A Study Of VMI Supply Chain In Three Scenarios

With the increasing labor costs and the prices of urban property, retailers face more and more severe market environment. With developing modern information technology and convenient logistics, the cost can be reduced by the cooperation of retailers. Retailers share the trade and inventory information with suppliers, and let inventory management entrusted by the supplier, thus in this background vendor managed inventory (VMI) is born. Vendor managed inventory has become a hot spot in the research of the supply chain management. Scholars recognize that since the enterprises in the VMI supply chain are at different stages in development, together with different micro environments, only the study of the optimization decision problems is targeted to the specific market situation, can it bring effective theoretical guidance to the enterprises.Under the background of reality and theory of VMI supply chain mentioned above, this article considers profit sharing and production decisions in cooperative advertising, decisions about intermediate products, and decisions made in offline experience and online order. These three situations are widely existed in common markets, but no deep theoretical analysis has yet been done in academic so far. The research content of this article can be divided into the following three parts.The first part is the study of profit sharing and production decisions under the background of cooperative advertisement, and how to solve the model efficiently is considered. Members in a VMI supply chain make joint decisions on inventory policy and cooperative advertising on the basement of their cooperation. However, very few research results which develop methods to facilitate such joint decision making have been reported due to difficulty of modeling and complexity of computation. It considers a two level VMI supply chain including a manufacturer and m retailers. A non-linear, mixed integer Nash bargaining model is developed to model the complex joint decision making of (m+1) players. In view of the difficulties in model solving, this study further gives an algorithm to greatly reduce the complexity of computation. The validity of the Nash bargaining model and the effectiveness of the solution methodology is proved by numerical examples. Finally, a number of managerial implications are drawn based on sensitivity analysis.The second part is the study of production decisions and pricing of intermediate products. We develop a piecewise objective function and use analytical methods and genetic algorithm to solve the model. It considers a two level VMI supply chain including a manufacturer and two retailers. They produce and sale saleable intermediate products and final products respectively. Since the inventory level at the manufacturer’s side is determined by relationship between capacity and time of production of two types of products, we develop the model with piecewise objective function to describe the production and pricing decisions of two types of products for the manufacturer and retailers by listing and summarizing all cases. In consideration of the complexity of model solving, we utilize analytical method and genetic algorithm to solve the model. Further sensitivity analysis is made for the parameters.The third part is the study of production and pricing decisions in offline experience and online order. We analyze the properties of all variables in the objective function, and use the analytic methods to solve all the decision variables. It considers a two level VMI supply chain including a manufacturer and two retailers which are both in a common local market. The retailers provide responsible service in the experience shop to attract customers and the manufacturer produces one type of product for two retailers and manages the inventory in the local market warehouse uniformly. We construct the Stackelberg game model between them, and use analytical method to solve the model based on the analysis of the properties of each decision variable.After elaborating the above research content, we summarize the main innovations and contributions as follows:Considering the cooperative advertising mode in which demand is affected by advertising, we construct the Nash bargaining model based on the mode. The Nash bargaining model is multivariate, multiparameter, and high-order and contains polynomial products. Because of these attributes, it is very difficult to obtain optimal solutions by directly analyzing properties of all decision variables. Thus, we adopt a decomposition strategy to develop a solution methodology, which includes an integrated model and hybrid algorithm. The integrated model provides the same optimal values of the decision variables as the Nash bargaining model. In view of their properties, analytical methods and the GA are adopted in solving the integrated model; the Lagrange multiplier method is employed to solve the rest decision variables. The hybrid algorithm not only yields better optimal solutions than a pure GA but also solves the model much faster, as demonstrated by numerical examples. Sensitivity analysis demonstrates that the change of wholesale price only affects extra profit distribution, so we do not need to adjust other decision variables at this time. In response to a retailer’s wholesale price change, the chain members should re-negotiate the unit profit sharing for obtaining optimal profits. Retailer’s advertising elasticity affects the number of retailers to be included in a VMI supply chain. Therefore, this paper is expected to help practitioners make suitable decisions, for example, coordination, on cooperative advertising and inventory policies for achieving higher individual profits.It considers a decision model of VMI supply chain including saleable intermediate products and final products. Due to the relationship of the capacity and production time of the two types of products can lead to different structure of stock levels, and inventory cost calculated also is different, thus we adopt the idea of the classification, the enumeration and the induction to construct the inventory cost function. In the first place, according to the capacity relationship we classify all cases to two classes. We enumerate all cases based on different production time collocation ion and then combine some cases..For the piecewise function in which variables have different range, we utilize analytical methods and genetic algorithm to solve it. Through sensitivity analysis we find that when the market size of one type of product expands in a market, manufacturers should improve wholesale prices of the product in the market to gain profit, at the same time improve wholesale prices of the other type of products in the market and of the two types of products in two market, thus reducing the corresponding demand and transfer capacity to the product. When the intermediate products’capacity increases, the manufacturer lower wholesale price at first, and then improve it to a constant level. When the capacity of the final products change, the manufacturer lowers wholesale price of the final products fast, and lowers wholesale price of the intermediate products slowly. At last wholesale price of the final products is improved, wholesale price of intermediate products is lowered and his demand equal to his capacity to reduce costs. The manufacturer should take different measures to deal with the change of capacity of two types of products.We describe the impact of his own demand and the other retailer’s demand on retailing price in the local market in the VMI supply chain, and consider model characteristics that the manufacturer manages inventory of all products in one local warehouse. It is very difficult to solve wholesale price directly, so we adopt the idea of the transformation, make total demand as the intermediate variable, transform the objective function to the function which select total demand as the independent variable, and we derive the conditions which optimal solution satisfies and greatly simplify the solving process. Through sensitivity analysis of one retailer’s price sensitivity to his own demand, we find when it rises, the manufacturers should lower at first and improve wholesale price at last to keep the optimal profit; Through sensitivity analysis of price sensitivity to the other retailer’s demand, We find that although the sensitivity has multipled, the wholesale prices should be kept constant.