Fine-grained Dynamic Price Prediction in Ride-on-demand Services: Models and Evaluations

Guo, Suiming; Chen, Chao; Wang, Jingyuan; Liu, Yaxiao; Xu, Ke; Chiu, Dah Ming

doi:10.1007/s11036-019-01308-5

Cited by 4 publications

(2 citation statements)

References 35 publications

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“…As the DP algorithms have not been made public by ride-sharing platforms, it is impossible for third parties to predict future prices and demand patterns, and to be sure that ride-sharing platforms are not manipulating prices [21,24]. The opaque algorithm also causes customers to be confused and annoyed with nontransparent pricing methods and might even prevent them from making quick decisions to request a ride [22,23,25]. To prevent such situations, some countries/ cities have implemented regulations to limit price increases caused by DP, and even set a limit on how much ride-sharing platforms can charge the customer [22].…”

Section: Dynamic Pricing In the Taxi Industrymentioning

confidence: 99%

“…Our findings corroborate this, as we found that traditional taxi industry values such as price transparency (C8) and considerations of what customers and drivers value (C9-C10) are constraints to adoption of DP. As DP is not transparent [23,25], it clashes with the ideal of price transparency.…”

Section: Summary Of Findingsa Model Of Nonadoption Of Technology For ...mentioning

confidence: 99%

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Non-Adoption of Dynamic Pricing in Traditional Taxi Dispatch Organizations

Tervo¹,

Väyrynen²

2022

Proceedings of the Annual Hawaii International Conference on System Sciences

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Dynamic pricing (DP) was introduced into the taxi industry through ride-sharing platforms such as Uber. Prior research has identified benefits of DP for ridesharing organizations, drivers and consumers. A legal reform in Finland in July 2018 made DP of taxi rides legally possible. However, even though traditional Finnish dispatch organizations have adopted different technology (e.g., ride-hailing apps), they have not adopted DP. To find out the reasons for the non-adoption, we conducted a qualitative case study among Finnish dispatch organizations. Utilizing IT artifact as an analytical lens, we identified ten aspects related to the technology, the structure and the context within which DP is embedded that help explain why it has not been adopted. We propose that DP in the taxi industry should be seen more broadly than just as "Uber-type" realtime DP, as it has been viewed in previous literature. Our findings have implications for research and practice.

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