Search Results (19)

This article aims to analyze the use of a bike-sharing system (BSS) during the flooding event caused by extreme rainfall that hit the municipality of Porto Alegre, Brazil, in May 2024. Public transport services were interrupted, prompting an investigation into the resilience of the BSS during the crisis. Considering data from the Tembici BSS company, a set of approximately 400,000 trips made between 104 stations in the municipality of Porto Alegre from January to May 2024 were analyzed. Daily rainfall data from the National Institute of Meteorology (INMET) were compared with the daily trip flow to identify the travel flow patterns on the days most affected by the flooding. The results indicate an abrupt drop in shared bicycle use during May 2024, but 7600 trips were recorded despite the crisis. Regarding the travel pattern between 1 May and 10 May, most trips were still for recreational purposes (73%), while trips for work and study accounted for 22% of the total, and only 5% were for delivery services. Overall, the resilience of the BSS during the extreme climate event in question points to the continuation of practical daily activities, although with more significant effects on economic-related activities and lesser effects on leisure-related activities. Full article

During public health emergencies, studying the travel characteristics and influencing factors of shared bicycles during different time periods on weekdays can provide valuable insights for urban transportation planning and offer recommendations for bike-sharing systems (BSS) affected by such events. Utilizing bike-sharing data, this study initiated the analysis by scrutinizing the spatial flow patterns in the core area of Beijing, employing network indicators within the framework of complex network theory. Subsequently, influencing factors associated with bike-sharing trips were pinpointed using the exponential random graph model (ERGM). Using COVID-19 as an example, it examines the impact of public health emergencies on bike-sharing during multiple time periods. Supported by the network analysis method, our findings revealed that the majority of travel activities occurred between adjacent areas. Throughout weekdays, a consistent level of travel activity was observed, exhibiting distinct patterns during daytime and nighttime. The period from 4:00 to 8:00 emerged as the peak time, characterized by heightened traffic and temperature changes. Morning commuting extended until 8:00–12:00, followed by a transition period from 12:00–16:00. The most active travel time, encompassing various purposes, was identified as 16:00–20:00. Additionally, the presence of hospitals and train stations amplified travel within the pandemic-affected area. Finally, variants of ERGMs were employed to assess the influence of finance, shopping, dining, education, transportation, roads, and COVID-19 on bike-sharing activities. The road network emerged as the most critical factor, exhibiting a significant negative impact. Conversely, COVID-19 had the most pronounced positive influence, with transportation stops and educational institutions also contributing significantly in a positive manner. This research provides valuable transportation planning insights for addressing public health emergencies and promotes the effective utilization of bike-sharing systems. Full article

In recent years, numerous cities around the world have adopted bike sharing systems (BSSs). The increasing popularity of these transportation means is directly related to their eco-friendly and health advantages. Several factors affect how citizens make use of BSS, for instance, the size and configuration of a city, where docking stations are located, the associated prices, and others. Moreover, these systems have different usage patterns that vary according to the month, day, or hour but remain constant when compared yearly. However, the onset of the COVID-19 pandemic modified mobility behaviors as various governments around the world implemented mobility restrictions to avoid the spread of the virus. The objective of this investigation is to determine if the usage patterns of BSSs have changed permanently or if we have recovered pre-pandemic levels and usage patterns. Given the special characteristics of each BSS, this study focuses on Barcelona’s BSS, called Bicing. To understand the impact of other BSSs, the further analysis of each system’s unique characteristics is necessary. The study employs bike usage information from the public open data service maintained by Barcelona City Hall, namely, the Open Data BCN website, from January 2019 to December 2023, and it covers mechanical and electrical bikes with more than 4 million records per month. The results show that usage patterns were similar before and after the pandemic; the usage increased in 2021 and 2022 and stabilized in 2023, registering a rise of 17.5% in Bicing usage from 2021 to 2023. However, bike type preferences have changed for reasons unrelated to the pandemic restrictions. The main limitation of this investigation is the lack of continuity in the data due to a change in the company that provides the service in Barcelona. For future research, data from other transportation means can be used to analyze all communication behavior in this city. Additionally, if data are available, a study by gender and age can be performed and used to improve the system for certain groups. Full article

