Guest Reviewers Research Articles

Technological innovations and preexisting markets: The interaction between Airbnb and New York’s hotel and housing markets

AbstractThis paper analyzes the interaction between Airbnb and two traditional markets in New York City, long‐term rentals and hotels, to investigate whether Airbnb is a substitute to either one. Using data from InsideAirbnb, the American Community Survey (ACS), Zillow Research, and the City Planning Primary Land Use Tax Lot Output (PLUTO), we estimate three different models: (i) a fixed effect panel data model relating the number of listings to the number of hotels and socioeconomic variables; (ii) hedonic price regressions relating long‐term rents to the number of Airbnb host listings and prices; and (iii) a simultaneous equation model of supply and demand for long‐term rentals where rental supply and demand are functions of Airbnb nightly rates. We find that: (i) the numbers of host listings and guest reviews are higher in neighborhoods with higher concentration of hotels; (ii) there is a positive relationship between long‐term rents and both the number of Airbnb listings and Airbnb rates; (iii) the supply‐and‐demand simultaneous equations model shows a negative relation between the supply of properties for rent and Airbnb nightly rates; and (iv) the supply‐and‐demand simultaneous equations model shows a positive relationship between the demand for rentals and Airbnb nightly rates. These results are consistent with Airbnb being a substitute to both hotels and long‐term housing rentals.

AN ETNOGRAPHY EXAMINATION OF TRIPADVISOR REVIEWS: A CASE STUDY OF THE ST REGIS HOTEL KUALA LUMPUR

There has been a growing reliance on consumer-generated content as a source of knowledge for hospitality product decision-making. People post their views, ratings, and reviews of products and services on such platforms, and companies and research organizations are interested in analyzing and extracting all of the comments. Hotels must take advantage of online customer review information to better understand their customers and enhance hotel efficiency. However, analyzing guest reviews is challenging as it contains abundant data. Using The St Regis Kuala Lumpur as a case study, the objective of the paper is to 1) profile the online hotel reviews using netnography approach, (2) identify the hotel attributes that guests comment on based on the hotel online reviews and (3) examine the guest satisfaction attitude based on the online hotel reviews. A total of 388 reviews ranging from TripAdvisor were collected. The finding revealed that most hotel guests who left comments were international tourists, couples and left an excellent rating for the hotel. The result shows nine attributes are frequently mentioned; amenities, location, price, service, cleanliness, food and beverages, hotel and room environment. The results also show that guests left positive and negative reviews in a few common categories: hotel cleanliness, hotel environment, and amenities. Among all the attributes, satisfied guests tend to leave positive comments in hotel cleanliness, hotel and room setting, while dissatisfied guests emphasise amenities. The findings from this study make several theoretical and managerial implications regarding identifying hotel attributes that generate guest satisfaction and understanding of satisfied and dissatisfied guests using comments left by guest. The paper concludes with limitations and suggests future research.

Effectiveness of structural equation modeling to measure hotel customer satisfaction

Although some studies on gauging hotel guests' levels of satisfaction have been published in several research findings, structural equation modeling's efficacy in Indonesia is still rarely investigated. The study's objective is to assess hotel patron satisfaction utilizing an electronic system for guest reviews that is centered on online and Internet technology. The research's data came from 500 hotel guests staying at two five-star full-service hotels in Medan, North Sumatra. To accomplish this goal, the study used structural equation modeling to uncover the inherent link between consumer assessments of hotel services and amenities on one side and perceived usefulness, contentment, and their intention to return and refer customers on the other side. The findings demonstrate the clear correlations between value, contentment, desire to return and suggest as well as customer ratings of employee quality of service, guest bedroom quality, safety, and service disruption. Additionally, it should be highlighted that major mediating influences had an impact on how well-liked the hotel's amenities and employees provided service to guests. Through the use of web-based technologies, the research offered several recommendations for improving guest satisfaction with hotel operations. The results of this study could contribute to hotel management concentrating on the elements of the experiences of their guests that are the most important factors for boosting the level of satisfaction.

