Ridesharing as a Service: Exploring Crowdsourced Connected Vehicle Information for Intelligent Package Delivery

Wang, Fangxin; Zhu, Yifei; Wang, Feng; Liu, Jiangchuan

doi:10.1109/iwqos.2018.8624152

Cited by 18 publications

(19 citation statements)

References 15 publications

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“…The most related work with this paper is [9] and [4]. Chen et al [9] exploit relays of taxis with passengers to help transport package collectively, without degrading the quality of passenger solutions.…”

Section: Crowdsourced Package Deliverymentioning

confidence: 99%

“…In our paper, no consignment warehouses are needed, and the package delivery is nonstop. Wang et al [4] propose a ridesharing based package delivery solution. When the pickup location of the package is close to the vehicle's source, and the drop off location is close to the vehicle's destination, the vehicle is assumed to deliver the package in a ridesharing way.…”

Section: Crowdsourced Package Deliverymentioning

confidence: 99%

“…A promising alternative to the traditional package delivery methods is by leveraging the ridesharing systems, as the potential delivery capability through ridesharing within an urban environment is enormous [4]. By allowing the passengers and the packages with similar itineraries and time schedules to share one vehicle, the delivery cost can be reduced significantly [5], [6].…”

Section: Introductionmentioning

confidence: 99%

“…Nevertheless, existing ridesharing solutions for package delivery are with two major defects, stopping them from being widely adopted in practice. First, most ridesharing solutions attempt to deliver a package in one shot, i.e., onehop ridesharing [7], [4], [8]. For example, Walmart proposes to make use of its in-store customers to deliver goods to its online customers on their way home from the store [7].…”

Section: Introductionmentioning

confidence: 99%

“…For example, Walmart proposes to make use of its in-store customers to deliver goods to its online customers on their way home from the store [7]. Wang et al [4] encourage a private car to change its regular route to a similar one which passes through the package pick up and drop off locations. Such one-hop ridesharing systems provide little chance to be utilized in the citywide package delivery, as the similar itineraries with likely origin and destination are quite limited.…”

Section: Introductionmentioning

confidence: 99%

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PPtaxi: Non-Stop Package Delivery via Multi-Hop Ridesharing

Chen

Guo

Tang

et al. 2020

IEEE Trans. on Mobile Comput.

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City-wide package delivery becomes popular due to the dramatic rise of online shopping. It places a tremendous burden on the traditional logistics industry, which relies on dedicated couriers and is labor-intensive. Leveraging the ridesharing systems is a promising alternative, yet existing solutions are limited to one-hop ridesharing or need consignment warehouses as relays. In this paper, we propose a new package delivery scheme which takes advantage of multi-hop ridesharing and is entirely consignment free. Specifically, a package is assigned to a taxi which is guided to deliver the package all along to its destination while transporting successive passengers. We tackle it with a two-phase solution, named PPtaxi. In the first phase, we use the Multivariate Gauss distribution and Bayesian inference to predict the passenger orders. In the second phase, both the computation efficiency and solution effectiveness are considered to plan package delivery routes. We evaluate PPtaxi with a real-world dataset from an online taxi-taking platform and compare it with multiple benchmarks. The results show that the successful delivery rate of packages with our solution can reach 95% on average during the daytime, and is at most 46.9% higher than those of the benchmarks.

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Section: Crowdsourced Package Deliverymentioning

confidence: 99%

Section: Crowdsourced Package Deliverymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

PPtaxi: Non-Stop Package Delivery via Multi-Hop Ridesharing

Chen

Guo

Tang

et al. 2020

IEEE Trans. on Mobile Comput.

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5G in Logistics 4.0: potential applications and challenges

Lagorio

Cimini

Pinto

et al. 2023

Procedia Computer Science

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Continuous participation intention in on-demand logistics: interactive effects of order assignment and delivery-related information disclosure strategies

Zhao

Yuan

Liu

et al. 2022

IMDS

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PurposeCouriers are in an unequal relationship with on-demand logistic platforms with regards to order assignment and delivery-related information acquisition, which leads to high courier turnover rates. Based on social cognitive theory and justice theory, this research investigates the impact of order assignment and delivery-related information disclosure strategy on couriers' perceived justice and continuous participation intention and presents managerial suggestions to on-demand logistic platforms to lower the courier turnover rate.Design/methodology/approachTaking Chinese couriers as experimental subjects, this study conducts experiments by constructing an order receiving scene of order assignment strategy (performance-priority vs distance-priority) and delivery-related information disclosure strategy (detailed-information vs brief-information) and analyzes the results of 452 valid respondents.FindingsThe results indicate that the interaction between order assignment and delivery-related information disclosure strategy in on-demand logistics significantly affects couriers’ continuous participation intention, specifically under performance-priority order assignment and detailed-information (vs brief-information) disclosure strategy. Informational justice and distribution justice play mediating roles, and work experience and proactive personality moderate the relationship interactions.Practical/Social implicationsThe research helps us to understand the order-receiving justice demand and delivery-related information demand of couriers in on-demand logistics platforms and sheds light on cutting down turnover rates through different strategies designs and justice environment construction.Originality/valueThis research integrates social cognitive theory into on-demand logistics and combines with justice theory to fill platform strategies, couriers’ justice perception and characteristics, as well as behavior into “triadic reciprocal causation.” Meanwhile, it investigates different impacts and interactive relationships of order assignment and delivery-related information disclosure strategy, expands strategies from the impact of operational efficiency to the impact of couriers’ participation and extends the literature of justice perception and individual characteristics in on-demand logistics.

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Ridesharing as a Service: Exploring Crowdsourced Connected Vehicle Information for Intelligent Package Delivery

Cited by 18 publications

References 15 publications

PPtaxi: Non-Stop Package Delivery via Multi-Hop Ridesharing

PPtaxi: Non-Stop Package Delivery via Multi-Hop Ridesharing

5G in Logistics 4.0: potential applications and challenges

Continuous participation intention in on-demand logistics: interactive effects of order assignment and delivery-related information disclosure strategies

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