In real-world operations, firms implement different combinations of strategies for quality disclosure and remanufacturing. However, it is unclear how these two strategies interact with each other. Motivated by real practice in industries such as automobile and electronics, this paper investigates the manufacturer's quality disclosure strategy when remanufacturing is conducted by either itself or a third-party remanufacturer. We construct analytical models to integrate quality disclosure into remanufacturing operations and consider two types of remanufacturing, namely manufacturer remanufacturing (MR) and third-party remanufacturing (TR). Several interesting results are derived in our work: (i) With moderate remanufacturing savings, the manufacturer should induce the partial (full) remanufacturing strategy with disclosure (no disclosure) under both MR and TR scenarios. This indicates that the manufacturer could use the quality disclosure strategy to coordinate (affect) its remanufacturing (the third-party remanufacturer's) operations strategy under MR (TR) scenario. (ii) MR may either enhance or reduce the manufacturer's disclosure incentive, while TR always dampens it. (iii) Compared with MR, interestingly, from both ex-post and ex-ante perspectives, the manufacturer may prefer no remanufacturing (NR), even if the cost associated with remanufacturing is negligible. By contrast, compared with NR, the manufacturer will ex-post welcome the third-party remanufacturer to enter the market.

Nowadays, many two-sided platforms are actively launching new services beyond their main service to reach a broader range of consumers (e.g., Amap adding local lifestyle services in addition to its navigation service). As users migrate across different services, the original two-sided pricing mechanisms are altered due to network effects. Furthermore, different service introduction strategies adopted by competing platforms also reshape the competitive landscape. In this article, we develop a game-theoretical model to examine the optimal pricing strategies of two competing platforms when introducing new services. We theoretically show that when platforms introduce new services, they typically reduce consumer-side fees or even offer subsidies. However, on the provider side, whether platforms adjust their pricing strategies depends on the service introduction strategies of their competitors. Counterintuitively, the profitability of new services does not depend solely on their development costs; the intensity of market competition also leads platforms to adopt different equilibrium strategies. When competition is intense, platforms may fall into a "prisoner's dilemma" when introducing new services. In contrast, when competition is weak, introducing new services is more likely to result in a win-win outcome. Finally, we show that service complementarity increases the likelihood of a prisoner's dilemma but does not affect the win-win outcome. We further extend the analysis by endogenizing the user conversion rate and introducing asymmetric consumer base utility, and show that our main findings remain robust.

This study examines how artificial intelligence (AI) adoption by manufacturers or retailers impacts operational decisions and expected profits in a two-tier supply chain. Through the newsvendor framework, we analyze three scenarios: no adoption (N), manufacturer adoption (MA), and retailer adoption (RA). Our findings indicate that AI adoption contributes to enhancing service levels and order quantities. However, the adopting party does not always secure higher profits, as benefits are partially transferred to the non-adopting counterpart through free-riding effects. By comparison, we observe that manufacturer adoption is preferable when its cost-saving advantages exceed the demand-enhancing advantages of retailer adoption, and vice versa. Furthermore, we explore the impact of stockout on the effectiveness of AI adoption. Our results show that optimal order quantities increase with the intelligence level of AI, while the presence of stockout costs weakens this relationship. Interestingly, stockout costs reduce the positive effect of AI adoption on manufacturers’ profits but amplify its benefits for retailers. Finally, we examine the scenario where both the manufacturer and the retailer adopt AI (MRA) and find that simultaneous adoption is not necessarily a better choice.

