The Social Capital of Venture Capitalists and Its Impact on the Funding of Start-Up Firms

How does the social capital of venture capitalists (VCs) affect the funding of start-ups? Extant entrepreneurship literature conceptualizes a substitute effect between the social and financial capital that new firms attain from their investors. On the contrary, by building on the rich social capital literature, we hypothesize a positive effect of VCs’ social capital, derived from past syndication, on the amount of money that start-ups receive. Specifically, we argue that both structural aspects of VCs’ social network, such as the number of connections and the spanning of structural holes, and relational aspects, such as the diversity of network partners’ attributes, provide VCs with superior access to information about current investment objects and opportunities to leverage them in the future, increasing their willingness to invest in these firms. Our empirical results, derived from a novel dataset containing more than 5,000 funding rounds in the Internet and IT sector, strongly confirm our hypotheses. Both structural and relational attributes of VCs’ syndication networks have a significant influence on the funds received by start-up firms, highlighting the importance of a social capital perspective on new venture funding. We discuss the implications of our findings for theories of venture capital and entrepreneurship, showing that the role and effect of VCs’ social capital on start-up firms is much more complex than previously argued in the literature.social networks;social capital;start-ups;venture capital;structural holes

The Social Capital of Venture Capitalists and Its Impact on the Funding of Start-Up Firms

How does the social capital of venture capitalists (VCs) affect the funding of start-ups? Extant entrepreneurship literature conceptualizes a substitute effect between the social and financial capital that new firms attain from their investors. On the contrary, by building on the rich social capital literature, we hypothesize a positive effect of VCs’ social capital, derived from past syndication, on the amount of money that start-ups receive. Specifically, we argue that both structural aspects of VCs’ social network, such as the number of connections and the spanning of structural holes, and relational aspects, such as the diversity of network partners’ attributes, provide VCs with superior access to information about current investment objects and opportunities to leverage them in the future, increasing their willingness to invest in these firms. Our empirical results, derived from a novel dataset containing more than 5,000 funding rounds in the Internet and IT sector, strongly confirm our hypotheses. Both structural and relational attributes of VCs’ syndication networks have a significant influence on the funds received by start-up firms, highlighting the importance of a social capital perspective on new venture funding. We discuss the implications of our findings for theories of venture capital and entrepreneurship, showing that the role and effect of VCs’ social capital on start-up firms is much more complex than previously argued in the literature

Co-evolution of firms, industries and networks in space

The cluster literature suffers from a number of shortcomings: (1) by and large, cluster studies do not take into account that firms in a cluster are heterogeneous in terms of capabilities; (2) cluster studies tend to overemphasize the importance of place and geographical proximity and underestimate the role of networks which are, by definition, a-spatial entities; (3) most, if not all cluster studies have a static nature, and do not address questions like the origins and evolution of clusters. Our aim is to overcome these shortcomings and propose a theoretical framework on the evolution of clusters. Bringing together bodies of literature on clusters, industrial dynamics, the evolutionary theory of the firm and network theory, we describe how clusters co-evolve with: (1) the industry they adhere to; (2) the (dynamic) capabilities of the firms they contain; and (3) the industry-wide knowledge network they are part of. Based on this framework, we believe the analysis of cluster evolution provides a promising research agenda in evolutionary economic geography for the years to come

Applying social network analysis in economic geography: framing some key analytic issues

Social network analysis attracts increasing attention in economic geography. We claim social network analysis is a promising tool for empirically investigating the structure and evolution of inter-organizational interaction and knowledge flows within and across regions. However, the potential of the application of network methodology to regional issues is far from exhausted. The aim of our paper is twofold. The first objective is to shed light on the untapped potential of social network analysis techniques in economic geography: we set out some theoretical challenges concerning the static and dynamic analysis of networks in geography. Basically, we claim that network analysis has a huge potential to enrich the literature on clusters, regional innovation systems and knowledge spillovers. The second objective is to describe how these challenges can be met through the application of network analysis techniques, using primary (survey) and secondary (patent) data. We argue that the choice between these two types of data has strong implications for the type of research questions that can be dealt with in economic geography, such as the feasibility of dynamic network analysis

Knowledge networks and innovative performance in an industrial district : The case of a footwear district in the South of Italy

The traditional district literature tends to assume that: (1) the competitiveness of firms depends on external sources of knowledge; (2) all firms in a district benefit from knowledge externalities; (3) relying on external knowledge relationships necessarily means these are confined to the district area. Our case study of the Barletta footwear district in the South of Italy suggests otherwise. Based on social network analysis, we demonstrate that the local knowledge network is quite weak and unevenly distributed among the local firms. A strong local network position of a firm tended to increase their innovative performance, and so did their connectivity to extra-local firms. So, it mattered being connected either locally or non-locally: being co-located was surely not enough. Having a high absorptive capacity seemed to raise only indirectly, through non-local relationships, the innovative performance of firms