ماهیت همکاری و نوآوری شرکت های کوچک و متوسط : یک تجزیه و تحلیل چند عددی و چند بعدی
|کد مقاله||سال انتشار||مقاله انگلیسی||ترجمه فارسی||تعداد کلمات|
|20203||2013||11 صفحه PDF||سفارش دهید||محاسبه نشده|
Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : International Journal of Production Economics, Volume 141, Issue 1, January 2013, Pages 316–326
Recent work on SMEs and networks has emphasised the importance of external co-operative ties in enhancing firms’ innovative performance. These external ties provide resource constrained SMEs with access to a wider set of technological opportunities through information sharing and resource pooling. Previous studies of the SME innovation–cooperation relationship have used categorical measures to capture tie existence which, while providing some useful insights, largely fail to capture the strength of co-operative relationships and/or the variety of relational directions in which co-operation occurs. This study aims to address this measurement deficiency and explore the SME innovation–cooperation relationship by designing and utilising measures that capture both the multi-scalar (strength) and multi-dimensional (variety) nature of co-operation and innovation. We then apply these measures to a survey of UK manufacturing SMEs. Data is obtained for 371 SMEs, and we then assess the innovation–co-operation relationship within a multivariate regression framework. We find that the strength of cooperative ties across a range of productive activities within the value chain are important facilitators for SME innovative capability; this is true for both product and process innovation. However, we find that SME co-operation with rivals (co-opetition) has no significant impact upon innovation. Our results have significant implications for both supply chain managers and policy-makers interested in enhancing innovation among SMEs. In particular, we argue that SME innovative activity benefits from good, close dyadic relations within the supply chain, while more generally policy should be geared towards nurturing and sustaining SME innovation networks.
There is now an extensive literature on the role of inter-firm networks and their impact upon firm performance (for a review, see Hoang and Antoncic, 2003) and especially an interest in the links between network ties and innovative performance, particularly among small and medium sized firms (SMEs).1 Network ties offer internally resource constrained SMEs access to a wider set of technological opportunities (Chesbrough, 2003 and Chesbrough, 2007).2 By establishing networks, SMEs can overcome their internal resource constraints and obtain the advantages often associated with larger size (Nooteboom, 1994). Indeed, a plethora of earlier studies highlighted that SMEs were as innovative as larger firms despite employing less internal resources (see Rothwell and Zegveld, 1982, Pavitt et al., 1987, Oakley et al., 1988 and Acs and Audretsch, 1990) and, in this regard, both Lipparini and Sobrero (1994) and De Propris (2002) have postulated this relatively superior performance might reflect the greater capacity of SMEs to (better) exploit their network relationships through information sharing and resource pooling. Additionally, Fountain (1998) has also noted an increasing tendency for large firms to subcontract innovation processes out to their (largely SME) supply chains, which often benefitted from good links with regulators and state funded bodies. Over the last two decades, policy has followed these developments with numerous initiatives promoting greater inter-firm networking and collaboration being pursued. For instance, in the OECD, innovation policy has shifted from predominantly direct subsidies to individual firms towards funding projects that promote collaborative ties between firms (Bougrain and Haudeville, 2002). In the UK, such an approach continues to influence innovation policy, as evident in recent government directives concerned with the leadership, strategy and delivery of innovation (see Department for Innovation, Universities and Skills (DIUS), 2008). Innovation networking and collaboration, particularly among SMEs and along supply chains, are thus salient issues for both managers and policy-makers. A key feature of networks is the degree of co-operation between partner firms and, in particular, the strength of such ties (Uzzi, 1996). Indeed, this is particularly the case in supply chain management (see for instance, Bessant, (2003)). Unfortunately, as we shall highlight, many previous empirical studies exploring innovation–co-operation relationships among SMEs do not explicitly measure the strength of co-operative ties and/or capture the range of relational directions over which co-operation occurs. Rather they tend to capture the existence of such ties through the use of categorical variables. While undoubtedly providing useful insights, such studies may thus omit important information. The aim of this study is two-fold. First, we aim to overcome some of the measurement deficiencies in previous studies by utilising unique survey data of UK based SME's in manufacturing to explore the relationships between innovation (both product and process) and types of co-operation along the vertical supply chain and horizontally with competitor firms. In doing so, our approach seeks to capture both the scale and the various dimensions of collaboration between firms by using multivariate regression to assess whether the strength of co-operative ties, across a range of productive activities, furthers innovative capability among SMEs. Second, our analysis seeks to add to the literature on SMEs and innovation networks and draw conclusions for both practitioners and policy-makers. The remainder of this paper is set out as follows. Section 2 provides a comprehensive review of the previous literature on SME networks, co-operation and innovation. The section ends with the formulation of three testable hypotheses. In Section 3, we carefully outline our methodological approach and provide details of the data used. Section 4 introduces the model specification, the estimation procedure and presents the main results. In Section 5, we consider the implications of our results for managers and policy-makers, while also deliberating on some wider issues relating to networks. Finally, Section 6 concludes with some caveats to our approach and suggestions for future research.