Guest Reviewers

Guest Reviewers

Examining Airbnb guest satisfaction tendencies: a text mining approach

ABSTRACT Given Airbnb's changes since its inception and the dynamism of customer preferences, a study that sheds light on how customer satisfaction is evolving is relevant. An automated method is proposed for identifying these satisfaction tendencies at a large scale. This study follows a text mining approach to analyse 590,070 reviews posted between 2010 and 2019 on the Airbnb platform in Lisbon. Topic Modelling is employed in order to identify the main topics discussed in the reviews, and Sentiment Analysis to understand the topics that compose guest’s satisfaction in the context of Airbnb services. Three major topics are extracted from Airbnb reviews: ‘host’s service’, ‘physical aspects’, and ‘location’. Although a positivity bias in guest reviews is confirmed, the satisfaction level seems to be decreasing over the years. The results also reveal that ‘physical aspects’ is the predominant topic when considering the negative guest reviews. This research considers big data the base to create knowledge, data spanning over the years, offering consistency to the research.

Promoting Guest Satisfaction: Digital Platforms as a Means to Encourage Economic Development in Hospitality

ABSTRACT Digital platforms can provide mechanisms to reduce barriers to entry for individuals in Internet-enabled commerce. These platforms provide a broad range of technical and administrative capabilities to support marketing and transaction processing; however, users may fail to take full advantage of these capabilities. This study examines how property hosts apply the affordances of a hospitality digital platform within developing economies. We consider skill by which a host uses the online platform as a resource, and evaluate the extent to which a host’s use of the platform corresponds with guest review scores. Our findings demonstrate that, after accounting for location and property characteristics, hosts who skillfully utilize hedonic marketing affordances achieve higher guest review scores than those who do not.

Editorial

Dear Readers, It gives me great pleasure to announce the sixth regular issue of 2022. First of all, I would like to welcome all the new members of our editorial board and also express my sincere gratitude to all the members who have recently retired. It is only thanks to the expertise of our editorial board and volunteer guest reviewers, as well as the generous support of the J.UCS consortium and the novel contributions of our authors, that we are able to maintain this high standard and even improve the impact factor over the years. In this issue, various topical aspects of computer science are covered by 12 authors from 5 countries in 4 articles. Stefano Masneri, Ana Domínguez, Mikel Zorrilla, Mikel Larrañaga and Ana Arruarte from Italy present a systematic review of the literature on the use of augmented reality applications in primary and secondary schools, with a specific focus on collaborative, multi-user, and interactive applications. In their article, Julio Cesar Vale Neves, Luiz Enrique Zarate and Mark Alan Junho Song from Brazil describe an approach to add a new data structure, binary decision diagrams (BDD), to the TRIAS algorithm and retrieve triadic concepts for high dimensional contexts. In a collaborative research between Croatia and Ukraine, Igor Tomicic, Markus Schatten, and Vadym Shkarupylo propose an open ontology for self-sustainable human settlements in an effort to find a common language for modeling self-sustainable systems and address issues of heterogeneity of physical devices, protocols, software components, data and message formats, and other relevant factors for the implementation of smart systems. Last but not least, Derya Yiltas-Kaplan from Turkey presents her research on traffic optimization with software-defined network controllers.

Thanks to Our Guest Editors and Reviewers for Their Critical Contributions in 2021

Thanks to Our Guest Editors and Reviewers for Their Critical Contributions in 2021

Guest Reviewers

Guest Reviewers

Recognition/Appreciation of JFS Guest Reviewers—2021

Journal of Forensic SciencesEarly View GUEST REVIEWER RECOGNITION Recognition/Appreciation of JFS Guest Reviewers—2021 Michael A. Peat Ph.D., Michael A. Peat Ph.D. Editor-in-Chief Journal of Forensic SciencesSearch for more papers by this author Michael A. Peat Ph.D., Michael A. Peat Ph.D. Editor-in-Chief Journal of Forensic SciencesSearch for more papers by this author First published: 09 May 2022 https://doi.org/10.1111/1556-4029.15048Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinked InRedditWechat Early ViewOnline Version of Record before inclusion in an issue RelatedInformation

Practical Analysis of Long-Term Impacts of Hotels Strategic Responses and How to Overcoming in the Covid-19 Crisis?

