Research on Supply Chain Coordination and Profit Allocation Based on Altruistic Principal under Bilateral Asymmetric Information

Abstract

To ensure supply chain coordination and equitable profit allocation when there is bilateral asymmetric information, a supply chain consisting of one manufacturer with private manufacturing cost information and one retailer with private selling cost information is considered. A bilateral adverse selection model is established with a virtual altruistic principal as the coordination subject, for which the supply chain coordination conditions and an allocation rule for the supply chain surplus are then given. It was found that contract coordination depended on the costs and risk rates of both parties and market demand; that is, the lower the costs and the risk rate, the easier the supply chain coordination. Second, the trading volume distortion degree was positively correlated with production cost, sales cost, and price sensitivity and negatively correlated with the market environment parameter. Third, the allocation proportion for the supply chain surplus was determined. Finally, under a specific cost distribution assumption, a numerical example was given to simulate the contract execution and analyze the relationships between costs and profit.

Operational Strategy for Low‐Carbon Supply Chain under Asymmetric Information of Fairness Concerns

“…Finally, some explored bilateral asymmetric information. For example, the manufacturer privately knew the information of his production cost, and the retailer privately knew the information of market demand as discussed by Wang et al [30] or her selling cost by Gu et al [31]. Mobini et al [32] investigated the case, and both the processing cost of the retailer and market demand were asymmetric information.…”

Quality Improvement Incentive Strategy in Agricultural Products Supply Chain Under Social Preference

“…Dong et al (2017) proved that retailer was more inclined to cooperate with altruistic manufacturer under large demand. Gu et al (2018) established a bilateral adverse selection model, and studied the impact of altruistic reciprocity on the coordination of supply chain and the profit distribution. Xu and Wang (2018) established a strategic model of competition and cooperation based on online and offline retail channels under altruistic reciprocity, which can improve the supply chain channel efficiency.…”

Multimodal Transport Network Optimization Considering Safety Stock under Real-Time Information

“…With the update of demand information, enterprises can effectively deal with the mismatch between supply and demand through the multimodal transport logistics supply network, which can reduce inventory backlog and improve customer service level [4][5][6][7][8]. The imbalance of inventory control caused by mismatch between supply and demand can be handled by means of emergency ordering or by multimodal transport from the transshipment center [9][10][11][12][13][14][15]. The problem of emergency ordering is that the adjustment of production resources and the compression of the construction period will inevitably lead to high costs [16][17][18][19][20].…”

“…Therefore, more and more enterprises tend to adopt multimodal transport to deal with the problem of supply and demand mismatch between regions [21]. Previous studies showed the significance of multimodal transport problems [1][2][3][4][5][6][7][8][9][10][11][12][13][14][15][16][17][18][19][20] and solutions [21] that can be improved from different perspectives. For instance, Mengliang et al [1], Todd et al [2], and Pałaszewskatkacz et al [3] showed that demand information cannot be ignored; references [4][5][6][7][8] found the importance of requirements updates; researchers [9][10][11][12][13][14][15] emphasized that safety stock should be considered in multimodal transport; costs control should be considered in multimodal transportation optimization from literatures [16][17][18][19][20]; and Zhang et al [21] provided a good method reference for multimodal transport network optimization problem.…”