Artificial intelligence (AI) based training recycled data was applied in remanufacturing to minimize the screening and inspection misses. We focus on the diffusion of green practices and intelligent technology when AI is applied to remanufacturing supply chains and how to control. A remanufacturing supply chain network is constructed based on epidemic models with a three-stage game, where an AI provider activates, then firms produce, and consumers purchase. This model captures the firms’ learning and consumers’ imitation, and reveals a seesaw effect between the self-driven power from AI and the out-driven power from the AI provider. We show that appropriately leveraging influential “big customers” with high hyperdegree and configuring network connectivity can promote greening and intelligence diffusion. Interestingly, contrary to traditional wisdom, higher data efficiency and accuracy of AI do not always accelerate diffusion, highlighting the potential mismatch between technological performance and adoption. Based on 16 parameter experiments, each involving over 2000 data instances with 100 replicates, simulations indicate that incomplete diffusion is general. However, adjusting these factors increase the greening and intelligence diffusion level to up to 94.73% and 81.50%, while inspection misses are reduced by 38.11% compared to the baseline. These results imply that more firms are induced to remanufacture and adopt AI-enabled inspection, so as to improve operational efficiency and reduce waste. Furthermore, neither the remanufacturer nor the third-party technical vendor is universally dominant as an AI provider, as their motivations to activate AI adoption vary across industry contexts. Overall, we indicate that promoting green practices and smart technologies depends on the integration of network structure, product design, and technical attributes, rather than relying solely on technical performance or provider identity.

Disruptions caused by many factors, such as epidemics and policy uncertainties, affect the recycling of used products. This paper investigates a closed-loop supply chain where a remanufacturer collects from customers (online channel) directly or a third party (offline channel). When collection channel disruptions happen, the remanufacturer can close the disrupted channel or implement a delay strategy. The results show that no matter with or without the delay strategy, disruptions are always harmful, and the online disruption causes more damage than the offline disruption. Furthermore, the delay strategy is always better for the remanufacturer. However, with the delay strategy and customer transferring, the online disruption may damage less, and we surprisingly find that the online disruption may increase recycled quantity and firms’ profits when with high transfer ratio; moreover, the complete online disruption may perform better than partial one; finally, the hybrid remanufacturing strategy can alleviate the damage of offline disruption.

IntroductionIn the e-commerce supply chain, many risk-averse suppliers face the dilemma of capital constraints. Bank financing helps to alleviate these financing difficulties, and blockchain trust mechanisms can optimize bank financing strategies.MethodsTo address the issue of capital constraints for suppliers, based on the two operating modes of Consignment and Direct Selling in the e-commerce supply chain, using the Stackelberg game, considering the company’s risk-averse behavior and consumers’ green preferences, a game model is constructed to explore the impact of factors such as blockchain, risk aversion, product greenness, guarantee interest rates, and information verification efforts on bank financing strategies.Results and discussionWhen the blockchain technology is adopted within a certain threshold, the supplier can obtain higher financing income by adopting consideration than Direct Selling. Compared with the Direct Selling mode, the blockchain trust mechanism under consideration mode can play a better role and improve the financing efficiency of suppliers. The financing efficiency of suppliers will also decrease with the increase of risk aversion coefficient, and the impact of risk aversion on suppliers will be greater in the case of blockchain, but the trust of blockchain will increase with the increase of risk aversion coefficient. Product greenness will increase the sales price of e-commerce supply chain under consideration mode, and improving product greenness will help improve enterprise cash flow. However, under the Direct Selling mode, the impact on the price is not great, and the impact on the financing strategy will be different. Although the guaranteed interest rate will increase the financing cost, it will make banks more willing to provide financing for suppliers with financial constraints. In practice, managers should comprehensively consider the balance between guaranteed interest rate and financing return. Information verification efforts will increase product greenness and green preference coefficient, and the improvement of information transparency will make e-commerce platforms more willing to provide guarantees for suppliers. This study is expected to provide decision-making references for the managers of e-commerce supply chain.

Product ratings are so important that sellers need to focus on rating rules, i.e., how ratings are calculated by e-commerce platforms. However, limited studies have examined the impact of these rules on the review system design. Using programming codes, we simulate consumers' online shopping activities and the functioning of the review system. Through an indicator system, we compare the performance of the dynamic rating rule, which displays the mean of recent ratings in one rating cycle, and the traditional rating rule, which displays the average of all posted ratings. Results show that the dynamic rating rule always performs better on competition fairness. This rule also usually displays higher values of ratings and diminishes the disconfirmation effect, although it generates a lower number of reviews. Interestingly, these results may be reversed for search products. This study offers guidance to e-commerce platforms on how to manipulate the review system by adapting rating rules.

