Study On Sourcing Decision Models Considering The Supply Chain Members' Psychological Behavior Factors

As one of the most important content of supply chain management,sourcing management occupies a strategic position in the supply chain management concept.Good sourcing management can not only speed up the flow of materials and information,shorten the delivery cycle,reduce inventory and enhance the flexibility of response to market,but also significantly reduce the enterprise cost,increase profits,which is helpful for the enterprise to win advantage in market competition.The research models on traditional sourcing management are usually based on assumptions such as "rational economic man" and constant preferences.However,in the process of sourcing management,decision-makers are often influenced by psychological factors,which may lead to the real decision-making results deviated from the optimal results of the theoretical model.In addition,due to variety and complication of the internal and external environment,supply chain members are often confronted with a variety of realistic situations and even these situations interactively exist,which undoubtedly increases the complexity of the problem.Therefore,it is strongly necessary to conduct specific and detailed researches on the sourcing decision-making models considering different supply chain members' psychological behavior factors under various situations,which can offer more appropriate and practical theoretical guidance to the supply chain members.Directed at the production stage and the circulation stage,this dissertation studies the sourcing decision-making problems such as supplier selection and ordering strategy from the perspective of the manufacturers and the retailers.It considers the supply chain members' different psychological behavior factors under various realistic situations,such as cloud platform,parts collaborative procurement,supply disruption risk,multi-product ordering and service level constraints.Specifically,this paper includes the following research contents:(1)The two-stage parts supplier pre-selection considering the comprehensive satisfaction degree of the dual parts of "manufacturer-supplier".In order to improve the competitive advantage of supply chain,better cope with the personalized customer demand,and resist possible risks,this part proposes the two-stage MTSS method and constructs the candidate pool of suppliers which can realize the win-win mechanism.(2)Parts supplier selection considering the psychological behavior factors of the dual parts of "manufacturer-customer" in the make-to-order manufacturing mode.Specifically,based on characteristics of the intelligent manufacturing system,such as intelligent,self-independent,networking and quick response,this part analyzes the operation mode of the supply chain in the make-to-order manufacturing of the intelligent manufacturing system as well as the supply disruption risks.At last,the integrated optimization models are established to realize the supplier selection.(3)The retailer procurement decision-making considering both scenarios of supply disruption and strategic customer behavior.Firstly,the strategic customer behavior was analyzed and the conditions of rational expectation equilibrium were derived.Based on this,the optimum order quantity and pricing,together with the corresponding profits under patterns of single sourcing and dual sourcing are explored.Further,they were compared with the counterpart results when the strategic customer behavior was neglected.The results indicate that when neglecting the strategic customer behavior,the retailer's optimum order quantity and pricing are higher than those when considering it;on the contrary,the optimum expected profits are negative and much less than those when considering the strategic customer behavior.In addition,the relationship among the sourcing patterns selection,the disruption risk and the emergent procurement cost is deduced.(4)The multi-product newsvendor problem under the service level requirement with dynamic reference points based on Prospect Theory.To explore the optimal order quantities of the Multi-Product Newsvendor Problem(MPNP)under the service level requirement,this part establishes the MPNP model based on Prospect Theory(PT)through maximizing the retailer's integrated utility.In our model,the retailer's reference point is assumed to be dynamic and closely related to the order quantities and his optimism level for future markets.In addition,it theoretically analyzes the influences of the service level requirement and the application of PT to the optimal order quantities.Moreover,the solution algorithms for our proposed models are developed based on the characters of the optimal solutions.At last,a numerical example is given to justify our conclusions.Finally,the dissertation concludes the research and proposes the future research topics.