Article: An Examination of Alignment of Hotel Brand Differentiation and Customer Priorities: A Case Study of Three Unique Destinations Journal: Journal of Business and Management (JBM) 2023 Vol.28 No.2 pp.61 - 88 Abstract: Purpose - Marketers spend millions to distinguish their properties from the competition via varying marketing paraphernalia; however, online hotel reviews may trump these marketing efforts and create reputational inferences for potential visitors that can run counter to existing corporate branding and positioning. This research has three objectives: 1. To examine the alignment of hotel brand differentiation and customers' perspective through online reviews. 2. To explore whether online reviews are typically general in nature or alternatively, match the uniqueness of the hotels being reviewed. 3. To examine the types of hotels that successfully maintain distinctiveness in online reviews. Method - This study examines online hotel reviews of nine distinctive properties for three different destinations, namely, beach, big city, and eco-tourism locations. The text analysis model is generated to examine 25,579 hotel reviews across three destinations. Text processing and machine learning models were implemented to analyse the online reviews to find similarities and differences between the reviews of the selected distinct locations. The supervised machine learning method is created to predict the correct hotel category based on the text of the review. Findings - The study finding suggests that despite the destination of type of hotel, customers care more about concepts such as 'service', 'room', and 'staff'. Big city luxury hotels were the only contradiction as they focused on their location and customers echoed that in their reviews, but the eco and beach resorts do not offer online reviews that are distinctive from each other. Limitations - As far as limitations are concerned, we only selected the top 5 hotels in each category, and the findings might be biased toward more expensive hotels. For future studies, we would like to use the same methodology on different hotel prices in the same category and see if the results are the same or not. Implications - The study provides evidence into the evolving status of ethical funds. The growing acceptance and popularity of such funds coincide with significantly greater cash inflows into the funds, which may continue to impact the volatility behavior of such assets. Furthermore, the growing worldwide attraction and acceptance of ethical funds may generate sufficient cash inflows so that these funds behave the same way as non-ethical funds in the future. Originality - This research contributes to the literature as it uniquely uses processing and machine learning techniques to compare User-generated Content (UGC) such as online reviews to corporate marketing messaging and brand positioning across three different types of hotels and destinations. Additionally, a new theoretical model of User-generated Content Influence (UGCI) is proposed. Inderscience Publishers - linking academia, business and industry through research

Title: An Examination of Alignment of Hotel Brand Differentiation and Customer Priorities: A Case Study of Three Unique Destinations

Authors: Leili Javadpour; Sacha Joseph-Mathews

Addresses: Author address listing can be found in the "About the Authors" section at the end of the article.

Abstract: Purpose - Marketers spend millions to distinguish their properties from the competition via varying marketing paraphernalia; however, online hotel reviews may trump these marketing efforts and create reputational inferences for potential visitors that can run counter to existing corporate branding and positioning. This research has three objectives: 1. To examine the alignment of hotel brand differentiation and customers' perspective through online reviews. 2. To explore whether online reviews are typically general in nature or alternatively, match the uniqueness of the hotels being reviewed. 3. To examine the types of hotels that successfully maintain distinctiveness in online reviews. Method - This study examines online hotel reviews of nine distinctive properties for three different destinations, namely, beach, big city, and eco-tourism locations. The text analysis model is generated to examine 25,579 hotel reviews across three destinations. Text processing and machine learning models were implemented to analyse the online reviews to find similarities and differences between the reviews of the selected distinct locations. The supervised machine learning method is created to predict the correct hotel category based on the text of the review. Findings - The study finding suggests that despite the destination of type of hotel, customers care more about concepts such as 'service', 'room', and 'staff'. Big city luxury hotels were the only contradiction as they focused on their location and customers echoed that in their reviews, but the eco and beach resorts do not offer online reviews that are distinctive from each other. Limitations - As far as limitations are concerned, we only selected the top 5 hotels in each category, and the findings might be biased toward more expensive hotels. For future studies, we would like to use the same methodology on different hotel prices in the same category and see if the results are the same or not. Implications - The study provides evidence into the evolving status of ethical funds. The growing acceptance and popularity of such funds coincide with significantly greater cash inflows into the funds, which may continue to impact the volatility behavior of such assets. Furthermore, the growing worldwide attraction and acceptance of ethical funds may generate sufficient cash inflows so that these funds behave the same way as non-ethical funds in the future. Originality - This research contributes to the literature as it uniquely uses processing and machine learning techniques to compare User-generated Content (UGC) such as online reviews to corporate marketing messaging and brand positioning across three different types of hotels and destinations. Additionally, a new theoretical model of User-generated Content Influence (UGCI) is proposed.

Keywords: User-generated content; branding; online reviews; hotels and tourism; natural language processing; machine learning.

DOI: 10.1504/JBM.2023.141299

Journal of Business and Management, 2023 Vol.28 No.2, pp.61 - 88

Published online: 05 Sep 2024 *

Title: An Examination of Alignment of Hotel Brand Differentiation and Customer Priorities: A Case Study of Three Unique Destinations

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