Online Travel Communities Research Articles

Adapting and Validating Scale of Customer Engagement in Online Travel Communities

Increasing attention towards customer engagement has caused its measurement to remain a highly debated issue among scholars. This study adapts and validates measurement scales for customer engagement in Online Travel Communities. It builds on previous studies on scale development for customer engagement. Data were collected from 450 members of Online Travel Communities in eight countries: Australia, Canada, Hong Kong (Chinese territory), New Zealand, Singapore, South Africa, the United Kingdom and the United States of America. The process of adapting and validating the scale involved exploratory factor analysis, testing for differential item functioning, examination of item response theory, confirmatory factor analysis, testing for invariance and criterion validity. The results found that three dimensions (affection, absorption, and interaction) suitably and adequately measure customer engagement in Online Travel Communities.

Effects of intrinsic and extrinsic motivation on social loafing in online travel communities

Previous research has confirmed that social loafing as a pronouncing obstacle undermines the development of online communities. However, relevant studies centered on the critical factors that affect social loafing in online travel communities are still not well understood. Drawing on self-determination theory and social identity theory, this paper critically focuses on the effects of intrinsic motivation (enjoyment in helping and hedonic motivation), extrinsic motivation (reputation and reciprocity) and community identification on social loafing in online travel communities, using data collected from 300 respondents in China. After a structural equation modeling analysis, the results of this study indicate that only enjoyment in helping exhibits a significantly negative relationship with social loafing, whereas the other three types of motivation are reinforced by community identification to inhibit social loafing indirectly. Meanwhile, community identification is more positively influenced by extrinsic motivation (reputation and reciprocity), and social loafing can be effectively diminished by community identification. Theoretical and practical suggestions are discussed for future research.

What factors determine reviewer credibility?

PurposeThe experiential nature of travel and tourism services has popularized the importance of electronic word-of-mouth (EWOM) among potential customers. EWOM has a significant influence on hotel booking intention of customers as they tend to trust EWOM more than the messages spread by marketers. Amid abundant reviews available online, it becomes difficult for travelers to identify the most significant ones. This questions the credibility of reviewers as various online businesses allow reviewers to post their feedback using nickname or email address rather than using real name, photo or other personal information. Therefore, this study aims to determine the factors leading to reviewer credibility.Design/methodology/approachThe paper proposes an econometric model to determine the variables that affect the reviewer’s credibility in the hospitality and tourism sector. The proposed model uses quantifiable variables of reviewers and reviews to estimate reviewer credibility, defined in terms of proportion of number of helpful votes received by a reviewer to the number of total reviews written by him. This covers both aspects of source credibility i.e. trustworthiness and expertness. The authors have used the data set of TripAdvisor.com to validate the models.FindingsRegression analysis significantly validated the econometric models proposed here. To check the predictive efficiency of the models, predictive modeling using five commonly used classifiers such as random forest (RF), linear discriminant analysis, k-nearest neighbor, decision tree and support vector machine is performed. RF gave the best accuracy for the overall model.Practical implicationsThe findings of this research paper suggest various implications for hoteliers and managers to help retain credible reviewers in the online travel community. This will help them to achieve long term relationships with the clients and increase their trust in the brand.Originality/valueTo the best of authors’ knowledge, this study performs an econometric modeling approach to find determinants of reviewer credibility, not conducted in previous studies. Moreover, the study contracts from earlier works by considering it to be an endogenous variable, rather than an exogenous one.

Effects of socialization interactions on customer engagement in online travel communities

Purpose Travel companies are increasingly hosting online communities to extend their initiatives of customer relationship management and gain additional insight into their business. While the benefits to companies from hosting online communities are clear, another closely related issue has not been given comparative attention: Why do customers engage voluntarily in online travel communities? The purpose of this paper is to answer the question by developing and testing a conceptual model that exploring the influence of socialization interactions on customer engagement with the community. Design/methodology/approach Hypotheses were tested by applying structural equation modeling based on survey data collected from an online travel community (n=665). Findings The results supported the research hypotheses and demonstrated that socialization interactions (i.e. information and social exchange) in the online travel community are important catalysts for customer engagement. Originality/value The contribution of this study is twofold. First, from a theoretical perspective, it offers new insights into the conceptualization of customer engagement and its antecedents in the context of the online travel community. Second, from a pragmatic perspective, the conceptual model derived from this research aids practitioners in stimulating customer engagement from the perspective of socialization interactions.

