A Comparative Revenue Analysis of Hotel Yield Management Heuristics

Yield management is the dynamic pricing, overbooking, and allocation of perishable assets across market segments in an effort to maximize short-term revenues for the firm. Numerous optimization heuristics for allocation and overbooking exist for the airline industry, whose perishable asset is the airplane seat. When an airplane departs, no revenue is gained from the empty seat(s). In the hotel industry, the perishable asset is the hotel room-once a room is left empty for a night, that night's revenue cannot be recaptured. The literature on yield management heuristics for the hotel industry is sparse. For the hotel operating environment, no research has adequately (1) integrated overbooking with allocation, (2) modeled the phenomenon of hotel patrons extending or contracting their stay at a moment's notice, or (3) performed a realistic performance comparison of alternative heuristics. This research develops (1) two hotel-specific algorithms that both integrate overbooking with the allocation decisions, (2) a simulation model to reproduce realistic hotel operating environments, and (3) compares the performance of five heuristics under 36 realistic hotel operating environments. Seven conclusions are reached with regard to which heuristic(s) perform best in specific operating environments. Generally, heuristic selection is very much dependent on the hotel operating environment. A counterintuitive result is that in many operating environments, the simpler heuristics work as well as the more complex ones.     

服务定制情境下选项的战略呈现:呈现框架对消费者选择的影响

在服务定制情境下,企业可以采用两种不同方式让消费者定制服务包:呈现完整服务包让消费者从中删除不想要的业务(减法式);呈现基本服务包让消费者选择添加所需附加业务(加法式).本研究考察了这两种不同的选项呈现方式对消费者心理反应和选择行为的影响,分析了业务类型与呈现方式之间的交互作用,通过以移动通信服务为背景的实验发现:(1)相对于呈现基本服务包来让消费者进行"加法"定制来说,消费者在完整服务包基础上进行"减法"定制时会选择更多数量和更高总金额的附加服务;(2)选项呈现框架与业务类型之间具有显著的交互作用.相对于减法框架,在加法框架下,实用型业务会比享乐型业务更有可能被选择;而在减法框架下,享乐型业务会比实用型业务更有可能被选择;(3)在减法框架下,消费者的反应时间更长,感知到的决策乐趣更高,对决策结果更不易后悔.但是,两种框架下消费者的心理冲突和决策难度没有显著差别.基于上述研究发现,作者讨论了本研究的理论意义和应用价值,并围绕企业如何通过有效的服务业务组合和战略呈现来创造利润提出了管理建议.     

An Information‐Processing Approach for Evaluating In‐Store Retail Operational Design Strategies

We develop a model to evaluate retail store operational design strategies using an information‐processing perspective of organizational design. We propose that three model constructs pertaining to in‐store shopper task uncertainty—the product mix complexity, the service production complexity, and the product mix changeover—create shopper encounter information requirements (IR). These requirements can be met using specific retail service operational design choices for managing shopper encounters, namely, designing layouts for self‐service (SS) and providing employees with task empowerment (TE). The model is then operationalized using a two‐stage approach to develop new multi‐item, measurement scales. The psychometric properties and predictive validity of the scales and model are then confirmed by using structural equation modeling with survey data from 175 merchandise retail store managers. We find that our model can be generically applied across the retail industry to understand how shopper encounter IR motivate retailer store design choices and can be used to determine whether to design stores for SS or to provide store employees with TE. We then evaluate the efficacy of the studied store design choices on customer delivery satisfaction, and offer some suggestions for future research.     

