Service failures and recovery actions in the hotel industry: A text-mining approach

Abstract

The purpose of this article is to cluster service failures and recovery actions in the hotel industry. Keywords were extracted from the descriptive responses of hotel guests and systematically clustered to identify major areas of service failures and recovery actions in the hotel industry. Two sets of textual data (service failure and service recovery) were collected from 75 hotel guests using the critical incident technique and content-analyzed with a text-mining program. Text-mining analysis identified 50 keywords in eight clusters from the service failure data and 50 keywords in seven clusters from the service recovery data. The identified keywords were conceptually graphed to map meaningful findings that are logically precise and computationally tractable. The major theoretical and practical implications are also discussed in this study.