WARN-Count in xref table is 0 at offset 1368785 1 Working Paper No. 2013/28 Entrepreneurial Orientation and Network Ties Innovative Performance of SMES in an Emerging -Economy Manufacturing Cluster Theresia Gunawan1, Jojo Jacob2 and Geert Duysters3 August 2013  The authors, 2013 1 Maastricht School of management and Technical University of Eindhoven, The netherlands 2 United Nation University-Maastricht Economic and Social Research Institute on Innovation and Technology (UNU MERIT), The netherlands 3 Tilburg University, The netherlands 2 The Maastricht School of management is a leading provider of management education with worldwide presence. Our mission is to enhance the management capacity of professionals and organizations in and for emerging economies and developing countries with the objective to substantially contribute to the development of these societies www. msm. nl The views expressed in this publication are those of the author (s). Publication does not imply endorsement by the School or its sponsors, of any of the views expressed 3 Entrepreneurial Orientation and Network Ties Innovative Performance of SMES in an Emerging-Economy Manufacturing Cluster Theresia Gunawan a Jojo Jacob b and Geert Duysters c a Maastricht School of management, and Technical University of Eindhoven, The netherlands b United Nation University-Maastricht Economic and Social Research Institute on Innovation and Technology UNU MERIT), The netherlands c Tilburg University, The netherlands Preliminary Draft ABSTRACT This study investigates the role of intra-cluster ties, extra-cluster ties, and entrepreneurial orientation in shaping firms†innovative performance. We conduct our analysis on a primary data set of 120 SMES in the Cibaduyut footwear-manufacturing cluster, Indonesia. We find that extra-cluster ties mediate the relationship between proactiveness and innovative performance. A combination of high extra-cluster ties and risk taking exert a positive impact on innovative performance. Surprisingly, we find that risk taking negatively moderates the influence of intra-cluster ties on innovative performance. Overall, the findings of this study point to the synergistic effects of entrepreneurial orientation and extra-cluster ties on innovative performance Introduction A growing body of literature in regional economic geography has demonstrated the positive impact of networks within a regional cluster on innovation. Intra-cluster networks (ICTS encourage cooperation, trust, collective learning, and smooth exchange of knowledge. Clusters play a particularly important role in compensating for the resource constraints SMES face and spur innovation and growth in these firms. However, knowledge and information trapped in a regional cluster can decay and become obsolete (Giuliani & Bell, 2005). Therefore, although being part of a geographically localized cluster is advantageous, in order to access new knowledge a firm needs to establish linkages beyond its local cluster (Mesquita & Lazzarini 2008). ) Research has shown that ties that extend beyond a firm†s cluster, or extra-cluster ties ECTS), are important gateways of critical knowledge and information (Giuliani & Bell, 2005 Thus while ICTS may generate critical location-driven synergies, ECTS complement them by bringing in diverse, novel knowledge inputs 4 From a resource based view (RBV) the network encompassing ICTS and ECTS of a firm can be seen as its resource pool, contributing to the firm†s technical know-how, trade contacts, and capital (Wernerfelt, 1984. In addition, network ties provide legitimacy, increasing a firm†s odds of forming partnerships with highly valuable potential partners (Eisenhardt & Schoonhoven 1996). ) The large bundle of resources that networks generate can increase the ability of the form to create new combinations of knowledge, thereby enhancing its competitive advantage Wernerfelt, 1984. Such a so called recombinatorial ability is particularly relevant when firms confront a high degree of competition, as SMES in emerging economies do. Next to network ties entrepreneurial orientation (EO) is another significant resource for achieving competitive advantage in general (Covin & Miles, 1999; Covin & Slevin, 1991; Lumpkin & Dess, 1996 Wiklund & Shepherd, 2005), and doing so in particular through innovation (Avlonitis & Salavou, 2007; Boso, Cadogan, & Story, 2012; Pà rez-Luã o, Wiklund, & Cabrera, 2011. EO represents a unique resource to a firm because it cannot be purchased in the market, and it is difficult to copy because firms invest considerable time to nurture their EO cultures (Lee, Lee, & Pennings, 2001. Like a firm†s network, EO too is particularly salient for market success in the highly competitive and turbulent environments in emerging economies (Covin and Slevin 1989 In line with RBV, EO, along with network ties, is a resource that adds to the competitive advantage of a firm. Surprisingly, only a few studies have examined the concurrent impact of entrepreneurial orientation and networks (Lee, et al. 2001; Stam & Elfring, 2008. In their study Lee et al. 2001) investigated the relationship of EO and external networks such as government and university on sales growth, and Stam and Elring (2008) worked on the impact of EO