Barriers and Driving Forces that Affect Potential Adopters of BECs in Sweden
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DEGREE PROJECT IN INDUSTRIAL MANAGEMENT, SECOND CYCLE, 30 CREDITS STOCKHOLM, SWEDEN 2021 Barriers and Driving Forces that Affect Potential Adopters of BECs in Sweden How the Transition to Battery Electric Cars can be Accelerated CHRISTIAN ASMAR RADE NIKOLIC KTH ROYAL INSTITUTE OF TECHNOLOGY SCHOOL OF INDUSTRIAL ENGINEERING AND MANAGEMENT
Barriers and Driving Forces that Affect
Potential Adopters of BECs in Sweden
How the Transition to Battery Electric Cars
can be Accelerated
by
Christian Asmar
Rade Nikolic
Master of Science Thesis TRITA-ITM-EX 2021:204
KTH Industrial Engineering and Management
Industrial Management
SE-100 44 STOCKHOLM
Barriärer och Drivkrafter som Påverkar
Potentiella Användare av Batterielbilar i
Sverige
Hur Övergången till Batterielbilar kan Accelereras
av
Christian Asmar
Rade Nikolic
Examensarbete TRITA-ITM-EX 2021:204
KTH Industriell teknik och management
Industriell ekonomi och organisation
SE-100 44 STOCKHOLM
Master of Science Thesis TRITA-ITM-EX 2021:204
Barriers and Driving Forces that Affect Potential
Adopters of BECs in Sweden
How the Transition to Battery Electric Cars
can be Accelerated
Christian Asmar
Rade Nikolic
Approved Examiner Supervisor
2021-06-04 Frauke Urban Tatiana Nevzorova
Commissioner Contact person
Abstract
The transport industry makes up a significant portion of the carbon dioxide emissions and the
greenhouse effect. Although the transition to electric cars is already happening, the transition is
not happening fast enough to meet the EU targets. Because of this, our study has the aim to
investigate how the transition to electric cars can be accelerated in Sweden. The study has the goal
to identify driving forces and barriers to the adoption of electric cars. Our study starts with a
literature review used to gather insight into the research area and construct the data collection,
which is done using a survey and interviews. Based on the empirical data, identified aspects are
presented. The data from the survey and interviews are combined to label each aspect as a driving
force or barrier.
Multiple driving forces for electric cars were identified. One of them was the driving experience.
Another was the low operational cost, which the potential adopters expected to remain low in the
future. It was also found that the potential adopters have good faith in the future development of
the charging infrastructure. Lastly, the visibility of electric cars in information channels and media
was found to be prominent. With these aspects already being considered relatively good for
potential adopters in Sweden, the focus should instead be put on the barriers. However, multiple
barriers of significance were found. Most of these stem from limited range, slow recharging, and
insufficient infrastructure. It was found that the slow charging and low density of fast charging
stations made electric cars impractical except for shorter distances. Also, these factors create range
anxiety for the drivers. To solve these issues, the government should incentivize the expansion of
the fast-charging network. The purchase cost and total cost of the electric car were also found to
be barriers. This is mainly due to the cost of the battery, which is significant. One suggestion is to
remove the VAT for electric cars, such economic incentives have proven efficient in other places
globally and will also be efficient in Sweden.
Keywords: electric vehicle, potential adopters, car, barriers, driving forces, adoption, diffusion
Examensarbete TRITA-ITM-EX 2021:204
Barriärer och Drivkrafter som Påverkar
Potentiella Användare av Batterielbilar i Sverige
Hur Övergången till Batterielbilar kan Accelereras
Christian Asmar
Rade Nikolic
Godkänt Examinator Handledare
2021-06-04 Frauke Urban Tatiana Nevzorova
Uppdragsgivare Kontaktperson
Sammanfattning
Transportbranschen utgör en betydande del av koldioxidutsläppen och växthuseffekten. Även om
övergången till elbilar redan sker, sker inte övergången tillräckligt snabbt för att uppfylla EU: s
emissionsmål. På grund av detta syftar vår studie till att undersöka hur övergången till elbilar kan
påskyndas i Sverige. Studien har som mål att identifiera drivkrafter och hinder för införandet av
elbilar. Vår studie börjar med en litteraturöversikt som används för att samla inblick i
forskningsområdet och konstruera datainsamlingen, vilket görs med hjälp av en enkät och
intervjuer. Baserat på empiriska data presenteras identifierade aspekter. Uppgifterna från
undersökningen och intervjuerna kombineras för att märka varje aspekt som en drivkraft eller
barriär.
Flera drivkrafter för elbilar identifierades. En av dem var körupplevelsen. En annan var de låga
driftskostnaderna, som de potentiella användare antog skulle förbli låga i framtiden. Det
konstaterades också att de potentiella användare har god tro på den framtida utvecklingen av
laddningsinfrastrukturen. Slutligen visade sig elbilarnas synlighet i informationskanaler och media
vara framträdande. Eftersom dessa aspekter redan betraktas som relativt bra för potentiella
adopterare i Sverige, bör fokuset istället läggas på hindren. Emellertid hittades flera hinder av
betydelse. De flesta av dessa härrör från begränsat räckvidd, långsam laddning och otillräcklig
infrastruktur. Det visade sig att den långsamma laddningen och den låga densiteten hos
snabbladdningsstationer gjorde elbilar opraktiska förutom vid kortare sträckor. Dessa faktorer
skapar också räckviddsångest för förarna. För att lösa dessa frågor bör regeringen uppmuntra
utbyggnaden av snabbladdningsnätverket. Elbilens inköpskostnad och totalkostnad visade sig
också vara hinder. Detta beror främst på kostnaden för batteriet, vilket är betydande. Ett förslag är
att ta bort mervärdesskatten för elbilar, sådana ekonomiska incitament har visat sig vara effektiva
på andra globala lägen, vilket kommer också att vara effektiva i Sverige.
