![]() Because the causes of these contradictory results have been studied in isolation, it has been impossible to compare them. These contradictory results might be the consequence of the heterogeneity of network-based incubation in terms of incubation practices (Aernoudt 2004), contextual differences (Soetanto and van Geenhuizen 2010) or a focus on distinctive performance measures. Other studies argue that network-based incubation does lead to improved start-up performance (Hansen et al. Some studies demonstrate that network-based incubation does not improve start-ups’ performance (Chan and Lau 2005 Oakey 2007 Soetanto and Jack 2013). However, as the field of literature grew, two major shortcomings emerged.įirstly, research on the influence of network-based incubation on start-up performance has led to contradictory results. The increased attention on network-based incubation resulted in a rich and broad variety of approaches, conceptualisations and insights (Theodorakopoulos et al. After all, as the earlier generations of incubation were found to improve start-up performance only marginally (Schwartz 2013), the network-based generation was expected to be superior in achieving that aim. Notably, the question of whether and how network-based incubation influences start-ups’ performance remained important (Ratinho et al. Consequently, in 2000, the network-based view of incubation was formulated and gained considerable interest (Hansen et al. ![]() Researchers have tried to keep up with the changing nature of incubation (Grimaldi and Grandi 2005 Hackett and Dilts 2004). This shift in focus echoes the observation that intangible resources particularly help start-ups (Brüderl and Preisendörfer 1998 Chen 2009). Through these networks, start-ups access intangible resources such as knowledge and legitimacy (Bruneel et al. Recently, incubators have augmented their approach by focusing on facilitating networks. The first generation of incubators focused primarily on providing infrastructure the second-generation incubation supplemented their way of operating by providing one-on-one business advice. During this period, incubators changed their way to support start-ups (Bruneel et al. Over the last five decades, the number of incubators has increased to more than 7000 worldwide (NBIA 2014). Incubation of technology-based start-ups has received considerable attention from policymakers and business people for its promise to contribute to technology transfer and entrepreneurship (Aernoudt 2004 Clarysse et al. We propose an agenda for further research on network-based incubation that leads to a fine-grained model of the mechanisms and impact of network-based incubation that goes beyond taken for granted assumptions about the positive impact of network-based incubation.īusiness incubation aims to help starting ventures by providing access to services and resources (NBIA 2009). ![]() There is a considerable opportunity to advance the network-based incubation literature with contemporary insights from management theories. However, the influence of these intermediary benefits on start-up performance is ambiguous. We find that the network-based incubation literature has convincingly shown that network-based incubation provides start-ups with resources, capabilities, knowledge, learning and social capital. The management theories are the resource-based view, knowledge-based view, organisational learning, and social capital theory. Therefore, this article uses three management theories to structure the literature, improve the theoretical underpinning and develop an agenda for further research. ![]() However, at the same time this literature has become quite fragmented, inconsistently conceptualised, and theoretically underdeveloped. The literature on how network-based incubation influences the performance of technology-based start-ups has recently grown considerably and provided valuable insights.
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