Using hotel reviews to assess hotel frontline employees’ roles and performances

Autor: Feng Hu, Rohit Trivedi, Thorsten Teichert
Rok vydání: 2022
Předmět:
Zdroj: International Journal of Contemporary Hospitality Management. 34:1796-1822
ISSN: 0959-6119
DOI: 10.1108/ijchm-04-2021-0491
Popis: Purpose This study aims to explore how marketers can use text mining to analyze actors, actions and performance effects of service encounters by building on the role theory. This enables hotel managers to use introduced methodology to measure and monitor frontline employees’ role behavior and optimize their service. Design/methodology/approach The authors’ approach links text mining and importance-performance analysis with role theory’s conceptual foundations taking into account the hotel industry’s specifics to assess the effect of frontline hotel employees’ actions on consumer satisfaction and to derive specific management implications for the hospitality sector. Findings This study identifies different actors involved in hotel frontline interactions revealing distinct role behaviors that characterize consumers’ perspectives of service encounters with different role types associated with front-office employees. This research also identifies role performance related to role behavior to improve service encounters. Practical implications Customer–employee interactions can be assessed by user-generated contents (UGC). Performance evaluations relate to frontline employee roles associated with distinct role scripts, whereby different hotel segments require tailored role designs. Insights of this study can be used for service optimization, market positioning as well as for improving human resource management practices in the hotel industry. Originality/value This study contributes to the service encounter literature by applying role theory in the text mining of UGC to assess frontline employees as actors and the effects of their actions on service quality delivery.
Databáze: OpenAIRE