This study examines how dynamic capabilities influence innovation performance throughout the startup lifecycle. We focus on the AgTech sector to understand how combinations of trust, commitment, and communication (collaboration capability), absorptive capacity, and organizational agility, impact innovation at different lifecycle stages.
We apply fuzzy-set qualitative comparative analysis (fsQCA) to a dataset of 237 startups (AgTechs) to identify sufficient combinations of dynamic capabilities that lead to high or low innovation performance. We performed multiple analyses of fsQCA, one for each lifecycle stage (organization and traction, growth and scale, and consolidation and transition).
The results highlight the critical role of absorptive capacity and organizational agility across all stages of a startups’ lifecycle. Commitment and communication emerge as key factors in explaining innovation performance, but their influence varies by lifecycle stage. The study underscores the changing needs of startups and how these impact their ability to innovate.
The research shows the roles of different dynamic capabilities throughout startups’ lifecycle, helping these companies prioritize resource allocation effectively. In other words, the relevance of dynamic capabilities is not static along the firm’s lifecycle. This research advances the theory of dynamic capabilities in startups by detailing the combinations of capabilities that lead to high or low innovation performance at different lifecycle stages. It also offers practical guidance for AgTechs entrepreneurs and managers navigating the challenges of innovation.