Nyckelord: elektriskt fordon, potentiella användare, bil, hinder, drivkraft, användare, spridning
Table of Contents
1. Introduction 1
1.1 Background 1
1.2 Problem Formulation 2
1.3 Aim and Research Question 3
1.4 Delimitations 3
2. Literature Review 4
2.1 History of BECs 4
2.2 Greenhouse Effect and the Transport Industry 4
2.3 The Practical Differences Between Fossil Fuel Cars and BECs 5
2.3.1 Disadvantages of BECs Compared to Fossil Fuel Cars 5
2.3.2 Benefits of BECs Compared to Fossil Fuel Cars 7
2.4 Market Share of BECs in Sweden 8
3. Theoretical Framework 10
3.1 Innovation Adoption Process 10
3.2 Categories of Adopters 11
3.3 Attributes of Innovations 13
3.3.1 Relative Advantage 13
3.3.2 Compatibility 13
3.3.3 Complexity 14
3.3.4 Trialability 14
3.3.5 Observability 14
3.3.6 Perceived Risk 14
3.3.7 Cost 14
3.4 Research Model 15
4. Methodology 16
4.1 Research Design 17
4.2 Data Collection 17
4.2.1 Literature 17
4.2.2 Interviews 17
4.2.3 Survey 19
4.3 Data Analysis 21
4.3.1 Primary Sources 21
4.3.2 Secondary Sources 22
4.4 Research Quality 22
4.5 Research Ethics 23
5. Results 24
5.1 Survey 24
5.1.1 Demographics of Respondents 25
5.1.2 Distribution of the Answers and Statistical Measurements 26
5.1.3 Ranking of the Survey Questions 29
5.1.4 Ranking of the Attributes 32
5.1.5 Additional Comments 33
5.2 Interview 35
5.2.1 Relative Advantage 35
5.2.2 Compatibility 36
5.2.3 Complexity 37
5.2.4 Trialability 38
5.2.5 Observability 39
5.2.6 Perceived Risk 40
5.2.7 Cost 42
6. Analysis and Discussion 45
6.1 Barriers, Driving Forces and the Acceleration of the Transition to BECs 45
6.1.1 Relative Advantage 46
6.1.2 Compatibility 47
6.1.3 Complexity 48
6.1.4 Trialability 49
6.1.5 Observability 50
6.1.6 Perceived Risk 51
6.1.7 Cost 53
6.1.8 Summary of the Barriers and the Driving Forces 55
6.2 Similarities and Differences from Previous Studies 56
6.3 Reflection on Chosen Theory and Method 57
7. Conclusion 59
7.1 Contribution and Practical Implications 60
7.2 Limitations of the Study 61
7.3 Future Research 62
References 63
Appendices 70
Appendix I 70
Appendix II 72
List of Figures and Tables Figure 2.1 Plug-in Sales Trend in Sweden Figure 3.1 The adoption process Figure 3.2 The normal bell-shaped curve and the S-curve Figure 3.3 Illustration of the theoretical framework created Figure 5.1 The demographical distribution Table 4.1 General information regarding the conducted interviews Table 4.2 Description of each section’s purpose of the survey Table 4.3 Overview of the theories and themes that influenced the collected interview data Table 5.1 Segmentation of survey questions Table 5.2 Number of answers of each survey question and the percentage distribution of the score Table 5.3 Mean value, standard deviation, skewness, and kurtosis of the questionnaire Table 5.4 Ranking of the mean values of the questions Table 5.5 Ranking from the lowest score of the mean values from each attribute and its corresponding survey questions Table 5.6 Additional comments regarding disadvantages and advantages of BEC Table 6.1 Systematic process of labeling the aspects Table 6.2 Systematic process of labeling the adoption attributes Table 6.3 Combination of survey and interview data for each aspect, and its effect on the outcome of the adoption attributes
Acknowledgment We would like to sincerely thank all the professors and students from the Royal Institute of Technology KTH that helped us through this project. Special gratitude is shown to our supervisor, Tatiana Nevzorova, who gave us helpful guidance and appreciated assistance through the whole process. The study could not have been fulfilled without the contribution of the respondents from the survey and the interviews. A big thank you from us for taking the time and giving us valuable information. Also, we would like to show our appreciation for the comments, discussions, and peer feedback given by our fellow students who participated in the seminars. Without the love and motivation of our family members, the finalization of this thesis would not be possible. The greatest gratitude is shown to them by us. Christian Asmar & Rade Nikolic Stockholm, June 2021
Abbreviations EU - European Union GHG - Greenhouse gas BEC - Battery electric car EV - Electric vehicle CO2 - Carbon dioxide VAT - Value added tax
1. Introduction
This chapter will introduce the general knowledge of battery electric cars through the
background, which later follows with the problem formulation and explains the underlying
motivation for the study. Afterward, the research question is formulated through the influence
of the formulated problem, and lastly, the chosen delimitation is described.
1.1 Background
Since the first mass-market car, the Model T by Ford, the automotive industry has been
dominated by fossil-fueled vehicles. Although the technology that makes electric vehicles
possible has existed for a long time, it was not until recent times that electric vehicles have
become economically feasible for mass production due to previous technical limitations
(Bohnsack et al., 2020). When the first electric car was made, the existing battery technology
was substandard due to the low energy density in battery packs, which made it infeasible to
place a big and expensive battery pack that weighs a lot in a car (Bohnsack et al., 2020).
Because of this, the fossil fuel car simply was superior and therefore dominated for a long time.
However, with the recent battery development, the range of electric cars has vastly increased,
and with the constantly improving infrastructure for electric cars, electric cars are becoming
more and more synonymous with traditional fossil fuel cars. Previously, electric cars were not
designed to travel long distances as a consequence of these limitations. Nevertheless, for each
year that passes now, electric cars are becoming more and more equivalent to fossil fuel cars
in terms of travel range and price. However, even though this gap is closing in, there still exist
many limitations with electric cars that are not present on fossil fuel cars.
A key factor that has changed in recent times is the awareness of the changing climate.
