Knowledge Spillovers in the Supply Chain: Evidence from the High Tech Sectors

Abstract

In addition to internal R&D, external knowledge is widely considered as an essential lever for innovative performance. This paper analyzes knowledge spillovers in supply chain networks. Specifically, we investigate how supplier innovation is impacted by buyer innovation. Financial accounting data is combined with supply chain relationship data and patent data for U.S. firms in high tech industries. Our econometric analysis shows that buyer innovation has a positive and significant impact on supplier innovation. We find that the duration of the buyer-supplier relationship positively moderates this effect, but that the technological proximity between the two firms does not have a significant effect on spillovers.

Knowledge exploration and innovation: A review and an inverse S-curve proposition

“…Moreover, Huang, Rice, and Martin (2015) found that the impact of interfirm networking on innovation performance is negatively moderated by firm size, in that only small and medium-sized enterprises (rather than large firms) benefit from interfirm networking in innovation. In the buyer–supplier partnership, Isaksson, Simeth, and Seifert (2016) also showed that relationship duration positively moderates the effect of knowledge exploration from buyer technological innovation on supplier technological innovation. Finally, Frankort (2016) uncovered that the positive influence of the knowledge acquisition from alliances on new product development is moderated positively by technological relatedness and negatively by product-market competition.…”

“…Building upon the generally positive relationship between exploration and innovation, some studies have identified several moderators that could potentially modify the learning process between exploration and innovation (e.g., McGrath, 2001; Laursen & Salter, 2006; Sidhu, Commandeur, & Volberda, 2007; Laursen, Masciarelli, & Prencipe, 2012; Zhou & Li, 2012; Li et al, 2013; Huang, Rice, & Martin, 2015; Frankort, 2016; Isaksson, Simeth, & Seifert, 2016). For instance, McGrath (2001) focussed on the role of managerial oversight in supporting variance-enhancing learning during exploration, and found that goal autonomy and supervision autonomy enhance the positive relationship between exploration and innovation in new business development projects.…”

“…Some core micro-level concepts of the framework, including knowledge elements, knowledge combination, and knowledge recombining, delineate the underlying process of macro-level learning and innovation. Empirical studies often operationalise knowledge elements as patents; thus, the number of knowledge elements of an organisation is the total number of patents it uses to develop new patents (e.g., Rosenkopf & Nerkar, 2001; Ahuja & Katila, 2004; Chatterji & Fabrizio, 2014; Wang, Rodan, Fruin, & Xu, 2014; Isaksson, Simeth, & Seifert, 2016). Knowledge elements can be external to the organisation (Ahuja & Lampert, 2001; Laursen & Salter, 2014; Operti & Carnabuci, 2014), and in this sense, its knowledge repertoire can be expanded by the incorporation of new knowledge elements from external sources, that is, knowledge exploration.…”

Tax Knowledge Diffusion via Strategic Alliances

“…Consistent with this, cooperation is found to mitigate problems ensuing from cultural differences (Kogut and Singh, 1988). Spillovers are also more likely to occur in cases of an high frequency of interactions between firms (Isaksson, Simeth, and Seifert, 2016) and with increasing partner trustworthiness (Jiang et al, 2016). Regarded as "lying somewhere in between single-firm activity and spot contracting" (Lindsey, 2008) and presenting increased mutual commitment in comparison to arm's-length market transactions (Chan et al, 1997), strategic alliances further comply with the diffusion requirements proposed by Rogers.…”

“…Repeated business transactions are found to enable knowledge spillovers (Isaksson, Simeth, and Seifert, 2016). However, not all corporate practices diffuse in the same way (Cai et al, 2014), as major barriers to knowledge spillovers are shown to be knowledge-related factors (Szulanski, 1996).…”