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.

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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
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article

Consumer sentiments in automotive purchases before and after COVID-19: a text-mining study

Shih Yung Chou, Jiaxi Luo, Ashok Bhattarai, Charles Ramser
International Journal of Business Environment
Sentiment Analysis and Opinion Mining
article

Consumer sentiments in automotive purchases before and after COVID-19: a text-mining study

Shih Yung Chou, Jiaxi Luo, Ashok Bhattarai, Charles Ramser
article en

Abstract

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.

International Journal of Business EnvironmentVol. 16(1)
Openalex Percentile: Top 80%
Sentiment Analysis and Opinion Mining
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