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Text mining approach to explore determinants of grocery mobile app satisfaction using online customer reviews

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  • Kumar, Avinash
  • Chakraborty, Shibashish
  • Bala, Pradip Kumar

Abstract

In recent years, there has been proliferation of grocery mobile apps as grocery shopping on mobile has found increasing acceptance among customers accelerated by multiple factors. Maintaining high level of customer satisfaction is important for grocery mobile apps in the highly competitive app market. Online reviews have been a rich source of information to analyze customer satisfaction with a product or service. This paper explores the determinants of customer satisfaction for grocery mobile apps using online reviews. Latent Dirichlet Analysis (LDA), which is a text mining technique, is used to analyze online customer reviews of 27,337 customers to identify determinants of customer satisfaction. The determinants identified were further analyzed using a series of analysis to understand the importance of each determinant. Dominance analysis examined the relative importance of the determinants of customer satisfaction based on the overall rating. Correspondence analysis identified determinants which cause satisfaction separately from the determinants which cause dissatisfaction. The results from this study will provide insights to business managers of grocery mobile apps for decision-making on customer satisfaction management.

Suggested Citation

  • Kumar, Avinash & Chakraborty, Shibashish & Bala, Pradip Kumar, 2023. "Text mining approach to explore determinants of grocery mobile app satisfaction using online customer reviews," Journal of Retailing and Consumer Services, Elsevier, vol. 73(C).
    • Handle: RePEc:eee:joreco:v:73:y:2023:i:c:s0969698923001108
    DOI: 10.1016/j.jretconser.2023.103363
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    1. Peter J. Danaher & Isaac W. Wilson & Robert A. Davis, 2003. "A Comparison of Online and Offline Consumer Brand Loyalty," Marketing Science, INFORMS, vol. 22(4), pages 461-476, February.
    2. Alberto Cavallo, 2017. "Are Online and Offline Prices Similar? Evidence from Large Multi-channel Retailers," American Economic Review, American Economic Association, vol. 107(1), pages 283-303, January.
    3. Driediger, Fabian & Bhatiasevi, Veera, 2019. "Online grocery shopping in Thailand: Consumer acceptance and usage behavior," Journal of Retailing and Consumer Services, Elsevier, vol. 48(C), pages 224-237.
    4. Wei, Pengfei & Lu, Zhenzhou & Song, Jingwen, 2015. "Variable importance analysis: A comprehensive review," Reliability Engineering and System Safety, Elsevier, vol. 142(C), pages 399-432.
    5. Verkijika, Silas Formunyuy & Neneh, Brownhilder Ngek, 2021. "Standing up for or against: A text-mining study on the recommendation of mobile payment apps," Journal of Retailing and Consumer Services, Elsevier, vol. 63(C).
    6. Anubhav Mishra & S M Satish, 2016. "eWOM: Extant Research Review and Future Research Avenues," Vikalpa: The Journal for Decision Makers, , vol. 41(3), pages 222-233, September.
    7. Ajzen, Icek, 1991. "The theory of planned behavior," Organizational Behavior and Human Decision Processes, Elsevier, vol. 50(2), pages 179-211, December.
    8. Wu, Jia-Jhou & Chang, Sue-Ting, 2020. "Exploring customer sentiment regarding online retail services: A topic-based approach," Journal of Retailing and Consumer Services, Elsevier, vol. 55(C).
    9. Agnieszka Zablocki & Bodo Schlegelmilch & Michael J. Houston, 2019. "How valence, volume and variance of online reviews influence brand attitudes," AMS Review, Springer;Academy of Marketing Science, vol. 9(1), pages 61-77, June.
    10. Etumnu, Chinonso Ezenwa & Widmar, Nicole Olynk, 2020. "Grocery Shopping in the Digital Era," Choices: The Magazine of Food, Farm, and Resource Issues, Agricultural and Applied Economics Association, vol. 35(2), June.
    11. Wagner, Tillmann & Rudolph, Thomas, 2010. "Towards a hierarchical theory of shopping motivation," Journal of Retailing and Consumer Services, Elsevier, vol. 17(5), pages 415-429.
