The need for change : Influencing factors on battery electric vehicles (BEVs) adoption among generation Y within the European market.

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The need for change

Influencing factors on battery electric vehicles (BEVs)

adoption among generation Y within the European market.

MASTER THESIS WITHIN: Business Administration NUMBER OF CREDITS: 15 credits

PROGRAMME OF STUDY: International Marketing AUTHORS: Alexandru Armasu & Martin Winkler JÖNKÖPING May 2020

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Acknowledgements

We would like to express our gratitude towards everyone who has helped us throughout the process of researching and writing this thesis. In particular our thesis advisor, Professor Tomas Müllern from Jönköping International Business School, whose guidance kept us on track the entire way. Tomas always provided valuable input and guided us throughout the whole writing process.

In addition, we would like to sincerely thank Jönköping University who made it possible to finalize our thesis even though the overall situation regarding the COVID-19 virus forced all countries to take massive steps in order to decrease infected people.

Furthermore, we would like to express our gratitude towards our colleagues who always provided valuable feedback on our thesis and guided us to this version of the given master thesis. Moreover, we would also like to thank all our participants whose insights and perceptions gave us the possibility to analyze a major topic of interest for the upcoming future. Also, for their invaluable decision to help us during the massive pandemic panic, it would have been impossible without their input.

Finally, we must also express our appreciation for our families and Martin especially for his fiancée Nina-Madeleine as they always supported us throughout our academic career and held our back in good times such as in bad times.

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Master Thesis Degree in Business Administration

Title: The need for change. Influencing factors on battery electric vehicles (BEVs) adoption among generation Y within the European market.

Authors: Armasu A. and Winkler M. Tutor: Tomas Müllern

Date: 2020-05-18

Key terms: BEV adoption, generation Y, influencing factors, perception, automotive

Abstract

Background: Climate change has been becoming a major topic of interest, for research as well

as for society. Transport caused emissions are constantly growing which forced the European Union to set the goal to decrease transport related emissions by 60% until 2050. A heavily discussed and promising tool seems to be being found in battery electric (BEV) vehicle adoption. However, BEV adoption seems to be underachieved which raises questions about potential influencing factors on BEV adoption. Additionally, latest research elaborated perception to be one of the key topics of interest for consumers adopting fully electric vehicles.

Purpose: The purpose of this thesis was to examine influencing factors affecting BEV

adoption and the perception of those factors among generation Y consumers.

Method: To attain the purpose, a qualitative research was conducted. After collecting

secondary data to evaluate existing factors influencing consumer’s willingness to adopt BEVs, 16 participants accountable to generation Y have been interviewed using semi-structured interviews. Using a qualitative research approach valuable data and in-depth insights which are essential for markets such as the automotive industry.

Conclusion: The results show that there is a generally positive attitude towards BEV adoption

among generation Y. However, there have been five influencing factors affecting consumer’s willingness to adopt BEVs. Analysis of the perception of each factor allowed the research team to get in-depth insights and to elaborate the importance of each factor and how the factors interrelate. Based on the gathered data relationships between influencing factors have been highlighted and based on

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Key Terms

Electric Vehicles: Electric vehicle is an alternative fuel automobile that uses electric power as

means of propulsion instead of fossil fuel (Pollet et al., 2012).

Battery Electric Vehicles (BEV): The electric vehicles battery powers the vehicles via an electric

motor, this battery has a limited every capacity and must be replenished via an external electrical source (Pollet et al., 2012).

Internal Combustion Engine (ICE) cars: Internal combustion engine cars still represent the

majority of currently used passenger cars (Monaghan, 1988). As gasoline or diesel are needed in order to power the car’s engine the technology has been widely accused to negatively impact the climate due to the need of fossil fuels and emitted emissions (Abdel-Rahman, 1998).

Generation Y: Summarizes all people being born from 1982 to 2002 (Pendergast, 2009).

Throughout the last years there have been several terms developed such as “Millennials, Nexters, Generation www, the Digital Generation, Generation E, Echo Boomers, N-Gens” (Martin, 2005, p. 40) but Generation Y has been proven to be the most widely accepted term. It is widely acknowledged that generation Y is being described as the most educated generation (Howe & Strauss, 2009).

Technological Acceptance: The technological acceptance is a psychological process that

undergoes in a consumer's mind whether to accept it or to reject it, based on the attitude and intention that were cultivated during this process (Davis, 1989).

Technology Acceptance Model (TAM): The TAM was developed to explain the underlying

factors behind accepting or rejecting a new technological innovation based on the subdimensions of Perceived Usefulness, Perceived Ease of Use and External Factors (Davis, 1989).

Technological Readiness Index (TRI): The Technological Readiness Index deals with

understanding individual’s tendency to embrace upcoming and advanced technologies (Blut & Wang, 2019).

Behavioral Intentions: “Behavioral Intentions are instructions that people give to themselves to

behave in certain ways”. (Triandis, 1980, p. 203).

Consumer behavior: It is the study of individuals, groups and organizations regarding the

acquisition, use and disposal of goods or services that they expect will satisfy their needs, including the emotional and mental responses (Schiffman & Wisenblit, 2015).

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List of Figures

FIGURE 1.STRUCTURE OF THE RESEARCH ... 4

FIGURE 2.TECHNOLOGY ACCEPTANCE MODEL (DAVIS,1998) ... 12

FIGURE 3.TECHNOLOGY READINESS INDEX (PARASURAMAN,2000)... 13

FIGURE 5.SUMMARIZED KEY FINDINGS RQ2 ... 41

FIGURE 6.GENERAL PERCEPTION OF BEVS AMONG GEN Y ... 42

FIGURE 7.BEVS PERCEIVED POTENTIAL ENVIRONMENTAL IMPACT. ... 43

FIGURE 8.THE BEV-ADOPTION MODEL (OWN MODEL). ... 51

List of Tables

TABLE 1.CONTENT ANALYSIS EXAMPLE ... 23

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1 Introduction

_____________________________________________________________________________________ The purpose of this chapter is to provide background information and related figures which subsequently give an insight why the given field of research deserves to be studied. In addition, the following chapter will

present the purpose of the study and the research questions.

_____________________________________________________________________________________

1.1 Background

CO2 emissions within the European Union (EU) linked to transport (including road traffic) have been the only pollution threat which have not decreased since 1990. In addition, they increased until 2005 and nearly remained steady until 2016, counting a total increase of approximately 24% in relation to 1990 (World Health Organization [WHO], 2019). Therefore, the EU has defined a goal of decreasing emissions linked to transport by 60% until 2050 (European Parliament, 2019). Furthermore, cities such as Madrid, Amsterdam, London, Oslo, Milan, Athens, Frankfurt and Berlin have started or already concretized plans to ban diesel and/or petrol cars from city centers (Nieuwenhuijsen & Khreis, 2016; Bendix, 2019).

