Showing papers in "Transportation Research Part A-policy and Practice in 2018"
TL;DR: In this paper, the authors identified and mapped the motivators and barriers for the diffusion of electric mobility through three levels of decision-making: Formal Social Units, Collective Decision-making Units, and Individual Units.
Abstract: European Union’s (EU) long-term objective of achieving a competitive low carbon economy is mainly based on enabling environmentally sustainable investments, particularly in terms of decreasing energy consumption in buildings, transition to electric vehicles, and developing smart electricity networks, while promoting renewable energy use in order to reduce greenhouse gas (GHG) emissions by at least 80% by 2050 compared to 1990 levels. Since, transport is one of the main sector responsible for EU’s emissions; diffusion of Electric Vehicles (EVs) could allow immense reduction. Therefore, since the announcement of 2050 Roadmap in 2009, there has been a great increase in studies exploring the viability of transition to e-mobility in a Europe-wide context, identifying common factors and variables. However, it is usually not that straightforward when decision makers seek to transform these variables into policy implications that will actually help to achieve the EU goals on energy transition. At this point, the motivators and barriers are of utmost importance. Accordingly, this study is based on an extensive and up-to-date review of the existing literature on e-mobility in Europe, with the main aim of identifying and mapping the motivators and barriers for the diffusion of electric mobility through three levels of decision-making: Formal Social Units, Collective Decision-Making Units, and Individual Units. Results of the analysis identifies that the main barriers are lack of charging infrastructure; economic restrictions and cost concerns; technical and operational restrictions; lack of trust; information and knowledge; limited supply of electricity and raw materials; and practicability concerns. Thus, key motivators appear to be environmental, economic and technical benefits associated with EVs, as well as personal and demographic factors.
202 citations
TL;DR: The results show that the integrated system has the potential of enhancing service quality, occupying fewer road resources, being financially sustainable, and utilizing bus services more efficiently.
Abstract: This paper proposes and simulates an integrated autonomous vehicle (AV) and public transportation (PT) system. After discussing the attributes of and the interaction among the prospective stakeholders in the system, we identify opportunities for synergy between AVs and the PT system based on Singapore’s organizational structure and demand characteristics. Envisioning an integrated system in the context of the first-mile problem during morning peak hours, we propose to preserve high demand bus routes while repurposing low-demand bus routes and using shared AVs as an alternative. An agent-based supply-side simulation is built to assess the performance of the proposed service in fifty-two scenarios with different fleet sizes and ridesharing preferences. Under a set of assumptions on AV operation costs and dispatching algorithms, the results show that the integrated system has the potential of enhancing service quality, occupying fewer road resources, being financially sustainable, and utilizing bus services more efficiently.
198 citations
TL;DR: It is found that gradient boosting decision trees have a stronger effect on weekdays than on weekends, and they show salient non-linear effects on driving distance in both models, challenging the linearity assumption commonly adopted in the literature.
Abstract: Although many studies have explored the relationship between the built environment and travel behavior, the literature offers limited evidence about the collective influence of built environment attributes, and their non-linear effects on travel. This study innovatively adopts gradient boosting decision trees to fill the gaps. Using data from Oslo, we apply this method to the data on both weekdays and weekends to illustrate the differential effects of built environment characteristics on driving distance. We found that they have a stronger effect on weekdays than on weekends. On weekdays, their collective influence is larger than that of demographics. Furthermore, they show salient non-linear effects on driving distance in both models, challenging the linearity assumption commonly adopted in the literature. This study also identifies effective ranges of distance to different centers and population density, and highlights the important role of sub-centers in driving reduction.
183 citations
TL;DR: A stated choice survey of 252 individuals administered via a face-to-face method is conducted in Sydney, Australia and a state-of-the-art preference model is estimated to address the research questions as mentioned in this paper.
Abstract: Mobility as a Service (MaaS), which uses a digital platform to bring all modes of travel into a single on-demand service, has received great attention and research interest Different business models have emerged in which travellers can either pre-pay for their mobility services bundled into a MaaS plan, or pay-as-they-go using a smart app linked to the service This study aims to understand how large the potential market of MaaS would be if travellers are offered this one-stop access to a range of mobility services, and how much potential users might value each item included in a MaaS plan A stated choice survey of 252 individuals administered via a face-to-face method is conducted in Sydney, Australia and a state of the art preference model is estimated to address the research questions Results indicate that almost half of the sampled respondents would take MaaS offerings, and the potential uptake levels vary significantly across population segments, with infrequent car users being the most likely adopters, and car non-users the least On average, Sydney travellers are willing to pay $640 for an hour of access to car-share, with one-way car-share valued more than station-based car-share Estimated willingness-to-pay for unlimited use of public transport is $590 per day which is much lower than the current daily cap These findings suggest a careful segmentation of the market and a cross-subsidy strategy is likely to be required by MaaS suppliers to obtain a commercially viable uptake level
159 citations
TL;DR: Zhang et al. as discussed by the authors analyzed the effects of consumer's knowledge about EVs, perceived risk, perceived usefulness and current financial incentive policies on consumer's intention to adopt EVs using an extended technology acceptance model.