Although climate change as an effect of greenhouse gases dates (GHG) back to the 1800s
(Solomon et al., 2009), the awareness of it has not been acknowledged until recent times. With
more and more countries being affected by it, more are looking for ways to change it. One key
part of the GHGs is that the transport industry makes up 30% of them (Statistics Sweden, 2020).
Fossil fuel cars make up a significant portion of this, and to combat the emission from the car
industry, more regulators are looking at ways to make people move over to electric vehicles
(Lutsey and Sperling, 2012). The changing climate can be seen as one of the major driving
forces of the transition to electric cars.
Due to increased incentives and more governmental regulations pushing auto producers to
produce electric vehicles, traditional automakers are sharing their plans to be fully electric in
the near future (VolvoCars, 2021). Also, new car producers who focus primarily on electric
cars have emerged. Some of them are Tesla, Polestar, Xpeng, and NIO, founded in 2003, 1996,
2014, and 2014. In the automotive industry, these companies are relatively new and can almost
be considered start-ups. These companies have gained increased market shares in recent years
and are threatening traditional automakers. Therefore, more traditional automakers are looking
at ways of how to participate in the transition to electric cars since it is well known in today’s
1society that electric cars are the future, and therefore, traditional automakers do not want to be
left with outdated technology in the years to come.
1.2 Problem Formulation
Since the 1990s, environmental concerns have grown higher and higher where stricter
regulations and policies have increased with hand (Marsden and Rye, 2010). For example, in
Sweden, there is a 60 000 SEK incentive for consumers who buy fully electric cars
(Regeringskansliet, 2020). These regulatory changes have aided more environmentally friendly
auto industry companies, while companies that affected the environment in a more harmful
manner had it harder to expand their traditional business since they would have to pay higher
taxes such as regulatory credits (Marsden and Rye, 2010).
The demand for battery electric cars escalated quickly since 2012 (Elbilsstatistik, 2020), which
caused incumbents to research and produce electric cars as a response in order to stay
competitive. Since 2012, the sales of electric cars have increased immensely in Sweden and
are expected to do so in the future (Elbilsstatistik, 2020). Meaning an increased market share
in the car industry. This means that cars that are based on internal combustion engines will
become outdated, and if incumbents do not change their focus area into electric cars, they will
eventually fade out as more and more customers will prefer electric cars over time.
From the third quarter of 2012 until the fourth quarter of 2020, the number of BECs (battery
electric cars) in Sweden had increased from 533 to 56 058 (Elbilsstatistik, 2020). Even though
the sales of BEC are increasing, the market share is significantly lower than other types of cars
(Transportstyrelsen, 2020; Elbilsstatistik, 2020). The latest data indicates that in 2020, 29 643
BEC cars were registered in Sweden, which was 8,6 % of that year’s market share (Allt om
Elbil, 2020).
The targets set to 2020 by the European Union (EU) regarding greenhouse gas (GHG)
emissions and renewable energy targets were not reached by all the members, including
Sweden (European Environment Agency, 2020). Furthermore, the additional targets for 2030
and 2050 for the EU members, including Sweden, emphasizes the necessity to put more effort
into reducing the GHG emissions in order to meet the emissions reduction targets (European
Environment Agency, 2020; EUobserver, 2019). All of these factors considered mean that the
electric car could be the new future for the car industry and the companies which majority of
their cars are dependent on fossil fuel are needed to change to electric cars. Not only that but
also to look back at their research and recent electric car productions in order to erase the errors
they made and implement potential improvements. However, as the climate is changing
quickly, the transition to electric cars must happen as soon as possible.
21.3 Aim and Research Question
In order to find a solution to the above stated problem, this study aims to investigate how the
transition to electric cars can be accelerated. To achieve this, the following research question
is formulated:
RQ: What are the driving forces and barriers that affect the consumer adoption process
of battery electric cars in Sweden?
1.4 Delimitations
The study will focus on finding the driving forces and barriers that affect the adoption process.
The sample target will be delimited to individual potential end-customers because BECs are in
the face of significant growth in the market share and the individuals have a stronger demand
force than companies themselves. Hence, the interest is solely on the individual potential
adopters. Additionally, the project’s focus will be nationally delineated by Sweden, as it is seen
as relevant because of where the project is taking place and because of the problem formulated
in the previous subchapter. Meaning that it facilitates the procedure of collecting data, which
increases the possibility of collecting larger amounts of data. A more global sample target is
not chosen because of the time constraint. Lastly, the thesis will be delimited to battery electric
cars.
32. Literature Review
The following chapter will present the literature review conducted. Firstly the history of BECs
and the environmental effects of the transport industry will be shown. Thereafter, the
differences between combustion engine cars and BECs are introduced which will have a
significant influence on the creation of the survey. Lastly, the market share will end this
chapter.
2.1 History of BECs
The beginning of the electric car’s history started in 1834 when the American inventor Thomas
Davenport built the first car solely driven by electricity. Nevertheless, the first electric car was
not practical enough to be able to penetrate itself into the market. William Morrison developed
the electric car and invented the first successful car around 1890, which helped spark the
general public’s interest (Anderson and Anderson, 2010). Over the next few years, the sales of
electric cars increased and accounted for approximately a third of all vehicles in the U.S. The
rise of the electric car did not last for long when Henry Ford in 1908 famously started mass
production of the Model T, a gasoline-powered car. The electric car’s market share declined
drastically because of Model T’s wide availability and affordability (Helmers and Marx, 2012).
Moving forward, during the 1990s, environmental concerns grew higher, and federal and state
regulations began to change the car market, which drove electric cars forward from the
perspective of demand. The environmental concerns and regulations grew higher over time,
leading to even more companies producing hybrid and fully electric cars. The announcement
of Tesla Motors in 2006 helped reshape the market by producing luxury electric sports cars
that had a distance range of more than 320 km on a single charge (Burton, 2013; Helmers and
Marx, 2012).
