Evaluating airlines with slack‐based measures and meta‐frontiers

This study develops a new performance evaluation model, called the meta dynamic network slack‐based measure (MDN‐SBM). This model incorporates the concept of meta‐frontiers to facilitate comparisons of performance of decision making units, while at the same time it generalizes the slack‐based measure (SBM), network SBM, and dynamic SBM. This MDN‐SBM model is capable of dealing with two important special features of the transportation industry: unfavorable accidents and non‐storable goods, i.e. available seat‐kilometers that are wasting assets that lose value completely if unsold before departure. Hence, this generalized model contains higher differentiable capability than all its SBM‐related submodels in the literature. To demonstrate, 35 international airlines with two divisions (production and consumption) in three terms (one‐year time periods from 2007 to 2009) have been analyzed using meta‐performance efficiency measures (ME) for all decision making units and have also been compared by geographical area (Asia‐Pacific, N. America/Europe). The numerical example and comparison validate the proposed MDN‐SBM model and suggest the airlines should put more focus on input resources reduction for productivity improvement. Copyright © 2016 John Wiley & Sons, Ltd.     

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.     

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.     

Seaport performance analysis using robust non-parametric efficiency estimators

Abstract

Seaport services have been developing year on year, playing an increasingly important role in the economy and the transportation markets of each country. This increases interest in measuring their performance. This paper evaluates the performance of a set of European seaports by means of robust non-parametric approaches. Using order-m and bootstrap procedures, the major problems of traditional data envelopment analysis and free disposal hull methods – concerning noise, presence of outliers and the ‘curse of dimensionality’ – are overcome. With this study considerable levels of inefficiency were found in the European seaports sector.     

The evaluation of transportation energy efficiency: An application of three-stage virtual frontier DEA

In this paper, transportation energy efficiency is newly defined and its inputs and outputs are obtained through literature review. Labor input, capital input and energy input are selected as the inputs, passenger turnover volume and freight turnover volume are defined as the outputs. A new model—three-stage virtual frontier DEA (three-stage virtual frontier Data Envelopment Analysis) is proposed to evaluate transportation energy efficiencies. The case of thirty Chinese PARs (provincial administrative regions) from 2003 to 2012 is applied to verify its rationality. In the three-stage virtual frontier DEA, the reference DMU (decision-making unit) set and the evaluated DMU set are two different sets so that it can distinguish the DEA efficient DMUs. And in the evaluating process, the reference DMU set remains unchanged to assure its results more reasonable than Super DEA model. The results show that transport structure and management measures have important impacts on transportation energy efficiency.     

Evaluating efficiency in the Norwegian bus industry using data envelopment analysis

This paper focuses on the performance of Norwegian bus companies subsidized by the government. The performance is evaluated from a productive efficiency point of view. The framework is that of a deterministic non-parametric Data Envelopment Analysis (DEA) approach to efficiency measurement. In this context several important issues are addressed: efficiency rankings, distribution and scale properties in the bus industry, potentials for efficiency improvements in the sector, the impact of ownership, area of operation and scope, and ways of improving efficiency in the sector. The findings show that the average bus company exhibits increasing return to scale in production of its services. The extent of such returns however vary, with size and is more prevalent among smaller companies. The average bus company is found to have a considerable input saving potential of about 28 percent. Neither economies of scope nor company ownership are found to have an influence on company performance. It is suggested that geographical factors need a closer attention in future research. The implications of DEA results are discussed and concluding remarks offered.     

A data envelopment analysis model for evaluating the performance of taxi operators: a case study in Harbin,China

ABSTRACT

This paper measures the performance of taxi operators using data envelopment analysis (DEA) and the improvement of performance based on benchmarks. This includes basic DEA models and a cross efficiency model. In the present work, a sample set of 20 taxi operators are considered, and an evaluation indicator framework is constructed, which mainly involves the identification of decision-making units (DMUs) and the determination of input-output variables. The combined results of multiple DEA models are used to evaluate the performance of taxi operators in a case study of Harbin. The results highlight the significance of the combined application of multiple DEA models, especially a cross-efficiency model that can obtain more objective efficiency values. Finally, the benchmarking method is used to capture the achievements of best-performing operators and provide valuable improvement recommendations for inefficient operators. Conclusions provide a suitable basis for the operation and management of the taxi market.     

Measuring the energy efficiency for airlines under the pressure of being included into the EU ETS

In 2008, European Union (EU) announced that from 2012, each international flight taking off and landing in EU would be given an emission permit. Therefore, the period of 2008–2012 can be regarded as a buffer period for global airlines. Although EU formally decides to exclude non‐EU airlines from the EU Emission Trading System on March 4, 2014, it is necessary to investigate the impacts of the policy on airline energy efficiency in this period. Airline energy efficiency is divided into three stages—operations stage, service stage, and sales stage—and Greenhouse gas emission is treated as an undesirable output of service stage. Two models, network range‐adjusted measure model with weak disposability and network range‐adjusted measure model with strong disposability, are established to evaluate the efficiencies of 22 international airlines from 2008 to 2012. The results show that (i) most airlines' efficiencies have decreased in the period, and the EU Emission Trading System is not effective for the efficiency improvement; (ii) the average efficiency of European airlines is almost the same as that of non‐European airlines; and (iii) the model with weak disposability is more reasonable in distinguishing efficiency differences, while strong disposability is a more reasonable way in treating undesirable outputs. Copyright © 2016 John Wiley & Sons, Ltd.     

