SERVICE SYSTEM DESIGN FOR THE PROPERTY AND CASUALTY INSURANCE INDUSTRY

This paper describes the changes that are forcing property and casualty insurance firms to rethink their service system design and in particular their distribution strategies. A set of questions related to distribution that are uppermost in the minds of executives in this industry are presented along with a literature survey of models that can be used to answer some of these questions. Based on the survey, a normative framework for designing the distribution system is proposed. Qualitative and quantitative analysis based on the proposed framework is presented along with empirical data to demonstrate the usefulness of the framework. The paper concludes with an agenda for further research.     

PIECING TOGETHER SERVICE QUALITY: A FRAMEWORK FOR ROBUST SERVICE*

This paper addresses the issue of service design, specifically that of designing the service encounter for improved quality. We introduce a framework based on the three T's of task, treatment, and tangibles as a means of organizing the application of the diverse and growing body of service quality literature to encounter design. The framework is consistent with how successful service managers disaggregate the design problem. More importantly, we show that mutually supportive interrelationships between the three T's produce an opportunity for designing in a robustness to service failure. The framework is supported by case based evidence.     

A NEW LEARNING APPROACH TO PROCESS IMPROVEMENT IN A TELECOMMUNICATIONS COMPANY

Redesigning and improving business processes to better serve customer needs has become a priority in service industries as they scramble to become more competitive. We describe an approach to process improvement that is being developed collaboratively by applied researchers at US WEST, a major telecommunications company, and the University of Colorado. Motivated by the need to streamline and to add more quantitative power to traditional quality improvement processes, the new approach uses an artificial intelligence (AI) statistical tree growing method using customer survey data to identify operations areas where improvements are expected to affect customers most. This AI/statistical method also identifies realistic quantitative targets for improvement and suggests specific strategies predicted to have high impart. This research, funded in part by the Colorado Advanced Software Institute (CASI) to stimulate profitable innovations, has resulted in a practical methodology used successfully at US WEST to help set process improvement priorities and guide resource allocation decisions throughout the company.     

ADAPTING THE QFD APPROACH TO EXTENDED SERVICE TRANSACTIONS

This paper proposes an adaptation of quality function deployment (qfd) for services, more specifically extended service transactions. We propose two modifications to service applications of Qfd. One is the inclusion of higher-level customer needs (consequences, benefits, experiences, and personal values) to incorporate the experiential and personal nature of extended service transactions into the process. The second modification is to use customers' knowledge and expertise regarding service production and delivery as input beyond the house of quality. An interviewing method is proposed for a comprehensive assessment of customer needs at multiple levels. Results from an empirical application of this technique to luxury business hotels support the proposed modifications to Qfd to increase its potential for application to services.     

PRODUCT AND SERVICE QUALITY: THE ANTECEDENTS OF CUSTOMER LOYALTY IN THE AUTOMOTIVE INDUSTRY

Prior literature has examined product quality and service quality separately as antecedents of customer loyalty. In the context of the automotive industry, we present a framework that examines the simultaneous impact of product and service quality on consumers' purchase intentions. The framework is operationalized as several hypotheses that posit relationships between service quality, service satisfaction, product quality, and customer loyalty. The hypotheses are tested using three sources of data: (i) archival data on product quality and customer purchases, (ii) consumersíresponses to a survey instrument, and (iii) Consumer Reports. Results indicate general support for main hypotheses proposed.     

A LONGITUDINAL STUDY OF THE EFFECT OF A SERVICE GUARANTEE ON SERVICE QUALITY

This paper develops a theoretical framework that relates a service guarantee to service quality. The framework hypothesizes that a service guarantee can positively affect service quality through its positive effect on both learning through service failure and employee motivation and vision. A longitudinal, empirical study was conducted to test these hypotheses. Surprisingly, the service guarantee was not found to have a direct effect on learning through service failure. However, the service guarantee clearly had a positive effect on service quality primarily through its positive effect on employee motivation and vision. The research strongly supports using a service guarantee to improve service quality.     

A MARKET UTILITY‐BASED MODEL FOR CAPACITY SCHEDULING IN MASS SERVICES

Only a small set of employee scheduling articles have considered an objective of profit or contribution maximization, as opposed to the traditional objective of cost (including opportunity costs) minimization. In this article, we present one such formulation that is a market utility‐based model for planning and scheduling in mass services (MUMS). MUMS is a holistic approach to market‐based service capacity scheduling. The MUMS framework provides the structure for modeling the consequences of aligning competitive priorities and service attributes with an element of the firm's service infrastructure. We developed a new linear programming formulation for the shift‐scheduling problem that uses market share information generated by customer preferences for service attributes. The shift‐scheduling formulation within the framework of MUMS provides a business‐level model that predicts the economic impact of the employee schedule. We illustrated the shift‐scheduling model with empirical data, and then compared its results with models using service standard and productivity standard approaches. The result of the empirical analysis provides further justification for the development of the market‐based approach. Last, we discuss implications of this methodology for future research.     

