{"title":"Spillover effects of online comments on high-involvement product sales: evidence from the Chinese automobile industry","authors":"Shutian Wang, Yan Lin, Lu Yan, Guoqing Zhu","doi":"10.1108/imds-01-2024-0015","DOIUrl":null,"url":null,"abstract":"PurposeOnline comments significantly impact consumer choice and product sales. Existing research focuses on the direct effects of online comments on product sales, whereas studies on the spillover effects of online comments are relatively limited, especially for high-involvement products. This study explores the impact of online comments of competing products on focal product sales in high-involvement products.Design/methodology/approachData mining techniques are used to collect 72,367 online comments from the Autohome platform, and sentiment analysis algorithms are used to quantify the textual information for subsequent analysis. Specifically, two panel two-way fixed-effects models are constructed to explore the impact of the average valence and quantity of online comments of competing cars on focal car sales, and analyse this impact in terms of heterogeneity across car price levels, while the moderating effect of online comments of competing cars is explored.FindingsThe results show that the average quantity of online comments of competing cars has a significant effect on the sales of the focal car in the overall sample, while the average valence of online comments of competing cars does not have a significant spillover effect. Moreover, the spillover effect varies by car price level. For high-priced cars, the average quantity of online comments of competing cars significantly and negatively affects focal car sales, and the average valence of online comments of competing cars significantly and negatively moderates the effect of the valence of focal car online comments on its sales. For lower-priced cars, online comments of competing cars don’t significantly affect focal car sales.Originality/valueThis study not only enriches the theory of online comments and high-involvement product sales, but also provides reference and guidance for exploring spillover effects of online comments for other products.","PeriodicalId":508405,"journal":{"name":"Industrial Management & Data Systems","volume":"31 16","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Industrial Management & Data Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1108/imds-01-2024-0015","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
PurposeOnline comments significantly impact consumer choice and product sales. Existing research focuses on the direct effects of online comments on product sales, whereas studies on the spillover effects of online comments are relatively limited, especially for high-involvement products. This study explores the impact of online comments of competing products on focal product sales in high-involvement products.Design/methodology/approachData mining techniques are used to collect 72,367 online comments from the Autohome platform, and sentiment analysis algorithms are used to quantify the textual information for subsequent analysis. Specifically, two panel two-way fixed-effects models are constructed to explore the impact of the average valence and quantity of online comments of competing cars on focal car sales, and analyse this impact in terms of heterogeneity across car price levels, while the moderating effect of online comments of competing cars is explored.FindingsThe results show that the average quantity of online comments of competing cars has a significant effect on the sales of the focal car in the overall sample, while the average valence of online comments of competing cars does not have a significant spillover effect. Moreover, the spillover effect varies by car price level. For high-priced cars, the average quantity of online comments of competing cars significantly and negatively affects focal car sales, and the average valence of online comments of competing cars significantly and negatively moderates the effect of the valence of focal car online comments on its sales. For lower-priced cars, online comments of competing cars don’t significantly affect focal car sales.Originality/valueThis study not only enriches the theory of online comments and high-involvement product sales, but also provides reference and guidance for exploring spillover effects of online comments for other products.
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