Strategic Capacity Management When Customers Have Boundedly Rational Expectations

In retailing industries, such as apparel, sporting goods, customer electronics, and appliances, many firms deploy sophisticated modeling and optimization software to conduct dynamic pricing in response to uncertain and fluctuating market conditions. However, the possibility of markdown pricing creates an incentive for customers to strategize over the timing of their purchases. How should a retailing firm optimally account for customer behavior when making its pricing and stocking/capacity decisions? For example, is it optimal for a firm to create rationing risk by deliberately under stocking products? In this study, we develop a stylized modeling framework to answer these questions. In our model, customers strategize over the timing of their purchases. However, customers have boundedly rational expectations in the sense of anecdotal reasoning about the firm's fill rate, i.e., they have to rely on anecdotes, past experiences, or word‐of‐mouth to infer the firm's fill rate. In our modeling framework, we distinguish two settings: (i) capacity commitment, where the firm commits to its capacity level in the long run, or (ii) the firm dynamically changes it in each season. For both settings, within the simplest form of anecdotal reasoning, we prove that strategic capacity rationing is not optimal independent of customer risk preferences. Then, using a general form of anecdotal reasoning, we provide sufficient conditions for capacity rationing to be optimal for both settings, respectively. We show that the result of strategic capacity rationing being suboptimal is fairly robust to different valuation distributions and utility functions, heterogeneous sample size, and price optimization.     

Subcontracting price schemes for order acceptance and scheduling

In this paper we study subcontracting price schemes between a subcontractor and a firm that are engaged in subcontracting of heterogeneous orders with distinct due dates, revenues, and processing times. We assume that the subcontractor proposes the subcontracting pricing and the firm follows by determining the subcontracted orders by solving its order acceptance and scheduling problem. When the subcontractor adopts a linear pricing scheme, we find the firm׳s optimal decisions and develop an algorithm to derive the subcontractor׳s own optimal pricing. We then design a fixed pricing with transfer payment scheme and a quantity discount pricing scheme to coordinate the firm׳s and subcontractor׳s decisions. We examine if the subcontractor can make a higher profit using either of these schemes than the linear pricing scheme, and if they will induce the firm to make decisions that lead to system-wide optimal outcomes.     

考虑跨渠道退货的双渠道闭环供应链决策研究

双渠道闭环供应链存在制造商网络直销渠道和零售商实体店零售渠道。消费者会对购买不满意的产品进行退货，由于网上商店购买的产品缺乏现场体验故退货率较高。相比线下实体商店，线上退货流程更为复杂，这往往容易影响消费者购物体验。因此本文设计考虑跨渠道退货的双渠道闭环供应链结构，并分析跨渠道退货率以及渠道消费偏好对供应链的决策影响，基于Stackelberg博弈和Nash均衡博弈理论，从集中式决策与分散式决策两方面研究不同闭环供应链结构下的定价决策与利润分配，并结合数值算例进行分析。研究结果表明，跨渠道退货率以及消费者渠道偏好对闭环供应链的定价策略以及利润分配等决策具有显著影响。     

全渠道零售商退货方式和定价研究

本文以全渠道零售商不同渠道的定价为背景,以企业利润最大化为目标,以顾客退货给零售商带来的损失为出发点,从三种不同的退货方式分析退货损失对零售商不同渠道最优定价和利润的影响。首先分析传统的原渠道退货(即：从购买产品的渠道退货),然后分析所有顾客都通过线上渠道退货,进而分析所有顾客都通过线下渠道退货。研究表明：三种退货方式下,当零售商与顾客的线上单位产品净退货损失之和小于线下单位产品净退货损失之和时,全渠道零售商选择全部退货到线上渠道可获得最大利润;当零售商与顾客的线上单位产品净退货损失之和大于线下单位产品净退货损失之和时,全渠道零售商应选择全部退货到线下的退货方式以获得最大利润;传统的退货方式不会让零售商获得最大利润。本文研究对于全渠道零售虑顾客退货损失的基础上,设置最合理的退货方式和不同渠道之间的最优定价有一定的指导意义和实际应用价值。     

CONTROL RIGHTS IN COMPLEX PARTNERSHIPS

This paper develops a theory of the allocation of authority between two players who are in a complex partnership, that is, a partnership which produces impure public goods. We show that the optimal allocation depends on technological factors, the parties’ valuations of the goods produced, and the degree of impurity of these goods. When the degree of impurity is large, control rights should be given to the main investor, irrespective of preference considerations. There are some situations in which this allocation is optimal even if the degree of impurity is very low as long as one party’s investment is more important than the other party’s. If the parties’ investments are of similar importance and the degree of impurity is large, shared authority is optimal with a greater share going to the low‐valuation party. If the importance of the parties’ investments is similar but the degree of impurity is neither large nor small, the low‐valuation party should receive sole authority. We analyze an extension in which side payments are infeasible. We check for robustness of our results in several dimensions, such as allowing for multiple parties or for joint authority, and apply our results to interpret a number of complex partnerships, including those involving schools and child custody.     

