect is: what drives SMES to open up the innovation process? Open questions in the inquiry allowed respondents to reveal their motives why their company is moving in the direction of an open innovation model. More specifically companies were asked to clarify their motives when they get involved in the following 'open innovation'-practices: outsourcing of R&d, setting up new ventures participation in new or existing firms, involvement of external partners in the innovation process, involvement of users in the innovation process, involvement of non-R&d employees in the innovation process The different answers of the respondents to the question what drives them to get involved in open innovation practices were coded, resulting in the categories described in Table 7. The coding process was organized with two reviewers. They first read all open-ended answers and together identified a number of preliminary categories. Next, they carefully studied all answers and classified them into the scheme. New categories could be proposed whenever they felt that the categories were insufficient or should be refined. Finally, all classifications were compared and different opinions discussed and resolved. Because only few SMES possess and trade 30 IP (see Table 2), the data did not contain enough records to provide reliable insights about respondents†motives and challenges on this topic Table 7. Classification of open innovation motives Category Description Control Increased control over activities, better organization of complex processes Focus Fit with core competencies, clear focus of firm activities Renewal Improved product development, process-/market-innovation, integration of new technologies Knowledge Gain knowledge, bring expertise to the firm Costs Cost management, profitability, efficiency Capacity Cannot do it alone, counterbalance lack of capacity Market Keep up with current market developments, customers, increase growth and/or market share Utilization*Optimal use of talents, qualities, and ideas of current employees Policy*Organization principles, management conviction that involvement of employees is desirable Motivation*Involvement of employees in the innovation process increases their motivation and commitment *Only used for coding motives related to employee-involvement Table 8 below shows that for almost all open innovation practices pursued by SMES the most important motives are market-related ones. For the majority of respondents using new innovation methods is regarded as a way to keep up with market developments and to meet customer demand, which should eventually result in increased growth, better results, or a bigger market share. Market-related motives are the most important determinant for companies to engage in venturing (31%),to participate in other firms (36) %and to involve user in the innovation process (61 %Many SMES believe it is necessary to use a broad set of methods to meet the ever -changing customer demand and to prevent the firm from being outperformed by competitors or new entrants Another important reason for companies to engage in open innovation is the pursuit of corporate renewal. Corporate renewal refers to motives related to process innovation, the desire to develop products faster and more effective, or to incorporate new technologies in current products. One out of five respondents engaged in venturing, participation in other firms, involvement of external parties, and user 31 involvement lists corporate renewal as a reason to further pursue a specific innovation practice An important finding is that the different innovation practices have the same underlying motives. This implies that venturing, participation in other firms, inter -organizational networks and customer involvement are complementary innovation activities in improving product development, integrating new technologies and keeping up with current market developments. The only exception is improving the involvement of non-R&d employees in the innovation process: this innovation practice is related to three motives that are clearly different from the other motives Table 8. Motives for different types of open innovation Type of open innovation Motive Outsourcing R&d n=134 Venturing n=83 Participation in other firms n=94 Network usage n=175 Customer involvement n=232 Employee involvement n=256 Control%1 1 3 1 1 9 Focus%3 8 0 1 0 -Renewal%8 23 24 21 19 -Knowledge%44 4 6 35 5 -Costs%9 13 11 2 2 -Capacity%13 0 5 7 3 -Market%14 31 36 22 61 13 Utilization%--30 Policy%--15 Motivation%--22 Other%8 19 14 11 10 11 Total%100 100 100 100 100 100 Employee involvement is the only type of innovation in which the respondents do not mention the objectives listed in the other types of innovation. Almost 30%of the respondents that involve non-R&d employees in their innovation process do so because they feel that the skills of their employees can be utilized in a more efficient way, and that they can complement the innovation initiatives of the management and/or R&d department. In