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Motivated by the industrial practice that the giant E-commerce platforms are well motivated to engage in offering the extended warranty service, this paper investigates the optimal extended warranty provision with a platform supply chain. Depending on who acts as the extended warranty underwriter with the two online channel modes (i.e., the online agency mode or the online reselling mode), several different extended warranty scenarios are hence formulated, based on which we apply Stackelberg game to address the equilibria. With the analytical studies, our results show several important and interesting insights. For example, but not limited to, it is found that: (a) the dynamics of the optimal extended warranty strategy is largely different in response to various combinations of the warranty underwriters and the online channel modes; (b) the agent, who takes the ownership over the product (i.e., the manufacturer with the online agency mode and the platform with the online reselling mode), acts more responsively in providing the extended warranty service across the two online channel modes; (c) offering the pricing discount is an important intermediary that affects the Pareto improvement zone benefiting the two individuals in this platform supply chain; (d) the specific extended warranty strategies that the warranty underwriter adopts across two online channel modes induce a significant implication for selecting the optimal online channel modes for both warranty underwriters. These results derived in our paper shed lights for the platform supply chain practice on who and when to offer the extended warranty service. • Explore optimal EW service provision with an E-commerce platform supply chain. • Reveal dynamics of the optimal EW strategy in response to various channel modes and warranty underwriters. • Examine who is better off by offing the extended warranty with two different online channel modes. • Examine the best online channel mode for different warranty underwriters. [ABSTRACT FROM AUTHOR]

• we price differentially by considering consumers' preference for remanufactured and new products. • we develop the models with or without fairness concern to explore its impact on decision-making. • We incorporate a relative fairness reference point into the manufacturer's utility function and find the manufacturer's fairness concern behaviour to punish the e-platform is detrimental to cultivating a remanufactured product consumer market. • A new contract of "dual-revenue and service-cost sharing" can effectively eliminate the efficiency loss of the two decentralized models. The e-commerce market expands rapidly, and manufacturers sell remanufactured and new products online, making e-commerce closed-loop supply chains face product differential pricing and follower firms' unfair psychology due to the large profit gap between system members. Therefore, we price differentially by considering consumers' preference for remanufactured and new products and develop a centralized model and two decentralized models with or without fairness concern to explore its impact on decision-making. We show that consumers' higher preference for the remanufactured product is conducive to the two products' price and the remanufactured product's sales, then the sensitivity analysis shows that the higher preference positively affects system operation. We next incorporate a relative fairness reference point into the manufacturer's utility function and find the manufacturer's fairness concern behaviour to punish the e-platform is detrimental to cultivating a remanufactured product consumer market and causes the loss of its profits to be greater than that of the e-platform's profit. Additionally, a new contract of "dual-revenue and service-cost sharing" can effectively eliminate the efficiency loss of the two decentralized models. Our paper provides theoretical contributions to product pricing, the setting of a utility function with fairness concern, and the design of dual coordination mechanism. [ABSTRACT FROM AUTHOR]

• A novel delivery-driven intralogistics synchronization problem is proposed. • The model seeks a tradeoff between manual picking and robotic sorting operations with given delivery requirements. • The proposed synchronized solutions are consistently superior to the sequential solutions under various scenarios. This paper treats intralogistics processing in a typical robotic forward-reserve e-commerce warehouse involving a reserve area with manual order-picking operations and a forward area with robotic parts-to-picker order sorting operations. It is critical to synchronize intralogistics operations between the two areas considering delivery requirements to optimize the performance in terms of makespan and costs. This challenge is formulated as a delivery-driven intralogistics synchronization (DDIS) problem. This paper develops a tailored variable neighborhood search solution method. A series of comprehensive numerical experiments under various scenarios show the superiority and stability of the DDIS as benchmarked with sequential approaches. A substantial reduction can be achieved in both makespan and forward area size, indicating significantly improved intralogistics operational efficiency and space utilization. Managerial insights are also discussed for specific action plans regarding the market size, the labor force, and the trolley configuration. [ABSTRACT FROM AUTHOR]

• We study the E-commerce Shipping Problem where orders with deadlines must be shipped. • The retailer can enter the supply chain of a service provider at various levels. • The retailer must make consolidation decisions at each period to ship orders. • We model and solve the static and dynamic cases of this problem. • We develop and compare four shipping policies for the dynamic case. We consider an e-commerce retailer who must ship orders from a warehouse to a set of customers with delivery deadlines. As is often the case, the retailer uses a third-party service provider to ensure its distribution. The retailer can enter the supply chain of the service provider at various levels. Entering it at a higher level entails lower sorting costs for the retailer, but higher delivery costs, and longer delivery times. The customer orders arrive at various moments over a rolling planning horizon. This means that the retailer must also make consolidation decisions. We model and solve the static and dynamic cases of this problem. The static case is modeled as an integer linear program and solved by CPLEX. We develop and compare four shipping policies for the dynamic case. Extensive computational results based on real location data from California and Texas are reported. [ABSTRACT FROM AUTHOR]