Durable goods pricing with reference price effects

A price benchmark shaped by consumers on the basis of their perception of past prices is known as a reference price. Behavioral decision research suggests that consumers are likely to be backward-looking in that they make purchase decisions based not only on the current price but also on the reference price. It is evident that the reference price effect, which has significant impact on consumer demand, exists for both consumables and durables. Yet, how this effect works has only been investigated in relation to the pricing of consumables, and thus the corresponding results are unable to yield normative implications for durable goods pricing where the saturation effect must enter the picture. This study aims to provide marketers of durables with relevant insights that can be practically used to guide their design of pricing strategies in the presence of the reference price effect. Specifically, we develop a dynamic pricing model which incorporates both the reference price effect and the saturation effect into a framework to broaden our understanding on the durable goods pricing problem. As the internet technology and social media have enhanced consumers’ ability to recall and compare past prices, the need for such a pricing model with backward-looking consumer behavior is increasingly compelling. Our results indicate that while it is optimal for a myopic seller to adopt the skimming pricing strategy, either the price skimming strategy or the penetration strategy is optimal for a forward-looking seller, contingent on the potential market and consumers’ reference price effects.     

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.     

Why Do We Observe Stockless Operations on the Internet? Stockless Operations Under Competition

Due to the proliferation of electronic commerce and the development of Internet technologies, many firms have considered new pricing‐inventory models. In this paper, we study the role of stockless (i.e., zero‐inventory) operations in online retailing by a considering duopoly competition in which two retailers compete to maximize profit by jointly optimizing their pricing and inventory decisions. In our model, the retailers are allowed to choose either an in‐stock policy or stockless operations with a discounted price. We first present the characteristics and properties of the equilibrium. We then demonstrate that the traditional outcome of asymmetric Bertrand competition is observed under head‐to‐head competition. However, when the two firms choose different operational policies, with corresponding optimal pricing, they can share the market under certain conditions. Finally, we report interesting observations on the interaction between pricing and inventory decisions obtained from an extensive computational study.     

Pricing,Allocation, and Overbooking in Dynamic Service Network Competition When Demand Is Uncertain

We study the problem of combined pricing, resource allocation, and overbooking by service providers involved in dynamic noncooperative oligopolistic competition on a network that represents the relationships of the providers to one another and to their customers when service demand is uncertain. We propose, analyze, and compute solutions for a model that is more general than other models reported in the revenue management literature to date. In particular, previous models typically consider only three or four of five key revenue management features that we have purposely built into our model: (1) pricing, (2) resource allocation, (3) dynamic competition, (4) an explicit network, and (5) uncertain demand. Illustrative realizations of the abstract problem we study are those of airline revenue management and service provision by companies facing resource constraints. Under fairly general regularity conditions, we prove existence and uniqueness of a pure strategy Nash equilibrium for dynamic oligopolistic service network competition described by our model. We also show, for an appropriate notion of regularity, that competition leads to the underpricing of network services, a finding numerically illustrated by an example of intermediate size. Our proposed algorithm can be implemented using well‐known off‐the‐shelf commercial software.     

基于总成本和碳减排的物流园区与产业园区协同选址

随着经济全球化的不断深化，世界各国越来越重视通过构建和延伸产业链，通过区域之间的产业联动发展等方式，来获得更多的经济要素、占领更大的市场和实现产业转型升级，以达到提高整个区域产业竞争力的目的，物流园区和产业园区的协同选址以及货物的优化分配方案有利于加强区域产业间的协同效应，从而促进区域经济的整体发展。本文在物流园区和产业园区备选点确定的前提下，针对物流园区和产业园区协同选址问题，采用多目标理论，分别以总成本和总废气排放量为目标函数，建立多目标选址模型，并设计了带有精英策略的非支配排序遗传算法，通过算法求解物流园区和产业园区的协同建设地址以及货物优化分配方案。应用算例对算法进行了分析，结果表明本文设计的算法具有一定的高效性，同时通过对主要参数的敏感性分析，验证了模型具有稳定性。     

Effects of Remanufacturable Product Design on Market Segmentation and the Environment