Secondly, fossil fuel has been one of the biggest drivers of climate change recently beside industrial waste (Höök & Tang, 2013). The fact that fossil fuel is still in high demand is unquestionable, as a better and more practical solution has just not yet been put at the discussion table. Furthermore, with the “Dieselgate” scandal it was clear that assessing the global situation became an even bigger problem with companies deliberately lying about their emissions (Siano et al., 2017). A research done by Covert et al. (2016) has meditated on the future of fossil fuel and the results were quite discouraging, both for the future of EV’s and climate change.

As mentioned before, transport including vehicles is one of the core drivers of climate change which contributed to the fact that battery electric cars (BEV) have been becoming tremendously relevant, which can be derived from constantly growing market shares of 45% in Norway, 8.9% in the Netherland or 5% in Sweden counted in the first half of 2019 (Gnann et al., 2018; Kane, 2019).

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1.2 Problem Discussion

Although transport, and especially vehicles have a major impact on climate and awareness among car consumers has been increasing steadily (Karlsson, 2017) current market shares reveal that there is still a long tramp within the electric car market in order to have a positive influence on decreasing emissions and environmental pollution (Mamalis et al., 2013). Apart from the phenomenon that BEVs have failed to meet industries’ expectations (Steinhilber et al., 2013; Philip, 2013; Winton, 2019; Long et al., 2019) several researchers already pointed out that electric vehicles might not be as sustainable as consumers expect them to be (Hawkins et al., 2012; Racz et al., 2015).

In addition, there are several potential influence factors including unsatisfactory charging station infrastructure, insufficient recharging times and high market prices which hold customers from buying BEV’s (Schuitema et al., 2013; Nilsson & Nykvist, 2016; Bonges & Lusk, 2016; Liao et al., 2017; Munoz, 2019). Although BEV’s reduce emissions, greenhouse gases and lead automotive industry towards a more sustainable industry (Larson et al., 2014) by using renewable energy (Egbue & Long, 2012), it seems that consumers’ perceptions still remain unsatisfying which might cause major problems for carmakers as they have to decrease their average CO2-fleet emission due to EU-legislation down to 95g/km in 2021 (European Commission, 2019).

Nevertheless, factors influencing consumer’s adoption of BEVs in a negative way are commonly known among marketers (Schuitema et al., 2013), there has hardly been any research on influence factors on BEVs adoption among potential consumers accountable to generation Y. Moreover, the importance of generation Y will not only increase tremendously but also has a major impact on sustainability and environmental awareness among the next generations (Kuhlman & Farrington, 2010). In addition, existing literature hardly tried to explore the subjective, personal aspects behind the adoption which leaves marketeers back with a variety of questions about influence factors.

• Which factors are true barriers for EV adoption?

• How do these factors influence the adoption among consumers?

• Does adoption anxiety decrease with providing information or increasing experience?

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1.3 Purpose

As mentioned, previous research already evaluated a variety of factors influencing the adoption of BEVs among consumers. Nevertheless, existing literature and current understanding does not provide sufficient information to answer vital questions as mentioned above. Hence, the research team intends to take a look beyond the already evaluated factors and the perception of BEVs. This is contributed by the fact that previous literature evaluated perception as one of the core factors in order to adopt BEVs among consumers (Ziefle et al., 2014; She et al., 2017). In addition, using a semi-inductive grounded theory approach, the research will use the Technology Readiness Index (TRI) (Parasuraman, 2000) as a guiding framework for the coding and results chapter as well as the Technology Acceptance Model (TAM) for an in-depth analysis (Davis, 1989).

Taking previous research and existing literature into consideration, the purpose of this thesis is to explore influencing factors for consumer’s affecting BEV adoption and the perception of those factors among generation Y consumers within the European market.

1.4 Research Questions

In order to guide this research towards achieving the purpose the researchers decided to formulate two research questions (RQ):

RQ1: What are the main influence factors keeping generation Y consumers from BEVs adoption

within the European market?

Considering the fact that there has been hardly any research about a summary of all core factors affecting BEV adoption the first research question aims to explore which factors do indeed play an essential role among consumers. Based on existing literature RQ1 solely mirrors the factors themselves and contributes to RQ2 which aims to get more into detail and to explore perceptions affecting consumers’ intention to adopt BEVs.

RQ2: How are influencing factors perceived among generation Y consumers within the European

market?

Being built on the outcome of RQ1, RQ2 aims to mirror the perspective of the consumers and their perception towards BEVs. Moreover, the research team argues that it is not only important to explore core factors affecting BEV adoption but also to take a look behind consumer’s views in order to address challenges and possibilities for marketers and industry.

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1.5 Research Structure

The following thesis is based on a qualitative study with the goal of examining the perception of BEVs among generation Y consumers within the European market and to analyze if there are influence factors keeping consumers from BEVs adoption. In order to do so, chapter two mirrors the historical background of BEVs adoption within Europe and follows up with providing previous research, key findings and theories building a guiding foundation of this thesis. Chapter three deals with the methodology, discussing the researchers’ semi-inductive approach and the followed qualitative research design of the thesis. In addition, the decision using semi-structured interviews to gather data as well as sampling will be explained in detail. Chapter four mirrors the empirical findings based on the data gathered within the research. Chapter five subsequently analyzes the findings in order to answer the research questions and to contribute to the formulated purpose. In addition, following a semi-inductive approach of the research, the authors introduce a theoretical model linking researches’ findings to theoretical framework discussed in chapter two. Finally, chapter six provides a conclusion drawn by authors and provides implications, suggestions for further research as well as limitations with regards to the conducted study.

Introduction _BackgroundTheoretical Methodology _{& Method} Empirical _Results Empirical _Findings Conclusion & _Discussion

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2 Theoretical background

______________________________________________________________________ The purpose of this chapter is to provide theoretical background as a foundation for both, the understanding

in general but also for important links during empirical research and analysis. In addition, several key terms playing an important role within this thesis will be described in more detail in order to better understand the

structure and the content of this paper.