2.2 Greenhouse Effect and the Transport Industry
Currently, the greenhouse gases consist of several different gases that together make up the
total greenhouse effect. Although there are multiple greenhouse gases, CO2 is the one with the
most impact. Despite a ton of methane having 25 more times more warming potential than one
ton of CO2, the latter has a much more impact since CO2 stays in the atmosphere for centuries,
compared to methane, which stays in the atmosphere for decades (Pindyck, R., 2020).
The CO2 emissions originate from these different sectors in Sweden, where the sectors with
the most impact are domestic transports (32%), industry 32%, and agriculture 14% (Statistics
Sweden, 2020). As transportation makes up 32% of the total CO2 emissions in Sweden, it can
be stated that transportation is a big part of the changing climate. Because of this, a method to
combat the greenhouse effect is to reduce the amount of CO2 emissions in the transport
industry.
4Although electric cars have less emission than fossil fuel cars under operation, it is essential to
investigate how the two differ in their whole life cycles. According to a study made by Per et
al., (2018), it was shown that battery electric cars have significantly less effect on climate
change than fossil fuel cars. This is mainly due to the absence of greenhouse gas emissions in
the operation of electric cars. However, the carbon footprint of battery electric cars compared
to fossil fuel cars in the manufacturing phase is significantly higher (Pero et al., 2018). This is
due to the large amounts of metals, chemicals, and energy required to produce the electric
powertrain and the battery (Pero et al., 2018). Because of this, the electric car has to travel a
certain distance to compensate for the added production footprint, which is compensated by
the lack of CO2 emissions. One thing to note is that the energy mix used for charging the
electric car highly affects the distance the car has to travel before reaching the break-even
distance. This varies greatly between different countries due to different energy mixes. For
average European and Norway energy mixes, the break-even numbers are 45 000km and 30
000km (Pero et al., 2018), while for Poland, the break-even never happens during the lifecycle
of the electric car (Pero et al., 2018).
2.3 The Practical Differences Between Fossil Fuel Cars and BECs
An electric car differs from a fossil fuel car in some areas that affect the end customer's
experience of using the vehicle. Extensive research on this topic has been done by various
researchers worldwide, which have found many differences. Some of them, which the authors
deemed as most relevant for this study, will be listed below.
2.3.1 Disadvantages of BECs Compared to Fossil Fuel Cars
Slow charging
A major difference between electric cars and fossil fuel cars is the speed at which the car can
be recharged or refueled. Refilling a fossil fuel car is a trip to the nearest gas station and a few
minutes filling the tank. For electric cars, it is significantly different. Despite the availability
of charging stations for electric cars, most are not intended for fast charging, resulting in a
scarcity of fast charging stations (Giansoldati et al, 2020). Although the fast charging stations
are considerably faster, the energy rate is still inferior to fossil fuel stations and consumers
consider the time waiting as dead time (Graham et al., 2012). This makes electric cars
impractical for consumers who travel long distances on road trips regularly. It also imposes
additional planning for travelers on longer car trips or unplanned journeys (Axsen et al., 2013).
Need for home charging
Since electric cars are much slower to charge than regular fossil fuel cars, it is more time
efficient to charge the car while at home or work instead of doing so on the road while traveling
(Noel et al., 2020). This poses a challenge for plenty of consumers looking to buy electric
vehicles since many do not currently have access to home or work charging. Electric cars also
5need a special charging station when charged at home, simply connecting to the wall outlet is
a fire risk. Therefore, there is an initial cost to enable home charging.
Insufficient number of fast charging stations
As previously mentioned, electric cars have slower charging times. This makes many electric
car owners prefer to only charge in high speed charging stations, which are far more spread out
than regular charging stations (Giansoldati et al, 2020). The problem is amplified in bad
weather since electric cars’ range is reduced in low temperatures (Reyes et al., 2016). Many
electric cars have heat pumps to combat this issue, but those who do not, suffer severe range
loss in lower temperatures.
High purchase price
Another disadvantage with electric cars is the high initial purchase price, which can be up to
$15 000 higher than similarly sized gasoline cars (Krause et al., 2013). Although plenty of
countries offer incentives to combat this issue, the incentives are not strong enough and most
electric cars are still considerably more expensive than their fossil fuel counterparts. The high
purchase price is a strong barrier for potential adopters (Berkeley et al., 2018). The high price
is somewhat relieved by the lower fuel costs since electricity is cheaper than gas (Gelmanova
et al., 2018), but the high purchase price is still an obstacle for many consumers looking to buy
electric cars.
Range anxiety
As a combination of multiple factors, many electric car owners experience range anxiety.
Electric cars have less range than fossil fuel cars and therefore have to refill energy more often.
Also, electric cars' battery capacity is reduced during the winter (Reyes et al., 2016; Charged
Future, 2020). This is often combated with a heat pump in the electric car but not all electric
cars have it. In addition, the fast-charging stations are not always nearby (Giansoldati et al,
2020; Delos et al., 2016). Because of these factors, many owners experience the fear of being
stranded with their electric cars (Egbue & Long, 2012). This is further enhanced by the fact
that owners who have access to home charging prefer to charge when reaching home instead
of having to stop somewhere along the road to charge since the time charging at public stations
is considered dead time (Graham et al., 2012).
Battery depreciation and disposal
The battery in the electric car is the most expensive component of the car. For consumers who
buy electric cars, many are uncertain what will become of their cars after several years when
the warranty is over. Replacing the battery is a big cost (Krause et al., 2013) and is something
that most consumers want to avoid. Also, since the battery gets worse during its lifetime, battery
deprecation is a real issue and therefore consumers fear that their battery cars’ range will
worsen over time (She et al., 2017). This deprecation also affects the resale value of the car.
62.3.2 Benefits of BECs Compared to Fossil Fuel Cars
However, for consumers with the right setup, infrastructure, and circumstances, electric cars
can be more practical than fossil fuel cars.
