Utilizing a game-theoretic model, this study distinguishes between privacy-protecting and privacy-disclosing consumers, examining the impact of digital privacy on manufacturers’ channel strategies, including no encroachment, encroachment, and shifting. The results indicate that when consumers prefer privacy disclosure, manufacturers consistently opt for the shifting strategy. In contrast, when privacy protection is prioritized, the outcome depends on the intensity of consumer preferences. Specifically, weak preferences lead to encroachment, whereas strong preferences favor no-encroachment. This contingency framework illustrates how privacy preference thresholds shape channel strategy selection. From a practical perspective, the findings offer actionable guidance for manufacturers. First, a win-win outcome depends on the manufacturer’s cost-efficiency in channel-shifting operations, suggesting that firms should assess their operational capabilities before implementation. Second, consumer benefits under encroachment imply manufacturers can adopt this strategy for competitive advantage while addressing privacy concerns. These insights equip practitioners with a decision-making toolkit for balancing privacy compliance, channel efficiency, and stakeholder value creation in digital transformation initiatives.

Extended warranty (EW) is an optional contract that typically provides additional guarantee to users by the manufacturer after the initial warranty period of the equipment expires. To meet users' demand for minimizing the EW cost-availability ratio during the device's EW period and protect the manufacturer's profit, this article innovatively proposes a grouping preventive maintenance (GPM) strategy for multi-part series system, based on the consideration of user and manufacturer sharing warranty cost proportionally. This strategy can integrate the preventive maintenance (PM) of each individual component in the system, thereby reducing the total number of PM times and lowering the preparation cost for PM. The decision objective of the GPM strategy is to minimize the cost-availability ratio of the system's EW, and the decision variables are the PM interval and PM improvement factor. In the case analysis, taking the power system of electric vehicles as the research object, it was found that after adopting the GPM strategy, the EW cost-availability ratio of the system reduced by 16.6%, thus verifying the superiority of the GPM strategy proposed in this paper.

In China’s modern economic system, e-commerce has become a crucial driver for the development of businesses and supply chains. To clarify the impact and mechanisms of e-commerce development on the competitiveness of corporate supply chains, this study conducts an empirical analysis using data from A-share listed companies between 2010 and 2022. The results indicate that: (1) The development of e-commerce significantly enhances the competitiveness of corporate supply chains, with results remaining robust after endogenous and robustness tests; (2) The level of e-commerce development can further promote the improvement of supply chain competitiveness by improving resource integration, alleviating financing constraints, and increasing R&D investment; (3) The effects of e-commerce development exhibit heterogeneity: in state-owned enterprises and firms with lower competition, the influence of e-commerce on supply chains is more significant; in regions with high-speed rail (HSR) connectivity, e-commerce not only stabilizes customer relationships but also promotes corporate innovation, whereas in areas without HSR, e-commerce development may significantly mitigate issues related to capital occupation. The core innovation of this paper lies in the construction of a “e-commerce—resource integration/financing constraints/innovation investment—supply chain competitiveness” three-dimensional driving framework, establishing a multi-indicator evaluation system, and conducting heterogeneity and mechanism analyses from multiple perspectives. This provides systematic empirical evidence for the role of e-commerce in enhancing supply chain resilience and competitive advantage, offering policy recommendations for businesses to effectively improve their competitiveness.

In the low-carbon supply chain, when confronted with an external market offering higher profitability prospects, the monopoly manufacturer will prioritize serving that market, inevitably resulting in supply disruptions to local channels. This study delves into two distinct subsidy strategies employed by the government to avert supply disruption: a technology-driven "push" subsidy, devised to improve the ability to reduce emissions, and a price-responsive "pull" subsidy, geared towards influencing wholesale prices. Furthermore, if the external market spans international borders, the manufacturer must contend with the imposition of tariffs. Consequently, we analyze how these two subsidy types mitigate the risk of local supply disruptions within domestic and cross-border markets. The presence of carbon tariffs will have an impact on government subsidies and manufacturer capacity. Specifically, the surge in external market prices augments the strength of the effect. Alternatively, when the external market price is low, capacity has a negative impact on government subsidies. Moreover, we observed that when the manufacturer's capacity falls short, the government favors the implementation of pull subsidies. This arises from the fact that scarcity of goods tends to drive up prices, prompting the government to adopt the pull model to bolster consumption and alleviate the pressure on consumers.

This study develops a framework consisting of normative, leadership, and sustainable capabilities to evaluate corporate green governance capabilities (CGGC) in supply chains. The Fuzzy Best-Worst Method (FBWM) is used to determine indicator weights, and the Combined Compromise Solution (CoCoSo) method is applied to rank firm performance in the Yangtze River Delta from 2014 to 2022. Results show low but improving governance levels with notable differences across regions and enterprise types. Leadership capabilities are more affected by external shocks. State-owned and high-pollution firms perform better, while non-state and labor-intensive firms improve more rapidly. The study contributes methodological and practical insights.