SERVICE PROCESS CONFIGURATIONS IN ELECTRONIC RETAILING: A TAXONOMIC ANALYSIS OF ELECTRONIC FOOD RETAILERS

We developed a taxonomy of service processes in electronic retailing using data from 255 electronic food retailers. The taxonomy is comprised of eight service process configurations. Analysis of publicly available data on on‐line customer ratings for 52 retailers in the study sample shows that the ordering of the configurations in the taxonomy on a continuum of low to high flexibility is associated positively with (i) customer satisfaction with web site aesthetics, web site navigation, product selection, product information, customer support, and ease of return, and (ii) customer loyalty.     

THE MARKET SHARE IMPACT OF SERVICE FAILURES

This paper develops a simple but powerful model that relates service satisfaction/dissatisfaction to market share. The model is based on an intuitive service satisfaction framework that relates three service system parameters (service success rate, complaint rate, and service recovery rate) to the percent of satisfied customers. A dynamic model is then posited that relates the defection rate and the addition rate to market share changes. The service satisfaction/market share model yields useful insights into how market share is influenced by these service system parameters. The surprisingly simple model predicts changes in market share due to changes in customer satisfaction.     

THE MALL IS MY FACTORY: REFLECTIONS OF A SERVICE JUNKIE

This paper presents a personal perspective on the history, current research, and emerging topics in the field of Service Operations Management. I see research in the field evolving from a focus on classifications and operations research models in the 1970s and 1980s, to a current focus on laboratory studies, and survey- and case-based research. Selected current research is presented under the following headings: Service encounter design, service quality, drivers of service competitiveness, yield management, and the information revolution and the globalization of services. Examples of creativity in service delivery and some whimsical characteristics of service junkies are also presented.     

POWER APPROXIMATIONS FOR A TWO-ECHELON INVENTORY SYSTEM USING SERVICE LEVELS

We consider a two-echelon inventory system with one warehouse and several stores. The warehouse as well as the stores are controlled by periodic review (s, S) inventory policies. We study the interrelationship between the safety stocks at the warehouse and the stores. Stockouts at the warehouse will result in supply delays to the stores and cause the lead time to be stochastic. The stores may react by increasing their safety stock. However, there is a trade-off between the safety stock at the warehouse and the safety stock at the stores. We use a service level at the warehouse to quantify the effect of warehouse stockouts on the lead time to the stores. The service level at the warehouse is considered a decision variable to find the best compromise between the various safety stocks by minimizing the overall costs. Using power approximations for the (s, S) policies, we provide an iterative procedure for adjusting the lead time distribution to the stores; this can result in substantial savings, but it doesn't guarantee the overall optimality. Numerical studies are provided to test the accuracy of approximations. The effects of the different system parameters on the inventory policy give general guidelines for use of the policies.     

A DYNAMIC PROGRAMMING MODEL FOR OPTIMAL ALLOCATION OF DECISION TIME

Recurrent decision making by a lower-level manager can be viewed as a sequential decision process in which time and uncertainty are limiting factors. Under these conditions, the manager must determine how to best utilize his decision making time consistent with his own particular set of decision values. A dynamic programming model was devised to determine the optimal (consistent) allocation of decision time among five different types of problems for a sequence of simulated recurrent decision situations. Fifty-one lower-level managers were interviewed about their use of decision time and decision procedures. The model was validated by comparing model assumptions and results with the findings from the interviews. The model was used to determine the effects of variations in the levels of time available and uncertainty upon the optimal allocation of decision time.     

EMPLOYEE DEVELOPMENT: AN EXAMINATION OF SERVICE STRATEGY IN A HIGH‐CONTACT SERVICE ENVIRONMENT

A critical component of service strategy in high‐contact environments is service encounter management. Effective service encounters are a result of the quality of employee development, including systems for work and job design, training and development, and attention to employee well being. Results of empirical analysis indicate that service strategies reflecting the dimensions of employee development drive employee outcomes such as productivity and satisfaction. Employee outcomes are significantly associated with customer satisfaction, but only some linkages to financial performance are significant. This study illustrates the importance of employee development in service strategy design for managing service encounters in high contact service environments.     

A DYNAMIC PROGRAMMING MODEL FOR PERIODICAL SELECTION

This paper presents a model for choosing the periodical collection in a reading room. The model consists of two stages. In the first stage the probability distribution of contacts by users with a given periodical is developed and employed to determine the utility of the periodical. In the second stage the problem of choosing an optimum periodical collection is formulated as a capital budgeting problem and solved with the aid of dynamic programming. The implementation of this model at the University of Connecticut is described in detail.     

