Please use this identifier to cite or link to this item: http://idr.iimranchi.ac.in:8080/xmlui/handle/123456789/1689
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dc.contributor.authorKumar, Avinash.-
dc.contributor.authorChakraborty, Shibashish.-
dc.contributor.authorBala, Pradip Kumar.-
dc.date.accessioned2023-07-25T23:30:41Z-
dc.date.available2023-07-25T23:30:41Z-
dc.date.issued2023-07-
dc.identifier.citationAvinash Kumar, Shibashish Chakraborty, and Pradip Kumar Bala (2023). Text mining approach to explore determinants of grocery mobile app satisfaction using online customer reviews. Journal of Retailing and Consumer Services, 73(July), 103363. https://doi.org/10.1016/j.jretconser.2023.103363en_US
dc.identifier.issn1873-1384-
dc.identifier.urihttps://doi.org/10.1016/j.jretconser.2023.103363-
dc.identifier.urihttp://idr.iimranchi.ac.in:8080/xmlui/handle/123456789/1689-
dc.description.abstractIn 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.en_US
dc.language.isoenen_US
dc.publisherJournal of Retailing and Consumer Servicesen_US
dc.subjectTopic modellingen_US
dc.subjectOnline customer reviewsen_US
dc.subjectText miningen_US
dc.subjectCustomer satisfactionen_US
dc.subjectGrocery mobile appsen_US
dc.subjectIIM Ranchien_US
dc.titleText mining approach to explore determinants of grocery mobile app satisfaction using online customer reviewsen_US
dc.typeArticleen_US
dc.volume73en_US
dc.issueJulyen_US
Appears in Collections:Journal Articles

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