Developing a Knowledge Management Framework for Innovation Performance in Tech Startups

Abstract

Abstract: The objective of this study is to develop a comprehensive knowledge management (KM) framework that enhances innovation performance in tech startups. This study employs a qualitative research design using semi-structured interviews to gather insights from 16 participants, including founders, managers, and senior executives from tech startups. The interviews focused on knowledge management practices, leadership roles, and innovation strategies within their organizations. Thematic analysis was conducted using NVivo software, and data was coded through open, axial, and selective coding processes to identify key themes and patterns related to KM and innovation. The principle of theoretical saturation guided the sample size. The study identified several critical factors that influence knowledge management in tech startups, including the importance of knowledge sharing practices, leadership support for KM initiatives, and the role of technology in facilitating knowledge transfer. Organizational learning and external collaborations were found to play a crucial role in enhancing innovation performance. Additionally, barriers such as knowledge silos, internal communication challenges, and resource constraints were noted as significant obstacles to effective KM. A flexible organizational structure and strong absorptive capacity were identified as essential for integrating external knowledge and driving innovation. The findings suggest that an effective KM framework, supported by leadership, technology, and a culture of knowledge sharing, is crucial for driving innovation in tech startups. Addressing barriers to KM and promoting continuous learning and collaboration can enhance innovation performance. Startups should focus on building their absorptive capacity and leveraging external partnerships for sustained growth and competitiveness.