The Impact of Capacity Costs on Product Differentiation in Delivery Time,Delivery Reliability,and Price

We develop an analytical framework for studying the role capacity costs play in shaping the optimal differentiation strategy in terms of prices, delivery times, and delivery reliabilities of a profit‐maximizing firm selling two variants (express and regular) of a product in a capacitated environment. We first investigate three special cases. The first is an existing model of price and delivery time differentiation with exogenous reliabilities, which we only review. The second focuses on time‐based (i.e., length and reliability) differentiation with exogenous prices. The third deals with deciding on all features for an express variant when a regular product already exists in the marketplace. We subsequently address the integrative framework of time‐and‐price‐based differentiation for both products in a numerical study. Our results shed light on the role that customer preferences towards delivery times, reliabilities and prices, and the capacity costs (absolute and relative) have on the firm's optimal product positioning policy.     

The price-setting newsvendor with service and loss constraints

Current performance measurement systems consider not only financial measures, like costs and profits, but also non-financial indicators with respect to customer service, quality and flexibility. Using the newsvendor model, we analyse the respective influence of these possibly conflicting performance measures on important operations and marketing decisions, for instance the order quantity and the selling price of a product. As in the classical newsvendor model for price-independent as well as price-dependent demand distribution, the objective of the firm is to maximise expected profit. In this paper, we also consider a service constraint—a lower bound for the level of product availability—and a loss constraint—an upper bound for the probability of a loss occurring. For both models, we provide conditions for the existence of solutions. We then analyse the influence of demand variability using a set of conditions specifying the quantiles of the predetermined performance measures: a higher variability of demand implies a smaller admissible region of the decision variables. In the price-independent case, the optimal solution has a control-limit structure: the optimal order quantity is thus given either by the classical newsvendor solution or by the control-limits corresponding to the constraints. In the price-setting model with multiplicative demand, this structure is used to check whether small admissible prices are determined by the service constraint or by the loss constraint. Using these structural results, a procedure is developed to more easily enable the computation of the optimal values of the order quantity, selling price and expected profit.     

A Multi‐Supplier Sourcing Problem with a Preference Ordering of Suppliers

We study a sourcing problem faced by a firm that seeks to procure a product or a component from a pool of alternative suppliers. The firm has a preference ordering of the suppliers based on factors such as their past performance, quality, service, geographical location, and financial strength, which are commonly included in a supplier scorecard system. Thus, the firm first uses available inventory from supplier 1, if any, then supplier 2, if any, and so on. The suppliers differ in costs and prices. The buyer firm seeks to determine which suppliers to purchase from and in what quantities to maximize its total expected profit subject to the preference ordering constraint. We present the optimal solution to this problem, and show that it has a portfolio structure. It consists of a sub‐set of suppliers that are ordered by their underage and overage costs. This portfolio achieves a substantial profit gain compared to sourcing from a unique supplier. We present an efficient algorithm to compute the optimal solution. Our model applies to component sourcing problems in manufacturing, merchandizing problems in retailing, and capacity reservation problems in services.     

基于工业互联网平台的增值服务收费模式研究

工业互联网平台的增值服务可以给制造商提供数字化转型服务赋能，实现提质降本增效的作用。本文构建包含一个工业互联网平台、一个制造商和一个零售商组成的三级供应链博弈模型，求解基于使用量收费和订阅收费模式下的最优决策。分析不同定价模式下企业数字化转型决策和利润受到增值服务因子、成本降低因子的影响，以及对两种定价模式下的最优决策进行比较。研究显示：存在不同的平台增值服务效果阈值，当服务效果位于不同阈值范围时，平台和制造商将选择订阅收费模式或按使用量收费模式。当平台增值服务效果适中时，平台和制造商都选择订阅收费模式。当平台增值服务效果较低(高)时，平台(制造商)选择基于使用量收费模式，而制造商(平台)选择订阅收费模式。     

Prices,Markups, and Trade Reform

This paper examines how prices, markups, and marginal costs respond to trade liberalization. We develop a framework to estimate markups from production data with multi‐product firms. This approach does not require assumptions on the market structure or demand curves faced by firms, nor assumptions on how firms allocate their inputs across products. We exploit quantity and price information to disentangle markups from quantity‐based productivity, and then compute marginal costs by dividing observed prices by the estimated markups. We use India's trade liberalization episode to examine how firms adjust these performance measures. Not surprisingly, we find that trade liberalization lowers factory‐gate prices and that output tariff declines have the expected pro‐competitive effects. However, the price declines are small relative to the declines in marginal costs, which fall predominantly because of the input tariff liberalization. The reason for this incomplete cost pass‐through to prices is that firms offset their reductions in marginal costs by raising markups. Our results demonstrate substantial heterogeneity and variability in markups across firms and time and suggest that producers benefited relative to consumers, at least immediately after the reforms.     

