ASC_MOBILITY_ECONOMICS

Business Research Methods
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An Economic Study in to the Impact of Disruptive Autonomous, Shared
and ConnectedTechnologies on Mobility in the United Kingdom by 2030
A Conceptual Theoretical Research Proposal
MoD Programmes MBA

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Table of Contents
Section One Introduction 4
1.1 Need 4
1.2 Global Trends 4
1.3 Justification 5
1.4 Aim 6
1.5 Definition of Terms 6
1.6 Research Hypotheses 7
1.7 Research Questions and Objectives 7
1.8 Limitations 7
Section Two Literature Review 8
2.1 Moral Hazard and the Agency Problem 8
2.2 The Economics of Ride Sharing 9
2.3 The Economics of Economy 9
2.4 The Diffusion of Innovation 9
2.5 Fuzzy Cognitive Mapping of Travel Behaviours 10
2.6 Leaders and Followers 11
2.7 Findings and Literature Gap 12
2.8 A Final Thought? 12
Section Three Research Approach and Methodology 13
3.1 Data Collection 13
3.2 Data Analysis and Outcome 14
Section Four References 15
Appendices
A James’s and Louise’s Callous Calculations 17
B Definitions of Autonomy 19
C Project Plan 20
Photo, P2, top. Lutz Pathfinder. Designed
and manufactured by Coventry-
based automotive innovation firm RDM, it is an
electric-powered two-seater pod with
autonomous control systems. The LUTZ
Pathfinder self-driving pods project is
underway on pedestrianized areas of Milton
Keynes.
Photo, P2, bottom. SMMT. Key areas being
developed in Intelligent Transport Systems
(ITS) which allow vehicle-to-vehicle and
vehicle-to-infrastructure communication.
Implementing these communication systems
can help to reduce road accidents, relieve
congestion and reduce emissions.

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SECTION 1 - INTRODUCTION
1.1 Need
The impact of James’s scenario on the UK Economy equates to £75.8 billion in lost opportunity
through the value of time lost to commuting alone.
With similarly swift and rudimentary calculations Louise’s scenario equates to a mere 2.18% of
asset utilisation. Louise’s (average) car would be costing her £245 per day of utility.
The basis for these wild claims can be found at AppendixA. Whilst the examples are hypothetical
and the calculations hyperbole by virtue of irresponsible oversimplification, it is easy to see howthe
opportunities are appealing to governmentsand business alike. It is important to manage optimism
and expectations to ensure that these technologies are launched on a sure foot with the world at
large.
1.2 Global Trends
Increasing life expectancies, declining levels of child mortality and continuing high birth rates are
set to see continuing global population growbeyond 8 billion within the next decade and the higher
end of expectation would see a global population of more than 9 billion by 2030. Populations will
continue to migrate towards urbanised “mega-cities”. Concerns for the environment are likely to
continue to growas demands on natural resources and the global commons increase.
As technology and computing power continues to accelerate1 the maturity of autonomous features
coupled with the proliferation beyond the developed world of advanced mobile devices means that
a future of Autonomous, Shared and Connected (ASC) mobility could be much nearer than some
are predicting.
The confluence of rapidly increasing and compounding demands driving an increase in mobility
requirements and advancements in capabilities, accessibility and technology mean that it is
incomprehensible that automotive utilisation rates can remain below 5%, which Goldman Sachs
(2015) estimates, for long. There is absolutely no doubt that the automotive industry and broader
physical mobility is ripe for disruption.
1
Broadly followingMoore’slaw.
Life with a car in the 21st Century
James has a demanding day job working for a
multi-national corporate where he is expected
to know what is happening in the world and
how it may impact on his day before he arrives
at work in the morning. He is a committed
family man who shares family responsibilities
with his wife, also a full time professional.
Passionate about self-improvement, James
has also committed to a post-graduate Masters
programme, which he enjoys, but is a further
burden on his time. James commutes for a
total of 41 minutes every day, which he spends
listening to Radio 4. Whilst some of the content
is relevant, the inability to actively search for
relevant news, make notes or reply to e-mails
strikes him as a lost opportunity.
Louise works in London but lives in
Hertfordshire. She has a 10 minute daily
commute to the train station where she parks
her car in a multi-storey car park at around
0830 and returns to her car at 1730 each
evening for the 10 minute drive back. Much as
she would like, she cannot cycle or walk due to
daily chores and childcare responsibilities on
the way to and from work. She works in
Financial Services and one day started to
consider her car from the point of view of a
financial asset. Using her car just 20 minutes a
day on a Monday to Friday and on average for
only 2 hours at weekends she concluded that
as the second most expensive financial
commitment in her household, after the house
itself, her car was not being used in a very
efficient manner.

