• International Journal of Highway Engineering
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• v.16 no.1
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• pp.63-73
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• 2014

PURPOSES : The aim of this study is to analyze economic effect of bike-sharing after its introduction in Korea. METHODS : This study reviews current bike-sharing situations in Korea and other nations. We conduct surveys on bike-sharing system's bike usage patterns and economic benefits in Changwon and Goyang cities where public bikes are the most popular in the nation. Economic benefits are itemized after reviewing relevant previous studies. Then, the survey is implemented using the Contingent Valuation Method (CVM). Then estimated benefit is compared to the cost which is necessary for bike-sharing introduction and operation. RESULTS : Using the average WTP per household, the total economic benefit of bike-sharing is estimated as much as 1.75 billion KRW to 3.75 billion KRW in Goyang and Changwon city. Using estimated benefit, economic effect of bike-sharing are calculated as 0.69 and 1.00, respectively. CONCLUSIONS : The result of this study shows bike-sharing could be useful economic policy in Korea. However, economic effect of bike-sharing differs by city.

• Asia pacific journal of information systems
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• v.29 no.3
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• pp.414-427
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• 2019

The sharing economy has significantly changed the way of living for years. The emergence and expansion of sharing economy empowered by the mobile information technologies and intellectual algorithms reconfigure how people use transportation means. In this paper, the bike sharing phenomenon is highlighted. Combining a big data set provided by the Seoul government about user logs and air quality data set, the empirical findings reveal that temperature change is tightly associated bike sharing activities. Also, the concentration of particulate matter is weakly related to bike sharing, but the trend should be carefully examined. By considering external environmental factors to bike sharing businesses, this work is differentiated. To further understand empirical data, data mining methods and econometric approaches were adopted.

• The Journal of the Korea Contents Association
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• v.21 no.7
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• pp.259-270
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• 2021

Recently, interests in the use of Sharing Bike is increasing in consideration of eco-friendly transportation and safety from viruses. As the technology for collecting and storing data is improved with the development of ICTs, research on mobility using the Sharing Bike Data is also actively progressing. Therefore, this paper analyzes the properties of Sharing Bike Data and cases of researches on it through literature review, and based on the results of the review, data of Eoulling, the Sharing Bike System of Sejong City is analyzed as a way to utilize Sharing Bike Data. Most of the selected literature used structured data, and analyzed it through statistical methods or data mining. Through data analysis, it identified the current status, found out problems of the Sharing Bike System, proposed a solution to solve them, developed plans to activate the use of Sharing Bike. This provides basic data for efficient management and operation plans for Sharing Bike System. Ultimately, it will be possible to explore ways to improve mobility in urban spaces by utilizing Sharing Bike Data.

• ETRI Journal
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• v.44 no.2
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• pp.244-259
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• 2022

Bicycle- or bike-sharing systems (BSSs) have received increasing attention as a secondary transportation mode due to their advantages, for example, accessibility, prevention of air pollution, and health promotion. However, in BSSs, due to bias in bike demands, the bike rebalancing problem should be solved. Various methods have been proposed to solve this problem; however, it is difficult to apply such methods to small cities because bike demand is sparse, and there are many practical issues to solve. Thus, we propose a demand prediction model using multiple classifiers, time grouping, categorization, weather analysis, and station correlation information. In addition, we analyze real-world relocation data by relocation managers and propose a relocation algorithm based on the analytical results to solve the bike rebalancing problem. The proposed system is compared experimentally with the results obtained by the real relocation managers.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.34 no.5
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• pp.1517-1524
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• 2014

In recent years, the interest of environmental-friendly transportation modes has been growing. This is because of social and environmental problems such as increasing gas price and climate change. In Europe, bike-sharing service, one of the environmental-friendly transportation modes, has been already operated. Bike-sharing service named "Tashu" has been operated in Daejeon city since 2009. This study is a fundamental research to increase utilization efficiency of bike-sharing service and to decide optimal locations of bike stations. In addition this study examines characteristics of bike usage and analyzes factors affecting to demands using multiple regression model. Based on the result of examining of characteristics of bike usage, the rate of bike usage is higher compared with installation rate of public bike stations near parks in Daejeon. In addition demands of bike usage in weekend is higher than in weekday. It reveals that the main purpose of bike usage could be recreational activities. The return rate at the same location with rental station is comparatively high. Moreover, bike usage pattern is biased in specific areas (Dunsan and Yuseong) because bike-sharing stations are not equally located. As a result of multiple regression model, the factors affecting to demands are number of passengers in buses, length of bike lanes, parks, distance to waterfront, and rate of young people. A statistical significance of factors (r-square) is 0.748, which has strong relationship.