Reducing Packaging Waste and Cost via Consumer Price Discounts

Low‐waste packaging may imply an inconvenience to consumers and cause firms to offer a compensating price discount. For example, Starbucks’ “Take the Mug Pledge” campaign provides a 10‐cent discount for customers who purchase coffee without a standard cup (i.e., customers provide their own cup). Understanding how such a discount drives demand and profit is the focus of this article. We consider a monopolist that can offer a reduced‐packaging option for its product at a variable cost savings. That option implies a transactional “inconvenience” cost for consumers. While that transactional cost is generally positive, our model also permits some consumers to associate convenience with reduced packaging. We derive the optimal price and discount that maximize profits. We show the optimal discount is bounded by the magnitude of the variable cost savings associated with the packaging reduction. We explore when the optimal discount is negative (a price premium), which requires a specific proportion of consumers to associate convenience with reduced packaging. We also derive conditions under which the firm should price to eliminate demand for the standard product, rather than segment the market, to leverage the variable cost savings of reduced packaging. When the variable cost savings are low (e.g., as is true for Starbucks), we show the profit curve for the segmenting policy is relatively flat for a discount up to several multiples of the cost differential. Finally, we demonstrate the potential for the reduced packaging option, with optimal discounting, to simultaneously increase profit and consumer surplus while reducing waste.     

IMPLICIT OPTIMAL AND HEURISTIC LABOR STAFFING IN A MULTIOBJECTIVE,MULTILOCATION ENVIRONMENT*

This paper presents a tractable set of integer programming models for the days-off scheduling of a mix of full- and part-time employees working α to β days/week (cycle) in a multiple-objective, multiple-location environment. Previous models were formulated to specifically schedule part-time employees working either two or three days per week. These models were intractable because they required complete employee schedule information. The new models are deemed implicit optimal since they are required to supply only essential information. While the number of variables in previous models is an exponential increasing function of β-α, the size of three of the new models is independent of α and β. The first three models developed here (as in [18]) deal with the trade-offs between idle time, the number of employees required to work at multiple “locations,” and the size of the total labor pool. The inherent flexibility of the implicit modeling approach is illustrated by the presentation of various modifications of the basic models. These modifications permit the use of preference weights on the number of employee work days/week (cycle) or the minimization of payroll costs where differential pay rates exist. These latter models may also be formulated such that idle time is ignored, constrained or minimized. The execution time for the implicit models (on a CDC CYBER 730 computer with commercially available software) averaged well under five seconds on 1200 trial problems for the type of application considered in [18]. A solution was obtained in less than 46 seconds of CPU time for a trial problem which would have required over 1.4 million integer variables with previous models. The availability of optimal solutions was invaluable in the development of two heuristics designed to deal with the trade-offs of [16]. In an experimental analysis a previous heuristic produced results which averaged from 74 to 508 percent above optimum across six experimental conditions. The comparable new heuristic produced results which averaged from 3 to 8 percent above optimum for the same experimental conditions. The paper concludes by developing a framework to integrate the results of this research with the tour scheduling problem and by identifying several other areas for related research.     

Optimal and Heuristic Decision Strategies for Integrated Production and Marketing Planning

In this study we examine the effects of integrating production and marketing decisions for a short- to medium-range planning horizon in a profit maximizing firm. We formulate two models for determining price, marketing expenditure, demand or production volume, and lot size for a single product with stable demand when economies of scale are present. The full integration (FI) model simultaneously determines all the decisions involved, while the partial integration (PI) model separates the lot sizing decision from the others, as happens frequently in practice. Geometric programming (GP) techniques and marginal analysis are used to compare FI and PI, and obtain important managerial implications regarding the two models.     

The Value to the Customer of RFID in Service Applications*

This article examines how customer value may be affected by deploying radio frequency identification (RFID) technologies within service environments. Business articles promote operational cost savings and improved inventory management as key benefits of deploying RFID. In response, service firms are using RFID to reengineer service transactions and customer touchpoints. Customers may view these RFID applications to offer both benefits and drawbacks. This article demonstrates that individuals will recognize far more value from RFID service applications than just cost savings and inventory availability. The article analyzes qualitative survey responses on the value gained from RFID to identify a broad list of value objectives—benefits and drawbacks—associated with RFID service applications. The article contributes to academic literature by providing salient value dimensions for return on investment models of service RFID applications and for future empirical analyses of means‐ends and value‐profit chain models. Managers can use the list of dimensions to develop rich business cases for evaluating the benefits and costs from enhancing service operations with RFID. The identified drawbacks also provide managers with a resource for understanding potential risks of RFID applications.     

