Essays on Electric Vehicle Adoption

104 Pages·2014·6.67 MB·English

Essays on Electric Vehicle Adoption
A Dissertation submitted to the
Graduate School
of the University of Cincinnati
in partial fulfillment of the
requirements for the degree of
Doctor of Philosophy
in the Department of Operations, Business Analytics, and
Information Systems
of Carl H. Lindner College of Business
by
Saravanan Kuppusamy
M.S. West Virginia University 2001
B.S. Coimbatore Institute of Technology 1997
Committee Members
Michael Magazine, Ph.D. (chair)
Uday Rao, Ph.D. (chair)
Michael Fry, Ph.D.
Debashis Pal, Ph.D.
August 2014
' Copyright by Saravanan Kuppusamy, 2014.
All rights reserved.
Abstract
As a part of the initiative to improve the local air quality, cities encourage fleets of ve-
hicles to adopt alternative technologies like electric vehicles. Motivated by the above,
we study an environment consisting of a Taxi Cab company (TC) and an Electric-
Vehicle Infrastructure Service Provider (SP). The TC has a fleet of taxicabs and must
make a fleet renewal decision with some combination of electric vehicles (EVs) and
internal combustion engine vehicles (ICEs). The SP has a network of battery swap-
ping stations and offers infrastructure services such as swapping and recharging for
a fee.The SP has to decide whether to invest in battery swapping stations for TC
along with planning for EVs in terms of the number of batteries stocked at the swap-
ping stations. First, in a centralized setting, we combine SP and TC into a single
vertically-integrated entity and analyze factors that influence EV adoption such as
the average miles driven by vehicles, the associated uncertainty in miles driven, the
diversity in miles driven by different vehicles, and varied cost parameters. Second,
in a decentralized setting, we treat SP and TC as individual entities. We examine
the SP’s problem of pricing infrastructure services to TCs and identify strategies for
the SP to maximize profits. Third, we integrate emissions control policies into the
decision-making process and study their impact on the coordination of adoption deci-
sions. Overall, we identify several managerial insights on EV adoption using multiple
perspectives: vertical integration of entities, decentralized and emissions.
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Acknowledgements
I would like to express my deepest gratitude to my co-advisors Professors Mike
Magazine and Uday Rao, for their guidance, caring, patience and for providing a
nurturing environment to conduct research. It is impossible for me to forget their
contribution and guidance. Their passion for research is contagious and it will be
a constant source of motivation for me in years to come. I would like to thank my
committeemembers,ProfessorsMikeFryandDebashisPal,forprovidingmefeedback
and keen insights.
Special thoughts go to Professor Kipp Martin for being a great teacher, a coauthor
and an invaluable resource on the optimization analysis. I would like to thank Pro-
fessor Jeff Camm for providing me with the excellent opportunities to teach business
analytics.
Iwouldliketothankmyfriend,aPhDgraduateofthedepartmentofmathematics,
Ramaruban Nadesan, for introducing me the unknown corners of world literature,
music and cinema. I would like to acknowledge the love and support I received from
my wife, Kalaiselvi Kumarasamy. She was always there cheering me up and stood by
me through the rain or shine. I also want to thank our son, Ruban Aathi, who has
been a good sport and cheered me in his own little ways that helped me take stress-
off the dissertation work. Finally, I thank my parents, Kuppusamy Vellingiri and
Saraswathi Kuppusamy, for their continued love and support; without them, I would
have never had the opportunity to thank the wonderful individuals that I mentioned
above.
