Performance assessment of transport services with the ERM-NDEA model: evidence from a domestic airline in Taiwan

Abstract

This paper estimates comprehensive operational performance measures for transport services. A network efficiency approach is used to analyze the production efficiency, service efficiency, and operational efficiency in a unified framework to reflect the transportation service characteristics of airline operations. We show how a modified version of the network data envelopment analysis model can be utilized for evaluating the performance of air route operations. This study considers 15 air routes operated by a domestic airline in Taiwan to highlight the value of the approach. The results of the analysis show the inputs and consumed outputs leading to production inefficiency and service inefficiency respectively as well as the magnitudes of excesses and shortfalls.     

Measuring energy and environmental efficiency of transportation systems in China based on a parallel DEA approach

Because of China’s rapid economic development, its transportation system has become one of China’s high-energy-consumption and high-pollution-emission sectors. However, little research has been done which pays close attention to China’s transportation system, especially in terms of energy and environmental efficiency evaluation. In this paper, data envelopment analysis (DEA) is applied to measure the energy and environment performance of transportation systems in China with the goal of sustainable development. This paper treats transportation as a parallel system consisting of subsystems for passenger transportation and freight transportation, and extends a parallel DEA approach to evaluate the efficiency of each subsystem. An efficiency decomposition procedure is proposed to obtain the highest achievable subsystem efficiency. Our empirical study on 30 of mainland China’s provincial-level regions shows that most of them have a low efficiency in their transportation system and the two parallel subsystems. There are large efficiency differences between the passenger and freight transportation subsystems. In addition, unbalanced development has occurred in the three large areas of China, with the east having the highest efficiency, followed by central China and then west. Therefore, more measures should be taken to balance and coordinate the development between the three large areas and between the two subsystems within them. Our analysis approach gives data for determining effective measures.     

CO2 emissions and expansion of railway,road, airline and in-land waterway networks over the 1985–2013 period in China: A time series analysis

China, the world’s largest CO₂ emitter, is continuing its long-term strategy to use transportation investments as a tool for development. With the expectation that transportation will contribute 30–40% of the total CO₂ emissions in China in the near future, there is an imminent need to identify how the development of different transportation modes may have different long-term effects on CO₂ emissions. Using time series data over the period of 1985–2013, this paper applies the combined autoregressive distributed lag (ARDL) and vector error correction model (VECM) approach to identify short- and long-run causal relationships between CO₂ emissions and mode-specific transportation development, including railway, road, airline, and inland waterway. We find that China’s domestic expansions of road, airline, and waterway infrastructure lead to long-run increases in CO₂ emissions. Among them, waterway has the strongest positive impact on CO₂ emissions, followed by road. Despite a short-run, positive impact on CO₂ emissions, railway expansion leads to long-run decreases in CO₂ emissions. The results are especially encouraging for the central government of China given its long-standing and on-going efforts to expand railway infrastructure at the national level. Looking forward, it is recommended that China continues its national investments in railway infrastructure to achieve both environment and economy goals.     

A multiobjective land development optimization model: the case of New Castle County,Delaware

This paper develops a multiobjective optimization model to consider transportation impacts of the future development of land. The output of the model is the best location and type of land use that has minimal negative transportation effects and uses the maximum available public transportation infrastructure. It provides tools for both planners and transportation engineers and enables them to consider different scenarios of possible policies and land development. Since multiple objectives and their nonlinear structures are considered, the model is solved using mixed integer nonlinear programming. The final results are shown in both tabular and graphical format. The effectiveness of the model is applied to the northern part of New Castle County, Delaware. The results show that the model successfully finds the best locations for both residential and commercial land uses in order to meet several criteria discussed in the paper.     

Modelling and simulation of transportation system effectiveness to reduce traffic congestion: a system dynamics framework

ABSTRACT

This paper is designed to evaluate and improve the effectiveness of transportation systems and reduce traffic congestion through the use of simulation models and scenario development. A system dynamics framework is used to test and evaluate the alternatives of future strategies for the city of Surabaya, Indonesia. Some factors affecting the effectiveness of transport systems include operational effectiveness and service effectiveness, as well as uncertainty. To improve the effectiveness of transportation systems, several strategies can be implemented, such as subsidizing public transportation, increasing the cost of private vehicle parking fees, raising taxes on private vehicles, and reducing delays in public transportation through scenario development. Scenario results show that, by pursuing these strategies, effectiveness could be improved by 80% as the impact of the increase in operational and service effectiveness, helping to mitigate traffic congestion. Congestion could be reduced to 70% (on average) due to the decrease in daily traffic.     