_____________________________________________________________________________________

2.1 The History of BEV Adoption in Europe

Although electric cars have been becoming frequently popular in recent years, the history of electric cars themselves goes back to the early 19th century when Robert Anderson invented the first electric vehicle in the 1830s (Royal Academy of Engineering (Great Britain), 2010). At this point it is worth to mention that traditional internal combustion engines (ICEs) were demonstrated nearly 50 years later when the German car manufacturer Benz presented his Benz Patent-Motorwagen Nummer 1 in 1886 (Høyer, 2008). Later on, beginning from 1880 to the early 1920 (Westbrook, 2001) electric cars have experienced fundamental technological developments and deployments which can be derived from the fact that even in contemporary times those cornerstones build the basis for the latest electric car technologies (Anderson & Anderson, 2005).

However, the core disadvantage of EVs in comparison to classical gasoline or diesel cars has always been their limited performance and driving range (Ehsani et al., 2018) which can still be seen as one of the main research topics within this field of interest (Rezvani et al., 2015; Yuan et al., 2018). In addition, the 1960s and 1970s forced a rethinking process within the society as several researchers and laboratories raised concerns about environmental issues which led to the fact that research put its focus on EVs again (Ehsani et al., 2018).

Nevertheless, several ecological disasters such as Hurricane Katrina (2005), or the tsunami in the Indian Sea region (2004) influenced policymakers to implement new market instruments in order to restrain carbon emissions (Orsato, 2009). On the other hand environmental awareness has been increasing steadily among the society and carmakers identified a new potential within the electric car market which led to the fact that the Frankfurt Motor Show 2009, one of the most influential and prestigious car shows every year can be seen as the renaissance of BEVs (Dijk et al., 2013). Almost all well-known car makers such as Audi, BMW, Mercedes Benz, Peugeot, Renault, Toyota, Volvo, Volkswagen and Tesla revealed concept cars with electric engine technology or new BEVs, already planned

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to go into production (Voelker, 2009). However, electric cars have been widely seen quite controversial in various fields of interest such as technical (Gao & Ehsani, 2002), environmental (Doucette & McCulloch, 2011) or in terms of exploiting resources (Massari & Ruberti, 2013). To conclude, it should be mentioned that there are several influence factors on electric cars such as 100% renewable energy to charge, long-term planning for battery recycling or also decreasing CO2-emissions during production but in fact industry deals with an upcoming technology which still needs to be discovered and offers a variety of new possibilities whereas for most ICE cars it seems that the horizon of technological development has just been reached.

2.2 The Role of Perception in Consumer Behavior

Regarding consumer behaviour, perception refers to “the process by which stimuli are selected, organized or interpreted” (Solomon et al., 2010, p.118). Kotler and Armstrong (2011) argue that that the way of processing marketing stimuli and deriving information from them guides the decision-making process. In consumer behavior two facets of perception play a vital role: the awareness of people regarding their environment considering the five senses which contributes to the importance of sensation as the process where perception begins (Foxall, 2015). Secondly, the process of how stimuli are processed depending on socio-psychological meanings are vital as perceptions differ among consumers based on their interpretation of social or physical stimuli (Foxall, 2015).

Blythe (2013) mentioned that in terms of building consumer knowledge for long time success, the understanding of perception is crucial as it influences attitudes towards products, technologies or brands. For marketers within the automotive industry it is therefore relevant to understand perceived stimuli among consumers (Solomon et al., 2010). Given this context marketers also need to evaluate how individual needs, experiences and beliefs impact the perception process (Solomon et al., 2010).

In addition, it can be summarized that current models of perception in consumer behavior related fields of interest refer to the perception of products in terms of:

• Consumers characteristics (Solomon & Stuart, 2002) • Product characteristics (Aaker, 1991)

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In terms of automotive industry research revealed that consumer’s adoption of BEVs rather depend on perception than on technological facts and attributes (Rezvani et al., 2015; Egbue & Long, 2012). In general, existing literature majorly focused on positive and negative perceptions based on behavioral frameworks such as the rational choice theory (He, Zhan & Hu, 2018). Moreover, previous research reveals that personality traits can be considered as significant factors of technology acceptance (Özbek et al., 2014).

For the given thesis the research team decided to additionally focus on the evaluation of perception among consumers on BEVs as social acceptance within the society is inherently subjective and based on consumer’s perception of them. In addition, this followed path is strengthened by previous researchers identifying perception as one of the core factors in order to adopt BEVs among consumers (Ziefle et al., 2014; She et al., 2017; Krause et al., 2013). Therefore, discovering consumer’s perception towards BEVs does not only contribute to answering the research questions but also helps to devote to have “a look behind” the influence factors on BEVs adoption. The assumption being made can be derived from existing literature which reveals that one of the most crucial determinants of intention towards adopting new technologies is the perceived value (Anckar et al., 2003; Shin, 2009).

2.3 Generation Y

In current research, generational theory is commonly derived from Mannheim (1970) and pursues to understand cohorts of people and to explore patterns across generation groups in process (Pendergast, 2009). Gardiner et al. (2014) mentioned that “In both academia and practice, grouping people on the basis of generational cohort membership has become a popular way to explain consumer’s past, present and future behavior” (p. 706).

In existing literature generation Y is widely accepted as all people who are born between 1982 and 2002. In addition, this generation is expected to be the next influential cohort with an exclusive bundle of needs, expectations and beliefs (Leask et al., 2013). Moreover, it is widely acknowledged that generation Y is being described as the most educated generation (Howe & Strauss, 2009). According to Giovannini et al. (2015) the generation’s large size and its increasing power are key indicators to view generation Y as a strategically important consumer segment. Shaped by influencing factors such as globalization, parenting and technology (Canavan, 2018) generation Y stands out with its openness and flexibility in terms of social issues and its diversity (Lipkin & Perrymore, 2009).

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Although generation Y has been widely described to be an influential and unique consumer group, researchers argue that they are poorly understood (Noble et al., 2009). In addition, Kozinets (2015) argued that there is an increasing critique regarding misuses of methods in order to understand consumer demands within this generation. Hence, brands must adapt their products and services to appeal to this generation with an enormous collective spending power (Tangsupwattana & Liu, 2017). Moreover, the importance of generation Y will not only become tremendously important but also has a major impact on sustainability and environmental awareness among the next generations (Kuhlman & Farrington, 2010). Although it has been evaluated that generation Y is majorly interested in leisure and lifestyle products, appealing to their emotions and feelings (Esmaeilpour, 2015) there has been hardly any research on intentions of BEV adoption throughout this cohort. Nevertheless, automakers and marketeers argue that it is crucial to understand intentions towards BEV adoption as generation Y is being expected to be the most important consumer group within the market (Paik et al., 2017).