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1.3 Justification
There are many investment and consultative papers available with some bold stock predictions
and estimated benefits to global and national economies. Much of this material has been
commissioned by “agents” in order to construct arguments to convince “principals” to invest.
Goldman Sachs (2015) estimated eventual global benefits to be $3.5tn and KPMG (2015) claimed
benefits to the UK of £51bn by 2030. In February 2016 the Government announced the first £20mn
of funding committed to 8 projects around the United Kingdom as part of its £100mn intelligent
mobility fund.2
“The Grateful 8”
The first eight projects to be funded from the Governments Intelligent Mobility Fund are:
1. UK Connected Intelligent Transport Environment will explore the benefits of "talking car"
technologies on 40 miles of Coventry roads
2. Insight will develop driverless shuttles with advanced sensors and control systems, with a
focus on providing transport for disabled and visually impaired people
3. Tools for autonomous logistics operations and management will develop modelling tools in a
collaboration between transport modellers and the computer games industry
4. Flourish will develop tools to improve the understanding of users' needs with regard to
autonomous vehicles, in Bristol.
5. Move-UK will accelerate the creation and market readiness of autonomous driving systems.
6. Innovative Testing of Autonomous Control Techniques will try to reduce the cost of testing
driverless systems.
7. Pathway to Autonomous Commercial Vehicles will explore technologies to monitor vehicle
data to predict safety risks.
8. i-Motors - Intelligent Mobility for Future Cities Transport Systems will develop hardware that
analyses sensory data in real-time.
There is academic substantive and middle-theory to support stove-piped elements of these
technologies and their potential impacts on our world. Very fewconsider the accelerative effect of
these technologies combined. This research should apply some independent thinking and
academic rigour to secondary data and consultative proposals.
2
https://www.gov.uk/government/news/driverless-cars-technology-receives-20-million-boost

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1.4 Aim
To study the relationship between principal and agent, and investigate its impact on the
diffusion of Autonomous, Shared and Connected (ASC) technologies in the mobility
environment of the UK by 2030
1.5 Definition of Terms3
Autonomous – (philosophy) Acting or able to act in accordance with rules and principles of
one's own choosing.
A grey area exists in common academic and consultative literature between the treatment of
automatic and autonomous behaviours. At AppendixB are 2 taxonomies commonly used in the
context of autonomous mobility: 1 is very simple and was used by the UK Government in the
pathway to driverless cars summary, perfect for explaining the basicconcepts to “outsiders”. The
second is the SAE defined international standard; it has greater levels of granularity and is of
more utility when dealing with “insiders”.
The author would consider basic levels of automation in the second taxonomy as simple
automatic “behaviours” (such as cruise control or anti-lock brakes). The true economic benefits
of autonomy in the context of mobility only start to gather momentum as the market approaches
L4 (High Automation).
Shared - A part or portion of something owned, allotted to, or contributed by a person or group.
Noting in the context of personal mobility shared is a concept which continues to evolve and
includes everything from ride sharing, whereby travellers list themselves as either a supplier or a
demander of transport on a given route at a given time and the exchange of service provision is
made in return for a benefit all the way through to the next generation of “on demand digital,
networked taxi services” and finally business models of shared ownership (in much the same
way as “time-shares” of property exist) and temporary use/hire services.
In literature, terms such as “Demand Responsive Transportation Services” and “Transportation
Network Companies (TNCs)” are starting to appear but there is little common taxonomy beyond
the concept of “sharing”.
Connected - Joined or linked together.
Much as per autonomy, the real economic benefits start to gather momentum when the vehicle
is connected across all lines of development and use; to the transport infrastructure, to other
mobility users and of course for the occupant to route to which form of connectivity they require
during their journey.
Mobility - The ability to move physically.
There are many contexts with which the word mobility can be associated; whilst it may be
obvious, it is important to clarify here that the research concerns physical mobility over distances
which are generally not practical or desirable to be covered without vehicular assistance.
3
http://www.collinsdictionary.com/dictionary/english