Abstract: Electric vehicles (EVs) have been regarded as one of the most promising green technologies to reduce carbon emissions and energy consumption from the transport sector. Understanding and exploring the factors that affect consumer’s intention to adopt EVs is important. The main purpose of this research is to analyze the effects of consumer’s knowledge about EVs, perceived risk, perceived usefulness and current financial incentive policies on consumer’s intention to adopt EVs using an extended technology acceptance model. The model is empirically tested using questionnaire survey data collected from 320 consumers in China. The results shown that consumer’s knowledge about EVs is positively and significantly related to perceived usefulness, attitude and intention to adopt EVs, but negatively and significantly related to perceived risk. Perceived risk negatively affects perceived usefulness, attitude and intention to adopt EVs. Meanwhile, perceived usefulness has a positive effect on adoption intention and attitude, and attitude is also positively related to the intention to adopt EVs. However, the results also indicate that the financial incentive policy has no significant effect on intention to adopt EVs. In addition, the results also find that consumers lacking of knowledge about EVs and perceiving high risk of EVs could be the psychological barriers to their acceptance of EVs. Based on the results, policy implications for increasing the adoption of EVs and suggestions for future research are discussed.
154 citations
TL;DR: Wang et al. as mentioned in this paper investigated the impact of HSR on the economic geography of China and found that HSR has improved the accessibility of Chinese cities by 12.11% at the national level from 2009 to 2013.
Abstract: The rapidly expanding high-speed rail (HSR) network in China has produced and will continue to produce a progressive contraction of space by significantly shortening the rail travel time among major Chinese cities. Does economic growth follow the extension of HSR as a result of improved accessibility? This study investigates the impact of HSR on the economic geography of China. We find that HSR has improved the accessibility (as measured by weighted average travel time) of Chinese cities by 12.11% at the national level from 2009 to 2013. However, the accessibility benefit of HSR is not distributed evenly over space. Cities in the wealthy eastern region and with HSR access enjoy higher accessibility benefit compared with cities in the hinterland and without direct HSR access. Using a difference-in-differences analysis and an instrumental variable strategy to address the non-random placement of HSR stations, we also find that on average, HSR cities have experienced a significant increase in fixed asset investment after the inauguration of HSR service, which could stimulate future economic growth. The treatment effect of HSR on investment varies with city size. Second-tier cities with relatively large population bases benefit more from HSR in attracting investment compared with small cities and mega cities, which could experience marginal or negative investment growth.
143 citations
TL;DR: There is a need to embed ethical implication as a construct for user trust leading to user acceptance model in future studies, according to the researcher who proposes that ethical implication can be an important element of user trust toward autonomous technology.
Abstract: The autonomous vehicle innovation has a potential effect on traffic and it’s a widespread issue in the academic municipal. Based on its feature, autonomous vehicle is expected to improve traffic flow, reduce accidents, reduce social exclusion and improve the utility of time on travel. It is increasingly accepted that the next step to the evolution of human transportation is the replacement of human as the driver by the Artificial-intelligence-capable machine. Regardless, the challenges remain especially in convincing the consumers to switch to autonomous cars despite the apparent benefits. In the past, papers highlighted individual trust toward machine as the key point to encourage acceptance of autonomous cars. This paper seeks to highlight the ethical implications of the autonomous technology and how it is related to the user acceptance of the technology. This paper reviewed recent studies on the ethical implications of the autonomous vehicle and the user acceptance of the technology. A systematic review of papers from the literature was done using Scopus, ISI and Web of Science. The results of the review have shown that the level of trust, which may vary on the sociodemographic profile of the users, has been studied as one of the factors for user acceptance. Many researchers also highlight ethical implication as an important aspect of autonomous technology that needs to be tended to. The researcher proposes that ethical implication can be an important element of user trust toward autonomous technology. Hence, there is a need to embed ethical implication as a construct for user trust leading to user acceptance model in future studies. In the line of this research review researcher was addressed the following comprehensive groups: examination of autonomous vehicle topographies and flexibility prototypes, consequences for street traffic and connectivity to substructure (specifically in the urban areas with the medium and low density), communal attitudes and apprehensions, transportable behaviour and plea, possible business models, and strategy implications. Lastly, the main objective of this research article is to recognise critical problems for the growth of an effort cluster investigation to comprehend attitudes of possible manipulators of AVs and to highpoint autonomous vehicle growth issues for Malaysian lawful agencies.
123 citations
TL;DR: In this paper, the effects of land-use and built environment vary across different population segments in the United States, including younger Millennials, Gen Xers, and Baby Boomers.
