Text mining approach to explore determinants of grocery mobile app satisfaction using online customer reviews |
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| Institution: | 1. Area of Marketing, Indian Institute of Management, Ranchi, Jharkhand, Pin-834008, India;2. Area of Information Systems and Business Analytics, Indian Institute of Management, Ranchi, Jharkhand, Pin-834008, India;1. School of Management, Shandong University, Jinan, 250100, China;2. School of Business, Qingdao University of Technology, Tsingtao, 266071, China;1. Department of Management, Korea National Open University, 86 Daehak-ro, Jongno-gu, Seoul, 03087, South Korea;2. College of Business Administration, Seoul National University, 1 Gwanak-ro, Gwanak-gu, Seoul, 08826, South Korea;1. Department of Marketing, School of Business Administration, Hunan University, Changsha, 410000, China;2. Hunan Key Laboratory of Macroeconomic Big Data Mining and its Application, School of Business, Hunan Normal University, Changsha, 410000, China;3. Department of Management, School of Business Administration, Huaqiao University, Quanzhou, 362000, China;1. College of Arts & Physical Education, Gachon University, 1342 Seongnamdaero, Seongnam-si, South Korea;2. Department of Clothing & Textiles, Chungnam National University, South Korea, 99 Daehak-ro, Yuseong-gu, Daejeon, South Korea;3. College of Business and Management, VinUniversity, Vinhomes Ocean Park, Gia Lam District, Hanoi, Viet Nam |
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| 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. |
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| Keywords: | Topic modelling Online customer reviews Text mining Customer satisfaction Grocery mobile apps |
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