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1.6 Research Hypotheses
1. Economic Benefit. It is proposed that there are significant benefits to be realised to the UK
economy through leading the introduction of ASC technologies in mobility. However, there is a
conspiracy of optimism, which should be balanced to represent the potential costs to the UK
economy in other sectors.
2. Diffusion of Innovation. It is also proposed that the forecast of adoption of these
technologies is potentially overly pessimistic. The most significant hindrance to the adoption of
technologies in mobility has traditionally been the high entry barrier represented by newvehicle
prices, which stifles rates of diffusion. The economic and environmental benefits of ASC
technologies will lower this entry barrier in the future and act as a catalyst accelerating diffusion
beyond traditionally accepted norms.
1.7 Research Questions and Objectives
To achieve the aim and develop the hypotheses, research will be based on answering the following
questions and meeting the corresponding objectives.
Research Question Research Objective
1. How will the £51 billion benefit to the UK
economy be generated?
a. Identify the revenue streams which contribute
to the £51 billion estimated benefit
b. Establish the principal actors considered in
this research and assess those missing
c. Describe the benefit or cost from the
perspective of those actors not considered
2. Why is the diffusion rate of ASC technologies
important?
a. Determine assumed rates of diffusion for the
economic benefits already outlined
b. Describe the potential differences in the
diffusion of these innovations
c. Develop an explanatory theory explaining the
relationship between the principal, the agent
and the diffusion of these technologies.
1.8 Limitations
Whilst consideration will be given to imported and exported effects or spill-over’s from other
economies and other economic sectors these will not form part of the primary conclusions. The
following limitations apply:
Limitations
Economic impact is restricted to the United Kingdom
Mobility will be viewed within the land-based environment (not air, sea or space).
Non-public mobility may be considered but is not the primary focus of this study.
Modes of mobility will focus on road and highway (not rail or lowspeed infrastructure).

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SECTION 2 – LITERATURE REVIEW
The main aim of this research project is to develop the 2 hypotheses relating to the economic
benefit and rate of diffusion of innovation (ASC technologies) in the UK mobility market. Following
the development of thought trees and subsequent brainstorming, research areas were refined and
a preliminary table of search terms was developed and executed using the University Library
search engine and Google Scholar. Additionally, Google Alerts were used to keep the author up to
date on developments in the media as well as a number of feeds and blogs, which were monitored
through social media.
The 2 principle economic grand theories, using Creswell’s typology of theories at Figure 1, applied
at this stage were “Agency Theory” and the “Diffusion of Innovation”. Whilst noting that these are
the principle grand theories at the outset of this research project, it is expected through the use of
an inductive approach that other theories at all 3 levels are likely to be discovered and applied;
these could be found more, less or equally relevant to the research area.
Figure 1. Creswell’s Typology of Theories
2.1 Moral Hazard and the Agency Problem
The Agency problem as it is understood today emerged in the 1970s as a result of the combination
of economic and institutional theories. According to Ross (1973), an agency relationship has arisen
when an agent acts for, or on behalf of, or as a representative for the other, designated principal.
The theory has come to extend well beyond social science and economics and can be applied to
all contexts of information asymmetry, uncertainty and risk. The principal agent theorycan be
applied at multiple levels and across multiple sub-sectors to the hypotheses suggested within the
scope of this research proposal.
In the context of this research proposal, agency relationships exist between the Government and
industry, automotive, petrochemical, mobile service providers, local Government, the Rest of the
World (RoW) etc. Furthermore, examples exist between industry and professional services firms,
transport providers,investors and financial services institutions to name but a few. The relevance
of this theory to the proposed research area is the provision of a framework through which to study
information asymmetry put forward by stakeholders (principals and agents) whose interests may
not be aligned with the greater good of the (UK) macroeconomic environment. It is worth noting,
that upon raising this to a global level, there is yet another principal agent relationship whereby the
UK itself is an agent with the RoW as the principal and it cannot be assured that the decisionsthe
UK make are themselves best for the global economy.
The MoD UK (2011) concluded that a widespread ‘conspiracyof optimism’ existed between
industry, the military, officials and Ministers. Further research is required to investigate whether or
not this is the case in the British automotive and mobility sector.