Abstract: There is a growing literature on the changing travel patterns in the United States. The changes are largely driven by the emerging shared-mobility services and the travel behavior of the younger generations. This study builds on an investigation of Millennials’, Gen Xers’ and Baby Boomers’ bike sharing ridership in New York City. This study examines station-level bike share use focusing on whether and how the effects of land-use and built environment vary across different population segments. Using New York’s Citi Bike system data, we develop zero-inflated negative binominal models to estimate hourly trip productions at stations for five age cohorts: younger Millennials (born 1995 to 2000), mid Millennials (1989 to 1994), older Millennials (born 1979 to 1988), Generation Xers (born 1965 to 1978), and Baby Boomers (born 1946 to 1964). Consistent with the literature, our results suggest that weather related variables, land-use and built environment characteristics have significant effects on the overall bike sharing usage. Our findings also reveal variations across age cohorts. For example, intersection density is positively related to younger Millennials’ bike share trip production. However, this factor is not statistically significant for other age groups. Our findings provide valuable insights for planners and policy-makers, and set the basis for improving the understanding of cohort differences in bike sharing demand.
120 citations
TL;DR: In this article, the authors investigated NEV policies that were launched by China's national, provincial, and municipal authorities from 2010 to 2016 in terms of their similarities and differences, as well as their successes and failures.
Abstract: Environmental impact and climate change urge governments across the globe to prioritize to the development of new energy vehicles (NEVs). Since 2010, the Chinese government has introduced numerous policies to accelerate the development of the NEV industry. These policies have various effects on NEVs due to several complex factors, such as timing, regional economies, and other demands on the government’s attention. This paper investigates NEV policies that were launched by China’s national, provincial, and municipal authorities from 2010 to 2016 in terms of their similarities and differences, as well as their successes and failures. By doing so, we trace the evolution of Chinese NEV policies and compare them, in order to advise on the policies that are most beneficial to the future development of the Chinese NEV industry. The main results are as follows: (1) the implementation of NEV policies consisted of a “plan-pilot-promotion-subsidy-development” process; (2) the coordination mechanisms of central and local governments should be strengthened; (3) future policies should focus on infrastructure construction, research and development (R&D), the recycling of batteries, and private purchase regulations. This paper contributes to policy-making in Chinese NEV industry.
114 citations
TL;DR: In this paper, the authors applied the generalized ordered logistic regression approach and examined how the mode, duration, purpose, and companionship characteristics of a trip shape six different emotions during the trip, including happy, meaningful, tired, stressful, sad, and pain.
Abstract: Positive emotions have long-lasting benefits for human development. Understanding the connections between daily travel behavior and emotional well-being will not only help transportation practitioners identify concrete strategies to improve user experiences of transportation services, but also help health practitioners to identify innovative solutions for improving public health. Prior research on the subject had focused on limited travel behavior dimensions such as travel mode and/or travel duration. Other dimensions such as travel purpose and travel companionship have received limited attention. Using data from the 2012–2013 American Time Use Survey, this paper applied the generalized ordered logistic regression approach and examined how the mode, duration, purpose, and companionship characteristics of a trip shape six different emotions during the trip, including happy, meaningful, tired, stressful, sad, and pain. After controlling for personal demographics, health conditions, and residential locations, we find that biking is the happiest mode; public transit is the least happy and least meaningful; and utilitarian walking for transportation is associated with all four negative emotions. Trip duration has a negative association with happiness and a positive association with stress. Travel for discretionary purposes such as leisure, exercise, and community activities is generally associated with higher levels of positive emotions and lower levels of negative emotions than travel for work or household maintenance. Trips with eating and drinking purposes appear to be the happiest and trips with the purpose of spiritual and/or volunteering activities appear to be the most meaningful. Travel with family especially children or travel with friends is happier and more meaningful than travel alone. Transportation planners in the U.S. are recommended to promote biking behavior, improve transit user experiences, and implement spatial planning strategies for creating a built environment conducive to shorter trips, more discretionary trips, and more joint trips with family and friends.
110 citations
TL;DR: A data-driven Bayesian Network (BN) based approach is proposed to analyse risk factors influencing PSC inspections, and predict the probability of vessel detention, which effectively help port authorities to rationalise their inspection regulations as well as allocation of the resources.
