Measuring sentiments and attitude of people toward self-drive rental car services in Bangalore City, India

This paper explores the emotions of self-drive rental car users in India on social-media platform using sentiment analysis and estimates the relationship between socio-demographic factors and factors influencing the decision of renting a car. An ordered logit model is used to determine the factors which are affecting individuals’ demographic characteristics to rent from a self-drive rental car service. A total of six models are computed for each of the influencing factors. The results suggest that there is a positive image of self-drive rental car service as perceived from social media platform and in the 18-25 years age group. Private employees are significantly affected by quality of car and ease to hire facility offered by this service. It is also estimated that time flexibility is the most influencing factor considered while renting a car. The outcomes of this study may aid these service providers in strategic planning and policy framework.

• Record URL:
  https://doi.org/10.1080/19427867.2021.1914966
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/19427867
• Supplemental Notes:
  • © 2021 Informa UK Limited, trading as Taylor & Francis Group. Abstract reprinted with permission of Taylor & Francis.
• Authors:
  • Verma, Meghna
  • Verma, Ashish
  • Narsaria, Isha
• Publication Date: 2022-7

Language

• English

Media Info

• Media Type: Web
• Features: References;
• Pagination: pp 622-628
• Serial:
  • Transportation Letters: The International Journal of Transportation Research
  • Volume: 14
  • Issue Number: 6
  • Publisher: Taylor & Francis
  • ISSN: 1942-7867
  • EISSN: 1942-7875
  • Serial URL: http://www.tandfonline.com/toc/ytrl20/current

Subject/Index Terms

• TRT Terms: Attitudes; Consumer behavior; Decision making; Demographics; Rental cars
• Geographic Terms: Bangalore (India)
• Subject Areas: Economics; Highways; Passenger Transportation; Planning and Forecasting;

Filing Info

• Accession Number: 01853780
• Record Type: Publication
• Files: TRIS
• Created Date: Aug 1 2022 5:20PM