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.     

Increasing productivity in exponential queues by server-sharing

This paper sets out to investigate the effects of productivity improvements on the operation of queueing systems, the most noticeable effect being a change in the quality of the service that is provided to customers. A bulk-service queueing model is developed and solved, in which the average service time per batch is assumed to increase with the batch size, and the implications for service quality are discussed. The analysis shows that, under certain conditions, the benefits of group service over those of serving customers individually are quite substantial.     

Improving the Utilization of Front-Line Service Delivery System Personnel*

There are two types of work typically performed in services which differ in the degree of control management has over when the work must be done. Serving customers, an activity that can occur only when customers are in the system is, by its nature, uncontrollable work. In contrast, the execution of controllable work does not require the presence of customers, and is work over which management has some degree of temporal control. This paper presents two integer programming models for optimally scheduling controllable work simultaneously with shifts. One model explicitly defines variables for the times at which controllable work may be started, while the other uses implicit modeling to reduce the number of variables. In an initial experiment of 864 test problems, the latter model yielded optimal solutions in approximately 81 percent of the time required by the former model. To evaluate the impact on customer service of having front-line employees perform controllable work, a second experiment was conducted simulating 5, 832 service delivery systems. The results show that controllable work offers a useful means of improving labor utilization. Perhaps more important, it was found that having front-line employees perform controllable work did not degrade the desired level of customer service.     

Customer Use of Virtual Channels in Multichannel Services: Does Type of Activity Matter?

Many firms have recently adopted virtual channels, based most notably on the Internet and the phone, to complement the delivery of services to their customers by their existing physical facilities. The success of such multichannel (MC) strategies relies on the alignment of service design decisions—namely those concerning the allocation of service activities to virtual channels—with customers’ MC behavior. Although prior studies have looked at the intensity with which customers use virtual channels, they have not addressed virtual channel use for different types of service activities. In our study, we investigate whether customers’ use of virtual channels for MC services varies with the type of service activities they engage in, and if so, in what way. In doing so, we address two objectives. First, we investigate the impact of accessibility to the physical channel on the degree of use of virtual channels (Internet and phone, aggregated) for different types of activities. Second, we look at channel preferences (Internet vs. phone) for different types of activities when customers do resort to virtual channels to conduct activities. To address our objectives, we develop and test hypotheses regarding customers’ use of virtual channels based on the match between activity attributes (complexity and volume) and channel attributes (access efficiency, interface efficiency, interface richness). Using data from a MC bank, we find that the impact of accessibility to physical channels (specifically, customer distance) on customers’ use of virtual channels, as well as the relative use of Internet versus phone, depend on the type of activities.     

A Simulation Metamodel for Response-Time Planning*

Field service management continues to be a major challenge for many service organizations as companies are required to provide more service with less resources. Especially in information intense environments, short response times for service calls are essential to avoid disruptions to a business office or production facility. Managers must regularly assess their manpower needs, and ensure that their allocation and operational decisions lead to the best service at the lowest cost. Xerox Corporation provides copiers, duplicators, and printing systems to an international market. Xerox operates a service network consisting of over 30,000 trained service personnel, each allocated to service regions by the service planning staff. Response-time planning involves many challenging problems: requirements planning at the national level, allocation planning at the district level, and operational planning at the team level. Customer service is critical and is commonly measured by response time—the time that elapses from when a service call is placed to when a service engineer begins service. This paper discusses how Xerox Corporation has used simulation models and metamodels to improve response-time planning and field service operations.     

An Analysis of the Production Line versus the Case Manager Approach to Information Intensive Services*

The production line approach has been beneficially used in manufacturing companies to yield consistent-quality standard products at relatively low cost. For this reason, service firms have also employed this approach, which embodies a division of labor, sequential flow processes, and standardization of services. Today's customers, however, are demanding customized services and shorter cycle times—outcomes that the production line approach finds difficult to achieve. An alternative process design proposed for information intensive services is the emerging “case manager” approach, in which all the steps required to deliver a service are performed by a single information technology-enabled individual. This paper uses queuing theory to compare the waiting time performance of the production line and the case manager approaches. This comparison shows that when the number of process steps under the production line approach is relatively large, the relative efficiency of the case manager is sufficiently high, system utilization rate is moderate, and the size of staff downsizing is small, the case manager approach is preferred. Critical issues for the design of enabling information technology are then discussed. The paper concludes with suggestions for future research on the case manager approach.     

