The relationship between network capabilities and innovation performance. Evidence from Chinese high-tech industry
| Pages | 1638-1654 |
| Published date | 09 September 2019 |
| Date | 09 September 2019 |
| DOI | https://doi.org/10.1108/IMDS-02-2019-0060 |
| Author | Gang Fang,Qing Zhou,Jian Wu,Xiaoguang Qi |
| Subject Matter | Information & knowledge management |
The relationship between
network capabilities and
innovation performance
Evidence from Chinese high-tech industry
Gang Fang and Qing Zhou
School of Management, Hangzhou Dianzi University, Hangzhou, China
Jian Wu
Hangzhou Dianzi University, Hangzhou, China, and
Xiaoguang Qi
Wolfson College,
University of Cambridge, Cambridge, UK and
Hangzhou Dianzi University, Hangzhou, China
Abstract
Purpose –Innovation networks provide an efficient mechanism for organizations to realize their potential
for knowledge learning and innovation improvement. Firms situated within innovation networks require
specific abilities to acquire the knowledge and the complementary assets that facilitate their innovation
performance. Motivated by recent research studies in the area of social network and RBV, the purpose of this
paper is to improve the understanding of the precise manner in which network capability affects a firm’s
innovation performance.
Design/methodology/approach –Based onthe data obtained from Chinese high-techfirms, the hypotheses
are tested by using hierarchical multiple regressions.
Findings –This study identifies two types of network capabilities: network structural capability and
network relational capability. The findings suggest that network structural capability has a greater positive
impact on innovation performance than network relational capability does within an exploration-orientated
network. However, network relational capability is more positively associated with innovation performance
within an exploitation-orientated network.
Practical implications –A firm canenhance the value of its ego networkby shaping and adjusting network
configurations,rather than by passively reapingthe benefits from existing relationships or ties withpartners.
Originality/value –This paper contributes to strategic management theory and social network theory by
illustrating how a networked firm can enable network value and appropriate this value according to its strategic
purposes and by suggesting that a firm can improve its ego network’s value through exerting its network
capabilities to shape and adjust network configurations. This paper also advances the contingent approach within
social network research by offering a new complementary perspective and new evidence from a Chinese context.
Keywords Innovation, Resource-based view, Innovation, Network capabilities
Paper type Research paper
1. Introduction
A firm situated within a network can acquire complimentary assets and resources from its
network partners (Dyer and Singh, 1998; Kale et al., 2000; Levin and Cross, 2004). In
particular, the knowledge sharing and learning routines between network partners can
contribute to the firm’s ability to innovate (Tsai, 2001; Cooke, 2006). Previous research in
strategic management theory has introduced the concept of network resources (Dyer and
Singh, 1998; Gulati, 1999; Gulati et al., 2000), which can be described as the source of a firm’s
Industrial Management & Data
Systems
Vol. 119 No. 8, 2019
pp. 1638-1654
© Emerald PublishingLimited
0263-5577
DOI 10.1108/IMDS-02-2019-0060
Received 1 February 2019
Revised 14 April 2019
11 June 2019
Accepted 24 June 2019
The current issue and full text archive of this journal is available on Emerald Insight at:
www.emeraldinsight.com/0263-5577.htm
This study is jointly supported by the National Science Foundation of China for the funding of projects
(Grant Nos 71872059, 71874046), and the Humanities and Social Sciences Foundation for the Youth
Scholars of the Ministry of Education, China (Grant No. 16YJC630087).
1638
IMDS
119,8
competitive advantage (Barney, 1992; Madhok and Tallman, 1998). However, competitive
advantages cannot be generated by resources alone. They are contingent on the ways
through which resources are effectively exploited and deployed, and these require specific
capabilities (Grant, 1991; Amit and Schoemaker, 1993). Consequently, it is believed that
firms situated within innovation networks require specific capabilities to better exploit
network resources for enhancing and improving their innovation performance.
Previous research in social network theory has suggested that because of firms’
asymmetric access to resources and their differing capacities of information gathering,
inter-firm networks can significantly influence a firm’s performance (Granovetter, 1983).
Similarly, Gulati (1998) argued that a firm’s embeddedness within a network, which includes
both structural embeddedness and relational embeddedness, can either facilitate or impede
the benefits that the firm obtains from its partners. Firms that are “better connected”to their
partners (Burt, 2000) can obtain more benefits from innovation networks through extensive
knowledge sharing with each other than those that are not (e.g. Kale et al., 2000; Levin and
Cross, 2004; Tsai, 2002), thereby improving their innovation success (Bellamy et al., 2014;
Mahmood et al., 2011; Owen-Smith and Powell, 2004).
However, there has been a long-running debate within the network literature on the kind of
network configuration that enhances a firm’s performance, i.e. what is the “better connection”?
Weak ties (Granovetter, 1973) or strong ties (Krackhardt, 1992), and sparse structure (Burt, 1992)
or dense structure (Coleman, 1988)? As a way to promote this debate further, several recent
studies have proposed the use of a contingency approach. For instance, some studies have
argued that weak or strong ties and sparse or dense structure can each be critical for a firm’s
innovation performance, depending on the particular context being studied (Ahuja, 2000; Wang
et al., 2017) and/or the firm’s specific strategic purpose (Gilsing and Nooteboom, 2005). Such
studies have shed light on our understanding of the specific conditions under which strong/weak
and sparse/dense networks are positively related to firm performance (Rowley et al.,2000).
Althoughprevious studies havehighlighted theneed for different levels of networkdensity
or tie strength in particular contexts, substantially less attention has been focused on the
differential impactsof network densitycompared to tiestrength on the innovation performance
of a firm witha specific strategicpurpose. Especially, exploration and exploitation mayrequire
inconsistent network configurations and firm capabilities. Some recent research (e.g. Gilsing
and Nooteboom, 2005) has already discussed the impact of exploration and exploitation on
value extraction from innovation network. However, our knowledge still remains undeveloped
and, at least, unsystematic.
Drawing on the resource-based view and social network theory, this study aims to
deepen our understanding of the precise manner in which network capability affects a firm’s
innovation performance. Following the contingency approach, it further attempts to identify
the specific capability, whether network structural or network relational, that a firm would
need most to maximize value appropriation while keeping in line with the firm’s strategic
focus of exploration or exploration.
2. Theory and hypotheses
2.1 Network capabilities
Innovationnetwork is a system of autonomous and equal firmsconnected by selective, formal
and persistent relations to transfer knowledge, or to innovate cooperatively. It provides an
efficient mechani sm for embedded firms to acquir e new knowledge from partners ( Kale et al.,
2000), sharerisk or uncertainty with partners (Bleeke andErnst, 1991) and cope with systemic
innovation (Freeman, 1991). One major research stream in innovation network area is based
on social networktheory. The majority of recent studies indicate that network configurations
affect a firm’s success in innovation. Network configuration refers to “the make-up of
networksand how these can be formed to benefit strategicgoals”(Pittaway et al., 2004, p. 143).
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Network
capabilities
and innovation
performance
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