Pricing and Operational Performance in Discretionary Services

In many services, for example, website or landscape design, the value or quality derived by a customer depends upon the service time, and this valuation differs across customers. Customers procure the service based on the expected value to be delivered, prices charged, and the timeliness of service. We investigate the performance of the optimal pricing scheme as well as two commonly used pricing schemes (fixed fee and time‐based pricing) for such services on important dimensions such as revenue, demand served, and utilization. We propose a novel model that captures the above features and wherein both service rate and demand are endogenous and functions of the pricing scheme. In particular, service time is an outcome of the pricing scheme adopted and the heterogeneous valuations of customers, unlike in the queueing‐based pricing literature. We find that the service system may benefit from a greater variance in consumer valuations, and the performance of pricing schemes is impacted by the shape of the distribution of customers' valuation of service time and the responsiveness desired by customers. Both the fixed fee and time‐based schemes do well relative to the optimal pricing scheme in terms of revenue in many plausible scenarios, but there are substantial differences between the pricing schemes in some important operational metrics. For instance, the fixed fee scheme serves more customers and has higher utilization than the time‐based scheme. We also explore variants of the fixed and time‐based schemes that have better revenue performance and show that the two‐part tariff which is a combination of fixed and time‐based pricing can do as well as the optimal scheme in terms of revenue.     

Stochastic Optimal Control for Staffing and Backlog Policies in a Two‐Stage Customized Service Supply Chain

Motivated by an oilfield services industry case study, we investigate the dynamic behavior of customized service supply chains by developing a two‐stage serial staffing model. Each stage holds no finished goods inventory, but rather only backlogs that can be managed by adjusting staffing levels. We develop optimal control policies to balance backlog costs against hiring and firing personnel costs'assuming shared backlog information—under both centralized and decentralized control. We examine when there is sufficient economic incentive for two completely decentralized stages to begin: (1) to share backlog information without centralizing control, or (2) to completely centralize control. These switching points are determined by the relative service and personnel costs of the two stages. From these results, we show that decentralizing control in many cases does not materially worsen performance, so long as information is shared. Moreover, in some cases, even sharing information is of only marginal benefit.     

考虑定价和需求关系的供应链网络优化研究

本文通过引入价格-需求函数描述产品价格变化对消费者需求的影响,构建了一个由制造商、仓库和消费者组成的三级供应链网络。在此基础上,以最大化供应链总利润为目标、以定价和需求为决策变量,建立了混合整数非线性规划(MINLP)模型。基于该模型目标函数非线性的复杂性,采用外部近似法将目标函数近似线性化,即切割成有限条切线,使其可以求解。最后通过不同规模的算例分析验证了模型和算法的可行性与有效性,从而指导供应链上的企业权衡其成本和收益,提高顾客的满意度。     

Quality‐Speed Competition in Customer‐Intensive Services with Boundedly Rational Customers

We consider a system in which two competing servers provide customer‐intensive services and the service reward is affected by the length of service time. The customers are boundedly rational and choose their service providers according to a logit model. We demonstrate that the service provider revenue function is unimodal in the service rate, its decision variable, and show that the service rate competition has a unique and stable equilibrium. We then study the price decision under three scenarios with the price determined by a revenue‐maximizing firm, a welfare‐maximizing social planner, or two servers in competition. We find that the socially optimal price, subject to the requirement that the customer actual utility must be non‐negative, is always lower than the competition equilibrium price which, in turn, is lower than the revenue‐maximizing monopoly price. However, if the customer actual utility is allowed to be negative in social optimization, the socially optimal price can be higher than the other two prices in a large market.     

