Using the “Computers are social actors” paradigm, this study brings the concept of power to human–computer interactions in tourism. Building on theories of social power and deliberate practice, the ...authors examine psychological effects of expert power of online travel review platforms (influencer) and its interaction effects with the power of users (influenced). Two expert platform attributes are conceptualized: specialization and experience. A significant interaction effect was identified between platform specialization, platform experience, and user power on perceived information-task fit using a 2 × 2 × 2 between-subjects experiment. When users are powerful, specialization affected perceived information-task fit for low-experience platforms; no significant effect was evident for high experience platforms. When users are powerless, specialization did not affect perceived information-task fit, regardless of experience condition. Perceived information-task fit mediated the effect of specialization on intention to use. The findings contribute to power discourses by exploring the workings of expert power.
There has been exponential growth in the power exercised by social media in hospitality and tourism. The power of social media platforms as stakeholders has been widely accepted by both academics and ...industry practitioners. However, to the best of the current authors’ knowledge, there has been no conceptualization of the power attributable to social media. On this basis, it is both timely and necessary to establish theoretical grounds that explain the concept of social media power and its application in hospitality and tourism. A hierarchical model that characterizes social media power is constructed in the present article by bringing together fundamental power discourses, media effect theories, and technology determinism. The authors identify definitions and sources of social media power at different levels of the power pyramid and present various technological mechanisms that trigger such sources. This conceptual study proposes theoretical foundations for future research and theory-building.
Social media are acknowledged as an important information source that influences tourists’ travel choices. However, qualitative studies that take an inductive approach to identify the roles of social ...media by investigating how social media affect travel choices are limited. By interviewing 21 tourists who had recently taken trips, this article aimed to identify the roles that social media played in the tourists’ choices of six travel components (destination, transportation, accommodation, food and dining activities, attractions, as well as shopping and leisure activities). Four roles have been identified: Need Generator, Supporter, Guider and Approver. Theoretical and practical implications along with future research suggestions are discussed.
The intellectual structure of the sharing economy Sainaghi, Ruggero; Köseoglu, Mehmet Ali; Mehraliyev, Fuad
Tourism economics : the business and finance of tourism and recreation,
08/2021, Letnik:
27, Številka:
5
Journal Article
Recenzirano
This study analyzes the intellectual structure of the sharing economy (SE) in the hospitality and tourism industry, starting from a sample of 189 papers. A co-citation analysis was performed on the ...99 most frequently cited studies. The analysis carried out identified five clusters. These groups include the following: (i) the constituent elements of sharing, (ii) the SE and the sharing phenomenon, (iii) noncommercial website platforms and the social impact generated by sharing firms, (iv) economic impacts, and (v) some negative impacts. Each cluster is succinctly described, presenting the main theme and some subtopics.
The crucial role of sensory dimensions in customer experiences has been supported in literature. However, traditional self-reported sensory measurements have limited capacity in capturing the ...multi-dimensional experiences sensed by individuals and articulating the distinct effect of different sensory dimensions on actual behavior. This study is the first attempt to test the effects of positive and negative experiences involving all five senses (sight, smell, sound, taste, and touch) on customer ratings. The sensory experiences reported in social media reviews were captured and explored using text mining and sentiment analysis. The findings show that although the majority of customers’ experiences were positive, the negative sensory experiences had higher effect on customer rating. Furthermore, the five senses had different weights in forming overall experience, which provides theoretical contributions to the literature on sensescapes, prospect theory, and discourses on satisfiers and dissatisfiers.
•New methodological technique to analyze big online review data.•New multidimensional sensory experience sentiment scale.•Application of the scale to restaurant reviews demonstrate the effect of five sensory experiences on customer ratings.•Taste, touch and sight experiences are the most important components of memorable restaurant experiences.•The negative sensory experiences have higher effect on customer rating, compared to their positive counterparts.
Intellectual connections in tourism studies Koseoglu, Mehmet Ali; Mehraliyev, Fuad; Xiao, Honggen
Annals of tourism research,
November 2019, 2019-11-00, Letnik:
79
Journal Article
Recenzirano
This paper looks at intellectual connections in tourism studies through a co-citation analysis of its source knowledge. Reference sources from articles in Annals of Tourism Research are analyzed to ...describe source subject clustering and evolution over the last two decades. The subject clustering, connections and evolutions of twelve major source knowledge domains (namely, authenticity, tourist experiences, tourism planning, resident attitudes, tourism impacts, tourism area lifecycle, consumer behavior, backpacker tourism, performance approach, paradigms in tourism, dark tourism, and mobility) are visualized, described and discussed by four lustra (1998–2002, 2003–2007, 2008–2012, and 2013–2017). Implications of these source knowledge connections and evolutions for tourism studies are then reflected, and limitations of this research are also acknowledged.
•Co-citation analyses of source knowledge for tourism studies•Describe and discuss intellectual connections and source knowledge network evolutions•Offer reflections on tourism studies from an evolutionary perspective
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.
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.
Role of virtual avatars in digitalized hotel service Choi, Youngjoon; Mehraliyev, Fuad; Kim, Seongseop (Sam)
International journal of contemporary hospitality management,
04/2020, Letnik:
32, Številka:
3
Journal Article
Recenzirano
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.
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.
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