Lower operating costs
For consumers with access to home charging, electric cars can be very cheap to operate. The
cost difference between petrol and electricity at home per kWh is usually relatively big
(Gelmanova et al., 2018). Because of this, consumers who travel for longer periods will save
money in the long run. Also, the electric motor has fewer parts than the fossil fuel internal
combustion engine, resulting in lower maintenance costs (KIA, 2017). Because of these factors,
the electric car is cheaper to use compared to the operation of the fossil fuel car.
Better performance and driving experience
Electric cars have instant torque, meaning that the car accelerates instantly when the accelerator
(the name for the gas pedal in electric cars) is being pressed. This results in electric cars having
higher acceleration than fossil fuel cars. This effect is further amplified with the electric motor
only having one gear resulting in the car seamlessly speeding up without changing gears.
Furthermore, the engine in the electric car produces less sound than the internal combustion
engine, resulting in less noise pollution when driving (Pardo-Ferreira et al., 2020). Together,
these factors make the electric car perform better and make the driving experience better for
those who do not like the engine sound.
More environmental friendly
Consumers who want to be environmentally friendly are going to benefit from purchasing an
electric car. Over the lifecycle of both types of vehicles, electric cars are considerably much
more environmentally friendly than fossil fuel cars if the energy used for the electric car is
“green enough” (Pero et al., 2018). This will make the consumers who are aware of the
environment feel less responsible for climate change and feel that the individual is contributing
to changing the climate for the good (Sovacool & Hirsh, 2009).
Convenient charging for everyday trips
Consumers who do not travel long distances regularly, do not make road trips, and also have
access to work/home charging will find the charging of the electric car more convenient than
the fossil fuel car. Instead of having to regularly visit gas stations to refill the car, the owner
can instead just seamlessly charge at home or at work by plugging in the car in just a few
seconds. Another convenience is that charging at home will mean that the car will always have
a full battery at the start of the next day, which is not a possibility for fossil fuel car owners.
Together, these factors make the charging experience very convenient for consumers with the
right circumstances.
7Tax credits and incentives
Many countries offer tax credits and tax reliefs to owners of electric cars. These vary greatly
between countries. In Sweden, it is 60 000 SEK which will be increased to 70 000 SEK later
this year (Regeringskansliet, 2020). Historically, this credit has increased and is expected to
increase further on (Regeringskansliet, 2020). In Norway, electric cars are already outselling
fossil fuel cars due to big amounts of tax credits and incentives to buy an electric car in Norway
(Mersky et al., 2016).
Special benefits
In some places, electric cars get the special benefits of using certain lanes on the highway, free
parking at certain locations, use bus lanes, or other privileges. These types of benefits are
heavily used in Norway, where electric car owners have many privileges that fossil fuel car
owners do not have the right to (Deuten et al., 2020). 40% of passenger vehicle sales in 2017
consisted of electric cars in Norway (Deuten et al., 2020).
Growing EV infrastructure
Electric cars are the future and are expected to grow in popularity in the coming years. This
statement is verified by the fact that many countries are looking to ban fossil fuel vehicles in
the near future (Burch and Gilchrist, 2020). Additionally, several automakers have shared their
plans to become fossil fuel in the near future (VolvoCars, 2021). As a consequence of the
growing popularity, the current problems around the infrastructure for electric cars are slowly
fading away and becoming less of an issue. Although it will take time, the infrastructure for
electric cars is slowly but steadily improving thanks to the climate change goals and incoming
bans of fossil fuel cars.
82.4 Market Share of BECs in Sweden
Figure 2.1: Plug-in Sales Trend in Sweden (CleanTechnica, 2021)
Although EV sales have only made up for a very small amount of total automotive vehicle sales
until recent years, this change is expected to increase even further through exponential growth,
according to the Swedish-based EV-Volumes database (CleanTechnica, 2021). The model
states that electric and hybrid vehicles in Sweden will make up 65% of the total new automotive
sales in 2025. This growth is fuelled by regulatory incitements that encourage customers to buy
fossil fuel free cars. The current incitement of 60 000 SEK has increased historically and will
increase to 70 000 SEK by 2021, and is expected to increase even further (Regeringskansliet,
2020). Because of this, the market share in Sweden of electric vehicles is expected to increase
in the future. Similar progress can be found in other developed countries that are looking to
phase out fossil fuel cars (Burch and Gilchrist, 2020).
93. Theoretical Framework
This chapter will represent the theoretical framework that will be used for the structure and
analysis of the study. The framework has been chosen based on the problem formulation and
the literature review. The purpose of this framework is to give guidelines to the study and
facilitate the analysis, interpretation, and coding of the empirical outcomes. Additionally, the
chosen framework is correlated with the research question because the attributes affect the
diffusion rate and the adoption which are meaningful factors for the adoption acceleration.
3.1 Innovation Adoption Process
An innovation can be defined as “an idea, practice, or object that is perceived as new by an
individual or other unit of adoption” (Rogers, 1995, p.11). An idea is an innovation if it seems
new to the individual. Before an individual adopts an innovation, the potential adopter has to
receive knowledge about it. This process of learning before adapting is called Innovation
Adoption Process (Rogers, 1995) and is listed and explained below with five different stages:
Figure 3.1: The adoption process
Knowledge (Awareness)
This is the very early stage of the process where the individual is for the first time exposed to
the existence of the innovation while gaining introducing knowledge of its functions (Rogers,
1995). The individual lacks deep and complete understanding and is a passive stage where the
inspiration is low to find out more (de Hart et al., 2015).
Persuasion (Interest)
In this stage, the individual has gained a specific interest or feeling towards the innovation
which is based on the previous knowledge and additional information is being actively sought.
10Decision (Evaluation)
The decision stage in this process happens when the individual is analyzing the positive and
negative outcomes of the innovation. If the individual evaluates the innovation as interesting
and suitable the person will decide to try it out but not fully adopt it yet.
Implementation (Trial)
This is where the innovation is tried out by the individual. Before this stage, the process has
been mainly mentally demanding. Now the actual innovation is put into practice by the
individual. This phase could be seen as a practical testing phase where the expectations and
reality are measured against each other.