and bridging ties on sales growth. We take a different approach, i e. we study the interplay of EO and network on innovative performance. In our study, we distinguish the role of EO into proactiveness and risk-taking because we believe they have a unique role in leveraging innovation. Furthermore, we differentiate among a network based on internal and external cluster ties because SMES in emerging countries can benefit from both kind of ties in different ways We argue that entrepreneurial firms seek to improve their competencies, on the one hand by establishing new network ties (Low & Abrahanson, 1997), and on the other by tapping resources from their existing ties (Lipparini & Sobrero, 1994. This is particularly true for ECTS because assimilating knowledge elements from non-local partners requires distinct capabilities to those required for assimilating knowledge from partners within a firm†s own cluster. The former category of partners may exhibit greater differences not only in knowledge and expertise, but 5 also in attitudes and cultures compared to the latter category of partners. Therefore a strong entrepreneurial commitment is required to establish and maintain ECTS, to take chances with these ties, and to proactively uncover new opportunities (Covin & Miles, 1999). A firm with a high EO is therefore able to actively pursue knowledge and information available through its existing and new network ties Next, we distinguish the two well known traits of EO€ proactiveness and risk taking†and examine their specific roles in generating innovative gains through ICTS and ECTS Proactiveness represents a â€oefirst mover†orientation of the firm, encapsulating a firm†s ability to stay ahead of its competitors in anticipating future changes. Risk-taking orientation reflects a firm†s â€oetolerance of uncertainty†and capture a firm†s willingness to involve in and make risky investments. In a departure from extant research (Kreiser, 2011; Lee, et al. 2001; Stam & Elfring, 2008; Wiklund & Shepherd, 2003), we conceptualize these two EO traits as serving distinct functions in relation to a firm†s network ties. We propose that proactiveness exerts only an indirect effect on innovation through ICTS and ECTS, while risk taking affects innovation directly, as well as by reinforcing the positive innovation effect of a firm†s ties A firm with a high proactiveness orientation may be particularly adept at forging new ties because such a firm seeks out resources that would add value to the firm both in the present and in the future. The ability to read and anticipate changes in their environments is an eminent trait of entrepreneurial firms. Linkage within its own geographic areas (ICTS) constitutes an important social resource that generates a high level of trust and encourages the diffusion of tacit knowledge. While such knowledge transfers are easier, they may be mainly promoting incremental innovation (Capello, 1999. A proactive firm therefore may expand its network beyond its specific location so as to draw on the resources of organizations that may have different norms and practices (Rodan & Galunic, 2004. Such ties (ECTS) not only bring new insights to a firm, but also enable it to think out of the box such that the firm is able to adopt new technologies faster than would be otherwise possible Although a firm†s network ties constitute an important resource, such ties carry major risks The firm†s partner may not be reciprocative in information exchanges, and, even if this is not the case, technological uncertainties may prevent exchange relationships from yielding the desired results. In spite of these risks, a firm that nurtures its ties through the necessary investments in relationship building and knowledge sharing might stand to benefit more from its linkages than a firm that makes little investments in its ECTS. While both ICTS and ECTS carry risks, the risks associated with the latter are likely to be higher due to the relatively higher differences in business practices, norms and such like between the partners. On the other hand, the pay offs to 6 risk taking may also be higher in respect to ECTS, given the potentially novel and non-redundant information that such ties bring about Our paper contributes to the literature on SMES and innovation by integrating studies in the economic geography tradition that stress the role of a firm†s network and those that emphasize the importance of entrepreneurial orientation, adopting the theoretical umbrella of the resource based view of the firm. While most studies on the effects of cluster, as well as of entrepreneurship, on innovative performance have been conducted in developed countries particularly in the context of high-tech industries (Stam & Elfring, 2008), our study is carried out in the context of a low-tech manufacturing cluster in an emerging-economy†the footwear industry cluster in Cibaduyut, Indonesia THEORY AND HYPOTHESES Role of Clusters for Innovation in SMES: Intra-and Extra-Cluster Ties An extensive body of research has highlighted that interactions within a regional cluster provide an effective platform for learning and innovation (Feldman, 1993; Gilbert, Mcdougall & Audretsch, 2008; Mccann & Folta, 2011. Firms within a cluster are