Abstract: In the past decades, maritime transportation not only contributes to economic prosperity, but also renders many threats to the industry, causing huge casualties and losses. As a result, various maritime safety measures have been developed, including Port State Control (PSC) inspections. In this paper, we propose a data-driven Bayesian Network (BN) based approach to analyse risk factors influencing PSC inspections, and predict the probability of vessel detention. To do so, inspection data of bulk carriers in seven major European countries from 2005 to 2008 1 in Paris MoU is collected to identify the relevant risk factors. Meanwhile, the network structure is constructed via TAN learning and subsequently validated by sensitivity analysis. The results reveal two conclusions: first, the key risk factors influencing PSC inspections include number of deficiencies, type of inspection, Recognised Organisation (RO) and vessel age. Second, the model exploits a novel way to predict the detention probabilities under different situations, which effectively help port authorities to rationalise their inspection regulations as well as allocation of the resources. Further effort will be made to conduct contrastive analysis between ‘Pre-NIR’ period and ‘Post-NIR’ period to test the impact of NIR started in 2008. © 2018 Elsevier Ltd
TL;DR: An overview of good and bad practice for understanding and curbing cost overrun in large capital investment projects is given, with a critique of Love and Ahiaga-Dagbui (2018) as point of departure.
Abstract: This paper gives an overview of good and bad practice for understanding and curbing cost overrun in large capital investment projects, with a critique of Love and Ahiaga-Dagbui (2018) as point of departure. Good practice entails: (a) Consistent definition and measurement of overrun; in contrast to mixing inconsistent baselines, price levels, etc. (b) Data collection that includes all valid and reliable data; as opposed to including idiosyncratically sampled data, data with removed outliers, non-valid data from consultancies, etc. (c) Recognition that cost overrun is systemically fat-tailed; in contrast to understanding overrun in terms of error and randomness. (d) Acknowledgment that the root cause of cost overrun is behavioral bias; in contrast to explanations in terms of scope changes, complexity, etc. (e) De-biasing cost estimates with reference class forecasting or similar methods based in behavioral science; as opposed to conventional methods of estimation, with their century-long track record of inaccuracy and systemic bias. Bad practice is characterized by violating at least one of these five points. Love and Ahiaga-Dagbui violate all five. In so doing, they produce an exceptionally useful and comprehensive catalog of the many pitfalls that exist, and must be avoided, for properly understanding and curbing cost overrun.
TL;DR: Based on China's latest national railway network planning proposal, the connectivity and accessibility indices of China's high speed railway network (CHSRN) in different time periods are computed to evaluate the implications of high-speed rail (HSR) for Chinese cities as mentioned in this paper.
Abstract: Based on China’s latest national railway network planning proposal, the connectivity and accessibility indices of China’s high-speed railway network (CHSRN) in different time periods are computed to evaluate the implications of high-speed rail (HSR) for Chinese cities. An overall index for measuring the connectivity-accessibility of cities on the HSR network is proposed based on three indicators: (a) the Beta index, to reflect the connectivity of the HSR, (b) the number of reachable counties by HSR within the 500-km domain of a city, to reflect the location-based accessibility of the HSR, and (c) the population of the reachable places by HSR within the 500-km domain of a city, to reflect the potential-based accessibility of the HSR. Finally, the differences in the normalized connectivity-accessibility levels of different categories of cities are qualified to measure the impact of China’s future national HSR network on the potential development of cities. It is found that “Mid-to-Long-Term Railway Network Plan (Revised in 2016)”, if fully realized, would profoundly change the HSR connectivity/accessibility of different cities. Most notably, cities in the Yangtze River Delta would suffer the most whereas cities of the central and western regions would gain the most. This could potentially contribute to, or bring about new changes in, the socioeconomic landscapes in China. The methodological contribution of this paper is twofold. Firstly, an overall index to evaluate the comprehensive connectivity and accessibility levels of the HSR network is designed. Secondly, this paper investigates how to qualify the impact of the future HSR network on different tiers of cities in different time periods according to the change of the overall connectivity/accessibility index.
TL;DR: In this article, the authors investigated the impact of transport energy consumption and transport infrastructure on economic growth by utilizing panel data on MENA countries (the Middle East and North Africa region) for the period of 2000-2016.
Abstract: This paper investigates the impact of transport energy consumption and transport infrastructure on economic growth by utilizing panel data on MENA countries (the Middle East and North Africa region) for the period of 2000–2016. The MENA region panel is divided into three sub-groups of countries: GCC panel (containing the Gulf Cooperation Council countries), N-GCC panel (containing countries that are not members of the Gulf Cooperation Council), and North African countries (called MATE—Morocco, Algeria, Tunisia and Egypt). Using the Generalized Method of Moments (GMM), we find that transport energy consumption significantly adds to economic growth in MENA, N-GCC and MATE regions. Transport infrastructure positively contributes to economic growth in all regions. The Dumitrescu-Hurlin panel causality analysis shows the feedback effect of transport energy consumption and transport infrastructure with economic growth. The empirical results add a new dimension to the importance of investing in modern infrastructure that facilitates the use of more energy-efficient modes and alternative technologies that positively affect the economy with minimizing negative externalities.
TL;DR: In this paper, the authors apply a gradient boosting logit model to examine the influences of BE characteristics at both residential and workplace locations and commuting programs (transit/vanpooling subsidies and parking provision) on commute mode choice.