Coordinating Service‐Sensitive Demand and Capacity by Adaptive Decision Making: An Application of Case‐Based Decision Theory*

The subject of this article is the simultaneous choice of product price and manufacturing capacity if demand is stochastic and service‐level sensitive. In this setting, capacity as well as price have an impact on demand because several aspects of service level depend on capacity. For example, delivery time will be reduced if capacity is increased given a constant demand rate. We illustrate the relationship between service level, capacity, and demand reaction by a stylized application problem from the after‐sales services industry. The reaction of customers to variations in service level and price is represented by a kinked price‐demand‐rate function. We first derive the optimal price‐capacity combination for the resulting decision problem under full information. Subsequently, we focus on a decision maker (DM) who lacks complete knowledge of the demand function. Hence the DM is unable to anticipate the service level and consequently cannot identify the optimal solution. However, the DM will acquire additional information during the sales process and use it in subsequent revisions of the price‐capacity decision. Thus, this decision making is adaptive and based on experience. In contrast to the literature, which assumes certain repetitive procedures somewhat ad hoc, we develop an adaptive decision process based on case‐based decision theory (CBDT) for the price‐capacity problem. Finally, we show that a CBDT DM in our setting eventually finds the optimal solution, if the DM sets the price based on absorption costs and adequately adjusts the capacity with respect to the observed demand.     

面向价值共创的服务衍生供需决策优化研究

针对制造企业服务衍生时，制造企业与客户间可能存在的"双重边际效应"问题，以制造企业服务衍生特征刻画为基础，构建了服务衍生供需价值创造模型，比较分析了分散和集中两种决策情形下的价值创造，发现集中决策下供需双方能够创造整体更高的价值，但制造企业存在陷入"服务悖论"的风险，由此，设计了有助于协调供需价值分配的收益共享契约。研究表明，收益共享契约能够缓解制造企业与客户间的"双重边际效应"，契约能够激发制造企业以更为积极主动的态度改进服务衍生方案，提升方案的性价比，并由此促进市场需求，实现供需双方的价值共创。     

THE ESTIMATION OF LINEAR PRODUCTION FUNCTIONS HAVING MULTICOLLINEAR INPUTS

In this paper linear production functions with highly correlated independent variables are estimated. Because many production processes require the use of inputs in fixed proportions, multicolinearity is usually a serious problem. This is usually the case when one attempts to estimate a linear or Cobb-Douglass (in log linear form) production function. Estimates of the marginal products of a linear production function are obtained by employing the first order conditions of the output maximizing solution given a cost constraint. Parameter estimates are determined for the case where the input costs are constants. The general case, where the input prices are functions of utilization levels, is delineated.     

Coordinating pricing and production decisions for multiple products

We consider a dynamic problem of joint pricing and production decisions for a profit-maximizing firm that produces multiple products. We model the problem as a mixed integer nonlinear program, incorporating capacity constraints, setup costs, and dynamic demand. We assume demand functions to be convex, continuous, differentiable, and strictly decreasing in price. We present a solution approach which is more general than previous approaches that require the assumption of a specific demand function. Using real-world data from a manufacturer, we study problem instances for different demand scenarios and capacities and solve for optimal prices and production plans. We present analytical results that provide managerial insights on how the optimal prices change for different production plans and capacities. We extend some of the earlier works that consider single product problems to the case of multiple products and time variant production capacities. We also benchmark performance of proposed algorithm with a commercial solver and show that it outperforms the solver both in terms of solution quality and computational times.     

FAIR PRICING

This paper explores the consequences of supposing that consumers see a firm as fair if they cannot reject the hypothesis that the firm is somewhat benevolent towards them. When consumers can reject this hypothesis, some become angry, which is costly to the firm. The desire to appear benevolent can lead firms to adopt third‐degree price discrimination based on the income of different consumer classes while foreswearing third‐degree price discrimination based on differences in the elasticity of demand. It can also explain why prices seem to be more responsive to changes in factor costs than to changes in demand that have the same effect on marginal cost. Lastly, if consumers experience regret or disappointment when faced by increased prices, the model can explain why prices can be more rigid in response to disasters that increase demand dramatically than they are when there is a less substantial increase in demand.     

UNCERTAIN DEMAND,CONSUMER LOSS AVERSION,AND FLAT‐RATE TARIFFS

We consider a model of firm pricing and consumer choice, where consumers are loss averse and uncertain about their future demand. Possibly, consumers in our model prefer a flat rate to a measured tariff, even though this choice does not minimize their expected billing amount—a behavior in line with ample empirical evidence. We solve for the profit‐maximizing two‐part tariff, which is a flat rate if (a) marginal costs are not too high, (b) loss aversion is intense, and (c) there are strong variations in demand. Moreover, we analyze the optimal nonlinear tariff. This tariff has a large flat part when a flat rate is optimal among the class of two‐part tariffs.     