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2.2 The Economics of ride sharing
Horpedahl (2015) demonstrated a broad level of support amongst practising economists for
Transportation Network Companies (TNCs) or ride sharing services throughout the United States.
He noted strong opposition from traditional Taxi “cartels” who would put pressure on government to
maintain regulation which outlawed TNCs. This was due to evidence of monopolistic rents which
themselves were inducing a form of Moral Hazard where the interests of principal (government)
and agent (taxi drivers) were not aligned. This led to the destruction of price competition and
significant economic waste. Horpedahl suggested Tullock’s transitional gains trap would lead to the
market being kept in a sub-optimal state without intervention. The benefitsof deregulation would
lead to, amongst other things, dynamic pricing which could increase consumer awarenessand
encourage a more responsible approach to consumption and increased market efficiency.
Horpedahl’s theories are substantive and represent a small segment of a single market.
2.3 The Economics of Economy
Whilst not directly related to ASC technologies, Wang (2011) looked at the macroeconomic impact
of advanced vehicles focusing on increases in powertrain efficiencies and corresponding fuel
economy. It is worthy of mention here as it follows a trend, which is relatively widespread in journal
articles, of considering only single elements of the incorporation of technology within mobility
solutions and falls once again foul of viewing future economic benefits through the lens of historic
fleet turnover and innovation diffusion.
2.4 The Diffusion of Innovation
"There is no reason for any individual to have a computer in his home."
Olsen, K. (1977)
In context, and given the size of a computer at the time, Olsen’s comment to the World Future
Society Convention in 1977 was not unreasonable, but hindsight makes it somewhat amusing
nevertheless. In 2012 Google predicted that there would be automated vehicles in mass production
by 2018. The UK Government predicts fully automated vehicle technologies around 2020 and
beyond. Volvo is currently trialling fully autonomous vehicles in Sweden with selected members of
the population. So why do Goldman Sachs predict less than 5% of vehicles in the US will be
autonomous by 2030 and total penetration will not occur until 2060?
In the Journal of Economic and Cultural Change (1969), Brown noted a gap in theory between
innovational diffusion at the market (micro) level, and innovational diffusion at the macro- level.
Brown considered the role of market factors and social networks in guiding diffusion. In the time
that has passed the obvious explosion of connectivity and globalisation makes some of his
observations more relevant than ever.
Figure 2. Browns Scale of Innovations
The very nature of ASC technologies in mobility is such that it will not necessarily behave in the
same way as traditional or historic innovations. Through global connectivity ASC technologies can
penetrate multiple markets simultaneously without significant geographic restraints. However, it is
the simple model at Figure 2, which hints towards the true nature of the coming disruption.

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Brown suggested that the place of an innovation on his scale is likely to be characterised by the
presence of a distributor (principal) who is vitally concerned with its propagation. In this context,
one could usefully construct a trinity similar to that suggested by Clausewitz (1832). The wonderful
trinity of war contained passion, reason and chance. The 2 versions the author suggests below
have the automotive industry represented by passion and the government by reason. In Version 1,
the third element of the trinity is labelled Stakeholders and Society (SaS). “Stakeholders” are
considered to be groups, or organisations, which are actively engaged and have a beneficial or
detrimental interest in the propagation of ASC technologies in the mobility market. It could be
argued that society are also stakeholders, but for the purposes of this model the difference
between society and stakeholders is based on perceived levels of activity. Referring to Figure 4,
stakeholders would be toward the “activist” end of Kellermanstypology of followers whilst society
would err toward the “bystander” end of the scale. In the second version of the model, to avoid this
confusion, society and stakeholders have been separated. The 3 elements of the trinity interact
with one another and all three elements act together, to varying degrees, with society. The trinity at
version 2 could act, as Brown suggested, as a principal could act, potentially frustrated with
restrictions and relative inefficiencies to help cultural and ideological norms lead technology and
ultimately proliferation of manufactured goods and services. This would ensure that attitudes keep
up with technological advance or that demand is created as supply is developed.
Logically, Schumpeter’s (1942) galesof creative destruction would belong in chance. In the
suggested versionsapplied to mobility this would translate to the side represented by stakeholders.
This translation is highly relevant, as it is the non-traditional stakeholders who hold the key to the
greatest levels of disruption and the potential collapse of the trinity. It is rival market entrants such
as Google and Apple and newentrants such as Über or Tesla who potentially pose the biggest
threat to the automotive industry.
Figure 3. Clausewitzian Trinity applied to Mobility
2.5 Fuzzy Cognitive Mapping of Travel Behaviours
Vogt et al., (2015) conducted a study of potential changes to travel behavioursusing a fuzzy
cognitive map. By combining a number of disruptive changes to the travel and mobility
environment and mapping their relative dependencies they were able to imply a number of useful
causal relationships. Whilst they stop short of using it as a predictive tool, instead mapping
dependencies and the extent to which different elements of disruption could affect one another it

