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Motives for Participating in the Peer-to-Peer Car Sharing Economy

Master thesis MSc Business Administration – Marketing track Amsterdam Business School – University of Amsterdam

Name: Luc Burggraaff Student number: 11424176 Date: 22-06-2018 (final version) Word Count: 18529

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Statement of Originality

This document is written by Luc Burggraaff who declares to take full responsibility for the contents of this document.

I declare that the text and work presented in this document is original and that no sources other than those mentioned in the text and its references have been used in creating it.

The Faculty of Economics and Business is responsible solely for the supervision of completion of the work, not for the contents.

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Contents

Statement of Originality ... 1 Contents ... 2 List of Tables ... 3 List of Figures ... 3 Abstract ... 4 1. Introduction ... 5 2. Literature review ... 8 2.1 Sharing economy ... 8

2.1.1 Different types of sharing ... 10

2.1.2 Car sharing ... 11

2.1.3 Motivators to participation ... 13

2.2 Relational Model Theory ... 14

2.3 Platform Positioning ... 18

2.4 Sustainability ... 19

2.5 Enjoyment ... 20

2.6 Trust ... 20

2.7 Conceptual framework and hypotheses ... 21

3. Methodology ... 23

3.1 Car sharing platform SnappCar ... 23

3.2 Research design ... 24

3.3 Survey Questionnaire ... 24

3.4 Measure Development ... 25

3.4.1 Perceived relational models ... 25

3.4.2 Perceived sustainability ... 25 3.4.3 Enjoyment ... 26 3.4.4 Trust ... 26 3.4.5 Intention to participate ... 26 3.4.6 Control variables ... 26 3.5 Pre-test ... 27 3.6 Applied manipulations ... 28 3.7 Results pre-tests ... 29 3.8 Exploratory study ... 31

3.9 Modifications after exploratory study ... 33

4. Data collection and analysis ... 34

4.1 Data Collection ... 34 4.2 Data analysis ... 34 5. Results ... 36 5.1 Descriptive statistics ... 36 5.2 Distribution ... 36 5.3 Manipulation check ... 37 5.4 Correlations ... 38

5.5 Correlations for Millennials ... 40

5.6 Hypotheses testing ... 41

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5.6.2 Testing of Hypothesis 3 ... 44

5.6.3 Testing of Hypothesis 4 ... 44

6. Discussion ... 47

6.1 Summary of the results ... 47

6.2 Discussion of results ... 47 6.2.1 Direct relationship ... 48 6.2.2 Mediation effects ... 49 6.2.3 Sustainability ... 50 6.3 Theoretical implications ... 51 6.4 Managerial implications ... 53

6.5 Limitations and future research suggestions ... 54

7. Conclusion ... 56

References ... 57

Appendix 1 – Vignettes ... 61

Appendix 2 - Main questionnaire ... 65

Appendix 3 – Measures ... 70

Appendix 4 - Survey pre-test ... 72

Appendix 5 - Skewness and Kurtosis ... 75

List of Tables

Table 1. Overview of hypotheses ... 22

Table 2. Overview of the vignettes ... 24

Table 3. Pearson Correlations between variables of the pre-test ... 30

Table 4. Pearson Correlations between variables of the pre-test without sustainability ... 30

Table 5. Means, Standard Deviations, Correlations of the exploratory study ... 31

Table 6. Regression Model of the exploratory study ... 31

Table 7. Overview of hypotheses after exploratory study ... 33

Table 8. Distribution of respondents across our vignettes ... 35

Table 9. Pearson Correlations for manipulation check ... 38

Table 10. Means, Standard Deviations and Pearson Correlations - Overall ... 40

Table 11. Means, Standard Deviations and Pearson Correlations - Millennials ... 41

Table 12. Coefficients and p-value of direct, total and indirect effect - Overall ... 43

Table 13. Coefficients and p-value of direct, total and indirect effect - Millennials ... 43

Table 14. Coefficients - Overall ... 45

Table 15. Coefficients - Millennials ... 46

Table 16. Overview of hypotheses ... 46

List of Figures

Figure 1. Summary of frameworks ... 17

Figure 2. Conceptual framework ... 22

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Abstract

This research focusses on car sharing as one of the most recognized applications of the sharing economy. Current car sharing platforms seem to have difficulty convincing car owners to share out their car. In order to expand several positive benefits of the car sharing economy to a larger mass of consumers, this research addresses car owners’ motivating factors that drives the participation. Globally, business-to-consumer car sharing platforms most often use financial benefits to convince car owners to participate in the car sharing economy. However, academic research suggests that sociability is a much larger driver of behavioural intentions than money within peer-to-peer sharing. Given the fact that current marketing approaches for car owner acquisitions are not making enough headway, this study examines whether a marketing approach that appeals to the social and environmental benefits of sharing would be more effective for growth. We building on the Relational Model Theory, whereby we separate social and economic exchange relationships as a way of positioning. This research argues that the positioning of a car sharing platform has an effect on the intention to participate. Specifically, we predict that a social exchange positioning has a more positive effect on the intention to participate. Moreover, we expect that enjoyment and trust have a mediating effect on this intention. An online vignette study (N=201) was conducted in collaboration with the Dutch car sharing platform, SnappCar. The results suggest that platform positioning based on social exchange has no significant effect on the intention to participate for our total sample. But we found evidence that social exchange has positive effect on the intention to participate for Millennials. The literature confirmed those findings and indicate that Millennials are in particular more open to access-based consumption because they are less materialistic and have more concern for others.

Keywords: Sharing economy, Car sharing, Social exchange, Millennials, Relational Model Theory, Enjoyment, Trust, Intention to participate, Platform Positioning, Motivations

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1. Introduction

The sharing economy is on the rise worldwide and has offered consumers numerous alternatives to product ownership. Many products, such as tools, houses and cars are now being shared via online networks (Habibi, Laroche, & Kim, 2016; Lamberton & Rose, 2012). Bardhi and Eckhardt define the sharing economy as “access-based consumption” transactions that can be

market mediated but where no transfer of ownership takes place” (Bardhi & Eckhardt, 2012 p

881). With access-based consumption we mean that consumers have temporary access to

products or services against a fee, but without the change of ownership. Millennials, people born between the early 1980s and the early 2000s, are in particular more open to access-based

consumption because they are less materialistic and have more concern for others (Bardhi & Eckhardt, 2012; Hwang & Griffiths, 2017). The current literature shows that the upcoming generation, Generation Z the follow-ups of the Millennials, share this mind-set as well (Hwang & Griffiths, 2017; KiM, 2015).

