AUTHOR=Lin Mei-Hsing , Chou Hsin-Hui TITLE=Collapse of Better Place: A Managerial Cognition Perspective on the Failure of an Entrepreneurial Initiative JOURNAL=Frontiers in Psychology VOLUME=13 YEAR=2022 URL=https://www.frontiersin.org/journals/psychology/articles/10.3389/fpsyg.2022.846434 DOI=10.3389/fpsyg.2022.846434 ISSN=1664-1078 ABSTRACT=

The survival of any entrepreneurial initiative depends on a working business model that could create value for the customers and, simultaneously, allow the firm to capture value from what has been created. Despite increased attention to business model research, the understanding of business models’ impact on entrepreneurial development is quite constrained. In particular, the question of how an entrepreneurial firm’s business model is influenced by its organizational members’ managerial cognition remains under-explored. To tackle this research question, we drew a linkage between the business model literature and a managerial cognition perspective to build the theoretical foundation. We used this theoretical lens to investigate the failure of Better Place, an Israeli entrepreneurial company that focused on its proprietary battery-swap electric vehicles. In our findings, we argued that organizational members’ managerial-cognition-based conceptual framework is critical to the business model decision-making of an entrepreneurial firm. The discrepant and strongly held conceptual framework may result in misjudgment of environmental changes, especially when emerging-market numbers in an industry are high, and consensus regarding technology innovation in an industry is still lacking. The improper conceptual framework can generate mistaken business models, which further bring about an organizational decline. It is crucial for entrepreneurial firms to learn and improve existing conceptual frameworks and consequent business models by business interaction in the initiative stage if they are to avoid failure. The research outcome paves the way for future empirical studies to contribute to machine learning in the field of cognitive automation, artificial-intelligence-driven smart manufacturing, and sustainable industrial value creation in the era of digital transformation.