Multisensory experience for enhancing hotel guest experience: Empirical evidence from big data analytics

Abstract

Purpose

This study aims to investigate the effect of customers’ multisensory service experience on customer satisfaction with cognitive effort and affective evaluations using big data and business intelligence techniques.

Design/methodology/approach

Online customer reviews for all New York City hotels were collected from Tripadvisor.com and analyzed through business intelligence and big data analytics techniques including data mining, text analytics, sentiment analysis and regression analysis.

Findings

The current study identifies the relationship between affective evaluations (i.e. positive affect and negative affect) and customer satisfaction. Research findings also find the negative effect of reviewer’s cognitive effort on satisfaction rating. More importantly, this study demonstrates the moderating role of multisensory experience as an innovative marketing tool on the relationship between affect/cognitive evaluation and customer satisfaction in the hospitality setting.

Originality/value

This study is the first study to explore the critical role of sensory marketing on hotel guest experience in the context of hotel customer experience and service innovation, based on big data and business intelligence techniques.

Citation

Lee, M., Lee, S.(A). and Koh, Y. (2019), "Multisensory experience for enhancing hotel guest experience: Empirical evidence from big data analytics", International Journal of Contemporary Hospitality Management, Vol. 31 No. 11, pp. 4313-4337. https://doi.org/10.1108/IJCHM-03-2018-0263