Confirmation (Adoption)
The confirmation stage is the final adoption decision. After the trial of the innovation, the
individual wants to confirm if the innovation should be completely adopted. If the decision is
reinforced the individual will keep the adoption of it and even become more attached to it.
3.2 Categories of Adopters
Innovations, which are presented to the market, will not be adopted by all individuals in a social
system at the same time. Instead, the innovations are adopted in different time sequences, which
can be classified into separated adopter categories based on the initiating usage of a new idea.
The adoption of innovation over time can be described by the diffusion of innovation model,
which was popularized by Rogers (1995). The model can be illustrated in a diagram and a
graph such as in Figure 3.2. The blue bell-shaped curve shows the adoption of innovation on a
frequency basis over time, while the yellow S-shaped curve shows the adoption on a cumulative
basis. The model consists of five standardized categories of adopters: Innovators, Early
Adopters, Early Majority, Late Majority, and Laggards. The x-axis illustrates time, while the
x-axis illustrates the percentage of adopters, i.e the market share.
Figure 3.2: The normal bell-shaped curve and the S-curve (Rogers, 1995). The x-axis indicates the
time.
11The specific adopter categories can be separately explained as following (Rogers, 1995):
Innovators
These adopters are venturesome and are completely impatient in order to try new ideas. The
innovators play a significant role in the process of diffusing innovation by initiating the new
idea in the social system by importing the innovation from the external side of the system’s
boundaries. The shortest period of innovation adoption comes from the innovators compared
to all of the other categories.
Early adopters
The early adopters serve as the greatest opinion leaders in most social systems. Advice and
information regarding the innovation from early adopters are seen as reliable and trustworthy
by potential adopters. Early adopters are considered as “the individuals to check with” by
potential adopters before adopting an innovation.
Early Majority
The new ideas are adopted by this category just before the average adopting member of a social
system. Leadership positions are seldom held by the early majority on the adoption process and
they interact frequently with their peers. The early majority are more deliberate and want to
pick the same proven innovation as others in order to minimize the risk when adopting the
newly emerging idea.
Late Majority
The late majority would not adopt the innovation if they did not feel the increasing network
pressure. These adopters only adopt when most others in their social network have been doing
the same. After almost all of the practical uncertainty of the innovation is removed, the late
majority is convinced to adopt.
Laggards
Laggards are the last ones to adopt an innovation in a social system. Laggards are quite
traditional and frequently refer to the past, meaning that they compare to what has been done
in previous generations, “the way we have always operated”. Before adopting the innovation,
the laggards have to be entirely certain that the new idea will not fail. One of the reasons is
their limited economic resources.
123.3 Attributes of Innovations
The theory of Diffusion of Innovations by Rogers (1995) and its extension made by Bauer, R.
A. (1960), and Gatignon and Robertson (1989) will be used as the theoretical framework in
this study in order to understand the factors that drive or hinder the consumer adoption process
of BECs in Sweden. There exist different kinds of theories regarding the theory of Diffusion
of Innovation, however, the theory given by Rogers (1995) has been chosen as it is widely
accepted in the academic area and is a useful systematic framework to describe adoptions
(MacVaugh and Schiavone, 2010). Furthermore, the chosen framework does not include all
literature in Diffusion of Innovations, rather, Roger’s five attributes of innovations and its
extension will be used, which explains the innovations’ characteristics that affect the diffusion
and adoption rate. Roger’s selection of these five attributes is based on previous research and
writings. Additionally, the standard classification of attributes can be seen as descriptions of
innovation characteristics in universal terms so that it can be used without dependence on the
type of innovation. The five attributes and the extensions are namely; Relative advantage,
Compatibility, Complexity, Trialability, Observability, Perceived Risk, and Cost, which are in
detail explained in the subheadings down below.
These attributes will be used for the structure and questions of the interviews and questionnaire.
Furthermore, the themes used in the coding phase for the collected empirical data will be based
on the characteristics given by Roger’s theory and the extensions. In detail, this means that the
data and arguments given by the interviewees will be analyzed and connected to respective
themes in order to find driving forces and barriers that affect the adoption rate of electric battery
cars in Sweden.
3.3.1 Relative Advantage
This type of attribute is explained as the degree to which an innovation is perceived as being
better than the idea it supersedes (Rogers, 1995). Meaning how potential consumers/adopters
perceive the innovation relative to its predecessor or other competing options. A potential
adopter wants to know the degree to which the innovation is better than existing ideas. Relative
advantage is one of the most important factors in order to predict an innovation’s future rate of
adoption (Rogers, 1995).
3.3.2 Compatibility
Compatibility is a characteristic that indicates to which extent the idea or innovation is
perceived as consistent with the potential adopters’ lives, e.g. previous experiences, needs,
values, beliefs, etc. The higher the compatibility is in innovation the less uncertain it is to the
potential adopter. If a significant lifestyle change needs to be made before adopting the
innovation, then the risks are higher for it to be unsuccessful because it is not compatible with
the adopter’s lifestyle. There is a positive relationship between how compatible the innovation
is and its adoption rate.
133.3.3 Complexity
The extent to how difficult the innovation or idea is to be understood and used by the potential
adopter is the definition of the term complexity in this case. The harder it is for potential
adopters to get a clear understanding of the innovation the less likely it is for it to get adopted.
The time is not highly invested by the potential adopter regarding learning innovation, hence,
the negative relationship between complexity and the adoption rate. Empirical studies in
Canada and Sweden have concluded that complexity was the second highest innovation
characteristic that was related to the adoption rate (Roger, 1995).
3.3.4 Trialability
The degree to which a potential adopter can experiment and explore innovation on a limited
basis is described by the term trialability. A potential adopter would rather try out the
innovation before adopting it because then the individual would feel less uncertain about the
innovation when evaluating its benefits. There exists a positive relationship between an
innovation’s trialability and its adoption rate.
