The impact of environmental variables on the efficiency of Chinese and other non-Chinese airlines

Wu, Yue; He, Changzheng; Cao, Xuefei

doi:10.1016/j.jairtraman.2013.02.004

Cited by 31 publications

(15 citation statements)

References 7 publications

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“…Given the relative importance of China to the world economy, it is possible to affirm that Chinese airlines consist of a relatively understudied topic. As a matter of fact, only a few studies were devoted to this particular industry (Chow, 2010 andWu et al, 2013;.…”

Section: Introductionmentioning

confidence: 99%

“…It finally finds that Chinese airlines' productivity has improved significantly in the past decade, but still lags behind that of industry leaders. Meanwhile, Cui and Li (2015) use DEA and the Malmquist index to calculate the civil aviation safety efficiency of ten Chinese airline companies from 2008 to 2012, and the Panel Regression Model is usedto identify the important influencing factors on civil aviation safety efficiency Wu et al (2013). employ DEA to evaluate the operational efficiency and a bootstrapped truncated regression to explore the impact of environmental variables on efficiency of Chinese and non-Chinese airlines.…”

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confidence: 99%

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A structural vector autoregressive model of technical efficiency and delays with an application to Chinese airlines

Tsionas

Chen

2017

Transportation Research Part A: Policy and Practice

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This study reports on the performance assessment of Chinese airlines from 2006-2014 using a stochastic distance function where technical efficiency and a measure of flight delays follow a joint structural autoregressive process. This model is used to investigate whether technical efficiency causes flight punctuality or the other way around. The model, however, yields a non-trivial likelihood function and is not amenable to estimation using least squares or standard maximum likelihood techniques. To estimate the model therefore, we propose and implement maximum simulated likelihood with importance sampling. The results suggest a mutual dependence (feedback) between technical efficiency and delays. Policy implications are derived.

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Section: Introductionmentioning

confidence: 99%

mentioning

confidence: 99%

A structural vector autoregressive model of technical efficiency and delays with an application to Chinese airlines

Tsionas

Chen

2017

Transportation Research Part A: Policy and Practice

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“…Scheraga (2004) applies the input-oriented CCR model to measure the efficiency performance of 37 international airlines in 2000 and then uses Tobit analysis to relate the efficiency measure to expenditures on operations, passenger services, and ticketing, promotion, and sales. The standard CRS DEA models are used to evaluate the operational efficiency of 12 airlines in Asia, Europe, and the United States during the 2006À2010 period in Wu, He, and Cao (2013), and a bootstrapped truncated regression is then applied to explore the impact of international operation, cargo traffic, and employee salary levels on the observed operational efficiency levels. Other studies using the two-stage DEA-Tobit approach include Joo and Fowler (2014), Merkert and Hensher (2011), Barros and Peypoch (2009), Assaf and Josiassen (2011), etc.…”

Section: Gross Productivity and Residual Productivity Or Efficiencymentioning

confidence: 99%

“…Chinese carriers have improved their productivity significantly over the last decade, but still lags behind that of industry leaders Wu et al (2013) Two-stage DEA 12 international airlines: 2006À2010…”

Section: European and Us Airlines In 1992à1995mentioning

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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“…Jiang et al (2003) provided a forecast of China's air cargo demand through 2020 based on the association between economic development and air cargo traffic. Wu et al (2013) also concluded that rising demand provided Chinese airlines with opportunities to develop air cargo business. Air cargo is likely to become some Chinese airlines' primary business rather than by-product ( Merkert et al, 2017 ).…”

Section: Introductionmentioning

confidence: 99%

A SWOT analysis of China's air cargo sector in the context of COVID-19 pandemic

2020

Journal of Air Transport Management

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This paper discusses the situation of China's air cargo sector facing the COVID-19 pandemic. Based on the expectation that it can go out of recession more easily than China's air passenger sector, this paper analyzes four aspects that are favorable and unfavorable for its further development: (1) strengths (China's sustainable economic basis and proliferating cargo suppliers), (2) weaknesses (insufficient cargo capacity and less business internationalization), (3) opportunities (top authority support, rising e-commerce demand, and new technological momentum), and (4) challenges (uncertain trade environment and increasing profitability pressure). Then this paper suggests strategies for China's air cargo suppliers to adapt to the pandemic.

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The impact of environmental variables on the efficiency of Chinese and other non-Chinese airlines

Cited by 31 publications

References 7 publications

A structural vector autoregressive model of technical efficiency and delays with an application to Chinese airlines

A structural vector autoregressive model of technical efficiency and delays with an application to Chinese airlines

Airline Productivity and Efficiency: Concept, Measurement, and Applications

A SWOT analysis of China's air cargo sector in the context of COVID-19 pandemic

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