Effect of efficient triple-helix collaboration on organizations based on their stage of growth

Abstract

Triple Helix (TH) theory, which emphasizes synergy between universities, industries, and government, has not been tested empirically from the perspective of differences in R&D efficiency. We examine how firms’ TH strategies affect R&D efficiency and how synergy varies according to stage of growth. First, we classify the firms into four groups by TH strategy. We estimate each firm’s R&D efficiency and compare each group’s technical gap ratio relative to the meta-frontier. The results show that synergy does exist in long-term R&D efficiency and potential. Discussion of the heterogeneous effects of TH strategies according to the firms’ stage of growth follows.

Introduction

Knowledge is the most important asset of sustainable firm growth (Kogut and Zander, 1992; Teece, 1998; Winter, 1997). Despite its importance, firms still struggle to create new knowledge as the process of recombining existing knowledge becomes more complex (Rivkin, 2001; Sorenson et al., 2006; Trout and Rivkin, 2010). Recent studies reported that finding new ideas has become difficult and the overall R&D efficiency has decreased (Bloom et al., 2017). To improve the R&D efficiency, R&D cooperation, which shares risks and costs and responds quickly to market changes, has become more important, and such R&D cooperation strategies are being actively studied (Ahuja, 2000; Baldwin and Green, 1984; Czarnitzki et al., 2007; Levinson, 1984). In this regard, firms need more sophisticated R&D cooperation strategies to create new knowledge and increase R&D efficiency.

New knowledge comes from a recombination or reconfiguration of existing useful knowledge (Gibbons, 1994; Katila and Ahuja, 2002; Nerkar, 2003). For easier and better knowledge recombination, collaboration is necessary for better outcomes compared to working individually (Bollinger and Smith, 2001; Gold et al., 2001; Inkpen, 1996; Siegel et al., 2003). Therefore, creating efficient collaborative networks is considered an important innovation strategy at the firm level (Nieto and Santamaría, 2007), the industry level (Freeman, 1991), and the national level (Etzkowitz, 2002).

New and highly complex knowledge is often found via universities or government-funded research institutions rather than industries by themselves. In this case, close connections with universities or research institutions can benefit entire industries in terms of knowledge creation (Rosenberg and Nelson, 1994). Especially, universities can play an enhanced role in industry innovation because advanced knowledge in science and technology provides the foundation for future industrial development in highly complex knowledge-based societies (Etzkowitz and Leydesdorff, 2000).

The triple helix (TH) model is proposed in this context. TH is a tripartite cooperative interaction between universities, industries, and government, which can result in innovation at the national level (Etzkowitz and Leydesdorff, 1997). Innovation can be enhanced not only by increasing the number of actors (double or triple), but also by improving the synergy (helix) between the intensity and quality of interaction. Ivanova and Leydesdorff (2015) gave an example of such synergy via three-dimensional collaboration, university-industry-government (UIG), showing it is more likely to create advanced complex knowledge than two-dimensional collaborations of university-industry (UI) or government-industry (GI). In other words, increasing firms’ collaborative dimension is a more efficient way for firms to create complex knowledge, therefore affecting their R&D efficiency in a positive way.

TH theory, however, has not been tested empirically from the perspective of differences in R&D efficiency. The R&D efficiency of TH is difficult to specify due to the countless possibilities of synergy-creating factors such as increased R&D expenditure, innovation policy change, inventor mobility, and so on (Hollanders and van Cruysen, 2008; Ivanova and Leydesdorff, 2015). Previous studies on the relationship between innovation capability and efficiency of innovation have mostly been conducted in the form of case studies about developing countries’ National Innovation Systems (NIS) in a descriptive way. However, few studies have been conducted using quantitative methods. Since TH originates from NIS theory, the implications have often targeted policymakers at the national level. Correspondingly, there has been a large body of research analyzing the outputs of R&D collaboration with other competing firms, rather than R&D collaboration with non-competing organizations such as universities or government-funded research institutions (Belderbos et al., 2004).

Here, we discuss the remaining questions about how a firm’s TH collaborative strategies affect R&D efficiency. Specifically, we focus on the following questions. 1) How do the two kinds of two-dimensional synergy, UI and IG, vary in terms of R&D efficiency? 2) How large is the synergy effect of the triple helix (UIG) compared to other collaboration types? 3) What is the best collaborative strategy regarding firms’ stage of growth? To answer these questions, we first measure the R&D efficiencies of the four categorized TH strategic groups using stochastic frontier analysis. Based on meta-frontier analysis, we also measure the R&D efficiency among all firms belonging to different strategic groups and compare the efficiencies directly. Lastly, to examine the existence of the synergy effects, we determine if the variously measured R&D efficiencies are statistically different among the TH strategic groups.

The remainder of this paper is as follows. First, we explain the theoretical foundations of how TH can be translated into R&D efficiency. We then suggest methods for categorizing the firms’ TH strategies, measuring the R&D efficiency, and linking the two variables together. Finally, we present our results along with a discussion, including suggestions for managerial implications based on the growth phase of the firm.