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A Study on Strategic Behavior of Drivers on Ride-hailing Platforms

Tavassoli, Parto | 2021

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 54442 (44)
  4. University: Sharif University of Technology
  5. Department: Management and Economics
  6. Advisor(s): Aslani, Shirin
  7. Abstract:
  8. Recently, the advent of online platforms as an intermediary tool has provided an opportunity for service providers and manufacturers to offer their services/products to consumers. Ride-hailing platforms are an example of these businesses where independent drivers and passengers are matched via an online platform. One of the most significant challenges faced by these companies is the emergence of strategic behaviors on both the demand and the supply side, which might affect the performance and profitability of the platform.In this thesis, we study the strategic behavior of drivers and its impact on their performance, using the data of one of the largest ride-hailing companies in Iran. We use the data of one of the major cities of Iran, from September 10 to October 31, 2019, containing 5,800,000 requests, 2,170,000 fulfilled trips, and 2295 full-time local drivers.Inspired by the literature, we define two strategic behaviors in this research. The results show that about 5.1% of drivers show both behaviors. Using the statistical analysis, we show that there is no significant difference between the earning per hour of strategic and non-strategic drivers, inferring that strategic behavior does not improve driver's income on average. Interestingly, none of the strategic drivers have joined the platform in the recent 30 days of the specified time interval, which means inexperienced drivers rarely exhibit strategic behaviors. According to the results, the earning per kilometer of strategic drivers is, on average, higher than that of non-strategic drivers meaning that although strategic drivers do not increase the platform's revenue, they themselves benefit by earning higher profits.Furthermore, we show that none of the top 5% drivers with the highest earning/hour are strategic. We use logistic regression to model the acceptance/rejection behavior of drivers for three categories of strategic, high-earning, and other drivers. These models enable us to compare the decision making process of these three types of drivers, and to determine what factors cause higher earnings. We show that high-earning drivers take longer and higher-priced rides on average compared to strategic drivers. On the other hand, strategic drivers consider higher earning per kilometer, higher ride speed (i.e., less traffic on the route), and shorter ride durations when deciding whether to accept a request or not and rides with two destinations are more likely to be accepted by these drivers. The managerial insights derived from these results can be a guide for setting the platform’s strategies
  9. Keywords:
  10. Two-sided Market ; Strategic Behavior ; Drivers Behavior ; Surge Pricing ; Ride Sharing Platforms ; Ride-Hailing Platforms

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