Utilizing multi-stage behavior change theory to model the process of bike share adoption

Biehl, Alec; Ermagun, Alireza; Stathopoulos, Amanda

doi:10.1016/j.tranpol.2019.02.001

Cited by 24 publications

(13 citation statements)

References 83 publications

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“…Extensive studies about bike-sharing have explored improving the planning and operation of bike-sharing, to provide better services for users. Previous studies about bike-sharing can be generally classified into three categories: (1) user demand ( Wang et al, 2018 ; Biehl et al, 2019 ; Cheng et al, 2020 ; Reilly et al, 2020 ; Chen et al, 2021 ); (2) bike rebalancing ( Caggiani et al, 2018 ; Bruck et al, 2019 ; Huang et al, 2020 ); and (3) parking allocation ( Lin et al, 2018 ; Loidl et al, 2019 ; Hua et al, 2020 ).…”

Section: Literature Reviewmentioning

confidence: 99%

Should bike-sharing continue operating during the COVID-19 pandemic? Empirical findings from Nanjing, China

Hua

Chen

Cheng

et al. 2021

Journal of Transport & Health

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Introduction Coronavirus disease 2019 (COVID-19) has triggered a worldwide outbreak of pandemic, and transportation services have played a key role in coronavirus transmission. Although not crowded in a confined space like a bus or a metro car, bike-sharing users are exposed to the bike surface and take the transmission risk. During the COVID-19 pandemic, how to meet user demand and avoid virus spreading has become an important issue for bike-sharing. Methods Based on the trip data of bike-sharing in Nanjing, China, this study analyzes the travel demand and operation management before and after the pandemic outbreak from the perspectives of stations, users, and bikes. Semi-logarithmic difference-in-differences model, visualization methods, and statistic indexes are applied to explore the transportation service and risk prevention of bike-sharing during the pandemic. Results Pandemic control strategies sharply reduced user demand, and commuting trips decreased more significantly. Some stations around health and religious places become more important. Men and older adults may be more dependent on bike-sharing systems. The declined trips reduce user contacts and transmission risk. Central urban areas have more user close contacts and higher transmission risk than suburban areas. Besides, a new concept of user distancing is proposed to decrease transmission risk and the number of idle bikes. Conclusions This paper is the first research focusing on both user demand and transmission risk of bike-sharing during the COVID-19 pandemic. This study evaluates the mobility role of bike-sharing during the COVID-19 pandemic, and also provides insights into curbing the viral transmission within the city.

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Section: Literature Reviewmentioning

confidence: 99%

Should bike-sharing continue operating during the COVID-19 pandemic? Empirical findings from Nanjing, China

Hua

Chen

Cheng

et al. 2021

Journal of Transport & Health

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“…First and foremost, it suffers from a limited scope and short duration, and therefore, the observed effect on commuting behavior is only a short-term effect. Acknowledging the limited sample size and its non-representativeness, the findings are rather tentative, and with a larger sample, it would definitely benefit from more elaborate analyses, e.g., controlling for various sociodemographic, socio-economic, and other contextual factors that have been shown to influence commuting behavior, such as gender, age, family and occupational status, bike availability, biking skills, and perceived safety [ 30 , 31 , 32 ]. Both of these limitations point to a challenge for future research: These studies should examine potential long-term effects, the persistence of an effect after incentive cessation, and additional means to habitualize induced behavioral change.…”

Section: Discussionmentioning

confidence: 99%

Incentivizing Commuter Cycling by Financial and Non-Financial Rewards

Máca

Ščasný

Zvěřinová

et al. 2020

IJERPH

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Current mobility patterns over-rely on transport modes that do not benefit sustainable and healthy lifestyles. To explore the potential for active mobility, we conducted a randomized experiment aimed at increasing regular commuter cycling in cities. In designing the experiment, we teamed up with developers of the “Cyclers” smartphone app to improve the effectiveness of the app by evaluating financial and non-financial motivational features. Participants in the experiment were recruited among new users of the app, and were randomly assigned to one of four different motivational treatments (smart gamification, two variants of a financial reward, and a combination of smart gamification and a financial reward) or a control group (no specific motivation). Our analysis suggests that people can be effectively motivated to engage in more frequent commuter cycling with incentives via a smartphone app. Offering small financial rewards seems to be more effective than smart gamification. A combination of both motivational treatments—smart gamification and financial rewards—may work the same or slightly better than financial rewards alone. We demonstrate that small financial rewards embedded in smartphone apps such as “Cyclers” can be effective in nudging people to commute by bike more often.

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“…Indeed, literature suggests one of the keys to a successful bike share is to encourage people to adopt a positive attitude towards these bikes [ 44 ]. Research also recommends using multistage behavior change theory to align interventions with user readiness to turning intentions to use bike share into actions [ 45 ].…”

Section: Discussionmentioning

confidence: 99%

Socio-Ecological Predictors of Frequent Bike Share Trips: Do Purposes Matter?

Chen

Hsu

2020

IJERPH

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Using bike share could increase physical activity and improve health. This study used the social-ecological model to identify predictors of frequent bike share trips for different purposes. Participants residing in the U.S. were recruited via Amazon Mechanical Turk (MTurk). Self-report trip purposes were used to group participants into using bike share for commuting only (n = 260), social/entertainment only (n = 313), exercise only (n = 358), dual or triple-purpose (n = 501), and purposes other than commuting, social/entertainment, and exercise (n = 279). Results showed that at the intrapersonal level, perceived use of bike share to be helpful for increasing physical activity was a significant predictor for all groups, except for the other purpose group. Adjusting outdoor activity based on air quality was a significant predictor for the dual or triple-purpose group. At the interpersonal level, having four or more friends/family using bike share was a significant predictor for the other purpose group. At the community level, distance to the nearest bike share within acceptable range was a significant predictor for social/entertainment and dual or triple-purpose groups. The findings suggest that it is important to consider factors at multiple levels for predicting bike share usage. Moreover, health educators and policy makers should adopt different strategies for promoting bike share usage based on trip purposes.

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Utilizing multi-stage behavior change theory to model the process of bike share adoption

Cited by 24 publications

References 83 publications

Should bike-sharing continue operating during the COVID-19 pandemic? Empirical findings from Nanjing, China

Should bike-sharing continue operating during the COVID-19 pandemic? Empirical findings from Nanjing, China

Incentivizing Commuter Cycling by Financial and Non-Financial Rewards

Socio-Ecological Predictors of Frequent Bike Share Trips: Do Purposes Matter?

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