TY - JOUR
T1 - Modelling and analysis of online ride-sharing platforms – A sustainability perspective
AU - Guo, Yuhan
AU - Zhang, Yu
AU - Boulaksil, Youssef
AU - Qian, Yaguan
AU - Allaoui, Hamid
N1 - Funding Information:
This work was supported by the Natural Science Foundation of China [Grant Nos. 61404069 and 71771111 ] and the Provincial Natural Science Foundation [Grant No. 2019-ZD-0048 ]. The data source of this work is provided by the Didi Chuxing GAIA Initiative.
Funding Information:
This work was supported by theNatural Science Foundation of China [Grant Nos. 61404069 and 71771111] and the Provincial Natural Science Foundation [Grant No. 2019-ZD-0048]. The data source of this work is provided by the Didi Chuxing GAIA Initiative.
Publisher Copyright:
© 2022 Elsevier B.V.
PY - 2023/1/16
Y1 - 2023/1/16
N2 - By directly connecting passengers and private transportation service providers, online ride-sharing platforms reduce the number of intermediaries and improve the utilization of transportation resources. In addition to economic benefits, ride-sharing could provide environmental and social advantages. This paper studies a sustainability-oriented operational model for online ride-sharing platforms. We develop a holistic multi-objective mathematical model considering important indicators of the triple-bottom-line and examine its effects on the dispatching strategy. An effective method has been introduced to solve the model, as well as an approach to efficiently generate the Pareto front. Moreover, we validate the model and the solution methods through an extensive case study with different scenarios based on large-scale real-world data. We study the correlation among the objectives and analyse their variation trends when adjusting the influential factors. Finally, in this paper, useful managerial insights are provided for decision-makers of the platforms, such as how to balance the triple-bottom-line in a smart way.
AB - By directly connecting passengers and private transportation service providers, online ride-sharing platforms reduce the number of intermediaries and improve the utilization of transportation resources. In addition to economic benefits, ride-sharing could provide environmental and social advantages. This paper studies a sustainability-oriented operational model for online ride-sharing platforms. We develop a holistic multi-objective mathematical model considering important indicators of the triple-bottom-line and examine its effects on the dispatching strategy. An effective method has been introduced to solve the model, as well as an approach to efficiently generate the Pareto front. Moreover, we validate the model and the solution methods through an extensive case study with different scenarios based on large-scale real-world data. We study the correlation among the objectives and analyse their variation trends when adjusting the influential factors. Finally, in this paper, useful managerial insights are provided for decision-makers of the platforms, such as how to balance the triple-bottom-line in a smart way.
KW - Decision analysis
KW - Pareto front
KW - Ride-sharing
KW - Service supply chain
KW - Sustainability
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U2 - 10.1016/j.ejor.2022.04.035
DO - 10.1016/j.ejor.2022.04.035
M3 - Article
AN - SCOPUS:85130387905
SN - 0377-2217
VL - 304
SP - 577
EP - 595
JO - European Journal of Operational Research
JF - European Journal of Operational Research
IS - 2
ER -