Purpose: Building supply chain (SC) resilience is crucial for business continuity given the ever-changing environmental conditions. Based on the resource orchestration and organizational culture theories, the purpose of this paper is to investigate the business value of SC resilience with the consideration of the roles of internal integration (II) and external integration (EI), risk management culture (RMC) and SC flexibility (SCF).Design/methodology/approach: This study investigates how RMC, SCF and intra and interorganizational integration affect the performance of SC resilience. It collects primary and secondary data from 194 manufacturing firms listed in the Taiwan Stock Exchange and Taipei Exchange.Findings: Results validate the authors’ hypothesis that RMC, SCF and II improve the financial performance of firms through SC resilience efforts.Research limitations/implications: This study uses firms from Taiwan manufacturing industry, which might introduce country and industry bias.Practical implications: This study helps managers improve the financial performance of their SC resilience efforts by developing RMC, SCF, II and IE across functions and partner firms.Originality/value: This study contributes to the literature by empirically testing the relationship between SC resilience and financial performance, and how the relationship is moderated by RMC, SCF, II and EI based on the theories of organizational culture and resource orchestration.

While consumers’ trust in social media influencers (SMIs) has spurred the growth of influencer marketing, consumers have come to distrust what these SMIs say recently. Despite this trend reversal that the industry is undergoing, academic efforts to investigate whether, and if so, why, consumers experience such attitudinal ambivalence in trust and distrust in the SMI landscape is notably lacking. Building upon the concept of attitudinal ambivalence between trust and distrust, this study addresses this gap in the literature. The study used a mixed-method approach. In Study 1, we conducted an exploratory, qualitative study using two focus group interviews. During the interviews, participants were asked to discuss the open-ended questions freely, which included such questions as “What do you think about your choice of SMI in terms of trustworthiness?” and “If you trust (or distrust, or feel ambivalent toward) SMIs, why?” Based upon the findings from Study 1, Study 2 developed and tested empirically the conceptual framework that describes the antecedents and consequences of consumers’ ambivalence within the SMI context: (1) whether SMIs’ personality traits (similarity and attractiveness) and content attributes (visual appeal and informativeness) promote consumers’ trust in the SMIs; (2) whether perceived ad clutter triggers their distrust of the SMIs’ branded content, and (3) whether the attitudinal ambivalence in trust and distrust affect their behavior (i.e., behavioral intention to imitate the SMIs’ product and brand choices) independently as well as interdependently. Except for attractiveness and visual appeal, the online survey consumer data supported the proposed relations strongly, and the results provide meaningful implications for both theory and practice.

The novel coronavirus pandemic is a major global public health emergency, and has presented new challenges and requirements for the timely response and operational stability of emergency logistics that were required to address the major public health events outbreak in China. Based on the problems of insufficient timeliness and high total system cost of emergency logistics distribution in major epidemic situations, this paper takes the minimum vehicle distribution travel cost, time cost, early/late punishment cost, and fixed cost of the vehicle as the target, the soft time window for receiving goods at each demand point, the rated load of the vehicle, the volume, maximum travel of the vehicle in a single delivery as constraints, and an emergency logistics vehicle routing problem optimization model for major epidemics was constructed. The convergence speed improvement strategy, particle search improvement strategy, and elite retention improvement strategy were introduced to improve the particle swarm optimization (PSO) algorithm for it to be suitable for solving global optimization problems. The simulation results prove that the improved PSO algorithm required to solve the emergency medical supplies logistics vehicle routing problem for the major emergency can reach optimal results. Compared with the basic PSO algorithm, the total cost was reduced by 20.09%.

In the context of carbon neutralization, the electric vehicle and energy storage market is growing rapidly. As a result, battery recycling is an important work with the consideration of the advent of battery retirement and resource constraints, environmental factors, resource regional constraints, and price factors. Based on the theoretical research of intelligent algorithm and mathematical models, an integer programming model of urban power battery reverse supply chain scheduling was established with the goal of the highest customer satisfaction and the least total cost of logistics and distribution, to study the influence of the resources and operation status of a built city recycling center and dismantling center on the power battery reverse supply chain. The model includes vehicle load, customer demand point satisfaction range, and service capacity constraints. This study collected regional image data, conducted image analysis, and further designed an improved Non-dominated Sorting Genetic Algorithm-II (NSGA-II) optimization algorithm suitable to solve the global optimization problem by introducing the improvement strategy of convergence rate, particle search, and the traditional elite individual retention. The results verified the practicability of the model, the global optimization ability of the algorithm to solve the problem, and the operation speed through comparing the results obtained from the basic algorithm. A reasonable comprehensive solution for the location and path optimization of the urban recycling center was also obtained. Multi-objective optimization was carried out in vehicle scheduling, facility construction, and customer satisfaction construction. The basic algorithm and integrated optimization software were compared. We found that the model and the scheme provided by the algorithm can significantly reduce the operation cost of the enterprise. This research provided new insights for enterprises to effectively utilize resources and optimize the reverse supply chain scheduling of an urban power battery.

Recycling waste electrical and electronic equipment (WEEE) has garnered considerable societal attention. To incentivize WEEE recycling within a closed-loop supply chain (CLSC), a deposit-refund system (DRS) has been implemented. This study delves into the implications of a market-driven DRS on WEEE recycling under different recycling models. A Stackelberg game analysis is employed, where an electronics manufacturer (leader) has sufficient channel power over an electronics retailer and a third-party recycler (followers). The results indicate that the market-driven DRS significantly incentivizes consumer recycling efforts, ultimately elevating the economic efficiency of the supply chain. When the electronics manufacturer assumes responsibility for WEEE recycling, it streamlines the recycling process, thereby enhancing operational efficiency and profitability. Conversely, when the electronics retailer handles WEEE recycling, it reduces retail prices and simplifies the recycling process, positively influencing consumer purchasing behavior. However, when a third-party recycler undertakes WEEE recycling, the recycling volume tends to be minimal, resulting in the lowest level of supply chain profits. This paper provides theoretical and practical implications for improving the recycling effectiveness and operational efficiency of the CLSC.