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Analyzing Location-Based Advertising for Vehicle Service Providers Using Effective Resistances

Published:20 June 2019Publication History

ABSTRACT

Vehicle service providers can display commercial ads in their vehicles based on passengers' origins and destinations to create a new revenue stream. We study a vehicle service provider who can generate different ad revenues when displaying ads on different arcs (i.e., origin-destination pairs). The provider needs to ensure the vehicle flow balance at each location, which makes it challenging to analyze the provider's vehicle assignment and pricing decisions for different arcs. To tackle the problem, we show that certain properties of the traffic network can be captured by a corresponding electrical network. When the effective resistance between two locations is small, there are many paths between the two locations and the provider can easily route vehicles between them. We derive the provider's optimal vehicle assignment and pricing decisions based on effective resistances.

References

  1. Kostas Bimpikis, Ozan Candogan, and Daniela Saban. 2018. Spatial pricing in ride-sharing networks. Operations Research (2018).Google ScholarGoogle Scholar
  2. Arpita Ghosh, Mohammad Mahdian, R Preston McAfee, and Sergei Vassilvitskii. 2015. To match or not to match: Economics of cookie matching in online advertising. ACM Transactions on Economics and Computation, Vol. 3, 2 (2015). Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. Hongyao Ma, Fei Fang, and David C Parkes. 2018. Spatio-temporal pricing for ridesharing platforms. arXiv:1801.04015 (2018).Google ScholarGoogle Scholar
  4. Haoran Yu, Ermin Wei, and Randall A Berry. 2019a. Analyzing location-based advertising for vehicle service providers using effective resistances. Proceedings of the ACM on Measurement and Analysis of Computing Systems, Vol. 3, 1 (2019).Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. Haoran Yu, Ermin Wei, and Randall A Berry. 2019 b. A business model analysis of mobile data rewards. In Proc. of IEEE INFOCOM . Paris, France.Google ScholarGoogle ScholarCross RefCross Ref

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            cover image ACM Conferences
            SIGMETRICS '19: Abstracts of the 2019 SIGMETRICS/Performance Joint International Conference on Measurement and Modeling of Computer Systems
            June 2019
            113 pages
            ISBN:9781450366786
            DOI:10.1145/3309697

            Copyright © 2019 Owner/Author

            Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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            Association for Computing Machinery

            New York, NY, United States

            Publication History

            • Published: 20 June 2019

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            • extended-abstract

            Acceptance Rates

            SIGMETRICS '19 Paper Acceptance Rate50of317submissions,16%Overall Acceptance Rate459of2,691submissions,17%

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