• Journal of Digital Convergence
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• v.18 no.7
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• pp.167-175
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• 2020

With the recent revitalization of the shared economy, bike-sharing services are gaining huge popularity in the bicycle sector. Bike-sharing services are characterized by reducing environmental pollution and borrowing bicycles at low prices. This study investigated the mechanisms for the formation of customer's continuance intention toward bike-sharing services. The theoretical framework clarified the role of perceived value and trust in enhancing customer's continuance intention. Perceived usefulness, perceived ease of use and perceived enjoyment are considered as the vital factors of enhancing perceived value and trust in a service provider. The research model was validated by data from 217 bike-sharing users in China. Both perceived value and trust in a service provider had a significant impact on user's continuance intention. However, the analysis results showed that perceived usefulness does not have a significant impact on both perceived value and trust in a service provider. Perceived ease of use and perceived enjoyment played a significant role in enhancing both perceived value and trust in a service provider. Our results are expected to provide academic and practical implications for bike-sharing services.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.43 no.3
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• pp.353-362
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• 2023

In this research, the usage status and characteristics of user big data of Mobike, a dockless bike sharing service introduced in Suwon city, were analyzed, and multiple regression analysis was performed to identify factors influencing the demand for dockless bike sharing service. For analysis, usage data of bike sharing system in Suwon city in 2019 were obtained, and they were organized by areas. As a result of analyzing the characteristics of the influencing factors selected for each area, it was found that the extension of bicycle roads shows high in areas with high demand for bicycles or adjacent areas. Also, the population of 10-30's shows high in areas with high demand for bicycles or adjacent areas. In addition, it was analyzed that the use of bike sharing system is high in areas with high maintenance rate of bicycle roads and large-scale residential and commercial facilities near residential districts and adjacent areas. As a result of the multiple regression analysis, it is analyzed that length of bicycle·pedestrian roads (non-separated), population of 10-30's, number of railway stations, number of schools, number of commercial facilities, number of industrial facilities factors were significant. It is expected that it may be possible to create an environment in which citizens want to use dockless bike sharing service by identifying factors affecting the number of stationless shared bicycles. Also, the results of data analysis are considered to be contributing to policy data to promote the use of dockless bike sharing.

• Journal of the Korean Operations Research and Management Science Society
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• v.41 no.1
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• pp.41-53
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• 2016

Static repositioning is a well-known and commonly used strategy to maximize customer satisfaction in public bike-sharing systems. Repositioning is performed by trucks at night when no customers are in the system. In models that represent the static repositioning problem, the decision variables are truck routes and the number of bikes to pick up and deliver at each rental station. To simplify the problem, the decision on the number of bikes to pick up and deliver is implicitly included in the truck routes. Two relocation-based local search algorithms (1-relocate and 2-relocate) with the best-accept strategy are incorporated into a variable neighborhood search (VNS) to obtain high-quality solutions for the problem. The performances of the VNS algorithm with the effect of local search algorithms and shaking strength are evaluated with data on Tashu public bike-sharing system operating in Daejeon, Korea. Experiments show that VNS based on the sequential execution of two local search algorithms generates good, reliable solutions.

• Journal of Korean Society of Transportation
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• v.34 no.5
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• pp.394-408
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• 2016

This study aims to study the impact of weather conditions and locational characteristics of bike stations on the usage of public bike sharing system for efficient deployment and operation of public bike systems. Linear regression analysis is used to estimate the usage of public bikes of Goyang city. The statistical analysis shows that the usage rate increases with average temperature and decreases under high wind (over 7m/s) or high temperature (over $29^{\circ}$) condition. The usage rate of public bike sharing system can be differentiated by locational characteristics of bike station such as residential area, commercial area, park, school, and metro station. The usage rate increases in park and commercial areas from 10 AM to 3 PM, while it increases in school areas from 3 PM to 5 PM. Public bikes are highly used near the metro station from 5 PM to 8 PM. The stations in parks are highly used in late night, and the usage rate in CBD area increases after the midnight.

• Journal of Internet Computing and Services
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• v.24 no.5
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• pp.107-120
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• 2023

The public bicycle of Seoul, Ttareungyi, was launched at October 2015 to reduce traffic and carbon emissions in downtown Seoul and now, 2023 Oct, the cumulative number of user is upto 4 million and the number of bike is about 43,000 with about 2700 stations. However, super growth of Ttareungyi has caused the several problems, especially demand/supply mismatch, and thus the Seoul citizen has been complained about out of stock. In this point, this study conducted a real time demand forecasting model to prevent stock out bike at stations. To develop the model, the research team gathered the rental·return transaction data of 20,000 bikes in whole 1600 stations for 2019 year and then analyzed bike usage, user behavior, bike stations, and so on. The forecasting model using machine learning is developed to predict the amount of rental/return on each bike station every hour through daily learning with the recent 90 days data with the weather information. The model is validated with MAE and RMSE of bike stations, and tested as a prototype service on the Seoul Bike Management System(Mobile App) for the relocation team of Seoul City.