3.3.5 Observability
The extent to which the results and benefits of an innovation or idea are visible and
communicable to potential adopters is defined by observability. Before adopting an innovation,
an individual wants to observe its practicality in order to see the benefits before making a
decision of adoption. This adoption attribute is mostly affecting the adopter types, which come
after early adopters and they rely on seeing these people using the innovation.
3.3.6 Perceived Risk
As a further addition to Rogers’s (1995) five attributes, some scholars extend the diffusion of
innovation framework with the theory of perceived risk described by Bauer, R. A. (1960). The
perceived risk of innovation is to which degree the adopters experience the innovation as risky
and uncertain. This negatively affects the adoption rate of innovation and therefore a high
perceived rate reduces the chance of adoption. For electric cars, the perceived risk can be that
electric cars are not the future (and therefore the existing infrastructure problems will not be
solved) and/or that the electricity prices will rise in the future making electric cars equally
expensive as fossil fuel cars to use.
3.3.7 Cost
As a last extension of the framework, Gatignon and Robertson’s (1989) theory of cost will be
used. Although Rogers (1995) included Cost in the Relative advantage attribute, it was deemed
that the high relevance of cost for electric cars makes it worthy to be separated. This will enable
a better focus on the cost in this study. The cost associated with innovation is a negative
attribute and therefore, a higher cost results in a lower adoption rate of the innovation. This
attribute consists of three parts: purchase cost, switching cost, and usage cost. In the case of
electric cars, the purchase cost represents the purchase of the electric car. Regarding the
14switching cost, it can be the infrastructure costs associated with switching over such as the need
for a charger. Lastly, the usage costs correspond to the wear, tear, and fuel costs associated
with electric cars.
3.4 Research Model
The framework will be a combination of the attributes mentioned in 3.1.1 to 3.1.7, i.e consist
of relative advantage, compatibility, complexity, trialability, observability, perceived risk, and
cost. This framework will be used to facilitate the analysis of the collected data in this study.
Figure 3.3: Illustration of the theoretical framework created
154. Methodology
This chapter will present the used methodology divided into five subchapters. First, the
research design of this study is described. This is followed by the data collection and the data
analysis. Thereafter, the research quality and research ethics of this study are discussed.
4.1 Research Design
The purpose of the study is to collect data that correlates to the driving forces and barriers that
affect the consumer adoption process of battery electric cars in Sweden. In order to meet this
purpose, a combination of an inductive and a deductive research approach was employed, in
other words, an abductive approach (Blomkvist and Hallin, 2015). The abductive approach was
used in order to compare the empirical outcome with the literature and theory chosen, and vice
versa. Interview questions were created in a semi-structured manner when collecting the
qualitative data in order to give the interviewee an open space to add further information that
was not thought of or planned beforehand. Additionally, a survey was created in order to collect
quantitative and qualitative data. Furthermore, the types of data were collected from potential
adopters because the focus on the performed study was on end-customers and not on the
producers themselves.
There are different kinds of academic research purposes such as descriptive (where the focus
is on characteristics of the study in order to understand the “what”), exploratory (the data
collected through exploration is used to come up with basic understandings of actions or
conditions of the researched area), and explanatory (where the main focus is to explain the
causes of the phenomena itself) (Yin, 2014). In this study, the consumer adoption process of
electric cars has been explored. This was done through the performance of an explorative case
study (Yin, 2014) on finding the attributes that affect the consumer adoption rate.
The strategy and approaches of a study for a researcher can have plenty of dimensions when
collecting the empirical data. On the dependence of the research question design, a researcher
has the possibility to choose between a case study, a survey (with a questionnaire for example),
an experiment, and analysis of previously made studies such as case study for example(Yin,
2014; Creswell and Poth, 2017). Since the sole purpose of the research is to study driving
factors and barriers that affect the consumer adoption process of battery electric cars, a case
study has been selected because it facilitates deep analysis of a target group, in this case,
potential adopters (Blomkvist and Hallin, 2015).
The theoretical framework, which contains Roger’s (1995) five attributes, and the addition of
them by Bauer (1960) and Gatignon and Robertson (1989) was used to give guidelines through
the research process and also for the structure and analysis of the study. More specifically, for
the qualitative interviews, interpretation, and coding of the empirical outcomes, and facilitation
of the analysis. The framework was the basis for the exploratory case study and the collection
of the qualitative data.
164.2 Data Collection
As the focus of the project was to understand the perspectives of the end-customers within
electric cars in Sweden, an abductive approach has been executed in order to collect relevant
data to create an updated paradigm. The abductive approach will be based on quantitative and
qualitative research methods. Interview questions and a survey will be created and used for the
study’s collection of data. This method will be executed during the data collection from
potential adopters by digital communication. During this study, quantitative and qualitative
data have been collected through the conduction of interviews and collection of survey
responses. Concurrently, the existing literature has been researched.
4.2.1 Literature
In order to research the existing literature in a critical manner, the credibility of sources such
as articles, books, and journals was inspected. The existing literature was examined by the
usage of reliable academic search engines such as Web of Sciences, KTH Library, Google
Scholar, and Scopus. Furthermore, the amounts of and types of citations were compared to the
literature themselves, which indicated the diffusion, impact, and acceptance of them (Yin,
2014). Additionally, in order to confirm the validity of the chosen literature (Yin, 2014), several
different sources were used that had the same or similar argument, which reinforced the
theories and concepts that were chosen.
4.2.2 Interviews
Before creating the interview questions, a theoretical framework was carefully chosen in order
to have a strong basis for the whole research process. After the theoretical framework was
defined, the interview questions were created, which were influenced by the framework.
Furthermore, when the interview questions were finalized, the questions’ quality and
correlation to the framework were confirmed by our supervisor. The conduction of the data
collection of the qualitative interviews was made through digital communication. The digital
tool that was mainly used was Zoom. The length of the interviews varied due to each
interviewee having different prior knowledge regarding the topic, and thus some interviewees
provided more detailed answers than the others. Every conducted interview was recorded in
order to be able in the later stages to transcribe and code the empirical outcome. Before each
interview, the interview questions were sent to the future interviewee (Hesse-Biber and Leavy,
2010) by email and a confirmation of recording the interviewee was asked and respected
(Swedish Research Council, 2017). The table below, Table 4.1, illustrates the general
information of the 15 interviews conducted. The selection was made by emailing professors,
students, and external individuals in the authors’ social network and thereafter only
interviewing individuals who did not own a BEC. Meaning that the interviewees were seen as
potential adopters.
