An evaluation of the world's major airlines' technical and environmental performance

Arjomandi, Amir; Seufert, Juergen H.

doi:10.1016/j.econmod.2014.05.002

Cited by 93 publications

(44 citation statements)

References 49 publications

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“…Airlines can overcome the tradeoff between quality and productivity. Arjomandi and Seufert (2014) 48 while dealing with rising energy and labor costs (Airlines for America, 2013). US airlines can accomplish this by reducing operating expenses, increasing operating revenue, or a strategic combination of both.…”

Section: Motivation and Contextual Settingmentioning

confidence: 99%

Efficiency of US airlines: A strategic operating model

Mallikarjun

2015

Journal of Air Transport Management

121

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Section: Motivation and Contextual Settingmentioning

confidence: 99%

Efficiency of US airlines: A strategic operating model

Mallikarjun

2015

Journal of Air Transport Management

121

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“…Li et al [35] conducted an analysis of impacts of included aviation into EU ETS on airline efficiency for 22 international airlines from 2008 to 2012 through three stages-i.e., operations, services and sales-using a Network Slacks-Based Measure with weak disposability and Network Slacks-Based Measure with strong disposability. Technical and environmental performance evaluation for major airlines from China, north Asia, and Europe over the period 2007-2010 was studied by Arjomandi and Seufert [36]. Egilmez and Park [24] quantified transportation related carbon, energy and water footprints of U.S. manufacturing sectors and evaluated environmental vs. economic performance based on eco-efficiency scores.…”

mentioning

confidence: 99%

Evaluation of Energy-Environment Efficiency of European Transport Sectors: Non-Radial DEA and TOPSIS Approach

Djordjević

Krmac

2019

Energies

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Transport is recognized as a major energy consumer and environment pollutant. Recently scholars have paid considerable attention to the evaluation of transport energy and environmental efficiency (EEE). In this paper, the non-radial Data Envelopment Analysis (DEA) model was employed to evaluate EEE on a macro level-i.e., of European road, rail and air sectors. The evaluation was conducted under the joint production framework, which considers energy and non-energy inputs, and desirable and undesirable outputs for the last ten years period. To rank decision-making units and check the aptness of this non-radial DEA model in transport EEE evaluation, the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method has been proposed. An empirical study has been conducted for as many European countries as possible, depending on availability of data. Based on the non-radial DEA model, it could be said that the level of EEE is improving for the road sector, while many evaluated countries have low EEE for the rail transport sector. Additionally, results have indicated that the TOPSIS method is more suitable than the non-radial DEA model in transport EEE evaluation and for identification of best practices.Energies 2019, 12, 2907 The Aim and the Scope of the PaperThe aim of this paper is twofold. The first is to evaluate and analyze the changes of EEE of European road, air, and rail transport sectors, where the methodology for evaluating EEE is based on a non-radial DEA model proposed by Wu et al. [6] for 2006-2008, 2010, 2012, and 2014-2016, using the available data for the European countries which represent DMUs. The second aim of the paper is the introduction of the TOPSIS method in the evaluation of EEE, where the TOPSIS method is used for the ranking of DMUs. The evaluation of transport EEE has been done under the joint production framework, using non-energy inputs (labor and transport assets) and energy input (energy consumption) to produce desirable outputs (volume of passenger and freight transport) and undesirable output (GHG emissions). Aside from other widely used non-radial DEA models such as Slack-based models, Russell measure models, and Directional distance function, in this paper, the non-radial DEA model has been chosen due to its ability to use different non-proportional adjustments, with decision maker specified weights assigned to each efficiency score, and because of its ability to proportionally decrease the amounts of energy inputs and undesirable outputs simultaneously as much as possible [5,6].The main contributions of this study are: (i) a newly systematic literature review in the field of transport EEE evaluation, (ii) a new definition of transport EEE, (iii) the evaluation of EEE with an extended set of used inputs, (iv) the evaluation of EEE of road, air, and rail transport sectors of European countries and their changing tendencies in terms of the EEE, (v) use of non-radial DEA and introduction of the TOPSIS method through DMUs ranking in the evaluation of transport EEE, ...

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“…Labor input is often measured by number of full time equivalent employees or employee hours. However, some authors classify employees into different categories and compute a weighted labor input (index) with relative salaries of the different categories as weights (Marin, 1998), and some consider flying personnel only (Arjomandi & Seufert, 2014). Fuel input is commonly measured by total gallons of fuel consumed.…”

Section: Airline Inputs and Outputsmentioning

confidence: 99%

“…Applying bootstrapped DEA models, Arjomandi and Seufert (2014) analyze 48 airlines during the 2007À2010 period in terms of both technical and environmental efficiency. They incorporate ton kilometers performed as a desirable output and CO 2 emission as an undesirable output in the DEA computation.…”

Section: Energy Efficiency Environmental Efficiency and Social Effimentioning

confidence: 99%

Airline Productivity and Efficiency: Concept, Measurement, and Applications

Yu¹

2016

Advances in Airline Economics

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This chapter provides a survey of alternative methodologies for measuring and comparing productivity and efficiency of airlines, and reviews representative empirical studies. The survey shows the apparent shift from index procedures and traditional OLS estimation of production and cost functions to stochastic frontier methods and Data Envelopment Analysis (DEA) methods over the past three decades. Most of the airline productivity and efficiency studies over the last decade adopt some variant of DEA methods. Researchers in the 1980s and 1990s were mostly interested in the effects of deregulation and liberalization on airline productivity and efficiency as well as the effects of ownership and governance structure. Since the 2000s, however, studies tend to focus on how business models and management strategies affect the performance of airlines. Environmental efficiency now becomes an important area of airline productivity and efficiency studies, focusing on CO 2 emission as a negative or undesirable output. Despite the fact that quality of service is an important aspect of airline business, limited attempts have been made to incorporate quality of service in productivity and efficiency analysis.The literature on airline productivity and efficiency is vast and encompasses different methodologies, ranging from simple ratio analysis to complex mathematical programming and econometric modeling. These studies investigate the effects of regulation and deregulation on airline performance in domestic or international markets, examine how ownership and governance have affected airline productivity and efficiency, and investigate the impacts of airline management strategies and-/or business models on productivity and efficiency.Surprisingly, there have been few, if any, comprehensive surveys and reviews of these studies. Pollack (1979) is perhaps the earliest survey of airline productivity measures. The paper, however, focuses on the description of various measures of so-called "resource activities," such as number of employees, number of stations, and number of flight departures, and its discussions on productivity measures are limited to a listing of a few "common productivity measures" including available seat miles per employee, number of aircraft miles per unit of fuel, etc. Rich (2004) reviews the literature on productivity growth in transportation industries including air transport, focusing on the impacts of changing technology and labor relations. Although not a survey paper, Mallikarjun (2015) provides a good summary of literature on airline productivity and efficiency.This chapter provides a survey of alternative methodologies 1 for measuring and comparing productivity and efficiency of airlines, and reviews representative empirical studies. The next section discusses the conceptual definition of productivity and productive efficiency. The section "Airline Inputs and Outputs" reviews various inputs and outputs that have been identified and used to measure airline productivity. The section "Non-Parametric and Index...

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An evaluation of the world's major airlines' technical and environmental performance

Cited by 93 publications

References 49 publications

Efficiency of US airlines: A strategic operating model

Efficiency of US airlines: A strategic operating model

Evaluation of Energy-Environment Efficiency of European Transport Sectors: Non-Radial DEA and TOPSIS Approach

Airline Productivity and Efficiency: Concept, Measurement, and Applications

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