2.4 Adoption of BEVs

The adoption of innovations has widely been explored in existing research. Roger (1983) emphasized on key factors such as compatibility, complexity and relative advantage as main characteristics for consumer decisions on product adoption and the time of adoption. Moreover, it has been stressed that consumers might not essentially see all new technological innovations as progressive or improving (Ram & Sheth, 1989). Furthermore, Cui et al. (2009) mentioned that consumers may tend to delay adoption as technologies usually tend to improve over time and products in later stages are much more simplified.

In terms of BEV adoption several authors conducted qualitative as well as quantitative researches. Due to the purpose of this study the adoption of BEV needs to be evaluated deeper by considering different perspectives from existing literature.

Within qualitative research there have been several studies focusing on the acceleration of BEVs adoption within Europe (Kester et al., 2018; Harrison & Thiel, 2017). Graham-Rowe et al. (2012) conducted a qualitative study where 20 participants were interviewed using semi-structured interviews after a seven-day period. Results identified several factors holding consumers back from BEVs adoption. In addition, a research by Noel et al. (2019) revealed that range anxiety still occurs to be one of the key influence factors for consumers being afraid of adopting BEVs. Using a mixed method approach with expert interviews, focus

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groups and surveys the researchers could gather data from more than 5.300 participants among Nordic countries which contributes to the fact that range anxiety might indeed play a major role in BEV adoption. In addition, a study based on content analysis and semi-structured interviews conducted by Morgadinho et al. (2015) stressed, that mass adoption of BEVs in Europe is still at an early stage due to its battery technology constraints and unsatisfactory pricing. Taking the marketing perspective into consideration a study conducted by Cherubini et al. (2015) examined critical success factors related to the electric car industry.

All in all, several authors used qualitative research approaches to evaluate consumer adoption of BEVs. Moreover, several key factors influencing the adoption have already been examined. Nevertheless, it is crucial to understand that there are still several open questions which contribute to the qualitative approach within this thesis. In order to get a better insight on the background of consumers adoption behavior and the perception of influence factor the research team will use TRI and TAM models as a guiding framework for coding and the analysis of the results obtained in the research.

2.5 Influence Factors on BEVs Adoption

Although already several studies examined benefits of BEVs in the European Union (Funk & Rabl, 1999; Lane & Potter, 2007; Finn et al., 2012; Harrison & Thiel, 2017) it is worth mentioning that research also investigates challenges and disadvantages of BEVs (Newton & Cantarello, 2014). Moreover, research on BEVs has been becoming rapidly important as one perspective of BEVs adoption figures is foremostly reliant on their perception among consumers (Schuitema et al., 2013). Hannan et al. (2017) outlined that factors such as high purchasing prices, lack of charging infrastructure, limited driving range and long charging times are holding customers back from considering BEVs as a promising mobility alternative. Egbue and Long (2012) evaluated that knowledge and perceptions of BEVs vary across demographic groups and outlined that the factor of sustainability plays a subordinate role whereas cost efficiency and performance are the key drivers of consumers’ intentions to choose BEVs. In comparison Peters and Dütschke (2014) conducted an online survey (N=969) in Germany where they compared four groups differing in their likelihood on purchasing a BEV based on socio-demographic characteristics. Key outcomes on their research based on Technological Acceptance Model (TAM) indicate that promotion should primarily focus on strengthening environmental advantages and financial incentives whereas performance indicators seemed to play a less important role among surveyed participants.

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Graham-Rowe et al. (2012) conducted a qualitative research based on grounded theory approach which showcased that contemporary BEVs are being seen as “work in progress” contributing to the fact that potential consumers might tend to wait for further progress within this industry whereas users indicated a tendency on using BEVs as a second car for short journeys.

In other researches various authors evaluated that the actual experience with BEVs in general shows a positive impact on consumers perceptions towards them (Schmalfuß et al., 2017) although scholars highlight a lack on further research on impacts of experiencing instrumental attributes such as charging time or driving range on BEVs perception (Franke et al., 2012). In addition, a frequently addressed potential influence factor on BEVs adoption might be derived from sustainability and ethical factors linked to the batteries of BEVs. Given this context it is worth to mention that due to the need of high-performance battery cells, materials such as cobalt or lithium need to be from high quality which contributes to higher prices (Faizal et al., 2019) compared to traditional ICE cars (Mohr et al., 2012). From an ethical perspective it has also been widely addressed that the disposal of used lithium-ion batteries still needs to be concretized (Mohr et al., 2012; Girardi et al., 2015) and causes emissions such as nitrogen oxide, carbon oxide or sulfur dioxide emitted during the production process (Peters et al., 2017; Ke et al., 2017). Moreover, battery manufacturing for BEV has been criticized constantly as two third of the world’s cobalt, the key mineral in the production process, are obtained by the Democratic Republic of Congo which has been accused of child labor in many cases (Hilson, 2008; Hayes & Perks, 2012). All in all, it is a matter of fact that research on BEVs has been becoming frequently popular and should be contemplated as “a new market rather than the evolution of a mature product” (Cherubini et al., 2014, p.2).

However, literature review revealed that there has hardly been any research on the leverage of technological acceptance and technological readiness on BEVs adoption among generation Y consumers within the BEV industry.

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Summarized from previous researches the following key influencing factors on BEV adoption have been identified:

• Driving range anxiety • Charging infrastructure • Purchasing costs • Ethical controversies • Driving experience

Seeing BEVs as “work in progress” (Graham-Rowe et al., 2012) it can hardly be assumed that all influence factors have been discovered yet. In addition, existing literature rather tested commonly known factors than moving a step forward and try to evaluate new directions and their origin. Hence, the research team assumes that qualitative research is crucially relevant at this stage. It offers the possibility to examine new factors and helps to have a look behind the perceptions towards them.

Within the transport research concepts and elements are generally abstracted from user’s perspectives by using inductive purposes (Mann & Abraham, 2006) in order to capture ‘real-life’ experiences and “reveal the complex psychological structures of understanding, explanation and decision-making” behind them (Graham-Rowe et al., 2012, p.142).

Clifton and Handy (2003) argue that qualitative methods can therefore establish promising and trendsetting concepts which might not be considered by quantitative deductive inquiries.

