Consumer sentiments in automotive purchases before and after COVID-19: a text-mining study
The COVID-19 pandemic has led to shortages in the automotive industry due to a limited supply of semiconductor chips, which has created a nonlinear dynamic and chaotic business environment in the industry.This leads to the following important yet unanswered questions: 1) Is there a divergence in consumer emphases placed on the car buying process prior to and after COVID-19?; 2) How do consumer sentiment patterns affect their ratings of car dealerships prior to and after COVID-19?To answer these questions, we utilise a text-mining approach and perform an ordered probit regression analysis.Results illustrate the following.First, the sentiment keyword 'fast' had a positive impact on consumer online ratings after COVID-19, whereas 'clean' had a positive impact on consumer online ratings before COVID-19.Third, the sentiment keyword 'wait' had a negative impact on consumer online ratings after COVID-19.Fourth, the sentiment keyword 'willing' had a negative impact on consumer online ratings both before and after COVID-19.Finally, the sentiment keyword 'mess' had a negative impact on consumer online ratings both before and after COVID-19.
Authors
- Shih Yung Chou (ORCID: https://orcid.org/0000-0002-4404-0050)
- Jiaxi Luo (ORCID: https://orcid.org/0000-0001-9180-8694)
- Ashok Bhattarai (ORCID: https://orcid.org/0000-0001-5823-5388)
- Charles Ramser (ORCID: https://orcid.org/0000-0003-3479-1034)
Publication Details
- Journal
- International Journal of Business Environment
- Published
- 2024-12-04
- DOI
- https://doi.org/10.1504/ijbe.2025.143093
- Primary Topic
- Sentiment Analysis and Opinion Mining
- Type
- article
- Field-Weighted Citation Impact
- 0.00