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does provide some useful indicators as to which elements of these changes are most likely to
cause the most disruption and the extent to which they could penetrate society and markets.
For this proposal, technologies have been broken into 3 complimentary key themes: Autonomy,
Sharing and Connectivity. Vogt et al. considered 9 themes. These are listed in the table below with
a short note as to the authors viewon how they link to the 3 key themes considered here.
Category Relationship to this Proposal
1 Autonomous Vehicles Key Theme – Autonomous
2 Connected Vehicle
Technologies
Key Theme – Connected
3 Development Density Trend – Relates to global trends and urbanisation
4 Demand Responsive
Transportation Services
Key Theme – Sharing
5 Fixed Route Transportation
Services
Limitation – Mostly Public Transport Services
6 Intelligent Infrastructure Enabler – Fundamental requirement for success
7 Low Speed Infrastructure Trend / Limitation – Inevitable by-product of trends (such as
urbanisation), enabled by public services (local Government)
8 Lightweight Personal
Transportation
Trend / Limitation / Enabler – Much as per 7. Enabled by
business and innovation; compliments journeys of all lengths
9 Mobile Technologies Key Theme / Enabler – Absolute requirement for connected
technologies and an enabler for shared mobility
Table 1. Vogt et al., (2015) Nine Categories of Mobility Change
2.6 Leaders and Followers
When considering the suggestion that the rate of innovational diffusion is going to be dependenton
the cultural or ideological acceptance and demand for these technologies, it leads that it is the
typology of adopter or person that is going to govern the rate of diffusion.
Ryan & Gross (1943) suggested 5 categories of adopter, which have been widely accepted and
popularised by Rogers. Considering adopters in this way is no more or less relevant than through
the lens of followership typology as suggested by Kellerman (2007).
Figure 4. Typology of Adopters and Followers

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However, as indicated by Vogt et al., such is the all-encompassing nature of howthese
technologies are likely to impact upon society and the benefits theyshould deliver acrossall
categories of adopters or followers that it is not helpful in this context to consider small groups of
die-hards or large groups of majorities. In the same way that these technologies will know little of
the geographical bounds,which concerned Brown, they will have limited respect for generational,
class or cultural typologies such as those at Figure 4. This will lead to less of a hierarchy of
adoption, with a spread and velocity more akin to an amorphous, viral blob throughout every
hitherto understood type or category of person, suggested at Figure 5. In laymen speak; one’s
Grandmother is as likely to be a user of the technology as the 21-year old tech entrepreneur.
2.7 Findings and Literature Gap
Agency theory helps make sense of the
motivations and potential problems of the
principal and agent relationships, which
exist within the proposed mobility trinity
suggested at Figure 3. If one were to
consider the trinity through the
perspective of Brown’s principal who is
vitally concerned in the propagation of
innovation then it is the trinity, in concert,
which needs to prepare the various
elements of society in order to embrace
the coming disruption. Working in concert
relies on the integrity of the trinity. The
gales of disruptive change set to engulf
the industry have the potential to bring
about the collapse of the trinity.
Figure 5. Blurring the boundaries of Adopter Typology
In the past, tech related gadgetswere often adopted by “geeks”, automotive gadgets by “petrol
heads” and innovations in medicine by those who had an immediate need. At Figure 5 it is
proposed that unlike previous innovations, ASC technologies will touch everyone and it is this
ubiquity that has the potential to see rates of adoption exceed current expectations.
There is little literature, which considers the strategicimpact of the convergence of all of these
factors on the macro economy. This is highly likely due to the scope of the topic being so large that
combining all of this uncertainty amountsto no more than idle speculation.
2.8 A final thought?
Even Vogt et al. did not include increasing powertrain efficiencies or safetybenefits in their fuzzy
cognitive map. In much the same way as most consumers are unwilling to spend money on safety
features, many are unwilling to spend money on increasing efficiency. Safety and efficiency are in
this respect a “public good” in terms of automotive or mobility features. With the correct
incentivisation and packaged in an appropriate business model, it may be possible, or even likely
that not only will the mobility of the very near future be autonomous, shared and connected, but
safer and more environmentally friendly than currently predicted.