usually a close-knit group that may include competitors, producers, suppliers, and distributors. Given their geographic proximity, these firms exhibit a high degree of interconnectedness between themselves and with local institutions such as government agencies, research institutes and universities (Porter, 2000. They benefit from the economies of agglomeration and joint action giving them collective efficiency and therefore a competitive advantage over firms that are not co-located within a cluster (Schmitz, 1995. Scholars have emphasized increasingly that being part of a geographically concentrated cluster enables a firm easy access to new ideas partly due to the localized nature of knowledge spillovers (Mccann & Folta, 2011. This follows the Schumpeterian view in which knowledge creation is conceptualized as a process of knowledge sharing within an actor†s network. This view that knowledge is embodied tacit and in individuals has inspired research into knowledge sharing through face-to-face interactions in regional clusters (Nonaka & Takeuchi, 1995; Polanyi, 1966. A cluster is a particularly relevant platform for knowledge sharing in that it ensures trust and cooperation, contributing to collective learning, synergies and smooth exchange of knowledge. It therefore creates an informal network of organizations as proximity increases visibility and firms may easily get referrals from their existing partners to help form new partnerships (Gilsing, Nooteboom, Vanhaverbeke, Duysters 7 & van den Oord, 2008. The degree of trust these informal ties provide is so high that it is common for firms in a cluster to visit their competitors†factories in order to gain know-how and new insights (K Nadvi, 1999. These benefits are not so easily accessed by firms that are located further away from the cluster. Clusters are therefore a significant locus of local economic development (Giuliani, 2002 Empirical research has shown that firms that are part of a regional cluster are more successful, in terms of both innovation and profit, compared to similar firms that are not part of a cluster (Caniels & Romijn, 2005; Oerlemans, Meeus, & Boekema, 2001; Schoales, 2006 Simmie, 2004. Caniels & Romijn (2005) show that ICTS expedite the flow of knowledge between the participating firms, enhancing their innovative capabilities. Creative clusters are shown to contribute to local economic development by enhancing firm productivity, thereby supporting high local wages (Schoales, 2006. Almeida & Kogut (1999) found that the development of clusters in the U s. computer industry in the 1980s led to increased innovation and industry rejuvenation. Gemser & Wijnberg (1996) found that the competitive strategy of the Italian furniture industry involved continuous improvement and product differentiation. This was made possible by the presence of industrial districts consisting of a network of SMES and loosely organized families. Studies in the context of emerging economies are far fewer, but they too suggest that clusters enhance the competitive advantage of SMES (Caniels & Romijn, 2003 Schmitz & Nadvi, 1999 In this study we aim to contribute to ongoing debates regarding the impact of clusters on innovation. Among others, Simmie (2004) and Romijn and Albaladejo (2002) found that networks are key to the success of clustered firms. In this study we want to take the concept of networks one step further. We now distinguish among intra cluster ties (ICTS) and extra cluster ties (ECTS. We argue that ICTS and ECTS can be the sources of distinct knowledge. Therefore we see that ICT and ECT development should be treated as an investment that enhances innovation While research on clusters have focused traditionally on ICTS, scholars have increasingly recognized that knowledge trapped within a cluster can decay and become obsolete (Boschma 2005; Cantwell & Iammarino, 2003; Giuliani & Bell, 2005. Market trends and technologies change rapidly and continuously, while intra-cluster knowledge flows may not be keeping pace with these changes. Therefore extending a firm†s network beyond the cluster in which it is located is vital†it allows a firm to absorb knowledge that is not sufficiently well developed in its region. Access to resources both internal and external to the cluster gives a firm the 8 opportunity to combine and recombine diverse knowledge elements, thereby increasing the chances for successful innovative outcomes. Research has demonstrated that firms that maintain ECTS are looked upon for advice and up to date knowledge by fellow firms who do not maintain such ties (Giuliani, 2005. Such ties are particularly important to achieve sustained competitive advantage for firm which operate in lagging technology clusters in developing countries where local knowledge and competency are insufficient (Bell & Albu, 1999; Fontes, 2005. SMES in emerging countries often lack resources for developing new knowledge themselves and most of their knowledge comes from learning from others (Tsui-Auch, 2003. The above arguments suggest that while proximity and trust between partners ensures exchange of fine-grained knowledge within a cluster, over-reliance on ICTS may only result in the absorption of redundant knowledge. Therefore, an SME€ s sustained