17Table 4.1: General information regarding the conducted interviews
Company/ Duration
Interviewee Role / Field of Study Date
Organisation [min]
Doctoral Student at the Unit of
Interview A KTH Sustainability, Industrial 2021-03-26 32
Dynamic & Entrepreneurship
Doctoral Student in
Interview B KTH Sustainable Operations 2021-03-29 25
Management
Interview C KTH Docent in Operations Strategy 2021-03-30 28
Associate Professor in
Interview D KTH Industrial Engineering and 2021-04-01 33
Sociotechnical Systems
Interview E Vattenfall IT Service Strategist 2021-04-01 27
Lecturer and Researcher in the
Interview F KTH Institution of Industrial 2021-04-06 36
Economics and Management
Interview G Ellevio AB Process Developer 2021-04-06 19
Associate Professor at the Unit
Interview H KTH 2021-04-07 22
of Heat and Power Technology
Professor of Production
Interview I KTH 2021-04-08 24
Logistics
Associate Professor at the Unit
Interview J KTH 2021-04-12 17
of Management & Technology
Interview K Picsmart AB Field Operator 2021-04-12 32
Senior Lecturer in the
Interview L KTH Institution of Industrial 2021-04-15 35
Production
Doctoral Student at
Interview M KTH Department of Energy 2021-04-15 32
Technology
Associate Professor in
Interview N KTH Operative Industrial 2021-04-16 30
Production Control
Sweco
Interview O Measuring Engineer 2021-04-18 N/A*
Sverige AB
* The interviewee responded to the questions through e-mail
184.2.3 Survey
In order to gather additional data, a questionnaire was created and later responded to by the
respondents. The creation and design of the questionnaire were made by the thesis’s authors
where aspects regarding the chosen framework were considered. Furthermore, as the interview
questions were created before the questionnaire, the creation and design of the questionnaire
were influenced by the already created interview questions and other publications, which
consisted of similar types and contents of questionnaires. Before allowing any respondents of
the questionnaire, a critical review was sought by sending it to the authors’ supervisor, which
was later received and the comments were carefully considered while upgrading the
questionnaire which enhanced its relevance and quality (Blomkvist and Hallin, 2015). The
questionnaire allowed the respondents to complete it all by themselves without any interference
from the authors. This was made possible by Google Forms which allows the potential
respondent to directly answer the questions in the computer or other digital tool. In order to
analyze the questionnaire’s outcome efficiently, every respondent had the same set of questions
in the same order (Saunders et al., 2015). This allowed the later part to use the same procedure
to collect and analyze each data given from the survey. Aforementioned, the questions were
connected to the framework, and this was done in order to reflect and connect to the aim of the
research project. This resulted in relevant questions that enabled relevant results for the study
(Zikmund et al., 2010).
The created questionnaire mainly collected quantitative data where the respondent had the
possibility to answer close-ended questions in numerical order from 1 to 5 (Creswell, 2014;
Maurer and Andrews, 2000; Croasmun and Ostrom, 2011), where 1 = Much Worse, 2 = Worse,
3 = Equally good/bad, 4 = Better, 5 =Much better. These scales were created in order to
compare each question to the existent competitive options to battery electric cars and also to
conclude, which categories are seen as driving forces or barriers. The scales below 3 were seen
as negative and the scales above 3 were seen as positive because of the chosen meaning that
each scale had. In total, 26 questions were created, which were segmented into three parts:
demographics, the attributes from the created framework, and additional comments. These
consisted of three, 22, and one question respectively. 25 questions were of a quantitative
character while one was of qualitative character. The survey was shared through social media
such as Linkedin and Facebook where potential adopters of BEC could answer it. Almost all
of the questions could only be answered with predetermined responses, the scales, which were
necessary to label each question in the barrier or driving force domain. Additionally, the survey
consisted of an open-ended question at the end of the questionnaire where qualitative data was
the only possible data to gather from it. This allowed the respondent to add additional
information that she or he did not think was included in the questionnaire which enabled deeper
information and answers than quantitative data would (Creswell, 2014).
Furthermore, the questionnaire worked as a method to gather additional data which was later
used to identify correlations and possible differences from the data gathered from the
interviews. This reinforced both findings because of the concluded correlations between each
19topic from the qualitative and quantitative data. The data was collected and received in the form
of an Excel sheet where concrete data were analyzed and illustrated through diagrams. The
survey respondents were not the same individuals as in the interviews in order to receive two
different data sets for the interviews and the survey. A total of 60 unique survey responses were
collected.
Table 4.2: Description of each section’s purpose of the survey
Survey section Purpose
General Questions To identify the demographics of the respondents which could be
used for the analysis of the distribution of the survey
Relative Advantage To investigate the respondents’ view regarding the different aspects
of the relative advantage of battery electric cars compared to other
types of cars
Compatibility To investigate the respondents’ view regarding the different aspects
of the compatibility of battery electric cars compared to other types
of cars
Complexity To investigate the respondents’ view regarding the different aspects
of the complexity of battery electric cars compared to other types of
cars
Trialability To investigate the respondents’ view regarding the different aspects
of the trialability of battery electric cars compared to other types of
cars
Observability To investigate the respondents’ view regarding the different aspects
of the observability of battery electric cars compared to other types
of cars
Perceived Risk To investigate the respondents’ view regarding the different aspects
of the perceived risk of battery electric cars compared to other types
of cars.
Cost To investigate the respondents’ view regarding the different aspects
of the cost of battery electric cars compared to other types of cars
Optional Comment To identify additional opinions regarding battery electric cars that
could be implemented in the chosen attributes
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