This research focusses on car sharing as one of the most recognized applications of the sharing economy (Novikova, 2017). More than 7 million users worldwide are part of the car sharing community and have used car sharing multiple times. Several studies suggest that this number will be above the 20 million users worldwide in 2025 (Telegraph, 2017). One of the positive outcomes of the sharing economy are the environmental benefits (Frenken & Schor, 2017; Hwang & Griffiths, 2017). Different studies found evidence that car sharing reduce CO2-equivalent emissions (Skjelvik, Erlandsen, & Haavardsholm , 2017). In addition to the

environmental benefits, social and financial benefits have an important position within the

sharing economy as well (Botsman & Rogers, 2010; Frenken & Schor, 2017; Hwang & Griffiths, 2017). Consumers’ attitudes towards sharing are mainly positive and the willingness to share exists, but the eventual participation is staying behind. Hamari, Sjöklint, & Ukkonen indicates

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this as an attitude behaviour gap (Hamari et al. 2015). Current car sharing platforms seem to have difficulty convincing car owners to share out their car. In order to expand the positive benefits of the car sharing economy to a larger mass of consumers, online sharing platforms should require more knowledge about consumers’ motivating factors (Wilhelms, Henkel, & Falk, 2017). The aim of this thesis is to put the car sharing economy into perspective by providing a conceptual framework that allows us to give insight and more knowledge about motivating factors that are related for car owners to participate within the peer-to-peer car sharing economy.

Other studies related to sharing have been mainly focusing on identifying users' consumption motives in business-to-consumer contexts. It is often implicitly assumed that financial gains represent the greatest driver of willingness to participate among practitioners (Bardhi & Eckhardt, 2012; Bucher, Fieseler, & Lutz, 2016; Milanova & Maas, 2017). Globally, car sharing platforms most often use financial benefits to convince car owners to participate in the car sharing economy. For example, Getaround, an American car sharing company, describes its services on its website thusly: “Do you have a car? Share on Getaround. Make up to

$10,000/year” (Getaround, 2018). Another American car sharing company, Turo, states: “The car that pays for itself. Make a dent in your monthly car payments” (Turo, 2018). And finally the Dutch car sharing company SnappCar asserts: “Reimburse your car expenses, share your car easily and safely via SnappCar and quickly earn € 1000 per year” (SnappCar, 2018). All of those sales taglines focus on consumers’ financial benefits. However, academic research suggests that sociability is a much larger driver of behavioural intentions when it comes to peer-to-peer car sharing (Bucher et al. 2016). There is a great deal of confusing about the use of the concept of sharing between business-to-consumer and peer-to-peer, this may explain why various studies have found different outcomes. This study expected that peer-to-peer car sharing is not dominant being driven by financial motivations, as we expected that sociality motives matters more. Given

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the fact that current marketing approaches for car owner acquisitions are not making enough headway, this study examines whether a marketing approach that appeals to the social and environmental benefits of sharing would be more effective for growth. This study also attempts to uncover those motivating factors of car owners. The research question is; “How can social and environmental aspects of cars sharing platforms result in a higher intention for car owners to participate?”

Furthermore, we suggest that enjoyment and trust are also important factors to participate for car owners. Different studies have shown significant positive effects of enjoyment on

satisfaction and intention to participate in the peer-to-peer sharing economy (Fung So, Min, & Oh, 2018; Tussyadiah, 2016; Van der Heijden, 2004). Besides enjoyment, trust plays also an important role in consumer behaviour, as economic transactions involve risk and trust. Car owners should providing strangers access to their cars and having the risk of misbehaviour which has an effect on their intention to participate (Hartl, Hofmann, & Kirchler, 2016).We expect that if car sharing platforms can create an enjoyable and safe feeling around their platform, results in a positive effect on the intention to participate. It is important to know these motivators and effects for marketers, because this information can benefit the position of the car sharing platforms and improve the communication of relevant benefits for car owners. Also, it is important to continue to appeal to potential new car owners who take part in the sharing economy, as growth can only be realized if people also make their cars available.

This research consists of six parts. The following chapter consists of the existing theory regarding sharing, the car sharing economy and the hypotheses and conceptual model. Chapter 3 describes the methodology this research. Chapter 4 presents the data collection and analyse. Chapter 5 discusses the results and will be followed through Chapter 6 where we discuss our findings, implications, limitations and suggestions for future research. The final chapter, Chapter 7, provides our final conclusion based upon the research outcomes.

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2. Literature review

The literature review discusses relevant theory of the sharing economy and mainly focus on the car sharing economy. Finally, we will provide the hypotheses and conceptual model of this research.

2.1 Sharing economy

The sharing economy is on the rise worldwide. For consumers, it is becoming more common to rent or let their tools, houses and cars peer-to-peer (P2P) via online networks (Habibi et al. 2016; Lamberton & Rose, 2012). For example, 19% of the total adult population of the United States has engaged in a sharing economy transaction (PricewaterhouseCoopers, 2015). This upcoming way of consumption, the sharing economy, has disruptive effects for many traditional industries such as the hotel and transportation sectors, and it has created a new form of competition. The growth in the number of sharing economy platforms is enormous and will continue, especially through the rise of technology (Habibi et al. 2016).

One of the effects of the sharing economy is that consumers become less dependent on the ownership of several goods. Emerging generations are increasingly used to sharing things instead of owning them - for example, Millennials, those born between the early 1980s and the early 2000s (Godelnik, 2017). J. Hwang and M. Griffiths (2016) stated in their research that Millennials are more open to the sharing economy than older generations. In their research they state: “Millennials are being touted as the segment of consumers for whom collaborative

consumption is most appealing, as a means of providing access to products, services and resources without the necessity of purchasing or owning them.” (Hwang & Griffiths, 2016, p. 132). Millennials tend to be more open to new methods of ownership because they have adopted another mind-set and they are comfortable with peer-to-peer interaction (Godelnik, 2017).

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Furthermore, Millennials have more understanding of social and sharing causes and tend to be more pragmatic about the environmental impact of their choices than older generations (Hwang & Griffiths, 2016). In addition to the Millennials, we found that the attitudes and willingness towards sharing are generally positive. Consumers link several benefits to the sharing economy, such as environmental, economic and social benefits (Bridoux & Stoelhorst, 2016; Frenken & Schor, 2017). The environmental benefits are difficult to measure, but sharing is assumed to reduce the production of goods as a result of reduction in demand. PricewaterhouseCoopers indicate that 74% of consumers agree that the sharing economy is better for the environment (PricewaterhouseCoopers, 2015). The economic benefits are positive as well, as the income of consumers will be higher as a direct consequence of renting goods instead of buying them. For the rental side, it means that the income of consumers rises when they earn money from temporarily renting out their privately owned goods (Frenken & Schor, 2017) Regarding the social benefits, participants of P2P platforms often meet new people, which can result in

meaningful contacts or, in some cases, new friends (Frenken & Schor, 2017). Therefore, people want to be part of a community, and experience the fun and excitement to meet new people (Bucher, et al. 2016).

As we found in the literature consumers’ positive attitudes and willingness towards the sharing economy leads not direct to participation. In a North American study, respondents were asked if they would rent their car to a total stranger, and nearly 50% of respondents (car owners) indicated that they would consider sharing their car. But when we look to the total percentage of car owners that share their car in North American this number is much less (Wilhelms, et al. 2017). This is in line with the attitude-behaviour gap of Hamari, 2016. Consumers are really positive about sharing, but this does not always lead to participation (Hamari, et al. 2016). Therefore it is important to understand the sharing economy in a more deeper level, especially

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because there are different types of sharing and those types have an impact on consumer behaviour and motivations.

