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Stream/Area:
-
Subject:
-
Paper ID:
10.55041/IJSREM31138
Volume:
8 |
4 |
Apr 2024
Pages:
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
The Unravelling Transportation Trends with Data Engineering and Analytics project delves into the correlation between driver behavior and customer ratings within ride-hailing platforms. Utilizing a dataset akin to Uber’s, the study investigates the impact of acceptance rates and cancellation rates on customer satisfaction, aiming to glean valuable business insights for enhancing service quality and fostering business growth. Meticulous data collection and preprocessing ensure data accuracy and reliability, while secure cloud-based storage facilitates efficient data processing. By analyzing driver behavior metrics and customer ratings, the project uncovers pivotal patterns and trends, offering essential guidance for optimizing driver performance. This data-driven approach empowers ride-hailing services to implement targeted strategies for improving service quality, enhancing customer retention, and cultivating a loyal customer base.
KEYWORDS
Publication Date
12/31/45401
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
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