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Evaluation of Airline Efficiency and Environmental Impacts Using Data Envelopment Analysis PDF

242 Pages·2017·2.59 MB·English
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Dissertations and Theses 8-2018 EEvvaalluuaattiioonn ooff AAiirrlliinnee EEffifficciieennccyy aanndd EEnnvviirroonnmmeennttaall IImmppaaccttss UUssiinngg DDaattaa EEnnvveellooppmmeenntt AAnnaallyyssiiss Arun Paul Saini Follow this and additional works at: https://commons.erau.edu/edt Part of the Management and Operations Commons SScchhoollaarrllyy CCoommmmoonnss CCiittaattiioonn Saini, Arun Paul, "Evaluation of Airline Efficiency and Environmental Impacts Using Data Envelopment Analysis" (2018). Dissertations and Theses. 417. https://commons.erau.edu/edt/417 This Dissertation - Open Access is brought to you for free and open access by Scholarly Commons. It has been accepted for inclusion in Dissertations and Theses by an authorized administrator of Scholarly Commons. For more information, please contact [email protected]. EVALUATION OF AIRLINE EFFICIENCY AND ENVIRONMENTAL IMPACTS USING DATA ENVELOPMENT ANALYSIS By Arun Paul Saini A Dissertation Submitted to the College of Aviation in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy in Aviation Embry-Riddle Aeronautical University Daytona Beach, Florida August 2018 © 2018 Arun Paul Saini All Rights Reserved. ii ABSTRACT Researcher: Arun Paul Saini Title: EVALUATION OF AIRLINE EFFICIENCY AND ENVIRONMENTAL IMPACTS USING DATA ENVELOPMENT ANALYSIS Institution: Embry-Riddle Aeronautical University Degree: Doctor of Philosophy in Aviation Year: 2018 Airline efficiency has been a focus of research since the birth of the airline industry. Data envelopment analysis has become a highly accepted methodology for performing efficiency analysis and assessing relative differences between comparable business entities; over the last decade, airline efficiency research has proliferated into this linear programming domain. While early airline efficiency research focused primarily on revenue generation and profitability, growing commercial social responsibility is driving greater investment into understanding and improving the environmental impact of airline operations. This study is intended to partially fill a gap in exigent literature. While limited data envelopment analysis including environmental impacts has been conducted, the models treat environmental impacts as an output, never as an input or intermediate variable in the decision-making models. This study constructed a linear programming model utilizing the data envelopment analysis methodology to assess the relative efficiencies of thirteen airlines. The model consumes operational and financial performance indicators of the airlines, as well as abatement success measured as a function of the carbon dioxide emissions iv produced by the airline operations. The study analyzed airline activities from 2013 to 2015. The results of the study indicated that the linear programming model was successful in measuring airline operational efficiency, inclusive of: (a) different capacity and cost components of airline operations, (b) carbon dioxide emissions abatement, (c) differing airline business models associated with service levels, and (d) the implications of different routes and networks. Airline-specific recommendations are presented, based on analysis of their 2013-2015 operational performance reviewed in conjunction with airline strategy disclosures included in annual reports. The study provides theoretical and practical contributions to airline efficiency research. The study is the first to include environmental impact abatement expense as an input into airline decision-making for an overall airline efficiency model, as opposed to an output which is calculated as part of an optimization strategy focused on capacity or revenue generation. v DEDICATION I dedicate this work to my mother and father. Mom, your support and perpetual reinforcement have been the wind beneath my wings through this seven-year journey. Thanks for seeing this through with me. Dad, your memory and achievements continue to influence the course I plot. I will forever be blessed to have so much advice available to me, long after I lost the opportunity to ask you for it. vi ACKNOWLEDGEMENTS I would like to acknowledge everyone that made this dissertation possible. This doctoral program has encompassed a seven-year period, and I would not be at this point without extraordinary support in my academic, professional, and personal life. First, I must recognize my dissertation chair, Dr. Dothang Truong, for his mentorship and guidance over the last two years. His inputs have been invaluable to my strategy and execution of this dissertation. I would also like to express my gratitude to my dissertation committee members – Dr. Ahmed Adelghany, Dr. David Esser, and Dr. Matthew Fischer – for their feedback, thought-provoking input, and support. My career has carried me through three very different jobs at Gulfstream Aerospace during this program. In the positions I have held, it has required understanding and accommodation from my leaders for me to survive this journey. Chronologically, I must recognize the support of Mark Sells & Bill Bradley; Greg Collett, Becky Elliott, Jonathan Ringham, & Melissa Grant; and Steve Ritchie. My family and friends have accepted my absence over the last several years while continuing to provide love and understanding. My mother’s support has never wavered. The Saini-Shea’s have accepted my aberrant attendance to family gatherings; I hope my two nieces are too young to remember. The Atkinsons, Fosters, Pearlmans, and Shepards continued to include me as the friend they see every day, though I seemed to decline 95% of their invitations. Finally, a special thanks to Andrea Burkhardt for her support of the dissertation. In the last year of this program, she has literally taken on the responsibility of my day-to-day survival so I could focus on this work. vii viii TABLE OF CONTENTS Page Abstract ............................................................................................................................. iv Dedication ......................................................................................................................... vi Acknowledgements .......................................................................................................... vii List of Tables .................................................................................................................. xiii List of Figures ................................................................................................................. xiv Chapter I Introduction ................................................................................................ 1 Statement of the Problem ............................................................... 5 Purpose Statement .......................................................................... 6 Significance of the Study ............................................................... 6 Research Questions ........................................................................ 8 Delimitations .................................................................................. 8 Limitations and Assumptions ...................................................... 10 Definitions of Terms .................................................................... 13 List of Acronyms ......................................................................... 15 Chapter II Review of the Relevant Literature ........................................................... 16 Review of Research in Airline Efficiency ................................... 16 Airline Efficiency Utilizing Total Factor Productivity (TFP). ............................................................................... 16 Application of DEA in Measuring Airline Efficiencies. . 19 Environmental Impacts in Aviation ............................................. 28 Environmental Motivations in Aviation. ......................... 28 ix

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revenue generation and profitability, growing commercial social differing airline business models associated with service levels, and (d) the of the cost efficiency (first stage) and service effectiveness (second stage) tGD=G. J. GKL. ≤ žoG& q = 1, … , D. tGF;G. J. GKL. ≥ nF;G& @ = 1, …
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