The risk and information sharing of application services supply chain

We study an application services supply chain consisting of one application service provider (ASP) and one application infrastructure provider (AIP). The AIP supplies the computer capacity to the ASP that in turn sells the value-added application services to the market. The market is characterized by a price-sensitive random demand. The ASP’s objective is to determine the optimal price of its service to the market and the optimal capacity to purchase from the AIP. The AIP’s goal on the other hand is to maximize its profit from selling the capacity to the ASP.     

专有服务机制下提供免费体验服务的服务系统优化设计研究

通过提供免费的体验服务,服务系统可以吸引潜在顾客成为忠实顾客。本文考虑专有服务机制下提供免费体验服务和付费(常规)服务的服务系统,基于顾客的延时敏感特性,利用排队论的矩阵分析方法和谱扩展方法,研究服务系统的相关性能指标以及服务系统的优化设计,进而构建服务提供商利润函数并通过数值实例来获得免费体验服务的最优服务速率以及常规服务收取的最优服务费用,并为服务提供商提供相应的管理启示。研究表明,当越来越多的体验顾客转为付费顾客时,服务提供商需要降低体验服务的服务速率,来缓解系统的拥堵情况,减少顾客的逗留时间,并且服务提供商需要降低常规服务的服务费来弥补顾客因拥堵而造成的服务延迟。新到达顾客选择体验服务的人数越多时,服务提供商需要大幅度降低常规服务的收费标准,来吸引体验顾客成为付费顾客。     

On a Profit Maximizing Location Model

In this paper we discuss a locational model with a profit-maximizing objective. The model can be illustrated by the following situation. There is a set of potential customers in a given region. A firm enters the market and wants to sell a certain product to this set of customers. The location and demand of each potential customer are assumed to be known. In order to maximize its total profit, the firm has to decide: (1) where to locate its distribution warehouse to serve the customers; (2) the price for its product. Due to existence of competition, each customer holds a reservation price for the product. This reservation price is a decreasing function in the distance to the warehouse. If the actual price is higher than the reservation price, then the customer will turn to some other supplier and hence is lost from the firm's market. The problem of the firm is to find the best location for its warehouse and the best price for its product at the same time in order to maximize the total profit. We show that under certain assumptions on the complexity counts, a special case of this problem can be solved in polynomial time.     

线上商品与多种快递服务的组合优化研究

针对网上销售的商品所捆绑的快递服务无法满足顾客多样化需求,而快递服务商又失去了市场空间的问题,提出一种“线上商品+多种快递服务”的组合销售模式,以扩大电商的市场规模,提高快递服务商的利润和差异化竞争水平。在市场细分和顾客需求调查的基础上,综合考虑电商、快递服务商、网购顾客三方的利益,以快递服务商收益最大为目标,构建基于顾客选择行为的“线上商品+多种快递服务”组合销售模式优化模型。以SP调查为数据基础,优化线上商品与多种快递服务的组合销售模式及确定各组合销售模式的均衡价格。模型的求解结果准确地揭示了顾客在网上购物时的快递服务选择行为、快递服务商的末端利润与组合模式之间的关系。     

The Joint Determination of Price, Quality, and Capacity: An Application to Supermarket Operations

This paper focuses on a service provider who, faced with competition, must determine the optimal price and level of service quality to provide in order to maximize profits. Service quality and price are assumed to impact jointly on demand for services. Both demand and service quality impact on the cost of providing service. While a considerable literature exists on the impact of service quality on demand or cost, less work has focused on the explicit impact of service quality jointly on both demand for and the cost of providing services. A service quality constraint is appended to the formulation in order to guarantee that a declared service standard is met. Conditions are developed which characterize optimal solutions, together with comparative statics. Illustrative results are presented based on empirical data obtained from a supermarket study.     

Optimal static pricing for a service facility with holding costs

We study a service facility modelled as a single-server queueing system with Poisson arrivals and limited or unlimited buffer size. In systems with unlimited buffer size, the service times have general distributions, whereas in finite buffered systems service times are exponentially distributed. Arriving customers enter if there is room in the facility and if they are willing to pay the posted price. The same price is charged to all customers at all times (static pricing). The service provider is charged a holding cost proportional to the time that the customers spend in the system. We demonstrate that there is a unique optimal price that maximizes the long-run average profit per unit time. We also investigate how optimal prices vary as system parameters change. Finally, we consider buffer size as an additional decision variable and show that there is an optimal buffer size level that maximizes profit.     

Price and speed decisions in customer-intensive services with two classes of customers

In many customer-intensive services, the perceived quality of service decreases in the speed of service. Usually, an increase in service speed induces different marginal reductions in quality for heterogeneous customers. To bring insight into the managerial implications of this difference, we classify customers in terms of intensity parameters, and investigate the behavior of each class of customers in a queueing framework. The optimal service speed and price are derived to maximize service provider’s revenue. Our results demonstrate that no class is always attractive to the provider, and thus there are usually several combinations of service price and speed reaching the same maximal revenue. Moreover, under some mild conditions, the provider could gain more revenue by treating different classes with discrimination than by adopting uniform treatment.     

