Does traveler satisfaction differ in various travel group compositions?: Evidence from online reviews

Purpose This study aims to investigate the online customer review behavior and determinants of overall satisfaction with hotels of travelers in various travel group compositions. Design/methodology/approach We collected data from online reviews of travelers in various travel group compositions from 600 hotels in 100 of the largest cities in the United States from Booking.com and used latent semantic analysis (LSA) to identify the positive and negative factors from online reviews of travelers in various travel group compositions. Then we used text regression to determine the influential factors of overall satisfaction of travelers in various travel group compositions. Findings We found that not all the positive and negative textual factors mined from travelers’ online reviews significantly influenced their overall satisfaction. In addition, the determinants of traveler satisfaction were different when travelers were in different travel group compositions. Research limitations/implications We found similar ...

[1]  A. Mattila,et al.  The role of tie strength on consumer dissatisfaction responses , 2012 .

[2]  Thanika Devi Juwaheer,et al.  Exploring international tourists' perceptions of hotel operations by using a modified SERVQUAL approach – a case study of Mauritius , 2004 .

[3]  B. Gu,et al.  First Step in Social Media - Measuring the Influence of Online Management Responses on Customer Satisfaction , 2011 .

[4]  Barry J. Babin,et al.  Atmospheric Affect as a Tool for Creating Value and Gaining Share of Customer , 2000 .

[5]  V. Mittal,et al.  Satisfaction, Repurchase Intent, and Repurchase Behavior: Investigating the Moderating Effect of Customer Characteristics , 2001 .

[6]  Murtaza Haider,et al.  Beyond the hype: Big data concepts, methods, and analytics , 2015, Int. J. Inf. Manag..

[7]  Markus Zanker,et al.  Automated Semantic Annotations of Tourism Resources Based on Geospatial Data , 2009, J. Inf. Technol. Tour..

[8]  Lidija Lalicic,et al.  Exploring the generalizability of discriminant word items and latent topics in online tourist reviews , 2017 .

[9]  H. Parsa,et al.  Building a model of commitment for Generation Y: An empirical study on e-travel retailers , 2011 .

[10]  W. Kim,et al.  The impact of social media reviews on restaurant performance: The moderating role of excellence certificate , 2016 .

[11]  I. Ajzen.  The theory of planned behavior , 1991 .

[12]  D. Mount,et al.  Other consumers in service encounters: a script theoretical perspective. , 2011 .

[13]  K. Weber,et al.  The stress of anonymous online reviews: a conceptual model and research agenda , 2015 .

[14]  Matthew K. O. Lee,et al.  What drives consumers to spread electronic word of mouth in online consumer-opinion platforms , 2012, Decis. Support Syst..

[15]  U. Gretzel,et al.  Influence of Star Rating and Ownership Structure on Brand Image of Mainland China Hotels , 2014 .

[16]  B. Latané.  The psychology of social impact. , 1981 .

[17]  F. Okumus,et al.  Understanding Satisfied and Dissatisfied Hotel Customers: Text Mining of Online Hotel Reviews , 2016 .

[18]  Zheng Xiang,et al.  A comparative analysis of major online review platforms: Implications for social media analytics in hospitality and tourism , 2017 .

[19]  Sunghyup Sean Hyun,et al.  Do luxury room amenities affect guests' willingness to pay? , 2015 .

[20]  Thorsten Teichert,et al.  Big data for big insights: Investigating language-specific drivers of hotel satisfaction with 412,784 user-generated reviews , 2017 .

[21]  W. Kim,et al.  The effects of perceived justice on recovery satisfaction, trust, word-of-mouth, and revisit intention in upscale hotels. , 2009 .

[22]  Shun Ye,et al.  Refreshing hotel satisfaction studies by reconfiguring customer review data , 2014 .

[23]  Bona Kim,et al.  Analysis of satisfiers and dissatisfiers in online hotel reviews on social media , 2016 .

[24]  Xiaolin Lin,et al.  Social commerce research: Definition, research themes and the trends , 2017, Int. J. Inf. Manag..

[25]  Stuart J. Barnes,et al.  Mining meaning from online ratings and reviews: Tourist satisfaction analysis using latent dirichlet allocation , 2017 .

[26]  Xun Xu,et al.  The antecedents of customer satisfaction and dissatisfaction toward various types of hotels: A text mining approach , 2016 .

[27]  R. Oliver.  A Cognitive Model of the Antecedents and Consequences of Satisfaction Decisions , 1980 .

[28]  Dwayne D. Gremler,et al.  Electronic word-of-mouth via consumer-opinion platforms: What motivates consumers to articulate themselves on the Internet? , 2004 .

[29]  Richard R. Perdue,et al.  The effects of cognitive, affective, and sensory attributes on hotel choice , 2013 .

[30]  Z. Schwartz,et al.  What can big data and text analytics tell us about hotel guest experience and satisfaction , 2015 .

[31]  Rob Law,et al.  A segmentation of online reviews by language groups: How English and non-English speakers rate hotels differently , 2015 .

