Understanding Antecedents That Affect Customer Evaluations of Head-Mounted Display VR Devices through Text Mining and Deep Neural Network
Although the market for Head-Mounted Display Virtual Reality (HMD VR) devices has been growing along with the metaverse trend, the product has not been as widespread as initially expected. As each user has different purposes for use and prefers different features, various factors are expected to inf...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-07-01
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| Series: | Journal of Theoretical and Applied Electronic Commerce Research |
| Subjects: | |
| Online Access: | https://www.mdpi.com/0718-1876/18/3/63 |
| _version_ | 1797579203963518976 |
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| author | Yunho Maeng Choong C. Lee Haejung Yun |
| author_facet | Yunho Maeng Choong C. Lee Haejung Yun |
| author_sort | Yunho Maeng |
| collection | DOAJ |
| description | Although the market for Head-Mounted Display Virtual Reality (HMD VR) devices has been growing along with the metaverse trend, the product has not been as widespread as initially expected. As each user has different purposes for use and prefers different features, various factors are expected to influence customer evaluations. Therefore, the present study aims to: (1) analyze customer reviews of hands-on HMD VR devices, provided with new user experience (UX), using text mining, and artificial neural network techniques; (2) comprehensively examine variables that affect user evaluations of VR devices; and (3) suggest major implications for the future development of VR devices. The research procedure consisted of four steps. First, customer reviews on HMD VR devices were collected from Amazon.com. Second, candidate variables were selected based on a literature review, and sentiment scores were extracted. Third, variables were determined through topic modeling, in-depth interviews, and a review of previous studies. Fourth, an artificial neural network analysis was performed by setting customer evaluation as a dependent variable, and the influence of each variable was checked through feature importance. The results indicate that feature importance can be derived from variables, and actionable implications can be identified, unlike in general sentiment analysis. |
| first_indexed | 2024-03-10T22:33:37Z |
| format | Article |
| id | doaj.art-01d33cae5fb743569fa8eb7b49dcf90f |
| institution | Directory Open Access Journal |
| issn | 0718-1876 |
| language | English |
| last_indexed | 2024-03-10T22:33:37Z |
| publishDate | 2023-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Journal of Theoretical and Applied Electronic Commerce Research |
| spelling | doaj.art-01d33cae5fb743569fa8eb7b49dcf90f2023-11-19T11:32:08ZengMDPI AGJournal of Theoretical and Applied Electronic Commerce Research0718-18762023-07-011831238125610.3390/jtaer18030063Understanding Antecedents That Affect Customer Evaluations of Head-Mounted Display VR Devices through Text Mining and Deep Neural NetworkYunho Maeng0Choong C. Lee1Haejung Yun2Graduate School of Information, Yonsei University, Seoul 03722, Republic of KoreaGraduate School of Information, Yonsei University, Seoul 03722, Republic of KoreaDepartment of International Office Administration, College of Science & Industry Convergence, Ewha Womans University, Seoul 03722, Republic of KoreaAlthough the market for Head-Mounted Display Virtual Reality (HMD VR) devices has been growing along with the metaverse trend, the product has not been as widespread as initially expected. As each user has different purposes for use and prefers different features, various factors are expected to influence customer evaluations. Therefore, the present study aims to: (1) analyze customer reviews of hands-on HMD VR devices, provided with new user experience (UX), using text mining, and artificial neural network techniques; (2) comprehensively examine variables that affect user evaluations of VR devices; and (3) suggest major implications for the future development of VR devices. The research procedure consisted of four steps. First, customer reviews on HMD VR devices were collected from Amazon.com. Second, candidate variables were selected based on a literature review, and sentiment scores were extracted. Third, variables were determined through topic modeling, in-depth interviews, and a review of previous studies. Fourth, an artificial neural network analysis was performed by setting customer evaluation as a dependent variable, and the influence of each variable was checked through feature importance. The results indicate that feature importance can be derived from variables, and actionable implications can be identified, unlike in general sentiment analysis.https://www.mdpi.com/0718-1876/18/3/63e-commerceconsumer behaviorbig datacustomer reviewHMD VRneural network |
| spellingShingle | Yunho Maeng Choong C. Lee Haejung Yun Understanding Antecedents That Affect Customer Evaluations of Head-Mounted Display VR Devices through Text Mining and Deep Neural Network Journal of Theoretical and Applied Electronic Commerce Research e-commerce consumer behavior big data customer review HMD VR neural network |
| title | Understanding Antecedents That Affect Customer Evaluations of Head-Mounted Display VR Devices through Text Mining and Deep Neural Network |
| title_full | Understanding Antecedents That Affect Customer Evaluations of Head-Mounted Display VR Devices through Text Mining and Deep Neural Network |
| title_fullStr | Understanding Antecedents That Affect Customer Evaluations of Head-Mounted Display VR Devices through Text Mining and Deep Neural Network |
| title_full_unstemmed | Understanding Antecedents That Affect Customer Evaluations of Head-Mounted Display VR Devices through Text Mining and Deep Neural Network |
| title_short | Understanding Antecedents That Affect Customer Evaluations of Head-Mounted Display VR Devices through Text Mining and Deep Neural Network |
| title_sort | understanding antecedents that affect customer evaluations of head mounted display vr devices through text mining and deep neural network |
| topic | e-commerce consumer behavior big data customer review HMD VR neural network |
| url | https://www.mdpi.com/0718-1876/18/3/63 |
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