IDEAS home Printed from https://ideas.repec.org/a/eee/joreco/v82y2025ics0969698924003552.html
   My bibliography  Save this article

From online reviews to smartwatch recommendation: An integrated aspect-based sentiment analysis framework

Author

Listed:
  • Ray, Rajeev Kumar
  • Singh, Amit

Abstract

In the current landscape, smartwatches have gained popularity as wearable devices thanks to their fitness tracking and health monitoring capabilities. However, the abundance of features and options has made it challenging to select the right alternative. In this regard, we propose a text analytics-based product recommender system that leverages online reviews as peers' recommendations and creates a shortlist of available alternatives based on existing users’ perceptions. It uses a pre-trained transformer-based aspect-level sentiment analysis algorithm, InstructABSA, to quantify consumer sentiments expressed in textual reviews, which are analysed using the integrated House of Quality (HoQ) and Preference Ranking Organisation Method for Enrichment Evaluation-II (PROMETHEE-II) to construct a relative performance index for the selected manufacturers. The proposed framework may assist potential customers in making well-informed purchase decisions and help manufacturers understand their relative position in the market. It also helps customers compare the alternatives concerning selected features and associated consumer perceptions. In addition, manufacturers may use it to discover their perceived strengths and weaknesses. The proposed framework is tested on a review dataset pertaining to 12 smartwatch manufacturers, and their relative ranks are proposed.

Suggested Citation

  • Ray, Rajeev Kumar & Singh, Amit, 2025. "From online reviews to smartwatch recommendation: An integrated aspect-based sentiment analysis framework," Journal of Retailing and Consumer Services, Elsevier, vol. 82(C).
    • Handle: RePEc:eee:joreco:v:82:y:2025:i:c:s0969698924003552
    DOI: 10.1016/j.jretconser.2024.104059
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0969698924003552
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.jretconser.2024.104059?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 search for a different version of it.

