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What platform perceptions are most attractive in

the sharing economy and do trust and prosociality

influence this?

Claire Henriette Christine Tromp - 10268391 Master Thesis – 23rd of June 2017

Master in Business Administration - Marketing University of Amsterdam - Business School Supervisor - Nicole Stofberg

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Statement of originality

This document is written by Student - Claire Henriette Christine Tromp - who declares to take full responsibility for the contents of this document. I declare that the text and the 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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Abstract

The sharing economy is on the rise, but with the exception of household names such as Airbnb, Blablacar and Couchsurfing, many platforms are still small and are having a difficult time attracting new users and living up to their potential on paper. In an attempt to crank up usage numbers, these platforms are appealing to utilitarian interests of potential users. However, as this strategy has resulted in limited success to date, this thesis goes back to the roots of sharing and investigates how relational value might be more effective in increasing sharing of users than market incentives. In doing so, this thesis builds on Fiske’s relational models theory to investigate whether the perceived effects of the relational models

Communal Sharing (CS) and Equality Matching (EM) are more effective than the perceived effect of Market Pricing (MP) in stimulating participation. This is based on the fact that MP is linked to gaining utilitarian value and CS and EM are linked to gaining social and

communal value. This research looked into whether trust serves as a mediator as trust stimulates online transactions and so trust is expected to be an important determinant of online sharing behavior. Besides, it looked into whether prosociality serves as a moderator, as it is expected that prosocial people intend to help others more and thus participate more often in online sharing activities. A vignette study was conducted among Dutch participants (N = 302). The perceived relational models (CS/EM/MP) doesn’t seem to be solely triggered by the different conditions (CS/EM/MP). Future research needs to investigate how relational models can be triggered, so individuals also perceive/frame it that way. Furthermore, the results ascribed in this paper confirm the relationship of the perceived relational models and sharing intentions, as well as of the mediating effect of trust between the relational models and sharing intentions. Even an unexpected effect of trust as a mediator between perceived MP and sharing intentions was found. Finally, this study could not establish the expected moderating effect of prosociality.

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Contents

INDEX OF FIGURES AND TABLES ... 4

1. INTRODUCTION ... 5

2. LITERATURE REVIEW ... 9

2.1THE SHARING ECONOMY ... 9

2.2MOTIVATIONS TO PARTICIPATE IN THE SHARING ECONOMY ... 11

2.3RELATIONAL MODELS ... 12

2.4TRUST AND RELATIONAL MODELS ... 17

2.5PROSOCIALITY ... 20

3. THEORETICAL FRAMEWORK AND HYPOTHESIS ... 21

3.1CONCEPTUAL MODEL ... 22

3.2(PERCEIVED) RELATIONAL MODELS ... 22

3.3PERCEIVED RELATIONAL MODELS AND SHARING INTENTIONS ... 24

3.4TRUST AND SHARING INTENTIONS ... 25

3.5PROSOCIALITY AND SHARING INTENTIONS ... 27

4. METHODOLOGY ... 28

4.1STIMULI DEVELOPMENT (PRE-TEST) ... 29

4.2RESEARCH DESIGN ... 32

4.3MEASUREMENT OF VARIABLES ... 33

4.3.1 The independent variable: Perceived relational models (CS, EM and MP) ... 33

4.3.2 The dependent variable: Sharing intention ... 33

4.3.3 The mediator: Trust ... 34

4.3.4 The moderator: Prosociality ... 34

4.3.5 Demographic variables ... 34

4.4THE SET-UP OF THE SURVEY ... 35

4.5SAMPLE OF THE SURVEY ... 36

4.6POPULATION AND PROCEDURE ... 37

4.7DATASET ... 37 5. RESULTS ... 38 5.1DESCRIPTIVE STATISTICS ... 38 5.2RELIABILITY ANALYSIS ... 40 5.3MANIPULATION CHECK ... 41 5.4CORRELATION MATRIX ... 42 5.5HYPOTHESIS TESTING ... 43