addition, many companies involve employees for motivational reasons. Up to 15%of the respondents is convinced of the added value 32 of employee involvement for innovation; often this is part of the firm's policy in this case. Another 22%sees the involvement of employees mainly as a way to motivate them. The direct impact on the bottom-line in that case is less important as employees are engaged primarily in the innovation process to increase their overall performance on the job. Finally, market considerations are also important: after all, employees may be closely related to the market and therefore have a better idea than managers or engineers about the potential success of products and the problems they experience with customers. In this case, employee involvement is a valuable source of knowledge in the innovation process Finally, there are also motives that are primarily related to specific types of open innovation. For instance, 8%of the respondents list the corporate brand reputation as a reason to engage in venturing activities. In this case, the new venture commercializes products that do not fit the corporate brand or strategy. In addition lack of internal knowledge forces SMES to source new, externally developed knowledge and expertise (44%)and to get external actors involved in the firm's innovation process (35%.%Another vital reason for the outsourcing of R&d is to gain from complementary resources in order to spread the risks and to compensate for a lack of current R&d capacity (13 %5. 5 Barriers to open innovation in SMES The barriers companies perceive when they pursue an open innovation strategy is another important issue in determining the success of open innovation in SMES. For each of the different types of open innovation activities, respondents were asked to list the hurdles they experienced. The answers were categorized again using an open coding process. Table 9 shows the resulting classification 33 Table 9. Classification of open innovation barriers Category Description Administration Bureaucracy, administrative burdens, conflicting rules Finance Obtaining financial resources Knowledge Lack of technological knowledge, lack of competent personnel, lack of legal/administrative knowledge Marketing Insufficient market intelligence, market affinity, marketing problems with new products Organization/culture Balancing innovation and daily tasks, communication problems, aligning partners organization of innovation Resources Costs of innovation, time needed Property rights Ownership of developed innovations, user rights when different parties cooperate Quality of partners Partner does not meet expectations, deadlines are met not User acceptance Adoption problems, customer requirements misjudged Customer demand Customer demand too specific, innovation appears not to fit the market Competent employees Employees lack knowledge/competences, not enough labor flexibility Commitment Lack of employee commitment, resistance to change Idea management Employees have too many ideas, no management support Table 10 shows the extent to which the barriers mentioned above matter for each of the different types of open innovation activities. Organization and corporate culture -related issues that typically emerge when two or more companies are working together are clearly the most important barrier that firms face when they engage in venturing (35%),participation in other firms (75), %and the involvement of external parties and users (resp. 48%and 30%.%These types of open innovation require cooperation among different organizations, or, in the case of venturing, employees who leave the organization. These inter-organizational relationships frequently lead to problems concerning the division of tasks and responsibility, the balance between innovation and day-to-day management tasks, and communication problems within and between organizations 34 Table 10. Barriers to different types of open innovation Type of open innovation Motive Venturing n=40 Participation in other firms n=45 Network usage n=53 Customer involvement n=68 Employee involvement n=88 Administration%28 13 10 --Finance%10 0 5 --Knowledge%5 5 ---Marketing%10 5 ---Organization/culture%35 75 48 30 -Resources%5 0 7 10 17 Property rights%--5 10 -Quality of partners%--24 --User acceptance%--13 -Customer demand%--28 -Competent employees %--24 Commitment%--51 Idea management%--8 Other%8 3-8 -Total%100 100 100 100 100 The availability of time and resources is another barrier. This is a barrier for almost all types of open innovation practices but the relatively low scores in Table 10 indicate that time and resources are not the most important barriers to implement open innovation practices. Administration-related problems occur much more frequently typically in the context of venturing (28%),participation in other firms (13%)and the involvement of external parties (10%),more specifically when cooperating with governmental or other not-for-profit institutions. Administrative burdens are also prominent when the