2.1.1 Different types of sharing

There is a great deal of confusing about the use of the concept of sharing and there are no clear boundaries of the definition (Frenken & Schor, 2017; Habibi et al. 2016). Belk defines sharing as “the act and process of distributing what is ours to others for their use as well as the act and

process of receiving something from others for our use” (Belk, 2010, p717). This definition is

really based on peer-to-peer sharing while Habibi describes the difference between pure sharing, pure exchange and dual modes. Those different definitions, or types of sharing, have an impact on consumer behaviour and motivations. Companies in the sharing economy see themselves gladly as ‘pure sharing’ because of the beneficial image it promotes, by having a ‘feel good’ value and associated media attention (Frenken & Schor, 2017; Habibi et al. 2016). When we do a careful analysis of these companies we can conclude that many of them, especially operating in the car sharing sector, are actually not pure sharing. Belk (2014, p.7) defines this phenomenon as ‘pseudo-sharing’ and we expected that this phenomenon is an important cause of the differences in motives of participation in the business-to-consumer and peer-to-peer sharing economy.

ZipCar (a one-way classical car sharing company) is an example of a

business-to-consumer company, pure exchange and can be considered as pseudo-sharing. ZipCar’s members are able to pick-up and return a car without any communication with others, and has therefore nothing to do with a community or creating social bonds (Habibi et al. 2016). The primary motivations to make use of ZipCar are convenience and financial gain. The opposite, for example Couchsurfing (a hospitality network that shares an accommodation for travellers), is pure sharing. Although the platform supervises all the communications between the peers, the communication about the accommodations consist cooperative behaviour, communal bonding, and establish friendships among members. Money is irrelevant and not important for the

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members of Couchsurfing (Habibi et al. 2016). In the middle stands Airbnb (an online

marketplace for the rental and booking of private accommodations), for example. Airbnb can be placed as a dual mode because it contains a mix of pure exchange and sharing. It is

profit-oriented but it also creates social bonds (Habibi et al. 2016, 2017). Consumers and house owners who use Airbnb have created a sense of community and exchange social connections during and sometimes after the stay. Most of the time, the owners create a social atmosphere and engage with their guests during their stay (Habibi et al. 2017). Those parts of the community and social connections motivators may have significant influences on the participation of owners to join the sharing economy and rent out their house.

Frenken and Schor (2017) provide a conceptual framework that defines the sharing economy from their perspective, and in their paper, they describe a new phenomenon called “stranger sharing,” which is new compared to historically pure sharing. Before the

technologically developments existed that make this kind of sharing possible, people were not accustomed to sharing with strangers and only trusted their family, friends and neighbours (Frenken & Schor, 2017). Today, many sharing platforms involve sharing with strangers, which results in a higher degree of risk and trust among users. Frenken and Schor (2017) defines the sharing economy as: consumers granting each other temporary access to under-utilized physical

assets (“idle capacity”), possibly for money (Frenken & Schor, 2017, pp. 2-3). This research

follows Frenken and Schor’s definition of the sharing economy and focusses on pure and dual sharing within the peer-to-peer market. In the next paragraph, we will focus on the car sharing market as part of the sharing economy.

2.1.2 Car sharing

Car sharing gives individuals the opportunity to use private cars without owning them. It is a type of short-term car rental without the responsibilities and costs of ownership (Novikova, 2017). Car sharing is increasingly growing worldwide. Some authors expect that car sharing

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could be the new “mainstream transportation mode” within a few years (Shaheen & Cohen, 2012). Currently there are seven million users part of the car sharing community worldwide. Several reports suggest that this number will be above the 20 million users worldwide in 2025 (Telegraph, 2017). Other studies are even suggesting that it will be even above 36 million users in 2025 (Frost & Sullivan, 2016).

There are several types of car sharing within our society (Bauwens, et al. 2013). For example, Bauwens (2012) differentiates between peer-to-peer (P2P) car sharing and business-to-consumer car sharing (Bauwens et al. 2013). The P2P car sharing includes individuals who offer their cars for rent on an online platform. The providers of the online platform provide the legal and administrative policies, for example SnappCar. This is different in comparison to the business-to-consumer variant because in that case, a company owns the cars and facilitates the sharing among users, for example ZipCar (Shaheen & Cohen, 2012; KiM, 2015). The business-to-consumer is close to the pure exchange side as it is mostly profit-oriented and it is unable to deliver the social benefits and create a community (Habibi et al. 2016). During this research, we will focus on the P2P variant of car sharing. The P2P car sharing market is a type of dual modes of sharing. This type of sharing include both characteristics of exchange and pure sharing. It is profit-oriented as the vehicle owner lends his car through a third-party operator, but it also creates social bonds as the owner transfers the vehicle’s keys to the user (Shaheen & Cohen, 2012). The P2P market is still a niche market, and there is hardly any empirical research available on the use of the various products and services that are offered (KiM 2015).

Unlike B2C car sharing in which the ultimate owner and responsible party for the cars is the platform, involves P2P car sharing other unknown individuals that rent or lend a car. Given the centrality of ‘stranger sharing’ in P2P car sharing schemes it should come as no surprise that unlike in a B2C settings, peer trust is paramount that consumers need to know that they can trust one another regarding usage habits, maintenance, insurance and pick-up and return agreements

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(Möhlmann, 2016; Wilhelms, et al. 2017). The literature shows that there are two main barriers that keep people from participating in P2P car sharing: insurance concerns and the fear of sharing one’s car with strangers (Shaheen & Cohen, 2012). In particular, the high costs of car insurance policies inhibit the breakthrough of car sharing. Many people are still afraid to lend their valuable property to others, as car owners have no confidence in a positive outcome (KiM, 2015; Shaheen & Cohen, 2012). Overall, people are concerned with how others treat their goods and therefore trust is of great importance (Schaefers et al. 2016; Tam & Ho, 2005; Wilhelms, et al. 2017). We can separate two types of participants in the car sharing economy: the car owner (supply side) and the user (demand side). Trust is especially important for the supply side as they have most to risk from misbehaviour on the side of the user. The challenge is therefore to bring the positive aspects of sharing into the limelight, create trust that to overcome fear and create social bonds that should result in a higher intention to participate.

2.1.3 Motivators to participation

Bucher, et al. (2016) conducted a recent study that outlined three overarching motivational patterns that drive car owners to join the P2P car sharing community. These are social-hedonic (seeking human connection), moral (more meaningful, sustainable and environmentally

friendly), and monetary (save money) motives, whereby the social-hedonic motives have the strongest influencers of sharing, followed by the moral motives. We can separate the findings of Bucher, et al (2016) into intrinsically or extrinsically motivations. Intrinsically motivation consist internal desire to do something for its own sake, for example helping others. The social-hedonic and moral motives are part of the intrinsically motivations. The opposite, extrinsically motivation, is motivated by an external factor pushing you to do something in hopes of earning a reward, or avoiding a negative outcome, for example safe money.The monetary motives are part of the extrinsically motivations.

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The most important factors to participate in the car sharing economy are currently debated in the literature. Various studies suggest that sharing platforms should try to convince potential

consumers with extrinsically financial motivators (Bardhi & Eckhardt, 2012), while other studies suggest that sustainability and social benefits, the intrinsically motivators, are the most important for car sharing (Botsman & Rogers, 2010; Bucher, et al. 2016; Lindloff, et al. 2014). The

literature that state that car sharing is driven by financial motivations is mostly taken place in a B2C context as pure exchange or pseudo-sharing practice and will act out of self-interest. This is not comparable to a P2P context. When the focus shifts to intrinsically motivators, it is possible to create a different relationship between the user and owner with positive behaviour as a result.

