IDEAS home Printed from https://ideas.repec.org/a/eee/jbrese/v199y2025ics0148296325002553.html

When reviews speak through pictures: Visual content and its influence on helpfulness

Author

Listed:
  • Vidaurreta-Apesteguia, Paula
  • Alzate, Miriam
  • Arce-Urriza, Marta
  • Armendáriz-Iñigo, José Enrique
  • D’Acunto, David

Abstract

This research investigates the impact of service quality dimensions displayed in user-generated photos on their perceived helpfulness. Building on the SERVQUAL model and the Haywood-Farmer framework, we propose a novel methodology that integrates advanced image-to-caption techniques with topic modeling algorithms and negative binomial regression to extract, interpret, and quantify the effect of visuals on review helpfulness. Two studies were conducted relying on two sample of online reviews from two tourism-related service types (5,293 hotel reviews from Cancun, Mexico, and 11,252 spa and wellness reviews from Iceland). The results underline the role of visuals in affecting review helpfulness, with aspects such as “Room” “Leisure” and “Hotel Outdoor” positively impacting review helpfulness in hotels and “Natural Water Features” emerging as significant in spa and wellness reviews. Overall, this study underscores the relevance of tangibles and empathy in service evaluation, providing actionable strategies for businesses to optimize visual content.

Suggested Citation

  • Vidaurreta-Apesteguia, Paula & Alzate, Miriam & Arce-Urriza, Marta & Armendáriz-Iñigo, José Enrique & D’Acunto, David, 2025. "When reviews speak through pictures: Visual content and its influence on helpfulness," Journal of Business Research, Elsevier, vol. 199(C).
    • Handle: RePEc:eee:jbrese:v:199:y:2025:i:c:s0148296325002553
    DOI: 10.1016/j.jbusres.2025.115432
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0148296325002553
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.jbusres.2025.115432?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to

    for a different version of it.