Despite documented benefits of remanufacturing, many manufacturers have yet to embrace the idea of tapping into remanufactured‐goods markets. In this article, we explore this dichotomy and analyze the effect of remanufacturable product design on market segmentation and product and trade‐in prices by studying a two‐stage profit‐maximization problem in which a price‐setting manufacturer can choose whether or not to open a remanufactured‐goods market for its product. Our results suggest that it is optimal for a manufacturer to design a remanufacturable product when the value‐added from remanufacturing is relatively high but product durability is relatively low and innovation is nominal. In addition, we find that entering a remanufactured‐goods market in and of itself does not necessarily translate into environmental friendliness. On the one hand, the optimal trade‐in program could result in low return and/or remanufacturing rates. On the other hand, a low price for remanufactured products could attract higher demand and thereby potentially result in more damage to the environment. Meanwhile, external restrictions imposed on total greenhouse gas emissions draw criticism in their own right because they risk stifling growth or reducing overall consumer welfare. Given these trade‐offs, we therefore develop and compare several measures of environmental efficiency and conclude that emissions per revenue can serve as the best proxy for emissions as a metric for measuring overall environmental stewardship.     

The effects of price subsidy and fairness concern on pricing and benefits of take-away supply chain

In this paper, from the perspective of game theory, we study the impact of price subsidy and fairness concern on the pricing strategies and benefits of members in the take-away industry. In the single-channel supply chain, we build a Stackelberg game model between the take-away platform and the restaurant for the online take-away business. By comparing and analyzing the product pricing and revenue in the cases of no price subsidy and price subsidy, we obtain the optimal pricing strategy for both parties. In the dual-channel supply chain, we explore the benefits of supply chain members under the combined effects of fairness concern and price subsidy. Under the single channel price subsidy model, we find that restaurant always raises prices, and the price increase is directly proportional to the subsidy intensity. Such a proper price increase always brings more benefits to both parties. Under the dual-channel model, consumer fairness concern may curb the price increase behavior of restaurants. Regardless of the model, in the long term, the optimal subsidy of the platform will decrease with the expansion of the online take-away market.

     

集装箱班轮二维收益管理在线动态定价策略

为了在现实约束条件下最大化班轮公司收益,研究了集装箱海运二维收益管理多航段多箱型在线动态定价模型,提出了其最优在线动态定价策略,并且证明了模型价值函数的单调性及其上界.基于降维的思想提出了更为实际的启发式算法.在算例中分析了单航段单箱型、单航段多箱型和多航段多箱型3种情况下的最优动态定价策略,分析结果表明:在单航段单箱型的情况下,最优价格具有单调性;在单航段多箱型和多航段多箱型的情况下,最优价格不一定具有单调性.     

Service Coproduction with Information Stickiness and Incomplete Contracts: Implications for Consulting Services Design

Drawing from three theoretical bases—“information stickiness” from the knowledge management literature, “service coproduction” from the service operations management literature, and “incomplete contract theory” from the transaction cost economics literature—we discuss a theoretical framework and develop models to study the efficiency of the service coproduction process in a knowledge‐intensive consulting environment. We apply, refine, and interpret these theories to determine how work should be allocated between the consultant and the client and the corresponding pricing under different contractual relationships that occur in this industry. We find that, with a pricing schedule that relates the fee adjustment to the self‐service level and one party's ownership of the residual right to specify the workload allocation, the client underinvests her efforts in the service coproduction process, whereas the consultant overinvests his efforts, resulting in an inefficient process. In addition, to improve overall process efficiency, we show that the more productive party should own the residual right to respecify the self‐service level when the final service need emerges. Our results, as well as interview data from experienced consultants, provide insights into the causes of inefficient service delivery processes and offer direction for achieving better efficiency through contract design and pricing schedules.     

不对称信息下线上零售商定价与O2O渠道策略研究

针对由制造商和线上零售商组成的供应链，考虑消费者退货行为以及产品退货会给企业造成退货损失，且线上零售商退货损失为其私有信息，研究不对称信息下的供应链定价、O2O渠道策略以及合同设计问题，分析线上零售商引入O2O渠道的可行条件及其对供应双方最优决策和消费者剩余的影响，考察不对称信息对各个企业、供应链系统利润的影响。研究表明，线上零售商引入O2O渠道存在可行条件，取决于退货损失的大小；当线上零售商引入O2O渠道时，制造商和供应链系统的期望利润水平均能得到有效提升；O2O渠道策略有利于提高消费者剩余，但到体验店体验产品的消费者不一定能够得到更高的消费者剩余；如果满足一定条件，则线上零售商会选择信息共享谈判与制造商共享其私有信息，进而实现"双赢"。     

Profitability of Service‐Level‐Based Price Differentiation with Inventory Rationing