All-in all this study asserts that the current marketing strategy of many platforms to attract new consumers by playing into financial motivations (e.g. Getaround, Turo and SnappCar - all highlight the financial benefits) may not be the most effective way to grow these P2P car sharing platforms. First of all because, as we explained in detail above, contrary to B2C car sharing when sharing is between peers they are more attracted to sociability and thus more likely to choose a platform that capitalizes on a social promise. Moreover, at a more fundamental level, when platforms engage in symbolic management that highlight higher order motivations such as helping others and the environment this sends out a message that members as a whole operate according to norms in which they respect and want to help one another and one’s property. These values are especially important to attract owners of cars, who as was stated earlier are very sensitive to cues about the cooperative behaviours of others and seeking human connection. 2.2 Relational Model Theory

According to Fiske (1991), people take responsibility for others and exchange goods in different relationships. For this research, we build on Fiske’s (1991, 1992) Relational Model Theory to frame the relationships on the sharing platforms of participants. The Relational Model Theory provides a framework of four models that explain relationships. These models are Communal

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Sharing (CS), Authority Ranking (AR), Equality Matching (EM), and Market Pricing (MP). The developer of the framework, Fiske (1992), claims that individuals are fundamentally social and that they organize their social lives in terms of their relationships with other people. “Whatever the context and content, whatever the substance and surface form of the interaction, people’s primary frames of reference in social life are the same four elementary relational models” (Fiske A. , 1992, p. 690). Three of the four relational models are relevant for relationships between participants on sharing platforms in our research: Communal Sharing (CS), Equality Matching (EM), and Market Pricing (MP). This means that we do not further discuss the Authority Ranking relationship. Fiske defined the relevant models in the following way:

‘Communal sharing is a relation of unity, community, undifferentiated collective identity, and kindness, typically enacted among close kin. […] Equality matching is a one-to-one correspondence relationship in which people are distinct but equal, as manifested in balanced reciprocity (or tit-for-tat: revenge), equal share distributions or identical contributions, in-kind replacement compensation, and turn taking. Market pricing is based on an (intermodal) metric of value by which people compare different commodities and calculate exchange and cost/benefit ratios.’ (Fiske A. , 1991, p. ix)

The relational models can create expectations of how the participants behave within the sharing economy. According to Heyman & Ariel (2004), we can divide those relational models into two general categories: social and economic exchange (Heyman & Ariely, 2004). CS and EM relationships are part of the social exchange, and MP relationships are part of the economic exchange. Both categories have different levels of interdependence and commitment. Social exchange is largely independent of compensation for effort, while economic exchange is characterized to show effort for compensation (Heyman & Ariely, 2004). CS relationships consists of pure sharing among friends and family and are very dependent on other people in completing their activities. People treat all members as equal, and the solidarity and identity of the group are important. For CS relationships it is not important how much people give and receive; it is more important that a good collaboration exists between the different parties. As

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described in Figure 1, CS and MP are the two extremes and EM is the midpoint, which is part of the social exchange category. An EM relationship is perceived as a balanced reciprocity, and as Sahlins describes offers a ‘tit-for-tat’ balance (Sahlins, 2017, p. 176). Therefore, when car sharing is considered to be dual mode with a high focus on the interests of the group rather than only self-interest, sharing is associated with higher levels of trust and recurrence (Belk, 2010; Homans, 1958).

MP forms the economic exchange relationship and is based on people who focus on transactions and act out of self-interest. These types of people are not willing to put effort into relationships and mostly act interdependently. Several studies on human behaviour describe self-interest to be a key motivator of behaviour in general, while building relationships and

collaborating would be more beneficial (Cropanzano, Goldman, & Folger, 2015). Economic exchange focuses on the minimization of transaction costs, cost reduction and the maximization of utility (Möhlmann, 2015, p. 194). Figure 1 shows that Habibi, et al. (2016) describe this type of relationship as a pure exchange (Habibi et al. 2016). As the opposite of the social exchange, the economic exchange only focuses on supporting the transition and not the relationship itself. When a transaction occurs in an economic exchange relationship between two people, both want to minimize their costs and maximize their value. This mostly results in misbehaviour and impersonal outcomes (Habibi et al. 2016).

To provide an overview of the discussed literature, we include a summery of the different frameworks of Habibi, et al. (2016), the relational models of Fiske (1992) and the exchange relationships of Heyman & Ariel (2004). Habibi. et al. (2016), state that the most practices fall between the two extremes of pure sharing and pure exchange, which this researcher refers to as dual modes. In Figure 1, this framework indicates that we can expect stronger commodity-exchange characteristics for the left side. Therefore, when it comes to the consumers’

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and feelings of community, and low profit-seeking motives to P2P car sharing (Habibi, et al. 2016).

Figure 1. Summary of frameworks (Fiske, 1992; Habibi, et al. 2016; Heyman & Ariel, 2014)

Given the impact of relational models in relation to non-ownerships’ collaborative consumption, sharing platforms should prefer a social exchange relationship between peers. As an economic exchange relationship, in which trust between peers is low, is based on people who act out of self-interest and is rather impersonal. In social exchange relationships participants expect the others’ motivations to surpass self-interest (Stofberg 2017), which results in a high level of trust and recurrence. This research will use the social exchange (CS and EM) and economic exchange (MP) as independent variables. Those social and economic exchanges will be manipulated to test the ‘Platform Positioning’ on different landing pages of SnappCar. We used framing, a cognitive

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sense making process, to affect the interpretations of events among our respondents (Fiss & Zajac, 2006). Framing enables us “to comprehend, understand, explain, attribute, extrapolate, and predict” (Starbuck & Milliken, 1988, p. 51) what is going on in the mind of consumers. This study uses the principles of framing to identify something within the lives of respondents in order to shape the representations of the respondents’ relationships with the others (Bridoux & Stoelhorst, 2016; Starbuck & Milliken, 1988). With this technique we want to figure out the type of relationship that result in a positive effect on the intention to participate.

2.3 Platform Positioning

Current car sharing platforms mainly focus on financial benefits for current and potential

participants to share their cars. This research asserts establishes a belief amongst participants that relationships with others are guided by Market Pricing principles that include low

interdependence, low commitment as self-interested behaviour to the expense of the group. Another consequence is that participants in this case have low trust in a good outcome

(Möhlmann, 2016). Möhlmann (2016) states that many participants act out of self-interest in the sharing economy, which results in decreased trust. This can be resulted in misbehaviour and low commitment as Schaefers, Wittkowski, Benoit and Ferraro (2016) found in their research. Schaefers, et al. (2016) suggest that sharing platforms should address customer misbehaviour by creating more personal relationships with customers and increasing communal identification among customers. This is also in line with The Relational Models: CS and EM, which forms the social exchange relationships. Therefore, we expect that a high level of social exchange as Platform Positioning is associated with higher rates of intention to participate.

• H1. A high level of social exchange (Communal Sharing and Equality Matching) as

Platform Positioning is associated with higher rates of intention to participate than a high level on economic exchange (Market Pricing) as Platform Positioning.

