Efficiency of US airlines: A strategic operating model

Mallikarjun, Sreekanth

doi:10.1016/j.jairtraman.2014.12.004

Cited by 117 publications

(45 citation statements)

References 68 publications

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“…If the efficiency of DMU i is 1, DMU i is technically an efficient DMU; if its efficiency less than 1, it is technically inefficient. Barros and Wanke (2015) 29 African airlines 2010-2013 Two-stage TOPSIS and neural networks Cui and Li (2015a) 11 international airlines 2008-2012 Virtual Frontier Benevolent DEA Cross Efficiency model Cui and Li (2015b) 10 Chinese airlines 2008-2012 Data Envelopment Analysis and Malmquist index Mallikarjun (2015) 27 US European airlines 2012 Three-stage unoriented network DEA To observe the slacks, many SBM models are proposed-SBM in Tone (2001) and some derived models such as SBM in Network DEA (Tone and Tsutsui, 2009) and SBM in Dynamic DEA (Tone and Tsutsui, 2010).…”

Section: Methodsmentioning

confidence: 99%

“…Following the structure of Mallikarjun (2015), in this paper, airline efficiency is divided into Operations Stage, Services Stage and Sales Stage. Different from Mallikarjun (2015) and referring to Lu et al (2012) and Tavassoli et al (2014), we apply Number of Employees (NE), Aviation Kerosene (AK) and Sales Costs (SC) to replace Operating Expenses, which makes the content of expenses more specific. Furthermore, we assign Sales Costs (SC) as the input of the Sales Stage to make the inputs more complete.…”

Section: The Efficiency Modelmentioning

confidence: 99%

“…For service effectiveness, passenger-plane-km and cargo-plane-km are the inputs to generate passenger-km and ton-km. We found an important work by Mallikarjun (2015) in that airline efficiency was firstly divided into three stages: Operations Stage, Services Stage and Sales Stage. In the operations Stage, the input is defined as Operating Expenses and the output is Available Seat Miles.…”

mentioning

confidence: 99%

See 2 more Smart Citations

Evaluating airline efficiency: An application of Virtual Frontier Network SBM

Wang

Cui

2015

Transportation Research Part E: Logistics and Transportation Re

115

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Section: Methodsmentioning

confidence: 99%

Section: The Efficiency Modelmentioning

confidence: 99%

mentioning

confidence: 99%

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Evaluating airline efficiency: An application of Virtual Frontier Network SBM

Wang

Cui

2015

Transportation Research Part E: Logistics and Transportation Re

115

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“…Airlines' productivity levels, either measured by TFP or RTFP, improved over the years, especially in the late 1990s and during the period from 2003 to 2007; but their productivity performance is not converging Kwan and Rutherford ( There is little difference in terms of production efficiency, but LCC performance better in terms of marketing efficiency Mallikarjun (2015) Three-stage DEA 27 US airlines in 2012 Major US airlines are more efficient than national US airlines in spending operating expenses and gaining operating revenue Marin (1998) Stochastic production function 10 European and 9 US airlines: 1980À1989…”

Section: Effects Of Deregulation and Liberalization On Productivity Amentioning

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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“…The network DEA models have been applied to evaluate the efficiency of a wide variety of applications, such as universities [10], electricity power production and distribution plants [11], investment trust corporations [12], production systems [13], sustainability of supply chain management systems [14,15], energy saving and emission reduction [16], banking [17], bus transit systems [18], airlines [19], and insurance industry [20].…”

Section: Introductionmentioning

confidence: 99%

A bargaining game model for performance assessment in network DEA considering sub-networks: a real case study in banking

Mahmoudi

Emrouznejad

Rasti−Barzoki

2018

Neural Comput & Applic

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Several network-data envelopment analysis (DEA) performance assessment models have been proposed in the literature; however, the conflicts between stages and insufficient number of decision-making units (DMUs) challenge the researchers. In this paper, a novel game-DEA model is proposed for efficiency assessment of network structure DMUs. We propose a two-stage modeling, where in the first stage network is divided into several sub-networks; we at the same time categorize input variables to measure efficiency of sub-networks within each input category. In the second stage, we calculate efficiency of the network by aggregating efficiency scores of sub-networks within each category. In this way, the issue of insufficient number of DMUs when there are many input/output variables can be handled as well. One of the main contributions of this paper is assuming each category and stage as a player in Nash bargaining game. Using the concept borrowed from Nash bargaining game model, the proposed game-DEA model tries to maximize distances of efficiency scores of each player form their corresponding breakdown points. The usefulness of the model is presented using a real case study to measure the efficiency of bank branches.

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Efficiency of US airlines: A strategic operating model

Cited by 117 publications

References 68 publications

Evaluating airline efficiency: An application of Virtual Frontier Network SBM

Evaluating airline efficiency: An application of Virtual Frontier Network SBM

Airline Productivity and Efficiency: Concept, Measurement, and Applications

A bargaining game model for performance assessment in network DEA considering sub-networks: a real case study in banking

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