Exploring the Movements of Chinese Free Independent Travelers in the U.S. : A Social Network Analysis Approach

In a new age of smart tourism, free independent travelers (FITs) choose their travel routes in a more diversified and less predictable way with the aid of smart services. This paper focuses on the movements of Chinese outbound FITs in the U.S. in the year of 2018. 110 places to visit (destinations) extracted from 122 travel routes recommendations on Qyer.com, a major online travel community in China, are analyzed with social network analysis (SNA). Based on the results of SNA, employing degree centrality, eigenvector centrality, betweenness centrality, network visualization, and cluster diagram methods, some preferred cities and natural attractions outside city centers (i.e., New York City (NYC), Los Angeles, San Francisco, Washington D.C., and Niagara Falls) are identified. Moreover, it is found that NYC in the East and Los Angeles in the West play a major role in the movements of Chinese FITs. This study contributes to the body of knowledge on tourist destination movements and provides valuable implications for smart service development in the tourism and hospitality industry.

Reciprocity and commitment in online travel communities

PurposeWith social exchange theory as a basis, the purpose of this paper is to seek a better understanding of advice processes in online travel communities, which offer crucial advice for travelers’ decisions. It also predicts that relational capital variables (commitment, reciprocity perceptions) moderate the main relationships.Design/methodology/approachData from a web survey of 456 users of online travel communities affirm the scale’s validity and provide the input for structural equation modeling and multisample analyses of the hypotheses.FindingsHigher levels of commitment reinforce the effect of following past advice on passive and active participation intentions. Users’ perceptions of reciprocity in the community strengthen the influence of following past advice on active participation. However, a high level of reciprocity causes users following past advice to reduce their intentions to continue following that advice.Practical implicationsManagement tactics should specify active and passive participation in online travel communities. Specifically, to encourage the creation of high-quality new content, community managers should create interactive environments marked by high levels of reciprocity and commitment.Originality/valueThis research elucidates the role of relational capital variables in advice processes and advances understanding of online travel communities.

Exploring Chinese Outbound Tourist Shopping: A Social Practice Framework

Chinese tourist shopping reflects the new consumer culture in contemporary China, but remains underexplored in the tourism literature despite its importance to many destinations. The present study applies social practice theory to tourist shopping research with the aim of exploring the key features of Chinese tourist shopping in Australia. Tourist shopping as a social practice is the basic unit of analysis, while tourists are decentralized as carriers of this practice. This study employed a qualitative methodology to analyze shopping-related posts in 40 travel blogs from two Chinese online travel communities. The findings show that tourist shopping practice consists of four interconnected elements: materials, competences, meanings, and settings—with utilitarian products purchased in large quantities and maintaining guanxi emerging as unique features of the Chinese tourist shopping practices. The article concludes with a discussion of the potential of social practice theory to enhance theoretical approaches in this area.

The effect of online interaction and trust on consumers’ value co-creation behavior in the online travel community

ABSTRACT This study proposes a three-dimensional conceptualization of consumer value co-creation and examines perceived online interactivity as its major antecedent in the context of the Chinese online travel community. Through a structural equation model analysis, it is found that Chinese online travel community users’ value co-creation behavior can be conceptualized as a three-dimensional model consisting of engagement, personalization and dependence, and their value co-creation behavior was effectively triggered by online interactivity. Path analysis revealed evidence for the underlying psychological mechanism of perceived online interactivity on consumers’ value co-creation via online trust. Based on these findings, theoretical contributions and managerial implications are discussed.

온라인 여행 커뮤니티의 신뢰, 구성원의 준사회적 상호작용, 조언수용 및 여행만족간의 관계

This study examined the structural relationships trust in online travel community, parasocial interaction, intention to follow advice and travel satisfaction. To empirically test the conceptual model, questionnaire were distributed to members of online travel community, who have experienced to obtain tourism information and/or to share information prior to and during their travel. A total of 351 community members participated in survey and the data were analyzed using SPSS 23.0 and AMOS 23.0 statistical program. The results showed that members’ perceived trust in online travel community influenced their parasocial interaction online positively. In addition, members’ trust in online travel community and parasocial interaction online pre- and during travel found to be predictors for intention to follow advice. Finally, the higher members’ intention to follow advice, the higher their travel satisfaction. These findings provide insightful implications with both practitioners and researchers.

Not all posts are treated equal: An empirical investigation of post replying behavior in an online travel community

The post replying behavior in online communities (OCs) has garnered little consideration, even though the feedback behavior represents the central social dynamic of OCs and greatly determines the vibrancy of OCs. To fill this gap, this study aims to identify major sharing post-related variables that explain the heterogeneity in the post replying behavior in knowledge sharing OCs. The research model is validated through a panel dataset assembled from an online travel community. The results reveal that sharing post length and vividness, contributors’ expertise and degree centrality, and members’ social interactions have significant associations with the number of replying posts.

