Modelling and Optimization for the Employment of Full-Time and Part-Time Drivers in Ride-Hailing Platforms

Chunhui Liu; Yangguang Lu

doi:doi:10.11648/j.ijefm.20210906.11

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Modelling and Optimization for the Employment of Full-Time and Part-Time Drivers in Ride-Hailing Platforms

Chunhui Liu, Yangguang Lu

Published in International Journal of Economics, Finance and Management Sciences (Volume 9, Issue 6)

Received: 18 October 2021 Accepted: 5 November 2021 Published: 12 November 2021

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Abstract

The employment strategy is of great significance to improve the performances of the ride-hailing platforms. This paper establishes a nonlinear programming model to characterize the employment problem of a ride-hailing platform where full-time drivers and part-time drivers coexist, facing a month-varied daily market size. The daily online time of the full-time drivers is assumed to be fixed, while the daily online time of the part-time drivers is self-scheduled. The objective of the decision model is to maximize the total effective demand of the ride-hailing platform, and the constraints are to guarantee the minimum income of both the full-time and part-time drivers. By solving the models, we find the decision problem can be simplified as a linear programming model and the optimal numbers of full-time drivers and part-time drivers are derived. Theoretical results show that it is optimal for the ride-hailing platform to employ only part-time drivers if the cap of number of part-time drivers is sufficiently high, and the number of part-time drivers satisfies that the expected income per unit time during the month with the minimum daily market size equals the required minimum income. Otherwise, if the cap of number of part-time drivers is not sufficiently high, full-time drivers and part-time drivers will coexist. Finally, a numerical experiment is conducted to illustrate the theoretical results.

Published in	International Journal of Economics, Finance and Management Sciences (Volume 9, Issue 6)
DOI	10.11648/j.ijefm.20210906.11
Page(s)	221-224
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2021. Published by Science Publishing Group

Keywords

Optimization, Employment, Ride-Hailing Platforms

References

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[5]	Zhong Y., Lin Z. Matching supply and demand on ride-sharing platforms with permanent agents and competition [J]. International Journal of Production Economics. 2019, 218: 363-374.
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[7]	Taylor T. A. On-Demand Service Platforms [J]. Manufacturing & Service Operations Management. 2018, 20 (4): 704-720.
[8]	Bai J., So K., Tang C. S., et al. Coordinating supply and demand on an on-demand service platform with impatient customers [J]. Manufacturing & Service Operations Management. 2019. 21 (3): 556-570.
[9]	Chen M. K., Chevalier J. A., Rossi P. E., et al. The Value of Flexible work: Evidence from Uber drivers [J]. National Bureau of Economic Research. 2017.
[10]	Farber H. S. Is tomorrow another day? The labor supply of New York city cabdrivers [J]. Journal of political Economy. 2005, 113 (1): 46–82.
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APA Style

Chunhui Liu, Yangguang Lu. (2021). Modelling and Optimization for the Employment of Full-Time and Part-Time Drivers in Ride-Hailing Platforms. International Journal of Economics, Finance and Management Sciences, 9(6), 221-224. https://doi.org/10.11648/j.ijefm.20210906.11

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ACS Style

Chunhui Liu; Yangguang Lu. Modelling and Optimization for the Employment of Full-Time and Part-Time Drivers in Ride-Hailing Platforms. Int. J. Econ. Finance Manag. Sci. 2021, 9(6), 221-224. doi: 10.11648/j.ijefm.20210906.11

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AMA Style

Chunhui Liu, Yangguang Lu. Modelling and Optimization for the Employment of Full-Time and Part-Time Drivers in Ride-Hailing Platforms. Int J Econ Finance Manag Sci. 2021;9(6):221-224. doi: 10.11648/j.ijefm.20210906.11

