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Article
Publication date: 11 October 2021

Fuad Mehraliyev, Irene Cheng Chu Chan and Andrei Petrovich Kirilenko

This study aims to conduct a systematic review and critically analyze the sentiment analysis literature in hospitality and tourism from methodological (data sets and analyzes) and…

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Abstract

Purpose

This study aims to conduct a systematic review and critically analyze the sentiment analysis literature in hospitality and tourism from methodological (data sets and analyzes) and thematic (topics, theories, key constructs and their relationships) perspectives.

Design/methodology/approach

Qualitative thematic review and quantitative systematic review were performed on 70 papers obtained from hospitality and tourism categories of two databases, namely, Web of Science and Scopus.

Findings

A total of 5 topics and 27 sub-topics were identified and the major theme is market intelligence. Sentiment variables were investigated not only as independent but also as dependent variables. The customer rating is the most investigated dependent variable, whereas moderators and mediators were rarely tested. Most reviewed studies did not use theory. The findings from the methodological review show that analysis of big data was rare. Moreover, testing the performance of sentiment analyzes was uncommon, and only one paper tested the performance of aspect/feature extraction.

Research limitations/implications

This study extends prior review studies by providing a comprehensive view of how knowledge and methodologies of sentiment analysis have developed. The identified themes and key constructs serve as a solid base for future knowledge advancement. Future research directions on sentiment analysis are also provided.

Originality/value

To the best of the authors’ knowledge, this study is the first comprehensive methodological and thematic review of sentiment analysis in hospitality and tourism. Based on the identified findings, the authors propose several directions for future research.

Details

International Journal of Contemporary Hospitality Management, vol. 34 no. 1
Type: Research Article
ISSN: 0959-6119

Keywords

Article
Publication date: 13 November 2019

Fuad Mehraliyev, Youngjoon Choi and Mehmet Ali Köseoglu

The purpose of this paper is to conduct a systematic and quantitative review of published papers on smart tourism. More specifically, the paper aims to identify the smart tourism…

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Abstract

Purpose

The purpose of this paper is to conduct a systematic and quantitative review of published papers on smart tourism. More specifically, the paper aims to identify the smart tourism research life cycle, collaboration trends, main social structure, disciplinary approaches and foundations, research topics and methodological approaches.

Design/methodology/approach

Systematic quantitative review techniques were used to review smart tourism literature. Frequency analysis, network analysis, text mining techniques were performed on data obtained from 96 papers collected from three databases as follows: Web of Science, Scopus and EBSCOhost.

Findings

The smart tourism research life cycle has two turning points with an exponential increase: 2015 and 2017. The latter is mainly associated with the internationalization of collaboration. Social structure of smart tourism research was revealed. Many of the ideas and research trends are affected by one research cluster. Destination related articles are dominant in smart tourism research. Internet of things and tourist experience are less researched areas. Only a quarter of the articles was published in tourism and hospitality journals. In particular, there is a big gap in published papers in hospitality journals. An important gap from methodological aspect is limited number of qualitative studies with human subjects. The geographical limitation is high concentration of smart tourism studies in Korea.

Research limitations/implications

This study collected and analyzed only full papers published in peer-reviewed journals. Future research may consider including book chapters and/or conference proceedings. This study was mainly based on quantitative review techniques. Qualitative or mixed review techniques may be conducted.

Originality/value

This study is the first literature review on an increasingly popular topic of smart tourism.

研究目的

本研究旨在从以下几方面探讨智慧旅游的沿革:(1)出版量和研究主题, 2)主要学科、社会结构和合作趋势, 以及3)方法论和研究范式。

研究设计/方法论/方法

本研究对1995至2017年间发表的96篇文章进行了系统的定量评价, 并采用了评价和相关回顾的方法对文献进行了分析。

研究结果

研究结果阐释了智能旅游研究的生命周期。自2015以来, 相关文献的出版数量迅速增长, 2017年更是呈现出指数增长的趋势。2017年, 相关的国际合作也大幅增加。在学科重点方面, 智能旅游研究并不仅局限于旅游, 而是采用跨学科/多学科的方法。在社会结构方面, 智能旅游的知识在很大程度上是由具有相似社会文化背景和制度背景的学者建构的。在研究主题方面, 与目的地相关的文章占主导地位。在研究方法方面, 智能旅游研究采用的主要是定量研究, 其次是概念研究和混合方法研究。令人惊讶的是, 定性研究则十分有限。在研究范式方面, 由于研究样本主要来自韩国, 研究可能存在文化偏见, 。

研究局限/启示

本研究仅收集并分析了在同行评审期刊上发表的论文。未来的研究可以考虑加入书籍章节和/或会议论文。本研究主要采用定量评价, 未来的研究可以考虑可以采用定性或混合方法技术。

