Attenuating the negative effects of network change on innovation: A whole network level analysis of Taiwanese business g
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Attenuating the negative effects of network change on innovation: A whole network level analysis of Taiwanese business groups Shuping Li 1
& Sai
Yayavaram 2
# Springer Science+Business Media, LLC, part of Springer Nature 2018
Abstract This paper investigates when and how changes in interorganizational networks affect innovation at a whole-network level. We consider three forms of network change as suggested by prior research on networks: membership change, change in network structure, and tie restructuring. We examine the independent and interactive effects between membership change and other types of network changes on group innovation. Our longitudinal analyses of the intra-group network changes in Taiwanese business groups show that membership change in the intra-group networks has a negative effect on group-level innovation. However, the negative effect is attenuatedwhen the centralization of intra-group networks decreases and when ties involving hub firms are reconfigured. The findings provide implications for both inter-firm network governance and innovation management, especially in the context of business groups. Keywords Whole network . Network changes . Innovation . Business groups
Networks, defined as a set of relationships and interactions among a group of interdependent firms, play an important role in fostering innovation (Ahuja, 2000; Uzzi & Spiro, 2005). As a governance mechanism that is alternative to markets and hierarchies, networks are believed to reduce transaction costs and build up mutual trust among members, which in turn enhance members’ commitment towards investing in * Shuping Li [email protected] Sai Yayavaram [email protected]
1
Faculty of Business, Hong Kong Polytechnic University, M907, Li Ka Shing Tower, Hung Hom, Hong Kong
2
Strategy Area, Indian Institute of Management Bangalore, Bannerghatta Road, Bangalore 560076, India
S. Li, S. Yayavaram
specialized assets such as human capital for innovation (Dyer & Singh, 1998). Network ties may also function as conduits for complementary information and resource flows, which provide key elements for knowledge recombination in innovation (Burt, 1992; Dyer & Singh, 1998). In addition, the network itself may directly produce knowledge in the sense that it represents a form of coordination guided by shared and enduring principles of organization (Kogut, 2000). It is now largely agreed that networks, appropriately structured, can enhance innovation by network members (Lazer & Friedman, 2007; Phelps, Heidl, & Wadhwa, 2012). However, the current networks literature is limited in that it has not given adequate attention to network change (Ahuja, Soda, & Zaheer, 2012; Doz, 1996; Majchrzak, Jarvenpaa, & Bagherzadeh, 2014). Rather, it typically assumes network membership to be stable and network ties and structure to be exogenous. Perceiving network structure as static or exogenous leads to a strong deterministic bias when initial network conditions define network outcomes (Doz, 1996). For instance, it is unclear whether the p
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