In this paper, we study the profitability of service‐level‐based price differentiation (SLBPD) in an inventory‐rationing context. SLBPD implies that a company offers several combinations of prices and guaranteed service levels, from which customers self‐select; different customers choose different offerings because they incur different shortage costs if an order is not fulfilled immediately. We develop an analytical model for SLBPD and explore if and when such a service differentiation strategy yields higher profits than a single undifferentiated offering. The results of our analyses suggest that SLBPD is profitable only if a company faces pricing restrictions, e.g., because of competitive pressure or regulatory restrictions. We develop necessary and sufficient conditions under which a specific and relevant form of SLBPD (called “service‐level‐based upselling”) is profitable, and provide an algorithm to compute the optimal parameters of such a policy. Based on this algorithm we carry out numerical analyses that allow us to characterize the profit increment of service‐level‐based upselling. We derive managerial insights into the attractiveness of SLBPD and explain how our basic analytical framework can be extended to account for more complex practical features.     

Flexible Capacity Investments and Product Mix: Optimal Decisions and Value of Postponement Options

In this article, we study a firm's interdependent decisions in investing in flexible capacity, capacity allocation to individual products, and eventual production quantities and pricing in meeting uncertain demand. We propose a three‐stage sequential decision model to analyze the firm's decisions, with the firm being a value maximizer owned by risk‐averse investors. At the beginning of the time horizon, the firm sets the flexible capacity level using an aggregate demand forecast on the envelope of products its flexible resources can accommodate. The aggregate demand forecast evolves as a Geometric Brownian Motion process. The potential market share of each product is determined by the Multinomial Logit model. At a later time and before the end of the time horizon, the firm makes a capacity commitment decision on the allocation of the flexible capacity to each product. Finally, at the end of the time horizon, the firm observes the demand and makes the production quantity and pricing decisions for end products. We obtain the optimal solutions at each decision stage and investigate their optimal properties. Our numerical study investigates the value of the postponed capacity commitment option in supplying uncertain operation environments.     

Dynamic Mechanism Design: A Myersonian Approach

We study mechanism design in dynamic quasilinear environments where private information arrives over time and decisions are made over multiple periods. We make three contributions. First, we provide a necessary condition for incentive compatibility that takes the form of an envelope formula for the derivative of an agent's equilibrium expected payoff with respect to his current type. It combines the familiar marginal effect of types on payoffs with novel marginal effects of the current type on future ones that are captured by “impulse response functions.” The formula yields an expression for dynamic virtual surplus that is instrumental to the design of optimal mechanisms and to the study of distortions under such mechanisms. Second, we characterize the transfers that satisfy the envelope formula and establish a sense in which they are pinned down by the allocation rule (“revenue equivalence”). Third, we characterize perfect Bayesian equilibrium‐implementable allocation rules in Markov environments, which yields tractable sufficient conditions that facilitate novel applications. We illustrate the results by applying them to the design of optimal mechanisms for the sale of experience goods (“bandit auctions”).     

Effects of Random Yield in Remanufacturing with Price‐Sensitive Supply and Demand

In this study, we investigate the effects of recovery yield rate on pricing decisions in reverse supply chains. Motivated by the automotive parts remanufacturing industry, we consider an end‐of‐life product from which a particular part can be recovered and remanufactured for reuse, and the remainder of the product can be recycled for material recovery. Both the supply of end‐of‐life products and demand for remanufactured parts are price‐sensitive. Yield of the recovery process is random and depends on the acquisition price offered for the end‐of‐life products. In this setting, we develop models to determine the optimal acquisition price for the end‐of‐life products and the selling price for remanufactured parts. We also analyze the effects of yield variation to the profitability of remanufacturing, benefits of delaying pricing decisions until after yield realization, and value of perfect yield rate information.     

Risk‐Based Sampling: I Don't Want to Weight in Vain

Recently, there has been considerable interest in developing risk‐based sampling for food safety and animal and plant health for efficient allocation of inspection and surveillance resources. The problem of risk‐based sampling allocation presents a challenge similar to financial portfolio analysis. Markowitz (1952) laid the foundation for modern portfolio theory based on mean‐variance optimization. However, a persistent challenge in implementing portfolio optimization is the problem of estimation error, leading to false “optimal” portfolios and unstable asset weights. In some cases, portfolio diversification based on simple heuristics (e.g., equal allocation) has better out‐of‐sample performance than complex portfolio optimization methods due to estimation uncertainty. Even for portfolios with a modest number of assets, the estimation window required for true optimization may imply an implausibly long stationary period. The implications for risk‐based sampling are illustrated by a simple simulation model of lot inspection for a small, heterogeneous group of producers.