    References listed on IDEAS

    as
    1. Kar, Arpan Kumar & Dwivedi, Yogesh K., 2020. "Theory building with big data-driven research – Moving away from the “What” towards the “Why”," International Journal of Information Management, Elsevier, vol. 54(C).
    2. Chang, Yung-Chun & Ku, Chih-Hao & Chen, Chun-Hung, 2019. "Social media analytics: Extracting and visualizing Hilton hotel ratings and reviews from TripAdvisor," International Journal of Information Management, Elsevier, vol. 48(C), pages 263-279.
    3. Mike Thelwall & Kevan Buckley & Georgios Paltoglou & Di Cai & Arvid Kappas, 2010. "Sentiment strength detection in short informal text," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 61(12), pages 2544-2558, December.
    4. Xiao, Yan & Li, Congdong & Thürer, Matthias & Liu, Yide & Qu, Ting, 2022. "User preference mining based on fine-grained sentiment analysis," Journal of Retailing and Consumer Services, Elsevier, vol. 68(C).
    5. Liu, Yang & Shi, Jiale & Huang, Fei & Hou, Jingrui & Zhang, Chengzhi, 2024. "Unveiling consumer preferences in automotive reviews through aspect-based opinion generation," Journal of Retailing and Consumer Services, Elsevier, vol. 77(C).
    6. T. Ravichandran & Chaoqun Deng, 2023. "Effects of Managerial Response to Negative Reviews on Future Review Valence and Complaints," Information Systems Research, INFORMS, vol. 34(1), pages 319-341, March.
    7. Sánchez-Franco, Manuel J. & Arenas-Márquez, Francisco J. & Alonso-Dos-Santos, Manuel, 2021. "Using structural topic modelling to predict users’ sentiment towards intelligent personal agents. An application for Amazon’s echo and Google Home," Journal of Retailing and Consumer Services, Elsevier, vol. 63(C).
    8. Zhang, Jason Q. & Craciun, Georgiana & Shin, Dongwoo, 2010. "When does electronic word-of-mouth matter? A study of consumer product reviews," Journal of Business Research, Elsevier, vol. 63(12), pages 1336-1341, December.
    9. Jia Huang & Ling-Xiang Mao & Hu-Chen Liu & Min-shun Song, 2022. "Quality function deployment improvement: A bibliometric analysis and literature review," Quality & Quantity: International Journal of Methodology, Springer, vol. 56(3), pages 1347-1366, June.
    10. Martí Bigorra, Anna & Isaksson, Ove & Karlberg, Magnus, 2020. "Semi-autonomous methodology to validate and update customer needs database through text data analytics," International Journal of Information Management, Elsevier, vol. 52(C).
    11. Bharati Sanjay Ainapure & Reshma Nitin Pise & Prathiba Reddy & Bhargav Appasani & Avireni Srinivasulu & Mohammad S. Khan & Nicu Bizon, 2023. "Sentiment Analysis of COVID-19 Tweets Using Deep Learning and Lexicon-Based Approaches," Sustainability, MDPI, vol. 15(3), pages 1-21, January.
    12. Mitra, Satanik & Jenamani, Mamata, 2020. "OBIM: A computational model to estimate brand image from online consumer review," Journal of Business Research, Elsevier, vol. 114(C), pages 213-226.
    13. Antonio Moreno-Ortiz & Soluna Salles-Bernal & Aroa Orrequia-Barea, 2019. "Design and validation of annotation schemas for aspect-based sentiment analysis in the tourism sector," Information Technology & Tourism, Springer, vol. 21(4), pages 535-557, December.
    14. Vairetti, Carla & Aránguiz, Ignacio & Maldonado, Sebastián & Karmy, Juan Pablo & Leal, Alonso, 2024. "Analytics-driven complaint prioritisation via deep learning and multicriteria decision-making," European Journal of Operational Research, Elsevier, vol. 312(3), pages 1108-1118.
    15. Dong Zhang & Chong Wu & Jiaming Liu, 2020. "Ranking products with online reviews: A novel method based on hesitant fuzzy set and sentiment word framework," Journal of the Operational Research Society, Taylor & Francis Journals, vol. 71(3), pages 528-542, March.
    16. Cheah, Jun-Hwa & Lim, Xin-Jean & Ting, Hiram & Liu, Yide & Quach, Sara, 2022. "Are privacy concerns still relevant? Revisiting consumer behaviour in omnichannel retailing," Journal of Retailing and Consumer Services, Elsevier, vol. 65(C).
    17. Chen, Yubo & Fay, Scott & Wang, Qi, 2011. "The Role of Marketing in Social Media: How Online Consumer Reviews Evolve," Journal of Interactive Marketing, Elsevier, vol. 25(2), pages 85-94.