innovative performance and long run competitive advantage hinges on its ability to complement the intense exchange of knowledge associated with its ICTS with ECTS that bring in information and knowledge that is locally not available Bathelt, 2004; Cantner & Graf, 2008. However, while a firm†s network is vital for innovation we argue that a broader understanding of the link between the two requires taking into account certain entrepreneurial qualities of the firm that shape and influence the efficacy of a firm†s linkages Interplay of ICTS and ECTS with Entrepreneurial Orientation To be successful, a firm must possess a certain ability to continually build and nurture its network and to process and implement newly gathered knowledge and information. This ability is reflected in a firm†s EO capabilities, defined as the extent to which top managers are inclined to take business-related risks and seek opportunity in anticipation of future demand (Covin & Slevin, 1988,1991; Danny Miller, 1983. This definition captures respectively EO€ s two key characteristics that we focus on in this paper in relation to a firm†s ties: risk taking and proactive action (Pà rez-Luã o, et al. 2011). ) Proactiveness refers to the active search for new opportunities identifying them, assessing their potentials, and devising strategies to exploiting these potentials Lumpkin & Dess, 1996. This is a particularly important trait in order to be able to pioneer new procedures, technologies, and products or services†an ability on which hinges the long term success of a firm (Christensen, 1997. Risk taking is a complementary EO characteristic that reflects the commitment to high-risk investment or the willingness to invest resources into unpredictable opportunities, after they have been identified by proactive-oriented firms. Studies affirm that a successful entrepreneur makes calculated risks for potentially rewarding future benefits (Low & Abrahanson, 1997. In short, proactiveness and risk taking are two important 9 features that shape how a firm acquire and utilize its resources for achieving success in the long run. Given that network ties represent a critical resource for SMES, particularly in emerging economies, it is important to understand the interplay between EO and a firm†s network ties In this paper therefore we attempt to integrate the theories related to geographical clusters that emphasize the importance of ICTS and ECTS (Giuliani & Bell, 2005) and the literature on EO that stresses the role of an organization†s entrepreneurial culture for firm success (Lumpkin & Dess, 1996. To the best of our knowledge this is the first study to look into the specific role of proactiveness and risk taking in relation to a firm†s ICTS and ECTS. However, prior literature does emphasize how a firm†s absorptive capacity (Larraã eta, Zahra, & Gonzã¡lez, 2012) and the social capital its network creates (Stam & Elfring, 2008) exerts a contingent effect on the link between EO and performance. Our paper extends this line of research by differentiating the influences of proactiveness and risk taking on a firm†s network ties (ICTS and ECTS) in the specific context of an emerging-economy, low-tech manufacturing cluster. While proactiveness and risk-taking orientation both contribute to innovation and enhanced firm performance, we suggest they do so in distinct ways. In particular we argue that whereas proactive orientation exerts its influence in establishing network ties, risk taking ensures that the firm makes the necessary commitments in order to derive value from its network ties. We discuss these two influences in turn Proactiveness and Innovation: The Mediating Roles of ICTS and ECTS We argue that proactiveness contributes to a firm†s innovative performance indirectly through the firm†s ICTS and ECTS because firms with high levels of proactiveness find opportunities anticipate future developments, and identify new trends and available niches faster than their competitors (Lumpkin & Dess, 1996. Such firms accordingly seek out network ties more actively for accessing resources that are geared towards meeting the expected challenges and opportunities. The resulting ICTS and ECTS therefore represent an important resource for the firm (Eisenhardt & Schoonhoven, 1996), with more such ties providing access to potentially greater varieties of knowledge (Cross & Jonathon, 2004. By focusing on the specific EO trait of proactive orientation, we refine prior research which has shown that EO, in general, plays an important role in establishing inter-organizational networks that glue a firm†s internal expertise with externally acquired resources (Lipparini & Sobrero, 1994 Proactive-oriented firms may also be more adept at leveraging their existing ties to forge new ties. We know from the network literature (e g. Gulati, 1999) that a firm†s existing network 10 enables it to establish new linkages through, among other factors, referrals by its current partners and the visibility that the current ties provide. We suggest that proactive behavior ensures that a firm is able to seek out referrals and leverage its visibility in the cluster such that it forms new partnerships in response to changes in external environments faster than firms lacking