Dynamic Customer Acquisition and Retention Management

In consulting, finance, and other service industries, customers represent a revenue stream, and must be acquired and retained over time. In this paper, we study the resource allocation problem of a profit maximizing service firm that dynamically allocates its resources toward acquiring new clients and retaining unsatisfied existing ones. The interaction between acquisition and retention in our model is reflected in the cash constraint on total expected spending on acquisition and retention in each period. We formulate this problem as a dynamic program in which the firm makes decisions in both acquisition and retention after observing the current size of its customer base and receiving information about customers in danger of attrition, and we characterize the structure of the optimal acquisition and retention strategy. We show that when the firm's customer base size is relatively low, the firm should spend heavily on acquisition and try to retain every unhappy customer. However, as its customer base grows, the firm should gradually shift its emphasis from acquisition to retention, and it should also aim to strike a balance between acquisition and retention while spending its available resources. Finally, when the customer base is large enough, it may be optimal for the firm to begin spending less in both acquisition and retention. We also extend our analysis to situations where acquisition or retention success rate, as a function of resources allocation, is uncertain and show that the optimal acquisition and retention policy can be surprisingly complex. However, we develop an effective heuristic for that case. This paper aims to provide service managers some analytical principles and effective guidelines on resource allocation between these two significant activities based on their firm's customer base size.     

Service Personnel,Technology, and Their Interaction in Influencing Customer Satisfaction*

Managing both the technologies and the personnel needed for providing high‐quality, multichannel customer support creates a complex and persistent operational challenge. Adding to this difficulty, it is still unclear how service personnel and these new communication technologies interact to influence the customer's perceptions of the service being provided. Motivated by both practical importance and inconsistent findings in the academic literature, this exploratory research examines the interaction of media richness, represented by three different technology contexts (telephone, e‐mail, and online chat), with six customer service representative (CSR) characteristics and their influences on customer satisfaction. Using a large‐sample customer survey data set, the article develops a multigroup structural equation model to analyze these interactions. Results suggest that CSR characteristics influence customer service satisfaction similarly across all three technology‐mediated contexts. Of the characteristics studied, service representatives contribute to customer satisfaction more when they exhibit the characteristics of thoroughness, knowledgeableness, and preparedness, regardless of the richness of the medium used. Surprisingly, while three other CSR characteristics studied (courtesy, professionalism, and attentiveness) are traditionally believed to be important in face‐to‐face encounters, they had no significant impact on customer satisfaction in the technology‐mediated contexts studied. Implications for both practitioners and researchers are drawn from the results and future research opportunities are discussed.     

价格敏感型供应链网络规划模型及其混合遗传算法

针对价格敏感型供应链中,供应价格与批量之间通常具有非线性的函数关系,建立了采购、需求和物流服务环节均具有价格敏感性的多供应商、多配送中心和多零售商的供应链网络规划整数非线性规划INLP模型,设计解决此NP-hard问题的混合遗传算法,以启发式算法修复进化过程中出现的非法染色体,提高算法寻优速度,通过算例及与SAS/OR模块运行结果的比较,验证该算法具有很强的稳定性和高效性。     

Bundling of Vertically Differentiated Products in a Supply Chain*

We consider a supply chain consisting of a single manufacturer and a single retailer. The manufacturer produces a basic and a premium product. If desired, a bundle of the two products might also be produced at a unit bundling cost. We allow either the manufacturer or the retailer to produce the bundle from the component products. All products, however, must be sold exclusively through the retailer. Using game theoretic models, we compare and contrast the equilibrium outcomes under retailer bundling and manufacturer bundling scenarios. We show that under manufacturer bundling, the manufacturer never offers the full product line composed of the basic product, the premium product, and the bundle, at equilibrium; while the same does not hold under retailer bundling. We show that total supply chain profit under retailer bundling weakly dominates that under manufacturer bundling and characterize the region in the parameter space where this domination is strict. We explore an extension where there is a capacity constraint in producing one or both of the component products and characterize the equilibrium outcomes. We show that unlike the infinite capacity case, offering the full product line is an equilibrium outcome under manufacturer bundling when the capacity of the premium good is limited.     

