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This paper explores how the existence of a second-hand market can affect remanufacturing decisions for durable goods in the presence of patent protection.

The authors construct a dynamic decision model between a durable goods original manufacturer and a durable goods remanufacturer considering the characteristics of the multi-cycle uses of new durable goods and remanufactured durable goods.

The results show that (1) the second-hand market compresses the cost space of a durable goods original manufacturer and a remanufacturer; (2) when the second-hand market exists, the optimal pricing of new durable goods is reduced, the optimal pricing of remanufactured durable goods is increased and the patent cost of each unit of durable goods increases and (3) the presence of the second-hand market will increase the original manufacturer's and remanufacturer's profits.

The research conclusion has certain reference value for the production strategy selection of each enterprise in the process of patented product remanufacturing and the government's fiscal policy formulation at each stage of the remanufacturing industry's development.

The purpose of this study is to investigate the impact of greening and promotional effort dependent stochastic market demand on the remanufacturer's and the collector's profits when the quality of used products for remanufacturing is uncertain in a reverse supply chain.

The proposed model is developed to obtain optimal profits for the remanufacturer, the collector and the whole supply chain. Both the centralized and decentralized scenarios are considered. To motivate the collector through profit enhancement, the remanufacturer designs a cost-sharing contract. Through numerical examples and sensitivity analysis, the consequences of greenness and promotional effort on optimal profits are investigated.

The results show that the remanufacturer gets benefited from greening and promotional effort enhancement. However, a higher value of minimum acceptable quality level decreases the profits of the manufacturer and the collector. A cost-sharing contract coordinates the supply chain and improves the remanufacturer's and the collector's profits. Besides green innovation, remanufacturing mitigates the harmful effects of waste in the environment.

Two different viewpoints of remanufacturing are considered here – environmental sustainability and economic sustainability. This paper considers a reverse supply chain with a remanufacturer who remanufactures the used products collected by the collector. The quality of used products is uncertain, and customer demand is stochastic, green and promotional effort sensitive. These two types of uncertainty with green and promotional effort sensitive customer demand differs the current paper from the existing literature.

The purpose of this study is to explore the interplay between the selection of selling formats of remanufactured products for a third-party remanufacturer (TPR) and the quality decision of an original equipment manufacturer (OEM).

This study considers a remanufacturing supply chain, where the OEM sells new products through a platform retailer, but the products remanufactured by the TPR can be sold via a direct or indirect channel. The authors model a Stackelberg game and explore the optimal quality decision of the OEM and selling format choice of the TPR.

The OEM's optimal decision depends mainly on consumers' discounted utility coefficient and cost-scale factor of remanufactured products. A higher consumers' valuation of the remanufactured product will not result in a higher retail price, but may lead to an increase in new product's sales. Given the cost-scale factor, the TPR prefers to sell directly no matter what the value of consumers' discounted utility coefficient is. An all-win situation is achieved with selling directly when consumers' discounted utility coefficient is sufficiently large.

These results provide some support to the operational strategies of the OEM and TPR.

This study firstly endogenizes the quality decision and combines the selling format selection of the TPR and the quality decision of the OEM to explore the interplay between these two important decisions.

This paper aims to introduce corporate social responsibility into the green supply chain and analyse the impact of different decision makers’ decision-making schemes on carbon emission reduction in the supply chain.

This study uses a two-stage low-carbon supply chain composed of a manufacturer and retailer as the research object. It uses the Stackelberg game model to analyse optimal carbon emission reduction and its influence under different decision-making modes.

Increased consumer green preferences and trust can improve the manufacturing enterprises’ carbon emission reduction rate. The carbon emission reduction rate decreases with increased green innovation costs. When green technology innovation costs remain constant, the greater the market capacity, the higher the carbon emission reduction rate. Market capacity has the most significant impact on the optimal carbon emission reduction rate without considering social responsibility decisions and has the least impact on the optimal carbon emission reduction rate while fully considering the social responsibility decision. To achieve decarbonisation production, the market capacity must be small, and when green innovation costs are high, it is the optimal choice without considering social responsibility. To achieve a higher level of carbon emission reduction, when the market capacity is low and the research and development cost is high or when the market capacity is large, it is the optimal choice.