such abilities. Therefore, we propose that proactive orientation enhances innovative performance through its effect on ICTS and ECTS H1a. The effect of a firm†s proactiveness on innovative performance is mediated by its intra -cluster ties H1b. The effect of a firm†s proactiveness on innovative performance is mediated by its extra -cluster ties How Does Risk Taking Moderate the Effect ICTS and ECTS on Innovative performance Establishing network ties do not necessarily mean that a firm is fully tapping into the resources available to it through such ties. The underlying relationships are reciprocal so the extent to which a firm can access resources hinges partly on the extent to which it is willing to commit its own resources. However, such commitments carry an inherent risk. In the first place partners may renege on their promises so the firm may stand to loose the resources it has committed. Another significant risk is associated the uncertainty with innovation (Zahra & Covin, 1995; Zahra, Nielsen, & Bogner, 1999. Even if a firm†s network partners reciprocate in line with the firm†s expectations, knowledge exchanges may not generate valuable innovative outcomes. As regards an acceptable level of risk, psychologists posit that this level may be chosen as a compromise between the desire for success and the desire to avoid risk (Mandel 2003). ) Too low a risk tolerance will prevent a firm from making progress (Naldi, Nordqvist Sjoberg, & Wiklund, 2007. As observed by Ward (1997, p. 323) â€oewithout risk taking †the prospects for business growth waneâ€. This suggests that some level of risk taking is essential for effective use of firms†ICTS and ECTS. When ICTS and ECTS are supported by an adequate degree of risk taking though investment of time, money, and effort, the rate of innovation will increase. The interplay between risk taking on the one hand and ICTS and ECTS on the other can contribute to innovation, right from the discovery of an opportunity or the conception of an idea to its planning and implementation Nevertheless, we suggest that the extent to which risk taking is essential can vary for ICTS and ECTS. Within a cluster there is certain degree of mutual interdependence, implying that 11 firms need to honor their commitments or they may face sanctions from others within the cluster Within-cluster ties may therefore be compared to dense networks characterized by repeated interaction and a high degree of trust between partners (e g. Gordon, Kogut, & Shan, 1997 Gulati & Gargiulo, 1999; Uzzi, 1997. Greater trust and the threat of sanction can make risk taking less salient for ICTS compared to for ECTS. We therefore propose the following two related hypotheses H2a. A firm†s risk-taking orientation positively moderates the positive impact of its network ties (both ICTS and ECTS) on innovative performance H2b. A firm†s risk-taking orientation has a greater moderating effect on the impact of its ECTS, compared to its ICTS, on innovative performance Hypothesized Research Model Figure 1 shows the conceptual framework that explains the relationships proposed in our hypotheses, depicting how the interplay between ICTS, ECTS, proactiveness and risk taking affects innovation Figure 1 Innovative performance and the interplay between ICTS, ECTS, Proactiveness and Risk-Taking METHODS Proactiveness Intra-cluster ties Extra-cluster ties Innovation Risk taking H1a H1b H1a H1b H2b H2a 12 Research Setting While many studies on SME clusters have been conducted in high-tech industries in developed countries (Stam & Elfring, 2008), our study is carried out in the context of a creative industry with low to intermediate technology-a footwear industry in the Cibaduyut manufacturing cluster in Indonesia. We chose Indonesia because its manufacturing SMES are representative of those in other emerging countries, on which few studies exist. Our focal firms are located in a cluster with clear geographical boundaries and who operate similar technologies Stam & Elfring, 2008. Why is this research setting interesting? First, this is a highly competitive footwear cluster so firms are compelled to produce innovative products. Without such products, it is difficult to get orders from distributors (Gunawan, 2011. Second, firms possess limited internal resources so ICTS and ECTS constitute key resources for the firms Biggs & Messerschmidt, 2005 Research Design and Data Collection We collected the data in 2012 based on an extensive survey in this cluster, using questionnaires and interviews among owners and managers of the companies. Our sample is comprised of 120 owners/managers representing 120 footwear firms in Cibaduyut. As is typical in emerging economies there only exists limited information about footwear producers in this cluster; the official database of company addresses is at best incomplete. We combed through every area in Cibaduyut and compiled contact addresses. We then distributed questionnaires to all footwear producers that we found, and we followed this up with interviews. The resulting data set presents a near complete representation of firms in this cluster Measures and Validation Innovative performance Innovation is understood traditionally to mean the introduction of new goods, the use of