Transportation Research Interdisciplinary Perspectives最新文献

A substantial body of empirical research has employed the theory of planned behavior (TPB) to investigate individual decision-making within the social context in Indonesia, which is characterized by interconnections and mutual influences. The present research is concerned with the key variables in the theory of planned behavior, namely attitudes, subjective norms, and perceived behavioral control. This investigation examines the influence of these three variables on the intention to use electric motorcycles, either directly or indiretcly, with tax incentives in the form of purchase tax subsidies acting as a moderating variable. The research findings indicate that all TPB variables have a positive impact on the intention to use electric vehicle products directly. However, the findings also demonstrated that tax incentives do not exert a significant influence on the intention to use electric vehicle products. This suggests that tax incentives function as a moderating variable and cannot operate independently to influence the intention to use electric vehicle products. These findings have a direct implications for policymakers and practitioners in the field of transportation.

Decarbonization of the world is greatly contributed to by the recent technological advancements that have fostered the development of electric vehicles (EVs). The EVs relieve transportation dependence on natural fossil fuels as an energy source. More than 50 % of the petroleum products produced worldwide are estimated to be used in the transportation sector, accounting for more than 90 % of all transportation energy sources. Consequently, studies estimate that the transportation sector produces about 22 % of global carbon dioxide emissions, posing significant environmental issues. Thus, using EVs, particularly on road transport, is expected to reduce environmental pollution. To accelerate EV development and deployment, governments worldwide invest in EV development through various initiatives to make them more affordable. This research aims to investigate the changing needs of EV users to establish factors to be considered in the selection of charging demands using machine learning, using an extreme gradient boosting model. The model reached high accuracy, with an R2-Score of 0.964 to 1.000 across all predicted needs. The model performance is greatly affected by age, median income, education, and car ownership. High values of people with high income, high education, and age between 35–54 years show a positive contribution to the model’s performance, contrary to those with 65+, low income, and low education attainment. The outcomes of this research document factors that influence EV charging needs; therefore, it provides a basis for decision-makers and all stakeholders to decide where to locate EV charging stations for usability, efficiency, sustainability, and social welfare.

Governing bodies are continuing to research, conduct pilot programs, and adopt policy for mileage fees as alternatives to the gas tax, yet public support remains critically low. Lack of support generally stems from assumptions that mileage fees will cost more, be inequitable for rural and low-income households, and will impede privacy through invasive mileage collection. In this study, we assess the extent to which these perceptions of mileage fees, which ultimately shape policy opinion formation, are related to low levels of information or lacking information. We also evaluate the unique aspects of policy opinion formation, including engagement with both individual and aggregate ideologies and material self-interests. Our survey instrument encourages issue engagement through iterative voting and educational experiences, through which we see information has a statistically significant effect on policy opinions and changes what we think we know about public support for mileage fees. Across the educational experiences, which include policy-relevant information provided through videos and tailored annual cost calculations for the policy alternatives, 24% of respondents changed their opinion by the end of the study, and 44% changed their opinion at least once during the study. We conclude with suggestions for public opinion polling around controversial policies that apply to both researchers and practitioners looking to engage with their constituents.

The air transport market in Africa is regulated and viable for designated carriers. Although there are some sub-regional liberalizations, airlines primarily compete based on the specifications of bilateral air service agreements. However, this competitive landscape has not been thoroughly investigated. This study examines market concentration in the African aviation industry and explores its impact on the output of African airlines. The competition was measured at the airport level using the Herfindahl-Hirschman index. Panel data were drawn from 54 countries, 339 airports, and 221 airline groups for the period 2015–2019. Kernel density estimation shows that the region’s market for air transport services is fragmented, with many small airlines. Strong competition is more prevalent at larger hub airports, airports near tourist destinations, and major airports far from larger African hubs, while markets tend to be concentrated where dominant and protected flag carriers operate. Competition is also low or limited at smaller airports offering limited flights. The results of panel regression analysis reveal a nonlinear relationship between market concentration and airline output, as strong competition may limit airlines’ output, and high concentration may promote a dominant airline or alliance that may hinder other airlines from entering or remaining in the market.