    References listed on IDEAS

    as
    1. Kim, Molan & Lee, Seung Min & Choi, Sanghak & Kim, Sang Yong, 2021. "Impact of visual information on online consumer review behavior: Evidence from a hotel booking website," Journal of Retailing and Consumer Services, Elsevier, vol. 60(C).
    2. Ert, Eyal & Fleischer, Aliza & Magen, Nathan, 2016. "Trust and reputation in the sharing economy: The role of personal photos in Airbnb," Tourism Management, Elsevier, vol. 55(C), pages 62-73.
    3. Papathanassis, Alexis & Knolle, Friederike, 2011. "Exploring the adoption and processing of online holiday reviews: A grounded theory approach," Tourism Management, Elsevier, vol. 32(2), pages 215-224.
    4. R. Filieri & M. Mariani, 2021. "The role of cultural values in consumers' evaluation of online review helpfulness: a big data approach," Post-Print hal-04713693, HAL.
    5. Ashlee Humphreys & Rebecca Jen-Hui Wang & Eileen FischerEditor & Linda PriceAssociate Editor, 2018. "Automated Text Analysis for Consumer Research," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 44(6), pages 1274-1306.
    6. Fang, Bin & Ye, Qiang & Kucukusta, Deniz & Law, Rob, 2016. "Analysis of the perceived value of online tourism reviews: Influence of readability and reviewer characteristics," Tourism Management, Elsevier, vol. 52(C), pages 498-506.
    7. R. Filieri & E. Raguseo & C. Vitari, 2021. "Extremely Negative Ratings and Online Consumer Review Helpfulness: The Moderating Role of Product Quality Signals," Post-Print hal-04713689, HAL.
    8. R. Filieri & Fraser Mcleay & Bruce Tsui & Zhibin Lin, 2018. "Consumer perceptions of information helpfulness and determinants of purchase intention in online consumer reviews of services," Post-Print hal-04779103, HAL.
    9. Kübler, Raoul V. & Lobschat, Lara & Welke, Lina & van der Meij, Hugo, 2024. "The effect of review images on review helpfulness: A contingency approach," Journal of Retailing, Elsevier, vol. 100(1), pages 5-23.
    10. R. Filieri & Z. Lin & G. Pino & S. Alguezaui & A. Inversini, 2021. "The role of visual cues in eWOM on consumers’ behavioral intention and decisions," Post-Print hal-04779114, HAL.
    11. Bitty Balducci & Detelina Marinova, 2018. "Unstructured data in marketing," Journal of the Academy of Marketing Science, Springer, vol. 46(4), pages 557-590, July.
    12. Albayrak, Tahir & Caber, Meltem, 2015. "Prioritisation of the hotel attributes according to their influence on satisfaction: A comparison of two techniques," Tourism Management, Elsevier, vol. 46(C), pages 43-50.
    13. de Haan, Evert & Padigar, Manjunath & El Kihal, Siham & Kübler, Raoul & Wieringa, Jaap E., 2024. "Unstructured data research in business: Toward a structured approach," Journal of Business Research, Elsevier, vol. 177(C).
    14. Filieri, Raffaele, 2015. "What makes online reviews helpful? A diagnosticity-adoption framework to explain informational and normative influences in e-WOM," Journal of Business Research, Elsevier, vol. 68(6), pages 1261-1270.
    15. repec:hal:journl:hal-03511272 is not listed on IDEAS
    16. A. Camilleri & R. Filieri, 2023. "Customer satisfaction and loyalty with online consumer reviews: Factors affecting revisit intentions," Post-Print hal-04779131, HAL.
    17. Alzate, Miriam & Arce-Urriza, Marta & Cebollada, Javier, 2022. "Mining the text of online consumer reviews to analyze brand image and brand positioning," Journal of Retailing and Consumer Services, Elsevier, vol. 67(C).
    18. Hu, Ya-Han & Chen, Kuanchin, 2016. "Predicting hotel review helpfulness: The impact of review visibility, and interaction between hotel stars and review ratings," International Journal of Information Management, Elsevier, vol. 36(6), pages 929-944.
    19. R. Filieri & S. Alguezaui & F. Galati & E. Raguseo, 2023. "Customer experience with standard and premium Peer-To-Peer offerings: a mixed-method combining text analytics and qualitative analysis," Post-Print hal-04474167, HAL.
    20. Raffaele Filieri & Elisabetta Raguseo & Claudio Vitari, 2018. "When are extreme ratings more helpful? Empirical evidence on the moderating effects of review characteristics and product type," Grenoble Ecole de Management (Post-Print) halshs-01923243, HAL.
    21. Deng, Ning & Li, Xiang (Robert), 2018. "Feeling a destination through the “right” photos: A machine learning model for DMOs’ photo selection," Tourism Management, Elsevier, vol. 65(C), pages 267-278.
    22. R. Filieri & Elisabetta Raguseo & Claudio Vitari, 2019. "What moderates the influence of extremely negative ratings? The role of review and reviewer characteristics," Post-Print hal-04779104, HAL.
    23. Robert Zinko & Paul Stolk & Zhan Furner & Brad Almond, 2020. "A picture is worth a thousand words: how images influence information quality and information load in online reviews," Electronic Markets, Springer;IIM University of St. Gallen, vol. 30(4), pages 775-789, December.
    24. repec:hal:journl:hal-04781815 is not listed on IDEAS
    25. Øystein Moen & Lars Jaako Havro & Einar Bjering, 2017. "Online consumers reviews: Examining the moderating effects of product type and product popularity on the review impact on sales," Cogent Business & Management, Taylor & Francis Journals, vol. 4(1), pages 1368114-136, January.
    26. Raffaele Filieri & Elisabetta Raguseo & Claudio Vitari, 2019. "What moderates the influence of extremely negative ratings? The role of review and reviewer characteristics," Post-Print hal-03511270, HAL.
    27. Filieri, Raffaele & Lin, Zhibin & Pino, Giovanni & Alguezaui, Salma & Inversini, Alessandro, 2021. "The role of visual cues in eWOM on consumers’ behavioral intention and decisions," Journal of Business Research, Elsevier, vol. 135(C), pages 663-675.
    28. Miyea Kim & Jeongsoo Han & Mina Jun, 2020. "Do same-level review ratings have the same level of review helpfulness? The role of information diagnosticity in online reviews," Information Technology & Tourism, Springer, vol. 22(4), pages 563-591, December.