How did Chicago develop one of the largest and most successful Bicycle Sharing Systems in a very short time, what benefits does this system afford to the city and its residents, and what developments threaten this success? Urban areas benefit significantly and in a variety of ways from micromobility, which contributes to an urgently needed sustainability transformation. In this qualitative, exploratory case study, we examine the foundations of the success and types of benefits of the second largest bicycle sharing system in North America, the City of Chicago’s Divvy. We juxtapose our data, which consists of participant and non-participant observations, fieldwork, interviews, documents, and social media posts, with a typology gleaned from the academic literature on bicycle sharing systems to explore Divvy’s wide-ranging positive impact. This typology includes economic, environmental, health and safety, and quality of life benefits. In addition, we identify two further benefits from our data: modularity and zoetic capacity. Despite this impact, we show how the consequences of changes in the ownership structure since 2018 are threatening the success and benefits. The emerging service model is no longer based on the initial pillars of its success: the city’s policy and vision for Divvy, the funding and ownership structure, and the strategic deployment of bicycle stations to balance demand potential with locational equity. Based on our study, we conclude that it is unlikely that the new micromobility system, refocused on more profitable e-bike and e-scooter rentals in privileged neighborhoods, is viable in the long term because it is abandoning the core values that embedded Divvy into the fabric of the city. Worse, the emergent model may actually contribute to a systematic exclusion of poorer neighborhoods and less privileged residents of Chicago. Full article

Decades ago, bicycles used to play an important role in urban transportation in Chinese cities, but they have been gradually replaced by private cars, metro, buses, and some other modes, owning to the fast-growing mobility demand as a result of urban expansion and motorization. However, in recent years, with the development of Information and Communication Technologies (ICT) and the initiative of the sharing economy, bike-sharing systems (BSSs) have been implemented extensively in Chinese cities. Their usage patterns can be revealed via system-generated data, yet less is known about users’ attitudes towards and preferences for these systems. In this study, we draw on two surveys conducted in Guangzhou and Beijing on the perceptions of travelers using BSSs to estimate the effect of demographic factors, bicycle ownership, and trip-level factors on the willingness and potential frequency of BSS usage. In addition, a latent class model is built to analyze the different aspects of theses systems concerned with different types of urban travelers. It is found that respondents’ age, occupation, income, mode combination, and the proximity of origin or destination to the docking station, etc., influence the willingness and frequency of using BSSs. In addition, respondents generally value features such as the proximity of docking stations to trip destinations, safety to ride, and appropriate level of fare. However, different latent classes show a different preference for other features of BSSs. According to the model results, proposals are given for the improvement of the existing systems in Chinese cities. Full article

Bicycle-sharing systems (BSSs) are an effective solution to reduce private car usage in most cities and are an influential factor in encouraging citizens to shift to more sustainable transport modes. In this sense, the location of BSS stations has a critical impact on the system’s efficiency. This study proposed an integrated geographic information system–multi-criteria decision-making (GIS-MCDM) framework that includes the analytic hierarchy process (AHP), technique for order preference by similarity to the ideal solution (TOPSIS), and spatial data processing in GIS to determine a ranking of potential locations for BSS stations. The results of the proposed GIS-MCDM method can be used for both planning a new BSS or expanding one that is currently under operation. The framework was applied to a case study for expanding GIRA, the BSS of Lisbon, Portugal. In it, location criteria were selected in four categories, including criteria from the literature and extracted from available transaction data; in addition, we also suggested some criteria. The rebalancing operator’s staff were the decision makers in this study via their responses to the AHP questionnaire. The rebalancing staff believed that the main criterion of “city infrastructure” with the two sub-criteria of “population density” and “slope” were the most important. Furthermore, the proximity to the “bike network” with the sub-criterion of “proximity to the current bike stations” had less importance. Each criterion’s weight and inconsistency rate were obtained using the Expert Choice software. The geographic values of each criterion were created utilizing the ArcGIS software, and its network analyst module was employed for applying location techniques. Based on the created suitability map, the city’s center was the main suitable area for establishing new stations. Forty-five new bike stations were identified in those areas and ranked using the TOPSIS technique. Full article

A bicycle-sharing system (BSS) has been implemented in Seoul, South Korea to promote green transportation policy as a Sustainable Development Goal (SDG) to mitigate climate change, reduce traffic jams, and promote physical activity. However, the concentration of air pollutants in Seoul often exceeds the standards of the World Health Organization, thereby creating a conflict with SDG 3 (Health). Therefore, it is important to recognize the trade-offs between actions targeted at SDGs as they might offset each other. In this context, a primary concern is investigating how the behavior of BSS users regarding outdoor air pollution appears. This study explores the relationship between ambient air pollution and the behavior of BSS riders in Seoul. We conducted a time-series analysis of associations between particulate air pollution and participation in the BSS. We used generalized additive models, adjusted for mean temperature, humidity, rainfall, day of the week, long-term trends, and seasonality to construct an exposure–response relationship. We observed a nonlinear relationship between increasing air pollution and bicycle ridership. This study method can be used as a basis for similar analyses to investigate BSS policies in other cities. Full article

