Pricing And Inventory Management With Different Information

Considering the significance of information for operation management, both indus-try and academy have pay special attention to operation management with informa-tion. Withe the development of information technology, managers can obtain valuable information from Internet, Internet of Things, and e-commerce platforms. By taking advantage of these information, managers are able to reduce the uncertainties in op-eration management, strengthen the control, and improve the efficiency of operation management. As an important resource, people have widely recognized the role of information, and are strongly interested in how to use this resource.Although a lot of research efforts have been spent on operation management with information, there are still many issues in this field remaining unanswered. In this thesis, several operation management models are built by incorporating different information. By studying optimal decisions in these models, I show how the information affects operation management.The first part of this thesis concentrates on the optimization of inventory problems in combination of demand forecasts. I first study a newsvendor model incorporating demand forecast, in which a retailer periodically determines the order quantity based on the dynamically updated demand forecast. Moreover, the retailer’s ordering quantity is constrained by her cash on hand. By considering such a model, I show how the forecast information and cash flow constraints affect the retailer’s optimal ordering decisions, and the interaction between information and cash flow. In particular, if the retailer’s cash is sufficiently lower than a threshold, the value of the forecast information can be zero for the retailer in future.I then consider a warehouse system with rent demand forecast. The manager not only stores her own products in the warehouse, but also rents out unused warehouse space to other retailers. The manager needs to properly allocate warehouse space for storing these two products by dynamically optimizing her ordering and renting decisions. I prove that the two product inventories are economic substitutes, and show the monotonic properties of optimal decisions with respect to system states and other system parameters. Two heuristics, one is based on the lagrangian approach and the other is based on the approximate dynamic programming, are designed for efficiently computing near optimal solutions. An interesting finding is that the performance of the solution yielded by the heuristic based on the lagrangian approach can be arbitrarily bad.The second part of this thesis focuses on how to diffuse green products via word- of-mouth in social networks, and pricing decisions of green products. I first consider a problem of pricing single green product. In this problem, the green product is innovative and new to consumers. The diffusion of the green product in the social network depends on the word-of-mouth between consumers. A firm can affect the diffusion by pricing and designing the green product, which finally serves the purpose of profit maximization. I find that the diffusion of the green product will succeed if and only if the probability that a consumer is willing to engage in word-of-mouth transmission is larger than a threshold. Moreover, the threshold is a function of the network connectivity. I then show how network connectivity affects optimal pricing and designing decisions. It is interesting to find that the environmental condition degrades as the network connectivity grows.I then address a problem of pricing both green and non-green products. In this problem, the green product is new to consumers, while the non-green one is well known by consumers. The diffusion of the green product also depends on the word-of-mouth between consumers. Due to the coexistence of green and non-green products, the deci-sion maker needs to tradeoff the profit margins, word-of-mouth transmission, and social network when determining the prices of the two products. By analyzing this problem, I find that how network connectivity affects the optimal price and market shares of the two products. When the decision maker only determines the price of the green product, the increase in network connectivity not only results in an increase in optimal price, but also in market share of the green product. When the decision maker jointly determines the prices of the two products, optimal price of the green product can be decreasing in network connectivity, which is contradictory to previous finding.