A Service Quality Process Map for Credit Card Processing

Evaluating marketing (external) and operations (internal) service quality performance in most organizations is a data-oriented management task that involves many variables for many different types of services. These two diverse sets of service quality information seldom “match up well” because the marketing and operations functions define and evaluate service quality “their way.” Management's interpretation of what the data “mean” often contributes to extra meetings, unnecessary disagreements within and between functional areas, and poor decision making. This situation can affect the quality and timing of decisions, and ultimately, the organization's profitability and market share. This paper quantitatively relates the customer's evaluation (perception) of service quality directly to the activities and performance criteria of the service delivery process for a credit card processing center. Basic statistical analyses and a recursive path analysis model define the relationships between marketing- and operations-based service quality information. The idea of a “service quality process map” is introduced. A service quality process map relates a flowchart of the service delivery process to the customer's perception of service using the power of multivariate data analysis. Management insights gained from an analysis of marketing (external) and operations (internal) measures of service quality performance can be used to allocate resources wisely. The objective is to gain the most improvement in the customer's perception of service for the least cost. Service quality with this type of evaluation capability can be used to gain competitive advantage in the marketplace.     

Management Policies to Improve the Effectiveness of Multi-Station Service Organizations*

A SLAM based simulation model of a multi-station, tandem queuing structure characteristic of a variety of service systems is employed to test various design options for the system. The model is based on an extensive study of the State of Florida driver licensing offices. The multiple objectives of low time in the system for customers and the efficient use of personnel resources are employed to measure the benefits of policy options. The use of simulation analysis permits the incorporation of complex system characteristics, therefore providing a realistic representation of the effects of possible management actions. Effective methods to control labor in such systems are suggested.     

Managing Internet Product Returns: A Focus on Effective Service Operations

Product returns present one of the biggest operational challenges in the world of Internet retailing due to the sheer volume and cost of processing returns. But returns also represent an often‐missed opportunity to manage customer relationships and build customer loyalty to the retailer. Based upon data from a survey of 464 customers of five different Internet retailers, this article explores how firms' returns management systems affect loyalty intentions. We draw upon extant literature in the fields of Internet retailing, service quality, supply chain management, and customer satisfaction/loyalty to develop a model and a set of hypotheses relating ten latent variables in the service returns offering area. Our resulting structural equation model provides evidence of the impact of the returns management system upon customer loyalty intentions. The model also identifies effects on loyalty intentions arising from customers' satisfaction with, and perceptions of, the value of the returns service offered. These findings will help inform managers' choices regarding investment in the returns management system as an element of service quality improvement and a potential means of improved profitability. In addition, this study's empirical exploration and testing of a returns management model in the Internet retailing environment is a contribution to the currently underrepresented body of academic literature linking marketing and supply chain management in the context of end consumers.     

Service Systems with Experience‐Based Anecdotal Reasoning Customers

The existing queueing literature typically assumes that customers either perfectly know the expected waiting time or are able to form rational expectations about it. In contrast, in this article, we study canonical service models where customers do not have such full information or capability. We assume that customers lack full capability or ample opportunities to perfectly infer the service rate or estimate the expected waiting time, and thus can only rely on past experiences and anecdotal reasoning to make their joining decisions. We fully characterize the steady‐state equilibrium in this service system. Compared with the fully rational benchmark, we find that customers with anecdotal reasoning are less price‐sensitive. Consequently, with a higher market potential (higher arrival rate), a revenue‐maximizing firm may increase the price if the service rate is exogenous, and it may decrease the price if the service rate is at the firm's discretion. Both results go against the commonly accepted pricing recommendations in the fully rational benchmark. We also show that revenue maximization and welfare maximization lead to fundamentally different pricing strategies with anecdotal reasoning, whereas they are equivalent in the fully rational benchmark.     