Abstract: This study explores the interplay between public measures adopted by the governments to combat COVID-19 and the performance of the hospitality industry. Overall, our findings show that most of the government interventions were associated with a negative response in the returns of the hospitality industry, a response that became more negative as the COVID-19 pandemic evolved. The main research shows that labour actions, especially plans for temporary employment regulations, innovation and differentiation strategies, and reorientation to closer markets and obtaining information from official sources as a guarantee of their certainty, are the measures that have a greater impact on the possibilities of recovering hotel activity. In addition, government measures that contribute to the improvement of the financial situation of firms can also play a relevant role in hotel recovery. The aims to identify the possible shift in importance of hotel choice and satisfaction attributes during the Covid-19 pandemic. To explore a shift of importance, a qualitative thematical analysis was chosen. Further, guest reviews were collected from two major OTAs. The resumption of activities during and after the pandemic, comparing the COVID-19 pandemic with previous public health crises, and measuring the impact of the pandemic in terms of economics. However, the ongoing Covid-19 pandemic has decelerated and changed the hotel industry globally. For many guests, it is the first time, they travel after the hotel industry almost stopped globally, with lockdowns and curfews. A hotel company is interconnected with various partners in the supply chain, thus, the problem in hotel operation is transferred upstream the supply chain. provisions to cope with the new reality, including safety measures, technology application, quality of service, marketing communication, human resource management, and the supply chain management. Keywords: COVID-19, pandemic, hospitality industry, tourism, systematic, hotel business, safety, WHO, variants, Crisis management, Lockdown, healthcare, hotel management, AI

Bookshelf

Debra Greschner reviews So You Want to Sing Cabaret: A Guide for Performers by David Sabella and Sue Matsuki (Lanham, MD: Rowman & Littlefield, 2020) as a volume that offers an overview of cabaret and a multitude of interviews with noteworthy professionals in the field. Guest reviewer Abigail Dueppen characterizes Queering Vocal Pedagogy by William Sauerland (Lanham, MD: Rowman & Littlefield, 2022) as a useful guide for creating inclusive voice studios. Guest reviewer Abigayle Ferguson recommends The Tongue as a Gateway to Voice, Resonance, Style, and Intelligibility by Angelika Nair (San Diego: Plural Publishing, 2021) as a comprehensive and effective guide to understanding the role of the tongue in singing and speaking.

Front Office Department Service Quality during the Covid-19 Period

ABSTRACT
 Purpose: This study was to determine the service quality of the front office department and the efforts of the front office department in Canggu Dream Village, Bali, Indonesia, to maintain and improve the quality of the services given.
 Research methods: This study used descriptive statistical analysis techniques with 90 samples of guest reviews selected using purposive sampling method. The source of data is guest reviews for one year from January 2020 to December 2020 on online travel agents.
 Results and discussion: There were comparisons of positive reviews with a total of 94% while negative reviews are only 6%. Each variable gets a different percentage, the empathy variable gets a percentage of 50% and becomes the most dominant variable in positive reviews.
 Implication: All the variables have a higher percentage of positive reviews than negative reviews.
 
 Keywords: quality of service, guest complaints, front office department.