A bus route evaluation model based on GIS and super-efficient data envelopment analysis

When compared to large cities in developed countries, the shares of public transportation in most Chinese cities are low. Increasing the competitiveness of urban public transportation remains an urgent problem. A capable evaluation method for public transportation is required to assist the development of urban transit systems. This paper focuses on the bus system. Being devoid of standard criteria, it is difficult to determine the efficiency of a transit system or any bus line using a single evaluation index. This paper proposes a comparative analysis to evaluate bus lines so as to filter out candidates for further optimization. From the viewpoints of transit planning, operation and quality of service, this paper establishes 10 subordinate evaluation indices and then uses geographical information system tools, global positioning system data and smart card data to assist the index definition and calculation. Super-efficient data envelopment analysis (DEA) method is adopted for the proposed single factor and comprehensive evaluation models. Finally, the bus system in Shenzhen, China is used as a case study. The comparable significant results validate the capability of the proposed model.     

Efficiency measurement of bus routes and exogenous operating environment effects on efficiency

This study develops an independent efficiency measurement model framework of bus routes, so as to treat preferably the heterogeneous outputs in a data envelopment analysis (DEA)-based efficiency measurement. It then introduces four new exogenous operating environment factors at the microscopic level of bus routes, and applies the three-stage DEA approach to incorporate operating environment effects and statistical noise into the efficiency measurement framework. The main purpose is to measure impartially the managerial efficiency of bus routes, purged of operating environment effects and statistical noise, and additionally to investigate the operating environment effects on efficiency. An empirical analysis, based on 39 routes operated in Jiangyin City, China, is presented. The principal finding is that the adoption of the independent efficiency measurement model framework is reasonable and has many virtues. Moreover, the proposed approach could substantially provide decision support both for regulators and for producers of bus services. In addition, the operating environment does indeed significantly affect operating efficiency and quality efficiency, especially the latter.     

Cost-efficiency benchmarking of European air navigation service providers

This study uses EUROCONTROL data on operating performance of the national air navigation service providers over the 2002–2011 time period to document in detail the efficiency changes across providers and time using data envelopment analysis. Our results suggest that overall providers’ productivity improved over the time period covered by the data, driven by improvements in technical rather than allocative efficiency. However, some trend reversals in the post-2008 crisis period are also observed.     

Sustainability assessment of inland transportation in China: A triple bottom line-based network DEA approach

The transport sector accounts for nearly one third of the world’s total energy use, while inland transport alone is responsible for half of the global petroleum consumption. The expansion of motorization in newly industrialized economies necessitates setting realistic targets. To support decision-makers in better assessment of transport sustainability performance, we introduce a systematic triple bottom line-based approach to evaluate inland transport, considering social, economic, and environmental dimensions of sustainability. The proposed network data envelopment analysis (DEA) measure organizes the three components of the system into a parallel structure, allocates shared input across subsystems, and incorporates undesirable output. The empirical application determines the efficiency of regional inland transportation systems in China from 2006 to 2015. The results indicate a rise in overall transport efficiency between China’s 11th and 12th five-year development plan periods and link the economic growth with a decrease in environmental transport efficiency in the Central and Western zones and with a decline in social efficiency in the Eastern zone. Since 2012, the social sustainability remains the weakest component of inland transport, which requires special attention by policy-makers to support vulnerable groups of transport users. This study provides further insight into the investigated measures and proposes recommendations for the improvement of inland transport in China.     

Evaluating sustainability of supply chains by two-stage range directional measure in the presence of negative data

Assessing sustainability of supply chains is a critical and increasingly complex problem. In recent years sustainability has received more attention in supply chain management (SCM) literature with triple bottom lines including social, environmental, and economic factors. Conventional data envelopment analysis (DEA) models consider decision making units (DMUs) as black boxes that consume a set of inputs to produce a set of outputs and do not take into consideration internal interactions of DMUs. Two-stage DEA models deal with such DMUs. However, existing two-stage DEA models are applicable only in technologies characterized by positive inputs/outputs. This paper aims to build and present a new two-stage DEA model considering negative input-intermediate-output data. Some numerical examples along with some theorems and properties are given to show capability of proposed method. The proposed ideas are used in a case study where 29 Iranian supply chains producing equipment of expendable medical devices are evaluated in terms of sustainability.     

