Is negative e-WOM more powerful? Multimodal data analysis on air passengers’ perception of COVID-19 safety measures
During the normalization stage of the COVID-19 epidemic prevention and control, the safety threats caused by improper epidemic prevention measures of airlines have become the primary concern for air passengers. Negative e-WOM related to safety perception obtained based on online multimodal reviews o...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2022-10-01
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| Series: | Frontiers in Psychology |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/fpsyg.2022.983987/full |
| _version_ | 1798030315296391168 |
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| author | Shizhen Bai Dingyao Yu Mu Yang Rui Tang Hao He Jiayuan Zhao Peihua Huang |
| author_facet | Shizhen Bai Dingyao Yu Mu Yang Rui Tang Hao He Jiayuan Zhao Peihua Huang |
| author_sort | Shizhen Bai |
| collection | DOAJ |
| description | During the normalization stage of the COVID-19 epidemic prevention and control, the safety threats caused by improper epidemic prevention measures of airlines have become the primary concern for air passengers. Negative e-WOM related to safety perception obtained based on online multimodal reviews of travel websites has become an important decision-making basis for potential air passengers when making airline choices. This study aims to examine the relationship between potential air passengers’ negative safety perception and the usefulness of online reviews, as well as to test the moderating effect of review modality and airline type. It also further explores the effectiveness and feasibility of applying big data sentiment analysis to e-WOM management. To this end, the theoretical model of negative safety perception, review modality, and airline type affecting review usefulness was constructed. Then we select 10 low-cost airlines and 10 full-service airlines, respectively, according to the number of reviews sorted by the TripAdvisor website, and use crawling techniques to obtain 10,485 reviews related to COVID-19 safety of the above companies from December 2019 to date, and conduct safety perception sentiment analysis based on Python’s Textblob library. Finally, to avoid data overdispersion, the model is empirically analyzed by negative binomial regression using R software. The results indicate that (1) Negative safety perception significantly and negatively affects review usefulness, that is, extreme negative safety perception can provide higher review usefulness for potential air passengers. (2) Review modality and airline type have a significant moderating effect on the relationship between negative safety perception and review usefulness, in which multimodal reviews and full-service airlines both weakened the negative impact of negative safety perception on review usefulness. The theoretical model in this paper is both an extension of the application of big data sentiment analysis techniques and a beneficial supplement to current research findings of e-WOM, providing an important reference for potential air passengers to identify useful reviews accurately and thus reduce safety risks in online decision-making. |
| first_indexed | 2024-04-11T19:38:20Z |
| format | Article |
| id | doaj.art-3ba5451f01a9499e94164ccb40e064f9 |
| institution | Directory Open Access Journal |
| issn | 1664-1078 |
| language | English |
| last_indexed | 2024-04-11T19:38:20Z |
| publishDate | 2022-10-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Psychology |
| spelling | doaj.art-3ba5451f01a9499e94164ccb40e064f92022-12-22T04:06:46ZengFrontiers Media S.A.Frontiers in Psychology1664-10782022-10-011310.3389/fpsyg.2022.983987983987Is negative e-WOM more powerful? Multimodal data analysis on air passengers’ perception of COVID-19 safety measuresShizhen Bai0Dingyao Yu1Mu Yang2Rui Tang3Hao He4Jiayuan Zhao5Peihua Huang6School of Management, Harbin University of Commerce, Harbin, ChinaSchool of Management, Harbin University of Commerce, Harbin, ChinaDepartment of Management, Birkbeck, University of London, London, United KingdomSchool of Economics Teaching and Research, Party School of the Central Committee of C.P.C (Chinese Academy of Governance), Beijing, ChinaSchool of Management, Harbin University of Commerce, Harbin, ChinaSchool of Computer and Information Engineering, Harbin University of Commerce, Harbin, ChinaSchool of Management, Harbin University of Commerce, Harbin, ChinaDuring the normalization stage of the COVID-19 epidemic prevention and control, the safety threats caused by improper epidemic prevention measures of airlines have become the primary concern for air passengers. Negative e-WOM related to safety perception obtained based on online multimodal reviews of travel websites has become an important decision-making basis for potential air passengers when making airline choices. This study aims to examine the relationship between potential air passengers’ negative safety perception and the usefulness of online reviews, as well as to test the moderating effect of review modality and airline type. It also further explores the effectiveness and feasibility of applying big data sentiment analysis to e-WOM management. To this end, the theoretical model of negative safety perception, review modality, and airline type affecting review usefulness was constructed. Then we select 10 low-cost airlines and 10 full-service airlines, respectively, according to the number of reviews sorted by the TripAdvisor website, and use crawling techniques to obtain 10,485 reviews related to COVID-19 safety of the above companies from December 2019 to date, and conduct safety perception sentiment analysis based on Python’s Textblob library. Finally, to avoid data overdispersion, the model is empirically analyzed by negative binomial regression using R software. The results indicate that (1) Negative safety perception significantly and negatively affects review usefulness, that is, extreme negative safety perception can provide higher review usefulness for potential air passengers. (2) Review modality and airline type have a significant moderating effect on the relationship between negative safety perception and review usefulness, in which multimodal reviews and full-service airlines both weakened the negative impact of negative safety perception on review usefulness. The theoretical model in this paper is both an extension of the application of big data sentiment analysis techniques and a beneficial supplement to current research findings of e-WOM, providing an important reference for potential air passengers to identify useful reviews accurately and thus reduce safety risks in online decision-making.https://www.frontiersin.org/articles/10.3389/fpsyg.2022.983987/fulle-WOMnegative safety perceptionCOVID-19 safety measuresmultimodal reviewssentiment analysisreview usefulness |
| spellingShingle | Shizhen Bai Dingyao Yu Mu Yang Rui Tang Hao He Jiayuan Zhao Peihua Huang Is negative e-WOM more powerful? Multimodal data analysis on air passengers’ perception of COVID-19 safety measures Frontiers in Psychology e-WOM negative safety perception COVID-19 safety measures multimodal reviews sentiment analysis review usefulness |
| title | Is negative e-WOM more powerful? Multimodal data analysis on air passengers’ perception of COVID-19 safety measures |
| title_full | Is negative e-WOM more powerful? Multimodal data analysis on air passengers’ perception of COVID-19 safety measures |
| title_fullStr | Is negative e-WOM more powerful? Multimodal data analysis on air passengers’ perception of COVID-19 safety measures |
| title_full_unstemmed | Is negative e-WOM more powerful? Multimodal data analysis on air passengers’ perception of COVID-19 safety measures |
| title_short | Is negative e-WOM more powerful? Multimodal data analysis on air passengers’ perception of COVID-19 safety measures |
| title_sort | is negative e wom more powerful multimodal data analysis on air passengers perception of covid 19 safety measures |
| topic | e-WOM negative safety perception COVID-19 safety measures multimodal reviews sentiment analysis review usefulness |
| url | https://www.frontiersin.org/articles/10.3389/fpsyg.2022.983987/full |
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