独创性/价值

本研究通过对社会结构、主题、方法和研究范式等方面的研究空白的分析, 为智能旅游研究提供了有意义的理论贡献, 并指出了未来的研究方向。

Details

Journal of Hospitality and Tourism Technology, vol. 10 no. 4
Type: Research Article
ISSN: 1757-9880

Keywords

Article
Publication date: 19 May 2022

Jun Liu, Yunyun Yu, Fuad Mehraliyev, Sike Hu and Jiaqi Chen

Despite a significant focus on customer evaluation and sentiment analysis, limited attention has been paid to discrete emotional perspective in terms of the emotionality used in…

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Abstract

Purpose

Despite a significant focus on customer evaluation and sentiment analysis, limited attention has been paid to discrete emotional perspective in terms of the emotionality used in text. This paper aims to extend the general-sentiment dictionary in Chinese to a restaurant-domain-specific dictionary, visualize spatiotemporal sentiment trends, identify the main discrete emotions that affect customers’ ratings in a restaurant setting and identify constituents of influential emotions.

Design/methodology/approach

A total of 683,610 online restaurant reviews downloaded from Dianping.com were analyzed by a sentiment dictionary optimized by the authors; the main emotions (joy, love, trust, anger, sadness and surprise) that affect online ratings were explored by using multiple linear regression methods. After tracking these sentiment review texts, Latent Dirichlet Allocation (LDA) and LDA models with term frequency-inverse document frequency as weights were used to find the factors that constitute influential emotions.

Findings

The results show that it is viable to optimize or expand sentiment dictionary by word similarity. The findings highlight that love and anger have the highest effect on online ratings. The main factors that constitute consumers’ anger (local characteristics, incorrect food portions and unobtrusive location) and love (comfortable dining atmosphere, obvious local characteristics and complete supporting services) are identified. Different from previous studies, negativity bias is not observed, which poses a question of whether it has to do with Chinese culture.

Practical implications

These findings can help managers monitor the true quality of restaurant service in an area on time. Based on the results, restaurant operators can better decide which aspects they should pay more attention to; platforms can operate better and can have more manageable webpage settings; and consumers can easily capture the quality of restaurants to make better purchase decisions.

Originality/value

This study builds upon the existing general sentiment dictionary in Chinese and, to the best of the authors’ knowledge, is the first to provide a restaurant-domain-specific sentiment dictionary and use it for analysis. It also reveals the constituents of two prominent emotions (love and anger) in the case of restaurant reviews.

Details

International Journal of Contemporary Hospitality Management, vol. 34 no. 10
Type: Research Article
ISSN: 0959-6119

Keywords

Article
Publication date: 20 April 2020

Mehmet Ali Köseoglu, Fuad Mehraliyev, Mehmet Altin and Fevzi Okumus

This study aims to propose a competitor intelligence and analysis (CIA) model that can be used for the analysis of a firm’s competitors. Empirically, it investigates the…

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Abstract

Purpose

This study aims to propose a competitor intelligence and analysis (CIA) model that can be used for the analysis of a firm’s competitors. Empirically, it investigates the application of the CIA model on online reviews. This proposed model clarifies the confusion between terms such as competitive intelligence, competitor intelligence and competitor analysis and provides a more efficient process for managers.

Design/methodology/approach

The approach of the model integrates text mining techniques as a big data method with network analysis to form a competitor analysis. This study has considered two centrality metrics – degree centrality and betweenness centrality – to identify the functional associations among the resources elaborated by the customers of the hotels.

Findings

Findings show online reviews may be used as a solid source of intelligence. The intelligence maps visualized through the text-net technique is an efficient representation of tourist satisfaction and dissatisfaction with a tourism company and its competitors.

Practical implications

The proposed approach can be used in the hotel industry along with many others. The implications for scholars and managers and the possible directions for future research are also discussed in the study.

Originality/value

This study develops a new approach for competitive intelligence practices in the hotel industry and tests a new method for competitor analysis as a part of the competitive intelligence and analysis approach developed in this study.

