Research on Crowdsourcing Logistics Platform Pricing Considering Service Level

DOI

10.2991/assehr.k.200826.256How to use a DOI?

Keywords

crowdsourcing logistics, service level, network externality, rate of return, pricing

Abstract

Based on the externality of the network, this paper studies the problem of maximizing the revenue of crowdsourcing logistics platforms considering users’ preference for service level, and constructs a dynamic pricing mathematical model of crowdsourcing logistics service products during a fixed sales period. The impact of service level, network externalities, and return rate on the sales volume, optimal price, and total profit of crowdsourcing logistics services is analyzed. The research results show that: (1) For high-level crowdsourcing logistics services, the platform should increase prices to increase sales and revenue; (2) In the initial stage of sales, the platform can enhance network externalities by reducing prices, and then slowly increase price increases Income; (3) an increase in the rate of return will cause an increase in the marginal cost. In order to ensure a positive increase in the rate of return, the rate of return needs to be controlled within a certain reasonable range.

Copyright

© 2020, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Ren Nan
AU  - Sun Qun
PY  - 2020
DA  - 2020/08/28
TI  - Research on Crowdsourcing Logistics Platform Pricing Considering Service Level
BT  - Proceedings of the 2020 4th International Seminar on Education, Management and Social Sciences (ISEMSS 2020)
PB  - Atlantis Press
SP  - 1247
EP  - 1252
SN  - 2352-5398
UR  - https://doi.org/10.2991/assehr.k.200826.256
DO  - 10.2991/assehr.k.200826.256
ID  - Nan2020
ER  -