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It is important to note that the monetary transaction do not change for any type of exchange relationships. The desire of car owners to benefit financially from sharing their car is still

fulfilled but not underline within the social exchange relationship. The difference lies in the way in which the positioning underscores this monetary transaction.

2.4 Sustainability

The second independent variable is the effect of perceived sustainability on car owners’

intentions to participate. Sharing goods generally have a positive environmental impact because it increases the intensity of the usage of one single product and reduces overproduction. Several studies found evidence that car sharing reduce CO2-equivalent emissions through reduced driving of private cars, car production, and impacts on local air pollution. The literature indicate that households after becoming car sharing members could replace approximately 4 to 13

personal cars with one shared car (Skjelvik, Erlandsen, & Haavardsholm , 2017). Another benefit is that some European studies indicate that between 15.6 and 34% of car owners will sell their car after joining a car sharing platform (Shaheen & Cohen, 2012). In the face of present and future environmental concerns, people’s attitudes regarding the environment are becoming more important. Those attitudes have tended to motivate people to participate in car sharing (Shaheen & Cohen, 2012; Van Kasteren & Meijkamp, 2000). Those motives are moral motives and relate to the concept that sharing is a more sustainable alternative than owning goods by themselves (Bucher, et al. 2016). Author Luchs says that a sharing platform “optimizes the environmental, social, and economic consequences of consumption in order to meet the needs of both current and future generations” (Luchs, Walker, Irwin, & Raghunathan, 2010, p. 2). Therefore, we expect that the presence of sustainability is associated with higher rates of intention to participate.

• H2. Presence of sustainability is associated with higher rates of intention to participate

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2.5 Enjoyment

Enjoyment is a part of intrinsic motivations, and different studies have shown significant positive effects of enjoyment on satisfaction and intention to participate in the peer-to-peer sharing

economy (Fung So, Min, & Oh, 2018; Tussyadiah, 2016; Van der Heijden, 2004). Another study shows that social-hedonic motives have the strongest influence on sharing attitudes. Those motives relate to the fun and excitement of meeting new people and participating in a social dimension (Bucher, et al. 2016). The research of Hwang and Griffiths (2016) found that hedonic benefits, like enjoyment and pleasure, are important for the attitudes and emotional responses to sharing platforms (Hwang & Griffiths, 2016). These studies show the importance of enjoyment to the intention of participation. Therefore, we expect that the mediation of enjoyment between platform positioning and intention will be positively influenced.

• H3. Enjoyment mediates the relationship between positioning and intention to

participate, in a way that positioning based on social (economic) exchange is associated with higher (lower) levels of enjoyment, which positively (negatively) influences the intention to participate.

2.6 Trust

Several studies have shown that trust largely determines consumer behaviour (Möhlmann, 2015; Papadopoulou, Andreou, Kanellis, & Martakos, 2001). Möhlmann defines trust as “a good feeling, ensuring users’ faith in a provider’s reliability, and the impression of security during use or transaction” (Möhlmann, 2015 p. 196). In a sharing platform context, trust refers to the provider of an access-based consumption service and to the other participant with whom one shares and can be considered to be an important determinant (Botsman R. & Rogers, 2010). Overall, when there is no trust, the probability that two strangers engage in a transaction of any sort will be low (Kim, Chung, & Lee, 2011). Therefore, we can see trust as an underlying

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motivation that impacts the level of intention. We expect that a social exchange relationships of Platform Positioning increase the intention to share because it increases trust. This is the result based upon Communal Sharing relationships, which have higher levels of trust (Belk, 2010; Bridoux & Stoelhorst 2016). In a social exchange relationship, participants expect others to respect them and their property, which results in building trust (Bridoux & Stoelhorst 2016; Stofberg 2017). Conversely, economic exchange relationships of Platform Positioning, which focus more on self-centred behaviour, which limits relational depth and trust (Bridoux & Stoelhorst, 2016). The value that a platform and its consumers share affects consumer trust (Morgan & Hunt, 1994). This mediating role of trust leads to the following hypothesis:

• H4. Trust mediates the relationship between positioning and intention to participate in a

way that positioning based on social (economic) exchange is associated with higher (lower) levels of trust, which positively (negatively) influences the intention to participate.

2.7 Conceptual framework and hypotheses

This study examines the effects of Platform Positioning and the presence of sustainability on car owners’ intentions to participate in car sharing. The Platform Positioning is based on the

independent variable, social or economic exchange relationships. The social exchange

positioning includes the CS and EM relationships, whereas the economic exchange positioning includes the MP relationship. The social exchange is hypothesized directly with a positive effect on intention. The presence and absence of sustainability is the other independent variable. The effect of the presence of sustainability on intention is hypothesized directly. The first

independent variable is expected to be mediated by enjoyment and trust. Figure 2 illustrates the conceptual framework with the corresponding hypotheses. Table 1 presents an overview of the hypotheses.

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Figure 2. Conceptual framework

Table 1. Overview of hypotheses

H1. A high level of social exchange (Communal Sharing and Equality Matching) as Platform Positioning is associated with higher rates of intention to participate than a high level on economic exchange (Market Pricing) as Platform Positioning.

H2. Presence of sustainability claims is associated with higher rates of intention to participate than absence of sustainability claims.

H3. Enjoyment mediates the relationship between positioning and intention to participate, in a way that positioning based on social (economic) exchange is associated with higher (lower) levels of enjoyment, which positively (negatively) influences the intention to participate. H4. Trust mediates the relationship between positioning and intention to participate in a way that positioning based on social (economic) exchange is associated with higher (lower) levels of trust, which positively (negatively) influences the intention to participate.

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3. Methodology

This chapter discusses the methodology used in this study. First, we will explain our choice for the car sharing platform SnappCar. This is followed by the research design, which consists of a combination of a vignette experiment and a survey questionnaire. A pre-test is performed to ensure that the vignettes intend what they should do and to check the credibility of the hypothetical situation.

3.1 Car sharing platform SnappCar

This research is held in cooperation with the largest Dutch P2P car sharing platform, SnappCar. SnappCar is a peer-to-peer car sharing platform and was founded in 2011. This car sharing platform has more than 500.000 users and more than 50.000 available cars on the platform. Therefore, SnappCar make it possible to easily rent a car from one of your neighbours. SnappCar claims to be the largest peer-to-peer car sharing platform in Europe. Currently, the company is active in The Netherlands, Denmark, Sweden and Germany (Marketingfacts, 2018). The mission of SnappCar is to decrease 5 million new cars that can be reduced through sharing and to reduce pollution in Europe by 2022 (SnappCar, 2018). One of SnappCar’s most difficult problems is a shortage of rental cars. The CEO of SnappCar, Victor van Tol, says: “People find it scary to rent out their car” (Marketingfacts, 2018). Therefore, it is important that SnappCar increases its knowledge about the motivations of car owners to participate in the sharing economy. Like many other car sharing platforms, SnappCar’ Platform Positioning is currently based on a Market Pricing relationship. The current slogan is as follows: “Reimburse your car expenses. Share your car easily and safely via SnappCar and quickly earn € 1000 per year.” Therefore, SnappCar’s website focuses on an economic exchange relationship. This provides the opportunity to research further and determine whether social exchange would lead to a higher intention for car owners to participate.

