Exploring the factors affecting bike-sharing demand: evidence from student perceptions, usage patterns and adoption barriers

Torrisi, Vincenza; Ignaccolo, Matteo; Inturri, Giuseppe; Tesoriere, Giovanni; Campisi, Tiziana

doi:10.1016/j.trpro.2021.01.068

Cited by 37 publications

(21 citation statements)

References 22 publications

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“…One model, in particular, has shown excellent fit in identifying key variables for active commuting behaviors: the Theory of Planned Behavior (TPB, Ajzen, 1991 ). After the dispersal of COVID-19, the number of studies on bicycle use for active commuting in the Italian context has increased (e.g., Torrisi et al, 2021 ); however, none of these studies have focused on the TPB framework. In a recent review, Caballero et al (2019) observed that the model explained 25–73% of the variance in intention to use a bicycle.…”

Section: Introductionmentioning

confidence: 99%

Comparing the Relative Importance of Predictors of Intention to Use Bicycles

et al. 2022

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The use of bicycles for active commuting is an important target to reach because of the importance of increasing physical activity among the population and improving the air quality in cities. Among the models that have been utilized in previous studies, the Theory of Planned Behavior (TPB) has shown good results in terms of the total variance obtained. However, establishing the relative importance of the TPB variables is difficult. In the present study, which was carried out in the Italian context, the authors sought to establish the weight of the proposed variables based on the dominance analysis approach. Considering the initiatives, which the Italian government carries out, and the particular period in which the study was developed, the authors included two variables in addition to the classical factors: financial incentives and daily commuting habits. A survey was administered to 294 Italians (222 females and 72 males, from 18 to 77 years old) through social networks from July to September 2020. The results have shown how the main predictor of bicycle use was use habits, followed almost at the same level by financial incentives and attitude, while norms and perceived behavioral control (PBC) present low relative importance among the variables considered. Limits of the study have been discussed, and suggestions for future research have been proposed.

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Section: Introductionmentioning

confidence: 99%

Comparing the Relative Importance of Predictors of Intention to Use Bicycles

et al. 2022

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“…Excluding these variables, therefore, will have few consequences for the analysis of BSSs. Indeed, the attention of scientists notices the dependence of the use of public bikes on the population density, but rather focuses on social groups, such as tourists in Yang et al work [84], or students in Manca et al [7], Zainuddin et al [95], and Torrisi et al [96] publications. The issue of bicycle lane priority is usually understood in terms of traffic safety [97], but also as a promotional tool by Bagloee et al [98].…”

Section: Discussionmentioning

confidence: 99%

External Environmental Analysis for Sustainable Bike-Sharing System Development

Macioszek

Cieśla

2022

Energies

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The paper introduces a discussion regarding the development of a public bike-sharing system, considering random factors, based on selected external environmental analysis methods. The global energy crisis is forcing scientists to continuously improve energy-efficient sustainable methods and scientific solutions. It is particularly important in transportation since transport activities and the constant increase in the number of vehicles have a large share in global energy consumption. The following study investigates the social, technological, economic, environmental, and political aspects of bike-sharing systems in cities. The research purpose of the article is to select the most important macro-environmental factors and their mutual interaction influencing the sustainable development of bike-sharing systems based on the Polish cities case study. The evaluation was carried out through expert methods with STEEP environmental analysis, evaluation of factors with the weighted score, and structural analysis method with MICMAC computer application. The classification of key factors influencing the development of a bike-sharing system has divided them into five groups. It can support public transport service providers and organizers. This can optimize the planning process with decision-making based on future environmental trends.

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“…Kaplan et al [ 10 ] proposed the joint model of frequency and severity of cyclist–motorist collisions, and emphasized the focus on bicycle paths to improve road design and traffic management. Torrisi et al [ 24 ] believed that infrastructure construction can promote the use of sharing bikes. Moreover, the setting of management facilities also had a significant impact on cycling.…”

Section: Literature Reviewmentioning

confidence: 99%

Exploring Unobserved Heterogeneity in Cyclists’ Occupying Motorized Vehicle Lane Behaviors at Different Bike Facility Configurations

Zhang

Zhou

et al. 2022

IJERPH

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Cyclists occupying motorized vehicle lanes disrupt road traffic order and increase collisions. Exploring the contributing factors could help develop countermeasures to regulate such behaviors. The purpose of this study is to explore the intrinsic features influencing the behavior of cyclists in occupying motorized vehicle lanes at different bicycle facilities. We investigated a total of 34,631 cycling behavior samples in the urban area of Pingdingshan, China. A Bayesian random parameter logit model was used to account for the unobserved heterogeneous effects. The experimental results of all bike facilities demonstrate that the bike type, dividing strip type, bike lane width, temporary on-street parking, and whether it is a working day significantly affect cyclists’ occupying motorized vehicle lane behaviors. Factors associated with unobserved heterogeneity are age, barriers dividing strip, vehicle lane numbers, bike volume, vehicle volume, and daily recording time intervals. Comparing the estimated model of five type bike lane facilities across different dividing strips, we find that cyclists have a significantly different occupying probability and the heterogeneity factors of the various bike facilities also have their focus. When the non-motorized road conditions become more open, the cyclist behavior becomes more random and the heterogeneity factors become broader.

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Exploring the factors affecting bike-sharing demand: evidence from student perceptions, usage patterns and adoption barriers

Cited by 37 publications

References 22 publications

Comparing the Relative Importance of Predictors of Intention to Use Bicycles

Comparing the Relative Importance of Predictors of Intention to Use Bicycles

External Environmental Analysis for Sustainable Bike-Sharing System Development

Exploring Unobserved Heterogeneity in Cyclists’ Occupying Motorized Vehicle Lane Behaviors at Different Bike Facility Configurations

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