Designing or expanding a bicycle-sharing system (BSS) involves addressing the infrastructure’s location of the bicycle stations. Station location is an essential factor for designing and implementing a new system or for its operation. In a complex spatial optimization context, geographic information systems (GIS) can support this decision problem. There are also numerous ways of subdividing the broad spectrum of location-allocation models used in previous studies. However, a station location comprehensive review and systematization with the specific aim of characterizing the state of the art of BSS is missing. The present research aimed to provide a comprehensive systematization for station location problems, criteria, and techniques, seeking to identify the current state of practice. We searched scientific publication databases to collect relevant publications—the final list comprised 24 papers for the literature review. The systematization addresses the two major problems concerning bicycle station location: initial network design and operation improvement (where changes in operating a BSS are implemented). Based on the literature, we propose a set of four main criteria for choosing appropriate places for bike stations (or parking) in a city: “bike network”, “operator”, “user”, and “city infrastructure”. The sub-criteria mentioned in the literature are categorized based on the proposed classification and new sub-criteria are suggested. We also group location modeling techniques into three categories: “mathematical algorithms”, “multi-criteria decision making”, and “GIS”. Combining GIS and multi-criteria decision making (MCDM) has received more attention in recent years to locate bike stations, evaluate their operating performance, and have more accurate and practical results. Full article

Bicycle sharing systems (BSSs) have been implemented in cities worldwide in an attempt to promote cycling. Despite exhibiting characteristics considered to be barriers to cycling, such as hot summers, hilliness and car-oriented infrastructure, Southern European island cities and tourist destinations Limassol (Cyprus), Las Palmas de Gran Canaria (Canary Islands, Spain) and the Valletta conurbation (Malta) are all experiencing the implementation of BSSs and policies to promote cycling. In this study, a year of trip data and secondary datasets are used to analyze dock-based BSS usage in the three case-study cities. How land use, socio-economic, network and temporal factors influence BSS use at station locations, both as an origin and as a destination, was examined using bivariate correlation analysis and through the development of linear mixed models for each case study. Bivariate correlations showed significant positive associations with the number of cafes and restaurants, vicinity to the beach or promenade and the percentage of foreign population at the BSS station locations in all cities. A positive relation with cycling infrastructure was evident in Limassol and Las Palmas de Gran Canaria, but not in Malta, as no cycling infrastructure is present in the island’s conurbation, where the BSS is primarily operational. Elevation had a negative association with BSS use in all three cities. In Limassol and Malta, where seasonality in weather patterns is strongest, a negative effect of rainfall and a positive effect of higher temperature were observed. Although there was a positive association between BSS use and the number of visiting tourists in Limassol and Malta, this is predominantly explained through the multi-collinearity with weather factors rather than by intensive use of the BSS by tourists. The linear mixed models showed more fine-grained results and explained differences in BSS use at stations, including differences for station use as an origin and as a destination. The insights from the correlation analysis and linear mixed models can be used to inform policies promoting cycling and BSS use and support sustainable mobility policies in the case-study cities and cities with similar characteristics. Full article

Recent strategies to improve the performance of the cycling mode of transport are based on infrastructural, behavioral, and multimodal measures, which are related to the concept of bikeability. A literature review on “bikeability indexes” was conducted focusing on indicators, using a four-step systematic process. Fourteen studies were included for the final analysis and provided 138 indicators, 17 criteria, and four domains. The exploratory analysis evidenced limited application of indicators related to pollution, scarce use of indicators related to bicycle sharing systems (BSS), absence of indicators related to electric bicycles, lack of indicators related to digital solutions, and the need of a calibration and validation process for bikeability indexes. Considering the changes and opportunities created by emerging innovations (namely BSS and electric bicycles) and the health trade-off related to pollution reduction, this research reveals that the current bikeability indexes do not fully address the real potential of a cycle network, limiting its use as a comprehensive tool for the promotion of sustainable mobility. Full article

