R&D alliance partner attributes and innovation performance: a fuzzy set qualitative comparative analysis

Purpose Drawing upon the importance of research and development (R&D) alliances in driving firm innovation performance, extant research has analyzed individually the impact of R&D alliance partner attributes on firm innovation performance. Despite such analyzes, research has generally underestimated the configurations of partner attributes leading to firm innovation performance. This research gap is interesting to explore, as firms involved in R&D alliances usually face a combination of partner attributes. Moreover, gaining a better understanding of how R&D partner attributes tie into configurations is an issue that is attracting particular interest in coopetition research and alliance literature. This paper aims to obtain a better knowledge of this underrated, but important, aspect of alliances by exploring what configurations of R&D alliance partner attributes lead firms involved in R&D alliances to achieve high innovation performance. To tackle this question, first, this study reviews the extant literature on R&D alliances by relying on the knowledge-based view of alliances to identify the most impactful partner attributes on firms’ innovation performance. This paper then applies a fuzzy set qualitative comparative analysis (fsQCA) to explore the configurations of R&D alliance partner attributes that lead firms involved in R&D alliances to achieve high innovation performance. Design/methodology/approach This study selects 27 R&D alliances formed worldwide in the telecom industry. This paper explores the multiple configurations of partner attributes of these alliances by conducting a fsQCA. Findings The findings of the fsQCA show that the two alternate configurations of partner attributes guided the firms involved in these alliances to achieve high innovation performance: a configuration with extensive partner technological relatedness and coopetition, but no experience; and a configuration with extensive partner experience and competition, but no technological relatedness. Research limitations/implications The research highlights the importance of how partner attributes (i.e. partner technological relatedness, partner competitive overlap, partner experience and partner relative size) tie, with regard to the firms’ access to external knowledge and consequently to their willingness to achieve high innovation performance. Moreover, this paper reveals the beneficial effect of competition on the innovation performance of the firms involved in R&D alliances w