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AuthorAmit, Singh
AuthorJenamani, Mamata
AuthorThakkar, Jitesh J.
AuthorRana, Nripendra P.
Available date2023-06-08T07:25:28Z
Publication Date2021-09-10
Publication NameJournal of Business Research
Identifierhttp://dx.doi.org/10.1016/j.jbusres.2021.08.060
CitationSingh, A., Jenamani, M., Thakkar, J. J., & Rana, N. P. (2022). Quantifying the effect of eWOM embedded consumer perceptions on sales: An integrated aspect-level sentiment analysis and panel data modeling approach. Journal of Business Research, 138, 52-64.
ISSN0148-2963
URIhttps://www.sciencedirect.com/science/article/pii/S0148296321006275
URIhttp://hdl.handle.net/10576/44081
AbstractThis paper proposes a text-analytics framework that integrates aspect-level sentiment analysis (ASLSA) with bias-corrected least square dummy variable (LSDVc) – a panel data regression method – to empirically examine the influence of review-embedded information on product sales. We characterize the online perceptions as consumer opinions or sentiments corresponding to the product features discussed within the review. While ASLSA discovers key product features and quantifies the opinions in corresponding content, the LSDVc-based panel data regression analyses the consumer sentiments to explore their influence on product sales. The proposed framework is tested on the mid-sized car segment in India. Our findings suggest that review volume and the sentiments corresponding to the exterior and appearance significantly influence the mid-size car sales in India.
Languageen
PublisherElsevier
SubjectOnline reviews
Aspect-level sentiment analysis
Panel data analysis
Bias-corrected least square dummy variable
Sales prediction
Automobile industry
TitleQuantifying the effect of eWOM embedded consumer perceptions on sales: An integrated aspect-level sentiment analysis and panel data modeling approach
TypeArticle
Pagination52-64
Volume Number138
ESSN1873-7978
dc.accessType Abstract Only


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