2.6 Marketing related theories

2.6.1 Technology acceptance model (TAM)

Technology acceptance model has been one of the most influential throughout all technology acceptance models that helped to guide a big part of researchers to understand the patterns of human decision-making process (Charness & Boot, 2016). The model itself shows five dimensions that influence the human decision-making process, the model starts with the external variables that help understand what surrounds the individual during the acceptance process. The beauty of the Technology acceptance model is its ability to be molded into the liking of the research, therefore allowing to create a more up to date and on point model simulation (Granić & Marangunić, 2019).

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Figure 2. Technology acceptance model (Davis, 1998)

As it can be observed in Figure 1 the model (Davis, 1989) goes beyond its predecessor and adds in on crucial variable that is the “External variables” that allows to follow up on the primary data and link it directly to the model by referring to the same occurrences in the research data extracted from outside sources (Legris et al., 2003). In general, the more positivistic the external variables are, the more those will positively affect the Perceived usefulness and Perceived Ease of Use the stronger will be the Attitude and the Behavioral Intention to use the new technology.

2.6.1.1 External Variables

As mentioned previously, the addition of this extra variable will help guide the research topic and help link the primary data to the theoretical and methodological part of the paper. External variables define the constructs, that in this case would be the building blocks to help answer the research question. In the case of BEVs the external variables would be: quality, battery capacity, price and societal integration. As mentioned by Hong et al. (2002) and Venkatesh (2000) these relationships are significant to the study while Davis (1989) states that these factors are already meditated in the care factor in TAM. For the sake of clear structure, the research team has decided that external factors will be applied to this qualitative study.

2.6.1.2 Perceived Usefulness

Perceived usefulness defines to what degree the new innovation/technology will help them perform better in their day to day life or just enhance their performance (Venkatesh, 2000). In the case of electric vehicles one of those arguments could be Low taxation, in the European market every country has a method that promotes and gives an incentive to purchase electric vehicles, be that for personal use or business. Deveza (2019) affirmed that by the new Austrian government tax law all fully electric vehicles are exempt from any kind of taxation for CO2 emissions 0€/year, as of October 1, 2020. Compared to the normal ICE where the taxation rate is (CO2 in g/km – 115) /5 and a fixed sum of 350€ is to be paid

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yearly regardless of the actual use of the ICE cars. With tax laws like this all-over European countries it adds value and positive perks for the perceived usefulness, where the individual can see the added value and meditate whether the BEV will be a useful purchase and if it will somehow enhance their performance.

2.6.1.3 Perceived Ease of Use

Perceived ease of use explains to what degree the new technology would be free of effort or to what level of complicity is the new technology at. Judging by the work of Davis (1989) it could be said that some technology might lead to a more inclined usage and liking over the other, even if all other factors are equal. It goes without saying that there is a link between perceived ease of use and perceived usefulness, as mentioned in the work of Erasmus et al. (2015) where it is reported that if a technology becomes perceived as easy to use it will most likely be perceived as useful by the individual therefore establishing a attitudinal link between the two, that can be as positive as it can be negative. Since fully electric vehicles have been in constant development, they tend to have the most advanced User Interface compared to the usual cars, as more electric power allows to create some incredible combinations (Wolf et al., 2015).

2.6.2 Technology Readiness Index (TRI)

The Technology Readiness Index mirrors a 36-item measurement scale that assesses four dimensions of technology belief that impact an individual's up to date level of technological readiness regarding a certain new technology (Meng et al., 2009).

The four dimensions that assess the level are described by Parasuraman (2000) stated that two of the dimensions are contributors and two are inhibitors.

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2.6.2.1 Contributors

Optimism —the degree to which individuals believe that technology can benefit their lives

and give them more control over a certain action that would in other cases take too much time to complete, therefore creating a certain feeling of possible success, flexibility and best of all efficiency (Parasuraman, 2000).

Innovativeness —a natural desire to experiment with new technologies to understand their

placement in their own life, would it be more useful for private use or business use, or maybe both. Innovativeness also speaks about the ability to rank the new technology on par with same old ones, or the ones it branched off from to grasp the full potential impact (Parasuraman, 2000).

2.6.2.2 Inhibitors

Discomfort —a feeling that enforces the inner thoughts about lacking both control over

technology and the confidence in making the technology work in the day to day framework. This dimension is one of the most impactful ones as the discomfort feeling is not so easily overcome and might need a longer period of time to adjust in case the initial interception with the technology did not reach common ground with the individual (Parasuraman, 2000).

Insecurity — This dimension is the one that speaks differently to each one. To some this

may be about the price and quality and of others it could be a doubt about the neediness of the technology, would it be an investment or a bust in the long run. To say it in different terms: a certain need for assurance that the technology-based product or service will operate reliably and accurately or accommodate for a certain period of time (Parasuraman, 2000).

2.7 TAM and TRI in previous research

The TAM and TRI models were used in a wide variety of research studies on many types of new technologies, or their impact on some specific groups of people, as for example in Self driving cars, car sharing, car navigation systems and one of the biggest applications of TAM on elderly people (Walczuch et al., 2007; Godoe & Johansen, 2012; Van Biljon & Renaud, 2008; Geldmacher et al., 2019; Koul & Eydgahi, 2018; Park & Kim, 2014). Consequently, the TAM and TRI are a valuable means to get insights and understanding of the behavior and intentions associated with purchasing and using fully electric cars. Thus, the TRI focuses on the dimensions of optimism, innovativeness, discomfort and insecurity that directly could be used as a perfect replacement for the external variables. This specific model stands as one

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of the classic theories for measuring the technological readiness of an individual, not only on the factors of influence for the behavior, but also on the several ways of influencing consumers (Parasuraman & Colby, 2015). In this case, the TRI associates the main aspects strived after in this thesis: behavior, attitudes, and influence.

In general, the scope of TRI and TAM within this research is to help contributing to the research questions and the purpose of this paper. Therefore, the main point is to detect the influencing factors and observe how the interviewees’ answers could lead to better understanding and classification of those influencing factors, by using TRI and TAM to help create a concise and thorough analysis culminating with an eye opening result that would benefit the ecological and automotive industry in the future. Generation Y is the next generation that is supposed to take on the leadership role in the next decade and try and answer a decades long energy crisis as well and ecological catastrophe left by past generations that were limited by the technology of their time.

2.8 The purpose of theoretical background

The purpose of chapter 2 is to show the base of reference for the research team. Based on the given theoretical background the research team plans not only explore influencing factors on BEV adoption but also to get more into detail and find as well as analyze consumer’s perception based on the findings gathered during the conducted research. Although BEV research has been becoming frequently important over the past few years, automotive industry is still playing a subordinate role in common marketing research. Therefore, a short historical background aims to summarize key inventions and innovations in order to ensure that readers have the theoretical background needed to follow this thesis. As this research is based on Generation Y consumers, the research team also discerned the importance of introducing the theoretical background behind one of the most important consumer groups in the upcoming future.

