Modeling the Impact of Dock-less Bike-sharing System on Outpatient Trips

2021 ◽  
pp. 102853
Author(s):  
Yuyang Zhou ◽  
Minhe Zhao ◽  
William H.K. Lam ◽  
Anthony Chen ◽  
N.N. Sze ◽  
...  
Keyword(s):  
2020 ◽  
Vol 12 (19) ◽  
pp. 8215 ◽  
Author(s):  
Andreas Nikiforiadis ◽  
Georgia Ayfantopoulou ◽  
Afroditi Stamelou

The COVID-19 pandemic had a significant effect in urban mobility, while essential changes are being observed in travelers’ behavior. Travelers in many cases shifted to other transport modes, especially walking and cycling, for minimizing the risk of infection. This study attempts to investigate the impact that COVID-19 had on travelers’ perceptions towards bike-sharing systems and whether the pandemic could result in a greater or lesser share of trips that are being conducted through shared bikes. For that reason, a questionnaire survey was carried out in the city of Thessaloniki, Greece, and the responses of 223 people were analyzed statistically. The results of the analysis show that COVID-19 will not affect significantly the number of people using bike-sharing for their trips. However, for a proportion of people, bike-sharing is now more attractive. Moreover, the results indicate that bike-sharing is now more likely to become a more preferable mobility option for people who were previously commuting with private cars as passengers (not as drivers) and people who were already registered users in a bike-sharing system. The results also provide evidence about the importance of safety towards COVID-19 for engaging more users in bike-sharing, in order to provide them with a safe mobility option and contribute to the city’s resilience and sustainability.


2020 ◽  
Vol 12 (5) ◽  
pp. 2081 ◽  
Author(s):  
Mao Ye ◽  
Yajing Chen ◽  
Guixin Yang ◽  
Bo Wang ◽  
Qizhou Hu

This study quantifies the impact of individual attributes, the built environment, and travel characteristics on the use of bike-sharing and the willingness of shifting to bike-sharing-related travel modes (bike-sharing combined with other public transportation modes such as bus and subway) under different scenarios. The data are from an RP (Revealed Preference) survey and SP (Stated Preference) survey in Nanjing, China. Three mixed logit models are established: an individual attribute–travel characteristics model, a various-factor bike-sharing usage frequency model, and a mixed scenario–transfer willingness model. It is found that age and income are negatively associated with bike-sharing usage; the transfer distance (about 1 km), owning no car, students, and enterprises are positively associated with bike-sharing usage; both weather and travel distance have a significant negative impact on mode shifting. The sesearch conclusions can provide a reference for the formulation of urban transportation policies, the daily operation scheduling, and service optimization of bike-sharing.


2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Leonard Wong ◽  
Lyon Tan ◽  
Rachel Wong ◽  
Su Lin Yeo

PurposeThe overnight introduction of tens of thousands of dockless bike-share bicycles in Singapore with its indiscriminate parking drew the attention of the media, which generated extensive news reports on the activities carried out by bike-sharing operators. Given the meteoric rise and fall of the industry, this study examines the influence of agenda-setting of news reporting on the public’s perception of the industry and the impact on the firms’ corporate reputation.Design/methodology/approachUtilizing the Reputation Quotient Index, the study content analyzed 147 textual data of online reports which were crawled over two years between 2017 and 2018 from six mainstream news organizations.FindingsOur findings showed that the news reports carried more negative frames in the headlines and body content. It also found that only five out of six dimensions of the Index were emphasized with varying degrees of importance, indicating that the corporate reputation as determined by the media reports did not collectively represent the operators’ past actions and results with valued outcomes.Practical implicationsPractical implications discussed included the need to integrate corporate strategies into public relations programs and the importance of engaging the media to demonstrate congruence between business objectives and positive social impact on society.Originality/valueAlthough the study limited its data collection only to online media reports, it is one of the few research to provide empirical evidence concerning the media’s influence on the public’s perceptions and reputation of the nascent bike-sharing industry.


Author(s):  
Ali Rahim Taleqani ◽  
Jill Hough ◽  
Kendall E. Nygard

Dockless bike sharing is an emerging paradigm. Like many other technologies, it brings advantages and disadvantages to communities. Further investigation into public opinion will shed light on the impact of this technology on communities and provide input to city authorities for transportation planning. Transportation planning processes can be enhanced by engaging the community through social media technologies. Social media like Twitter, Facebook, and other microblogging media have been used for planning, but have not been extensively evaluated for that purpose. This study examined approximately 32,000 posts on Twitter to assess public opinion on dockless bike-sharing systems. Using a mix of text mining and statistical techniques, we examined relevant posts to determine the sentiment polarity of tweets, the underlying topics in the tweets, and the extent of engagement and impact on the decision-making process. Results given by two different sentiment algorithms show that there is more positive than negative polarity across the algorithms. Also, the findings show that the underlying topics in tweets include electric scooters, private e-hailing companies, and blockage of sidewalks, among others. The results indicate that the dockless shared mobility models are potentially useful in generating participation, but faced substantial technical, analytical, and communication barriers to influencing decision-making.


2021 ◽  
Vol 55 ◽  
pp. 378-386
Author(s):  
Stanislav Kubaľák ◽  
Marián Gogola ◽  
Mikuláš Černý
Keyword(s):  

2021 ◽  
pp. 1-12
Author(s):  
Peng-Sheng You ◽  
Yi-Chih Hsieh

Leveraging their networks, bike rental companies usually provide customers with services for renting and returning bikes at different bike stations. Over time, however, rental networks may encounter problems with unbalanced bike stocks. The potential imbalance between supply and demand at bike stations may result in lost sales for stations with relatively high demand and underutilization for stations with relatively low demand. This paper proposed a constrained mixed-integer programming model that uses operator-based redistribution and user-based price approach to rebalance bikes across bike stations. This paper aims to maximize total profit over a planning horizon by determining operator-based bike transfers and dynamic pricing. The proposed model is a non-deterministic polynomial-time problem, and thus, a heuristic was developed based on linear programming and evolutionary computation to perform model solving. Numerical experiments reveal that the proposed method performed better than Lingo, a well-known commercial software. Sensitivity analyses were also performed to investigate the impact of changes in system parameters on computational results.


Sign in / Sign up

Export Citation Format

Share Document