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This study establishes a network data envelopment analysis (DEA) model to evaluate the sustainability of public transportation services targeting rapid routes for buses in the Seoul metropolitan area. A network DEA-based optimization model is formulated to evaluate the sustainability of the public transportation service. By considering public transportation services from both the operators’ and users’ perspectives, this model produces results that reflect the interaction of three sustainable transport service properties, i.e., efficiency, equity, and environmental impacts. It is identified that the expansion of median bus lanes and the conversion of conventional buses into compressed natural gas vehicles could improve the sustainability of the public transportation services in the Seoul metropolitan area. Some limitations and future research agenda also are presented. [ABSTRACT FROM PUBLISHER]

Public transportation has been regarded as one of the most sustainable forms of transport, because of which local governments have put efforts in increasing the mode share of public transportation. Recently, not only level of service but also user satisfaction has been focused on for the assessment of transport policy; however, several points have been overlooked in previous research, such as attribute-based satisfaction, the relationship between level of service and satisfaction, and user expectation. This paper deals with these issues while assuming the heterogeneity of satisfaction, which is an indicator of perception. Out-of-vehicle times, particularly headway and access time, were selected in the analysis because they can affect travel behavior of current and potential public transportation customers. In this analysis, pattern-recognition models were applied, and public transportation users were segmented in terms of perception. The results suggest several notable recommendations for public transport policies and investigations. [ABSTRACT FROM AUTHOR]

The public bike system (PBS) has been actively promoted worldwide for the last decade. This study tried to find out policy strategies for sustainable PBS implementation targeting on the city that is under consideration of introducing bike sharing scheme. For this, the authors considered some psychological factors that may make impacts on PBS user's attitudes and hypothesized especially that individual environmental concern refers to an attitude toward environmental issues, influence an increase of their perceived value of PBS. The Norm Activation Model (NAM) is used to measure the public's environmental concern incorporating norm activation. In addition, willingness to pay (WTP) method is adopted to investigate the value of PBS individuals. Structural equation modeling (SEM) revealed that environmental concern influenced people's perception of the value of PBS. Furthermore, the positive correlation between environmental concern and awareness of consequences on cycling is observed. The study verifies how people perceive the value of a bike sharing system and how often people using a bicycle are dependent on their environmental concern. In conclusion, authors discuss how PBS could be promoted sustainably by suggesting policy strategies to enhance the perceived value of PBS and to increase bicycle use. [ABSTRACT FROM AUTHOR]

In order to improve the effectiveness of transit-oriented development (TOD), the integration of public transportation and bikes has been regarded as a good alternative because the catchment area of a station, that is, the spatial extent of TOD, can be increased. This paper suggests the concept of bicycle-based TOD (B-TOD) and estimates the spatial extent, considering the catchment area. For this, a trip survey was conducted among bicycle users who used bicycle and public transportation in Seoul metropolitan and Daejeon metropolitan areas in Korea. Regression and cumulative distribution models were used to estimate the spatial extent of B-TOD. The results show that the estimated access distances were 1.96 km and 2.13 km for origin (home)-to-station and station-to-work trips, respectively, and they can play a yardstick role in the TOD planning practices in Korea. In such cases, the catchment areas of B-TOD cover 73.7% and 93.6% of the whole area of Seoul, whereas conventional walking-only TOD can cover only 29.9% of the same. This implies that B-TOD can help to solve one of the key inherent weaknesses of the conventional TOD. Some limitations and recommendations for future research are also discussed. [ABSTRACT FROM AUTHOR]

This article focuses on micro-level walkability, which is measured at the route level and thus named “path walkability,” and tests whether path walkability influences transit users' mode choices to the station. To test its impact on access mode choices, a case study is conducted in downtown Mountain View, California. A station user survey is administered to collect access mode choice, socioeconomic status, and trip origins and walking routes of 249 transit users with previous experience of walking to the station. Using a path walkability measurement instrument developed for this research, 38 path walkability indicators are extracted from each of the 249 walking routes. The 38 walkability indicators are grouped by using factor analysis yielding four path walkability factors: “sidewalk amenities,” “traffic impacts,” “street scale and enclosure,” and “landscaping elements.” The four factors are utilized as new walkability variables for modeling access mode choices. With 150 walkers and 99 habitual auto users/occasional walkers, two access mode choice models are estimated. The basic model is first estimated without walkability variables and then the four path walkability variables are introduced for the expanded model. All four path walkability variables enter the expanded model and significantly improve the predictability of the mode choice model. The model result suggests that micro-level walkability influences access mode choices in a statistically significant way and having more walking-conducive walkability available for access trips increases the chance of choosing walking over driving. This research shows that improving micro-level walkability could be a cost-beneficial incentive for more walking to the station. [ABSTRACT FROM PUBLISHER]

Highlights: [•] We model spatial regressions to examine the determinant factors of rail transit ridership. [•] Rail transit service coverage of 500m gives the best fit for estimating rail transit ridership levels. [•] Development density is positively associated with rail transit ridership within 750m service coverage. [•] Land use diversity does not show a significant association with rail transit ridership. [•] Station-level accessibility measures are the most important factors for promoting rail transit ridership. [Copyright &y& Elsevier]

Distinguishing commuters from non-commuters is important for transportation planning and traffic demand management. A framework to identify commuters using public transit is proposed based on a spatial-temporal clustering algorithm. The framework extracts commute trips by mining spatial-temporal travel patterns depending on whether the travelers' trip chains are complete. The commuting features in terms of travel frequency, time regularity, and spatial regularity are utilized to compare the difference in travel behavior between commuters and non-commuters. The framework is applied to trip data collected from an incentive program implemented by the Metropolitan Transport Commission of Korea. The data records spatial and temporal information on travelers' boarding and alighting points, as well as actual origins and destinations. One trip record constitutes a complete trip chain for travelers who joined the incentive program. The results show that commuters exhibit a higher travel frequency and more regular spatial-temporal travel patterns than non-commuters. It is found that not all commuters travel during morning and evening peaks; some commuters leave work after evening peak. The proposed identification framework based on the spatial-temporal clustering approach is capable of exploiting the inherent spatial-temporal travel patterns of travelers to achieve a reliable identification of commuters. [ABSTRACT FROM AUTHOR]