Characterizing client usage patterns and service demand for car-sharing systems

Alencar, Victor Aquiles; Rooke, Felipe; Cocca, Michele; Vassio, Luca; Almeida, Jussara M.; Vieira, Alex Borges

doi:10.1016/j.is.2019.101448

Cited by 22 publications

(26 citation statements)

References 9 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…However, as a brand-new mode of car rental business, car sharing already has the key characteristics of disruptive innovation such as target market damage, low-price invasion and advantage of disruptive technology, which would cause a huge impact on traditional taxi industry [32]. Therefore, scholars began to explore the competitive advantages of car sharing from different aspects and analyze the competitive evolution trend of car sharing market [33][34][35][36][37][38][39]. Competitive advantage refers to the sustainable advantage compared with competitors, which includes cost leadership advantage and differentiation advantage [40,41].…”

Section: The Competition and Evolution Of The Car Sharing Marketmentioning

confidence: 99%

“…It was found that in contrast to station-based car sharing, free-floating car sharing does not rely on the high-quality public transport infrastructure [34]. Scholars also found that compared with round-way car sharing, one-way car sharing and free-floating car sharing are more often used for short trips [35]. Compared with one-way car sharing and free-floating car sharing, the usage of round-way car sharing is much lower [35].…”

Section: The Competition and Evolution Of The Car Sharing Marketmentioning

confidence: 99%

“…Scholars also found that compared with round-way car sharing, one-way car sharing and free-floating car sharing are more often used for short trips [35]. Compared with one-way car sharing and free-floating car sharing, the usage of round-way car sharing is much lower [35]. In addition, the game relationship between car sharing and existing transportation systems is a popular topic discussed by scholars [36][37][38][39].…”

Section: The Competition and Evolution Of The Car Sharing Marketmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

See 3 more Smart Citations

Understanding the Competitive Advantages of Car Sharing from the Travel-Cost Perspective

Dong

Cai

Cheng

et al. 2020

IJERPH

View full text Add to dashboard Cite

The emergence and development of car sharing can not only satisfy people’s diverse travel demands, but also can bring a new solution to facilitate urban low-carbon and green development. With the increasing acceptance of car sharing, the market competition between car sharing and traditional taxis is becoming increasingly fierce. Therefore, we explore the advantages of car sharing to travelers compared with taxis. In this paper, we first use the GPS (Global Positioning System) trajectory data of car sharing orders to construct a comparative advantage model based on travel-cost. Then, we take Beijing as the research area to explore the travel-cost advantages of car sharing in terms of the time and space dimensions compared with taxis, through calculating the travel-cost of car sharing and using simulation to calculate that of taxis. The results of the comparison between car sharing and taxis from the perspective of travel-cost are as follows: (1) Compared with short trips, the travel-cost advantage of car sharing is relatively higher in medium and long trips; for travelers, the taxi has a higher travel-cost advantage when the travel time is either very long or very short. (2) On weekdays, it is more cost-effective to travel by shared cars for travelers before the rush hours in the evening, and the travel-cost advantage of using taxis is greater after the evening peak. (3) Compared with weekdays, it is more cost-effective to travel by shared cars on weekends wherever travelers are living in the main urban areas or in the remote suburbs. It is suggested that relevant departments should understand the travelers’ preference and analyze the influence mechanism of other various factors on the market demand for car sharing as per the focus on the market on the travel-cost advantages of car sharing, so as to promote the healthy and sustainable development of urban shared transportation.

show abstract

Section: The Competition and Evolution Of The Car Sharing Marketmentioning

confidence: 99%

Section: The Competition and Evolution Of The Car Sharing Marketmentioning

confidence: 99%

Section: The Competition and Evolution Of The Car Sharing Marketmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

See 2 more Smart Citations

Understanding the Competitive Advantages of Car Sharing from the Travel-Cost Perspective

Dong

Cai

Cheng

et al. 2020

IJERPH

View full text Add to dashboard Cite

show abstract

“…In our previous work [18] we analyzed in depth the usage of different car sharing systems in Vancouver. Based on this data we developed a model of FFCS usage and built a simulator to design new systems based on electric vehicles [5].…”

Section: Related Workmentioning

confidence: 99%

On Car Sharing Usage Prediction with Open Socio-Demographic Data

Cocca¹,

Teixeira²,

Vassio³

et al. 2019

Preprint

Self Cite

View full text Add to dashboard Cite

Free Floating Car Sharing (FFCS) services are a flexible alternative to car ownership. These transportation services show highly dynamic usage both over different hours of the day, and across different city areas. In this work, we study the problem of predicting FFCS demand patterns -- a problem of great importance to an adequate provisioning of the service. We tackle both the prediction of the demand i) over time and ii) over space. We rely on months of real FFCS rides in Vancouver, which constitute our ground truth. We enrich this data with detailed socio-demographic information obtained from large open-data repositories to predict usage patterns. Our aim is to offer a thorough comparison of several machine learning algorithms in terms of accuracy and easiness of training, and to assess the effectiveness of current state-of-art approaches to address the prediction problem. Our results show that it is possible to predict the future usage with relative errors down to 10%, and the spatial prediction can be estimated with relative errors of about 40%. Our study also uncovered the socio-demographic features that most strongly correlate with FFCS usage, providing interesting insights for providers opening service in new regions.

show abstract

Feasibility Analysis of Electric Vehicle Promotion Based on Evolutionary Game

Huang

2020

Advances in Intelligent Systems and Computing

View full text Add to dashboard Cite

Characterizing client usage patterns and service demand for car-sharing systems

Cited by 22 publications

References 9 publications

Understanding the Competitive Advantages of Car Sharing from the Travel-Cost Perspective

Understanding the Competitive Advantages of Car Sharing from the Travel-Cost Perspective

On Car Sharing Usage Prediction with Open Socio-Demographic Data

Feasibility Analysis of Electric Vehicle Promotion Based on Evolutionary Game

Contact Info

Product

Resources

About