A Novel Categorization of Key Predictive Factors Impacting Hotels’ Online Ratings: A Case of Makkah

Harman Preet Singh () and Ibrahim Abdullah Alhamad
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Harman Preet Singh: Department of Management and Information Systems, College of Business Administration, University of Ha’il, P.O. Box 2440, Ha’il 81451, Saudi Arabia
Ibrahim Abdullah Alhamad: Department of Management and Information Systems, College of Business Administration, University of Ha’il, P.O. Box 2440, Ha’il 81451, Saudi Arabia

Sustainability, 2022, vol. 14, issue 24, 1-25

Abstract: In the present Internet age, customers have turned to online booking websites to meet their demand for quality hotel services and convey their experiences. As hotels can survive and succeed by satisfying consumers and obtaining high online ratings, this research predicts the key factors impacting these ratings. The study analyzes online consumer review data gleaned from the popular Booking.com website for hotel ratings near the key religious heritage site in Makkah, Saudi Arabia. The research applies the four-factor theory due to its importance in studying consumer satisfaction and prior non-application to the hospitality and tourism industry. This theory extended the two-factor theory to report four distinct sets of factors: satisfiers, dissatisfiers, criticals, and neutrals. Accordingly, the present research presents a novel categorization of key predictive factors and enriches the literature, which categorized factors as either satisfiers or dissatisfiers. Consequently, facilities and comfort are critical factors, while cleanliness, staff, and location are satisfiers; the value for the money spent is dissatisfier; the availability of breakfast and restaurants are neutral factors. The hospitality industry, specifically the hotel industry, can focus on characteristics of the four distinct sets of factors; various nations can leverage the findings to boost their hospitality and tourism sectors.

Keywords: consumer online hotels’ ratings; categorization; data mining; electronic word of mouth; hotels’ online travel reviews; online user generated content; prediction (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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