The results provide scientific policy decisions and management significance for governments and enterprises in low-carbon subsidies and supply chain management. The findings also provide a basis for future theoretical research and enterprise practice.

Reverse logistics (RL) has become integral in modern supply chains, with many companies investing in circular economy (CE), a recuperative and effective industrial economy. The traditional linear model triggered many negative environmental consequences such as climate change, ocean pollution, loss of biodiversity and land degradation. The development of RL strategies that support the transition between RL to CE is crucial. The purpose of this paper is to connect RL with CE in the context of Industry 4.0 and develop a hierarchal structure to explore the relationship between RL and CE critical success factors in the context of Industry 4.0.

This study used both qualitative and quantitative approach. Literature review in collaboration with the Delphi method is used to identify and validate critical success factors. Then, the ISM-based model and MICMAC method were used to determine the relationship between CE and RL success factors and its driving and dependence power.

This study result shows that waste reduction, skilled employees and expert's involvement and top management commitment and support will provide guidelines and paths for implementing CE and RL, leading to the competitiveness of a firm.

The findings provide managerial insight, particularly useful to third-party logistics companies' managers who are looking to implement RL and CE, to help prioritize where to invest company resources to generate prime difference. Furthermore, this study also identified Industry 4.0 technologies, which would tackle top identified critical success factors within the hierarchical model such as block chain and digital platforms.

This paper contributes to the literature by exploring the connection between RL and CE in the context of Industry 4.0 that determines the critical success factors enabling sustainable inter-firm collaboration.

Considering the network externalities of online selling, this paper builds three different online direct selling models: manufacturer direct selling (MN model), network platform direct selling (NN model) and retailer direct selling (RN model). The optimal advertising and pricing decision and corporate profits under each selling model are investigated.

Combining the characteristics of online direct selling, this paper formulates direct selling models that are dominated by different companies as Stackelberg game models. Numerical analyses are carried out, along with the comparison of the equilibrium solutions for each model.

The authors' research shows that increasing network externalities is conducive to the development of enterprises. The network platform's profit is the lowest in the RN model and the highest in the NN one. The comparison of manufacturers' profits between the MN model and the NN model primarily depends on consumers' sensitivities for sales price and advertising promotion level. The manufacturer does not benefit from the RN model due to the lowest efficiency.

Coupled with three different online direct selling models and detailed analyses of the optimal solutions, this study has enriched the theoretical foundation of online direct selling. Moreover, this study extends the research of network externalities to the field of e-commerce, revealing the network externalities' influence on the decision-making of the e-supply chain.

Under the carbon tax policy, the authors examine the operational decisions of the low-carbon supply chain with the triple bottom line.

This paper uses the Stackelberg game theory to obtain the optimal wholesale prices, retail prices, sales quantities and carbon emissions in different cases, and investigates the effect of the carbon tax policy.

This study’s main results are as follows: (1) the optimal retail price of the centralized supply chain is the lowest, while that of the decentralized supply chain where the manufacturer undertakes the carbon emission reduction (CER) responsibility and the corporate social responsibility (CSR) is the highest under certain conditions. (2) The sales quantity when the retailer undertakes the CER responsibility and the CSR is the largest. (3) The supply chain obtains the highest profits when the retailer undertakes the CER responsibility and the CSR. (4) The environmental performance impact decreases with the carbon tax.

The results of this study can provide decision-making suggestions for low-carbon supply chains. Besides, this paper provides implications for the government to promote the low-carbon market.

Most of the existing studies only consider economic responsibility and social responsibility or only consider economic responsibility and environmental responsibility. This paper is the first study that examines the operational decisions of low-carbon supply chains with the triple bottom line under the carbon tax policy.