Abstract: Although many studies explore built environment (BE) effects on commuting behavior, most overlook BE characteristics at workplace locations and their non-linear impacts More importantly, limited effort is placed on the integrative effects of the BE and transportation policies Using the data in Washington, DC, this study applies a gradient boosting logit model to examine the influences of BE characteristics at both residential and workplace locations and commuting programs (transit/vanpooling subsidies and parking provision) on commute mode choice We found that BE variables collectively contribute to 65% of the predicting power for mode choice Although workplace BE variables are more important than residential BE elements, the difference is mainly due to distance to CBD (central business district) Furthermore, most variables show non-linear effects on car mode choice There are also synergistic effects between BE variables and parking policy and between BE variables and transit/vanpooling subsidies Therefore, land use policies will be more effective where supportive transportation policies exist
TL;DR: In this article, a hierarchical structure is established to characterize the multidimensional features of public transit services from the passengers' point of view, which might help service providers obtain a systematic picture of public-transit services by measuring overall service performance through sub-dimensional service domains.
Abstract: Understanding passenger loyalty to public transit is important because it is a major determinant of urban and transport sustainability. An integrated framework to investigate loyalty by integrating Satisfaction-Loyalty Theory with Expectation-Confirmation Theory (ECT) is conceptualized and empirically examined in this study. A hierarchical structure is established to characterize the multidimensional features of public transit services from the passengers’ point of view, which might help service providers obtain a systematic picture of public transit services by measuring overall service performance through sub-dimensional service domains. The rationale for developing this comprehensive framework for customer loyalty is justified by the significant relations between constructs, an excellent model fit, the greater share of variance explained for loyalty than that of the model without the two ECT concepts, as well as the difference regarding the confirmation-satisfaction-loyalty paradigm between male and female groups. It is expected to contribute to an improved understanding of customer loyalty in the public transit services context.
TL;DR: In this article, the main differences between two test procedures are identified and their impact on CO2 emissions quantified using the in-house built simulation software CO2MPAS, and the potential total impact on the final reported type-approval CO 2 emissions is assessed.
Abstract: After significant efforts from many parties, the World-wide harmonized Light duty Test Procedure (WLTP) has seen its light first as the UNECE Global Technical Regulation and then as the procedure adopted in the type-approval of light-duty vehicles in Europe. The paper focuses its attention on the main procedural differences between the WLTP and the New European Driving Cycle (NEDC), which is the test-procedure currently used in Europe. In general terms the WLTP appears to be a significant improvement compared to the NEDC. The main differences between two test procedures are identified and their impact on CO2 emissions quantified using the in-house built simulation software CO2MPAS. On the basis of each of these differences, the paper assesses the potential total impact on the final reported type-approval CO2 emissions. The biggest impact on CO2 emissions is coming from the changes in the road load determination procedure (∼10% increase). Procedural changes concerning the test in the laboratory will bring another 8% and post-processing and declaration of results will result in difference of approximately 5% (each). Overall, the WLTP is likely to increase the type-approval CO2 emissions by approximately 25%. Therefore, the WLTP will be able to reduce more than half of the gap identified between the type-approval and real-life figures in Europe. This should be seen as a considerable improvement given the ontological limitations of a laboratory-based test procedure.
TL;DR: This paper quantitatively analyzes statistical topology parameters of Beijing rail transit network (BRTN) based on complex network theory (CNT) and provides recommendations on developing strategies for RTN design and performance evaluation.
Abstract: Rail transit network (RTN) has become the core of urban public transport system. Because RTN’s topological structure has become complicated with its scale, the phenomenon of overload operation frequently appears at stations or lines, reducing the stability of RTN in operation. There is a need to identify the key stations and to analyze the vulnerability of RTN in depth. This paper quantitatively analyzes statistical topology parameters of Beijing rail transit network (BRTN) based on complex network theory (CNT). The key stations are evaluated by different evaluation indicators, such as node degree, betweenness, and strength. Then, a model is proposed to analyze the cascading failures of weighted BRTN considering loading and redistribution of multi-static passenger flow based on coupled map lattices (CML). Results show that when the external perturbation is larger, the time of all stations failure is earlier once the failure is triggered. Moreover, the perturbation threshold for the cascading failure of weighted BRTN is determined. Transfer regularities of the risk stations in BRTN are researched under different combinations of the topological coupling coefficients and the flow coupling coefficients. Under attack, the threshold of loop line damaged is smaller than a straight line. And, while attacking the loop line, the discrete degree of peak time and all station failure time are higher under different perturbations, meaning that failure is hard to control. This study provides recommendations on developing strategies for RTN design and performance evaluation. Future studies will focus on the coordination of weighted complex public transit networks other than passenger flow redistribution within RTN.