The aim is to understand the importance of these influence factors and sort them by their influence in a consumer’s purchasing process, that devolves from these positive and negative perceptions that are formed in the mind of the consumer. Therefore, by executing enough research and combining with the data found in the conducted interviews the research team will be able or try to answer the posed two research questions which the paper revolves around.

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3 Methodology & Method

______________________________________________________________________ The purpose of this chapter is to present the methodology being chosen to attain answers for purpose and research questions. At the beginning, methodology and research approach are covered. Secondly, the chapter covers data collection, sampling and interview design. In addition, the data analysis process is being dealt with

followed by ethical considerations and quality of the research which aim to illustrate and mirror the process of ensuring trustworthiness and credibility to the gathered results.

______________________________________________________________________

3.1 Methodology

According to Saunders et al. (2009) there are two research designs that researchers should choose from, either quantitative or qualitative design. As mentioned before, the qualitative study focuses on how individuals perceive the world that surrounds them. Thus, this study will focus on attitudinal, behavioral and intentional aspects of generation Y and their adoption of BEVs.

Research design is a plan of how the research team will answer their research questions, therefore by forming semi-structured interviews and transcribing the data, measurement tools would be inefficient thus proving that qualitative methods would be more relevant (Patton, 1990). Qualitative methods rely much on interpreting the data by the researchers in order to answer their research questions, also associated with interpretive philosophy. In its nature it is interpretive as the research team needs to make sense of the subjective and social constructive meanings expressed about the phenomenon (Saunders et al., 2016), in this case technological adoption of generation Y.

This paper is an exploratory study which is usually used when a problem that is not clearly defined needs to be investigated (Saunders et al., 2016). Moreover, the research team aims to explore adoption issues for BEVs within the European market, where others have tried to dig into it as well to try and determine the causes for their slow adoption process. The exploratory study starts with a general idea backed up by primary data as a medium to identify the issues, thus these issues can be a possible focus for further research. The main aspect for exploratory research is that the research team should be willing and eager to change their direction in order to pursue new insight or new data (Saunders et al., 2016).

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3.1.1 Research Approach

Generally, when conducting a research, the research team is faced with a choice whether to adopt an inductive approach or a deductive approach (Grinnell & Unrau, 2005). The chosen approach helps overcome research design constraints.

The inductive approach generally starts with outsourcing the phenomenon, meaning that it moves upwards from the primary data in this particular case the semi-structured interviews that will serve as basis, most commonly used in qualitative research to observe the patterns in human behavior. Afterwards by gathering the data and analyzing it the next step is to propose a tentative hypothesis and answer it with the research gathered (Bryman & Bell, 2011). Thus, lastly arriving at creating/proposing a new theory.

As for this study the research team has decided to adopt a semi-inductive approach to the paper. The decision was taken towards this direction as the inductive approach suits the narrative of this study, but the research team would like to borrow a part of framework to potentially try to offer a new finding. In their book for planning a project, Saunders et al. (2012) mentioned that such an approach is tangible but if done poorly would result in an incomprehensible structure. The “semi” part of this inductive approach is placed in order to highlight the potential advance of not just testing theories, which in this case are the TRI and TAM models, but to try and come up with a new theory. The framework will be built up and strengthened by the emerging data gathered from the conducted interviews in strong conjunction with theoretical background from previous research. The semi part was added to remind the reader that although the inductive is generally focused on exploring a new phenomenon, the paper will use the framework of the models to create an interview to test those influence factors before submerging into the fully inductive part of the research approach.

3.2 Method

The following sub-chapters will give an insight about data collection techniques, sampling, interview design, data analysis, ethical consideration and the quality of the research which consequently contributes to the needed data for answering the formulated research question. As Bryman and Bell (2011) outlined the method of collecting data and analyzing it is primarily differentiated between qualitative and quantitative by either emphasizing the quantification or interpretation of collected words and analysis of the gathered data. In addition, Saunders et al. (2009) argue that qualitative studies mainly generate non-numerical data. This is further

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underpinned by the fact that qualitative research is often assumed to be theory generating whereas quantitative research focuses on theory testing (Bryman, 2001).

Although the purpose of the given thesis does not emphasize on testing existing theory but examining and understanding problems the researchers decided to focus on a qualitative research design (Bryman & Bell, 2011). In order to address influence factors for BEVs adoption within the European market the researchers believe that in-depth insights are required (Clifton & Handy, 2003) which mainly puts the focus on interpreting data. Given this fact it can be seen as an additional indication for a qualitative method.

3.2.1 Data Collection

In order to answer the research questions, researchers will use primary as well as secondary data. For this thesis, primary data are gathered due to the purpose of evaluating influence factors on the adoption of BEVs within the European market. Secondary data are used to provide background to the research as well as to support the theoretical and methodological chapters of the given thesis. In many cases a combination of primary and secondary data is used in order to answer the formulated research question (Saunders et al., 2009).

For the given thesis the research team decided to focus on primary data. Primary data could be described as data collected from the source in order to commence a research study, in general, it is raw and unstructured and needs to be processed in order to create a good understanding of the flow of the research paper (Saunders et al., 2009). The method of data collection chosen was semi-structured interviews, as this allowed the research team to have a controlled environment and ability to supervise and direct the flow of the interview. Moreover, the ability to be face to face with the interviewee allows having a more private conversation that would possibly result in a better context of answers (Bradley, 2010). When creating the interview the research team decided that it would be better if an interview plan is established beforehand to control the flow of the interview, but for the sake of an interactive interview, it was decided to leave it to be an unstructured interview, as this would facilitate better and more comprised answers from the interviewee. Moreover, it allows the researchers to formulate open ended questions as well as closed ended questions. Additionally, as it was mentioned before, this is exploratory research, therefore having a non-standardized method of performing the interviews is a great opportunity to shift the interview towards the liking to the interviewee and create a more personalized feeling to the interview (Saunders et al., 2012). Since this study engages in the theme of BEVs it is

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mandatory that the answers are as concrete as possible to better depict the finding in the analysis part.

3.2.2 Sampling

According to Morse and Niehaus (2009), sample methods can maximize the efficiency and validity of a research. According to Patton (2002) qualitative methods primarily focus on achieving a deep understanding. For qualitative research, Gentles et al. (2015, p. 1775) defined sampling as “the selection of specific data sources from which data are collected to address the research objectives”.