As the second-hand market continues to grow, many retail platforms initially specializing in selling new products (e.g., Amazon, JD, and Walmart.com) have begun allowing refurbishers to directly sell refurbished goods on their platforms and gain additional profits. The platform can provide blockchain certification services for refurbishers to eliminate consumers’ concerns about quality. In contrast to the existing literature, which primarily examines the introduction of blockchain technology from the perspective of cost factors, this paper investigates the platform’s blockchain introduction in the context of competition between the new and refurbished products and its impacts on the manufacturer’s and the refurbisher’s profitability. Motivated by practices, two prevalent selling modes for the new product are considered: reselling mode (R) and agency selling mode (A). Even without considering the cost of blockchain, we find that the platform may have no incentive to introduce blockchain under both modes because it could trigger a severe cannibalization problem or an excessively high price for the refurbished product. The refurbisher (manufacturer) benefits with (without) blockchain under mode R, but this result occurs under mode A only when the blockchain service fee is low. We also discuss the welfare and environmental implications of blockchain. We find that the selling modes may modify the environmental implications of blockchain, but not the welfare implications of blockchain.

We explore how financial constraints affect the sustainability of product market collusion in a bank-financed oligopoly, where firms operate within an imperfect credit market. Our analysis uncovers a non-monotonic relationship between the sustainability of collusion and the level of financial constraints, using a general demand function. Notably, collusion tends to be more sustainable when firms experience low to moderate financial constraints, as opposed to having no financial constraints at all. However, when firms are under complete financial constraints, the sustainability of collusion may decrease compared to situations without financial constraints. These findings hold true for both Cournot and Bertrand competition models in the product market.

As the online shopping user base continues to grow rapidly, livestream e-commerce has emerged as a pivotal commercial phenomenon. However, consumers’ impulse purchase intentions in this environment are influenced by numerous interrelated factors, and the underlying mechanisms remain complex. To address the limitations of traditional approaches in modeling nonlinear relationships and hierarchical structures, this study introduces an integrated DEMATEL-AISM approach tailored for the livestream e-commerce context. The λ-intercept method is applied to simplify the system structure and highlight key influencing factors. Based on prior literature, we designed and distributed structured questionnaires to 558 consumers and industry experts, followed by in-depth interviews with five domain experts. Through this process, an indicator system was developed encompassing 15 factors across three dimensions: product, consumer, and livestream room. Using DEMATEL-AISM, we conducted a causal analysis of these factors. The results reveal that: (1) discount intensity, livestream promotional frameworks, and time pressure are the three most critical factors influencing impulse purchase intentions; (2) product monetary value and design features act as fundamental drivers; and (3) consumer upward and downward anticipated regret, perceived product quality, perceived product scarcity, and perceived streamer’s product knowledge have direct impacts on impulse purchase. By identifying these key factors and revealing their interconnections, this study offers strategic, evidence-based recommendations for enhancing consumer engagement and profitability in livestream e-commerce. The proposed DEMATEL-AISM also provides a novel and effective methodological contribution for analyzing the complex influencing factors of impulse purchase intentions in the e-commerce environment.

More firms are adopting artificial intelligence (AI) to assist agricultural decision-making, but it is unclear whether and how AI can mitigate risk in agricultural supply chain. Driven by this question, we construct a multi-period and multi-layer agricultural supply chain network equilibrium model, where the theory of variational inequalities is utilized as the methodology. In this model, farmers make decisions at planting and harvest stages under yield uncertainty, and processors and retailers have to cope with potential disruptions through contingency measures. AI is introduced into supporting planting decision, and players’ interactions and risk cascade effects are incorporated. First, we find that AI enables farmers to shift from short-sightedness to a forward-looking perspective, which effectively stabilizes supply and price fluctuations, thereby mitigating risks. Second, AI makes the supply chain decisions for intertemporal products closer to those for non-intertemporal products, benefiting farmers, firms, and consumers. Third, AI can mitigate supply chain risks for non-intertemporal and low substitutable agricultural products more effectively than for other types of products. Finally, AI can also be a double-edged sword in specific scenarios, but the complementarity between AI and cold chain sharing enhances the efficiency of agricultural supply chains during unexpected disruptions. The findings provide valuable insights for the AI providers and managers to select the optimal agricultural products and develop incentive strategies.

