Aiming at the current charging dilemma of electric bicycles, this paper proposes a method for determining the location and capacity of centralized charging and battery swapping stations. Based on POI data, this study identifies hotspots of charging and battery swapping demand in the research area, constructs a comprehensive model targeting the minimization of operators' costs and users' time costs, and employs the simulated annealing-particle swarm optimization (SA-PSO) hybrid algorithm to solve the model for obtaining the locations of the stations and the configuration quantity of equipment. Through case analysis, the results of location and capacity determination for centralized charging and battery swapping stations in the research area are obtained, providing theoretical reference for electric bicycle charging and battery swapping operators.

With the development of the world economy and the severe situation of environmental pollution, the concept of corporate responsibility has shifted from traditional economic growth to a comprehensive perspective of Environmental, Social, and Governance (ESG). Under China's "high-quality development" and "dual carbon" strategies, corporate ESG performance has increasingly become an important evaluation indicator to measure a company's sustainable development capacity and long-term investment value. This paper analyzes the internal and external driving factors for the improvement of corporate ESG performance. External driving factors include policies, industry norm constraints, external attention, and industrial chains, while internal driving factors include the company's own scale, technological innovation, talent support, and executive characteristics.

With the development of the digital economy, digital-intelligent transformation has become an important force for creating new quality productivity. This paper uses Mindray Medical International Co., Ltd. (Mindray) as a case study. It reviews Mindray’s digital-intelligent transformation process since 2015 and uses the entropy-weight Analytic Hierarchy Process (AHP) method to build an evaluation indicator system. The paper evaluates how this transformation affects the company’s new quality productivity from three aspects: input, production, and output. The results show that from 2018 to 2024, Mindray’s overall score of new quality productivity increased steadily. This means that digital-intelligent transformation has continuously improved the company’s total factor productivity. In addition, Mindray has built a smart healthcare ecosystem based on “Device + IT + AI”. This ecosystem enables intelligent upgrading in research and development, production, and services. As a result, production factors are allocated in a more innovative way, and the value of data is used more efficiently.