Optimizing the distribution of perishable emergency materials in the aftermath of sudden disasters holds significant theoretical and practical value. This paper begins by defining the freshness of perishable emergency materials and develops a continuous piecewise function to describe the changes in quality and quantity of these materials at different time stages. Additionally, it considers distinct delivery requirements for each demand point regarding the same perishable emergency materials. Under the minimum freshness constraint, a vehicle distribution optimization model is established for perishable emergency materials, considering multiple distribution centers and multiple vehicles. Depending on whether the distribution center has an adequate number of vehicles, the solution can be classified into three scenarios. In the case of insufficient total emergency supplies but sufficient vehicles, an accurate algorithm is designed to address the model. Alternatively, when both the total emergency supplies and vehicles are insufficient, an approximate algorithm is developed to solve the model. Finally, when the total quantity of perishable emergency materials is inadequate, and some vehicles are sufficient while others are not, the problem is transformed into one of the first two situations to find a solution. To validate the accuracy of the model and the effectiveness of the algorithm, an analysis is conducted using the flood-stricken area in Shouguang, Shandong as a case study.

To enhance the overall accessibility and operational efficiency of highway networks, this paper proposes an integrated analytical approach based on node importance, network reliability, and critical link identification to identify key transportation corridors within highway networks. Initially, a comprehensive node importance measurement method is developed by integrating static geometric characteristics and dynamic traffic attributes of complex networks. The weights of static indicators are calculated using an improved entropy weight method, while the dynamic importance of nodes is assessed based on the h-index, resulting in a ranked node importance list. Subsequently, from the perspective of network reliability, critical nodes are identified and ranked by simulating node failure scenarios through attack strategies, evaluating their impact on network connectivity and travel time. Further, critical links are identified utilizing the Stochastic User Equilibrium (SUE) model and Ant Colony Optimization (ACO). Finally, a multi-objective key corridor identification method based on feature lines is formulated by comprehensively considering node importance, network reliability, and critical road segments. An empirical analysis is conducted on the highway network across 11 counties/districts of Zhaotong City, Yunnan Province. Three key transportation corridors are ultimately identified:Ludian County-Zhaoyang District-Daguan County-Yanjin County, Ludian County-Zhaoyang District-Daguan County-Yongshan County, Ludian County-Zhaoyang District-Yiliang County.

Based on the perspective of supply-demand imbalance, this article constructs a collaborative innovation decision-making model for the photovoltaic industry supply chain using differential game theory. It analyzes two different decision-making scenarios: decentralized decision-making and centralized decision-making, and focuses on studying the impact of cost sharing contracts under decentralized decision-making and revenue sharing contracts under centralized decision-making on the decision-making behavior of photovoltaic industry supply chain entities. Research has found that: 1) The supply-demand imbalance coefficient affects the pricing of photovoltaic silicon wafer suppliers. 2) In the case of decentralized decision-making, considering the cost sharing contract situation in the photovoltaic industry supply chain system can better optimize the profit value and innovation level of each subject in the photovoltaic industry supply chain. 3) The benefit sharing contract under centralized decision-making is more effective than the cost sharing contract under decentralized decision-making.

This study investigates the mechanisms underlying quality loss and compensation in dam concrete construction from both managerial and technical perspectives, presenting an innovative approach to quality control. The primary contribution of this research lies in the integration of characteristic functions into the Graphical Evaluation and Review Technique (GERT), facilitating the development of a quality gain-loss transmission network and enabling network parameter analysis. Additionally, models for identifying and predicting critical paths and processes have been developed. A case study focusing on quality control during the summer construction phase of a hydropower project was conducted to validate the proposed model's effectiveness and rationale. This study aims to offer valuable insights and make a significant contribution to technical advancements in quality control for dam concrete construction.

With the rapid growth of e-commerce, platform-based financing in electronic business (EB) has emerged as an innovative solution for online retailers facing capital constraints. This study develops a Stackelberg game-theoretic framework to analyze strategic financing decisions in a two-tier e-commerce supply chain, where an electronic business platform (EBP) , as the leader, assumes leadership by setting financing interest rates, while a capital-constrained, loss-averse online retailer (LOR), as the follower, optimizes order quantities and financing participation under behavioral risk preferences. A hierarchical game-theoretic framework is established to examine strategic interactions between an EBP and a LOR, and the equilibrium outcomes are given. The model derives optimal decisions for both financing rates and ordering strategies. Results demonstrate that when the retailer's initial capital grows, their necessity for external financing diminishes correspondingly, leading to smaller order quantities due to reduced bankruptcy risk. Moreover, higher levels of loss aversion cause retailers to order less and avoid financing, reflecting risk-sensitive behavior. The study also presents comprehensive numerical analyses to explore additional managerial implications, offering insights into how capital availability and behavioral factors like loss aversion shape decision-making in EB financing environments.