A Stochastic Goal Program for Employee Scheduling*

Deterministic goal programs for employee scheduling decisions attempt to minimize expected operating costs by assigning the ideal number of employees to each feasible schedule. For each period in the planning horizon, managers must first determine the amount of labor that should be scheduled for duty. These requirements are often established with marginal analysis techniques, which use estimates for incremental labor costs and shortage expenses. Typically, each period in the planning horizon is evaluated as an independent epoch. An implicit assumption is that individual employees can be assigned to schedules with as little as a single period of work. If this assumption violates local work rules, the labor requirements parameters for the deterministic goal program may be suboptimal. As we show in this research, this well-known limitation can lead to costly staffing and scheduling errors. We propose an employee scheduling model that overcomes this limitation by integrating the labor requirements and scheduling decisions. Instead of a single, externally determined staffing goal for each period, the model uses a probability distribution for the quantity of labor required. The model is free to choose an appropriate staffing level for each period, eliminating the need for a separate goal-setting procedure. In most cases this results in better, less costly decisions. In addition, the proposed model easily accommodates both linear and nonlinear under- and overstaffing penalties. We use simple examples to demonstrate many of these advantages and to illustrate the key techniques necessary to implement our model. We also assess its performance in a study of more than 1,700 simulated stochastic employee scheduling problems.     

Scheduling to Improve Field Service Quality*

This research addresses the problem of scheduling technicians to travel from customer site to customer site to perform emergency maintenance on office machines, computers, robots, telecommunications equipment, medical equipment, heating/cooling equipment, household appliances, and other equipment. We call this the Traveling Technician Problem (TTP). In its simplest form, the TTP is a multiserver, sequence-dependent, tardiness minimization problem. This research frames the TTP as a service quality maximization problem in which service quality is defined in terms of mean tardiness, mean technician phone response time, mean promise time, and mean response time. Tardiness is defined with respect to contractually guaranteed response times. Industry practice is to use dispatching rules to assign service calls to technicians. This research proposes scheduling procedures to maximize field service quality in a dynamic environment. A simulation experiment was used to compare three dispatching rules and three scheduling procedures for the TTP. The scheduling procedures dominated the dispatching rules on all four service quality measures. The proposed scheduling procedures hold promise for improving service quality in a wide variety of field service organizations and in other scheduling environments as well.     

R&D联盟条件下基于FMGTS评价的R&D项目合作成员选择

针对如何从多个候选R&D联盟成员中选择最理想的R&D项目合作成员问题,提出了一种操作性较强的选择方法。首先通过静态博弈得到了候选R&D联盟成员进行某R&D项目合作时竞标价格的可行区间,在考虑专家采用模糊多粒度语言(fuzzy multi-granularity term sets,FMGTS)进行期望获利度评价的状况下,运用基本语言转换函数将评价信息进行集结,据此确定候选R&D联盟成员的期望获利度和优化的竞标价格。在给出价格满意度与工期满意度公式的基础上,利用效用值法将基于不同满意度下的排名决策信息进行一致化处理,最后采用互补判断矩阵中的排序公式来选择理想的R&D项目合作成员。     

Viability of Auction‐Based Revenue Management in Sequential Markets

The Internet is providing an opportunity to revenue management practitioners to exploit the potential of auctions as a new price distribution channel. We develop a stochastic model for a high‐level abstraction of a revenue management system (RMS) that allows us to understand the potential of incorporating auctions in revenue management in the presence of forecast errors associated with key parameters. Our abstraction is for an environment where two market segments book in sequence and revenue management approaches consider auctions in none, one, or both segments. Key insights from our robust results are (i) limited auctions are best employed closest to the final sale date, (ii) counterbalancing forecast errors associated with overall traffic intensity and the proportion of customer arrivals in a segment is more important if an auction is adopted in that segment, and (iii) it is critically important not to err on the side of overestimating market willingness to pay.     