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Contents
Abstract . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . iii
Acknowledgements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . iv
List of Tables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . viii
List of Figures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ix
1 Introduction 1
1.1 Taxi Cab Company and Infrastructure-Service Provider . . . . . . . 2
1.2 Road Map . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
2 Electric Vehicle Adoption Decisions in a Fleet Environment 5
2.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5
2.2 Literature Review . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8
2.3 Fleet Renewal Model . . . . . . . . . . . . . . . . . . . . . . . . . . . 8
2.4 EV Adoption Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . 11
2.4.1 Impact of Average Miles Driven, µ . . . . . . . . . . . . . . . 11
2.4.1.1 Possible Cases of EV Adoption . . . . . . . . . . . . 12
2.4.2 Impact of Variance in Miles Driven . . . . . . . . . . . . . . . 14
2.5 Model Variants . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16
2.5.1 Non-Convex Inconvenience Cost Function . . . . . . . . . . . 16
2.5.2 Heterogeneous Fleet . . . . . . . . . . . . . . . . . . . . . . . 17
2.5.3 Risk Measure . . . . . . . . . . . . . . . . . . . . . . . . . . . 20
2.6 Technology and Infrastructure . . . . . . . . . . . . . . . . . . . . . . 21
2.7 Conclusion & Future Research . . . . . . . . . . . . . . . . . . . . . . 24
3 Contract Design in a Electric Vehicle Supply Chain 26
3.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26
3.2 Literature Review . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29
3.3 Contract Customization . . . . . . . . . . . . . . . . . . . . . . . . . 30
3.3.1 Assumptions and Parameters . . . . . . . . . . . . . . . . . . 31
3.3.2 Taxicab Company’s problem . . . . . . . . . . . . . . . . . . . 32
3.3.3 Service Provider’s problem . . . . . . . . . . . . . . . . . . . . 32
3.3.4 Single-Part Tariffs . . . . . . . . . . . . . . . . . . . . . . . . 33
3.4 Designing a Menu of Contracts . . . . . . . . . . . . . . . . . . . . . 34
3.4.1 A Profit Focus Approach - Model M1 . . . . . . . . . . . . . . 35
3.4.2 A Loss Inclusive Approach - Model M2 . . . . . . . . . . . . . 37
3.4.3 Discussion: Single, Two-Part and Three-Part Tariffs . . . . . . 38
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3.5 Numerical Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39
3.5.1 Price Discounting . . . . . . . . . . . . . . . . . . . . . . . . 40
3.5.1.1 Price Discounting Strategy - An Illustration . . . . . 40
3.5.1.2 Price Discounting in Profit-focus and Loss-Inclusive
Approaches . . . . . . . . . . . . . . . . . . . . . . . 41
3.5.2 The Number of Contracts Offered . . . . . . . . . . . . . . . . 43
3.5.3 Coverage . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44
3.6 Conclusions & Future Research . . . . . . . . . . . . . . . . . . . . . 45
4 Impact of Emission Control Policies on EV Adoption 47
4.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47
4.2 Literature Review . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49
4.3 Modeling Framework . . . . . . . . . . . . . . . . . . . . . . . . . . . 50
4.3.1 Assumptions and Parameters . . . . . . . . . . . . . . . . . . 50
4.3.2 Centralized Case . . . . . . . . . . . . . . . . . . . . . . . . . 52
4.3.3 Decentralized Case . . . . . . . . . . . . . . . . . . . . . . . . 52
4.3.3.1 Taxicab Company’s (TC) problem . . . . . . . . . . 53
4.3.3.2 Service Provider’s (SP) problem . . . . . . . . . . . . 53
4.4 Emissions Tax Policy . . . . . . . . . . . . . . . . . . . . . . . . . . . 54
4.5 Emissions Cap Policy . . . . . . . . . . . . . . . . . . . . . . . . . . . 56
4.6 Hybrid Emissions Policies . . . . . . . . . . . . . . . . . . . . . . . . 59
4.6.1 Hybrid Policy-H1 . . . . . . . . . . . . . . . . . . . . . . . . . 59
4.6.2 Hybrid Policy-H2 . . . . . . . . . . . . . . . . . . . . . . . . . 61
4.7 Given SP is taxed, should TC be taxed or capped? . . . . . . . . . . 63
4.8 Conclusions & Future Research . . . . . . . . . . . . . . . . . . . . . 65
A Appendix - Electric Vehicle Adoption Decisions 68
A.1 Proof of Proposition 2.4.2 . . . . . . . . . . . . . . . . . . . . . . . . 68
A.2 Proof of Proposition 2.4.3 . . . . . . . . . . . . . . . . . . . . . . . . 68
A.3 Proof of Proposition 2.4.4 . . . . . . . . . . . . . . . . . . . . . . . . 68
A.4 Heterogeneous Fleet . . . . . . . . . . . . . . . . . . . . . . . . . . . 68
A.5 Expected Cost and Variance Calculations . . . . . . . . . . . . . . . 70
B Appendix - Contract Design 71
B.1 Proof of Proposition 3.3.1 . . . . . . . . . . . . . . . . . . . . . . . . 71
B.2 Formulations with Linearized Objective Function with Quadratic Con-
straints - Model M3 . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71
B.3 Formulations with Linearized Objective Function with Quadratic Con-
