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The sports service supply chain faces various potential risks, such as market fluctuations, logistics issues, and partner uncertainties. To address these risks effectively, this study employs a combination of fuzzy comprehensive evaluation (FCE) methods and intelligent neural networks to create an innovative risk management framework. By considering diverse uncertainties and leveraging the analytical power of intelligent neural networks, this study aims to optimize the operation of the sports service supply chain and explore the risk factors within the public service supply chain of stadiums. This framework provides policy references to promote the healthy and sustainable development of the sports service industry. The main empirical findings, based on a representative survey of experts in China, are as follows: (1) When determining the weights of risk indicators for managing the public service supply chain of stadiums using the FCE method, the customer risk indicator is of paramount importance, with a weight of 0.286, accounting for 95.2% of the total significance; and (2) In evaluating various risk indicators of the public service supply chain of stadiums through the neural network method, the customer risk indicator scores the highest, achieving a score of 76.02. Notably, the customer complaint risk indicator scores slightly higher at 79.33. Based on these findings, the study recommends focusing on enhancing customer experience within risk management strategies. Additionally, it suggests strengthening the supervision of platforms and third-party activities to ensure the stability and efficient operation of the stadium service supply chain. This study aims to provide theoretical support and reference indicators for evaluating the public service capabilities of stadiums.
Cong et al. (Wed,) studied this question.