The Impact of Configuration of Ties With Different Types of Actors in an Innovation Network on Technology Newness Based on QCA

Introduction

Since Freeman (1991) proposed the concept of innovation network, innovation network has been one of the paradigms to drive technology innovation in the fast-changing marketplace. With the recognition and development of innovation network theoretically and practically, strength of tie, as the most indispensible network attribute, has been a constant focus of academics.

There remains to be a paradox about strength of tie in academic world. Coleman(1988) and Larson(1992) claims that strong tie helps firms to build mutual trust and form channels of efficient communication, which enables researchers to better understand new knowledge and therefore promotes technology newness of a focal firm; Granovetter (1973) and Burt (2009) assert that weak tie can convey fresh knowledge and information more effectively among firms, and non-redundant information brought by weak tie contribute more to technology newness. To stick to their own argument, two groups of scholars have conducted tremendous theoretical exploration and empirical investigation concerning strength of tie and technology newness. At present, both sides basically reach an agreement that strong tie deepens the understanding and communication of knowledge among firms, which is in favor of the transmission of complicated, coded and explicit knowledge. Therefore, technology innovation led by strong tie mainly relies on existent technique or knowledge. Weak tie brings about heterogenous and tacit knowledge, which enables firms to spark new ideas or new approaches. Thus, technology innovation brought by weak tie primarily originates from brand-new skills or knowledge. To promote technology newness, what types of actors does a focal firm maintain strong tie or weak tie with in an innovation network? Does the relationship with a certain type of actors change? In addition, there exists a high degree of interdependency among different types of actors in an innovation network (Borgatti & Jones,1998; Siggelkow,2002), researchers must take systematization, integrality and synergy into careful consideration when investigating the relationship between a focal firm and other actors in a network. Conventional techniques such as linear regression analysis or structural equation model are apt to investigate the causality between an individual independent variable and the dependent variable, which is unable to fulfill the above requirements.

The paper employs qualitative comparative analysis (hereafter, QCA) to address the question based on 166 knowledge- intensive firms in Beijing Hi-Tech Industrial Development Area, China. QCA is appropriate for complex configuration analysis, and there are alternative combinations of attributes leading to the equifinality (Ragin & Fiss, 2017). QCA assume that impact of attributes (in our case, strength of tie with different actors) on a specific outcome (technology newness) depends on how attributes are combined rather than the levels of the individual attribute per se. The result indicates that three alternative combinations of strength of tie with diversified actors constitute sufficient conditions for technology newness. Furthermore, it is a necessary condition for a focal firm to keep strong tie with other business counterparts. The study makes up for the blank of interdependency among different types of actors in an innovation network. It also addresses the question of “Paradox of strength of tie” by employing QCA to identify with whom a focal firm should maintain strong tie or weak tie. The findings also contribute a lot to practical management that three alternative combinations of strength of tie with different types of actors offer an accurate recipe for firms to foster technology newness.