In this paper, a combined contract composed of option and cost sharing is proposed to investigate coordination and risk‐sharing issues of the supply chain consisting of a dominant retailer and a risk‐averse manufacturer. Demand faced by the retailer is stochastic in nature and dependent on marketing effort. We adopt the conditional value‐at‐risk (CVaR) criterion to model risk aversion of the manufacturer, and derive the optimal strategy for each member with a Stackelberg game in which the retailer acts as the leader. It is verified that the combined contract can coordinate the supply chain and achieve Pareto‐improvement. Moreover, the dominant retailer can allocate the system‐wide profit arbitrarily only by option price in the premise of coordination. It is worth mentioning that coordination of the supply chain is reachable only when the manufacturer is low in risk aversion, and the manufacturer's risk aversion is a significant element for contract design and profit allocation.

This paper addresses a vendor-managed inventory (VMI) supply chain with a loss-averse manufacturer and a risk-neutral retailer. Market demand faced by the retailer is stochastic and dependent on product quality level and marketing effort level. We propose a combined contract composed of option and cost-sharing to investigate coordination and profit allocation issues of the supply chain. To model loss aversion of the manufacturer, we employ multiple mental accounts and apply the utility function to upside and downside potentials of manufacturer's production decision separately. We derive the optimal strategy for each member with a Stackelberg game in which the retailer acts as the leader. It is proved that both coordination of the supply chain and Pareto-improvement can be achieved synchronously by the combined contract. In the premise of coordination, the system-wide profit can be allocated arbitrarily only by option price. Through negotiation, the retailer and the manufacturer just need to confirm an appropriate option price to obtain that neither of them becomes worse off. We also find that the manufacturer's loss aversion is a significant element for contract design and profit allocation, and the manufacturer could benefit from its own loss aversion behavior under certain condition.

With the rising environmental concerns among consumers all over the world, sustainability has received considerable attention, and numerous enterprises are adopting various practices such as investing in energy-saving to improve sustainability in supply chains. However, many previous researches always assume that decision makers are perfectly rational and neglect the behavioral concerns of decision makers. This paper considers a two-stage sustainable supply chain with behavioral concerns in order to develop more realistic models, and mainly focuses on the energy-saving and pricing decisions in the decentralized system, as well as how to improve energy-saving level and profits. We develop decentralized decision-making models under two types of behavioral concerns: fairness concern and risk aversion, and derive the optimal strategy for each member with a Stackelberg game in which the manufacturer acts as the leader. The effect of the behavioral concerns on the optimal decisions and corresponding profits is discussed in detail. Theoretical analysis verified by numerical experiments shows that the fairness behavior always causes a negative effect on the manufacturer, total supply chain, and energy conservation, while it could benefit the retailer in profits. The risk aversion behavior always benefits the manufacturer, total supply chain, and energy conservation, whereas it could make the retailer suffer. Note that both the optimal energy-saving level and corresponding profit of the total supply chain under two types of behavioral concerns are lower than that in the centralized system, thereby we propose a revenue-cost-sharing contract to coordinate the supply chain, under which both the manufacturer and the retailer can achieve a win-win outcome and the energy-saving level can be improved. In addition, some managerial implications through our analytical and numerical results are summarized in this paper.

This paper deals with a one-period two-stage supply chain, in which a loss-averse retailer facing stochastic demand orders products from a risk-neutral supplier subject to yield uncertainty. Marketing effort exerted by the retailer is employed to enhance the final market demand. We first establish a performance benchmark, and show that the wholesale price contract fails to coordinate the supply chain due to the effects of double marginalization and loss aversion. Then we propose a revenue-cost-sharing contract in order to achieve supply chain coordination. It is verified that a properly designed revenue-cost-sharing contract can achieve perfect coordination and a win-win outcome synchronously. Our results reveal that it is simple to implement and arbitrarily allocate the total channel profit between the retailer and the supplier. In addition, we examine the effect of the retailer's loss aversion degree on contract parameters and profit allocation, and we show that both the retailer and the supplier can benefit from marketing effort.

With the growth of people’s environmental awareness and the encouragement of government policies, the use of electric vehicles in logistics distribution is gradually increasing. In order to solve the dual demand of customers’ simultaneous pick-up and delivery in the “last kilometer logistics”, an electric vehicle routing problem with simultaneous pick-up and delivery and time window (EVRPSPDTW) is considered from the perspective of multi-objective distribution in this paper. Firstly, a decision-making model based on distribution cost and power consumption function is established. In this model, distribution cost includes transportation cost, vehicle use cost, penalty cost of not arriving on time and charging cost. Power consumption function is the energy loss caused by air resistance, tire rolling friction and transmission system. Secondly, a multi-objective genetic algorithm (NSGA-II) optimization solution with fast nondominated ranking and elite strategy is designed, and in view of the shortcomings of traditional NSGA-II, it is proposed to complete population initialization through greedy algorithm and random rules, introduce adaptive cross-mutation strategy in the chromosome crossing and mutation stage, and design three different neighborhood operators in mutation operation based on variant fitness function. Finally, the sensitivity analysis of traffic congestion coefficient further proves the effectiveness of the proposed model and the improved algorithm.