Measurement of tourist satisfaction with restaurant services: A segment-based approach

TLDR

The tourist market is heterogeneous, yet segment‑specific satisfaction studies are scarce. The study aimed to segment tourists by dining experience, examine differing satisfaction determinants across segments, and assess whether segmentation yields simpler predictive models. The authors used factor analysis to identify service dimensions, cluster analysis to form homogeneous groups, and regression to assess each dimension’s influence on segment satisfaction. Five dining segments emerged, each with unique satisfaction drivers, and segment‑level models explained more variance than aggregate models, highlighting the value of segmentation.

Abstract

It is widely recognised that the tourist market is not homogeneous. Yet segment-specific satisfaction analysis has received inadequate attention both from researchers and managers. Focusing on tourists’ dining experiences, this study investigated whether tourists could be grouped into distinct segments; whether the composition of variables determining customer satisfaction differed among the identified segments; and whether market segmentation strategy could contribute to more parsimonious satisfaction prediction models. Factor analysis was performed to determine dimensions that are likely to influence tourist restaurant selection and evaluations, whereas cluster analysis was employed to identify homogeneous groups of respondents. Multiple regression analyses were then employed to examine the relative importance of service dimensions in determining satisfaction judgments of each segment. Based on the analyses, five distinct dining segments were identified. Different sets of service dimensions appeared to affect satisfaction judgments. Greater variation in satisfaction was explained when analysis was undertaken at market segment level compared to aggregate market level. Management and marketing implications of the study are discussed.