    18. Praveen, S.V. & Gajjar, Pranshav & Ray, Rajeev Kumar & Dutt, Ashutosh, 2024. "Crafting clarity: Leveraging large language models to decode consumer reviews," Journal of Retailing and Consumer Services, Elsevier, vol. 81(C).
    19. Peiyu Chen & Lorin M. Hitt & Yili Hong & Shinyi Wu, 2021. "Measuring Product Type and Purchase Uncertainty with Online Product Ratings: A Theoretical Model and Empirical Application," Information Systems Research, INFORMS, vol. 32(4), pages 1470-1489, December.
    20. Carolin Siepmann & Pascal Kowalczuk, 2021. "Understanding continued smartwatch usage: the role of emotional as well as health and fitness factors," Electronic Markets, Springer;IIM University of St. Gallen, vol. 31(4), pages 795-809, December.
    21. Yi, Jisu & Oh, Yun Kyung, 2022. "The informational value of multi-attribute online consumer reviews: A text mining approach," Journal of Retailing and Consumer Services, Elsevier, vol. 65(C).
    22. Zhang, Lei & Xuan, Yan & Li, Ziqi & Gao, Pengfei & Zheng, Yu, 2024. "How to obtain customer requirements for each stage of the product life cycle from online reviews: Using mobile phones as an example," Journal of Retailing and Consumer Services, Elsevier, vol. 80(C).
    23. Sharan Srinivas & Surya Ramachandiran, 2024. "Passenger intelligence as a competitive opportunity: unsupervised text analytics for discovering airline-specific insights from online reviews," Annals of Operations Research, Springer, vol. 333(2), pages 1045-1075, February.
    24. Bertrand Mareschal & Jean Pierre Brans & Philippe Vincke, 1986. "How to select and how to rank projects: the Prométhée method," ULB Institutional Repository 2013/9307, ULB -- Universite Libre de Bruxelles.
    25. Raghavendra, Ananya Hadadi & Bala, Pradip Kumar & Mukherjee, Arindam, 2024. "Text mining analysis of retail and consumer service leaders' sustainability narratives: Are they actually true?," Journal of Retailing and Consumer Services, Elsevier, vol. 80(C).
    26. Kumar, Anand & Bala, Pradip Kumar & Chakraborty, Shibashish & Behera, Rajat Kumar, 2024. "Exploring antecedents impacting user satisfaction with voice assistant app: A text mining-based analysis on Alexa services," Journal of Retailing and Consumer Services, Elsevier, vol. 76(C).
    27. Zhang, Yihan & Li, Kai & Qian, Chen & Li, Xiaotong & Yuan, Qinjian, 2024. "How real-time interaction and sentiment influence online sales? Understanding the role of live streaming danmaku," Journal of Retailing and Consumer Services, Elsevier, vol. 78(C).
    28. Brans, J. P. & Vincke, Ph. & Mareschal, B., 1986. "How to select and how to rank projects: The method," European Journal of Operational Research, Elsevier, vol. 24(2), pages 228-238, February.
    29. Mike Thelwall & Kevan Buckley & Georgios Paltoglou & Di Cai & Arvid Kappas, 2010. "Sentiment strength detection in short informal text," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 61(12), pages 2544-2558, December.
    30. Chatterjee, Swagato & Goyal, Divesh & Prakash, Atul & Sharma, Jiwan, 2021. "Exploring healthcare/health-product ecommerce satisfaction: A text mining and machine learning application," Journal of Business Research, Elsevier, vol. 131(C), pages 815-825.
    31. Richard Frankel & Jared Jennings & Joshua Lee, 2022. "Disclosure Sentiment: Machine Learning vs. Dictionary Methods," Management Science, INFORMS, vol. 68(7), pages 5514-5532, July.
    32. Kearney, Colm & Liu, Sha, 2014. "Textual sentiment in finance: A survey of methods and models," International Review of Financial Analysis, Elsevier, vol. 33(C), pages 171-185.
    33. Basu, Bibaswan & Sebastian, M.P. & Kar, Arpan Kumar, 2024. "What affects the promoting intention of mobile banking services? Insights from mining consumer reviews," Journal of Retailing and Consumer Services, Elsevier, vol. 77(C).
    34. Arpan Kumar Kar, 2021. "What Affects Usage Satisfaction in Mobile Payments? Modelling User Generated Content to Develop the “Digital Service Usage Satisfaction Model”," Information Systems Frontiers, Springer, vol. 23(5), pages 1341-1361, September.
    35. Singh, Jyoti Prakash & Irani, Seda & Rana, Nripendra P. & Dwivedi, Yogesh K. & Saumya, Sunil & Kumar Roy, Pradeep, 2017. "Predicting the “helpfulness” of online consumer reviews," Journal of Business Research, Elsevier, vol. 70(C), pages 346-355.
