Wisdom of crowds: Conducting importance-performance analysis (IPA) through online reviews |
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| Institution: | 1. Department of Information Management and Decision Sciences, School of Business Administration, Northeastern University, Shenyang, 110169, China;2. State Key Laboratory of Synthetical Automation for Process Industries, Northeastern University, Shenyang, 110819, China;1. Department of Tourism and Hotel Management, School of Management, Zhejiang University, Hangzhou, Zhejiang, 310058, PR China;2. School of Management and Marketing, Waikato Management School, The University of Waikato, Hamilton, New Zealand;1. Henley Business School, University of Reading, Greenlands, Henley on Thames, Oxfordshire, RG9 3AU, United Kingdom;2. Annenberg School for Communication and Journalism, University of Southern California, 3502 Watt Way, Los Angeles, CA, 90089, USA;1. Hohai University, Nanjing City, Jiang Su Province 21110, China;2. School of Management and Business, King''s College London, Franklin-Wilkins Building, 150 Stamford Street, London SE1 9NH, United Kingdom;1. Department of Decision Sciences, College of Business, San Francisco State University, 1600 Holloway Avenue, San Francisco, CA, 94132, United States;2. Department of Management, Operations, and Marketing, College of Business Administration, California State University, Stanislaus, One University Circle, Turlock, CA, 95382, United States;3. Department of Geography, University of Georgia, 210 Field St, Athens, GA, 30602, United States |
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| Abstract: | This paper proposes a methodology for conducting importance-performance analysis (IPA) through online reviews. The methodology is composed of three stages: (1) mining useful information from online reviews, (2) estimating each attribute's performance and importance, and (3) constructing IPA plot, where the latent dirichlet allocation (LDA), the improved one-vs-one strategy based support vector machine (IOVO-SVM) and the ensemble neural network based model (ENNM) are respectively used. A case study on two five-star hotels is given, and the results obtained by the proposed methodology through online reviews are compared with those obtained by the existing methods through questionnaires (or online ratings). The results indicate that the proposed methodology can obtain effective analysis results with lower cost and shorter time since online reviews are publicly available and easily collected. The proposed methodology can give managers or market analysts one more choice for conducting IPA or serve as a preparing process of large-scale survey. |
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| Keywords: | Importance-performance analysis (IPA) Online reviews Latent dirichlet allocation (LDA) Support vector machine (SVM) Ensemble neural network (ENN) |
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