Research in Transportation Business and Management最新文献

The emergence of Intelligent Transportation Systems (ITS) for freight transport in recent times has created interest among practitioners and researchers to extend freight ITS to support broader logistics processes, including dynamic tour scheduling, loading and unloading, warehousing, and even production. However, connecting transport data, ITS and logistics information systems require collaboration between different organizations and new business models to create business value for logistics actors. It is critical for these stakeholders to consider how their business models connect to create meaningful new data-to-information value chains. This study develops a conceptual framework to identify opportunities for logistics value creation with freight transport data. Building on the literature we construct a framework that reconciles multi-firm and firm-level business modelling. The main component is a generalized framework for Data-to-Value (DtV) chains for applications in information and communications technology. In order to support its business validity, we extend this framework with Business Model Canvases (BMCs) of the actors in the value chain. Three real-life use cases from a freight ITS community in the Netherlands are used to evaluate and illustrate the framework.

The COVID-19 pandemic profoundly affected freight transport. While several studies have explored the epidemic's impact on individual freight modes, a comprehensive exploration of its effects on transport modal shifts is lacking. This study addresses two inquiries: Can the pandemic catalyze freight modal shifts during its course? Additionally, how can port planners and government agencies leverage new opportunities emerging for freight transport in the post-epidemic period? Based on monthly panel data from September 2021 to August 2022 in 21 Chinese provinces, we investigate the epidemic's impact on modal shifts through difference-in-differences (DID) models, heterogeneity models, and moderating effects models. Moreover, particular emphasis is placed on spatial spillover effects, analyzed through spatial difference-in-differences (SDID) models. The findings reveal that the epidemic facilitated the modal shifts from road to waterway, but these effects are not enduring. Provinces with well-established waterway infrastructure, higher environmental consciousness, and robust policy foundations exhibit a more pronounced enhancement in modal shifts. The impact is further accentuated by lower waterway freight rates. Moreover, the epidemic manifests positive spatial spillover effects. Local outbreaks prompt freight modal shifts from road to water in neighboring provinces. The positive spillover effect primarily occurs between the affected province and its non-affected neighbors.

The rapid aging of the population poses significant challenges for social structures and economic development, with migration emerging as a key strategy for elderly individuals to enhance their social networks, quality of life, and overall well-being. This study delves into the role of high-speed rail (HSR) in facilitating intercity migration among the elderly in China, a country experiencing a pronounced demographic shift with a burgeoning aging population. By employing a Poisson regression model on unbalanced panel data from 2008 to 2017, this paper assesses the aggregate and heterogeneous effects of HSR on elderly migration, considering various migration purposes and the mediating effects of younger generation migration. The study uncovers that elderly migration is predominantly towards economically vibrant cities, with HSR significantly influencing migration patterns by improving accessibility and connectivity. The analysis reveals that the elderly migration along with their family is more influenced by accessibility improvements, while the elderly migration for work is more responsive to enhanced connectivity provided by HSR. Furthermore, the migration of younger generations moderates the positive impact of HSR on elderly migration, particularly for family and work-related migration, but not for healthcare-related migration. The insights from this study emphasize the importance of policies that encourage inter-generational migration, allowing younger and elderly family members to move together, which can help maintain family unity and reduce the social and economic pressures on cities that receive migrants. Moreover, the study advises cautious development of HSR in less prosperous areas to avoid exacerbating population loss and regional decline.

High-speed railways have a profound impact on entrepreneurship. Adopted China's city panel data, we use a time-varying DID model to estimate the influence of the high-speed railways on urban entrepreneurship and study its mechanism. The analysis results reveal that high-speed railways have improved the entrepreneurial vitality of cities. The mechanism test suggests that high-speed railway promotes entrepreneurship activities by accelerating human capital flow, strengthening producer services agglomeration, and promoting market integration. A range of robustness tests including a parallel trend test, placebo test, and PSM-DID model are used to ensure the reliability of the empirical results. Heterogeneity analysis and spatial analysis are used to deepen the research. Heterogeneity analysis reveals that high-speed railway construction is likely to motivate entrepreneurship in eastern cities, big cities, and cities with high-level business environments. The spatial analysis results show that the opening of the high-speed railways promotes the entrepreneurial level of surrounding cities. The research results help to evaluate the economic benefits of high-speed railway network expansion, and provide decision-making references for stimulating urban entrepreneurship.

Despite its substantial customer value in enhancing mobility and connectivity, air transportation prompts concerns regarding sustainability across social, economic, and environmental dimensions. Recognizing the sustainability challenges in Turkey's domestic air travel market and emphasizing the importance of assessing passenger perspectives to ensure regulatory effectiveness, this study investigates how environmental attitudes, perceived value, and satisfaction influence customer preferences. Results from the structural path model analysis highlight the significant impact of emotional value, reliability, comfort, and customer value on air travel satisfaction, affecting both current and future preferences. Gender moderates the influence of safety on satisfaction, with women perceiving it as more critical. While Turkish domestic air passengers express significant environmental concerns, these concerns do not always translate directly into their travel preferences.

