Research in Transportation Business and Management最新文献

The rapid growth of the e-commerce market creates new dynamics in the logistics landscape, which has been evolving for decades in cities around the world. It is a challenge for businesses and planners to meet the high demand for logistics facilities for e-commerce order fulfillment and goods handling. In the Tokyo Metropolitan Area, mega-scale multi-tenant logistics facilities have been developed in both the port area near the urban center and the periphery of the city, while delivery service providers (DSPs) locate many last-mile delivery stations, varying in number depending on the urban density. We analyze the spatial distribution and location factors of both mega-scale multi-tenant facilities and last-mile delivery facilities in comparison with logistics facilities in general. We found that, due to the scarcity of land, newly developed multi-tenant facilities are more likely to be in less accessible places from the expressway network and the places where development has historically been limited. The result also indicates the heterogeneity of the distribution of DSPs' facilities, reflecting the heterogeneity in business strategies, which can be partially explained by the historical context.

The operation of the China Railway Express (CRE) has diversified freight transportation between China and Europe, expanding the international freight channels in Chinese cities where CRE operates. However, the relationship between the evolution of China-Europe freight routes and the development of Chinese cities remains unclear. Therefore, we propose a potential model to assess the evolution of CRE routes and develop an indicator system to measure city sustainability. We employ a coupled coordination degree model (CCDM) and structural equation modeling (SEM) to determine the impact of CRE on the development of these cities. Findings reveal several key insights. Firstly, CRE has facilitated the expansion of China-Europe freight routes in Chinese cities, significantly enhancing the accessibility of China-Europe integrated inland transportation. Secondly, the growth of freight routes between China and Europe has exerted a substantial influence on the long-term development of Chinese cities, particularly inland cities. The positive relationship between route evolution and city development has strengthened over time. Lastly, the expansion of China-Europe freight routes indirectly contributes to the development of inland cities, primarily through stimulating innovation, industry scale, financial growth, and international trade. In contrast, coastal cities mainly benefit from the direct promotion of the international trade levels.

This paper identifies the state-of-the-art key aspects for the development of mobility-as-a-service (MaaS) ecosystems and provides evidence on the importance of cyber security which has been broadly overlooked in the literature. The analysis is carried out in three stages: (i) a literature review, (ii) a presentation of expert workshop findings, and (iii) a synthesis of both findings to develop a research agenda on cyber security aspects of MaaS ecosystems. The review identifies and bridges the gap between two strands of MaaS literature: the studies that focus on the factors that drive the development of MaaS, and those that create narratives of future MaaS scenarios.

The analysis employs the Business Model Canvas to synthesise important factors that underline the development of MaaS in a 7-dimension matrix. This matrix is then used to assess to what extent the available MaaS scenarios cover such dimensions, showing that the literature has overlooked the incentives for users, incentives for MaaS providers, public governance and cyber security elements of the MaaS development.

Finally, this paper synthesises the findings from the review of the literature and an expert workshop to develop a research agenda to characterise and analyse the role of incentives to influence the individuals' and organisations' data sharing preferences and emerging cyber security risks in MaaS ecosystems, which will be of interest to both scholars and policymakers. Only through explicit consideration of data-sharing behaviours and risks across individuals and organisations that MaaS ecosystems can support the transition to a net-zero economy.

Freight transport is crucial in fostering economic growth and enhancing societal well-being, but it also poses challenges for traffic management and environmental sustainability. For freight planning and policy formulation, it is important to measure and evaluate regional freight accessibility. This paper proposes a novel framework for analyzing regional freight accessibility based on truck trajectory data. The framework is structured around two principal components: extracting freight trip information and constructing a freight accessibility model. It introduces precise and effective methodologies for identifying truck parking zones based on trajectory data, thereby facilitating the extraction of complete freight trip information. Afterward, the framework integrates a distance-weighted topological analysis with multiple relevant indicators to comprehensively assess the freight accessibility of a region. Additionally, it incorporates spatial lag modeling to examine the factors influencing the spatial distribution of freight accessibility within a region. Applied to a case study in Hunan Province, China, the framework demonstrates its efficacy. The analysis reveals that accessibility in Changsha and two other cities stands out significantly higher than in other cities. The study offers valuable insights for strategic freight planning and policy formulation.

The rapid expansion of the automotive fleet in Latin America, coupled with the excessive utilization of automobiles, has resulted in significant challenges related to traffic congestion and environmental pollution. One of the mechanisms within transportation planning to mitigate excessive car use is utilizing the park and ride (P&R) system. Nevertheless, implementing multimodal hubs as a P&R system in Latin America has been relatively limited despite their prevalence in other global regions as a crucial transportation infrastructure component. Implementing a P&R system requires transportation planners with different types of expertise to study a set of criteria that are ranked in order of importance. To perform these analyses, it is necessary to use multi-criteria methods to understand which criteria are the ultimate important for their location. Our study highlights the gap in the limited implementation of P&R systems, particularly multimodal hubs, in Latin America despite their prevalence in other places such as Europe and the United States that have developed P&R systems in combination with the implementation of public transport systems. The adoption of the Full Consistency Method (FUCOM) with parsimonious preference information fills this gap by providing a flexible and adaptable approach to decision-making in dynamic and unpredictable urban environments like Cuenca in Ecuador. The findings indicate that utilizing this methodology enhances the efficiency and precision in determining the criteria for the placement of the P&R system. In conclusion, consideration of public transport accessibility serves as a foundational aspect for developing P&R system in the Latin American city under investigation. In essence, implementation of the P&R system is closely linked to optimization of public transportation system.

