Research in Transportation Business and Management最新文献

Over the past 35 years, the development of high-speed rail (HSR) in Japan has markedly enhanced market access and altered spatial distributional dynamics, thereby transforming the socioeconomic landscape in both urban and rural areas. This study delves into the impact of improved market access on regional disparities, with a particular focus on the shifts in population and economic activity between urban centers and their surrounding peripheral regions. We examine three key hypotheses: (1) HSR influences population dynamics, potentially leading to population decline in underdeveloped areas; (2) it affects demographic patterns, particularly in rural areas; and (3) it contributes to economic disparities, enhancing urban prosperity potentially at the expense of rural regions. Our analysis reveals pronounced effects of HSR: urban areas, exemplified by Tokyo, have seen substantial socioeconomic gains including a 26.10% income rise and an 18.34% population increase. Conversely, rural regions exhibit declining economic indicators with income dropping by 6.32% and population falling by 6.83%, accompanied by aging demographics. These trends, further illuminated by night-time light (NTL) data, underscore the uneven impact of HSR. Simulations suggest the continuation of these patterns with future HSR expansions. The study highlights the need for strategic policy measures to address the growing spatial disparities induced by HSR, advocating equitable infrastructure development and sustainable urban planning.

The issue of road safety is a growing global concern, and evaluating performance in this area is crucial for the development of effective safety policies and the allocation of safety resources. Amidst the input-output perspective of road safety risks, this study endeavors to assess the performance of provincial road safety in China from 2012 to 2021. To achieve this goal, the research employs data envelopment analysis (DEA) and the DEA-window approach, grounded in the framework of variable/constant returns to scale (VRS/CRS) models. The results reveal that Shanghai and Tibet consistently achieved efficient scores using both the DEA-VRS and DEA-CRS methods throughout the past decade. There is a small difference of 0.028 and 0.025 between the average scores obtained from the DEA and DEA-window analysis using the VRS and CRS models, respectively. Shanghai, Tibet, and Beijing demonstrate exceptional performance in both the DEA-CRS-window and DEA-VRS-window analysis, while North China, Southwest China, Central China, and South China exhibits the significant variations in performance ranking. This study enhances the understanding of the current road safety status in China and offers valuable insights for policymakers to formulate targeted measures, aiming to continuously improve road safety performance across various provinces through benchmarking management

The tariff landscape within Switzerland's public transport network is characterized by limited options: the flat rate (Generalabonnement), designed to accommodate frequent customers, and the pay-per-use model (Halbtax), tailored for those who use the network infrequently. However, there is a gap in provision for medium-frequency customers, who lack an intermediary tariff option. Our study employs a combination of conjoint analysis and market simulations to assess the potential appeal of a hypothetical novel three-part tariff structure, referred to as the bonus tariff. The paper first examines customers tariff selection, probing whether choices are influenced by biases favoring either the pay-per-use or flat-rate options. Further, we calculate the significance of various tariff attributes and identify sociodemographic variables predictive of tariff preference. Attributes such as the pre-pay credit and bonus levels exhibit the highest part-worth utilities. The analysis shows that the bonus tariff would capture a significant market share. A market simulation underscores the sensitivity of the business case to factors including bonus levels and the proportion of customers transitioning from flat-rate subscriptions. The overarching outcome suggests a positive impact on revenue with the introduction of the bonus tariff. The conclusion delves into the reasons for these findings and outlines implications for tariff management strategies.

Covid-19 has been a major shock for European aviation. After the general relaxation of state aid rules by the European Commission, Member States stepped in to support airlines, airports and other stakeholders in aviation. However, distribution of state resources raised significant doubts from competitors, as well as academic literature, with regard to the conditions of the aids and their effect on competition. A two-round Delphi study was employed in order to investigate the opinion of experts in European aviation, with the participation of thirty experts from airlines, airports, handling agents, government authorities and academia. The results show an overall appraisal of the European framework and its flexibility, but also desire for a greater degree of control, complaints over bureaucracy and procedural delays, as well as concern on the effects of state aid on competition in the internal aviation market.

Importance-Performance analysis, an advantageous method for analysis and decision-making, has been widely applied to many fields. The advantages and disadvantages of Importance-Performance analysis have been reported in previous literature. Previous studies proposed some revised or integrated methods for combining Importance-Performance analysis and other techniques to overcome the weaknesses of Importance-Performance analysis to increase measurement accuracy. However, the calculation procedures of those revised and integrated methods, including several methodologies, usually are complex. In addition, Importance-Performance analysis only focuses on customers' demands and neglects the practical viewpoints of the service providers' capabilities, e.g., finance, feasibility, land and resource availability, etc. Therefore, this study proposes a new Importance-Unsatisfaction-Improvement theory for analyzing and determining the priorities of improvement alternatives. This new Importance-Unsatisfaction-Improvement theory not only takes into account both the demands of customers and the supply capabilities of service providers but also has a simple calculation procedure. Finally, this study applied the new Importance-Unsatisfaction-Improvement theory to prioritize improvement alternatives for upgrading from a traditional port to a sustainable port in Taiwan. The results show that the priority alternatives comply with the practices of the port authority. As noted above, the new Importance-Unsatisfaction-Improvement theory is an easy-applicability research methodology that can efficiently explain complex customer behaviors, provide easy-to-implement improvement strategies and recommendations, and have calculation simplicity. It can be applied to solve decision-making problems in various fields in future studies.