Although several researchers already established that it is hardly possible to pre-define a sample size within qualitative research (Glaser & Strauss, 1967; Marshall, 1996). According to Marshall (1996), in order to adequately answer the given research question, a sufficient sample size in qualitative research is vital.

With regards to Saunders et al. (2012), sample definition requires researchers to choose between probability and probability sampling. The researchers decided to use non-probability sampling, purposive sampling in particular (Saunders et al., 2009), as the thesis is focused on a qualitative study which does not require generalized results (Firestone, 1993). Due to time constraint, researchers decided to select the sample within their nearby environment at Jönköping University which subsequently contributes to the choice of purposive sampling - all participants within the sample have the same occupation (being students) - as an appropriate sampling method (Saunders et al., 2009; Saunders et al., 2016). Moreover, the choice of purposive sampling was specified by applying homogenous sampling method meaning that a homogenous group of participants with same education or occupation for example, allows researchers to get more detailed information (Saunders et al., 2016). Given this context, it needs to be specified that the researchers focused on generation Y which is already accounted to be the largest generation within several countries (Lachman & Brett, 2011) but has been hardly taken into consideration in mobilities literature until now. Nevertheless, Delbosc and Currie (2013) argue, that the way of practicing mobility among generation Y will not only become tremendously important but also has a major impact on sustainability and environmental awareness among the next generations (Kuhlman & Farrington, 2010). Moreover, it has been evaluated that “traditional” BEVs consumers are predominantly male, holding a tertiary education degree, working in full-time employment

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and are below middle age (30-45). However, key outcomes of the study reveal that females with higher incomes show intention to adopt BEVs as well (Sovacool et al., 2018).

Based on the given context the researchers decided to set the following criteria for participants involved within the sample:

• The participant is between 20-40 years old

• The participant is studying in a full-time master program at Jönköping University • The participant is within his/her last year of studies

• The participant is citizen of a European country

• The participant has at least two years of driving experience • The participant intends to buy a car within the next five years • The participant is considered to be “environmentally aware”

As inclusion and exclusion criteria for defining the sample are foremostly specific within this thesis, the sample can be defined as homogenous which allows a rather small sample for the conducted research (Robinson, 2014). In order to answer the research question of the given thesis, the researchers decided to pre-define an estimated sample size of 30 interviews increasing credibility and in-depth insights compared to literature evaluating an estimated number of 12 participants (Saunders et al., 2012). This has been proven to be most sufficient within homogenous groups in qualitative research but obtaining more data does positively contribute to a larger amount of data and better insights within the analysis (Saunders et al., 2012; Marshall et al., 2013).

3.2.3 Interview Design

The main focus of these interviews is to try and detect the opinions and intentions of people that have been asked what their opinion is about BEVs and the industry in general. Based on the information from Peterson (2000) who wrote a book on constructing interviews, following its step by step guide, its help was unparalleled for the research team to build a structured interview that would also allow deviations, to gain all the possible insights needed to collect the primary data. Since the TAM and TRI model are made to detect and justify the level of readiness for the adoption of the new technology it does not hold an anchor point in gender and age, but this would be out of scope of the given research. Therefore, for the most natural occurrence of the research it was decided that the sample will be picked at random from the population, in order to receive the most accurate data possible, as close as possible to reflect reality.

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The research paper aims to study about BEVs and its technological acceptance in the European market by generation Y, therefore the questions were prepared in regard to the newest trends, new electric vehicles and their supporting companies. The questions were formulated based on the purpose of the proposed research linked along with the accompanying frame of reference to get an answer for the main research question of this research paper.

3.2.4 Interview Pilot Test

When conducting large scale interviews for a research topic, the most important part is the interview that the research team conducts in order to gain primary data, therefore the quality of the data is crucial and has to be collected thoughtfully (Turner, 2010). Thus, for the better data collection a pilot interview is created, which should help the research team to revise the interview for potential issues, unrelated questions and other weaknesses that would diminish the quality of the data (Maxwell, 2013). Moreover, by performing the pilot interview, the interviewee could point out some aspects of the questions that perhaps were unnecessary, ethically inappropriate, ambiguous or too complex (Chenail, 2011). Subsequently, it was decided by the research team to test the initial interview with some volunteers from a business background and with a general knowledge of the industry in order to receive the best form of feedback.

3.3 Data Analysis

Qualitative data collection methods, particularly semi-structured interviews with a mix of closed and flexible open-ended questions, commonly generate large amounts of data which makes it crucial to choose an appropriate and effective data analysis method to handle and make sense of the textual data (Saunders et al., 2016). As recommended by Saunders et al. (2016) the researchers developed a conceptual framework (see chapter 2.5) in order to guide the flow of the present thesis towards the answers related to the given research questions. Taking the structure derived from the theoretical framework chapter into consideration, the semi-structured approach within this thesis guided the researchers towards the factors playing a vital role to the contribution towards the purpose of the study. For this reason, the authors decided to utilize content analysis which has been proven to be efficient for identifying and analyzing specific themes within the obtained data (Bengtsson, 2016). Moreover, Malhotra and Birks (2007) argue that content analysis classifies textual content into categories through application of set rules which reduces potential effects of subjective interpretation.

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Using a semi-inductive, exploratory approach, the researchers emerged the theory using data collection, analysis and the interpretation of the data taking previous frameworks within the topic of interest as a tool of guidance. The situation with COVID-19 changed the interview framework in a way that word-by-word transcription of the recordings as well as additional notes played a central role within this research (Malhotra & Birks, 2007). In the transcript, authors have been indicated as IAA (interviewer Alexandru Armasu) and IMW (interviewer

Martin Winkler), whereas participants were indicated using a number and the gender (e.g. participant three, male: P03M or participant seven, female: P07F).

3.4 Content Analysis

As mentioned before, the researcher’s intention using content analysis for this thesis primarily focused on the data reduction. In current research, authors often describe how analysis has been conducted in reports (Tuckett, 2005) but yet do not state clearly what they intend to do, why they are using it and how they are using it by a distinct description of their analysis methods (Braun & Clarke, 2006). According to Bloor and Wood (2006) the purpose of content analysis is to describe the conducted content by scrutinizing effects and sayings within conversations. In research, content analysis is widely known as “a research method that provides a systematic and objective means to make valid inferences from verbal, visual, or written data in order to describe and quantify specific phenomena” (Downe‐Wamboldt, 1992, p.314). Given this context it needs to be stated that content analysis can be used for both, qualitative as well as quantitative research which can be derived from Berelson (1952) who initially defined content analysis as “a research technique for the objective, systematic and quantitative description of the manifest content of communication” (p. 18). In this context content analysis is unique as it has both, a qualitative (Downe‐Wamboldt, 1992) and a quantitative (Krippendorff, 2018) methodology and can be used inductively or deductively (Bengtsson, 2016).