Rural older adults reliant on transportation services represent an historically underserved demographic, yet their specific service needs remain inadequately understood. This study aims to explore important rural transportation service features for senior customers while identifying service gaps and potential misconceptions between senior customers and service providers. Utilizing data from a cross-sectional service survey in rural Wisconsin, 13 important service features were identified by both senior customers and service providers, and grouped into three categories—basic, technological, and special—via exploratory factor analysis. While consensus existed between seniors and providers on the primary importance of basic features, seniors attributed greater significance to technological aspects than service providers anticipated. Differing preferences surfaced between seniors and providers regarding special features. Statistical tests revealed the substantial importance of basic features, particularly among older females, individuals with mobility constraints, and limited leisure activity. Moreover, technological features received higher ratings from older females, younger individuals, and those with internet access. Varied attention towards special features aligned with diverse older adult needs. Service providers, regardless of their characteristics, exhibited consistent prioritization of service features. Our findings emphasize opportunities for rural transport service providers to better serve senior users by enhancing basic service provisions, embracing age-friendly technologies, and tailoring specialized services to meet distinct user requirements within local contexts.

Most European countries have been committed to reducing their carbon footprint, combating climate change, and reducing the air pollution typical in large cities over the past decade. Among current solutions that can be adopted are the replacement of fuel-powered means of transport with electric ones, as well as the introduction of car sharing, bike sharing and electric scooters.

The post-pandemic phase was characterized by a greater propensity to use these means of transport as they were perceived as a healthier choice (for a greater possibility of implementing social distancing) and cheaper (for the diffusion of shared services). The study of modal choice depends on socio-economic structures. The present work analyses data related to socio-economic factors (work, income and other) to examine the tendency to use electric scooters in the metropolis of Palermo, Sicily, through machine learning algorithms.

The comparison of different algorithms allowed us to underline how the multilayer perceptron algorithm obtained the best classification among the minimal sequential optimization algorithms. The findings also highlight middle-income and freelancer people as being more likely to use micro-mobility than others. Contrary to what was thought, these findings revealed that micro-mobility is not just a preferred mode of transport for low-income people or students. These trends will be able to encourage continuous monitoring of the relevant factors and will be able to help political decision-makers to increase and improve the diffusion of micro-mobility and to direct marketing campaigns to the groups identified here.

The global increase in electric vehicle (EV) usage is evident; however, inadequate infrastructure in many regions still creates range anxiety among drivers. To address this concern, this paper presents a two-stage methodology for analyzing green transformation projects at existing gas stations towards determination of the most appropriate location and capacity decisions. The first stage of the methodology involves a state of charge tracking optimization model to enhance the process of making location decisions and the optimization model is run several times by considering different parameter values to evaluate potential locations for electric vehicle charger installation. In the second stage, a simulation model is constructed to explore capacity decisions based on various scenarios related to regional densities. Afterwards, extensively tested experiments are performed through a real case from Trabzon province of the Karadeniz Coastal Road, a geographically significant area in Turkey's Eastern Black Sea region, to obtain remarkable insights and policy recommendations. As a result, policy recommendations derived from this study emphasize the prioritization of charging station installations at high-frequency locations and tailoring the number of charging units to regional density. The significance of this study is to offer adaptable solutions for various locations, enhance practical utility and support informed decision-making in infrastructure planning by providing a proposed two-stage methodology for sustainable transportation planning.

Cruising ride-hailing vehicles exacerbate traffic congestion by generating negative externalities. In contrast, reserved ride-hailing services leverage precise information regarding the departure times and origins-destinations of future trips. Platforms can use this data to dispatch and route drivers more efficiently, thereby reducing the need for cruising. Although previous research has largely concentrated on real-time ride-hailing services, the impact of the built environment on reserved ride-hailing remains unexplored with empirical data. This study integrates multi-source data from Haikou City in China and utilizes the gradient boosting decision tree model, which is an interpretable machine learning approach, to investigate potential relationships between reserved ride-hailing trip demand and the built environment. The rankings of relative importance reveal that factors such as the density of food services, education institutions, accessibility to town centers, and proximity to transportation hubs significantly influence the demand for reserved ride-hailing. Furthermore, the study demonstrates that the aforementioned factors exhibit non-linear effects on the demand for reserved ride-hailing. The findings have policy implications for local governments aiming to promote reserved ride-hailing and enhance urban mobility services.

The aim of this paper is to examine the relationships among the dimensions of bus-riding flow experience, relationship quality, and experiential outcome intentions. The data used in this study were acquired from a convenience sample of 535 passengers riding on driverless buses in Hengli Metro Station Bus Terminal of Guangzhou in China. The empirical results display that the dimensions of bus-riding flow experience (goal clarity, curiosity, positive affection, immersion, utility, and sensory challenge) and trust positively influence psychological ownership. Moreover, both trust and psychological ownership positively affect satisfaction. In addition, trust, satisfaction, and psychological ownership positively influence commitment, which in turn leads to the dimensions of experiential outcome intentions (experiential loyalty intention, experiential word-of-mouth intention, experiential riding intention, and willingness to ride on driverless buses). Finally, theoretical and practical implications based on study findings were outlined and recommendations for future research were made.