Additive models for network data envelopment analysis in the presence of shared resources

This paper studies the problem of evaluating the relative efficiency of a set of specialized and interdependent decision-making subunits that make up a large decision-making unit (DMU). The paper develops a data envelopment analysis (DEA) approach for measuring the efficiency of decision processes which can be divided into two stages. In these processes the first stage uses its own inputs to generate outputs which a part of these outputs become the inputs to the second stage. Moreover, DMUs use shared input sources in both operation stages. This paper provides a set of additive models which measure the performance of two-stage network DEA processes with shared inputs. Numerical examples show the applicability of the approach.     

Improving the efficiency of repeated dynamic network loading through marginal simulation

Currently, the applicability of macroscopic Dynamic Network Loading (DNL) models for large-scale problems such as network-wide traffic management, reliability and vulnerability studies, network design, traffic flow optimization and dynamic origin–destination (OD) estimation is computationally problematic. The main reason is that these applications require a large number of DNL runs to be performed. Marginal DNL simulation, introduced in this paper, exploits the fact that the successive simulations often exhibit a large overlap. Through marginal simulation, repeated DNL simulations can be performed much faster by approximating each simulation as a variation to a base scenario. Thus, repetition of identical calculations is largely avoided. The marginal DNL algorithm that is presented, the Marginal Computation (MaC) algorithm, is based on first order kinematic wave theory. Hence, it realistically captures congestion dynamics. MaC can simulate both demand and supply variations, making it useful for a wide range of DNL applications. Case studies on different types of networks are presented to illustrate its performance.     

Eco-design of transportation in sustainable supply chain management: A DEA-like method

This study addresses the issue of eco-design for transportation in sustainable supply chain management (SSCM). Data envelopment analysis (DEA) is adopted and extended to construct a model for this application. This proposed model, together with the tractable algorithm developed in this research, can provide stakeholders with a Pareto Optimal transportation strategy. This derived transportation strategy can help stakeholders realize certain transportation goals with less resource consumption and pollution emission. The discussion presented leads to a heuristic Joint Transportation Policy and concludes with two useful suggestions for putting the strategy into practice. The proposed model was used in an empirical study of design sustainable transportation mechanism for one air-condition manufacturer in China to transport its products as well, the analysis further demonstrating the theoretical and practical value of this research.     

A multi-objective analysis of a rural road network problem in the hilly regions of Nepal

This paper considers the rural road network upgrading problem, using a multi-objective optimization model, to support decision-makers in the choice of roads to upgrade in the hilly regions of Nepal. The model considers two objectives: minimization of user operation costs and maximization of population covered. The problem was solved for a real-world rural road network in the Gorkha district of Nepal. For this case, all non-dominated solutions were obtained and the ones providing more interesting trade-offs were analysed. The model was found suitable for the case under study, and possibly, easily extendable to rural areas of other developing countries.     

A multiple correspondence analysis of at‐fault motorcycle‐involved crashes in Alabama

According to the U.S. National Highway Traffic Safety Administration, in 2012, more than 4950 motorcyclists were killed in traffic accidents. Compared to passenger car occupants, mile for mile, motorcyclists are more than 26 times more at risk to dying in crashes. Due to the high fatality rate associated with motorcycle crashes, factors contributing to this type of crash must be identified in order to implement effective safety countermeasures. Given that the available datasets are large and complex, identifying the key factors contributing to crashes is a challenging task. Using multiple correspondence analysis, as an exploratory data analysis technique to determine the dataset structure, we identified the roadway/environmental, motorcycle, and motorcyclist‐related variables influencing at‐fault motorcycle‐involved crashes. This study used the latest available dataset (2009 to 2013) from the Critical Analysis Reporting Environment database to study motorcycle crashes in the state of Alabama. The most significant contributors to the frequency and severity of at‐fault motorcycle‐involved crashes were found to be light conditions, time of day, driver condition, and weather conditions. Copyright © 2017 John Wiley & Sons, Ltd.     

A bibliometric analysis on trends and characters of carbon emissions from transport sector

Transport sector’s substantial contribution to global greenhouse gas emissions has made it a growing area of study and concern. In order to identify trends and characteristics of carbon emissions research in the transportation sector we conducted a Bibexcel and complex network analysis for the period 1997–2016. In addition, we identify critical themes and contributions of research articles using h-index, PageRank and cluster analysis. We report contribution of countries, authors, institutions and journals, as well as performance of citations and keywords. Co-citing situations between different countries, authors, and institutions are also analyzed using network analysis. Between 1997 and 2016 we found a rise in publications on carbon emissions in the transportation sector and increased cooperation between countries, authors, and institutions. Authors from the USA, China and United Kingdom published the most articles and articles with the highest academic influence. Tsinghua University from China is the leading institution in carbon emissions research in the transportation sector. The most widely published author and cited author is Dr. He. We conclude our analysis by analyzing keywords and trends to suggest critical topic areas of future research. The systematic approach undertaken in this study can be extended and applied to other research topics and fields.