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SECTION 3 – RESEARCH APPROACH AND METHODOLOGY
There is an abundance of secondary data available in the proposed research area. Such is the
size and value of the automotive industry and interrelated businesses and organisations that data
availability and accessibility should not present a problem. However, there is the potential for
significant amounts of bias throughout the available information studies and data due to the
sources of information and the organisations presenting their findings. Moral Hazard and
information asymmetry is as rife as the quantity and sources of data themselves.
The author intends to approach the research with an interpretivist, qualitative approach. One
cannot assume that the information presented is perfect and the value of the information to this
study will be proportional to the perceived amount of bias inherent in its presentation. Furthermore,
the information available as well as the knowledge built throughout this study will be subject to the
perceptions of participants and observersboth during and after the finalisation of this project.
The research proposal has alreadyfollowed one cycle of inductive and deductive development of
ideas and identification of theories. Whilst this proposal involves an inevitable element of deduction
by looking at the relevance of extant theory, it is highly likely that an iterative cycle of hypotheses
development will continue to involve a switch between inductive and deductive approaches freeing
the researcher from the constraints of being bound by one or the other.
To that end, the research strategy encompasses an extended reviewof the literature looking at
grounded theory in and around the subject with an element of interviewand survey in order to build
upon qualitative arguments.
Longitudinal elements of the research will be confined to drawing historic comparisons and
modifying past ideas. However, the very nature of a study into something that is only just emergent
lends itself to a cross-sectional approach to research in order to combine potential outcomes
grounded in the broadest base of knowledge and opinion in order to assess the most likely
outcomes.
3.1 Data Collection
The researcher proposes collection of data from 4 sources, 3 of which are primary but limited and
the fourth is secondary and near limitless in quantity, if not quality of information.
The researcher will spend 4 weeks on an immersive career attachment within Intelligent Mobility
(iMobility) with the Group Strategy division of Jaguar Land Rover. The researcher will conduct at
least 1 interviewfrom a representative of each aspect of the trinitysuggested at Figure 3. The
researcher will also gather some generic views on the acceptance of ASC Mobility technologies via
an electronic survey to assess societal demand for these technologies.
Finally the researcher will continue to use secondarydata sources including, but not limited to,
literature and journals, blogs, social media and presentations from academics, practitioners,
scholars and researchers.

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3.2 Data Analysis and Outcome
The procedure for analysis of data in the conclusion of this proposal will be qualitative for a number
of reasons. Chief amongst these is that the significant number of variables and dependencies
coupled with large degrees of uncertainty and the relative far-sightednessof the subject would
make quantifying data at best speculative and at worst misleading. Instead, the data will be used to
try and drawlinks between existing theory whilst building credible argumentsto demonstrate how
theories are likely to evolve in response to the changing nature of the world around us.
Whilst Bryman and Bell (2011) comment that qualitative methodology lends itself to an inductive
approach and the generation of theories, the researcher does not expect to generate any new
theory rather proposes evolutions to existing substantive theory relevant to the chosen area of
research.
This proposal has a symmetry of outcomes which, according to Gill and Johnson (2002), is
important. Due to the size, complexity and importance of this subject, the findings are expected to
offer worthwhile insights to anyone who has an interest in the area; those directlyinvolved or
simply those with a curiosity to enhance their knowledge of ASC Mobility technologies in the UK
and beyond.
A full Project Plan is at Appendix C.