company receives governmental subsidies and grants Governmental support is experienced as being highly inflexible, also because it is not allowed to change partners and such programs cannot be ended prematurely In addition, every single open innovation practice has its own specific problems. For instance, when companies involve external parties in the innovation process, they frequently report that these partners cannot meet the expectations or deliver the required quality of a product or a service. User involvement goes together with problems related to property rights, adoption and too specific customer demands When involving employees, it often turns out that they do not have required the 35 capabilities or skills to make a valuable contribution to innovation, or they lack motivation to do so. It also happens that in the end, management decides not to take up any of the ideas provided by employees or that the number of ideas coming from individual employees just gets too large to handle in an efficient way. This, in turn poses new challenges to managers when they want to get the most out the creativity of large numbers of individuals. Eventually they can get assistance from a growing number of specialized services firms to execute this job4 Overall, we can conclude that many barriers for open innovation in SMES are related to corporate organization and culture, no matter which type of open innovation is pursued. On top of that, different types of open innovation also have their own specific types of problems and barriers to overcome. Remark also that the number of observations in Table 10 is quite smaller than in Table 9. There are three possible explanations for this observation: first, it can indicate that many respondents did not experience any barriers to implement open innovation practices; next, respondents may not be aware of any barriers because they cannot compare them with best practices; finally, respondents were aware of some problems but could not articulate them 6. DISCUSSION AND CONCLUSION SMES play an increasingly important role in innovation and job creation, but are nevertheless left out of the research on open innovation, which has been analyzed mainly within the context of large, technology user firms (Chesbrough, 2003. In this study we have addressed this gap by analyzing open innovation practices of SMES in The netherlands. The survey results indicate that open innovation is also becoming 4 A nice example is BIG Idea Group. See for more information Christensen and Anthony (2001 36 increasingly popular among SMES. This is not a surprising, considering the increasingly important role small and medium sized firms play in innovation. After all, small firms often lack resources to develop and commercialize new product in -house and as a result are inclined more often to collaborate with large, firms In addition, the survey results show that open innovation is not entirely different for services and manufacturing firms as we expected based on the literature Manufacturing firms are on average more active in the outsourcing of R&d and the out-licensing of IP, a result that is not surprising given the technological commitment of these firms, but they do not differ with service firms on other open innovation activities. This is an important finding; open innovation is as relevant for service firms as it is for manufacturing firms and research about open innovation should not be limited to SMES that are involved in formal R&d activities. In contrast, we found significant differences between different SME-sizes. The results of the cluster analysis furthermore show that there are different open innovation strategies and practices among SMES. We identified three clusters of firms that adapt open innovation practices in different ways. Consequently, further research about open innovation in SMES should concentrate on these different strategies of SMES to co-innovate with partners Finally, we identified several motives for firms to start open innovation practices and barriers that SME managers encounter when they open up their innovation process. Open innovation is motivated mainly by market-related targets these are the most important driver for firms to engage in venturing, to participate in other firms and to involve user in the innovation process. Most SMES use a broad set of methods to meet the ever-changing customer demand and to stay competitive Corporate renewal is second most important driver towards open innovation. In 37 addition, many barriers for open innovation in SMES are related to corporate organization and culture, no matter which type of open innovation practice is pursued Since the aim of this study was to explore the open innovation practices in small and medium sized enterprises, there are a number of avenues for future research. First, following up on the different clusters that were indentified in this study, future research needs to specify these different SME strategies how to tap into external innovation sources. Another