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3.2 Research design

This research contains quantitative methods of a vignette study and a closed-ended question survey. Vignettes consist realistic hypothetical characters in specified circumstances, to whose the respondent should response (Finch, 1987). With the vignette methodology, we are able to manipulate and control the independent variables and test the hypotheses in a realistic scenario (Aguinis & Bradley, 2014). This vignette study presents participants in a realistic scenario – viewing SnappCar’s landing page - to assess dependent variables of intentions to participate. The independent variables of Platform Positioning and sustainability are manipulated. Participants of the vignette study are placed in a realistic scenario in which the car owners, are motivated to participate in sharing their car. We have asked those who do not own a car to imagine the situation when they own a car by themselves. The participants are randomly assigned to one of the four landing pages. In Table 2 we presented an overview with the conditions of the four landing pages. We have designed the content of the landing pages based on SnappCar’s current website. All vignettes include a slider, introduction, how it works, testimonials and some confidence information. All the vignettes are attached in Appendix 1.

Table 2. Overview of the vignettes

Absence of sustainability Presence of sustainability Platform Positioning based on

social exchange

Vignette 1 Vignette 3

Platform Positioning based on economic exchange

Vignette 2 Vignette 4

3.3 Survey Questionnaire

The vignettes are followed by a survey questionnaire to enhance the understanding of the

dependent variable intention to participate and the mediators’ enjoyment and trust. In addition to this information, we collect data about the demographics of the participants. An online survey

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questionnaire is time- and cost-efficient and allows us to acquire a lot of data, which is very suitable for the closed-ended questions (Saunders, Lewis, & Thornhill, 2000; Wright, 2005). Closed-ended questions maximize the response rate and increase the completeness of the questionnaire (Pham, 2009). The survey questionnaire is in Dutch to prevent misunderstanding and misinterpretation of the survey questions. The full survey is attached in Appendix 2. 3.4 Measure Development

This paragraph describes how the variables are measured and how we adapted the variables into the questionnaire. We attempt to ensure the validity and reliability of our research by using existing constructs. All the adapted measures were originally in English and we have used a technique called back-translation in order to translate the measures to Dutch. An overview with all the measures are attached in Appendix 3.

3.4.1 Perceived relational models

The positioning manipulations where questioned by using a 7-point scale (1. I strongly disagree – 7. I strongly agree) to tell to what extent they match the presented platform vignette to the three relational models: CS: “SnappCar is a social car sharing platform”; EM: “SnappCar is a car sharing platform that makes everyone better”; and finally MP: “SnappCar is a car sharing platform where you only participate for financial motivations.”

3.4.2 Perceived sustainability

Sustainability is measured on a 5-point scale adopted by J. Hamari, M. Sjöklint and A. Ukkonen. The researchers state that the perceived sustainability has a positive effect on attitude.

Sustainability has a composite reliability of α=0.867 (Hamari, Sjöklint, & Ukkonen, 2016). The adapted measures are: “SnappCar contributes to saving natural resources through car sharing”; “SnappCar contributes to a sustainable way of consumption”; “SnappCar is efficient in the use of goods thanks to car sharing”; “SnappCar is environmentally friendly” and “SnappCar is

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ecological.” All of these scales are measured on a 7-point Likert scale, ranging from ‘completely disagree’ to ‘completely agree’ at an interval level.

3.4.3 Enjoyment

Enjoyment is mediated on a 5-point scale adopted by J. Hamari (2015) and has a composite reliability of α=.794. We adopted one of the items to “I find it exciting to share my car

(positive)”. In Dutch the direct translation can be seen as negative, which is the reason we added “positive” after this item (Dutch translation: “Ik vind het spannend om mijn auto te delen

(positief)”). The 5-point scale is measured on a 7-point Likert scale, ranging from ‘completely disagree’ to ‘completely agree’ at an interval level.

3.4.4 Trust

Trust is mediated on a 6-point scale adopted by M. Möhlmann (2015) and has a composite reliability of α=.84. One of the items is: “I trust that SnappCar adheres to what they

communicate on the website.” The 6-point scale are measured on a 7-point Likert scale, ranging from ‘completely disagree’ to ‘completely agree’ at an interval level.

3.4.5 Intention to participate

We combined two scales to ensure that this dependent variable is measured correctly. We used a 3-item scale adopted by Ajzen (1991), which has a composite reliability of α=.946. Furthermore, we added one questions from the scale developed by White et al. (2012) “It is likely I would use SnappCar to offer my car.” A 7-point Likert scale is used for both constructs.

3.4.6 Control variables

The control variables of the questionnaire are gender, education level, car possession, income and residency since these factors can influence the likelihood of participation in the car sharing economy. For instance, several studies found that Millennials are in particular more open to

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access-based consumption (Bardhi & Eckhardt, 2012; Hwang & Griffiths, 2017). Another study indicates that car sharing is more an urban phenomenon (Davis & Dutzik, 2017).

3.5 Pre-test

A pre-test was developed in order to determine whether the manipulations of the independent variables will work for the designed landing pages and the validity of the experiment. The pre-test checked if the outcome of our control questions are in line with the type of landing pages that the respondent has seen. This test was done to find out if there was a different intention rate and rating of the Relational Models within the four vignettes. The pre-test asked respondents on a 7-point Likert scale (1= not at all, 7 = very much) to what extent one of the four landing pages’ score on the Relational Models (CS, EM and MP). In specific, respondents were asked to what extent they were thinking about the Platform Positioning described in three types.

Type 1 (CS): SnappCar is an online sub-platform where transactions are characterized by a high level of generosity. On this platform people have the feeling that they have a lot in common and belong to the same group.

Type 2 (EM): SnappCar is an online sharing platform that arranges transactions on the basis of reciprocity and equality. People on this platform try to maintain a relationship in terms of the idea that everyone gets something or benefit from the platform.

Type 3 (MP): SnappCar is an online sharing platform that arranges transactions based on 'you get what you put into it.’ People on this platform believe that they receive a good return on what they put into the platform.

Moreover, this pre-test tested the absence or presence of sustainability, the other independent variable. This is done by manipulating environmental aspects into two of the vignettes. Of the four vignettes two (social and economic) included the presence of those environmental aspects. To test if the intention to participate was higher when sustainability was included, we asked on a 7-point Likert scale if “SnappCar contributes to saving natural resources through car sharing,

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SnappCar contributes to a sustainable way of consumption, and SnappCar is environmentally friendly.” The full pre-test survey can be found in the Appendix 4.

3.6 Applied manipulations

To trigger the social and economic exchange relationships and the absence or presence of sustainability, we have created four vignettes of the SnappCar landing page. The independent variable platform positioning (social / economic) was created by the outcomes of Habibi, Davidson and Laroche (2017). In their recommendations they communicated about social and financial sharing (Habibi, Davidson, & Laroche, 2017). The social exchange landing page condition consists of community and neighbourhood factors that are part of social relationships. The main messages of this condition are: “Share your car via SnappCar and help your

neighbours move forward,” “Create the ultimate neighbourhood feeling” and “Car sharing is sharing together.” In this vignette, we avoid references to money or other financial-related calculations. The economic exchange condition consists of financial factors as earning money by renting out one’s your car. With this condition, we want to trigger the MP relationship. The main messages of this condition are: “Do you want to make money with your car if you do not use it?” and “Rent your car via SnappCar and quickly earn 1000 euros per year.” Here, we exclude any neighbourhood-related factors and did not use the pronouns ‘we’ or ‘us’, but only ‘I’ and ‘you’. In addition to the textual modifications, we implemented other pictures for the social and

economic exchange vignettes. The social pictures showed several people, and the economic pictures did not show any people in the first two blocks.