As this thesis follows a semi-inductive, qualitative approach, the given analysis method seeks to draw interpretation of the results based on words and themes conducted from the obtained data (Bengtsson, 2016). Given the qualitative context, the researchers intend to use manifest content analysis which focusses on the researchers’ description of what participants actually say to describe the visible and obvious within the data (Downe‐Wamboldt, 1992). On the contrary, latent content analysis extends the research to an interpretive level where researchers seek to find the meaning behind the data (Catanzaro, 1988). As the main purpose of data analysis is to summarize, organize and evoke meaning from obtained data and to

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subsequently draw conclusions (Polit & Beck, 2006) the researchers decided to use a table within the analysis. The given table (see Table 1.) should help to scan transcripts for relevant information and to summarize them in order to display relevant and key findings for each interview.

Table 1.

Content analysis example

Interview Page Line Paraphrase Insight (concluded) Category (factor)

Related theory

P03M 2 5-6 I think that the driving range of BEVs does have a negative impact on my vacation plans.

Driving range is perceived as an insufficient influence factor Driving range anxiety Hannan et al., 2017

The combination of the technique’s utilization and summary of the given data ensured a thorough and efficient analysis of the qualitative textual data (Malhotra & Birks, 2007) for each participant. Moreover, it contributed to the fact that data could be “categorized in order to reduce them to a relatively small number of content categories for subsequent quantitative analysis” (Saunders et al., 2016, p. 609). In essence, responses were reproduced using paraphrasing and subsequently summarized (Insight (concluded)). Additionally, summaries were categorized referring to several influence factors derived from the theoretical framework (related theory). Following a semi-inductive approach, the collection and analysis of gathered data was the key intention whereas links to theoretical aspects helped to explain, support or strengthen the findings. Moreover, the theoretical perspective supported the possibility of alternative interpretations throughout the conducted data.

3.5 Ethical considerations

Ethical standards are a crucial part of every research process, especially when it comes to gathering primary data via the method that was picked by the research team. Meditating on the fact that the research team has inquired to do In-depth interviews, one must raise some concerns when it comes to credibility and quality of the gathered data (Orb et al., 2001). Therefore, to avoid this issue, some aspects were to emplace for the research team to follow:

• Ensuring that harm will not fall upon the participants • Participants’ dignity will not be compromised

• Participants have given their consent prior to the interview • Participants will be anonymized

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• Confidentiality of the research data will be ensured

Prior to the start of the interview phase, the nature of the research, the research question and the aim of the research will be clearly stated to all participants in order to avoid any deception from the team’s part.

3.6 Quality of the research

When it comes to research, one challenge that the research team is confronted with, is research quality as in what is the worth of the research if it was done sloppy and it generally does not make sense to the aim to the paper (Bryman & Bell, 2015). The importance of a thoroughly planned research design is assured in order to maintain credibility and has been pointed out by other researchers such as Bryman and Bell (2015) where emphasis was put on four factors: credibility, transferability, dependability and confirmability. Unlike a quantitative study the qualitative study is not dependent on numeric factors from SPSS (Courtney, 2013) that would otherwise prove or disprove a certain assumption, therefore stating the four factors ensures trustworthiness of the paper.

3.6.1 Credibility

Ensuring credibility in a research paper is an important part when discussing trustworthiness. Bryman and Bell (2015) argued that increasing credibility is heavily reliant on solely focusing on observation and data validation whereas researchers must also ensure that authors only mirror data which has been gathered during the research. Thus, data shall not be omitted or trumped up. Secondly, assembling a relevant sample group of decent size from the total population helps to increase credibility. Therefore, by choosing to have semi-structured interviews with 16 students would suffice to generate credibility (Merriam, 1988) of the research and earn the trust of the reader, that the data in front of him or her is credible and not some random answers to impress with numbers of interviews done.

3.6.2 Transferability

Transferability is the capability of a research to be used and applied in real life at a company or organization, but mostly build the foundation for further research in this area. Slevin and Sines (1999) mentioned that the research team must ensure at all times that the value of the research can be passed on to further deepen the contribution made to future generations that will base their research on these findings and subsequently contribute to the benefit of humankind. To conclude, the transferability of this study and its findings will be made sure by providing a clear frame of reference, complete set of interviews and generally applicable models.

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3.6.3 Dependability

Dependability refers to a certain type of replicability of the paper whereby the question is if by constantly replicating the inquiry the same results would be yielded repeatedly (Moon et al., 2016). Taking into consideration that this is an exploratory research it is required by mutual respect to make sure that the researchers would document research design and implementation, including the methods as well as the details of data collection. Thus, by analyzing the report and following the guideline from chapter 3 it would be possible to replicate the study if needed and test the results.

3.6.4 Confirmability

Confirmability is the last of the factors that raises the question about the potential biases, motivations, interests and perspectives of the research team (Moon et al., 2016). Therefore, the research team will demonstrate a distinct link between the results and the conclusion with a clear structure that can be followed and replicated. By providing a detailed methodological description, the researchers will be able to provide proof to the reader that confirmability is indeed present by providing the clear theoretical background, methodology and models used to help the reader accepting the research.

3.6.5 The influence of COVID-19 during the research process

Due to the COVID-19 crisis throughout Europe the research team had to switch from personal face to face interviews to interviews conducted using applications such as Facetime, Messenger and WhatsApp. Furthermore, it was necessitated to decrease the number of participants to 16, as less people were willing to participate after the global panic forced everyone to resort to social distancing and self-isolation. Nevertheless, the decreased sample is still located above the suggested number of twelve participants for interviews, maintaining the main requirements of the sample that the research team was looking for and enriching data within this qualitative study (Saunders et al., 2012).

Therefore, the research team has had the need to shift to a completely new interview design. Based on the findings of Peterson (2000), the main parts of the interviews were kept but got transformed into a one-on-one type of interview using channels mentioned above. Additionally, because of the fairly poor internet connections the recordings of the interviews were stopped as the audio file was not clear and subsequently not in good quality when

The need for change : Influencing factors on battery electric vehicles (BEVs) adoption among generation Y within the European market.