5.5.1 Hypothesis 1 – Checking relational models ... 43

5.5.2 Hypothesis 2 – Perceived relational models and sharing intention ... 44

5.5.3 Hypothesis 3 – Trust and sharing intentions ... 46

5.5.4 Hypothesis 4 - Trust as a mediator for the perceived models CS and EM ... 47

5.5.5 Hypothesis 5 – Trust as a mediator for the perceived model MP ... 50

5.5.6 Hypothesis 6 – Moderation prosociality on perceived CS and EM and sharing intention ... 52

5.5.7 Hypothesis 7 – Moderation prosociality on perceived MP and sharing intentions ... 52

6. DISCUSSION AND CONCLUSION ... 53

6.1DISCUSSION ... 53

6.2RESEARCH CONTRIBUTIONS ... 56

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6.5CONCLUSION ... 60

7. REFERENCES ... 62

8. APPENDIX 1: QUESTIONNAIRE INSTRUCTIONS ... 71

9. APPENDIX 2: DIFFERENT VIGNETTES OF PARKFLYRENT ... 72

9.1COMMUNAL SHARING ... 72

9.2EQUALITY MATCHING ... 73

9.3MARKET PRICING ... 74

10. APPENDIX 3: QUESTIONNAIRE ITEMS ... 75

Index of Figures and Tables Figure 1. Conceptual model Table 1. Results of pretest

Table 2. Allocation of participants over the relational models

Table 3. Frequencies and percentages of demographic variables of all respondents (N = 302) Table 4. Descriptive Statistics

Table 5. Normality test depended variable Table 6. Cronbach Alpha

Table 7. Correlation Matrix

Table 8. Regression results: Perceived CS, EM and MP on sharing intention Table 9. Regression results: Trust on sharing intentions

Table 10a. Process results perceived CS, Trust and Sharing intention

Table 10b. Process results perceived CS, Trust and Sharing Intentions: Indirect, direct and total effect

Table 11a. Process results perceived EM, Trust and Sharing intention

Table 11b. Process results perceived EM, Trust and Sharing Intentions: Indirect, direct and total effect

Table 12a. Process results perceived MP, Trust and Sharing intention

Table 12b. Process results perceived MP, Trust and Sharing Intentions: Indirect, direct and total effect

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1. Introduction

Sharing can be seen as the most basic form of human economic behavior. Sharing goes back as far as humanity has existed, but the recent reality of the sharing economy is a product of the rise of the Internet. This is a reality that was born in the digital age (Belk, 2014a). Digitalization and changes in attitude towards consumption, social media and other factors have contributed to a relatively new economic model where consumers are able to share products and services through collaborative consumption1 (Botsman & Rogers, 2010; Hamari et al., 2015). Today, the sharing economy is on the rise with platforms like Uber and Airbnb, however lots of sharing platforms are still at their infancy (Teece, 2010). To date, little research has been done into the fact that sharing economy platforms have difficulty growing.

The landscape of sharing economy platforms has changed; what used to be sharing out of ‘good faith’ is currently mainly sharing out of utilitarian and economic reasons (Habibi, Kim & Laroche, 2016a). Even Couchsurfing, “the free of charge platform”, which was known for offering up couches for free all around the world, for people to stay and meet locals, has changed its business model into a monetized business model; you have to pay for verification nowadays (Mettavant, 2014; Habibi, Davidson & Laroche, 2016b). It seems that the concept of sharing has been turned into a profitable business model (Sach, 2015). This model has been adopted by for example Uber; they have turned community-based sharing into economic self-interest (Codagnone & Martens). However not all platforms seem to have turned the advantages of the sharing economy in their favor.

In practice, lots of sharing platforms have difficulties to securing their share of the promised gold rush. Indeed while many consumers say they would participate in most sharing activities that extend beyond hailing a cab via an online platform and sharing their

accommodations in practice they are reluctant to share their cars, personal items, skills,

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means and so forth. For sharing economy businesses it is not clear exactly what attracts users (Teece, 2010). Many of them have followed the advice of academia and media to focus on tangible benefits and highlight convenience, yet this strategy does not appear to make a dent in the slow growth of small players (Belk, 2014b; Mettavant, 2014; Molz, 2013). This thesis asserts that the main problem is that the studies on topic to date have focused on the leading motivations of the individual, even though when it comes to sharing the intentions of others may be more telling (Frenken & Schor, 2017). After all, successful sharing depends on the cooperation between two peers. If one user in a sharing transaction freerides on the good intention of the other, the result could be that property is not handled with care and not returned in the state it was received in (Belk, 2010). Fear or mistrust of the other unknown user is often believed to be the main barrier toward sharing and, as this thesis asserts, the main reason that people do not put their money where their mouth is.