[32]  Kyung Hyan Yoo,et al.  What Motivates Consumers to Write Online Travel Reviews? , 2008, J. Inf. Technol. Tour..

[33]  R. Law,et al.  Analyzing changes in hotel customers’ expectations by trip mode , 2013 .

[34]  Ananthanarayanan Parasuraman,et al.  Do customer relationships mitigate or amplify failure responses , 2013 .

[35]  Kyung Hyan Yoo,et al.  Influence of personality on travel-related consumer-generated media creation , 2011, Comput. Hum. Behav..

[36]  M. Sotiriadis.  Sharing tourism experiences in social media , 2017 .

[37]  A. L. McGill,et al.  Consuming With Others: Social Influences on Moment-To-Moment and Retrospective Evaluations of an Experience , 2008 .

[38]  Karen L. Xie,et al.  The business value of online consumer reviews and management response to hotel performance. , 2014 .

[39]  Mohammad Salehan,et al.  Predicting the performance of online consumer reviews: A sentiment mining approach to big data analytics , 2014, Decis. Support Syst..

[40]  M. Geetha,et al.  Relationship between customer sentiment and online customer ratings for hotels - An empirical analysis , 2017 .

[41]  B. Pan,et al.  A retrospective view of electronic word-of-mouth in hospitality and tourism management , 2017 .

[42]  R. Law,et al.  Hospitality and Tourism Online Reviews: Recent Trends and Future Directions , 2015 .

[43]  Neha Singh,et al.  Service failures and recovery actions in the hotel industry: A text-mining approach , 2011 .

[44]  W. Deng,et al.  A customer satisfaction index model for international tourist hotels: Integrating consumption emotions into the American Customer Satisfaction Index , 2013 .

[45]  U. Gretzel,et al.  Communicative functions of Online Travel Review titles: a pragmatic and linguistic investigation of destination and attraction OTR titles , 2013 .

[46]  Ling Liu,et al.  Manipulation of online reviews: An analysis of ratings, readability, and sentiments , 2012, Decis. Support Syst..

[47]  Linchi Kwok,et al.  Factors contributing to the helpfulness of online hotel reviews , 2016 .

[48]  Gilbert A. Churchill,et al.  An Investigation into the Determinants of Customer Satisfaction , 1982 .

[49]  Marianna Sigala,et al.  Reviewing the Profile and Behaviour of Internet Users , 2004 .

[50]  D. Price,et al.  Some general laws of human emotion: Interrelationships between intensities of desire, expectation, and emotional feeling. , 1984 .

[51]  R. Law,et al.  INFORMATION TECHNOLOGY APPLICATIONS IN HOSPITALITY AND TOURISM: A REVIEW OF PUBLICATIONS FROM 2005 TO 2007 , 2009 .

[52]  Juan C. Valle-Lisboa,et al.  The uncovering of hidden structures by Latent Semantic Analysis , 2007, Inf. Sci..

[53]  Dimple R. Thadani,et al.  The impact of electronic word-of-mouth communication: A literature analysis and integrative model , 2012, Decis. Support Syst..

[54]  Linchi Kwok,et al.  Thematic framework of online review research: A systematic analysis of contemporary literature on seven major hospitality and tourism journals , 2017 .

[55]  James Allan,et al.  A Comparative Study of Utilizing Topic Models for Information Retrieval , 2009, ECIR.

[56]  Victor R. Prybutok,et al.  Causal Latent Semantic Analysis (cLSA): An Illustration , 2011 .

[57]  A. S. Cantallops,et al.  International Journal of Hospitality Management New Consumer Behavior: a Review of Research on Ewom and Hotels , 2022 .

[58]  Thomas L. Ngo-Ye,et al.  The influence of reviewer engagement characteristics on online review helpfulness: A text regression model , 2014, Decis. Support Syst..

[59]  Fred Bronner,et al.  Vacationers and eWOM: Who Posts, and Why, Where, and What? , 2011 .

[60]  Ana Catarina Calheiros,et al.  Sentiment Classification of Consumer-Generated Online Reviews Using Topic Modeling , 2017 .

[61]  David C. Bojanic,et al.  A Structural Analysis of Value, Quality, and Price Perceptions of Business and Leisure Travelers , 2000 .

[62]  Johann Füller,et al.  Customer delight and market segmentation: an application of the three-factor theory of customer satisfaction on life style groups. , 2008 .

[63]  Han Shen,et al.  The impact of language style on consumers′ reactions to online reviews , 2017 .

[64]  Hao Luo,et al.  Theoretical, empirical, and operational models in hotel location research , 2014 .

[65]  Wonjoon Kim,et al.  From valence to emotions: Exploring the distribution of emotions in online product reviews , 2016, Decis. Support Syst..

[66]  Yibai Li,et al.  Business intelligence in online customer textual reviews: Understanding consumer perceptions and influential factors , 2017, Int. J. Inf. Manag..

[67]  Shailesh S. Kulkarni,et al.  The Use of Latent Semantic Analysis in Operations Management Research , 2014, Decis. Sci..