Qualitative comparative analysis: Configurational paths to innovation performance

Abstract

Although innovation research has received considerable attention in recent decades, the main focus has been on net effects analysis derived from symmetric thinking. Few studies have taken a holistic approach by investigating causal combinations of antecedent conditions. In addressing the question of how to promote firms’ innovation performance, we propose six antecedents from the internal, interfirm, and external contexts. These antecedents are knowledge stock, absorptive capacity, knowledge depth, knowledge breadth, government support, and the business environment. We apply fuzzy-set qualitative comparative analysis (fsQCA) to identify alternative configurations leading to high innovation performance from the perspective of knowledge management and innovation ecosystems. Data from 253 listed Chinese manufacturing firms form the basis of the analysis. The findings reveal seven configurational paths that explain high innovation performance and three paths to the absence of high innovation performance. This study provides new insight for innovation research. The paper concludes by discussing the implications for managers and policymakers.