The signaling effect of management response in engaging customers: A study of the hotel industry

Published on Oct 1, 2017in Tourism Management10.967
· DOI :10.1016/J.TOURMAN.2017.03.009
Chunyu Li6
Estimated H-index: 6
(Guangdong University of Foreign Studies),
Geng Cui25
Estimated H-index: 25
(Lingnan University),
Ling Peng11
Estimated H-index: 11
(Lingnan University)
Sources
Abstract
Hotels today actively respond to online reviews given their tremendous influence on travelers' decisions. Yet, the questions of how to respond to online reviews continue to baffle hotel managers. By focusing on prospective travelers, we propose the effective management response signals hotels' care for customers and quality of service. Particularly, we postulate the frequency, speed and length of response influence the effectiveness of signaling in reducing information asymmetry. Based on the large-scale field data from TripAdvisor, this study demonstrates that the frequency and speed of response significantly enhance travelers’ engagement as indicated by more reviews, higher average valence, more votes for helpfulness, and higher popularity ranking. Furthermore, the frequent and speedy response is more effective for budget (vs. premium) hotels. Thus, management response to online reviews serves as a critical channel of communication to engage customers.
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Source
#1Roderick J. BrodieH-Index: 56
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Editorial, Roderick J. Brodie, Linda D. Hollebeek and Jodie Conduit Part 1: Engagement Conceptualisations 1. Customer Engagement and Value Co-creation, Matthew Alexander and Elina Jaakkola 2. Economic Outcomes of Customer Engagement: Emerging findings, contemporary theoretical perspectives, and future challenges, Sander F. M. Beckers, Jenny van Doorn and Peter C. Verhoef 3. Partner Engagement: A perspective on B2B engagement, Shiri D. Vivek, Vivek Dalela and Sharon E. Beatty4. Exploring Customer...
Source
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Source
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Source
#1Chung Hun Lee (GMU: George Mason University)H-Index: 7
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