We estimate technical efficiency using stochastic frontier techniques, distinguishing between persistent and transient inefficiency. Previous studies in the port efficiency literature have accounted for firm heterogeneity and time-varying technical inefficiency. However, no port studies to date have accounted for heterogeneity, time-invariant (persistent) and time-varying (transient) inefficiency. Accounting for both types of inefficiency is important because addressing them requires different types of managerial measures. Using data from a sample of Spanish port authorities observed over the period 1993–2020, we estimate a stochastic output distance frontier with four error components which includes determinants of persistent and transient inefficiency. Port authorities show very low levels of transient inefficiency but higher levels of persistent inefficiency. Overall inefficiency is therefore basically due to persistent inefficiency. We find that port authorities managing more than a single port suffer from greater persistent inefficiency, whereas those located on the Mediterranean seaboard have a structural advantage over their Atlantic seaboard counterparts in terms of persistent inefficiency. The type of output and its share of national output also affect persistent inefficiency.

With the increasing airline business model hybridization, the difference in service sensitivity concerning financial conditions between low-cost carriers (LCCs) and legacy carriers remains to be determined. Considering the close connections between systematic economic factors and airline financial conditions, we focus on how fuel costs, the interbank lending rate, and market concentration affect the service failures of LCCs and legacy carriers. In the US domestic airline business context, the analysis is conducted using an autoregressive distributed lag (ARDL)-bounds testing approach and time series data from June 2003 through May 2023. The results indicate that the long-run effects of the interbank rate and fuel costs on airline services vary across low-cost and legacy carriers. Despite the comparable service levels achieved by LCCs and legacy carriers, their service dynamics respond differentially to financial performance, a factor intricately linked to interbank rates and fuel costs. LCCs exhibit a superior proficiency in cost management, potentially contributing to their lower susceptibility to variations in financial performance compared to legacy carriers. Market concentration adversely impacts the service failures of LCCs and legacy carriers. Intense market competition, particularly when resulting in reduced pricing, may diminish the motivation for airlines to enhance their service quality. The research contributes to understanding the long-run relationship between financial performance and the service of LCCs and legacy carriers within the framework of business convergence. Such insights are of paramount significance for airline managers and policymakers. Furthermore, our research outcomes offer empirical evidence facilitating a more comprehensive understanding of the convergence of airline business models from a service perspective.

The aim of this study is to explore the factors influencing the intention to continually use dockless bike sharing connecting with metro in the context of various new convenient modes of transportation. Firstly, based on the questionnaires collected in Nanjing, China, basic attributes and travel characteristics of users who use dockless bike sharing to connect with the metro are compared and analyzed. Secondly, an ordered logit model is established to investigate the influencing factors of the continuous usage intention of the dockless bike sharing connecting with metro. The model results indicate that: (1) the increase in the monthly income and the education level has a restraining effect on the intention to continue using dockless bike sharing connecting with the metro, although this trend of reduced usage intention is less pronounced among users with higher education levels. (2) Travel duration and travel time also negatively affect the intention to continue using this mode. Interestingly, during peak hours on weekdays, users exhibit a higher willingness to use dockless bike sharing connecting with the metro. (3) Factors such as saving time, solving taxi availability issues, improving accessibility in remote areas, and users' environmental consciousness encourage the continued use of this travel mode. In contrast, high accessibility, network congestion, difficulties in finding parking lots, personal information security risks, high costs, imbalances in supply and demand during peak periods, traffic congestion, and bad weather discourage users to continuously use this mode. Finally, based on these findings, several policies and suggestions to promote the continuous use of dockless bike sharing connecting with the metro are proposed.

For transporting cargo from an origin to a destination, there are several routes with various transport modes, but in practice, only one route should be selected. In this regard, one of the main activities of Logistics Companies (LCs) is to select an optimal route for transporting freight. This complexity intensifies in periodic transport across multiple origins and destinations. This paper aims to develop a dual-phase mathematical model for LCs, considering cost, time, reliability, and air and noise pollution. Indeed, in periodic transport, there is a possibility of merging the cargo with the next shipment, which can lead to lower total costs. Multimodality is also another important consideration for LCs that can reduce cost and environmental impacts. The model leverages Data Envelopment Analysis in the tactical planning phase to filter efficient routes and a multi-objective model in the operational phase for optimal route selection. The proposed approach is validated by the real case of Thailand and Vietnam, which presents practical and managing insights for LCs and shippers. The study underscores the significance of route adjustments in periodic transport and provides valuable insights for LCs and shippers, emphasising the benefits of multimodal solutions in optimising freight logistics.

Benchmarking container ports of different physical sizes and figuring out the relationship between size and efficiency is complex due to the heterogeneous environment. In dealing with heterogeneity, the selection bias is often overlooked. Therefore, this study proposes an integrated multivariate genetic matching and stochastic DEA algorithm to evaluate the efficiency of container ports. It paves the way for container ports that differ in a selected feature, such as size, to be benchmarked using well-balanced clusters. Thus, the port managers can identify the most similar-featured peers in benchmarking with DEA or alternative models to acquire robust estimates without dependence on a longitudinal data set. The results of the model applied to international container ports imply the increase in size impacts efficiency negatively, while connectivity does positively, which contradicts the commonly held perception of stakeholders that the larger the container ports, the more efficient. That is, well-managed small container ports can also be as efficient. Therefore, it is concluded that the results of integrating genetic matching into the performance measurement provide beneficial inferences. In future research, clustering the observed container ports according to a specific feature and balancing clusters with multivariate genetic matching can provide valuable insights into the industry.