new materials, the development of new methods of production, the opening of new markets, or the implementation of a new approach to organization (Schumpeter, 1934. In this paper, we considered the ability of firms to develop new products as a measure of innovative performance New products are an important indicator of innovative performance (Katila & Ahuja, 2002 because they reflect a firm†s ability to adapt to changes in markets and technologies Schoonhoven, Eisenhardt, & Lyman, 1990) and they exert a significant impact on market share market value, and firm survival (Banbury & Mitchell, 1995. Product innovation, which 13 underlies new products, may include improvements in features, materials, and components, the development of new software, enhanced user friendliness, and other aspects (OECD, 2005). We define product innovation in terms of changes in materials, features, and design; we did not consider changes in color and size as representing an innovation. We then used the number of new products introduced to the market during the preceding year as our indicator of innovative performance (Stam & Elfring, 2008 Intra/Extra-Cluster Ties We map ICTS and ECTS by determining the number of partners with which the producers interact (Giuliani & Bell, 2005. The boundary of the Cibaduyut cluster is clear, enabling us to easily differentiate between intra-and extra-cluster ties. We constructed ICTS and ECTS variables as the number of a firm†s diverse set of partners, such as suppliers, distributors competitors, research centres and universities, within and outside its cluster respectively. Both variables are expressed in logarithms (Leiponen & Helfat, 2011 Proactiveness and Risk Taking We followed the approach of Covin and Slevin (1989) to measure proactiveness and risk taking. Respondents were asked about their firms†proactive-orientation and risk-taking behavior on a scale of 1, â€oestrongly disagreeâ€, to 5, â€oestrongly agreeâ€. We derived multi-item variables using factor analysis, testing for their reliability and validity. We confirmed the reliability of these indicators by computing the Cronbach-alpha coefficient, which was respectively 0. 80 for proactiveness and 0. 78 for risk taking†well above the minimum accepted value of 0. 70 (Field 2013). ) We further verified the validity of these indicators, finding a statistically significant correlation of proactiveness and risk taking with innovative performance respectively (r=0. 30 p<0. 01) and (r=0. 30, p<0. 01 Control Variables We use a number of variables as controls. We used the age of the owner or manager to control for the effect of experience on innovative performance. Older owners or managers can be trapped in an entrenched operational system such that they might be slow to adapt to new developments, resulting in slower absorption of new knowledge (Cohen & Levinthal, 1990. On the other hand, young owners and managers are less likely to have established routines and may are engaged with a flexible network of partners, making them more open to new ideas resources, and opportunities. We also included the education level of owner/manager to control 14 for differences in the ability to absorb and manage information. Better educated owners/managers may be more capable of obtaining new knowledge, and of adapting to changing technologies and market signals. We used the number of employees to account for the effect of differences in the size of the firm. Larger firms may employ more skilled human resources, be more knowledgeable, have more access to knowledge, and have the appropriate technology or the ability to acquire it (Damanpour, 1996. On the other hand, large firms are typically more formalized with standardized managerial practices which can hamper innovation Hitt, Hoskisson, & Ireland, 1990. While small organizations may be more flexible, which means they have a greater ability to adapt to changing environments, they may be constrained by limited access to facilities and financial resources Analytical Approach We employ ordinary least squares (OSL) estimation method. The dependent variable follows a normal distribution: the skewness and kurtosis values were less than 1. 5†below the acceptable limit for normal distribution of  2 (George & Mallery, 2011) †indicating that the data are close to normal. We employed a hierarchical regression analysis, with alternative models with and without interaction terms. We ensured that there was no serious multicolleinarity between the variables: the variance inflation factor was below three, and the tolerance values were close to 1 Barrow, 2009. As recommended by Aiken and West (1991), we applied mean centering to the variables used for creating interaction terms 15 RESULTS Table 1 shows the descriptive statistics of the variables used in the econometric model The average number of innovative products is about 7, with a maximum of 16 and a minimum of 2. The average number of ICTS is about 69 (4. 2 in logarithmic scale), while that of ECTS is much smaller at about 5. Correlation coefficients are all within acceptable limits, further confirming the absence of multicollinearity Table 1 Means, Standard deviations, and Correlations a Variable Mean s d. Min Max 1 2 3 4 5 6 7 1. Number of new products 7. 