The Economic Payout Model for Service Guarantees

Service guarantees consist of a promise to a customer (marketing), the delivery of a service to the customer (operations), and actions to appease the customer when service failures happen (recovery). A part of recovery involves offering the customer an economic and/or noneconomic payout when things go wrong. When the economic payout is too high or low, the impact on the organization and the customer is usually negative. Therefore, determining the size of the economic payout is of critical strategic and tactical importance in businesses. Yet, no systematic quantitative methods are found in the literature to help managers determine the economic payout for service failures. The current ways an economic payout is determined are management judgment, the consensus of customer focus groups, competitive benchmarking, and the use of simple expected value methods. In this article, we define the Economic Payout Model for Service Guarantees (EPMSG) that provides an optimal service guarantee economic payout under certain conditions. The EPMSG and its objective function considers customer revenue over the short‐ and long‐term, the cost of creating and providing the service, the cost of recovery, the probability of a service failure, and the probability of customer retention as a function of economic payout. A numerical example is provided of how EPMSG works. Customer retention probability distributions are examined assuming normal and gamma distributions. We end the article by describing the theoretical contributions, model limitations, managerial implications, and opportunities for future research.     

时间约束下不对称信息鲜活农产品供应链应对突发事件协调模型

针对一个由供应商和一个零售商构成的鲜活农产品供应链,在考虑损耗和新鲜度的影响下,假设产品的市场需求为零售价格的非线性函数,零售商成本为私有信息,研究如何协调供应链应对突发事件。 首先,给出了对称信息下供应链协调模型;然后,研究了不对称信息下集权式与分权式供应链的协调机制;再次,研究了在突发事件引起零售商成本分布函数扰动情况下,供应链的最优应对策略。 研究表明,供应链的最优生产计划、最优批发价格和最优零售价格均具有一定的鲁棒性,当突发事件造成零售商期望成本在一定范围内发生扰动时,三者可以保持不变。最后,通过数值仿真验证了相关结论。     

Determining Order Quantity and Selling Price by Geometric Programming: Optimal Solution,Bounds, and Sensitivity*

This paper presents a geometric programming (GP) approach to finding a profit-maximizing selling price and order quantity for a retailer. Demand is treated as a nonlinear function of price with a constant elasticity. The proposed GP approach finds optimal solutions for both no-quantity discounts and continuous quantity discounts cases. This approach is superior to the traditional approaches of solving a system of nonlinear equations. Since the profit function is not concave, the traditional approaches may require an exhaustive search, especially for the continuous discounts schedule case. By applying readily available theories in GP, we easily can find global optimal solutions for both cases. More importantly, the GP approach provides lower and upper bounds on the optimal profit level and sensitivity results which are unavailable from the traditional approaches. These bounding and sensitivity results are further utilized to provide additional important managerial implications on pricing and lot-sizing policies.     

How Long Should a Customer Wait for Service?

A major concern for service managers is the determination of how long a customer should wait to be served. Services, due to the customer's direct interaction with the process, must face a trade-off between minimizing the cost of having a customer wait and the cost of providing good service. A total cost model is presented for determining how long a customer should wait when these two conflicting cost components are considered. An integral part of this model includes a measure of customer satisfaction with waiting time which is used to develop a waiting cost function. The model is then applied to a major fast food chain, using data collected at several locations. Analysis of the data reveals that the “ideal” waiting time for this firm is significantly less than the current corporate waiting time policy. Thus, as indicated by the model, a corporate policy change is recommended to provide much faster service. The adoption of such a policy would result in increased labor costs, and would simultaneously increase the firm's overall profits. Although appearing contradictory, increases in current labor costs and long-term profits are both possible when management takes the long-range perspective suggested in this paper.