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The Design of Experiential Service Processes

Abstract

For many consumer-intensive (B2C) services, delivering memorable customer experiences to maximize customer satisfaction can be a source of competitive advantage since firms that deliver outstanding customer experience achieve greater customer satisfaction, and therefore greater customer loyalty. Yet, there is no clear methodology available for service encounter design that accounts for customer behavior. This dissertation shows how experiential services should be sequenced and timed to maximize satisfaction of customers who are subject to memory decay and acclimation.

The objective of the problem addressed in this thesis is to maximize the total remembered utility of customers from their experience of the service encounter. We consider service encounters where the service provider can alter either the sequence or the duration of activities across the encounter. In particular, we consider three stylized models of service encounters, (i) variable sequence and fixed duration (VSFD), (ii) fixed sequence and variable duration (FSVD), and (iii) variable sequence and variable duration (VSVD). The thesis is organized as follows.

The first chapter introduces the motivation behind the research question and the assumptions made to model the problem. The rationale for addressing the specific behavioral phenomena of memory decay and acclimation is also explained in this chapter.

This thesis draws on research from multiple disciplines. The second chapter provides an extensive literature review, spanning the areas of psychology, behavioral economics, decision theory, marketing, and operations management.

In chapter three, a mathematical model of customer satisfaction that includes the effect of acclimation and memory decay is introduced. Several empirical research papers have studied the satisfaction obtained from experiences by people subject to the effects of memory and adaptation. Our analytical model for total remembered utility is further validated by comparing its outcome with the reported results obtained from these experiments.

Chapter four discusses the three scenarios of service encounters mentioned above, (i) VSFD, (ii) FSVD, and (iii) VSVD. Analytical results indicate that memory decay favors positioning the highest service level near the end, whereas acclimation favors maximizing the gradient of service level. Although memory decay and acclimation lead to the same design individually, they can act as opposing forces when considered jointly.

Taken, together, they maximize the gradient of service level near the end, which may

result in (i) sequencing activities in a U-shaped fashion and (ii) lengthening the duration of

activities with the lowest service levels.

Chapter five discusses three heuristics for sequencing and duration allocation to design the service encounter. These heuristics are based on the analytical characterization of the optimal sequence and timing of activities derived in chapter three. The performance of the heuristics is benchmarked against the true optimum for small problem instances of VSFD and FSVD. For VSVD, the heuristic is benchmarked against an upper bound.

Chapter six discusses two extensions of the service provider's design problem, (i) endogenous service levels, and (ii) service design for a population of customers who are heterogeneous in terms of their rates of acclimation and memory decay.

In case of endogenous service levels we assume that every activity can be assigned a service level within a range, by the service provider. The sequence and duration of activities is assumed to be fixed. The results indicate that it is optimal to allocate activities towards the end of the service encounter a higher service level, and the activities near the beginning of the encounter a lower service level.

For heterogeneous customers we find that the sequence and duration allocation rules that are optimal for homogeneous customers are now not always optimal. For this scenario we numerically test the robustness of the service design that is optimal for homogeneous customers. We find that the sequence that is optimal for the mean value of the rates of acclimation and memory decay for the entire population of customers, serves as a good heuristic in the heterogeneous case.

Finally, in chapter seven we conclude by providing an overview of the results and provide directions for future research. The Appendix provides detailed proofs for analytical results.

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