TL;DR: In this paper, the authors analyse whether respondents who use their preferred travel mode (i.e., consonant travellers) are more satisfied with their trips compared to respondents travelling with a non-preferred travel mode, i.e. dissonant travellers.
Abstract: Numerous studies have indicated that travel mode choice is affected by travel-related attitudes. A positive stance towards a certain travel mode increases the probability that people will choose this mode for a particular trip. However, not a lot of studies have analysed whether people actually choose their preferred travel mode. In this paper we will look at whether respondents with a preference for car use, public transport use, cycling and walking will actually use these modes. Furthermore, we also analyse whether respondents who use their preferred travel mode (i.e., consonant travellers) are more satisfied with their trips compared to respondents travelling with a non-preferred travel mode (i.e., dissonant travellers). Results from this study, analysing leisure trips of 1656 respondents from the city of Ghent (Belgium), indicate that about half of the respondents chooses a non-preferred travel mode and that dissonant travellers can be mainly found within public transport users and least within cyclists, partly due to relatively low levels of public transport attitudes and high levels of cycling attitudes. Furthermore, travel mode dissonance seems to have an important impact on travel satisfaction. Consonant travellers have above average travel satisfaction levels, independent of the used travel mode, while dissonant travellers (except dissonant pedestrians) have below average travel satisfaction levels. This suggests that using a preferred travel mode has at least an equally important impact on travel satisfaction than the chosen travel mode itself.
TL;DR: This study demonstrates a resilience approach for rail transit network under daily operational incidents by integrating the network topological and passenger volume characteristics, and explicitly accounts for the impacts of accumulative affected passengers quantifying the varying resilience of rail network with time under different incidents.
Abstract: In the context of urban rail network analysis, most studies have focused on vulnerability analysis developing methodologies to measure consequences on network performance under destroy events. Few works are reported addressing the modeling of rail transit network resilience under operational incidents which could be more important analyzing the network performance changes under daily operations. This study demonstrates a resilience approach for rail transit network under daily operational incidents. Integrating the network topological and passenger volume characteristics, this approach explicitly accounts for the impacts of accumulative affected passengers quantifying the varying resilience of rail network with time under different incidents. The proposed methodology was applied to Shanghai Metro Network in Shanghai, China. Results show that critical stations are identified differently depending on duration time of different incidents and characteristics of the failed stations, and stations on network legs could be more important than those with redundant rail alternatives. Conclusions of this research would also have practical implications for the management and decision making of rail transit network under daily operational incidents.
TL;DR: In this paper, a survey was administered on 116 seafaring officers and the obtained data were analysed using structural equation modeling to analyse the core determinants of job satisfaction and performance of seafarers.
Abstract: The ability to motivate and retain seafarers is a critical manpower issue in view of global labour shortage and high turnover rate among seafarers. The objective of this paper is to analyse the core determinants of job satisfaction and performance of seafarers. A survey was administered on 116 seafaring officers and the obtained data were analysed using structural equation modelling. The results show that job satisfaction is considerably correlated with job performance of seafarers. In addition, the amount of stress associated with working onboard a ship and attractiveness of rewards are key determinants of job satisfaction. The dispositions of seafarers and appeal of the job design also have considerable impacts on job satisfaction. Based on literature review and post-survey interviews, a management model consisting of policies and strategies to motivate and retain seafarers is proposed.
TL;DR: In this paper, the authors employed a time-series regression model, controlling for various factors that may affect taxi trips and found no direct evidence that the number of taxi trips, the revenue per driver, or occupancy rates have decreased since Uber entered the market.
Abstract: This research aims to empirically examine how Uber has transformed the traditional taxi industry in New York. To this end, we employed a time-series regression model, controlling for various factors that may affect taxi trips, and found no direct evidence that the number of taxi trips, the revenue per driver, or occupancy rates have decreased since Uber entered the market. However, a closer investigation into other dimensions, specifically the degree of dispersion of pick-up and drop-off locations, reveals that taxi drivers have been forced to change their way of conducting business in order to retain their market position. Since Uber has crowded out taxis from the central area of Manhattan, the latter have actively responded by serving customers outside of this area. By increasing their geographic coverage and serving customers that were previously ignored, taxis were able to retain their numbers for trips and market share. Our results suggest that the incumbent taxi drivers actively responded to the disruptive threat of Uber’s entry and have consequently provided substantial benefits to consumers as taxis can now be hailed from a wider area of New York. We thus found that the sharing economy has transformed the existing market in a positive and welfare-enhancing way.
TL;DR: In this article, the authors explore the determinants of public transport ridership from 2002 to 2015 for 25 transit authorities in Canada and the United States using a longitudinal multilevel mixed-effect regression approach.