This study aims to analyze the spatial distribution and temporal evolution of the lodging industry around a major transportation hub, focusing on the agglomeration patterns of different types of lodging establishments, namely budget hotels, economy hotels, upscale hotels, and peer-to-peer accommodations. The study takes the high-speed rail (HSR) station in Beijing, China, specifically the Beijingnan Station, as the empirical setting. The findings reveal a gradual increase in the degree of agglomeration in the lodging industry since the opening of the HSR station, with the distribution center shifting closer to the station every year. The distribution pattern surrounding the station follows a six-ring structure, where budget hotels are located in the innermost ring, followed by economy hotels in the second ring, and upscale hotels in the outermost ring. Notably, peer-to-peer accommodations exhibit a dispersed and sporadic distribution pattern, which sets them apart from other types of lodging establishments.

Transportation and logistics in mountain regions are difficult due to the harsh weather conditions and complex terrain. It is crucial to have specialized expertise and advanced technologies to tackle such challenges. However, the field has unexplored domains, and available solutions are not holistically charted, necessitating a nuanced understanding of the innovation landscape and growth trajectories. This study aims to undertake a patent analysis on mountain transportation and logistics to unveil emerging trends, map technological advancements, and contribute to enhancing transportation systems. Relevant patent documents were extracted from the Derwent Innovation Index database through a keyword search combined with specific International Patent Classification categories. From these documents, technological fields were identified and grouped using the Latent Dirichlet Allocation technique, resulting in 12 clusters. Among them, seat and suspension control systems, intelligent vehicle control systems, electrical systems and electric vehicles, bicycle frame design, and safety devices are likely to attract notable interest in the future. The findings contribute to the academic discourse and hold practical implications for industry and policy stakeholders, offering a nuanced understanding of technological trends crucial for addressing transportation challenges in mountain terrains.

Road traffic is a significant source of carbon emissions in China, and a thorough understanding of vehicle operating characteristics is crucial for reducing these emissions. This paper presents an integrative approach to analyze the operation of heavy-duty trucks (HDTs) by fusing On-Board Diagnostic (OBD) data. The operational intricacies of HDTs, including load statuses, origin-destination (OD) trip characteristics, and the frequency of HDTs start-stop pairs, were analyzed. We used OBD data from 3792 HDTs in China over whole year of 2022 and employed novel big data mining methods for dwell detection, load identification, and OD trip information calculation. The findings reveal that for cargo trucks, dump trucks, and tractor trucks at the OD trip level, their respective empty-loaded driving rates stand at 33.01 %, 33.58 %, and 31.71 %. The average OD travel distances for these vehicle categories are 110 km, 95 km, and 195 km, while the average travel velocities are 23 km/h, 16 km/h, and 40 km/h, respectively. Additionally, the average number of start-stop pairs for these categories is 2.8, 3.9, and 4.9, and the average dwell duration is 1.2 h, 1.6 h, and 2.1 h, respectively. This study demonstrates the great potential of optimizing load management and trip planning, and provides a reference for improving the economic efficiency and reducing emissions of HDTs in China.

Last-mile logistics is of crucial importance to city life, but negative externalities require a transition to more sustainable modes of operation. Enhancing the capacity for informed decision-making is key in this multi-actor context with interdependent stakeholder views shaped by long-term contextual dynamics. This paper presents six scenarios representing potential futures of last-mile logistics based on the views of 26 logistics stakeholders with various roles in last-mile logistics using a Disaggregative Policy Delphi approach. They offer insight into the interdependencies between stakeholders and key enablers and barriers in the transition. Results suggest that actions of local authorities strongly influence the level and direction of technological innovation and cooperation. This stresses the importance for local authorities to build the capacity required to play a meaningful role in the transition, for example, by facilitating ongoing dialogue that may help actors to navigate their different preferences and negative impacts on quality of urban public space, and to identify joint courses of action towards more sustainable last-mile logistics.

When urban residents predominantly rely on private vehicles for their daily commutes, the urban ecosystem experiences substantial negative repercussions, including increased road congestion and significant negative environmental impact. This reality underscores the importance of evaluating and adapting modal share as a key objective in the planning of transportation systems. To provide accurate data-driven decision-making support, a modeling framework is proposed and utilized to analyze modal share change objectives, based on a real-world transportation demand dataset and the long-term mobility strategy from Budapest, Hungary. With the Modal Share Evaluation (MSE) algorithm supported by the Daily Activity Chain Optimization (DACO) framework, several variables, such as travel time, distance, and CO2 emissions, can be estimated for several future hypothetical scenarios. The data for the baseline scenario are derived from a historical dataset on travel patterns from the city, and respective estimations are made for future scenarios while considering five transport modes. The results indicate that a different prioritization of the adoption of transport modes for Budapest may result in various effects on the travelers' activity chains. The proposed MSE algorithm aims to be the first step towards a reproducible disaggregate-level framework that supports decision-makers in estimating how modal share change objectives affect travelers and the urban environment, which will help in creating future transportation policies.