    12. Howard Hao-Chun Chuang & Rogelio Oliva & Sheng Liu, 2016. "On-Shelf Availability, Retail Performance, and External Audits: A Field Experiment," Production and Operations Management, Production and Operations Management Society, vol. 25(5), pages 935-951, May.
    13. Iyer, Pramod & Davari, Arezoo & Mukherjee, Amaradri, 2018. "Investigating the effectiveness of retailers’ mobile applications in determining customer satisfaction and repatronage intentions? A congruency perspective," Journal of Retailing and Consumer Services, Elsevier, vol. 44(C), pages 235-243.
    14. Guo, Yue & Barnes, Stuart J. & Jia, Qiong, 2017. "Mining meaning from online ratings and reviews: Tourist satisfaction analysis using latent dirichlet allocation," Tourism Management, Elsevier, vol. 59(C), pages 467-483.
    15. Esbjerg, Lars & Jensen, Birger Boutrup & Bech-Larsen, Tino & de Barcellos, Marcia Dutra & Boztug, Yasemin & Grunert, Klaus G., 2012. "An integrative conceptual framework for analyzing customer satisfaction with shopping trip experiences in grocery retailing," Journal of Retailing and Consumer Services, Elsevier, vol. 19(4), pages 445-456.
    16. 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).
    17. Nilashi, Mehrbakhsh & Abumalloh, Rabab Ali & Minaei-Bidgoli, Behrouz & Abdu Zogaan, Waleed & Alhargan, Ashwaq & Mohd, Saidatulakmal & Syed Azhar, Sharifah Nurlaili Farhana & Asadi, Shahla & Samad, Sar, 2022. "Revealing travellers’ satisfaction during COVID-19 outbreak: Moderating role of service quality," Journal of Retailing and Consumer Services, Elsevier, vol. 64(C).
    18. Yokoyama, Narimasa & Azuma, Nobukazu & Kim, Woonho, 2022. "Moderating effect of customer's retail format perception on customer satisfaction formation: An empirical study of mini-supermarkets in an urban retail market setting," Journal of Retailing and Consumer Services, Elsevier, vol. 66(C).
    19. Demoulin, Nathalie & Willems, Kim, 2019. "Servicescape irritants and customer satisfaction: The moderating role of shopping motives and involvement," Journal of Business Research, Elsevier, vol. 104(C), pages 295-306.
    20. Jiménez, Fernando R. & Mendoza, Norma A., 2013. "Too Popular to Ignore: The Influence of Online Reviews on Purchase Intentions of Search and Experience Products," Journal of Interactive Marketing, Elsevier, vol. 27(3), pages 226-235.
    21. Tran, Trang P. & Mai, Enping Shirley & Taylor, Erik C., 2021. "Enhancing brand equity of branded mobile apps via motivations: A service-dominant logic perspective," Journal of Business Research, Elsevier, vol. 125(C), pages 239-251.
    22. Molinillo, Sebastian & Aguilar-Illescas, Rocío & Anaya-Sánchez, Rafael & Carvajal-Trujillo, Elena, 2022. "The customer retail app experience: Implications for customer loyalty," Journal of Retailing and Consumer Services, Elsevier, vol. 65(C).
    23. Moro, Sérgio & Lopes, Rui J. & Esmerado, Joaquim & Botelho, Miguel, 2020. "Service quality in airport hotel chains through the lens of online reviewers," Journal of Retailing and Consumer Services, Elsevier, vol. 56(C).
    24. Uzir, Md. Uzir Hossain & Al Halbusi, Hussam & Thurasamy, Ramayah & Thiam Hock, Rodney Lim & Aljaberi, Musheer A. & Hasan, Najmul & Hamid, Mahmud, 2021. "The effects of service quality, perceived value and trust in home delivery service personnel on customer satisfaction: Evidence from a developing country," Journal of Retailing and Consumer Services, Elsevier, vol. 63(C).
    25. Ho, Xuan Huong & Nguyen, Dong Phong & Cheng, Julian Ming Sung & Le, Angelina Nhat Hanh, 2022. "Customer engagement in the context of retail mobile apps: A contingency model integrating spatial presence experience and its drivers," Journal of Retailing and Consumer Services, Elsevier, vol. 66(C).
    26. 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.
    27. Alnawas, Ibrahim & Aburub, Faisal, 2016. "The effect of benefits generated from interacting with branded mobile apps on consumer satisfaction and purchase intentions," Journal of Retailing and Consumer Services, Elsevier, vol. 31(C), pages 313-322.
    28. Lucini, Filipe R. & Tonetto, Leandro M. & Fogliatto, Flavio S. & Anzanello, Michel J., 2020. "Text mining approach to explore dimensions of airline customer satisfaction using online customer reviews," Journal of Air Transport Management, Elsevier, vol. 83(C).
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