Railway transportation and environmental efficiency in China

Railway is one of the most efficient and environmental-friendly ways to transport people and goods. High-speed railway has been developing rapidly and the railway mileage has increased by 21.18% in China during the period of 2006–2011 and thus it is interesting to evaluate whether the railway transportation has reduced the environmental impact of transport in China. In this paper, we first use a non-radial DEA under managerial disposability to measure the environmental efficiency of 30 regions in China; then we propose a panel beta regression with fixed effects to model the impact of railway transportation on environmental efficiency. The results indicate that the environmental efficiency slowly increased during 2006–2011 and it exhibits regional disparities with the eastern area having the highest environmental efficiency and the western area being the lowest one; Moreover, we also find a significant positive impact of railway transportation on higher environmental efficiency.     

Identifying the most critical transportation intersections using social network analysis

Traffic congestion negatively impacts our society. Most of the traditional transportation planning techniques – though effective – require rigorous amounts of data and analysis which consumes time and resources. This paper uses social network analysis (SNA) to analyze transportation networks, and consequently corroborate the effectiveness of SNA as a complementary tool for improved transportation planning. After creating the connection between the language and concepts of SNA and those of transportation systems – as well as developing a model that utilizes different SNA centrality measures within the transportation context – the authors utilize SNA to investigate traffic networks in three case studies in the state of Louisiana, analyze the results and draw conclusions. To this effect, with minimal cost and time, the model identifies the most critical intersections that should be further investigated using traditional techniques. These results are in agreement with the findings of Louisiana’s Department of Transportation and Development.     

基于高速铁路常旅客计划的全流程智慧行李服务方案构建

随着"铁路畅行"和"客运提质计划"的提出,提供高质量、个性化的旅客服务成为高速铁路客运发展的关键方向。为打造全新旅客行李服务概念,基于"铁路畅行"会员常旅客计划,构建全流程、门到门智慧行李服务方案,从旅客需求角度出发,采取"人货分离"模式,突破传统站内行李服务的模式,拓宽业务场景,延长商业链,形成一套系统完整的方案。全流程智慧行李服务作为一项新的服务模式,为培育旅客需求,提高顾客粘合度,挖掘高铁行李服务的潜在市场,优化铁路盈利结构,加快构建铁路客运服务体系,提升铁路在运输市场的竞争力提供支持。     

My way or the highway? Framing transportation planners’ attitudes in negotiating professional expertise and public insight

Transportation planning continues to expand beyond traditional engineering and economic performance measures toward a broader scope of impacts across space and society. However, the attitudes of transportation planners as they balance their expert knowledge against public insights are not well-understood. We test a two-dimensional attitudinal framework using survey data from 311 U.S. and Canadian transportation planners. We reveal four attitudinal categories using principal component analysis, and hypothesis testing shows significant differences in personal and institutional attributes across these categories. We discuss what our results mean for training and regulatory measures striving to influence planner attitudes before proposing future directions for research.

     

Perceived accessibility,mobility, and connectivity of public transportation systems

Although public transportation is considered effective at reducing the external cost of driving private vehicles, many urbanites do not use public transportation. This study develops measures employing accessibility, mobility, and seamless connectivity for an entire public transportation service chain as indicators for evaluating public transport services, prioritizes underperforming scenarios from the perspective of urban travelers, and derives various market segmentation strategies that consider different socio-demographic characteristics. A conceptual model is set up herein to assess these latent constructs that describe unobservable and immeasurable characteristics. As a Likert ordinal scale can generate misleading statistical inferences, the Rasch model is used to eliminate bias generated by an ordinal scale when measuring these three latent constructs separately. The Rasch model compares person parameters with item parameters, which are then subjected to logarithmic transformation along a logit scale so as to recognize specific difficulties of service scenarios that cannot be easily eliminated by certain urban travelers. The multidimensional Rasch model also measures the perceptions of urban travelers in terms of the interactions between accessibility, mobility, and seamless connectivity of this public transportation system. While comparing urban travelers of two large cities in Taiwan, Taipei and Kaohsiung, the empirical results demonstrate that perceived accessibility, mobility, and seamless connectivity differ based on travelers’ age, frequency of weekly sports activities, and environmental awareness. This paper also advances appropriate improvement strategies and provides policy suggestions for urban planners, public transportation service operation agencies, and policy makers when they seek to create user-friendly public transportation services. The proposed approach can be generalized in other cities by considering their local context uniqueness and further evaluating their public transport services.     