Abstract: Public transport ridership has been steadily increasing since the early 2000s in many urban areas in North America. However, many cities have more recently seen their transit ridership plateaued, if not decreased. This trend in transit ridership has produced a lot of discussion on which factors contributed the most to this new trend. While no recent study has been conducted on this matter, understanding the levers that can be used to sustain and/or increase transit ridership is essential. The aim of this study is, therefore, to explore the determinants of public transport ridership from 2002 to 2015 for 25 transit authorities in Canada and the United States using a longitudinal multilevel mixed-effect regression approach. Our analysis demonstrates that vehicle revenue kilometers (VRK) and car ownership are the main determinants of transit ridership. More specifically, the results suggest that the reduction in bus VRK likely explains the reduction in ridership observed in recent years in many North American cities. Furthermore, external factors such as the presence of ridesourcing services (Uber) and bicycle sharing, although not statistically significant in our models, are associated with higher levels of transit ridership, which contradicts some of the experts’ hypotheses. From a policy perspective, this research suggests that investments in public transport operations, especially bus services, can be a key factor to mitigate the decline in transit ridership or sustain and increase it. While the results of this study emphasize that fare revenues cannot support such investments without deterring ridership, additional sources of revenues are required. This study is of relevance to public transport engineers, planners, researchers, and policy-makers wishing to understand the factors leading to an increase in transit ridership.
TL;DR: Wang et al. as mentioned in this paper investigated the factors affecting mode choice behavior with a focus on bike-sharing, and explored the effectiveness of different policy options aiming at increasing bike sharing ridership.
Abstract: Developing countries are facing increasing challenges to make urban mobility sustainable and to tackle the continuously growing air pollution and congestion caused by the rapid increase in car ownership. As part of a broad strategy to achieve sustainable urban mobility, bike-sharing services could contribute to car usage decrease, especially for short-distance trips. However, most of the developing countries have limited quantified evidence regarding the factors affecting bike-sharing choice and this hinders policy makers from effectively promoting bike-sharing usage. The case study city is Taiyuan, which operates one of the most in demand bike-sharing schemes in China. This research investigates the factors affecting mode choice behavior with a focus on bike-sharing, and explores the effectiveness of different policy options aiming at increasing bike-sharing ridership. Nested logit and mixed nested logit models are developed using both stated preference and revealed preference data. Policy effectiveness is studied by examining modal split changes. The results reveal the significant negative impact of air pollution on bike-sharing choice. Nevertheless, improving air quality is found to be less effective in promoting bike-sharing ridership than improving bike-sharing service itself (e.g. through access time saving, travel cost saving); although it is more effective in suppressing private car usage.
TL;DR: An entropy-Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) Method to evaluate the urban rail transit system’s operation performance from the operator's, passenger's and government's perspectives is formulated.
Abstract: Urban rail transit system operation performance evaluation results are important for government, transit operators and passengers. In this paper, we formulate an entropy-Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) Method to evaluate the urban rail transit system’s operation performance from the operator’s, passenger’s and government’s perspectives. Firstly, we establish the evaluation indicator system with 8 indicators and a total of 41 sub-indicators, the operational data of the 41 sub-indicators will be used as the input of the approach. Second, we formulate our new approach to obtain the performance evaluation: the Entropy Weight Method (EWM) will be used to calculate the weight of each sub-indicator; the product of the corresponding probability and weight will be used to formulate the performance from operator’s, passenger’s and government’s perspectives; the TOPSIS will be used to calculate the comprehensive evaluation values and rankings of performance for each month. Third, the Chengdu subway with 34 months initial data will be chosen as the case study to test our new approach, the related suggestions to the government, to the passengers as well as the operators and managers will also be given.
TL;DR: In this article, the authors quantified the substitution and complementary effects of high-speed rail (HSR) on air travel demand in terms of both route traffic and airport enplanement.
Abstract: This paper quantifies the substitution and complementary effects of high-speed rail (HSR) on air travel demand in terms of both route traffic and airport enplanement Employing the difference-in-differences (DID) method, the first part of the analysis measures the effect of new HSR routes on parallel air route traffic with a focus on East Asian regions (Mainland China, Japan, South Korea, and Taiwan) The second part examines the effect of air-HSR integration on passenger enplanement at East Asian airports and compares with that in the Central European market We find that in general the airport’s access cost (reflected by the distance from central city) has a negative impact on the air traffic The substitution effects of HSR are the most significant on short- and medium-haul (below 1000 km) air routes while introducing HSR services has encouraged long distance (over 1000 km) air travels in Mainland China The complementary effect is investigated in the context of air-HSR integration, which has significantly positive impacts on airport enplanement at primary hub airports when fitted with on-site HSR links The benefit is limited at secondary hubs and regional airports possibly by locations and HSR service frequencies
TL;DR: A framework is developed and applied to estimate the value perceived and assigned by commuters to the pure transfer penalty, which captures the effects of habit, crowding, walking, waiting and in-vehicle times, information, and the additional effect of intermodality on transfers.