APPOINTMENT POLICIES IN SERVICE OPERATIONS: A CRITICAL ANALYSIS OF THE ECONOMIC FRAMEWORK

In this paper we review the literature on appointment policies, specifically in terms of the objective function commonly used and the assumptions made about the behavior of demand. First, we provide an economic framework to analyze the problem. Based on this framework we make a critical analysis of the objective functions used in the literature. We also question the validity of the assumption made throughout the literature that demand is exogenous and independent of customers' waiting times. We conclude that the objective functions used in the literature are appropriate only in the case of a central planner facing a demand that is unresponsive to waiting time. For other scenarios, such as a private server facing a demand that does react to waiting time, these objective functions are only shortcuts for the real objective functions that must be used. A more general model is then proposed that fits these scenarios well. Finally, we determine the impact of using the literature's objective functions on optimal appointment policies.     

SCHEDULING FLEXIBILITY IN THE SERVICE SECTOR: A POSTAL CASE STUDY

This is a case study of workforce scheduling in the U.S. postal system. We use it to analyze the benefits of scheduling flexibility at postal distribution systems, which can come from several sources. We focus on the additional flexibility deriving from increasing the proportion of part-time employees, as well as from increasing the cross-training of part-time employees. These two dimensions of scheduling flexibility are decision points of particular interest to the postal management. We used a large-scale simulation model of the dynamic functioning of the postal distribution system in conjunction with a staff-scheduling model to obtain insights into policy issues of interest. Our results show that the operating environment at a distribution station affects cost and customer service performance, and that gains from greater scheduling flexibility are situationally dependent. The benefit of cross-training part-time workers is modest over the range of levels considered realistic for distribution stations. Our overall recommendation is for postal managers to increase the proportion of part-time employees, allowing more efficient matching of resources with the varying demands for mail delivery on different routes. For the range of conditions we modeled, cost reductions from more part-time workers average over six percent when capacity utilization is low. Customer service improvements are even larger, and range between 20 and 43% when capacity utilization is high. Improvements at the upper end of the range are achieved when demand variability is also at its highest.     

A DISCRETE DYNAMIC OPTIMIZATION MODEL FOR MADE-TO-ORDER COST ANALYSIS

A model is presented that yields optimal production rates for a firm producing a contracted order. The model is unique in that it considers the influence of production rate and learning on total program cost. An application to the specific characteristics of two military production programs is presented. As demonstrated by the application, models of this type may be used as decision-making tools when negotiating the cost impact of contract modifications.     

GREENING THE SERVICE PROFIT CHAIN: THE IMPACT OF ENVIRONMENTAL MANAGEMENT PRACTICES

This paper explores the relationship between environmental practices and performance in services and the impact of such practices on the external portion of the service profit chain. Using structural equation modeling, it tests the hypotheses developed with data from the European hospitality industry. The findings suggest that environmental practices are positively related to performance through the mediating effect of enhanced customer satisfaction and loyalty. The paper's contributions include: the conceptual development of the relationship between environmental practices and performance in services, the incorporation of environmental practices within the service profit chain, and the testing of their impact on customer satisfaction.     

A QUARTET OF SEMIGROUPS FOR MODEL SPECIFICATION,ROBUSTNESS, PRICES OF RISK,AND MODEL DETECTION

A representative agent fears that his model, a continuous time Markov process with jump and diffusion components, is misspecified and therefore uses robust control theory to make decisions. Under the decision maker's approximating model, cautious behavior puts adjustments for model misspecification into market prices for risk factors. We use a statistical theory of detection to quantify how much model misspecification the decision maker should fear, given his historical data record. A semigroup is a collection of objects connected by something like the law of iterated expectations. The law of iterated expectations defines the semigroup for a Markov process, while similar laws define other semigroups. Related semigroups describe (1) an approximating model; (2) a model misspecification adjustment to the continuation value in the decision maker's Bellman equation; (3) asset prices; and (4) the behavior of the model detection statistics that we use to calibrate how much robustness the decision maker prefers. Semigroups 2, 3, and 4 establish a tight link between the market price of uncertainty and a bound on the error in statistically discriminating between an approximating and a worst case model. (JEL: C00, D51, D81, E1, G12)     

A TEST FOR THE DETECTION OF A POISSON PROCESS

A statistical test is presented to detect the presence of a Poisson input source into a queueing system. The fact that the arrival times of a Poisson input source are distributed independently and uniformly over time is used in conjunction with the central limit theorem to develop a test, based on the sum of the arrival times over a given interval of time, for the hypothesis that an input source into a queueing system is Poisson. Failure to reject this hypothesis gives one an extra degree of assurance that traditional queueing models assuming a Poisson input are applicable.