straints - Model M4 . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73
C Appendix - Emission Control Policies 75
C.1 Emissions Control Models and Optimal Solutions . . . . . . . . . . . 75
C.1.1 Emissions Tax Model - Centralized . . . . . . . . . . . . . . . 75
C.1.2 Emissions Tax Models - Decentralized . . . . . . . . . . . . . 75
C.1.3 Emissions Cap Model - Centralized . . . . . . . . . . . . . . . 76
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C.1.4 Emissions Cap Model - Decentralized . . . . . . . . . . . . . . 77
C.1.5 Hybrid Emissions Policy - H1- Centralized . . . . . . . . . . . 78
C.1.6 Hybrid Emissions Policy - H1- Decentralized . . . . . . . . . . 78
C.1.7 Hybrid Emissions Policy - H2- Centralized . . . . . . . . . . . 79
C.1.8 Hybrid Emissions Policy - H2- Decentralized . . . . . . . . . . 80
C.2 Proofs for Theorems and Propositions . . . . . . . . . . . . . . . . . . 81
C.2.1 Proof of Proposition 4.4.1 . . . . . . . . . . . . . . . . . . . . 81
C.2.2 Proof of Proposition 4.4.2 . . . . . . . . . . . . . . . . . . . . 81
C.2.3 Proof of Proposition 4.5.1 . . . . . . . . . . . . . . . . . . . . 82
C.2.4 Proof of Proposition 4.5.2 . . . . . . . . . . . . . . . . . . . . 82
C.2.5 Proof of Proposition 4.6.1 . . . . . . . . . . . . . . . . . . . . 82
C.2.6 Proof of Proposition 4.6.2 . . . . . . . . . . . . . . . . . . . . 82
C.2.7 Proof of Proposition 4.6.3 . . . . . . . . . . . . . . . . . . . . 82
C.2.8 Proof of Proposition 4.6.4 . . . . . . . . . . . . . . . . . . . . 83
C.2.9 Proof of Proposition 4.7.1 . . . . . . . . . . . . . . . . . . . . 83
C.2.10 Proof of Proposition 4.7.2 . . . . . . . . . . . . . . . . . . . . 84
D Tables 85
D.1 Data for Parameter Setting . . . . . . . . . . . . . . . . . . . . . . . 85
D.2 Emission Parameters . . . . . . . . . . . . . . . . . . . . . . . . . . . 86
D.3 Contract Design - Problem Instance for Numerical Analysis . . . . . . 86
D.4 Contract Design - Computational Results . . . . . . . . . . . . . . . . 86
Bibliography 90
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List of Tables
2.1 Comparison of Expected Cost and Variance Criteria . . . . . . . . . . 21
2.2 Scenarios based on Technology . . . . . . . . . . . . . . . . . . . . . . 21
D.1 Parameter Settings . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85
D.2 Emission Parameters . . . . . . . . . . . . . . . . . . . . . . . . . . . 86
D.3 Problem Instance Used in Numerical Analysis . . . . . . . . . . . . . 87
D.4 M1 with 2 three-part tariffs . . . . . . . . . . . . . . . . . . . . . . . 87
D.5 M1 with 3 three-part tariffs . . . . . . . . . . . . . . . . . . . . . . . 88
D.6 M2 with 2 three-part tariffs . . . . . . . . . . . . . . . . . . . . . . . 88
D.7 M2 with 3 three-part tariffs . . . . . . . . . . . . . . . . . . . . . . . 88
D.8 Coverage - M1 with 2 three-part tariffs . . . . . . . . . . . . . . . . . 88
D.9 Coverage - M1 with 3 three-part tariffs . . . . . . . . . . . . . . . . . 89
D.10 Coverage - M2 with 2 three-part tariffs . . . . . . . . . . . . . . . . . 89
D.11 Coverage - M2 with 3 three-part tariffs . . . . . . . . . . . . . . . . . 89
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List of Figures
1.1 Interactions Between TC and SP . . . . . . . . . . . . . . . . . . . . 2
2.1 Multiple Adoption Zones . . . . . . . . . . . . . . . . . . . . . . . . . 12
2.2 One Adoption Zone . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13
2.3 The Impact of Variance . . . . . . . . . . . . . . . . . . . . . . . . . . 15
2.4 The Impact of Non-Convex Inconvenience Function . . . . . . . . . . 16
2.5 EV Adoption Decisions in a Heterogeneous Fleet Environment . . . . 18
2.6 Heterogeneous Fleet - The Impact of Variance . . . . . . . . . . . . . 19
2.7 Technology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22
2.8 Infrastructure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23
3.1 An Illustration of Contract Regions Under Collaboration . . . . . . . 34
3.2 Two and Three-Part Tariffs . . . . . . . . . . . . . . . . . . . . . . . 39
3.3 An Illustration of Price Discounting . . . . . . . . . . . . . . . . . . . 40
3.4 Discounting in Models M1 and M2 with 2 three-part tariffs . . . . . . 42
3.5 Comparison of Net Profits from M1 and M2 . . . . . . . . . . . . . . 43
3.6 Comparison of Net Profits When the Number of Contracts Increase . 44
3.7 Comparison of Coverages . . . . . . . . . . . . . . . . . . . . . . . . . 45
4.1 Adoption Decisions Under Emissions Tax Policy . . . . . . . . . . . . 55
4.2 Adoption Decisions Under Emissions Cap Policy - Centralized . . . . 57
4.3 Adoption Decisions Under Emissions Cap Policy - Decentralized . . . 59
4.4 Adoption Decisions Under H1 Policy - Centralized . . . . . . . . . . . 60
4.5 EV Adoption Under Hybrid Policy, H1, Decentralized Setting . . . . 61
4.6 EV Adoption Under Hybrid Policy, H2, Centralized Setting . . . . . . 62
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