Passenger facility charge vs. airport improvement program funds: A dynamic network DEA analysis for U.S. airport financing

Chang, Young Tae; Park, Hyosoo Kevin; Zou, Bo; Kafle, Nabin

doi:10.1016/j.tre.2016.02.001

Cited by 39 publications

(8 citation statements)

References 30 publications

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“…The primary merit of their model is that the inputs or outputs do not necessarily need to be improved equiproportionally, and the worst aspects of firm operation are emphasized. Chang, Park, Zou, and Kafle (2016c) examined the financing reform of the U.S. airports in a dynamic network framework. In particularly, substitutability between the passenger facility charge and airport improvement funds, which are the two major financing sources of the U.S. airports, were analyzed.…”

Section: Efficiency Analysismentioning

confidence: 99%

“…To find the determining factors on cruise efficiency, a regression model is used. Numerous existent papers (Barros, 2004;Chang et al, 2016c;Gillen & Lall, 1997;Zou, Kafle, Chang, & Park, 2015) applied Tobit regression for this purpose, which assumes a censored normal distribution, for efficiency scores are one at best. Simar and Wilson (2007), however, argued that the application of Tobit regression is erroneous because it ignores the data generating process (DGP) of observed variables.…”

Section: Bootstrapped Truncated Regressionmentioning

confidence: 99%

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Efficiency analysis of major cruise lines

2017

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h i g h l i g h t sThis study measured the efficiency of the top three cruise lines Network DEA and bootstrapped-truncated regression were used They were efficient at the operating stage, but varied at the non-operating stage Cruise lines attempting high capacity expansion were relatively inefficient Neglected hedging policy over financial risks also contributed to the inefficiency a b s t r a c t Three major cruise lines account for 82% of the total market share. Their financial statements show different results between the operating incomes and net incomes over time. To examine the major causes of the differences, this study measured the efficiency of the top three cruise lines to develop a network DEA model to analyze the cruise operations at two stages, namely operating and non-operating stages. In addition, the determinants of the efficiencies were examined using a bootstrapped-truncated regression model. Overall, cruise lines were efficient at the operating stage, but varied widely in the efficiency of the non-operating stage. Cruise lines attempting high capacity expansion were relatively inefficient because of the heavy interest payments arising from the high debt-to-capital ratio. Moreover, the neglected hedging policy regarding the financial risks also contributed to the inefficiency.

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Section: Efficiency Analysismentioning

confidence: 99%

Section: Bootstrapped Truncated Regressionmentioning

confidence: 99%

Efficiency analysis of major cruise lines

2017

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“…The study illustrated how management could better ascertain the interaction among each input resource that provides different levels of banking outcomes across time. Chang, Park, Zou, and Kafle () developed a new dynamic network DEA model to investigate the substitutability between airport improvement program and passenger facility charge. The novel model reflected more realistically airport production by decomposing it into aircraft loading and aircraft movement.…”

Section: Methodsmentioning

confidence: 99%

Improving innovation efficiency of emerging economies: The role of manufacturing

Wang

Hung

2019

Manage Decis Econ

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These studies have neglected that innovation activities in a country are generated by interactions among different sectors, especially manufacturing. The existing literature focusing on the influence of manufacturing on innovation indicated that an integrated pipeline of information technology, materials, and production process in manufacturing operation will provide manufacturers with the capability to bring renewed dynamism to this sector (Jagoda, Kiridena, & Lin, 2016). Manufacturing plays a critical role in innovative production by providing precision instruments and integrated systems that can efficiently transform investments in innovation into products (Cozzarin, 2016). However, studies rarely investigate the influence of manufacturing on the innovation process for emerging economies.This study provides an alternative model by characterizing the process of innovation via a three-stage model that emphasizes manufacturing effects. This model consists of human capital cultivation (Stage 1), manufacturing development (Stage 2), and innovation production (Stage 3). The dynamic network slacks-based measure (SBM), which can deal with multiple input/output variables of multidivisions in a long-term optimization, is employed to evaluate the performance of this three-stage model. This study also utilizes a truncated regression method to explore external factors, including enrollment rate in higher education, market size, intellectual property protection, and knowledge transfer (KT) that affect innovation efficiency. The empirical results may shed light on the importance of manufacturing to emerging economies in terms of improvement in the production of innovations. The structure of this study is presented as follows. Section 2 provides the literature review. Section 3 introduces the innovation model, data collection procedure, and research methodology. Section 4 addresses the experimental results. Section 5 provides managerial implications for innovation in emerging economies. Section 6 offers conclusions of this study.

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“…It has been employed in many studies to analyse the efficiency of many airports around the world. Several scholars use this approach to estimate airports' efficiency ( Bezerra and Gomes, 2016 ; Chang et al 2016 ; Fasone and Zapata-Aguirre, 2016 ). Ngo & Tsui (2020) used the Slack-Based Measure (SBM) DEA-Window Analysis model to address the small sample issue during the first-stage analysis and used an instrumental variable (IV) in the Tobit model to solve the endogeneity issue during the second-stage analysis.…”

Section: Literature Reviewmentioning

confidence: 99%

Evaluation of the Italian transport infrastructures: A technical and economic efficiency analysis

Sergi

D’Aleo²,

Arbolino

et al. 2020

Land Use Policy

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Highlights The deregulation process played a key role in terms of airport efficiency. The technical efficiency of 32 Italian airports has been evaluated. The methodological approach has been twofold: DEA and Tobit model. The main results show that efficiency is independent of an airport’s size. The findings highlight the decisive role of public shareholders in small airports.

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Passenger facility charge vs. airport improvement program funds: A dynamic network DEA analysis for U.S. airport financing

Cited by 39 publications

References 30 publications

Efficiency analysis of major cruise lines

Efficiency analysis of major cruise lines

Improving innovation efficiency of emerging economies: The role of manufacturing

Evaluation of the Italian transport infrastructures: A technical and economic efficiency analysis

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