The application of artificial intelligence (AI) in the e-commerce platform supply chain has profoundly affected the decision-making and sales format selection of supply chain members. This study examines the impact of AI on the e-commerce platform supply chain and analyzes how platform's commission rate and AI application cost jointly affect equilibrium sales formats. We initially use game theory method to establish a benchmark model without AI, and then construct two sales models that the application of AI will eliminate or reduce consumer returns. Then, we compare the sales models using AI with the benchmark model, analyze the impact of applying AI on optimal decision-making, profit, and equilibrium sales formats. Results indicate that the profitability of platform applying AI primarily depends on its application cost, however, the application of AI technology is consistently profitable for the supplier in the agency sale format. Moreover, when the platform's commission rate is low, no equilibrium format exists. With moderate to high commission rates, the agency sale format reaches the equilibrium. At very high or extremely high commission rates, the resale format becomes the equilibrium. Lastly, the evolution and development of AI will benefit supply chain members in the resale format, while may not necessarily bring higher platform's profit in the agency sale format. Under extension to the case with two suppliers, similar results of sales format selection demonstrate robustness of our proposed model.

Prior research mostly focuses on traditional trade-in programs where there is no up-front fee. Motivated by recent industrial practice that firms implement quality differentiated trade-in programs with up-front fees (TF programs), we investigate three types of TF programs: only recycling low-quality old products, only recycling high-quality old products, and recycling low- and high-quality old products. Compared with the traditional trade-in model, the firm sets a lower selling price in TF models. Specifically, when the consumers’ value discount for used products is low, the selling price in the TF model that recycles low- and high-quality old products is the lowest; when the value discount is high, the selling price in the TF models that recycles low- and high-quality old products or only recycle low-quality old products may be the lowest. Interestingly, we find that all types of TF programs lead to lower trade-in rebates for replacement consumers than the traditional trade-in program. The firm with the TF program that recycles low- and high-quality products serves most consumers and charges the highest recycling quantity. Finally, we extend the models and verify the robustness of our main conclusions.

Previous literature has discussed recycling strategy and government intervention in a closed-loop supply chain; however, differential recycling strategies considering the bounded rationality of decision-makers are unexplored. This study establishes evolutionary game models with a two-dimensional dynamical system to analyze the long-term recycling behavior of enterprises in a supply chain, which consists of manufacturers and retailers. The evolutionarily stable strategy (ESS) of enterprises is derived, and the government intervention is investigated. The enterprises choose from two recycling strategies: (1) ordinary recycling strategy, i.e., only recycling high-quality waste electrical and electronic equipment (WEEE); (2) differentiated recycling strategy, i.e., recycling high- and low-quality WEEE. The results show that when the recycling difficulty of enterprises is at different thresholds, the system will evolve into a different ESS. Moreover, the government's intervention is effective. If government subsidies and penalties meet a certain range, the enterprises without recycling qualifications will choose the ordinary recycling strategy, while the enterprises with recycling qualifications will choose the differentiated recycling strategy. Finally, when enterprises make decisions on price and recycling rate, the recycling difficulty and consumer environmental awareness will affect the decisions and profits of enterprises. However, only government intervention can effectively affect the ESS.

This paper aims to explore the role of blockchain in recycling when consumers have quality concerns about remanufactured products. Using the game-theoretical method, we analyze recycling and differential pricing strategies in closed-loop supply chains when a third party conducts the recycling activity. We further study the impacts of recycling channels. Our findings demonstrate that blockchain can increase the retail prices of new and remanufactured products and the profit of the third party when the blockchain usage fee is low. Otherwise, the manufacturer and the retailer will benefit from the use of blockchain. Besides, our study shows that when the blockchain usage fee is low, or the degree of quality information disclosure of remanufactured products is low, the application of blockchain can increase social welfare. Finally, we find blockchain can raise the collection rate, which is independent of the recycling channels.