基于“云排队”的经济效益分析

随着各种云智能排队预约系统的推出，顾客“排队难”的问题得到了极大的缓解。其简便的操作方式，受到了大量商家与顾客的好评。本文基于当下热门服务行业的运营模式，建立排队博弈模型，从理论上分析了“云排队”平台对顾客以及服务商的影响。本文主要得到了以下几个结果：(1) 给出了两类顾客的纳什均衡策略(包括进队策略与最优到达间隔)；(2) 发现当前的预约机制能够提高“线上”顾客的效用，并刺激更多的线上顾客购买该产品，但同时也降低了“线下”顾客的进队意愿；(3) 发现在云排队机制下服务商的收益将大大提高，同时该机制将刺激服务商收取更高的服务费用。     

An Experimental Comparison of Dispatching Rules for Field Service Support*

Field service repair management is increasing in importance as “high tech” machines such as computers, communication systems, and copy machines are becoming more popular and more widely disbursed geographically. Complicating the management of these systems are response time performance guarantees (e.g., 8-hour response time), which are a popular marketing tool for many field service businesses [21]. These response time), guarantees especially complicate the field service dispatching problem. With response time guarantees, dispatchers must consider travel times and other issues to determine which call should be assigned to an available technician. This research proposes several dispatching rules that might be applied for dispatching sequential-trip technicians in this environment and compares these rules in a simulation experiment to determine which rule is best in terms of average tardiness. The proposed composite travel time-expiration time rule was found to be the best on average tardiness performance and on all other tardiness-related measures. Given the increased importance of tardiness performance in field service organizations, the proposed composite rule appears to have promise.     

THE HARMS SHOE COMPANY: DEVELOPMENT OF A COMPUTER MODEL FOR THE CLASSROOM

This paper describes a case that examines five key topics in production and operations management [1]—forecasting, inventory control, transportation planning, aggregate planning, and the disaggregation of the aggregate plan—in an integrated, realistic manner for upper-level undergraduate business majors [3]. The case structure stresses the linkage of these interrelated subjects and supplements the regular classroom presentations dealing with them. The case relies on computer calculations at each stage to provide the information input for calculations at the next stage. It is a static model with a twelve-month planning horizon. Students complete several exercises and assume several roles as the case unfolds. They act on their own in filling some roles and as members of teams in performing others. They do not compete with each other, as the purpose of the case is to help them develop an appreciation of the factors that persons performing the role must consider.     

An Industrial Ocean-Cargo Shipping Problem

This paper reports the modeling and solution of an industrial ocean-cargo shipping problem. The problem involves the delivery of bulk products from an overseas port to transshipment ports on the Atlantic Coast, and then over land to customers. The decisions made include the number and the size of ships to charter in each time period during the planning horizon, the number and location of transshipment ports to use, and transportation from ports to customers. The complexity of this problem is compounded by the cost structure, which includes fixed charges in both ship charters and port operations. Such a large scale, dynamic, and stochastic problem is reduced to a solvable stationary, deterministic, and cyclical model. The process of modeling the problem and the solution of the resultant mixed integer program are described in detail. Recommendations from this study have been implemented.     

Practical scheduling for call center operations

A practical spreadsheet-based scheduling method is developed to determine the optimal allocation of service agents to candidate tour types and start times in an inbound call center. A stationary Markovian queueing model with customer abandonment is employed to determine required staffing levels for a sequence of time intervals with varying call volumes, handling times, and relative agent availabilities. These staffing requirements populate a quadratic programming model for determining the distribution of agent tours that will maximize the fraction of offered calls beginning service within a target response time, subject to side constraints on tour type quantities. The optimal distribution is scaled to reflect the total number of scheduled agents, and a near-optimal integer solution is derived using rounding thresholds found by successive one-dimensional searches. This novel approach has been successfully implemented in large service centers at Qwest Communications and could easily be adapted to other operational environments.     

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.     

Does a Supplier's Operational Competence Translate into Financial Performance? An Empirical Analysis of Supplier–Customer Relationships

We conduct an empirical investigation of how a supplier's operational competence, as reflected by outcomes in the areas of quality, cost, delivery, flexibility, and new product development, translates into financial gains from a key customer. In contrast to previous research directed at the firm level, this study focuses on the supplier–customer relationship level. Using survey data from 158 suppliers in the manufacturing industry, we perform structural equation modeling to map out the paths from operational competence to financial performance—via dependencies and cooperative behaviors between suppliers and their customers. This study is the first scholarly attempt to examine the link between suppliers’ operational competencies and financial performance in interorganizational relationships. It is also an early investigation into operational competence as a source of bi‐lateral dependence. Our findings show that the supplier's operational competences increase its customer's dependence by enhancing the value of its products/services. However, the resulting increase in the supplier's power is not leveraged to shape relationship behaviors or capture value from its customer. In contrast, the customer's existing power as a major buyer plays an important role in shaping cooperative behaviors and affecting the supplier's financial performance from the customer relationship.     

