Modeling the effects of a service guarantee on perceived service quality using Alternating Conditional Expectations (ACE)

Chee Chuong Sum, Yang Sang Lee, Julie M. Hays, Arthur V. Hill

Research output: Contribution to journalArticlepeer-review

26 Scopus citations

Abstract

This paper addresses the dearth of empirical research on the relationship between service guarantee and perceived service quality (PSQ). In particular, we examine the moderating effects of a service guarantee on PSQ. While a recent study provided empirical evidence that service quality is affected by service guarantee and employee variables such as employee motivation/vision and learning through service failure, the nature and form of the relationships between these variables remain unclear. Knowledge of these relationships can assist service managers to allocate resources more judiciously, avoid pitfalls, and establish more realistic expectations. Data was obtained from employees and customers of a multinational hotel chain that has implemented a service guarantee program in 89 of its hotels in America and Canada. As the employee variables could affect performance in a non-linear fashion, we relaxed the assumption of model linearity by using the Alternating Conditional Expectations (ACE) algorithm to arrive at a better-fitting, non-linear regression model for PSQ. Our findings indicate the existence of significant non-linear relationships between PSQ and its determinant variables. The ACE model also revealed that service guarantee interacts with the employee variables to affect PSQ in a non-linear fashion. The non-linear relationships present new insights into the management of service guarantees and PSQ. Explanations and managerial implications of our results are presented and discussed.

Original languageEnglish (US)
Pages (from-to)347-384
Number of pages38
JournalDecision Sciences
Volume33
Issue number3
DOIs
StatePublished - 2002

Fingerprint

Dive into the research topics of 'Modeling the effects of a service guarantee on perceived service quality using Alternating Conditional Expectations (ACE)'. Together they form a unique fingerprint.

Cite this