Decision-Making and Data Sharing in Smart Catering: An Evolutionary Game Approach

With the rapid advancement of the Internet and big data, data sharing has become pivotal for enhancing operational efficiency and user experience across industries. In the restaurant sector, the emergence of smart kitchens has accelerated digital transformation, underscoring the critical importance of data sharing. In this study, we investigate the evolutionary dynamics among four key stakeholders in the smart kitchen ecosystem: data providers, data-sharing platforms, data consumers, and regulators. We develop a four-party evolutionary game model to analyze the strategic interactions and behavioral evolution of each participant, applying replicator dynamics and Lyapunov stability theory. Our findings reveal that (1) data providers’ willingness to supply high-quality data is strongly influenced by platform incentives; (2) platforms’ adoption of data governance mechanisms depends on associated governance costs; (3) regulatory subsidies contribute significantly to system stability; and (4) increased financial support for regulators promotes favorable system evolution. This work offers both theoretical insights and practical guidance for data sharing in smart kitchens, providing a novel perspective on digital transformation within the restaurant industry.