Schedule Recovery: Unplanned Absences in Service Operations*

The U.S. service sector loses 2.3% of all scheduled labor hours to unplanned absences, but in some industries, the total cost of unplanned absences approaches 20% of payroll expense. The principal reasons for unscheduled absences (personal illness and family issues) are unlikely to abate anytime soon. Despite this, most labor scheduling systems continue to assume perfect attendance. This oversight masks an important but rarely addressed issue in services management: how to recover from short‐notice, short‐term reductions in planned capacity. In this article, we model optimal responses to unplanned employee absences in multi‐server queueing systems that provide discrete, pay‐per‐use services for impatient customers. Our goal is to assess the performance of alternate absence recovery strategies under various staffing and scheduling regimes. We accomplish this by first developing optimal labor schedules for hypothetical service environments with unreliable workers. We then simulate unplanned employee absences, apply an absence recovery model, and compute system profits. Our absence recovery model utilizes recovery strategies such as holdover overtime, call‐ins, and temporary workers. We find that holdover overtime is an effective absence recovery strategy provided sufficient reserve capacity (maximum allowable work hours minus scheduled hours) exists. Otherwise, less precise and more costly absence recovery methods such as call‐ins and temporary help service workers may be needed. We also find that choices for initial staffing and scheduling policies, such as planned overtime and absence anticipation, significantly influence the likelihood of successful absence recovery. To predict the effectiveness of absence recovery policies under alternate staffing/scheduling strategies and operating environments, we propose an index based on initial capacity reserves.     

Modeling and Managing the Percentage of Satisfied Customers in Hidden and Revealed Waiting Line Systems

We perform an analysis of various queueing systems with an emphasis on estimating a single performance metric. This metric is defined to be the percentage of customers whose actual waiting time was less than their individual waiting time threshold. We label this metric the Percentage of Satisfied Customers (PSC.) This threshold is a reflection of the customers' expectation of a reasonable waiting time in the system given its current state. Cases in which no system state information is available to the customer are referred to as “hidden queues.” For such systems, the waiting time threshold is independent of the length of the waiting line, and it is randomly drawn from a distribution of threshold values for the customer population. The literature generally assumes that such thresholds are exponentially distributed. For these cases, we derive closed form expressions for our performance metric for a variety of possible service time distributions. We also relax this assumption for cases where service times are exponential and derive closed form results for a large class of threshold distributions. We analyze such queues for both single and multi‐server systems. We refer to cases in which customers may observe the length of the line as “revealed” queues.“ We perform a parallel analysis for both single and multi‐server revealed queues. The chief distinction is that for these cases, customers may develop threshold values that are dependent upon the number of customers in the system upon their arrival. The new perspective this paper brings to the modeling of the performance of waiting line systems allows us to rethink and suggest ways to enhance the effectiveness of various managerial options for improving the service quality and customer satisfaction of waiting line systems. We conclude with many useful insights on ways to improve customer satisfaction in waiting line situations that follow directly from our analysis.     

The Importance of Social Embeddedness: Churn Models at Mobile Providers

This article argues the importance of social embeddedness at mobile providers by examining the effects of customers’ network topological properties on churn probability—the probability of a customer switching from one telecommunication provider to another. This article uses data from regional snowball sampling—the only practically feasible network sampling method—to identify groups with significantly different churn ratios for customers with different network topological properties. Clear evidence indicates that individual network characteristics (node‐level metrics) have considerable impact on churn probabilities. The inclusion of network‐related measures in the churn model allows a longer‐term projection of churners and improves the predictive power of the model. With no possibility to carry out repeated sampling, sample stability was checked through simulation results. On the one hand, this article highlights the importance and effectiveness of the provider's tailored marketing campaigns by showing that customers targeted by direct marketing campaigns are less threatened by churn than nontargeted customers. On the other, this article shows that social embeddedness blocks the impact of the very same marketing efforts. This article forwards the idea that social embeddedness, also prevalent in vendor switching, can be extended to understanding the development of professional societies threatened by membership churn.