The aim of this study is to investigate the impact of integration capabilities on reverse supply chain (RSC) adoption and, consequently, RSCs' effectiveness. Thus, supply chain (SC) integration capabilities and their types in relation to internal, supplier and customer integration capabilities are investigated.

In this paper a quantitative survey was conducted with Malaysian manufacturers with a certified the International Organization for Standardization (ISO) 14001 environmental management system. The entire population was utilized through census sampling; 150 useable survey responses were received. The partial least squares technique was used for the data analysis.

The results indicate that internal integration improves external integration. In addition, supplier and customer integration have a positive direct effect on the adoption of RSC activities. Though internal integration has no significant direct effect on the adoption of RSC activities, it has an indirect impact through both supplier integrative capabilities and customer integrative capabilities.

The findings of this study suggest that the managers of manufacturers whose internal integrative capabilities are the base and whose SC integrative capabilities and external integrative capabilities are reinforcing SC integrative capabilities should adopt RSC activities.

The paper offers in-depth insight into this issue and has shed light on the ambiguities in the literature regarding the role of SC integration in RSC adoption.

Industry practice has shown that technology licensing has an important effect on the R&D cooperation between firms. Different licensing methods will significantly impact a supply chain member's cooperative and price R&D decisions. However, there is scant literature investigating the decision on technology licensing and its impact on a supply chain member's price and cooperative R&D decisions. To address this gap, the authors investigate the R&D cooperation and the technology licensing in a supply chain formed of an original equipment manufacturer (OEM), a contract manufacturer (CM), and a third-party manufacturer which will compete with the OEM when the technology licensing occurs.

The authors investigate two licensing patterns, royalty licensing, fixed fee licensing together with the no licensing, within the R&D cooperative supply chain by developing two three-stage and a two-stage Stackelberg models.

Compare to the no licensing strategy, technology licensing always benefits to the OEM and the society especially when the technology efficiency and the brand power of the third-party manufacturer are more significant; the royalty licensing benefits to the OEM more when the technology efficiency and the brand power of the third-party manufacturer are higher; the fixed fee licensing benefits to the OEM more when the technology efficiency and the brand power of the third-party manufacturer are lower.

The royalty licensing is more effective for mitigating price competition intensity and helping firms to maintain higher sales margins; the fixed fee licensing induces firms' lower sales margins but increases the firms' sales quantities; in most cases, the fixed fee licensing is optimal from the perspectives of consumer and society, however, the CM's investment intention to the R&D technology with the fixed fee licensing is lower.

So far, different licensing models under the R&D cooperation have not been investigated, and the authors propose two three-stage Stackelberg models with considering the competition caused by technology licensing under the R&D cooperation to deal with the cooperative R&D and technology licensing issues.

As independent travel has become increasingly popular in recent years, factors influencing users’ attitudes and behaviors should be explored. Besides, the rise of video platforms like YouTube, Bilibili and TikTok has led to the flourishing of user generated content (UGC), among which travel vlogs have become convenient and essential references for tourists before and while they travel on their own.

This research used quantitative analysis through a survey designed for young people, as most vlog viewers are in those age groups, to explore the attitudes and perceptions of vlog preference, attitudes and cognizance of travel vlogs among different gender, guided by the decision-making theory and preference theory with 455 participants.

Survey results showed that both genders have common choices regarding travel vlog preference, attitudes, sharing and cognizance. Yet, gender differences appear in some cognition of travel vlogs and specific preferences, such as information searching habits, trusty travel and information sources.

Existing studies focus on the influence of platforms on users, but scant studies focus on user perceptions of vlogs as a new information carrier for young people in East Asia, especially regarding gender differences, which is crucial in media-based marketing. This research provides practical suggestions to marketers and vloggers to attract and engage different genders of young people and theoretical implications on decision and preference theories.