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@article{10.11648/j.ijefm.20210906.11,
  author = {Chunhui Liu and Yangguang Lu},
  title = {Modelling and Optimization for the Employment of Full-Time and Part-Time Drivers in Ride-Hailing Platforms},
  journal = {International Journal of Economics, Finance and Management Sciences},
  volume = {9},
  number = {6},
  pages = {221-224},
  doi = {10.11648/j.ijefm.20210906.11},
  url = {https://doi.org/10.11648/j.ijefm.20210906.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijefm.20210906.11},
  abstract = {The employment strategy is of great significance to improve the performances of the ride-hailing platforms. This paper establishes a nonlinear programming model to characterize the employment problem of a ride-hailing platform where full-time drivers and part-time drivers coexist, facing a month-varied daily market size. The daily online time of the full-time drivers is assumed to be fixed, while the daily online time of the part-time drivers is self-scheduled. The objective of the decision model is to maximize the total effective demand of the ride-hailing platform, and the constraints are to guarantee the minimum income of both the full-time and part-time drivers. By solving the models, we find the decision problem can be simplified as a linear programming model and the optimal numbers of full-time drivers and part-time drivers are derived. Theoretical results show that it is optimal for the ride-hailing platform to employ only part-time drivers if the cap of number of part-time drivers is sufficiently high, and the number of part-time drivers satisfies that the expected income per unit time during the month with the minimum daily market size equals the required minimum income. Otherwise, if the cap of number of part-time drivers is not sufficiently high, full-time drivers and part-time drivers will coexist. Finally, a numerical experiment is conducted to illustrate the theoretical results.},
 year = {2021}
}

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TY  - JOUR
T1  - Modelling and Optimization for the Employment of Full-Time and Part-Time Drivers in Ride-Hailing Platforms
AU  - Chunhui Liu
AU  - Yangguang Lu
Y1  - 2021/11/12
PY  - 2021
N1  - https://doi.org/10.11648/j.ijefm.20210906.11
DO  - 10.11648/j.ijefm.20210906.11
T2  - International Journal of Economics, Finance and Management Sciences
JF  - International Journal of Economics, Finance and Management Sciences
JO  - International Journal of Economics, Finance and Management Sciences
SP  - 221
EP  - 224
PB  - Science Publishing Group
SN  - 2326-9561
UR  - https://doi.org/10.11648/j.ijefm.20210906.11
AB  - The employment strategy is of great significance to improve the performances of the ride-hailing platforms. This paper establishes a nonlinear programming model to characterize the employment problem of a ride-hailing platform where full-time drivers and part-time drivers coexist, facing a month-varied daily market size. The daily online time of the full-time drivers is assumed to be fixed, while the daily online time of the part-time drivers is self-scheduled. The objective of the decision model is to maximize the total effective demand of the ride-hailing platform, and the constraints are to guarantee the minimum income of both the full-time and part-time drivers. By solving the models, we find the decision problem can be simplified as a linear programming model and the optimal numbers of full-time drivers and part-time drivers are derived. Theoretical results show that it is optimal for the ride-hailing platform to employ only part-time drivers if the cap of number of part-time drivers is sufficiently high, and the number of part-time drivers satisfies that the expected income per unit time during the month with the minimum daily market size equals the required minimum income. Otherwise, if the cap of number of part-time drivers is not sufficiently high, full-time drivers and part-time drivers will coexist. Finally, a numerical experiment is conducted to illustrate the theoretical results.
VL  - 9
IS  - 6
ER  -

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Author Information

Chunhui Liu

School of Business Administration, South China University of Technology, Guangzhou, China
Yangguang Lu

Big Data Institute, Sany Heavy Machinery Ltd., Suzhou, China

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Plain Text BibTeX RIS

APA Style

Chunhui Liu, Yangguang Lu. (2021). Modelling and Optimization for the Employment of Full-Time and Part-Time Drivers in Ride-Hailing Platforms. International Journal of Economics, Finance and Management Sciences, 9(6), 221-224. https://doi.org/10.11648/j.ijefm.20210906.11

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ACS Style

Chunhui Liu; Yangguang Lu. Modelling and Optimization for the Employment of Full-Time and Part-Time Drivers in Ride-Hailing Platforms. Int. J. Econ. Finance Manag. Sci. 2021, 9(6), 221-224. doi: 10.11648/j.ijefm.20210906.11