conclusion we can draw from this clear segmentation of innovating SMES is that research should not only focus on differences in open innovation practices between large firms and SMES but also between different types of SMES. There is certainly no one unique way in which SMES deploy open innovation strategies, but we have no further specifications about these different strategies. In addition, the current survey does not study how large and small firms interact in open innovation. Christensen et al. 2005) shows that large established companies and small start-ups manage open innovation differently reflecting their differential position within the innovation system. Hence, future research should focus on the requirements of open innovation on differences in culture, structure and decision making between partners of different sizes and from different industries. Next, our research does not indicate how SMES get organized to manage open innovation-practices. Considering that the typical management challenges for SME-managers are quite different than those of managers of large firms that want to ignite the organic growth engine in their company, this is an interesting uncharted area for future research (Chesbrough et al. 2006). ) Finally, we did not explore how open innovation in SMES is enhanced by the local or national innovation systems. The proximity of universities, research labs, large companies and lead users may play a role in the deployment of open innovation in SMES. In similar 38 vein, an innovation policy fostering transactions between these innovation partners may also play a significant role 39 REFERENCES Arora, A.,2002. Licensing Tacit Knowledge: Intellectual Property rights and the Market for Know-how. Economics of Innovation and New Technology 4 (1), 41 -59 Atuahene-Gima, K.,1996. Differential Potency of Factors Affecting Innovation Performance in Manufacturing and Services Firms in Australia. Journal of Product Innovation Management 13,35-52 Chesbrough, H.,2002. Making Sense of Corporate Venture capital. Harvard Business Review, March 2002,4-11 Chesbrough, H.,2003. Open Innovation: The New Imperative for Creating and Profiting from Technology. Harvard Business school Press: Boston, MA Chesbrough, H.,2006. Open business models: How to thrive in a new innovation landscape. Harvard Business school Press: Boston, MA Chesbrough, H.,Crowther, A k.,2006. Beyond high tech: early adopters of open innovation in other industries. R&d Management 36 (3), 229-236 Chesbrough, H.,Vanhaverbeke, W.,West, J.,2006 (eds. Open innovation Researching a new paradigm. Oxford university Press: London Christensen, C. M.,Anthony, S d.,2001. What's the BIG idea. Case nr 9-602-105 Harvard Business school, Boston: MA Christensen, J-F.,Oleson, M. H.,Kjã r, J. S.,2005. The industrial dynamics of Open innovation †Evidence from the transformation of consumer electronics. Research Policy 34,1533-1549 Cohen, W. M.,Florida, R.,Randazzese, L.,Walsh, J.,1998. In: Noll, R. Ed Industry and the Academy: Uneasy Partners in the Cause of Technological 40 Advance, in Challenges to the University, Brookings Institution Press WASHINGTON DC Cooke, P.,2006. Regional Knowledge Capabilities and open innovation: Regional Innovation Systems and Clusters in the Asymmetric Knowledge Economy. In Breschi, S.,Malerba, F. eds..Clusters, Networks & Innovation. Oxford: Oxford University Press Cooper, R. G.,Kleinschmidt, E. J.,1995. Benchmarking the firm's critical success factors in new product development. Journal of Product Innovation Management 12 (5), 374-391 Dushnitsky, G.,Lenox, M. J.,2005a. When do firms undertake R&d by investing in new ventures? Strategic Management Journal 26,947-965 Dushnitsky, G.,Lenox, M. J.,2005b. When do incumbents learn from entrepreneurial ventures? Corporate venture capital and investing firm innovation rates. Research Policy 34,615-639 EIRMA, 2003. Innovation through Spinning In and Out. Working group Report WG60, Eirma: Paris EIRMA, 2004. Technology Access for open innovation. Working group Report WG63, Eirma: Paris Ernst, H.,Witt, P.,Brachtendorf, G.,2005. Corporate Venture capital as a Strategy for External Innovation: An Exploratory Empirical Study. R&d Management 25 233-242 Everitt, B. S.,1993. Cluster analysis. Oxford university Press, London Fontana. R.,Geuna, A.,Matt M.,2006. Factors affecting university†industry R&d projects: The importance of searching, screening and signaling. Research Policy 35, 309†323 41 Foxall, G r.,Johnston, B.,1987. Strategies of user-initiated product innovation Technovation 6 (1), 77-102 Franke, N.,Shah, S.,2003. How Communities Support Innovative Activities: An Exploration of Assistance and Sharing Among End-users. Research Policy 32 157-178 Gales, L.,Mansour-Cole, D.,1995. User involvement in innovation projects: toward an information processing model. Journal of Engineering and Technology Management 12,77-109 George, G.,Zahra, S. A.,Wood, D. R.,2002. The effects of business-university alliances on innovative output and financial performance: A study of publicly traded biotechnology companies. Journal of Business Venturing 17,577-609 Gomes-Casseres, B.,1997. Alliance Strategies of Small Firms. Small Business Economics 9, 33-44 Hair, J. F.,Anderson, R. E.,Tatham, R. L.,Black, W c.,1998. Multivariate Data Analysis. 