The other independent variable, sustainability, consists elements that have a positive impact on the environment when this variable is present. We add two more vignettes and include the sustainability variable for the social and economic exchange. The social exchange and

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been added. The main message of this vignette is: “Help your neighbours ahead and contribute to a sustainable society.”

Finally, the economic exchange and sustainability landing page condition consist of the same economic aspects, and sustainability has been added. The main message of this vignette is: “Recoup your car costs and contribute to a more sustainable society.” The four vignettes are shown in the Appendix 1.

3.7 Results pre-tests

We performed a pre-test to determine if our vignettes work as we expected. The four vignettes are tested at a response of N=82 and work for Platform Positioning, but work not for

sustainability. Table 3 presents the results of the pre-test. The results show that social and economic exchange vignettes are significantly correlated to the descriptions of CS and MP relationships (r=.474 p<.01 and r= -.387 p<.01). For EM, we found not any significant

differences. The correlation between sustainability and social exchange (CS) is positive (r=.145 p<.194) and the correlation between sustainability and economic exchange (MP) is negative (r=-.115 p<.302). But both correlations are not significant. We did not find any significant results between sustainability and the Platform Positioning’s. Therefore, we performed more analyses and considered the intention as well. The intention to participate after respondents saw the social exchange vignette was significantly positive correlated with Platform Positioning (r=.550 p>.01). The intention to participate after respondents saw the economic vignette was significantly

negative correlated (r=-.270 p>0.5), which is in line with our expectations. The results for the sustainability vignette studies where again not significant. The presence of sustainability related to the intention to participate is not significant (r=.041 p>.715). This suggests that there is a direct relationship between the Platform Positioning variables, with the exception of

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Table 3. Pearson Correlations between variables of the pre-test Variable 1 2 3 4 5 1. Platform Positioning (social) 2. Sustainable -.028 3. CS .474** .145 4. EM .016 .082 -.004 5. MP -.387** -.115 -.433** .024 6. Intentions .550** .041 .374** -.032* -.270* N=82

** Correlation is significant at the 0.01 level (2-tailed) * Correlation is significant at the 0.05 level (2-tailed)

After the results of Table 4 we exclude the sustainable vignettes to extract the effect of the social and economic exchange relationships.

Table 4. Pearson Correlations between variables of the pre-test without sustainability

Variable 1 2 3 4 1. Platform Positioning (social) 2. CS .647** 3. EM -.133 -.004 4. MP -.548** -.433** .24 5. Intentions .613** .374** -.032 -.270* N=46

** Correlation is significant at the 0.01 level (2-tailed) * Correlation is significant at the 0.05 level (2-tailed)

As the results of Table 4 describe, we see that the effect without sustainability is even higher than we expected. The results show that the social and economic exchange vignettes are

significantly correlated to the descriptions of social exchange (CS) and economic exchange (MP) relationships (r=.647 p<.01 and r= -.548 p<.01). The intention to participate after respondents saw the social exchange vignette was significant correlated (r=.613 p>.01). The intention to participate after respondents saw the economic vignette was the same (r=-.270 p>.05). Therefore,

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we can conclude that the manipulations of the independent variable Platform Positioning are working for the designed landing pages (vignette 1 and 2). After reviewing the pre-test without the effects of sustainability we decided to do an exploratory study to get more insight about the effects of sustainability on the intention to participate. In the next chapter, we will discuss the outcome of this exploratory study.

3.8 Exploratory study

In the following section, the relation between the presence of sustainability, the intention to participate and perceived sustainability is analysed. The presence of sustainability is the

independent variable, intention to participate the dependent variable and perceived sustainability is the mediator. We found no significant positive or negative correlations as Table 5 presented. Table 5. Means, Standard Deviations, Correlations of the exploratory study

Variables Mean SD 1 2

1. Sustainability (presence) 0.439 0.5 -

2. Intention 0.549 0.13 -.36 -

3. Perceived sustainability 0.445 0.17 -.215 -.089

N=36

** Correlation is significant at the 0.01 level (2-tailed) * Correlation is significant at the 0.05 level (2-tailed)

In order to test the relation a regression analysis was conducted. It examined the linear relation between the independent variable, sustainability, and the dependent variable intention to participate. The results are shown in Table 6.

Table 6. Regression Model of the exploratory study

Variable R R2 B SE β T

.041 .002

Sustainability .095 .259 .041 .366

N=46

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The relationship between sustainability and the intention to participate is not significantly correlated, since the p-value is .715. The correlation coefficient, R, is .041. Therefore, we can conclude that the presence of sustainability is not correlated with the intention to participate. To test if perceived sustainability partly mediates the effect of sustainability on the intention to participate the SPSS macro of Hayes (2012) was used. In the first part of the indirect effect (a1), sustainability has a positive effect on perceived sustainability but not significantly (B= .06035, p= .0187). The other part, (b1)perceived sustainability, has a negative effect on intention, but this is not significantly (B= -.0560, p= .6291). The indirect effect is negative (B = -.0338) and indicates that the intention to participate is lower by the mediation of perceived sustainability. The direct effect (c1’) of sustainability to intention is positive, but not significantly (Effect= .1285, p= .6343). This exploratory study provides no evidence that the presence of sustainability is associated with higher rates of the intention to participate. Furthermore, we found no significant evidence that perceived sustainability has an effect on the intention to participate. From a managerial perspective, the exploratory study provides some implications. In particular, it shows that the presence of sustainability does not result in a higher intention to participate within the car sharing economy. As several studies state, that the presence of sustainability is a major factor to participate in the sharing economy, and we do not find any significant evidence. Other sustainability and environmental factors that we used as mediators, do not have a significant effect either. An interesting side note is that the outcome of the effect of perceived sustainability to intention produced a negative effect. In the event that it was significant, it should mean that people do not see car sharing as a way to improve the environment. In the open-question outcome, we find several opinions that promoting car sharing encouraged one to do more driving, which is not sustainable at all.

As the sample was really small (N=82), we cannot draw conclusions about the whole population. Other possibility is that the sustainable aspects in our vignette did not work out. Further research

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is needed with larger sample size to determine the effect of environmental aspects in relation with intention to participate. In the next subparagraph we presented the modifications as we did not found any effect of environmental aspects related to our vignettes.

3.9 Modifications after exploratory study

After the exploratory study, we decided to remove the presence of sustainability from the further analysis of our study, because we did not found any effect of environmental aspects related to our vignettes and we have doubts about the framing effects of the sustainability vignettes. We want to improve the quality of our study related to Platform Positioning. Therefore, we exclude vignette 3 and 4 and the questions related to environmental aspects from the further data

collection. This means that for our final study participants are randomly assigned to one of the two landing pages instead of one of the four. This also means that we remove H2 from our study. Table 7 presented our remaining hypotheses.

Table 7. Overview of hypotheses after exploratory study

H1. A high level of social exchange (Communal Sharing and Equality Matching) as Platform Positioning is associated with higher rates of intention to participate than a high level on economic exchange (Market Pricing) as Platform Positioning.