Many European cities are investigating how to transition to climate-neutral transport systems. Due to the transport system’s complexity and uncertainty about the future, identifying drivers and choosing effective policies to make the city more sustainable is challenging. Additionally, the chosen policies need to be supported by relevant actors. This study aims to support the municipality of The Hague in generating robust policies supported by and within the municipality. We build on participatory modeling and decision-making under deep uncertainty to create a novel approach to address this goal. In two workshops, the participants formulated goals and objectives, created Causal Loop diagrams, and identified potential interventions. Using a set of possible futures, the interventions were then stress-tested to evaluate their robustness. By explicitly linking, for the first time, participatory modeling and decision-making under deep uncertainty approaches, the participants could understand the system better and deal with uncertainty. Participants gained insight into systemic complexity and methods to deal with it, the inter-relatedness of interventions and their effects, and a shared understanding of the problem and its scope. This study demonstrates the potential of a novel approach to generate supported robust interventions to achieve the goal of a climate-neutral transport system.

The market share of electric vehicles (EVs) is growing rapidly, making it crucial to understand the charging behaviour of current and prospective users. Such understanding is essential for designing policies that positively influence consumers’ charging behaviour and facilitate EV adoption. In this study, we examined the heterogeneity in charging preferences of 994 respondents across Australia using a latent class cluster model that considers indicators of charging behaviour as outcomes of interest. We used sociodemographic characteristics, travel needs, and EV adoption status as covariates to predict class membership. Our findings indicate five segments of consumers with distinct charging preferences: routine-focused frugals, cost-oriented deliberators, range seekers, flexibility seekers, and indifferent late adopters. These segments differ in the importance they attach to charging attributes, their coping strategies with limited battery resources, and their risk attitude. Our results suggest that a uniform approach to EV-related policies is not appropriate, as each consumer segment has unique charging preferences and requirements. Furthermore, the study emphasizes the significance of accounting for charging behaviour heterogeneity in demand modelling, as assumptions in current models may not accurately represent the decision-making of most segments.

The urban logistics system causes negative externalities, such as pollution, noise and congestion. This study focuses on city hubs as a concept to reduce these externalities by improving consolidation and adopting zero-emission vehicles. Our research employs system dynamics as a method to uncover the dynamics and mechanisms related to the barriers and potentials of city hub implementation in Stockholm from the perspectives of the Logistic Service Providers (LSPs), the receivers and the public sector. Moreover, a mixed method approach is used for data collection, allowing us to extract the knowledge from the real implementation case, co-create a qualitative model as a Causal Loop Diagram (CLD) with the stakeholders involved in the system, and generalise the model. The mixed method approach includes a group model-building workshop, literature review, existing city hub analysis and stakeholder interviews. The main result is a CLD, visualising the dynamics of the introduction of city hubs. The CLD explores three potential incentives and policies: (i) the receivers change address; (ii) shippers oblige LSPs to use the hubs; (iii) the public sector gives monetary incentives to LSPs. The CLD presented in this paper establishes a validated system structure for the urban logistic system and facilitates the policymakers’ understanding of the barriers to implementing city hubs and what policies could help their implementation.

This paper focuses on sustainable initiatives in the maritime industry, specifically energy transition in EU ports. Our research aims to apply the stakeholder theory in port contexts, to examine the influence of different actors on the adoption of carbon–neutral energy generation technologies, from a port-employee perspective. To that aim, the proposed conceptual model is empirically tested through a survey among port employees, following the identification of applicable technologies via a literature review. Specifically, six types of energy generation technologies that advance the goal of carbon neutrality are identified, and likewise, following the stakeholder theory approach, we identified six categories of relevant stakeholders, perceived as external or internal. By means of a multiple regression analysis, we assess the influence of stakeholders identified regarding the carbon–neutral generation technologies. The results corroborate the suitability of the stakeholder approach for assessing port environments. The findings suggest the existence of different perceptions among port employees regarding the various technologies, while stakeholder influence can be either positive or negative depending on the type of technology. Among the stakeholders involved, customers and competitors appear as most influential. The main contribution of our results derive of tackling the differences in perception of carbon neutrality within the European Ports, and the carbon–neutral technologies in ports contributing towards carbon neutrality. By providing a more thorough understanding regarding the influence of diverse stakeholders in promoting carbon neutral energy generation technologies, this study can serve as a guideline for future research and be of value for practitioners in the field.