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SECTION 4 – REFERENCES
Brown, L.A. 1969, "Diffusion of Innovation: A Macroview", Economic Development and Cultural
Change, vol. 17, no. 2, pp. 189-211.
Foellmi, R., Wuergler, T. & Zweimüller, J. 2014, "The macroeconomics of Model T", Journal of
Economic Theory, vol. 153, pp. 617-647.
GERMANY. BCG. (2016) What’s Next for Car Sharing? Munich: BCG.
GREAT BRITAIN. Atkins. (2015) Connected & Autonomous Vehicles. London: Atkins.
GREAT BRITAIN. DEPARTMENT OF TRANSPORT. (2015) The Pathway to Driverless Cars.
London: DfT Publications.
GREAT BRITAIN. KPMG. (2015) Connected and Autonomous Vehicles – The UK Economic
Opportunity. London:KPMG.
GREAT BRITAIN. MINISTRY OF DEFENCE. (2011) Defence Reform. An independent report into
the structure and management of the Ministry of Defence. London: MoD UK.
GREAT BRITAIN. MINISTRY OF DEFENCE. (2014) Global Strategic Trends – Out to 2045.
London: MoD UK.
GREAT BRITAIN. OFFICE FOR LOW EMISSION VEHICLES. (2013) Driving the Future Today. A
strategy for Ultra LowEmission Vehicles in the UK. London: OLEV.
GREAT BRITAIN. OFFICE FOR NATIONAL STATISTICS. (2016) Statistical Bulletin: UK Labour
Market: February 2016. London:ONS.
Horpedahl, J. 2015, "Ideology Uber Alles? Economics Bloggers on Uber, Lyft, and Other
Transportation Network Companies", Econ Journal Watch, vol. 12, no. 3, pp. 360-374.
Kosch, T., Strassberger, M. & Schroth, C. 2012, Intelligent Transport Systems: Automotive
Internetworking, John Wiley & Sons.
Lyytinen, K. and Damsgaard, J., 2001. What’s wrong with the diffusion of innovation theory? (pp.
173-190). Springer US.
Olsen, K. (1977) World Future Society. Boston.
Ross, S.A. 1973, "The Economic Theoryof Agency: The Principal's Problem", The American
Economic Review, vol. 63, no. 2, pp. 134-139.
Saunders, M. 2007, Research methods for business students, 4th edn, Financial Times Prentice
Hall, Harlow.
Schumpeter, J.A. 1952, Capitalism socialism and democracy, 5th edn, Unwin.
Sturgeon, T., Van Biesebroeck, J. & Gereffi, G. 2008, "Value chains, networks and clusters:
reframing the global automotive industry", Journal of Economic Geography, vol. 8, no. 3, pp. 297-
321.
Taylor, A. & Jackson, M. 2010, Sixty to Zero: An Inside Look at the Collapse of General Motors--
and the Detroit Auto Industry, Yale University Press, US.

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Truett, L.J. & Truett, D.B. 2003, "The Italian Automotive Industry and Economies of Scale",
Contemporary Economic Policy, vol. 21, no. 3, pp. 329-337.
USA. GOLDMAN SACHS. (2015) Monetizing the Rise of Autonomous Vehicles. NewYork:
Goldman Sachs International (Cars 2025: Vol.3).
Vogt, R., Wang, H., Gregor, B. & Bettinardi, A. 2015, "Potential changesto travel behaviors &
patterns: a fuzzy cognitive map modeling approach", Transportation, vol. 42, no. 6, pp. 967-984.
Wang, G. 2011, "Advanced vehicles:Costs, energy use, and macroeconomic impacts", Journal of
Power Sources, vol. 196, no. 1, pp. 530-540.

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APPENDIX A
James’ and Louise’s Callous Calculations
The rough and ready calculations made in the introductory paragraphs were based on the figures
and logic below. These are not in any way meant to be representative of actual costs or benefits,
merely indicative of the scales of the numbers involved.
UK Statistic Source Article Accessed
Average
Working Week
37.6
Hours
ONS UK Labour Market: February 2016 9 Mar 16
Average
Commute
41
minutes
Randstad https://www.randstad.co.uk/about-
us/press-releases/randstad-
news/savvy-super-commuters-
spend-time-wisely/
9 Mar 16
Average
Wage
£26 500 High Pay
Centre
http://www.mirror.co.uk/news/uk-
news/uk-average-salary-26500-
figures-3002995
9 Mar 16
Employment 31.42
Million
ONS UK Labour Market: February 2016 9 Mar 16
Average New
Car
£28 973 Driven
Data
http://www.motortrader.com/motor-
trader-news/automotive-
news/average-car-price-rises-28973-
08-08-2012
9 Mar 16
Average UK
Car Life
7.44
years
(Average
age) x 2 =
14.88 yrs
British Car
Auctions
http://www.autoexpress.co.uk/car-
news/consumer-
news/59950/average-uk-car-seven-
years-old
9 Mar 16
The Impact of James’s scenario on the Economy
 According to the ONS, the average working week in the UK is 37.6 hours.
 The average UK worker commutes 41 minutes per day or 3.42 hours per week.
 This equates to 9.1% of the 37.6 hour working week.
 The average UK wage is £26 500
 There are 31.42 million people in work in the UK
0.091 x 26 500 x 31.42m = £75.8billion
The Opportunity Costs of sub-optimal Utility to Louise
 Louise’s car is utilised for 220 minutes per week
 This equates to 7.94 days per year or 2.18% of the time
 The average cost of a newcar is £28 973
 The average useful life of a car is 14.88 years
 Linear depreciation would be £1947.11 per year
1947.11 / 7.94 = £245 per day (of utility)
This horrendous over simplification accounts only for linear depreciation of the asset (it does not
take into account simple necessities such as running and maintenance costs)