H2. Presence of sustainability claims is associated with higher rates of intention to participate than absence of sustainability claims.

H3. Enjoyment mediates the relationship between positioning and the intention to participate, in a way that positioning based on social (economic) exchange is associated with higher (lower) levels of enjoyment, which positively (negatively) influences the intention to participate. H4. Trust mediate the relationship between positioning and the intention to participate in a way that positioning based on social (economic) exchange is associated with higher (lower) levels of trust, which positively (negatively) influences the intention to participate.

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4. Data collection and analysis

4.1 Data Collection

Data will be collected through an experimental survey among Dutch car owners. This

experimental survey will be based on vignettes. This survey will take place in the Netherlands and will be questioned to car owners from the age 18 years and older who already (or do not) participate within the car sharing economy. In the Netherlands, there are following the CBS 7.297.664 car owners of passenger cars (Centraal Bureau voor de Statistiek, 2017). We want to have an equal representation of women and men in all layers of society older than 18. To find suitable respondents this research has take place at different parking garages in the Netherlands, where we collected e-mails addresses to sent our questionnaires to. This type of data collection is a non-probability sampling technique, and we have used convenience sampling. The sample size is 200 or more respondents to have a great amount of data following the rough rule of Thumb. 4.2 Data analysis

The analysis of the data is exported by Qualtrics to IBM SPSS Statistics 25. A total of 280 people participated in the survey. In order to prepare the data for analysis, the data was checked for missing values. The respondents who did not complete the survey were excluded from further analysis. This resulted in 79 deleted responses. The number of incomplete responses could be caused by the mandatory time (50 seconds) that people must wait and screen the landing page before they were able to click further. We have seen that a large amount of respondents left the survey after filling in the first question, which occurred before we showed the landing page. After removing the 79 respondents who did not complete the survey, we still got the data of 201 respondents. Table 8 present the distribution of respondents across our vignettes. The next step we did were the tests for normality, skewness and kurtosis. After this test, we performed a

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categorical variables into dummy variables and combined the measuring variables for trust, enjoyment and intention to participate after checking the Cronbach’s alphas (α >.7) without possibilities to improve. When we prepared all data for further analysis, we analysed a correlation matrix. This matrix includes the variables Platform Positioning, trust, enjoyment, intention to participate, and the control variables and gives us insight into how the variables are related to each other. An ANOVA was used to compare the believability and credibility of the different vignettes.

Finally, the hypotheses testing was executed by regression analyses of PROCESS by Hayes (2013). This analysis gives us the indirect, direct and conditional effects of our mediators. Furthermore, we used this tool to check if our control variables, as moderators, have any effect of the outcome of our conceptual model. As recommended by Hayes (2013), we used Model 4 in PROCESS to test our hypothesis. The next section presents the results of these analyses.

Table 8. Distribution of respondents across our vignettes

Vignette N Percentage (%) 1. A 2. B Total: 98 103 201 49% 51% 100%

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5. Results

The results of the data analyses are described in this chapter. First, we describe the descriptive statistics of the analysis and second, we describe the distribution of the data.

5.1 Descriptive statistics

The sample consists of 201 participants, of whom 78,6% of the respondents owns a car (158) and 21,4% do not own a car (43). The average age of the respondents is 34 years (M = 33.81, SD= 14.08, range= 55). This indicates that the respondents are a diverse sample regarding age, ranging from 18 to 73 years old. Moreover, 90 respondents are male (44,8%), compared to 111 female respondents (55,2%). The majority of the sample (36,8%) was educated with an Applied Sciences degree; 18,4% have a WO Bachelor degree and 28,9% were highly educated (WO Masters or PhD). A total of 14,4% of the respondents are poorly educated (finished elementary school, high school or MBO). The largest group of respondents has an income between 1501 and 3500 euros per month (45,8%), followed by 26,4% of respondents that earn less than 1500 euros per month. A total of 11,4% earns on a monthly basis between 3501 and 5500 euros, and 7% earns over 5500 euros per month. A total of 9,5% of the respondents preferred not to disclose about their income. Regarding the urbanity of the respondents, 88,6 % of the respondents lives in a city (Amsterdam: 25,4%, Rotterdam: 3,5%, Den Haag: 3%, Other in Randstad: 28,9%, Other outside of Randstad: 27,9%) versus 11,4% of the respondents who live in a village.

5.2 Distribution

Both mediators’ enjoyment and trust and the dependent variable intention to participate are tested on skewness and kurtosis (Appendix 5). Some values have skewness or kurtosis problems: two of the five enjoyment values have negative kurtosis problems (<-1). One of the trust values has a negative skewness problem (<-1) and positive kurtosis problems (>1). The intention to

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variables in this condition are not normally distributed. The Kolmogorov-Smirnov and the Shapiro-Wilk tests have significant p- values (<.05). However, with large sample sizes the statistical analyses in this research are robust against skewness and kurtosis according to

Tabachnick and Fidell, since we have more than 200 respondents (Tabachnick & Fidell, 2001). 5.3 Manipulation check

To check whether the vignettes communicate the correct underlying theories, we present a correlation matrix in Table 9. Platform Positioning has a positive correlation with the CS

description (r= .159, p<.05) and a negative correlation with the MP description (r=-.347, p<.01). This indicates that the social and financial vignettes trigger the correct relational model. The EM description does not correlate significantly with Platform Positioning. The results show that CS and MP are negatively correlated with each other (r= -.221, p>.01). This is in line with our model. As our model also suggests, CS is positively correlated with EM (r = .176, p>.01), which indicates the social exchange relationship of Heyman & Ariely, 2004.

Furthermore, we have done an analysis of variance, an ANOVA, for CS (F(1, 199)=5.156,

p=.005), MP (F(1, 199)=27.221, p=.000) and EM (F(1, 199)=1.021, p=.313). This means that

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Table 9. Pearson Correlations for manipulation check Variable 1 2 3 4 5 1. Positioning 2. CS .159* 3. MP -.347** -.221** 4. EM -.071 .176* -.037 5. Enjoyment -.021 -.047 -184** .062 6. Trust .013 .206** -.133 .174* .376**

*. Correlation is significant at the 0.05 level (2-tailed). **. Correlation is significant at the 0.01 level (2-tailed) N=201

5.4 Correlations

In Table 10, the Means, Standard Deviations and Pearson Correlations of all variables are presented. There is no significant correlation between Platform Positioning and intention to participate. This suggests that there is no direct relationship between these variables, which is not in line with Hypothesis 1. There is no significant correlation between Platform Positioning and the mediators’ enjoyment and trust. Those results are also not in line with Hypothesis 3 and 4. However, there is a significant correlation between the mediators’ enjoyment and trust and the intention to participate. Enjoyment has a strong correlation with intention to participate (r=.561, p<.001). Trust has a strong significant correlation with intention to participate as well (r=.391, p<.001). These results are partly in line with Hypothesis 3 and 4, but do not cover the total effect of our established Hypotheses. This outcome suggests that Platform Positioning does not affect enjoyment or trust, but that enjoyment and trust does affect higher intention to participate. Finally, we found a significant positive correlation between enjoyment and trust (r=.376, p<0.01).

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