Bicycle Sharing Systems (BSSs) are exponentially increasing in the urban mobility sector. They are traditionally conceived as a last-mile complement to the public transport system. In this paper, we demonstrate that BSSs can be seen as a public transport system in their own right. To do so, we build a mathematical framework for the classification of BSS trips. Using trajectory information, we create the trip index, which characterizes the intrinsic purpose of the use of BSS as transport or leisure. The construction of the trip index required a specific analysis of the BSS shortest path, which cannot be directly calculated from the topology of the network given that cyclists can find shortcuts through traffic lights, pedestrian crossings, etc. to reduce the overall traveled distance. Adding a layer of complication to the problem, these shortcuts have a non-trivial existence in terms of being intermittent, or short lived. We applied the proposed methodology to empirical data from BiciMAD, the public BSS in Madrid (Spain). The obtained results show that the trip index correctly determines transport and leisure categories, which exhibit distinct statistical and operational features. Finally, we inferred the underlying BSS public transport network and show the fundamental trajectories traveled by users. Based on this analysis, we conclude that $90.60\%$ of BiciMAD’s use fall in the category of transport, which demonstrates our first statement. Full article

Bicycle sharing systems (BSSs) have established a new shared-economy mobility model. After a rapid growth they are evolving into a fully-functional mobile sensor platform for cities. The viability of BSSs is floored by their operational costs, mainly due to rebalancing operations. Rebalancing implies transporting bicycles to and from docking stations in order to guarantee the service. Rebalancing performs clustering to group docking stations by behaviour and proximity. In this paper we propose a Hierarchical Agglomerative Clustering based on an Ultra-Light Edge Computing Algorithm (HAC-ULECA). We eliminate the proximity and let Hierarchical Agglomerative Clustering (HAC) focus on behaviour. Behaviour is represented by ULECA as an activity profile based on the net flow of arrivals and departures in a docking station. This drastically reduces the computing requirements which allows ULECA to run as an edge computing functionality embedded into the physical layer of the Internet of Shared Bikes (IoSB) architecture. We have applied HAC-ULECA to real data from BiciMAD, the public BSS in Madrid (Spain). Our results, presented as dendograms, graphs, geographical maps, and colour maps, show that HAC-ULECA is capable of separating behaviour profiles related to business and residential areas and extracting meaningful spatio-temporal information about the BSS and the city’s mobility. Full article

Bike-sharing is widely recognized as an eco-friendly mode of transportation and seen as one of the solutions to the problem of air pollution and congestion. As there is little research exploring the performance of bicycle-sharing systems (BSS), many municipal authorities invest in their development without knowledge of their effectiveness. Therefore, the aim of this article is to identify factors that correlate with BSS performance. Data related to BSS and urban characteristics were collected for the 56 cities in Poland, which is the population of BSS systems in this country. The Ordinary Least Square regression model was used to estimate the model. Additionally, to support our findings, a survey of 3631 cyclists was conducted. Our main findings show that BSS performance was positively related to cities’ population, tourism, number of bike stations per capita, congestion, bicycle pathways’ length and higher temperature, and negatively related to precipitation. We have also found that one BSS operator was more effective compared to the others. Full article

The Bicycle-sharing System (BSS) has been globally adopted as a sustainable transportation system that helps improve air pollution, public health and traffic congestion. The increased usage of BSSs requires an increased number of rebalancing trucks to distribute bikes throughout the city. Operating rebalancing trucks is an expensive venture that requires intensive manpower that is dependent on traffic congestion. In this background, a user participation-based rebalancing service was introduced to solve the problem, but it was difficult to test the impact of the service and the estimated cost in the city. Thus, this research proposes a simulation system that tests user participation-based rebalancing services with different user parameters such as the amount of incentives, the user participation rate and extra walking distances. We conducted an incentive survey on actual BSS users to determine the accurate values of these parameters. We also identified that, among the three parameters, extra walking distance is the most influential element on which to improve the rebalance imbalance metric. We found that the incentive coefficient is an important variable in determining the estimated cost of the service. Thus, any city can utilize the proposed system to design a user participation-based rebalancing service that is suitable for their city. Full article

A highly debatable issue is whether or not a paradigm shift toward the sharing economy could help to address the economic, social and environmental challenges of our time. This article contributes to the academic discussion by exploring the types of value created by sharing organisations and the strategies they use to institutionalise themselves in relation to powerful institutions. The study applies two analytical frameworks, based on value creation and institutional strategies, to three empirical case studies of bicycle sharing systems (BSS) in Barcelona. Rich data was collected from a variety of primary and secondary sources, including a field visit to Barcelona, interviews with representatives of the three bicycle sharing systems, observations and literature analysis. We found that the environmental value these organisations create is closely interlinked with the social value they produce and that these values outweigh negative impacts of their operations. All case organisations employ regulative, normative and cultural-cognitive strategies for their institutionalisation but are also subject to powerful institutions beyond their individual control. We recommend that entrepreneurs, city officials, the public and other stakeholders engage in collaborative and open development processes to shape the emerging sharing economy alongside the institutional work of sharing organisations. Full article