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AMA Style

Chunhui Liu, Yangguang Lu. Modelling and Optimization for the Employment of Full-Time and Part-Time Drivers in Ride-Hailing Platforms. Int J Econ Finance Manag Sci. 2021;9(6):221-224. doi: 10.11648/j.ijefm.20210906.11

Copy | Download

@article{10.11648/j.ijefm.20210906.11,
  author = {Chunhui Liu and Yangguang Lu},
  title = {Modelling and Optimization for the Employment of Full-Time and Part-Time Drivers in Ride-Hailing Platforms},
  journal = {International Journal of Economics, Finance and Management Sciences},
  volume = {9},
  number = {6},
  pages = {221-224},
  doi = {10.11648/j.ijefm.20210906.11},
  url = {https://doi.org/10.11648/j.ijefm.20210906.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijefm.20210906.11},
  abstract = {The employment strategy is of great significance to improve the performances of the ride-hailing platforms. This paper establishes a nonlinear programming model to characterize the employment problem of a ride-hailing platform where full-time drivers and part-time drivers coexist, facing a month-varied daily market size. The daily online time of the full-time drivers is assumed to be fixed, while the daily online time of the part-time drivers is self-scheduled. The objective of the decision model is to maximize the total effective demand of the ride-hailing platform, and the constraints are to guarantee the minimum income of both the full-time and part-time drivers. By solving the models, we find the decision problem can be simplified as a linear programming model and the optimal numbers of full-time drivers and part-time drivers are derived. Theoretical results show that it is optimal for the ride-hailing platform to employ only part-time drivers if the cap of number of part-time drivers is sufficiently high, and the number of part-time drivers satisfies that the expected income per unit time during the month with the minimum daily market size equals the required minimum income. Otherwise, if the cap of number of part-time drivers is not sufficiently high, full-time drivers and part-time drivers will coexist. Finally, a numerical experiment is conducted to illustrate the theoretical results.},
 year = {2021}
}

Copy | Download

TY  - JOUR
T1  - Modelling and Optimization for the Employment of Full-Time and Part-Time Drivers in Ride-Hailing Platforms
AU  - Chunhui Liu
AU  - Yangguang Lu
Y1  - 2021/11/12
PY  - 2021
N1  - https://doi.org/10.11648/j.ijefm.20210906.11
DO  - 10.11648/j.ijefm.20210906.11
T2  - International Journal of Economics, Finance and Management Sciences
JF  - International Journal of Economics, Finance and Management Sciences
JO  - International Journal of Economics, Finance and Management Sciences
SP  - 221
EP  - 224
PB  - Science Publishing Group
SN  - 2326-9561
UR  - https://doi.org/10.11648/j.ijefm.20210906.11
AB  - The employment strategy is of great significance to improve the performances of the ride-hailing platforms. This paper establishes a nonlinear programming model to characterize the employment problem of a ride-hailing platform where full-time drivers and part-time drivers coexist, facing a month-varied daily market size. The daily online time of the full-time drivers is assumed to be fixed, while the daily online time of the part-time drivers is self-scheduled. The objective of the decision model is to maximize the total effective demand of the ride-hailing platform, and the constraints are to guarantee the minimum income of both the full-time and part-time drivers. By solving the models, we find the decision problem can be simplified as a linear programming model and the optimal numbers of full-time drivers and part-time drivers are derived. Theoretical results show that it is optimal for the ride-hailing platform to employ only part-time drivers if the cap of number of part-time drivers is sufficiently high, and the number of part-time drivers satisfies that the expected income per unit time during the month with the minimum daily market size equals the required minimum income. Otherwise, if the cap of number of part-time drivers is not sufficiently high, full-time drivers and part-time drivers will coexist. Finally, a numerical experiment is conducted to illustrate the theoretical results.
VL  - 9
IS  - 6
ER  -

Copy | Download