    36. Ray, Arghya & Bala, Pradip Kumar & Rana, Nripendra P., 2021. "Exploring the drivers of customers’ brand attitudes of online travel agency services: A text-mining based approach," Journal of Business Research, Elsevier, vol. 128(C), pages 391-404.
    37. Jeong, Byeongki & Yoon, Janghyeok & Lee, Jae-Min, 2019. "Social media mining for product planning: A product opportunity mining approach based on topic modeling and sentiment analysis," International Journal of Information Management, Elsevier, vol. 48(C), pages 280-290.
    38. Arpan Kumar Kar & Sunil Kumar & P. Vigneswara Ilavarasan, 2021. "Modelling the Service Experience Encounters Using User-Generated Content: A Text Mining Approach," Global Journal of Flexible Systems Management, Springer;Global Institute of Flexible Systems Management, vol. 22(4), pages 267-288, December.
    39. Sykora, Martin & Elayan, Suzanne & Hodgkinson, Ian R. & Jackson, Thomas W. & West, Andrew, 2022. "The power of emotions: Leveraging user generated content for customer experience management," Journal of Business Research, Elsevier, vol. 144(C), pages 997-1006.
    40. 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.
    41. Saurabh Kumar & Pradeep Kumar & Bharat Bhasker, 2018. "Interplay between trust, information privacy concerns and behavioural intention of users on online social networks," Behaviour and Information Technology, Taylor & Francis Journals, vol. 37(6), pages 622-633, June.
    42. Charu Gupta & Amita Jain & Nisheeth Joshi, 2019. "DE-ForABSA: A Novel Approach to Forecast Automobiles Sales Using Aspect Based Sentiment Analysis and Differential Evolution," International Journal of Information Retrieval Research (IJIRR), IGI Global, vol. 9(1), pages 33-49, January.
    43. Alantari, Huwail J. & Currim, Imran S. & Deng, Yiting & Singh, Sameer, 2022. "An empirical comparison of machine learning methods for text-based sentiment analysis of online consumer reviews," International Journal of Research in Marketing, Elsevier, vol. 39(1), pages 1-19.
    44. Moro, Sérgio & Ramos, Pedro & Esmerado, Joaquim & Jalali, Seyed Mohammad Jafar, 2019. "Can we trace back hotel online reviews’ characteristics using gamification features?," International Journal of Information Management, Elsevier, vol. 44(C), pages 88-95.
    45. Swagato Chatterjee & Prasenjit Mandal & Krishanu Rakshit, 2023. "Exploring the antecedents for hospitality reviewers’ trustworthiness and its impact on business patronage," Post-Print hal-04211062, HAL.
    46. Xu, Xun & Wang, Xuequn & Li, Yibai & Haghighi, Mohammad, 2017. "Business intelligence in online customer textual reviews: Understanding consumer perceptions and influential factors," International Journal of Information Management, Elsevier, vol. 37(6), pages 673-683.
    47. Pradeep K. Chintagunta & Shyam Gopinath & Sriram Venkataraman, 2010. "The Effects of Online User Reviews on Movie Box Office Performance: Accounting for Sequential Rollout and Aggregation Across Local Markets," Marketing Science, INFORMS, vol. 29(5), pages 944-957, 09-10.
    48. Rajat Kumar Behera & Pradip Kumar Bala & Nripendra P. Rana & Hatice Kizgin, 2022. "A Techno-Business Platform to Improve Customer Experience Following the Brand Crisis Recovery: A B2B Perspective," Information Systems Frontiers, Springer, vol. 24(6), pages 2027-2051, December.
    49. Stanca, Liana & Dabija, Dan-Cristian & Câmpian, Veronica, 2023. "Qualitative analysis of customer behavior in the retail industry during the COVID-19 pandemic: A word-cloud and sentiment analysis approach," Journal of Retailing and Consumer Services, Elsevier, vol. 75(C).
    50. Alan S. Abrahams & Weiguo Fan & G. Alan Wang & Zhongju (John) Zhang & Jian Jiao, 2015. "An Integrated Text Analytic Framework for Product Defect Discovery," Production and Operations Management, Production and Operations Management Society, vol. 24(6), pages 975-990, June.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Bai, Ye & Yu-Buck, Grace, 2025. "Identifying targeted needs from online marketer- and user-generated data," Journal of Retailing and Consumer Services, Elsevier, vol. 84(C).
    2. Wu, Peng & Sun, Shiyong & Zhou, Ligang & Yao, Yao & Deveci, Muhammet, 2025. "Platforms empower: Mining online reviews for supporting consumers decisions," Journal of Retailing and Consumer Services, Elsevier, vol. 84(C).

