Spatial Pricing in Ride-Sharing Networks

Bimpikis, Kostas; Candogan, Ozan; Sabán, Daniela

doi:10.1287/opre.2018.1800

Cited by 381 publications

(113 citation statements)

References 14 publications

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“…Ridesharing has long been a research hotspot in the transport field, previous studies have discussed the ridematching algorithms for ridesharing systems [2][3], dynamic ridesharing pricing [4][5], labour supply [6], trust among peers [7][8], socio-economic impacts of ridesharing services [9], environmental effects of ridesharing [10][11] Some scholars began to pay close attention to the impact of ridesharing on traffic congestion. There are different voices on distinguishing an impact of ridesharing on traffic.…”

Section: Literature Reviewmentioning

confidence: 99%

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A Side-Constrained Peer-to-Peer Carpooling Stochastic User Equilibrium Model

2020

Teh. vjesn

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Peer-to-peer (P2P) carpooling has become an effective way to utilize the idle car capacity and ease traffic congestion. However, the interactive relationship between carpooling and traffic congestion has not been fully quantified. To make up for this gap, this paper constructs a side-constrained P2P carpooling stochastic user equilibrium model to disclose the effects of carpooling on traffic congestion. Next, the proposed model was transformed into a linear constrained minimization problem, and the problem was proved to have a unique solution. The case study shows that the travellers prefer carpooling at a high fuel price and a low inconvenient cost.

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Section: Literature Reviewmentioning

confidence: 99%

“…2). The demand q of the OD pair (1,4) was set to 400. The details on ta, l a , and c a are shown in Tab.…”

Section: Case Studymentioning

confidence: 99%

A Side-Constrained Peer-to-Peer Carpooling Stochastic User Equilibrium Model

2020

Teh. vjesn

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“…The sharing economy, which is characterized by the sharing of usage rights, creates a great prospect about the potential sustainability benefits [29]. Current research on sharing economy focuses on collaborative consumption in the field of transportation [18], space [19], and durable goods [20]. Wu et al [30] studied the sharing economy from an environmental perspective and found that the sharing economy could help to allocate resources and reduce greenhouse gas emissions.…”

Section: Literature On Production Capacity Sharingmentioning

confidence: 99%

“…In recent years, although the issues about the production capacity sharing have attracted some scholars, this topic is still in its infancy. Firstly, scholars are keen to study capacity sharing in the field of consumption such as transportation, space, and durable goods [18][19][20], where the system generally consists of three parties: suppliers, demanders and sharing platforms. However, there are four parties repeated), etc.…”

Section: Introductionmentioning

confidence: 99%

Channel Selection and Pricing Decisions Considering Three Charging Modes of Production Capacity Sharing Platform: A Sustainable Operations Perspective

et al. 2019

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In the context of sharing economy, a manufacturer can source from two alternative channels: sharing and traditional, when facing production capacity constraints and sustainably conscious consumers. The aim of the paper is to analyze channel selection and pricing strategies of the manufacturer for achieving sustainable operations, to investigate the operations of the platform regarding charging modes, access requirements, and commission rates in different stages of development, and to discuss the interaction among all stakeholders for sustainability in the whole system. The game-theoretic approach is adopted. The results provide references for decisions of the manufacturer and surplus production capacity supplier to join in the sharing, as well as corresponding optimal pricing strategies, which guides platforms to keep a balance between profitability and attracting participants by relatively low access requirements and commission rates. Moreover, developing platforms prefer to charge suppliers and set low access requirements while relatively developed platforms tend to charge bilateral sides or manufacturers and set high access requirements. Charging the manufacturer encourages the bilateral participation of the platform most. In addition, as charging mode changes, the trend of changes in consumer surplus and social welfare is the same as that in the market share of products from the sharing channel.More specifically, from the perspective of actual operations, production capacity sharing brings new directions to sustainable supply chain management issues. For example, as consumers have become more sustainably concerned [16,17], production capacity sharing on the platforms is an effective alternative for manufacturing enterprises to ensure competitive advantage by meeting demands of the market, reduce their risk of wasting capacity, no longer face with the selection limitations, optimize business scheduling, and gain new revenue streams [13]. However, production capacity sharing mechanism design considering sharing features is challenging. For example, a capacity-constrained manufacturer or an overcapacity supplier needs to decide whether to join in the sharing considering the cost of the sharing and consumer's consciousness of sustainability comprehensively. In addition, a platform operator needs to design appropriate operational mechanisms particularly the charging mechanisms to balance the relationship between attracting participants of the platform and gaining profits, considering its own development levels and operational goals. Therefore, with regards to production capacity sharing, how to make channel selection decisions and corresponding optimal pricing strategies for manufacturing enterprises and how to design operational mechanisms for platforms from a sustainable operations perspective is important, urgent, and promising. In other words, the aims of this paper are to explore the behaviors of the overcapacity manufacturer and capacity supplier in traditional and sharing manufacturing environments and the ...

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“…Note that our survey reviews the papers that focus on operational decisions made by the P2P ride-sharing system operator, including the matching, routing, and scheduling of users. Therefore, this survey does not include the study of economics (Wang et al 2018a, Zha et al 2018b, Bimpikis et al 2019 and/or user equilibrium analyses (Wang et al 2018b) involved in such systems. Compared with the existing surveys (Agatz et al 2012, Chan and Shaheen 2012, Furuhata et al 2013, Ordóñez and Dessouky 2017, the contributions of this paper are threefold: (i) it includes the related work that has appeared since then, (ii) it delves into details of the proposed algorithms, and (iii) it identifies new directions for research.…”

Section: Introductionmentioning

confidence: 99%

Frontiers in Service Science: Ride Matching for Peer-to-Peer Ride Sharing: A Review and Future Directions

2020

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As a consequence of the sharing economy attaining more popularity, there has been a shift toward shared-use mobility services in recent years, especially those that encourage users to share their personal vehicles with others. To date, different variants of these services have been proposed that call for different settings and give rise to different research questions. Peer-to-peer (P2P) ride sharing is one such service that provides a platform for drivers to share their personal trips with riders who have similar itineraries. Unlike ride-sourcing services, drivers in P2P ride sharing have their own individual trips to make and are not driving for the sole purpose of serving rider requests. Unlike traditional carpooling, P2P ride sharing can serve on-demand and one-time trip requests. P2P ride sharing has been identified as a sustainable mode of transportation that results in several individual and societal benefits. The core of a P2P ride-sharing system is a ride-matching problem that determines ride-sharing plans for users. This paper reviews the major studies on the operations of P2P ride-sharing systems, with a focus on modeling and solution methodologies for matching, routing, and scheduling. In this paper, we classify ride-sharing systems based on their operational features and review the existing methodologies for each class. We further discuss a number of important directions for future research.

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Spatial Pricing in Ride-Sharing Networks

Cited by 381 publications

References 14 publications

A Side-Constrained Peer-to-Peer Carpooling Stochastic User Equilibrium Model

A Side-Constrained Peer-to-Peer Carpooling Stochastic User Equilibrium Model

Channel Selection and Pricing Decisions Considering Three Charging Modes of Production Capacity Sharing Platform: A Sustainable Operations Perspective

Frontiers in Service Science: Ride Matching for Peer-to-Peer Ride Sharing: A Review and Future Directions

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