The Usage of Opportunity Cost to Maximize Performance in Revenue Management*

To meet customer requirements efficiently, a manager needs to supply adequate quantities of products, capacity, or services at the right time with the right prices. Revenue management (RM) techniques can help firms use differential pricing strategies and capacity allocation tactics to maximize revenue. In this article, we propose a marginal revenue‐based capacity management (MRBCM) model to manage stochastic demand in order to create improved revenue opportunities. The new heuristic employs opportunity cost estimation logic that is unique and is the reason for the increased performance. The MRBCM model generates order acceptance policies that allocate available capacity to higher revenue generating market segments in both service and manufacturing environments. To evaluate these models, we design and conduct simulation experiments for 64 scenarios using a wide range of operating conditions. The experimental results show that the MRBCM model generates significantly higher revenues over the first come, first served rule when capacity is tight. In addition, we also show that the MRBCM model generally performs better than a recent RM model published in the literature.     

Optimal Configuration of a Service Delivery Network: An Application to a Financial Services Provider

Driven by market pressures, financial service firms are increasingly partnering with independent vendors to create service networks that deliver greater profits while ensuring high service quality. In the management of call center networks, these partnerships are common and form an integral part of the customer care and marketing strategies in the financial services industry. For a financial services firm, configuring such a call center service network entails determining which partners to select and how to distribute service requests among vendors, while incorporating their capabilities, costs, and revenue‐generating abilities. Motivated by a problem facing a Fortune 500 financial services provider, we develop and apply a novel mixed integer programming model for the service network configuration problem. Our tactical decision support model effectively accounts for the firm's costs by capturing the impact of service requirements on vendor staffing levels and seat requirements, and permits imposing call routing preferences and auxiliary service costs. We implemented the model and applied it to data from an industry partner. Results suggest that our approach can generate considerable cost savings and substantial additional revenues, while ensuring high service quality. Results based on test instances demonstrate similar savings and outperform two rule‐based methods for vendor assignment.     

A Simple Heuristic for Lot Sizing with Setup Times

This paper presents an easily understood and computationally efficient heuristic algorithm for the capacitated lot sizing problem (CLSP), the single machine lot-sizing problem, with nonstationary costs, demands, and setup times. The algorithm solves problems with setup time or setup cost. A variation of the algorithm can solve problems when limited amounts of costly overtime are allowed. Results of experimentation indicate that the most significant effects on solution quality are due to the level of setup costs relative to holding costs and the size of the problems as determined by the number of items. Also affecting solution quality are tightness of the capacity constraint and variability of demand in a problem. When the capacity constraint is extremely tightly binding, it sometimes has difficulty finding solutions that do not require overtime.     

Price and Service Competition in an Outsourced Supply Chain

We consider a buyer who outsources the manufacturing of a product to multiple symmetric make‐to‐stock suppliers who compete on price and service (fill rate). The buyer allocates demand to the suppliers using a score function with an exponential form, which specifies the relative importance of price vs. service, in order to minimize his costs, while the suppliers choose their prices and fill rates to maximize their profits. For the case of dual‐sourcing, we characterize the optimal parameter of the exponential score function, considering the impact of the buyer's decisions on the suppliers, and considering how the suppliers compete against each other to earn a portion of the buyer's demand. We prove the existence of a unique equilibrium and characterize the equilibrium behavior of the system. We then consider a general number of suppliers and show that the equilibrium prices and fill rates, and the buyer's cost, are increasing in the number of suppliers. We compare these results to a model of single‐sourcing, in which the buyer is the Stackelberg leader and extracts all profits from the supplier. We find that the buyer always prefers single‐sourcing to multisourcing. Finally, we study a centralized system and use the results to develop a coordinating contract for the decentralized system.     

Identification in Differentiated Products Markets Using Market Level Data

We present new identification results for nonparametric models of differentiated products markets, using only market level observables. We specify a nonparametric random utility discrete choice model of demand allowing rich preference heterogeneity, product/market unobservables, and endogenous prices. Our supply model posits nonparametric cost functions, allows latent cost shocks, and nests a range of standard oligopoly models. We consider identification of demand, identification of changes in aggregate consumer welfare, identification of marginal costs, identification of firms' marginal cost functions, and discrimination between alternative models of firm conduct. We explore two complementary approaches. The first demonstrates identification under the same nonparametric instrumental variables conditions required for identification of regression models. The second treats demand and supply in a system of nonparametric simultaneous equations, leading to constructive proofs exploiting exogenous variation in demand shifters and cost shifters. We also derive testable restrictions that provide the first general formalization of Bresnahan's (1982) intuition for empirically distinguishing between alternative models of oligopoly competition. From a practical perspective, our results clarify the types of instrumental variables needed with market level data, including tradeoffs between functional form and exclusion restrictions.