    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. Wu, Peng & Sun, Shiyong & Zhou, Ligang & Yao, Yao & Deveci, Muhammet, 2025. "Platforms empower: Mining online reviews for supporting consumers decisions," Journal of Retailing and Consumer Services, Elsevier, vol. 84(C).
    2. Praveen, S.V. & Gajjar, Pranshav & Ray, Rajeev Kumar & Dutt, Ashutosh, 2024. "Crafting clarity: Leveraging large language models to decode consumer reviews," Journal of Retailing and Consumer Services, Elsevier, vol. 81(C).
    3. Kumari, Vandana & Bala, Pradip Kumar & Chakraborty, Shibashish, 2024. "A text mining approach to explore factors influencing consumer intention to use metaverse platform services: Insights from online customer reviews," Journal of Retailing and Consumer Services, Elsevier, vol. 81(C).
    4. Bellary, Sreevatsa & Bala, Pradip Kumar & Chakraborty, Shibashish, 2024. "Exploring cognitive-behavioral drivers impacting consumer continuance intention of fitness apps using a hybrid approach of text mining, SEM, and ANN," Journal of Retailing and Consumer Services, Elsevier, vol. 81(C).
    5. David M. Goldberg & Nohel Zaman & Arin Brahma & Mariano Aloiso, 2022. "Are mortgage loan closing delay risks predictable? A predictive analysis using text mining on discussion threads," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 73(3), pages 419-437, March.
    6. Park, Sanghyun & Lee, Sungjoo, 2025. "Comparing information completeness in brand-related user-generated content media," Technological Forecasting and Social Change, Elsevier, vol. 214(C).
    7. Frantisek Darena & Jonas Petrovsky & Jan Zizka & Jan Prichystal, 2016. "Analyzing the correlation between online texts and stock price movements at micro-level using machine learning," MENDELU Working Papers in Business and Economics 2016-67, Mendel University in Brno, Faculty of Business and Economics.
    8. Xu, Xun & Lee, Chieh, 2020. "Utilizing the platform economy effect through EWOM: Does the platform matter?," International Journal of Production Economics, Elsevier, vol. 227(C).
    9. Sarraf, Shagun & Kushwaha, Amit Kumar & Kar, Arpan Kumar & Dwivedi, Yogesh K. & Giannakis, Mihalis, 2024. "How did online misinformation impact stockouts in the e-commerce supply chain during COVID-19 – A mixed methods study," International Journal of Production Economics, Elsevier, vol. 267(C).
    10. Nilashi, Mehrbakhsh & Abumalloh, Rabab Ali & Samad, Sarminah & Alrizq, Mesfer & Alyami, Sultan & Alghamdi, Abdullah, 2023. "Analysis of customers' satisfaction with baby products: The moderating role of brand image," Journal of Retailing and Consumer Services, Elsevier, vol. 73(C).
    11. Juan Feng & Xin Li & Xiaoquan (Michael) Zhang, 2019. "Online Product Reviews-Triggered Dynamic Pricing: Theory and Evidence," Information Systems Research, INFORMS, vol. 30(4), pages 1107-1123, December.
    12. Pooja Katyal & Reetika Sehgal, 2025. "Unraveling the impact of online consumer reviews on consumer buying behavior," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 16(1), pages 330-345, January.
    13. Christopher Gerling & Stefan Lessmann, 2024. "Leveraging AI and NLP for Bank Marketing: A Systematic Review and Gap Analysis," Papers 2411.14463, arXiv.org.
    14. Nohel Zaman & David M. Goldberg & Richard J. Gruss & Alan S. Abrahams & Siriporn Srisawas & Peter Ractham & Michelle M.H. Şeref, 2022. "Cross-Category Defect Discovery from Online Reviews: Supplementing Sentiment with Category-Specific Semantics," Information Systems Frontiers, Springer, vol. 24(4), pages 1265-1285, August.
    15. Xue, Zhebin & Li, Qing & Zeng, Xianyi, 2023. "Social media user behavior analysis applied to the fashion and apparel industry in the big data era," Journal of Retailing and Consumer Services, Elsevier, vol. 72(C).
    16. Kick, Markus, 2015. "Social Media Research: A Narrative Review," EconStor Preprints 182506, ZBW - Leibniz Information Centre for Economics.
    17. Sanaz Ghorbanloo & Sajjad Shokouhyar, 2023. "Consumers' attitude footprint on sustainable development in developed and developing countries: a case study in the electronic industry," Operations Management Research, Springer, vol. 16(3), pages 1444-1475, September.
    18. Kim, Su-Ah & Park, Sohyun & Kwak, Minjung & Kang, Changmuk, 2025. "Examining product quality and competitiveness via online reviews: An integrated approach of importance performance competitor analysis and Kano model," Journal of Retailing and Consumer Services, Elsevier, vol. 82(C).
    19. Yi Peng, 2015. "Regional earthquake vulnerability assessment using a combination of MCDM methods," Annals of Operations Research, Springer, vol. 234(1), pages 95-110, November.
    20. Denys Yemshanov & Frank H. Koch & Yakov Ben‐Haim & Marla Downing & Frank Sapio & Marty Siltanen, 2013. "A New Multicriteria Risk Mapping Approach Based on a Multiattribute Frontier Concept," Risk Analysis, John Wiley & Sons, vol. 33(9), pages 1694-1709, September.

    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:joreco:v:82:y:2025:i:c:s0969698924003552. 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: https://www.journals.elsevier.com/journal-of-retailing-and-consumer-services .

    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.