Abstract: The disutility of transfers in multimodal public transport goes beyond the additional walking and waiting times. Although the magnitude of this pure transfer penalty has been proven to be an essential element in the structural design of public transport lines, the scarce available research reveals a wide range of values. The aim of this paper is to develop and apply a framework to estimate the value perceived and assigned by commuters to this penalty. This framework includes all the other elements considered by users in the case of a trip involving (potential) transfers, in order to obtain the impact of each one. The framework is based on the discrete choices paradigm and applied to data collected in Madrid, Spain. The results show that the pure transfer penalty is comparable to a 15.2–17.7 equivalent increase in in-vehicle minutes; i.e. longer trips may be preferred to faster alternatives with transfers, even if the additional walking and waiting times are zero. As well as the pure transfer penalty, the model also captures the effects of habit, crowding, walking, waiting and in-vehicle times, information, and the additional effect of intermodality on transfers.
TL;DR: In this article, the effects of the HSR on urban sectoral employment using China's city-level data from 2003 to 2015 were investigated and it was found that cities connected to the high-speed railway network experienced a significant growth in the employment of the retail/wholesale and hotel/food industries, while no measurable effects were found in other sectors.
Abstract: This paper estimates the effects of the High-Speed Railway (HSR) on urban sectoral employment using China’s city-level data from 2003 to 2015. I found that cities connected to the HSR network experienced a significant growth in the employment of the retail/wholesale and hotel/food industries, while no measurable effects were found in other sectors. In order to explore whether the HSR effects are a growth or reorganization, this paper compared the effects of the HSR on the connected cities to those on adjacent cities, and found that the HSR promoted growth in the cities it directly passed through by drawing activities away from their neighbors. The further market potential approach suggests that the more people connected to the city within one to four commuting hours through the High-Speed Railway network, the higher the employment growth will be in the related sectors.
TL;DR: In this article, the authors develop a conceptual framework that explores automobility through a categorization of frames, or shared cultural meanings, which can help to enrichen discussion of transitions and policy relating to sustainable transportation.
Abstract: Automobility refers to the continued, self-perpetuating dominance of privately-owned, gasoline-powered vehicles used primarily by single occupants—a system which clearly has broad environmental and societal impacts. Despite increasing societal interest in transitions to more sustainable transportation technologies, there has been little consideration of how such innovations might challenge, maintain or support different aspects of automobility, and what that means for technology deployment, transport policy, and user practices. To bring attention to the complexity and apparent durability of the automobility system, in this paper we develop a conceptual framework that explores automobility through a categorization of frames, or shared cultural meanings. This framework moves beyond the typical focus on private, functional considerations of user choice, financial costs and time use to also consider symbolic and societal frames of automobility that exist among users, non-users, industry, policymakers and other relevant social groups. We illustrate this framework with eight particular frames of automobility that fall into four broad categories: private-functional frames such as (1) cocooning and fortressing and (2) mobile digital offices; private-symbolic frames such as (3) gender identity and (4) social status; societal-functional frames such as (5) environmental stewardship and (6) suburbanization; and societal-symbolic frames such as (7) self-sufficiency and (8) innovative adopters. Finally, we start the process of discussing several transportation innovations in light of these automobility frames, namely electrified, autonomous and shared mobility—examining early evidence for which frames would be challenged or supported by such transitions. We believe that appreciation of the complex and varied frames of automobility can help to enrichen discussion of transitions and policy relating to sustainable transportation.
TL;DR: In this paper, a sample of 403 respondents has been collected from Malaysia in order to forecast the customer's intention to adopt PHEVs by using the extended theory of planned behaviour.
Abstract: Malaysia is amongst the major energy intense countries and is under an excessive burden to advance its energy efficiency and to also work towards the reduction of its carbon emission. Plug-in Hybrid Electric Vehicles (PHEVs) have the potential to lessen the carbon emission and gasoline consumption in order to alleviate environmental problems. Consequently, attempts are being initiated to popularise the use of PHEVs as the main mode of transportation. The diffusion of PHEV adoption is a positive initiative. A sample of 403 respondents has been collected from Malaysia in order to forecast the customer’s intention to adopt PHEVs by using the extended theory of planned behaviour. The empirical outcome using the PLS investigation exposed that all four constructs, subjective norm, personal moral norm, perceived behavioural control, and attitude ominously shows an indirect effect which has inclined towards the Malaysian consumers’ intention to adopt PHEVs. All these four major constructs were significantly predetermined by their respective environmental concern. Whereas, hyperbolic discounting moderated the relationship between intention and adoption. The fostering result verifies that the relevance of the extended TPB had a good explanatory power in the line of predicting the Malaysian consumers’ intention to adopt PHEVs. For future study, grounded by the observed outcome, authors explain the implication aimed at promoting the PHEV adoption.