Exploring the effect of heuristic factors on the popularity of user-curated ‘Best places to visit’ recommendations in an online travel community

In online travel communities, ‘Top-K best places to visit’ recommendations are gaining more attention from travelers due to their ubiquitous access to the Internet, but little empirical effort has been made to investigate what factors lead to the popularity of user-curated ‘best places to visit (BP2V)’ recommendations. This research therefore aims to identify and validate the heuristic factors affecting the popularity of BP2V recommendations. Based on the heuristic-systematic model (HSM) of persuasion, we derive recommender-related (i.e., recommender's identity disclosure, reputation, experience, and location of residency) and recommendation-related (i.e., number of places recommended, helpfulness rating, number of comments added, and length of recommendation) heuristic characteristics of BP2V recommendations and investigate their impact on recommendation popularity. In addition, this study examines the moderating effect of destination category (i.e., attractions, food, shopping, and activities) on the relationship between heuristic characteristics and the popularity of BP2V recommendations. Our empirical results, which were based on 565 ‘best places to visit in the U.S.’ recommendation postings from Qyer.com, a major online travel community in China, suggest that recommender's identity disclosure, reputation, number of places recommended, helpfulness rating, and length of recommendation are positively associated with recommendation popularity. We also found that the relationships between heuristic factors and the popularity of BP2V recommendations are contingent on destination category. This study will contribute to the body of knowledge on online travel communities and HSM and provide valuable implications for general travelers and managers in the tourism and hospitality industry.

Posting-related attributes driving differential engagement behaviors in online travel communities

Users’ engagement behaviors such as likings, sharing and social interactions in online communities are critically important to the viability and the ultimate success of these communities. However, empirical research investigating which posting-related attributes driving these participation behaviors still lags. The purpose of this study is to understand what and how posting-related attributes drive the engagement behaviors. Using travelogue data from a large traveling knowledge-sharing community, we used econometric models to investigate and compare the antecedents leading to three different kinds of engagement behavior that users exhibit in online communities (i.e., consuming, contributing, and creating). The results reveal that five attributes are associated with these engagement behaviors. These attributes demonstrate the differential effectiveness on the engagement behaviors with different intensities. Our empirical findings provide both theoretical and practical implications for online community operators to build a vibrant and successful online community.

Potentials of changing customer needs in a digital world – a conceptual model and recommendations for action in tourism

While a few studies have already shown the potential benefits of digitization so far, there are no empirically developed approaches demonstrating the potentials of changing customer needs in a digital world in the tourism. This paper develops such a conceptual model, which is able to explore the customer needs in the tourism industry. An empirical, qualitative data collection by expert interviews forms the data basis. Grounded Theory is used to evaluate the transcribed interviews, as this method is particularly suitable for identifying new or unknown relationships. This methodology of qualitative social research serves to derive theories from previously categorized data without using concepts generated from literature. The objective of this study is to provide recommendations for touristic companies that have to face the challenges and the changing market environment through digitization. The main factors influencing the potentials of changing customer needs identified (digital services, digital marketing, data mining and online travel communities) form the conceptual model in order to present recommendations for action. The results of the study show that a personalized approach to the customer on digital communication channels represents an essential requirement in the future provision of services. In order to meet the changing needs, bilateral communication between customers and companies must be guaranteed during the entire customer journey, especially in structurally weak regions.

A cumulative prospect theory approach to commuters’ day-to-day route-choice modeling with friends’ travel information

This paper investigates the effects of social interaction information from friends on commuters’ daily route choice decisions. Besides the actual route travel time shared among friends, both the amount and percentage of friends choosing each route are regarded as being influence factors. For estimating the factors’ relative importance, this paper first develops a day-to-day route-choice learning model with friends’ travel information based on the Cumulative Prospect Theory (CPT), and then designs and conducts a laboratory behavioral experiment to collect the statistical data associated with subjects’ actual route choice decisions. Experimental results show that a larger rate of social interactions in an online travel community does not necessarily lead to a better route-choice outcome for individuals or the whole system. Furthermore, the overall impact of the amount and percentage of friends choosing each route on the generation of perceived travel time may be negative or positive, depending on the number of members in an online travel community. Using the developed model, the endogenous reference points of the subjects are estimated to first increase and then decrease over simulated days till being roughly leveling off, and the average travel prospect values of the subjects on all routes are estimated to first increase, then decrease and finally level off over simulated days. We also discuss the implication of integrating friends’ travel information into modeling by comparing the forecast accuracies of the models with and without direct consideration of friends’ travel information, and improve the developed model by incorporating the overlapping effects of routes.