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This poses 2 possible extremes of scenario for Louise.
Affordable Access to Luxury
If utility levels are artificially raised to 100%, noting howunrealistic this prospect is, then:
If Louise maintains her 7.94 days at £245 per day “budget” the annual available pooled (shared)
fund would be:
£245 x 365 = £89 500 annual fund
Giving an acquisition fund based upon a 14.88 year life of:
14.88 x 89 500 = £1.33 million acquisition fund
Cheaper Access to Mobility
Alternatively based on the “vehicle price” remaining the same:
28 973 / 14.88 / 365 = £5.33 per day
Connectivity underpins the solutions to both James’ and Louise’s problems. However, it is the
combination of autonomy and connectivity, which truly unlock James’ problems and the
combination of connectivity with sharing which unlocks Louise’s problems. The combination of all 3
help to unlock problems which James and Louise together have yet to have recognised.

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APPENDIX B
Definitions of Autonomy
1. Department for Transport: The Pathway to Driverless Cars
This report uses two definitions to describe different levels of automated or driverless vehicles:
High Automation and Full Automation.
High automation
This means a vehicle in which a driver is required to be present and may need to take manual
control for some parts of the journey. Under certain traffic, road or weather conditions, the vehicle’s
automation systems may request the driver to take control.
Early highly automated vehicles may only offer an automated mode under certain very specific
driving conditions such as highway cruising or in lowspeed conditions. As the technology
develops, the vehicle will be able to undertake driving duties autonomously for a greater and
greater proportion of the time.
Full automation
This means a vehicle in which a driver is not necessary. The vehicle is designed to be capable of
safely completing journeys without the need for a driver in all normally encountered traffic, road
and weather conditions.2 This can be seen as the most advanced form of such technology.
Occupants of fully automated vehicles will be able to engage in tasks other than driving for the
entire journey. Fully automated vehicles may still offer a full set of controls to allow a driver to
resume manual control if they so wish, but this would be entirely optional.
2. Levels of Driving Automation as Defined by SAE International Standard J3016
A common taxonomy and definitions for automated driving in order to simplify communication and
facilitate collaboration within technical and policy domains. It defines more than a dozen key terms,
including those italicized below, and provides full descriptions and examples for each level.

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APPENDIX C
Project Plan
Ethical Issues
The vast majority of research material likely to be used for the development of this project will
consist of secondary data. The researcher will ensure all sources are accurately cited using the
Harvard Referencing System in accordance with the Staffordshire University BMR Module
Handbook.
Some primary research will be conducted as outlined above. The research will not involve
members of vulnerable groups, sensitive topics or deliberately mislead any participants in any way.
It will be purely voluntary and conducted with the participants full and informed consent at the time
the research is carried out. The researcher bears no responsibilityfor any loss caused to any
business entity or individual upon taking decisions based on the conclusions reached in the
proposed research work.
Primary research will not commence until approval of an appropriate Ethical Review.
Contingencies
Whilst a time line has been suggested at AppendixC, due to uncertainty and external
commitments it is possible that the researcher will be unable to complete the project by the
suggested deadline. If this risk seems likely to materialise the researcher will engage with their
tutor as soon as possible to revise planned submission time-scales or amend the scope of the
project.
Data Collection. It is assessed that this entire research proposal could be conducted using nothing
more than secondary data. It is expected that the 3 primary data sources will enrich the project and
bring life to elements of theory as the project evolves. Furthermore, by conducting primary
research there is potential for an element of real world validation of some of the researchers
proposed ideas whilst noting that due to time constraintsthe quantity of data is unlikely to be of
statistical significance.
Resource Requirements
Costs relating to travel, supplies, copying, software, data entry, etc. are likely to be minimal and will
be absorbed by the author.

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