47 2. 99 2 16 2. ICTB 4. 23 1. 76 1 91 0. 11 3. ECTB 1. 64 1. 95 0 17 0. 35**0. 36 **4. Proactive orientation 10.07 1. 76 8 15 0. 30**0. 29**0. 54 **5. Risk-taking orientation 6. 16 1. 22 4 9 0. 30**0. 29**0. 39**0. 47 **6. Age of owner/manager 2. 49 0. 71<30>50 0. 01 0. 20 0. 30**0. 26**0. 01 7. Education of owner/manager 2. 85 0. 53 Ju Hi scho ol Bache -lor 0. 29**0. 04 0. 13 0. 27**0. 18*-0. 18 *8. Firm size 1. 57 0. 51<5 21-50 0. 09 0. 40**0. 45**0. 46**0. 25**0 . 24**0. 13 a n=120 b. Log-transformed *p<0. 05,**p<0. 01 Two-tailed tests Results of the regression analysis are reported in Table 2. To test whether the variables ICT and ECT mediate the effect of proactiveness on innovative performance (H1), we follow the three-step procedure suggested by Baron & Kenny (1986. In model 1, we include the two EO variables, proactiveness and risk taking, along with the control variables. As expected, the coefficients of both these EO variables are positive and significant. In the next step, we regress the same set of explanatory variables in turn on ICT and ECT. We find a significant positive coefficient for proactiveness in the ECT model (Î=0. 30, p<0. 01)( model 3), but not in the ICT model (Î=0. 09, n s.)(model 2). This is a first indication that while ECTS may be mediating the effect of proactiveness on innovative performance, ICTS may not be playing such a role. The final step is to run the innovative performance model with both the EO variables and the network variables (model 4). The proactiveness variable is not significant anymore (Î=0. 09, n s), unlike in model 1. Furthermore, the coefficient of ECT variable is positive and significant (Î=0. 30, p <16 0. 01), while that of ICTS is not (Î=-0. 16, n s.).This confirms that ECTS fully mediates the effect of proactiveness on innovative performance, in support of our hypothesis 1b. ICTS on the other hand does not play a mediating role, contrary to our hypothesis 1a Table 2 Result of OLS Regression Analyses Variable Hyp Model 1 Model 2 Model 3 Model 4 Model 5 Model 1 Innov Model 2 ICT Model 3 ECT Model 4 Innov Model 5 Innov Controls Age of owner/manager 0. 01-0. 11 0. 17*-0. 04-0. 06 Education of owner/manager 0. 22**-0. 08 0. 01 0. 21*0. 18 *Firm Size-0. 78 0. 35***0. 21**-0. 14-0. 17 +Risk taking 0. 19*0. 17+0. 19*0. 14 0. 21 *Hypothesis variables Proactiveness H1a &b 0. 18+0. 09 0. 30**0. 09 0. 03 ICTB H1a-0. 16 0. 31 *ECTB H1b 0. 30**0. 13 Two-way interactions ICT x Risk taking H2a-0. 41 **ECT x Risk taking H2b 0. 22 *R2 0. 17 0. 22 0. 38 0. 22 0. 34 Adjusted R2 0. 13 0. 18 0. 36 0. 17 0. 28 F 4. 67***6. 28***14.45***4. 61***6. 17 ***N 120 120 120 120 120 a Standardized coefficients are reported blog-transformed +p<0. 10 *p<0. 05 **p<0. 01 ***p<0. 001 17 Next, to test whether risk taking moderates the effect of ICTS and ECTS on innovative performance, we added to the variables in model 4, the interaction terms ICT x Risk taking and ECT x Risk taking (model 5). We find a positive and significant coefficient for ECT x Risk taking (Î=0. 22, p<0. 05) which partially support our hypothesis 2a. However in contrast to our assumption in this hypothesis we find a negative and significant coefficient for the variable ICT x Risk taking (Î=-0. 41, p<0. 01. These results provide full support for our hypothesis 2b which stated that a firm†s risk-taking orientation has a greater moderating effect on the impact of the firm†s ECTS, compared to its ICTS, on innovative performance. Coming to the results on control variables, we find that education of the manager has a positive impact on performance, while firms with younger managers also tend to perform better (models 1, 4, 5). A better educated manager gives an SME a greater ability to understand new knowledge, recognize its value and to commercialize it (Qian & Acs, 2013. There is also partial evidence that small-sized firms tend to be more innovative. This is in line with our understanding that smaller firms display greater agility and flexibility in adopting new innovative practices, giving them a competitive advantages over larger firms (Robertson & Langlois, 1995 Figure 2 The Moderating Effect of Risk-Taking on the Relationship between ECTS and Innovative Performance 18 From figure 2 we can better understand the extent to which risk taking moderates the effect of ECTS on innovative performance. It shows the predicted innovative performance across a range (from low to high) of ECTS for high-and low-risk taking firms. The horizontal axis measures the number of ECTS, and the dotted and solid lines respectively represent firms with high and low risk taking. Both lines have a positive slope indicating the positive effect of ECTS on innovative performance. However, the slope of the dotted line is much more steep than that of the other line, underscoring that risk taking substantially moderates the impact of ECTS on innovative performance. This suggests that firms that are greater risk takers benefit the most from increasing the number of their ECTS Robustness checks In addition to the tests described earlier, we conducted further tests to conclude that the assumption of BLUE (Best Linier Unbiased Estimator) of OLS is satisfied (Gujarati, 2003. The Koenker test with a Chi-Square statistic of 10.79 (p=0. 