The recycling and remanufacturing of e-waste is linked to a worldwide emphasis on the establishment and implementation of Extended Producer Responsibility system (ERP), which has become an important problem in the process of cycling economy. Meanwhile, with the development and expansion of large-scale retail enterprises, the power structure of supply chain channels is showing a tendency towards diversity as well. However, few studies on closed-loop supply chains (CLSC) have considered both recycling modes and channel power structures. We aim to explore the influence of different recycling modes and channel power structures on the optimal decisions and performance of a closed-loop supply chain (CLSC), considering three recycling channels including manufacturer recycling, retailer recycling and hybrid recycling of retailer and manufacturer and two dominant modes including manufacturer-led and retailer-led. We construct six closed-loop supply chain models under different combinations of three recycling channels and two dominant modes. We analyze the effect of different recycling channels on company decision-making under the same dominant mode, whether participating in recycling has an impact on company decision-making under different dominant modes, and the effect on supply chain members and supply chain system under different dominant modes and recycling channels. The results show that the hybrid recycling strategy is always optimal for both supply chain members; the sub-optimal recycling strategies are both recycled by the subordinate enterprise, and the worst recycling strategies are both recycled by the leading enterprise. Moreover, it is always the worst strategy for manufacturer to participate in a closed-loop supply chain dominated by retailer and recycled by retailer; participating in a closed-loop supply chain dominated by manufacturer and recycled by manufacturer is always the worst strategy for retailer. From a system point of view, system efficiency is the highest under hybrid recycling, and system efficiency is the lowest if leading company recycles separately.

Data envelopment analysis (DEA) assumes that data are continuous. However, there are situations where data are integers and bounded. For example, in basketball games, the total number of points that a player has scored is an integer and cannot exceed three times of the number of point field goals that a player has attempted. Without modelling the correct data type, the DEA results can be biased and erroneous. The current paper applies a bounded integer DEA model to evaluating the performance of National Basketball Association (NBA) players when bounded integer data exist. As a result, we correctly capture the data type. The current study also develops a super-efficiency measure under the bounded integer data. The bounded integer data problem is illustrated with data involving a set of NBA shooting guards in the 2013–2014 season.

This paper explores two Omnichannel retail models consisted of one online platform and one brick-and-mortar store under different power structures considering cost-sharing mechanisms. In retail supply chain dominated by the online platform and brick-and-mortar store, respectively, under a “Buy online and pick up in store” strategy, the influences of the cost-sharing ratio and the proportion of traditional consumers on pricing and service decisions, the demands of various groups of consumers, and the performance of the retail system have been examined. In addition, the results of decision-making and profitabilities of retailers under different power structures have also been considered. The key findings show that the optimal price and service level first increase and then decrease with the cost-sharing ratio in a retail system dominated by the online platform. In contrast, the price and service level increase with the cost-sharing ratio only when the proportion of traditional consumers is relatively large in a retail system dominated by brick-and-mortar store. The symmetry demand increases as the scale of traditional consumers shrinks when the cost-sharing ratio is relatively large in a retail system dominated by the online system. At the same time, it only increases when the cost-sharing ratio is in the range of $\left(5/8,5/6\right)$ in a retail system dominated by the brick-and-mortar store. No matter what the power structure is, the profit of the retail system always first increases and then decreases with the proportion of traditional consumers. Additionally, when the cost-sharing ratio and the proportion of traditional consumers are relatively small, the total demand in the retail system dominated by the online platform is higher than that in the retail system dominated by the brick-and-mortar store. The total profit is larger in the online platform-dominated retail system than that in the brick-and-mortar store-dominated retail system when the cost-sharing ratio is relatively high. However, when the cost-sharing ratio is relatively low, the profitability of the brick-and-mortar store-dominated retail system is stronger.