Trust is considered universally important when participating in online scenarios. For consumers, it is important that they choose a platform they trust, but they also need to trust the product or service that is offered and the provider of the specific good or service. In turn, the provider also needs to trust the consumer when giving access to these specific goods or services (Hawlitschek et al., 2016). Trusting the provider and trusting the consumer in turn could indicate that social cues are considered important when participating in collaborative consumption. It could be that sharing economy platforms become more attractive when they involve social/relational cues, because those cues can generate trust and motivate people to participate (Mohlmann, 2015). Therefore, this thesis builds on Fiske’s relational models theory when priming a certain platform (Fiske, 1991; 1992). This theory is based on the fact that participants use relational models to “plan and to generate their own action, to

understand, remember and anticipate others’ actions” (Fiske, 2004: 3). This means that participants derive specific relational cues from the platform when this is primed in a way

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that certain relational cues can be derived. Market Pricing (MP) is the most distant

relationship which we form with people, acting out of self-interest is the norm; individuals treat each other as business partners and it is based on individual gains. Communal Sharing (CS) and Equality Matching (EM) are both relationships where people do not act out of self-interest; individuals treat each other with respect and this is based on communal feelings and equality. We predict that platforms that are primed with social/relational cues are perceived as CS and/or EM, and that these perceptions are generating more trust than platforms primed without social/relational cues that are perceived as MP. Because trust is found to be an important instrument between perceived relational values and sharing intentions (Pavlou & Geven, 2004; Mohlmann, 2015; Stofberg, 2017), it is predicted that platforms with

social/relational cues that are perceived as CS or EM are mediated by trust and have a positive influence on sharing intentions. However it is expected that platforms without social/relational cues that are perceived as MP are negatively mediated by trust when it comes to sharing intentions.

Second, few studies have overlooked the fact that individual differences/personality differences might also play a leading role in one’s ultimate intentions to start sharing. It has been found that “individuals values might hinder or contribute the acceptance, adoption and diffusion of collaborative consumption” (Piscicelli, Cooper & Fisher, 2015: 28). Personal values and attitudes do have an effect on participatory behavior in collaborative consumption. Some people are more inclined than others to engage in behavior that helps others, even in the case of the sharing economy. “Prosocial attitudes capture the general tendency of people wishing for good outcomes not only for themselves but also for others” (Brief & Motowidlo, 1986: 710). It is assumed that prosociality serves as a moderator between the perception of relational models and sharing intentions, because people who engage in prosocial behavior

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are always more willing to help others than those who do not engage in prosocial behavior (Caprara, Alessandri & Eisenberg, 2012).

The aim of this study is to reveal what platform positioning makes people intend to participate most. Individuals’ perceptions of platform positioning are examined by using Fiske’s relational models (1991; 1992). Additionally, the generation of the trust that accompanies this perceived positioning and the influence of prosociality are scrutinized as well. This study investigates the links between perceived relational value, trust and

prosociality. This will reveal unique insights into the different (perceived) positioning of the platforms in combination with trust and prosociality. This study will contribute to existing literature by answering the following research question:

What platform perceptions are most attractive in the sharing economy and do trust and prosociality influence this?