온라인 여행 커뮤니티의 신뢰 구성요인이 지식의 질 및 지식 제공 의도에 미치는 영향

Online travel communities are virtual social communities where community members seek information about travel-related products and share their knowledge related to destinations. This study investigated the effect of trust (honesty, benevolence and competence) on the quality of knowledge and examined whether or not the quality of knowledge influence knowledge contribution intention of members in online travel community. The conceptual model was designed based on the previous literature and tested empirically. For the empirical test, survey was conducted in Busan, Korea, and 371 responses were collected from the members of online travel community. The data collected were analyzed using SPSS and AMOS statistical program. The results revealed that honesty, benevolence, and competence have a positive impact on the quality of knowledge in online travel community. The quality of knowledge also have a positive influence on the knowledge contribution intention. In this study, practical and academic implications were given based on these findings.

텍스트 마이닝을 이용한 온라인 리뷰의 호텔 선택속성 분석

With the development of social media, consumers are sharing and spreading information rapidly. Since hotel reviews affect hotel image and reputation, it is important to understand the value of customers in hotel reviews. This is in order to consistently provide hotel quality, maintain brand loyalty and create new customers. Hotel companies need to determine which selection attributes are the most meaningful and relevant in online reviews written by consumers. To accomplish this, hotel reviews were collected using the data analysis tool ‘R’ in the online travel community Trip advisor. The text network was analyzed using UCINET6, Netdraw, and the obtained results were then visualized. The results showed that the frequency and network centrality of the attribute room, cleanliness level, staff ability, kindness level, accessibility, and location were all significantly high factors affecting hotel image and reputation. Furthermore, attributes related to the core product of the hotel are being treated as important evaluation items. Based on these results, theoretical and practical implications for hotel market segmentation and future marketing strategies are suggested.

Measuring customer social participation in online travel communities

PurposeThe purpose of this paper is to develop and validate a scale to measure customer social participation in brand communities, specifically e-travel companies’ communities.Design/methodology/approachA qualitative research has been undertaken to generate a pool of items. Based on Churchill’s (1979) scale development process, numerous reliability and validity tests have been conducted to confirm the scale structure. Data were collected through online and field surveys from the students and hotel guests who have either subscribed, liked or joined any e-travel service companies’ community brand page using any social networking site or have ever posted or considered reviews and ratings of any e-travel service companies via their official site or via a mobile app while planning their travel.FindingsThe findings depict nine items on a three-dimensional scale for measuring customer participation in travel brand communities created on social networking sites.Research limitations/implicationsThe findings provide important implications for hotel and travel managers and are likely to encourage future studies in the field of social media and travel brand communities.Originality/valueThis paper contributes to the literature by providing refinement to the distinct operationalization and conceptualization of customer online participation, specifically in social media-based travel brand communities. This paper is the first to develop a multidimensional scale of customer social participation in e-travel companies’ communities. This is a new addition to existing literature, as the majority of empirical studies in this field are from participation other than customer social participation and contexts different from e-travel companies.

온라인 여행 커뮤니티의 유용성과 의사사회적 상호작용이 이용자의 관광만족과 재방문의도에 미치는 영향: 커뮤니티 참여도의 조절효과를 중심으로

온라인 여행 커뮤니티의 유용성과 의사사회적 상호작용이 이용자의 관광만족과 재방문의도에 미치는 영향: 커뮤니티 참여도의 조절효과를 중심으로

빅데이터 기반의 사회연결망 분석을 이용한 관광지 이미지 인식에 관한 연구

This study aims to extract meaningful information through a social network analysis based on Big data in order to investigate if a tourist’s awareness of destination image favorably affects competitiveness of tourist destination. A web crawler was employed to gather online review data from 117 destinations and tourism products in Seoul, Korea using Tripadvisor. This web crawler is representative of the online travel community used throughout global tourism industry. Specifically, 23 image factors and 200 components composing two aspects of cognitive and affective images were derived using a system of text mining analysis. This study tried to identify and enhance destination competitiveness by investigating a tourist’s awareness in terms of their destination image. This was measured using indicators of network analysis that were degree centrality, closeness centrality, between centrality and eigenvector centrality. The following results were found: First) 7 image components help to create a positive image of tourist awareness in terms of destination image. Second) 14 image components feel psychologically close to tourists in terms of destination image. Third) 8 image components favorable influence and enhance the competitiveness of destination. Fourth) 11 image components have a greater impact greater than the others when tourists have a perceived destination image. Implications and suggestions are presented along with the findings of the study, which will contribute to the theoretical framework by suggesting a new perspective for measuring destination image based on Big data.

온라인 여행 커뮤니티의 유용성과 의사사회적 상호작용이 이용자의 관광만족과 재방문의도에 미치는 영향: 커뮤니티 참여도의 조절효과를 중심으로

온라인 여행 커뮤니티의 유용성과 의사사회적 상호작용이 이용자의 관광만족과 재방문의도에 미치는 영향: 커뮤니티 참여도의 조절효과를 중심으로