Taxi driver's learning curves: An empirical analysis

Research output: Contribution to journalArticlepeer-review


This study aims to understand the dynamic change in individual taxi drivers’ performance in terms of income and passenger-search performance. We analyzed the global positioning system (GPS) data of 14,170 taxi drivers from a taxi company in Singapore, covering a period of 24 months. Our empirical analyses show that (1) accumulated driving experience increases income and that (2) as taxi drivers accumulate driving experience, they are likely to find new passengers more efficiently by spotting better search areas. We also conducted a field study to extend our understanding of and identify other factors that were not considered in our estimation but could play pivotal roles in performance enhancement, including improved passenger-search routine. The implications of our findings for both theory and practice are discussed.

Original languageEnglish
Pages (from-to)1-13
Number of pages13
JournalTransportation Research Part A: Policy and Practice
StatePublished - Dec 2022


  • Knowledge Management
  • Learning Curves
  • Passenger-Search Routine
  • Productivity Dynamics
  • Taxi


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