5th ed. Prentice hall, Englewood Cliffs, NJ Henkel, J.,2004. Open source software from commercial firms †Tools, complements and collective invention. Zfb-Ergã¤nzungsheft Henkel. J.,2006. Selective revealing in open innovation processes: The case of embedded Linux, Research Policy 35, 953†969 Herstatt, C.,Von Hippel, E.,1992. From experience: Developing new product concepts via the lead user method: A case study in a"low tech"field. Journal of Product Innovation Management 9, 213-221 Hienerth, C.,2006. The commercialization of user innovations: the development of the rodeo kayak industry. R&d Management 36,273-294 42 Jacobs, D.,Waalkens, J.,2001. Innovatie: vernieuwingen in de innovatiefunctie van ondernemingen. AWT achtergrondstudie 23, Kluwer: Deventer Lecocq, X.,Demil, B.,2006. Strategizing industry structure: the case of open systems in low-tech industry. Strategic Management Journal, 27: 891†898 Leonard-Barton, D. A.,1988. Implementation as mutual adaptation of technology and organization. Research Policy, 17: 251-267 Lettl, C.,Herstatt, C.,Gemuenden, H. G.,2006. Users†contributions to radical innovation: evidence from four cases in the field of medical equipment technology. R&d Management 36,251-272 Lichtenthaler, U.,2007. The drivers of technology licensing: An industry comparison California Management Review 49 (4), 67-89 Lord, M d.,Mandel, S w.,Wager, J. D.,2002. Spinning out a Star. Harvard Business Review 80,115-121 Lorenzoni, G.,Baden-Fuller, C.,1995. Creating a Strategic Center to Manage a Web of Partners. California Management Review 37,146-162 Meschi, P. †X.,1997. Longevity and cultural differences of international joint ventures: Toward time-based cultural management. Human Relations, 50: 211 -228 Milligan, G. W.,Cooper, M. C.,1987. Methodology Review: clustering methods Applied Psychological Measurement 11,329-354 Milligan, G. W.,Sokol, L. M.,1980. A two-stage clustering algorithm with robust recovery characteristics. Educational and Psychological Measurement 40,755 -759 Morgan, G.,1993. Imaginization. Sage California 43 National Science Foundation, 2006. Science Resource Studies, Survey of Industrial Research Development Newman, M.,Noble, F.,1990. User involvement as an interaction process: A case study. Information systems Research 1, 89-113 Nalebuff, B. J.,Brandenburger A m.,1996. Co-opetition. London: Harpercollins Prencipe, A.,2000. Breadth and depth of technological capabilities in Cops: The case of the aircraft engine control system. Research Policy 29 (7†8), 895†911 Punj, G.,Stewart, D. W.,1983. Cluster analysis in marketing research: review and suggestions for application, Journal of Marketing Research, 20: 134-148 Romijn, H.,Albaladejo, M.,2002. Determinants of innovation capability in small electronics and software firms in southeast England. Research Policy 31, 1053†1067 Rowley, T.,Behrens, D.,Krackhardt, D.,2000. Redundant governance structures: An analysis of structural and relational embeddedness in the steel and semiconductor industries. Strategic Management Journal 21, 369†386 Simonin, B. L.,1999. Ambiguity and the process of knowledge transfer in strategic alliances. Strategic Management Journal 20,595-623 Singh, J.,1990. A typology of consumer dissatisfaction response styles. Journal of Retailing 661,57-99 Teece, D.,1986. Profiting from technological innovation: Implications for integration collaboration, licensing and public policy. Research Policy 15,285-305 Van de Vrande, V.,Lemmens, C.,Vanhaverbeke, W.,2006. Choosing governance modes for external technology sourcing. R&d Management 36,347-363 Von Hippel, E.,1988. The Sources of Innovation, New york: Oxford university Press 44 Von Hippel, E.,2005. Democratizing Innovation. MIT Press: Cambridge, MA Wadhwa, A.,Kotha, S.,2006. Knowledge creation through external venturing Evidence from the telecommunications equipment manufacturing industry Academy of Management Journal 49, 819†835 West, J.,2003. How open is open enough? Melding proprietary and open source platform strategies. Research Policy 32, 1259†1285 West, J.,Callagher, S.,2006. Challenges of open innovation: the paradox of firm investment in open-source software. R&d Management 36,319-331 45 The results of EIM's Research Programme on SMES and Entrepreneurship are published in the following series: Research Reports and Publieksrapportages. The most recent publications of both series may be downloaded at: www. entrepreneurship-sme. eu Recent Research Reports and Scales Papers H200818 10-11-2008 High-Growth SMES Evidence from The netherlands H200817 3-11-2008 Internationalization of European SMES towards Emerging Markets H200816 27-10-2008 Measuring business dynamics among incumbent firms in The Netherlands H200815 20-10-2008 Vergrijzing