国外铁路运营安全效益评价现状及启示

铁路运输在国民经济运行中发挥着重要作用,各国铁路公司都非常重视对铁路运营、安全、效益的管理及评价。国外铁路经过两个世纪的发展,积累了丰富经验,通过分析美国、日本、欧洲等国家和地区的普速、高速铁路,在运营效率评价、运营安全评价、服务质量评价、经营效益评价、安全保障法律法规建设和第三方评价机构发展等方面的现状,从客户服务质量评价、安全评价标准体系建立、效率效益导向的经营效益评价机制建设、第三方专业评价机构发展等维度,总结对我国高速铁路运营安全效益评价的经验借鉴及启示。     

Exploring passenger anxiety associated with train travel

Although people are often encouraged to use public transportation, the riding experience is not always comfortable. This study uses service items to measure passenger anxieties by applying a conceptual model based on the railway passenger service chain perspective. Passenger anxieties associated with train travel are measured using a modern psychometric method, the Rasch model. This study surveys 412 train passengers. Analytical results indicate that the following service items cause passenger anxiety during trains travel: crowding, delays, accessibility to a railway station, searching for the right train on a platform, and transferring trains. Empirical results obtained using the Rasch approach can be used to derive an effective strategy to reduce train passenger anxiety. This empirical study also demonstrates that anxiety differs based on passenger sex, age, riding frequency, and trip type. This information will also prove useful for transportation planners and policy-makers when considering the special travel needs of certain groups to create a user-friendly railway travel environment that promotes public use.     

An efficient realization of deep learning for traffic data imputation

Traffic data provide the basis for both research and applications in transportation control, management, and evaluation, but real-world traffic data collected from loop detectors or other sensors often contain corrupted or missing data points which need to be imputed for traffic analysis. For this end, here we propose a deep learning model named denoising stacked autoencoders for traffic data imputation. We tested and evaluated the model performance with consideration of both temporal and spatial factors. Through these experiments and evaluation results, we developed an algorithm for efficient realization of deep learning for traffic data imputation by training the model hierarchically using the full set of data from all vehicle detector stations. Using data provided by Caltrans PeMS, we have shown that the mean absolute error of the proposed realization is under 10 veh/5-min, a better performance compared with other popular models: the history model, ARIMA model and BP neural network model. We further investigated why the deep leaning model works well for traffic data imputation by visualizing the features extracted by the first hidden layer. Clearly, this work has demonstrated the effectiveness as well as efficiency of deep learning in the field of traffic data imputation and analysis.     

Measuring production and consumption efficiencies using the slack‐based measure network data envelopment analysis approach: the case of low‐cost carriers

One of the most important outcomes of the deregulation of air transportation policy is the emergence of low‐cost carriers (LCCs) around the world. Although LCC airlines have been in operation for more than 30 years, not every LCC is successful. In order to reduce the inefficiencies of LCCs, this paper measures the performance of LCCs by using slack‐based measure network data envelopment analysis. This model combines both the production process with input orientation and the consumption process with output orientation into a unified model. Furthermore, envelopment map analysis LCCs are performed to determine the reasons for the LCCs' inefficiency and how improvements can be made. A sample of 16 low‐cost airlines from Europe, the USA, and Asia were selected for operational performance analysis. The results show that the main reason for easyJet's, US Airways', and Virgin Blue's inefficiency is production inefficiency, so these LCCs should reduce their input quantities to increase efficiency. Jet2, Aer Lingus, and JetBlue were, by contrast, found to be consumption inefficient; these LCCs should increase their output quantities in order to enhance performance. Copyright © 2012 John Wiley & Sons, Ltd.     

Automated real-time railway traffic control: an experimental analysis of reliability,resilience and robustness

Railway transportation provides sustainable, fast and safe transport. Its attractiveness is linked to a broad concept of service reliability: the capability to adhere to a timetable in the presence of delays perturbing traffic. To counter these phenomena, real-time rescheduling can be used, changing train orders and times, according to rules of thumb, or mathematical optimization models, minimizing delays or maximizing punctuality. In the literature, different indices of robustness, reliability and resilience are defined for railway traffic. We review and evaluate these indices applied to railway traffic control, comparing optimal rescheduling approaches such as Open Loop and Closed Loop control, to a typical First-Come-First-Served dispatching rule, and following the timetable (no-action). This experimental analysis clarifies the benefits of automated traffic control for infrastructure managers, railway operators and passengers. The timetable order, normally used in assessing a-priori reliability, systematically overestimates unreliability of operations that can be reduced by real-time control.     

Closing the loop in real-time railway control: Framework design and impacts on operations

