Ana Isabel Lopes, Edward C. Malthouse, Nathalie Dens, Patrick De Pelsmacker
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Therefore, this study tests whether and how several webcare strategies affect hotel bookings.</p><!--/ Abstract__block -->\n<h3>Design/methodology/approach</h3>\n<p>We apply machine learning classifiers to secondary data (webcare messages) to classify webcare variables to be included in a regression analysis looking at the effect of these strategies on hotel bookings while controlling for possible confounds such as seasonality and hotel-specific effects.</p><!--/ Abstract__block -->\n<h3>Findings</h3>\n<p>The strategies that have a positive effect on bookings are directing reviewers to a private channel, being defensive, offering compensation and having managers sign the response. Webcare strategies to be avoided are apologies, merely asking for more information, inviting customers for another visit and adding informal non-verbal cues. Strategies that do not appear to affect future bookings are expressing gratitude, personalizing and having staff members (rather than managers) sign webcare.</p><!--/ Abstract__block -->\n<h3>Practical implications</h3>\n<p>These findings help managers optimize their webcare strategy for better business results and develop automated webcare.</p><!--/ Abstract__block -->\n<h3>Originality/value</h3>\n<p>We look into several commonly used and studied webcare strategies that affect actual business outcomes, being that most previous research studies are experimental or look into a very limited set of strategies.</p><!--/ Abstract__block -->","PeriodicalId":48089,"journal":{"name":"Journal of Service Management","volume":"2 1","pages":""},"PeriodicalIF":7.8000,"publicationDate":"2024-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Is webcare good for business? 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Is webcare good for business? A study of the effect of managerial response strategies to online reviews on hotel bookings
Purpose
Engaging in webcare, i.e. responding to online reviews, can positively affect consumer attitudes, intentions and behavior. Research is often scarce or inconsistent regarding the effects of specific webcare strategies on business performance. Therefore, this study tests whether and how several webcare strategies affect hotel bookings.
Design/methodology/approach
We apply machine learning classifiers to secondary data (webcare messages) to classify webcare variables to be included in a regression analysis looking at the effect of these strategies on hotel bookings while controlling for possible confounds such as seasonality and hotel-specific effects.
Findings
The strategies that have a positive effect on bookings are directing reviewers to a private channel, being defensive, offering compensation and having managers sign the response. Webcare strategies to be avoided are apologies, merely asking for more information, inviting customers for another visit and adding informal non-verbal cues. Strategies that do not appear to affect future bookings are expressing gratitude, personalizing and having staff members (rather than managers) sign webcare.
Practical implications
These findings help managers optimize their webcare strategy for better business results and develop automated webcare.
Originality/value
We look into several commonly used and studied webcare strategies that affect actual business outcomes, being that most previous research studies are experimental or look into a very limited set of strategies.
期刊介绍:
The Journal of Service Management (JOSM) centers its scope on research in service management. It disseminates papers showcasing distinctive and noteworthy contributions to service literature, serving as a communication platform for individuals in the service management field, transcending disciplines, functional areas, sectors, and nationalities. The journal publishes double-blind reviewed papers emphasizing service literature/theory and its practical applications.