Dynamic pricing of inventory with cancellation demand

When an inventory item has such a limited selling period that only a single supply order can be placed to satisfy future demand, a decision-maker must determine the quantity of the order to meet future demand and how to price this stock. Although this problem has received considerable attention, related investigations typically view the demand and selling price as exogenous parameters and assume that customers cannot cancel an order or return the product after purchasing the item. Pricing is, however, an important pervasive marketing vehicle that affects demand, and customers indeed cancel or return their orders after placing them. The newsboy problem is extended here so that demand is price-dependent and customers may cancel their orders. This paper seeks to develop decision rules to maximize the total expected profit over a given planning period. Analysis results demonstrate the feasibility of applying the order-up-to structure to yield the order quantity.     

The uncapacitated facility location problem with demand-dependent setup and service costs and customer-choice allocation

We consider a generalization of the uncapacitated facility location problem, where the setup cost for a facility and the price charged for service may depend on the number of customers patronizing the facility. Customers are represented by the nodes of the transportation network, and facilities can be located only at nodes; a customer selects a facility to patronize so as to minimize his (her) expenses (price for service + the part of transportation costs paid by the customer). We assume that transportation costs are paid partially by the service company and partially by customers. The objective is to choose locations for facilities and balanced prices so as to either minimize the expenses of the service company (the sum of the total setup cost and the total part of transportation costs paid by the company), or to maximize the total profit. A polynomial-time dynamic programming algorithm for the problem on a tree network is developed.     

Managing a dual-channel supply chain under price and delivery-time dependent stochastic demand

Several leading manufacturers recently combined the traditional retail channel with a direct online channel to reach a wider range of customers. We examine such a dual-channel supply chain under price and delivery-time dependent stochastic customer demand. We consider five decision variables, the price and order quantity for both the retail and the online channels and the delivery time for the online channel. Uncertainty frequently arises in both retail and online channels and so additional inventory management is required to control shortage or overstock and that has an effect on the optimal order quantity, price, and lead time. We developed mathematical models with the profit maximization motive. We analyze both centralized and decentralized systems for unknown distribution function of the random variables through a distribution-free approach and also for known distribution function. We examine the effect of delivery lead time and customers’ channel preference on the optimal operation. For supply chain coordination a hybrid all-unit quantity discount along a franchise fee contract is used. Moreover, we use the generalized asymmetric Nash bargaining for surplus profit distribution. A numerical example illustrates the findings of the model and the managerial insights are summarized for centralized, decentralized, and coordinated scenarios.     

Impact of introducing make-to-order options in a make-to-stock environment

Firms engaged in consumer product sales often implement a strict make-to-stock approach, applying a single price to all customers. In such systems, customers can get the product at the given price upon availability on the shelf. However, consumers can often tolerate a delay between order placement and demand satisfaction under a price discount. Recognizing this phenomenon, a supplier may consider offering a menu of delivery-price options to consumers, where longer delay-time options imply lower prices. Demands from customers willing to wait provide advance demand information to the supplier. This paper studies strategies to exploit this additional information to improve profitability and service levels. Primarily assuming that delivery times are set exogenously, we determine optimal prices and stock levels under the new delayed demand satisfaction options. In addition, we develop analytical models to characterize the system performance gains under the new demand fulfillment option.     

Ordering and pricing of service products in an advance sales system with price-dependent demand

This investigation addresses a service inventory control problem in which a firm orders and sells a service which will be used or consumed by customers on a specific future date. The firm sells the product through an advance booking system, aiming to optimize product price to maximize the total expected profit. Considering situations in which product demand is price-dependent and customers with reservations may cancel advance orders, this work develops a continuous-time model to simultaneously determine the order quantity and selling prices. The analytical results reveal that the optimal ordering quantity and prices are derived via closed-form solutions. In addition, sensitivity analysis of the optimal prices with respect to the system parameters is also conducted to illustrate optimal decision characteristics.     

Capacitated procurement planning with price-sensitive demand and general concave-revenue functions

This paper develops effective solution methods for discrete-time, finite-horizon procurement planning problems with economies of scale in procurement, price-sensitive demand, and time-invariant procurement capacities. Our models consider general concave-revenue functions in each time period, and seek to maximize total revenue less procurement and inventory holding costs. We consider the case in which prices may vary dynamically, as well the important practical case in which a constant price is required during the planning horizon. Under mild conditions on the revenue function properties, we provide polynomial-time solution methods for this problem class. The structural properties of optimal solutions that lead to efficient solution methods also serve to sharpen intuition regarding optimal demand management strategies in complex planning situations.     