2021 Guest Reviewer Acknowledgment

2021 Guest Reviewer Acknowledgment

A Smart Tourism Case Study: Classification of Accommodation Using Machine Learning Models Based on Accommodation Characteristics and Online Guest Reviews

This paper deals with the analysis of data retrieved from a web page for booking accommodation. The main idea of the research is to analyze the relationship between accommodation factors and customer reviews in order to determine the factors that have the greatest influence on customer reviews. Machine learning methods are applied to the collected data and models that can predict the review category for those accommodations that are not evaluated by users are trained. The relationship between certain accommodation factors and classification accuracy of the models is examined in order to get detailed insight into the data used for model training, as well as to make the models more interpretable. The classification accuracy of each model is tested and the precision and recall of the models are examined and compared.

English Verb Valency Pattern in Padma Resort Legian Guest Reviews on TripAdvisor

This research was conducted in order to identify verb valency pattern found in reviews on TripAdvisor uploaded by visitors of Padma Resort Legian. It was executed as a descriptive qualitative research which complied with observation and note-taking method for data collection (Sudaryanto, 2015), continued by data analysis in accordance with Verbs and Their Satellites theory by D.J. Allerton (2006). The sample data was taken from reviews posted for Padma Resort Legian in TripAdvisor. It was compiled and analyzed in Microsoft Excel pivot table. Most of the verb valency pattern found consists of auxiliary verb with subject and predicative as its elaborators functioning as object. In terms of its transitivity, verb valency patterns on reviews were dominated with bi-valent, followed by tri-valent, mono-valent and tetra-valent in number.

2021 Guest Reviewer List

Journal of the Experimental Analysis of BehaviorVolume 117, Issue 2 p. 271-271 Guest Reviewers 2021 Guest Reviewer List First published: 15 March 2022 https://doi.org/10.1002/jeab.749Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinkedInRedditWechat No abstract is available for this article. Volume117, Issue2March 2022Pages 271-271 RelatedInformation

2021 Guest Reviewer Acknowledgement

2021 Guest Reviewer Acknowledgement

Preferensi tamu terhadap pelayanan Room Attendant di Doubletree by Hilton Johor Bahru pada masa pandemic covid -19

Guest preferences for room attendant services at Doubletree by Hilton Johor Bahru during the COVID-19 pandemic need to be detailed because of guest complaints that have been submitted via OTA. This complaint will have an impact on the hotel's image. This study aims to provide ideas and insights for decision makers in order to improve Room Attendant by understanding the preferences of guests staying at Doubletree Hotel.The type of data used by the writer is qualitative descriptive data and data collection techniques used ware documentation study and interviews. Data analysis techniques used to describe guest preference lists and guest reviews on the OTA for room attendant services with reference to hospitality, attraction, cleanliness, comfort, and safety at this hotel. Then analyzes preferences in the form of the most preffered reviews and the least preffered preference. In the research, it can be concluded that the reviews that appear the most are guests who like the room to be cleaned at breakfast, expect extra water and towels and the least preferred appears: does not like strong smells, guests prefer turn down service when guests are outside the room, and don't like the consistency of housekeeping and don't like the worn bed sheets.

Determination the competitiveness of a hotel based on ratings of its characteristics on the example of Aktau city

The hotel industry is developing dynamically in the Mangistau region in recent years. As a result, the competitive environment is strengthened in this area. Thus, it becomes harder for some hotels to operate due to increased competition. Determining the competitiveness of hotels is very important for managers in creating effective strategies to protect market positions and promote their business. This article uses statistical methods to compare hotels. Data from Booking.com was used to analyze and compare the ratings of six hotels. First of all, there was collected general data about the hotel. Many guest reviews were compared. The authors determined the segment of tourists of each hotel. Further, there was determined the stability of quality hotel service in a competitive environment using the standard deviation method. Third, analyzing the importance of the characteristics of a hotel for consumers, there was developed a perception map to demonstrate and compare six hotels and their differences in eight characteristics. The proposed methods are useful for researchers and hotel managers in assessing the competitiveness of hotels and identifying important characteristics that need to be improved in order to significantly attract potential customers.