van het arbeidsaanbod H200814 16-10-2008 User Innovation in SMES: Incidence and Transfer to Producers H200813 30-9-2008 How Does Entrepreneurial Activity Affect the Supply of Business Angels H200812 16-9-2008 Science and technology-based regional entrepreneurship in the Netherlands: building support structures for business creation and growth entrepreneurship H200811 8-9-2008 What Determines the Growth Ambition of Dutch Early-Stage Entrepreneurs H200810 6-8-2008 The Entrepreneurial Advantage of World Cities Evidence from Global Entrepreneurship Monitor Data H200809 25-7-2008 The Entrepreneurial Adjustment Process in Disequilibrium Entry and Exit when Markets Under and Over Shoot H200808 2-7-2008 Entrepreneurial Career Capital, Innovation and New Venture Export Orientation H200807 24-6-2008 Twee decennia ondernemerschapsbeleid in beeld: een jong beleidsprogramma in sociaaleconomische context geplaatst H200806 18-6-2008 Overcoming Resource-Constraints through Internationalization? An Empirical Analysis of European SMES H200805 9-6-2008 Whither a flat landscape? Regional differences in Entrepreneurship in The netherlands H200804 19-2-2008 Samenwerken op afstand H200803 1-1-2008 Explaining Preferences and Actual Involvement in Self -Employment: New Insights into the Role of Gender H200802 5-6-2008 Intrapreneurship; Conceptualizing entrepreneurial employee behaviour H200801 12-11-2008 Investigating Blue Ocean v. Competitive Strategy: A Statistical Analysis of the Retail Industry H200723 21-12-2007 Overoptimism Among Entrepreneurs in New Ventures: The Role of Information and Motivation H200722 21-12-2007 The relevance of size, gender and ownership for performance -related pay schemes H200721 21-12-2007 The Role of Export-Driven New Ventures in Economic growth A Cross-country Analysis H200720 21-12-2007 Entrepreneurial exit in real and imagined markets H200719 21-12-2007 Modelling latent and actual entrepreneurship H200718 21-12-2007 Knowledge management and Innovation: An empirical study of Dutch SMES H200717 21-12-2007 Entrepreneurship and innovation H200716 21-12-2007 Employment Growth of New Firms 46 H200715 21-12-2007 Entrepreneurial Culture and its Effect on the Rate of Nascent Entrepreneurship H200714 21-12-2007 Creative industries H200713 19-11-2007 New Ventures†Export Orientation: Outcome And Source Of Knowledge Spillovers H200712 29-10-2007 SME Choice of Direct and Indirect Export Modes Resource Dependency and Institutional Theory Perspectives H200711 24-10-2007 Family Orientation, Strategic Orientation and Innovation Performance in SMES: A Test of Lagged Effects H200710 15-10-2007 Drivers of entrepreneurial aspirations at the country level: the role of start-up motivations and social security H200709 12-10-2007 Does Self employment Reduce Unemployment H200708 10-9-2007 Social security arrangements and early-stage entrepreneurial activity H200707 11-5-2007 Competition and innovative intentions: A study of Dutch SMES H200706 eind maart High-Growth Support Initiatives H200705 14-2-2007 The relationship between economic development and business ownership revisited H200704 2-2-2007 The relationship between knowledge management, innovation and firm performance: evidence from Dutch SMES H200703 26-1-2007 Family orientation, strategy and organizational learning as predictors of knowledge management in Dutch SMES H200702 3-1-2007 Ambitious Nascent Entrepreneurs and National Innovativeness H200701 3-1-2007 Entrepreneurial diversity and economic growth H200627 21-12-2006 Motivation Based Policies for an Entrepreneurial EU Economy H200626 19-12-2006 Export Orientation among New Ventures and Economic growth H200625 18-12-2006 Institutionele voorwaarden voor zelfstandig ondernemerschap H200624 13-12-2006 Creative Destruction and Regional Competitiveness H200623 6-12-2006 Entrepreneurship, Dynamic Capabilities and New Firm Growth H200622 1-12-2006 Determinants of self employment preference and realization of women and men in Europe and the United states H200621 1-12-2006 Is human resource management profitable for small firms H200620 23-11-2006 The entrepreneurial ladder and its determinants H200619 20-11-2006 Knowledge Spillovers and Entrepreneurs†Export Orientation H200618 20-11-2006 The effects of new firm formation on regional development over time: The case of Great britain H200617 11-10-2006 On the relationship between firm age and productivity growth H200616 11-10-2006 Entrepreneurship and its determinants in a cross-country setting H200615 2-10-2006 The Geography of New Firm Formation: Evidence from Independent Start-ups and New Subsidiaries in the Netherlands H200614 25-9-2006 PRISMA-K: een bedrijfstakkenmodel voor de korte termijn H200613 25-9-2006 PRISMA-M: een bedrijfstakkenmodel voor de middellange termijn H200612 25-9-2006 PRISMA-MKB: modelmatige desaggregatie van bedrijfstakprognose naar grootteklasse H200611 25-9-2006 PRISMA-R: modelmatige desaggregatie van bedrijfstakprognoses naar provincie

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