Purpose

本研究提出了一个竞争对手情报与分析(CIA)模型, 可用于分析企业的竞争对手。对CIA模型在网络评论中的进行了实证研究。该模型厘清了竞争情报、竞争对手情报和竞争对手分析等术语之间的概念混淆, 为管理者提供了一个更有效的流程。

Design/methodology/approach

该模型将文本挖掘技术作为大数据方法与网络分析相结合, 来进行竞争对手分析。本研究考虑了两个中心性指标——度中心性和中介中心性——来识别酒店客户精心设计的资源之间的功能关联。

Findings

结果表明, 在线评论可被用作可靠的情报来源。情报地图通过文本网络技术可视化有效地展示了游客对旅游公司及其竞争对手的满意度和不满意度。

Practical implications

本文所提出的方法可用于酒店行业及许多其他行业。同时, 本文也探讨了本研究对学者与管理者的启示, 以及未来可能的研究方向。

Originality/value

本文提出了一种新的酒店行业竞争情报的实践方法, 并测试了一种新的竞争对手分析法, 作为竞争情报和分析方法的一部分。

Keywords

关键词 竞争情报, 竞争对手情报, 文本挖掘, 网络分析, 在线评论, 酒店

Objetivo

Este estudio propone un modelo de análisis de la inteligencia competitiva (CIA) que puede utilizarse para el análisis de los competidores de la empresa. Empíricamente, investiga la aplicación del modelo de la CIA a las reseñas on line. El modelo propuesto aclara la confusión entre términos como inteligencia competitiva, inteligencia de la competencia y análisis de la competencia y proporciona un procedimiento más eficiente para los gerentes.

Diseño/metodología/enfoque

El enfoque del modelo integra las técnicas de minería de textos, como método de Big Data, con el análisis de redes para realizar el análisis de la competencia. En este estudio se han considerado dos métricas de centralidad -centralidad de grado e intermediación- para identificar las asociaciones funcionales entre los recursos elaborados por los clientes de los hoteles.

Resultados

Los hallazgos muestran que las reseñas on line pueden ser utilizadas como una fuente sólida de inteligencia. Los mapas de inteligencia visualizados mediante la técnica de redes de texto son una representación eficiente de la satisfacción e insatisfacción de los turistas con la empresa turística y sus competidores.

Implicaciones prácticas

El enfoque propuesto puede utilizarse en la industria hotelera junto con otros muchos. En el estudio también se analizan las implicaciones para los investigadores y los gerentes y las posibles directrices para investigaciones futuras.

Originalidad/interés

Este artículo desarrolla un nuevo enfoque para la aplicación de la inteligencia competitiva en la industria hotelera y prueba un método nuevo para el análisis de la competencia como parte del enfoque del Análisis de la Inteligencia Competitiva desarrollado en este estudio.

Palabras clave Inteligencia competitiva, Inteligencia del competidor, Minería de textos, Análisis de redes, Reseñas on line, hoteles

Article
Publication date: 5 December 2023

Jun Liu, Sike Hu, Fuad Mehraliyev, Haiyue Zhou, Yunyun Yu and Luyu Yang

This study aims to establish a model for rapid and accurate emotion recognition in restaurant online reviews, thus advancing the literature and providing practical insights into…

Abstract

Purpose

This study aims to establish a model for rapid and accurate emotion recognition in restaurant online reviews, thus advancing the literature and providing practical insights into electronic word-of-mouth management for the industry.

Design/methodology/approach

This study elaborates a hybrid model that integrates deep learning (DL) and a sentiment lexicon (SL) and compares it to five other models, including SL, random forest (RF), naïve Bayes, support vector machine (SVM) and a DL model, for the task of emotion recognition in restaurant online reviews. These models are trained and tested using 652,348 online reviews from 548 restaurants.

Findings

The hybrid approach performs well for valence-based emotion and discrete emotion recognition and is highly applicable for mining online reviews in a restaurant setting. The performances of SL and RF are inferior when it comes to recognizing discrete emotions. The DL method and SVM can perform satisfactorily in the valence-based emotion recognition.

Research limitations/implications

These findings provide methodological and theoretical implications; thus, they advance the current state of knowledge on emotion recognition in restaurant online reviews. The results also provide practical insights into intelligent service quality monitoring and electronic word-of-mouth management for the industry.

Originality/value

This study proposes a superior model for emotion recognition in restaurant online reviews. The methodological framework and steps are elucidated in detail for future research and practical application. This study also details the performances of other commonly used models to support the selection of methods in research and practical applications.

Details

International Journal of Contemporary Hospitality Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0959-6119

Keywords

Article
Publication date: 28 March 2023

Jun Liu, Sike Hu, Fuad Mehraliyev and Haolong Liu

This study aims to investigate the current state of research using deep learning methods for text classification in the tourism and hospitality field and to propose specific…

Abstract

Purpose

This study aims to investigate the current state of research using deep learning methods for text classification in the tourism and hospitality field and to propose specific guidelines for future research.

Design/methodology/approach

This study undertakes a qualitative and critical review of studies that use deep learning methods for text classification in research fields of tourism and hospitality and computer science. The data was collected from the Web of Science database and included studies published until February 2022.