随机需求下物流服务供应链订购策略研究

针对由单个物流服务提供商和集成商组成的物流服务供应链,基于集中化模式、纳什博弈模式和Stackelberg博弈模式三种典型模式,考虑市场需求随机且受服务质量缺陷承诺水平的影响,探讨物流服务供应链的订购与质量缺陷承诺策略问题。通过分析发现:物流服务质量缺陷承诺水平随着市场需求弹性系数的增加而递减,但其受物流服务集成商观测水平的影响却因合作模式不同而变化不一致;集中化模式下的物流服务订购量随着物流服务集成商观测水平或市场需求弹性系数的增大而递减,但在其他两种合作模式下物流服务订购量随着物流服务集成商观测水平或市场需求弹性系数的增加而增加;在三种模式下,物流服务供应链的整体利润随着市场需求弹性系数的增加而递减,但其受物流服务集成商观测水平的影响却因合作模式不同而变化不一致。     

Optimal admission and pricing control problem with deterministic service times and sideline profit

We consider a discrete-time admission control problem in a company operating in service industries with two classes of customers. For the first class of customers, the company then (1) has an option to accept or reject him/her (admission control), or (2) decides on an offering price (pricing control). The second-class (sideline) customers are only served if no first-class customers are in the system, and this yields the sideline profit. In this paper, we discuss both admission control and pricing control problems within an identical framework, and we examine the properties of the optimal policies to maximize the total expected present discounted net profits. We show that when the sideline profit is large, the optimal policies may not be monotone in the number of first-class customers in the system.     

Fuzzy pricing,marketing and service planning in a fuzzy inventory model: A geometric programming approach

In the real world markets, demand is influenced by different parameters. Recently, many researchers have been interested in integrated production and marketing planning strategies in inventory models where demand depends on different parameters such as price and/or marketing expenditure. The quality of services that are offered to customers of a product is one of the most important parameters that affects demand in the real markets and has not been considered in development of inventory models. On the other hand, the cost parameters in real inventory systems and other parameters such as price, marketing and service elasticity to demand are imprecise and uncertain in nature. So, the notion of fuzziness can be applied to cope with this uncertainty. In this paper, a new fuzzy profit maximization inventory model with shortages is proposed. The demand is considered as a power function of price, marketing expenditure and service expenditure. Furthermore, unit cost is determined as a power function of order quantity. Since the proposed model is in a fuzzy environment, a fuzzy decision should be made to meet the decision criteria, and the results should be fuzzy. Therefore, the proposed model is formulated and solved using geometric programming and fuzzy optimization techniques to derive an approximation of the results’ membership functions. The model is illustrated with a numerical example and finally a case study is provided for evaluation and validation of the results of model.     

Integrated inventory models considering the two-level trade credit policy and a price-negotiation scheme

This paper develops the integrated inventory models with permissible delay in payment, in which customers’ demand is sensitive to the buyer’s price. The models consider the two-level trade credit policy in the vendor–buyer and buyer–customer relationships in supply chain management. A simple recursive solution procedure is proposed for the integrated models to determine the buyer’s optimal pricing and production/order strategy. Although the total profit from the buyer and vendor increases together, the buyer’s share lessens. To compensate the buyer’s loss due to the cooperative relationship, a negotiation system is presented in order to allocate the profit increase to the vendor and buyer to determine the pricing and production/order strategy. A numerical example and sensitivity analysis are provided to illustrate the proposed model. The results indicate that the total profit from the buyer and vendor together can increase, although a price discount is given to the buyer in the proposed models.     

基于网络顾客行为意向的物流服务供应链定价策略

就一个运营网络购物的供应链,分析物流服务需求方和服务提供方的定价和服务水平决策等问题。在成本共担优化模型中考虑基于顾客购买行为意向的产品需求函数,进而分别给出非合作、准合作和完全合作模式下供应链企业决策间的关系,以及网购顾客重购概率对最优定价策略的影响。结论有:证明三种合作模式下双方最优策略的存在性及存在条件;给出最优产品定价策略和服务定价策略间的数量关系,并证明其与网购顾客行为意向有关。数值分析表明,最优定价策略随服务水平和网购顾客重购概率的变化趋势受成本共担系数的影响;较小的成本分摊系数使最优产品定价随着服务水平和网购顾客重购概率的变化幅度增大。     

Optimal admission and pricing control problems in service industries with multiple servers and sideline profit

This paper deals with the problem of selecting profitable customer orders sequentially arriving at a company operating in service industries with multiple servers in which two classes of services are provided. The first class of service is designed to meet the particular needs of customers; and the company (1) makes a decision on whether to accept or to reject the order for this service (admission control) and (2) decides a price of the order and offers it to an arriving customer (pricing control). The second class of service is provided as a sideline, which prevents servers from being idle when the number of customer orders for the first class is less than the number of servers. This yields the sideline profit. A cost is paid to search for customer orders, which is called the search cost. In the context of search cost, the company has an option whether to conduct the search or not. In this paper, we discuss both admission control and pricing control problems within an identical framework as well as examine the structure of the optimal policies to maximize the total expected net profit gained over an infinite planning horizon. We show that when the sideline profit is large, the optimal policies may not be monotone in the number of customer orders in the system. Copyright © 2008 John Wiley & Sons, Ltd.