نتیجه گیری انگلیسی
The results in this study demonstrate that close co-operation along the supply chain plays an important role in the innovation process of SMEs. Through establishing networks, SMEs can overcome their internal resource constraints and obtain the advantages often associated with larger size (Nooteboom, 1994). In particular, it is the strength of co-operative ties and across a range of productive activities that is crucial for innovation. Given previous studies in this area, this may not appear an overly surprising result. However, prior studies of SME innovation networks have merely captured the existence of collaboration, but said little about the nature of dyadic relations between firms. In contrast, this study captured these multi-dimensional and multi-scalar characteristics in the data and empirical analysis, thus going beyond previous empirical approaches and facilitating the inclusion of additional information. The implications of the study suggest that nurturing innovation networks and improving the dyad between partner firms – particularly in relation to facilitating knowledge transfer and organisational learning – is crucial for SME innovative activity along the value chain. However, as we noted this is not always easy to achieve, since there are inherent difficulties in nurturing such relations. It may be that state funding and a larger role for trade associations is required to facilitate network development. A related issue which is not covered here, but is the focus of our future research is whether there is an optimal level of co-operation that firms should strive to achieve to enhance their innovative endeavour. As noted earlier (see footnote 7), firms can become over-embedded in relationships, and invest too much time and resources in specific dyads at the expense of seeking alternative partners (Granovetter, 1973). Identifying, an ‘appropriate’ level of co-operation for SMEs could improve resource allocation. Finally, there are some caveats in relation to our approach that should be noted. First, innovative and co-operative firms were identified by self-declaration, which could generate bias among self-confident firms. However, this is a problem familiar to all survey based approaches, where researchers use self-reported data and have to rely upon managers’ judgement regarding responses. Consequently, this should not overly detract from the analysis (Lasagni, 2012). Second, the assumption of causation running from co-operation to innovation; in cross-sectoral studies of this type, the reverse may be the case with more innovative firms engaging in co-operation. However, given previous studies have uncovered similar patterns, we hold a strong degree of confidence in our results and their wider interpretation.19 Future research may however, warrant a more qualitative approach, which may also seek to explore the intrinsic characteristics of dyadic relations in SME innovation networks in more detail. Third, the time window of the current study was relatively short (3 years). In part, this is the nature of survey work in that it typically captures variables at a specific point in time. By specifying a three year window, we were able to focus respondents upon their recent relations with their partners. However, our empirics are nonetheless, relatively static which may be a reason (though this is not uncommon in studies of this type) for the relatively low R-squared values in our models. It is highly probable that the dynamics of the relationships covered will change over time, particularly as new firms enter/exit industries and external challenges to supply chains emerge. Moreover, managers may change in firms and they will have different perceptions on their co-operative relationships. These dynamics might be better captured through periodic follow up surveys to provide longitudinal data that takes account of a longer time window.