Findings

Findings show that current research has mainly focused on text feature classification, text rating classification and text sentiment classification. Most of the deep learning methods used are relatively old, proposed in the 20th century, including feed-forward neural networks and artificial neural networks, among others. Deep learning algorithms proposed in recent years in the field of computer science with better classification performance have not been introduced to tourism and hospitality for large-scale dissemination and use. In addition, most of the data the studies used were from publicly available rating data sets; only two studies manually annotated data collected from online tourism websites.

Practical implications

The applications of deep learning algorithms and data in the tourism and hospitality field are discussed, laying the foundation for future text mining research. The findings also hold implications for managers regarding the use of deep learning in tourism and hospitality. Researchers and practitioners can use methodological frameworks and recommendations proposed in this study to perform more effective classifications such as for quality assessment or service feature extraction purposes.

Originality/value

The paper provides an integrative review of research in text classification using deep learning methods in the tourism and hospitality field, points out newer deep learning methods that are suitable for classification and identifies how to develop different annotated data sets applicable to the field. Furthermore, foundations and directions for future text classification research are set.

Details

International Journal of Contemporary Hospitality Management, vol. 35 no. 12
Type: Research Article
ISSN: 0959-6119

Keywords

Article
Publication date: 26 February 2020

Youngjoon Choi, Fuad Mehraliyev and Seongseop (Sam) Kim

This study aim to attempt to conceptualize agency in a hospitality setting and examine the psychological effects of agency-related visual cues on user perception and intention to…

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Abstract

Purpose

This study aim to attempt to conceptualize agency in a hospitality setting and examine the psychological effects of agency-related visual cues on user perception and intention to use to understand the role of agency in the digitalization of hotel services.

Design/methodology/approach

After developing demo videos of an express check-out application, two experiments were conducted to examine the effects of using an avatar and explain the psychological mechanism of how attributes of an avatar increase intention to use.

Findings

Study 1 found that the presence of an avatar had a positive influence on intention to use. Study 2 retested the findings of Study 1 and illustrated the psychological mechanism of how two attributes of an avatar (social position and gender) influenced perceived expertise and intention to use. A significant interaction effect between social position and gender was found on perceived expertise. Perceived expertise also mediated the effect of an avatar on intention to use in the male avatar conditions.

Originality/value

As the first attempt to investigate the role of avatars in human–computer interaction in a hotel setting, this study will serve as an example in testing the effects of agency-related technical features on user experience and behavioral intention, possibly broadening the current research scope of hospitality and tourism. This study also provides a useful guideline to develop and design a successful interface of digitalized hotel services.

Details

International Journal of Contemporary Hospitality Management, vol. 32 no. 3
Type: Research Article
ISSN: 0959-6119

Keywords

Content available
Article
Publication date: 21 November 2019

S. Mostafa Rasoolimanesh, Rob Law, Dimitrios Buhalis and Cihan Cobanoglu

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Abstract

Details

Journal of Hospitality and Tourism Technology, vol. 10 no. 4
Type: Research Article
ISSN: 1757-9880

Article
Publication date: 12 January 2022

Zhaoyu Chen and Irene Cheng Chu Chan

This study examined a tourism destination, Macao, a fast-progressing smart city under development, vis-à-vis a set of smart city quality of life (SCQOL) domains and verified their…

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Abstract

Purpose

This study examined a tourism destination, Macao, a fast-progressing smart city under development, vis-à-vis a set of smart city quality of life (SCQOL) domains and verified their effects on citizens' attitudes, perceptions and support for citizen-centric smart city development (SCD).

Design/methodology/approach

This study adopted a quantitative approach. In particular, a questionnaire survey was used to collect data from Macao citizens. Factor analysis was used to identify SCQOL domains, while multiple linear regression and cluster analysis were used to achieve the research objectives.

Findings

This study identified five SCQOL domains: smart environment, smart people, smart livelihood, smart economy and economic policy, and smart mobility. Each of the domains had a different influence on citizens' attitudes and support for SCD. Three citizen segments (passive, neutral and enthusiastic supporters) were identified.

Practical implications

The five SCQOL domains, their effects on citizens' support for SCD and the three citizen segments identified can help implement the appropriate measures to enhance the target groups' SCD. The findings are also of practical value in evaluating the citizen-centric approaches on smart progress in other contexts.

Originality/value

The concept of smart technology has been widely applied to all aspects of city development. The main goal of SCD is to enhance citizens' quality of life. However, most studies have only explored smart cities and quality of life in isolation. Grounded on citizen centrality, this study contributes to the literature on SCD by proposing a new concept of SCQOL, identifying the domains constituting SCQOL and their influence on citizens' support for SCD.

Details

Information Technology & People, vol. 36 no. 1
Type: Research Article
ISSN: 0959-3845

Keywords

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