Shuai Deng

To enhance privacy protection strategies in libraries-based Artificial Intelligence Generated Content (AIGC) technologies, this study investigates the interactive decision-making among government, libraries, and users. Based on evolutionary game theory, a three-party evolutionary game (TEG) model is constructed to analyze their strategic interactions. Replicator dynamic equations are applied to identify the drivers of strategy changes and the equilibrium stability conditions, while system dynamics simulations using Vensim PLE 7.5b explore parameter settings under which different equilibria emerge. The analysis further examines the sensitivity of stakeholder behaviors to incentive mechanisms. Results show that government reputation, libraries optimization costs and risks, and user disclosure incentives and privacy concerns are the critical factors shaping strategic choices. Accordingly, the study suggests that governments should strengthen the assessment of privacy protection performance to safe-guard reputation, libraries should reduce optimization costs through technological innovation, and users should enhance their awareness of privacy risks. Moreover, the findings emphasize the importance of incentive mechanisms, recommending that policymakers adopt moderate penalties and rewards to effectively promote privacy protection. In conclusion, this study has expanded our understanding of the AIGC privacy issues in libraries, and has also provided a theoretical basis and operational guidelines for the design of library privacy protection policies.

The entry of potential competitors disrupts the original market equilibrium, which in turn hinders the adoption of RFID technology. This paper focuses on a supply chain consisting of one supplier and two retailers in a master-slave relationship. It develops a decision model for RFID investment, employing a simultaneous game to analyze how RFID technology influences the revenue and strategic behavior of supply chain members. Based on numerical analysis, the key findings of this study are as follows: (1) The adoption of RFID technology increases the revenue of both retailers to some extent. (2) The incumbent retailer demonstrates a stronger ability to withstand risks. (3) The maximum label cost and revenue-sharing rate that suppliers can bear are influenced by the market equilibrium in the absence of RFID. This study offers both theoretical and practical insights for promoting RFID technology in competitive markets.

Recent frequent “thunderstorm incidents” of the internet financial platforms (IFPs) have caused the panic of investors. In order to measure and reduce the investment risk of IFPs, the focus of this study is to evaluate the reputation of IFPs regarding investment risk. First, the reputation evaluation indicator system of IFPs is constructed from two dimensions of direct and indirect reputations. Then, based on this system, an improved fuzzy evaluation approach (IFEA) integrating the method of fuzzy comprehensive evaluation (FCE), the analytic hierarchy process (AHP), and the factor analysis (FA) are proposed for evaluating the reputation of IFPs. Finally, a case study based on the data of 20 peer-to-peer (P2P) lending platforms from “Home of Online Loans” (HOL) in China is used to illustrate the IFEA. Results show that the IFEA can reduce uncertainty and randomness in the determination process of indicator weight and membership degree and therefore accurately obtain the reputation level of IFPs and help investors make better decisions. Meanwhile, the key factors in determining the reputation of IFPs are identified, thereby improving the reputation level of the IFPs.

This paper considers a supply chain consisting of one supplier and one retailer who jointly invest in item‐level radio frequency identification (RFID) by considering their demands and inventories. Since the supplier can be negative to adopt RFID, the main objective of this study is to design an effective mechanism that maximizes the profits of both players and the whole supply chain by implementing item‐level RFID. For this objective, we propose a novel revenue‐cost‐sharing (RCS) contract based on the bargaining game as the incentive to encourage the implementation, and numerical results show that the RCS contract is considerably more effective than the wholesale‐price contract for supply chain coordination. Moreover, we show that the retail supply chain can be coordinated perfectly under the RCS contract when the thresholds of the revenue/cost sharing rates are set appropriately. This study provides significant managerial insight into the incentive and coordination strategy to implement item‐level RFID in the retail supply chain.

Customer returns are a common phenomenon in many industries, and they have a significant impact on business organizations and their supply chains. False failure returns are returned products that have no functional or cosmetic defects, and they represent a large body of customer returns in practice. In this paper, we develop a mixed‐integer nonlinear programming model to study a multicommodity location‐inventory problem in a forward‐reverse logistics network. This model minimizes the total cost in this network by considering false failure returns, and it also considers many real‐world business scenarios in forward and reverse logistics flows. Moreover, we design a new heuristic approach to solve the model efficiently. Finally, numerical experiments are conducted to validate our solution approach and provide meaningful managerial insights.