    29. Dobin Yim & Timothy Malefyt & Jiban Khuntia, 2021. "Is a picture worth a thousand views? Measuring the effects of travel photos on user engagement using deep learning algorithms," Electronic Markets, Springer;IIM University of St. Gallen, vol. 31(3), pages 619-637, September.
    30. Raffaele Filieri & Elisabetta Raguseo & Claudio Vitari, 2021. "Extremely Negative Ratings and Online Consumer Review Helpfulness: The Moderating Role of Product Quality Signals," Post-Print hal-03511351, HAL.
    31. Raffaele Filieri & Elisabetta Raguseo & Claudio Vitari, 2018. "When are extreme ratings more helpful? Empirical evidence on the moderating effects of review characteristics and product type," Post-Print halshs-01923243, HAL.
    32. Filieri, Raffaele & Alguezaui, Salma & Galati, Francesco & Raguseo, Elisabetta, 2023. "Customer experience with standard and premium Peer-To-Peer offerings: A mixed-method combining text analytics and qualitative analysis," Journal of Business Research, Elsevier, vol. 167(C).
    33. Gerald Häubl & Valerie Trifts, 2000. "Consumer Decision Making in Online Shopping Environments: The Effects of Interactive Decision Aids," Marketing Science, INFORMS, vol. 19(1), pages 4-21, May.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Filieri, Raffaele & Lin, Zhibin & Pino, Giovanni & Alguezaui, Salma & Inversini, Alessandro, 2021. "The role of visual cues in eWOM on consumers’ behavioral intention and decisions," Journal of Business Research, Elsevier, vol. 135(C), pages 663-675.
    2. Yang Liu & Xingchen Ding & Maomao Chi & Jiang Wu & Lili Ma, 2024. "Assessing the helpfulness of hotel reviews for information overload: a multi-view spatial feature approach," Information Technology & Tourism, Springer, vol. 26(1), pages 59-87, March.
    3. Li, Yuanshuo & Zhang, Zili & Pedersen, Susanne & Liu, Xudong & Zhang, Ziqiong, 2023. "The influence of relative popularity on negative fake reviews: A case study on restaurant reviews," Journal of Business Research, Elsevier, vol. 162(C).
    4. Swagato Chatterjee, 2025. "Effect of construal level on the drivers of online-review-helpfulness," Electronic Commerce Research, Springer, vol. 25(2), pages 1115-1143, April.
    5. Herhausen, Dennis & Ludwig, Stephan & Abedin, Ehsan & Haque, Nasim Ul & de Jong, David, 2025. "From words to insights: Text analysis in business research," Journal of Business Research, Elsevier, vol. 198(C).
    6. R. Filieri & F. Acikgoz & D. Hao, 2023. "Electronic word-of-mouth from video bloggers: The role of content quality and source homophily across hedonic and utilitarian products," Post-Print hal-04713695, HAL.
    7. Han Yan & Rui Wang & Jin Qin, 2025. "Design factors of the tag-based review summarization system: Perspective of the consumers’ intention to use," Electronic Markets, Springer;IIM University of St. Gallen, vol. 35(1), pages 1-17, December.
    8. G. Onofrei & R. Filieri & L. Kennedy, 2022. "Social media interactions, purchase intention, and behavioural engagement on social networking platforms: The mediating role of source and content factors," Post-Print hal-04779119, HAL.
    9. Sangjae Lee & Kun Chang Lee & Joon Yeon Choeh, 2020. "Using Bayesian Network to Predict Online Review Helpfulness," Sustainability, MDPI, vol. 12(17), pages 1-17, August.
    10. Román, Sergio & Riquelme, Isabel P. & Iacobucci, Dawn, 2024. "Antecedents and consequences of perceived helpfulness of extremely positive and exaggerated reviews," Journal of Retailing and Consumer Services, Elsevier, vol. 80(C).
    11. Daniel Baier & Reinhold Decker & Yana Asenova, 2025. "Collecting and Analyzing User-Generated Content for Decision Support in Marketing Management: An Overview of Methods and Use Cases," Schmalenbach Journal of Business Research, Springer, vol. 77(3), pages 419-455, September.
    12. Cai, Xiaowei & Cebollada, Javier & Cortiñas, Mónica, 2023. "Impact of seller- and buyer-created content on product sales in the electronic commerce platform: The role of informativeness, readability, multimedia richness, and extreme valence," Journal of Retailing and Consumer Services, Elsevier, vol. 70(C).
    13. Barta, Sergio & Gurrea, Raquel & Flavián, Carlos, 2023. "Consequences of consumer regret with online shopping," Journal of Retailing and Consumer Services, Elsevier, vol. 73(C).
    14. Moradi, Masoud & Dass, Mayukh & Kumar, Piyush, 2023. "Differential effects of analytical versus emotional rhetorical style on review helpfulness," Journal of Business Research, Elsevier, vol. 154(C).
    15. Raoofpanah, Iman & Zamudio, César & Groening, Christopher, 2023. "Review reader segmentation based on the heterogeneous impacts of review and reviewer attributes on review helpfulness: A study involving ZIP code data," Journal of Retailing and Consumer Services, Elsevier, vol. 72(C).
    16. Elvira Ismagilova & Emma L. Slade & Nripendra P. Rana & Yogesh K. Dwivedi, 2020. "The Effect of Electronic Word of Mouth Communications on Intention to Buy: A Meta-Analysis," Information Systems Frontiers, Springer, vol. 22(5), pages 1203-1226, October.
    17. Raffaele Filieri & Elisabetta Raguseo & Claudio Vitari, 2018. "What moderates the influence of extremely negative ratings? The role of review and reviewer characteristics," Post-Print halshs-01923196, HAL.
    18. Yi Feng & Yunqiang Yin & Dujuan Wang & Lalitha Dhamotharan & Joshua Ignatius & Ajay Kumar, 2023. "Diabetic patient review helpfulness: unpacking online drug treatment reviews by text analytics and design science approach," Annals of Operations Research, Springer, vol. 328(1), pages 387-418, September.
    19. Mariani, Marcello M. & Borghi, Matteo & Laker, Benjamin, 2023. "Do submission devices influence online review ratings differently across different types of platforms? A big data analysis," Technological Forecasting and Social Change, Elsevier, vol. 189(C).
    20. Xu, Jian & Zhang, Wei & Li, Hengyun & Zheng, Xiang (Kevin) & Zhang, Jing, 2024. "User-generated photos in hotel demand forecasting," Annals of Tourism Research, Elsevier, vol. 108(C).

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:jbrese:v:199:y:2025:i:c:s0148296325002553. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/jbusres .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.