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The analysis of ride hailing user characteristics from app reviews

Author

Listed:
  • Pahmi Amri
  • Dia Meirina Suri
  • Syuhada

Abstract

Purpose – This research measures the perceptions of ride-hailing (Gojek) users on the Playstore review page.Design/methodology/approach – This research uses qualitative analysis and a sentiment analysis approach. The primary data for this research comes from 5000 user reviews of the Gojek application on the Play Store application. Data collection was carried out with the help of the Ncapture tool in Chrome, which was then exported to the NVivo 12 Plus software in a PDF file. This research uses NVivo 12 Plus software to visualize coding data for several reviews from Google Playstore.Findings – The research results show that the perception of Gojek application users is dominated by negative criteria, nuances of disappointment with the driver's behaviour, and application errors that flood the reviews. The ratings given by users are dominated by the number one, which indicates the lowest point.Research limitations/implications – This research provides a theoretical contribution that the sentiment analysis approach is one of the instruments successful in revealing user perceptions of a service application. Practical implications – This research provides a practical contribution to the Gojek application company in that user reviews can influence customer intentions, so it is necessary to carry out routine improvements and serious in-depth evaluations by considering reviews from earlier users.Originality/value – This study fills the gap regarding online transportation user sentiment by utilizing big data from reviews on Google Playstore.

Suggested Citation

  • Pahmi Amri & Dia Meirina Suri & Syuhada, 2024. "The analysis of ride hailing user characteristics from app reviews," Jurnal Siasat Bisnis, Management Development Centre (MDC) Department of Management, Faculty of Business and Economics Universitas Islam Indonesia, vol. 28(2), pages 241-262.
    • Handle: RePEc:uii:jsbuii:v:28:y:2024:i:2:p:241-262:id:33103
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