Although some prior studies have examined the optimal trade-in providers in supply chains, the impacts of alternative online selling models like reselling and agency selling that are widely adopted in the e-commerce environment are under-explored. Traditionally, both the manufacturer and retailer have incentives to offer trade-in programs to consumers in a supply chain. However, this is no longer true when an agency selling model is implemented. In this paper, we investigate the equilibrium “trade-in provider” under the two selling models respectively in a stylized e-commerce single-manufacturer single-e-tailer supply chain. Our findings show that different selling models do have distinct influences on the two firms’ preferences of who should provide the trade-in program. Particularly, under the reselling model, there is always a conflict between the two firms regarding who should provide trade-ins, which is consistent with the findings in related literature; however, under the agency selling model, there are some win-win cases under which the two firms possess consistent preferences on the trade-in format. Furthermore, the “boxed pigs game” equilibrium may appear under agency selling, where either of the two firms has to provide the trade-in program, although this is not their most preferred trade-in format. The robustness of our main results has been well verified by extending our study to consider (i) the case where the e-tailer can be delegated to implement trade-ins, (ii) the case where the e-tailer is the first-mover in determining whether to provide trade-ins, and (iii) the reselling and agency selling models co-exist.

This study investigates a sustainable three-echelon supply chain structure (supplier-retailer-customer) from the retailer's perspective for a perishable product where: (1) the retailer pays the purchase cost to the supplier in the form of an advance-cash-credit (ACC) payment while granting their customers a partial credit, (2) the supplier offers a price discount to the retailer to facilitate sales, (3) the deterioration rate of items increases over time due to an expiration date, (4) the customer is allowed a partial delay in orders with a fixed market tolerance period, and (5) the supply chain management (SCM) structure takes consideration of government cap-and-trade regulation. This paper intends to establish the retailer's optimum cycle time, selling price, and inventory period simultaneously to maximize his/her total profit. An efficient algorithm has been constructed to find optimal solutions. Two examples have been presented to validate the proposed model. Furthermore, a comparative analysis of the four different payment methods (upstream ACC, advance, cash, credit, and downstream partial credit payments) has been carried out and sensitivity analyses have been performed to gain managerial insights. Our numerical results reveal that with the increase in the discount rate, the selling price reduces significantly, however, the retailer's profit increases tremendously. The reason for this phenomenon is that a higher discount rate can lead to a higher profit for the retailer, hence, the retailer may set a lower price to increase sales. Many retailers desire a high discount rate, which is associated with the upstream advance and downstream partial credit payment; however, the computational results show that this payment method causes significant damage to the environment. Hence, two payment methods (upstream ACC, credit, and downstream partial credit payments) are recommended. The reason is that these two payment types bring more profits to the retailer and result in less damage to the environment.

The rise of live streaming selling has brought a revolution to the retail industry. The supply chain with platform-based retailing is faced with choice of sales formats and marketing decisions. We establish live streaming selling models with two sales formats of resale and agency sale, and three pricing strategies of same high, same low and differential strategies (HH, LL and D). We further explore the impacts of con-sumer returns, as they are typically higher in live streaming selling. Conventional wisdom believes that agency sale format can reduce double marginalization and benefit both the platform and the supplier, which cannot be achieved in resale format. Interestingly, our study shows that resale format may be-come a better choice for both the platform and the supplier when considering the impacts of consumer returns. This result holds in pricing strategies HH and D, where the key driver of sales format choice in strategy HH is commission rate while it is consumer's low valuation in strategy D. In strategy LL, resale is the supplier's preferred format and agency sale is better for the platform. Furthermore, we find with agency sale format, equilibrium pricing strategies HH and LL always exist; while with the resale format, equilibrium strategy HH exists only when considering consumer returns. Finally, we discuss the hybrid sales formats with and without price competition, and extend our models to encompass more scenarios.(c) 2022 Elsevier B.V. All rights reserved.