Railway traffic is heavily affected by disturbances and/or disruptions, which are often cause of delays and low performance of train services. The impact and the propagation of such delays can be mitigated by relying on automatic tools for rescheduling traffic in real-time. These tools predict future track conflict based on current train information and provide suitable control measures (e.g. reordering, retiming and/or rerouting) by using advanced mathematical models. A growing literature is available on these tools, but their effects on real operations are blurry and not yet well known, due to the very scarce implementation of such systems in practice.In this paper we widen the knowledge on how automatic real-time rescheduling tools can influence train performance when interfaced with railway operations. To this purpose we build up a novel traffic control framework that couples the state-of-the art automatic rescheduling tool ROMA, with the realistic railway traffic simulation environment EGTRAIN, used as a surrogate of the real field. At regular times ROMA is fed with current traffic information measured from the field (i.e. EGTRAIN) in order to predict possible conflicts and compute (sub) optimal control measures that minimize the max consecutive delay on the network. We test the impact of the traffic control framework based on different types of interaction (i.e. open loop, multiple open loop, closed loop) between the rescheduling tool and the simulation environment as well as different combinations of parameter values (such as the rescheduling interval and prediction horizon). The influence of different traffic prediction models (assuming e.g. aggressive versus conservative driving behaviour) is also investigated together with the effects on traffic due to control delays of the dispatcher in implementing the control measures computed by the rescheduling tool.Results obtained for the Dutch railway corridor Utrecht–Den Bosch show that a closed loop interaction outperforms both the multiple open loop and the open loop approaches, especially with large control delays and limited information on train entrance delays and dwell times. A slow rescheduling frequency and a large prediction horizon improve the quality of the control measure. A limited control delay and a conservative prediction of train speed help filtering out uncertain traffic dynamics thereby increasing the effectiveness of the implemented measures.     

An application of the directional distance function with the number of accidents as an undesirable output to measure the technical efficiency of state road transport in India

By using the directional distance function (DDF) of data envelopment analysis (DEA), this study measures the technical efficiency of 37 Indian state road transport undertakings (SRTUs) for the year 2012–13. We employ the DDF as a tool for analyzing a joint production function with both desirable and undesirable outputs (i.e., the number of accidents). A comparison between the results with and without accidents shows that several SRTUs have experienced significant changes in their efficiency scores as well as in their rankings after accounting for the undesirable output. This indicates the importance of including the number of accidents – a safety standard – as representative of the undesirable output in computing the efficiency scores of SRTUs. The results of the Tobit model indicate that SRTUs with greater vehicle productivity are more efficient under both conventional DEA and DDF approaches. We also employed zero-truncated negative binomial model to assess the factors influencing the number of road accident experienced by the Indian SRTUs and found that the accident count was significantly influenced by fleet utilization and vehicle productivity.     

Impact of service network topology on air transportation efficiency

Each stakeholder in the air transportation system has a different perspective on the performance efficiency metrics, making analysis of system-wide design options very difficult. This paper uses topological structures of service networks to examine trade-offs between efficiency metrics established around the passenger, airline, and air navigation service provider perspectives. The findings indicate that the scale-free type topologies are preferred under most of the metrics. However, with enough density, random topologies become more appealing with its high robustness feature and performance comparable to scale-free.     

动卧客运与快递货运的高速铁路夜间能力利用模式

目前我国高速铁路的日间行车能力已得到了较为充分的利用,而如何组织好高铁夜间垂直天窗与夜行列车之间的耦合关系、用好高铁夜间能力,是适应多样化市场需求的需要,也是进一步提升高铁经营效益的有效途径。对此,本文提出了动卧列车和货运动车组两种相对可行的高铁夜间运输产品,分别对其产品特征进行了分析,充分考虑高铁夜间天窗制约下两种列车的开行模式,基于市场需求提出了列车开行策略,并在充分对比两种产品的经济效益、客(货)源组织、能力分配等因素的基础上,给出了高铁夜间能力发展建议。     

Performance indicators for public transit connectivity in multi-modal transportation networks

Connectivity plays a crucial role as agencies at the federal and state level focus on expanding the public transit system to meet the demands of a multimodal transportation system. Transit agencies have a need to explore mechanisms to improve connectivity by improving transit service. This requires a systemic approach to develop measures that can prioritize the allocation of funding to locations that provide greater connectivity, or in some cases direct funding towards underperforming areas. The concept of connectivity is well documented in social network literature and to some extent, transportation engineering literature. However, connectivity measures have limited capability to analyze multi-modal public transportation systems which are much more complex in nature than highway networks.In this paper, we propose measures to determine connectivity from a graph theoretical approach for all levels of transit service coverage integrating routes, schedules, socio-economic, demographic and spatial activity patterns. The objective of using connectivity as an indicator is to quantify and evaluate transit service in terms of prioritizing transit locations for funding; providing service delivery strategies, especially for areas with large multi-jurisdictional, multi-modal transit networks; providing an indicator of multi-level transit capacity for planning purposes; assessing the effectiveness and efficiency for node/stop prioritization; and making a user friendly tool to determine locations with highest connectivity while choosing transit as a mode of travel. An example problem shows how the graph theoretical approach can be used as a tool to incorporate transit specific variables in the indicator formulations and compares the advantage of the proposed approach compared to its previous counterparts. Then the proposed framework is applied to the comprehensive transit network in the Washington–Baltimore region. The proposed analysis offers reliable indicators that can be used as tools for determining the transit connectivity of a multimodal transportation network.