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Guest Comments on Online Travel Agents Regarding the Front Office Department Service at Melia Bali Hotel

Introduction

Guest comments on online travel agents regarding the front office department service at melia bali hotel. Evaluate Melia Bali's Front Office service via OTA guest comments (2018-2023). Uncover positive (quick check-in, friendly staff) and negative (slow check-in, reservation issues) feedback to boost guest satisfaction.

Abstract

This research aims to evaluate guest comments on Online Travel Agents (OTAs) regarding the Front Office Department service at Melia Bali Hotel, Indonesia. The study uses a descriptive qualitative research method to assess guest comments obtained from OTA platforms such as Tripadvisor, Booking.com, and Tiket.com during the period from 2018 to 2023. Data collection techniques for this research involve observation and documentation, focusing on analyzing guest comments and identifying patterns in guest expectations regarding the Front Office Department service. The results indicate that there are positive comments related to the quick check-in and check-out processes, staff friendliness, and prompt service. Conversely, negative comments were found regarding slow check-in processes, reservation discrepancies, and a lack of information about hotel facilities. Based on these findings, it is hoped that recommendations can be made to improve the Front Office Department service at Melia Bali Hotel, thereby enhancing guest satisfaction and serving as a reference for future research in the hospitality field, particularly concerning the evaluation of positive and negative guest comments on OTAs regarding Front Office Department services.

Review

This study embarks on a pertinent and practical evaluation of guest comments concerning the Front Office Department service at Melia Bali Hotel, drawing data from prominent Online Travel Agent (OTA) platforms. The descriptive qualitative approach, analyzing guest feedback from Tripadvisor, Booking.com, and Tiket.com over a five-year period (2018-2023), offers a valuable snapshot into customer perceptions. The research successfully identifies specific areas of strength, such as efficient check-in/out processes and staff friendliness, alongside critical weaknesses like slow check-in, reservation discrepancies, and inadequate information dissemination. This direct linkage of online feedback to operational performance provides clear, actionable insights for the hotel and serves as a commendable application of readily available public data. A significant strength of this research lies in its practical utility and direct relevance to the hospitality industry. By systematically categorizing and analyzing guest comments from multiple OTAs, the study demonstrates a robust method for hotels to monitor and understand their service performance from the customer's perspective. The identified positive and negative themes are concrete, enabling the Melia Bali Hotel to pinpoint areas for immediate improvement and to reinforce existing service excellences. Furthermore, the long data collection period enhances the reliability of the findings, capturing trends and consistent feedback rather than isolated incidents, thus offering a more comprehensive understanding of guest expectations regarding Front Office services. While the study offers valuable insights, the abstract leaves room for questions regarding the depth of its qualitative analysis and potential methodological refinements. A more explicit description of how "patterns in guest expectations" were identified, beyond mere categorization of positive and negative comments, would enhance the methodological rigor (e.g., detailing thematic analysis or content analysis procedures). Additionally, acknowledging potential limitations inherent in OTA data, such as reviewer bias, the self-selection of reviewers, or the varying levels of detail in comments, would provide a more balanced perspective. Future research building on this foundation could explore the *frequency* or *intensity* of specific comments to provide further weighting, or compare these online sentiments with internal guest satisfaction metrics to validate findings and uncover discrepancies, thereby offering an even more comprehensive understanding of service quality.

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