29), and the Breusch-pagan test (Chi -Square 10.74 (p=0. 29) indicate that the assumption of homoscedasticity is violated not because the p is bigger than 0. 05. We tested for potential outlier problems and found that the value of Cook†s Distance is 0. 23, which is lower than the usually accepted limit of one (Tabachnick & Fidell, 2007), thereby indicating the absence of significant outliers DISCUSSION In this paper, we integrated the literature on entrepreneurial orientation with that on regional innovation and network ties. The EO literature identifies proactiveness and risk taking as two key EO characteristics (Lee, et al. 2001; Stam & Elfring, 2008; Wiklund & Shepherd, 2005 while the literature on innovation in regional clusters stresses the importance of ICTS and, more importantly, ECTS (Giuliani & Bell, 2005. We argued that the EO traits of risk taking and proactiveness interact differently with a firm†s ICTS and ECTS. On the one hand, proactiveness is likely to influence innovative performance indirectly through the creation of a firm†s ICTS and ECTS. Risk taking on the other hand positively moderates the impact of ICTS and ECTS We empirically tested our conjectures on a sample of 120 SMES in a creative-industry manufacturing cluster in an emerging economy, Indonesia. Our analysis, based on primary data collected through interviews and questionnaires, provided mixed support for our hypotheses. We found that ECTS mediate the proactive orientation of firms. A proactive-oriented firm is particularly adept at seeking resources from outside its cluster, increasing the diversity and 19 novelty of knowledge at its disposal (Larraã eta, et al. 2012). ) This in turn enhances the potential number of new knowledge combinations that the firm can create, resulting in improved innovative performance (Chen & Huang, 2009; Tà dtling, Lehner, & Kaufmann, 2009. On the other hand, we did not find the mediating role of ICTS on the link between proactiveness and innovative performance. One possible explanation is that the knowledge in a cluster might be saturated because â€oeeveryone knows what everyone knows†(Gilsing, et al. 2008). ) Being overembedded in their cluster though ICTS may induce in firms a certain satisfaction with the status-quo such that firms may not be keen to actively search for new knowledge. Proactive firms, however, are oriented future, prepared to meet future challenges and exploit future opportunities, and therefore may engage actively in search of new ideas outside of their cluster though ECTS We found that risk taking strengthens the relationship between ECTS and innovative performance. For SMES in particular, external knowledge is a key source of innovation (Jacob & Szirmai, 2007; Lipparini & Sobrero, 1994. However, external knowledge sourcing is inherently risky due to relative unfamiliarity of a firm†s partners and the resulting uncertainty about the outcomes (Dess & Lumpkin, 2005; Lee, et al. 2001; Walter, Auer, & Ritter, 2006 Zahra, et al. 1999). ) In this context, firms that take calculated risk are able to invest resources in their ECTS such that they are able to draw potentially valuable external resources. We however found that risk taking negatively moderates the effect of ICT on innovative performance. Too much resource commitment for within-cluster knowledge sharing may be counterproductive as this may result only in the diffusion of redundant knowledge instead of making new knowledge available to the firm. This underscores a concern raised in the literature that being located within a cluster is no guarantee for being successful (Schmitz & Nadvi, 1999. This presents a particular challenge for SMES that are located in regional clusters, which are characterized by limited inter-firm specialization, and scarce joint initiatives in marketing, production, distribution and technological development. Thus a key message of our study is that SMES in emerging economies should actively develop inter-organizational networks that go beyond the confines of the region in which they are located. Committing resources to nurture these networks, and increasing the diversity of a firm†s knowledge intake, can be vital for successful innovative outcomes 20 Limitations and Future Research Our study is not without limitations, but also provides new opportunities for future research First, the data we used, although original and derived from field research, is cross-sectional. This has prevented us from examining the effect of changes over time in firm behavior on innovative performance. Collecting longitudinal data in the emerging economy context is particularly challenging, given the lack of governmental level initiatives to this end Second, we examined innovative performance using the number of new products introduced Katila & Ahuja, 2002. It would be interesting to differentiate between radical vs. incremental innovation and examine how different configurations of EO and network characteristics affect these, especially in the context of a more technologically advanced industry Third, in this study we used a single industry, footwear manufacturing. This may limit the generalizability of the results to other industries. 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