This study addresses the inconsistencies of the perceived attractiveness of platforms in combination with trust and prosociality in the sharing economy. First a general overview of the sharing economy is given. Next, the main motivators behind why people participate in the sharing economy and the relational models that go with it are explained. Trust and

prosociality are also taken into account. Conclusions are drawn about the perceived relational models in combination with trust and prosociality in the sharing economy. Finally,

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2. Literature Review 2.1 The Sharing Economy

Sharing platforms are used in different ways, namely for ‘recirculation of goods’, ‘increased utilization of durable assets’, ‘exchange of services’, and ‘sharing of productive assets’ (Schor, 2014: 2). The sharing economy, in other words, collaborative consumption can be defined as the “peer-to-peer-based activity of obtaining, giving, or sharing the access to goods and services, coordinated through community-based online services” (Hamari et al., 2015: 1). The origins of the sharing economy are mainly rooted in non-profit initiatives; think of companies like Freecycle and Couchsurfing, where using and borrowing each other's stuff and houses was done free of charge and based on ‘good faith’ (Belk, 2014b; Codagnone & Martens, 2016). This idea has grown into big businesses such as Uber and Airbnb, who are taking a small portion of the sharing fee; by doing this these companies are turning

community-based sharing into economic self-interest (Codagnone & Martens, 2016). However, with the exception of Uber and Airbnb, lots of platforms are finding it difficult to grow (Teece, 2010).

The sharing economy has continued to grow in recent years; nowadays the concept of sharing has been transformed into a profitable business model (Sach, 2015). Collaborative consumption is not a niche trend anymore. The company PricewaterhouseCoopers expects the sharing economy to grow to a $335 billion dollar market in 2025; from a $15 dollar market in 2015 (PricewaterhouseCoopers, 2015). The disruptive possibility of the sharing economy can be illustrated by companies like Airbnb, the US-based peer-to-peer

accommodation platform. Airbnb is a real threat to hotels all around the world. Airbnb’s market value nowadays is around $2.5 billion (European Union, 2013), however lots of sharing economy companies are still starting out (Belk, 2014b). Lots of sharing platforms are facing difficulties growing and are looking for ways to attract potential users. For this, they

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need to use a business model that is attractive to users and profitable for themselves (Teece, 2010).

However, as mentioned before because of its wide applicability, the potential of online peer-to-peer businesses is massive (European Union, 2013). The sharing economy is considered to be a ‘mega-trend’ (Hamari et al., 2015), but the actual number of users is quite low. Therefore it is important for sharing economy businesses to understand what makes sharing platforms attractive and when and why people actually engage in sharing economy activities.

Nowadays, there is the strong belief that people are out for utilitarian value when it comes to participating in the sharing economy (Lamberton & Rose, 2012). Much research has shown that the desire to participate accompanies utilitarian/economic benefits. The prospect should be financially interesting and convenient, economic motivations in participation are considered to be dominant (Lamberton & Rose, 2012; Bardhi & Eckhardt, 2012; Eckhardt & Bardhi, 2015). Belotti et al., (2015) have replicated the study of Bardhi and Eckhardt (2012) and also found that economic motivations are dominant in participation. Financial crisis and the rise of the sharing economy are often linked; when people face economic difficulties, they rethink their consumption pattern in a more economical way (Gansky, 2010). Even

BlaBlacar, which started as a ridesharing service with social elements now meets clients with the slogan “pay the lowest price for your ride” (www.blablacar.nl). Sharing economy

platforms are trying to frame their sharing economy businesses in ways that allow customers to gain utilitarian value. However this does not seem to be the only motivator or even the most important one, if we take the losses suffered by Freecycle and Couchsurfing into account. Habibi et al., (2016a; 2016b) have stated that besides utilitarian benefits, other benefits and even dualistic motivators should be taken into account. A deeper understanding of this topic is required because most research focuses on business to consumer platforms that

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actually has little to do with peer to peer sharing (Hamari et al., 2015), as peer to peer sharing is the case in the sharing economy.

2.2 Motivations to participate in the sharing economy

It could be stated that growing concerns about climate change, a desire for social belonging and economic reasons have made the ‘sharing economy’/’collaborative consumption’to what it is nowadays (Botsman & Rogers, 2010; Albinsson & Perrera, 2012; Eckhardt & Bardhi, 2015). It seems that the few sharing economy businesses that are doing well now, benefitted from the economic collapse that began in 2008, when consumers lost their homes, cars and investments and became more price sensitive (Belk, 2014b). However, are these economic reasons the actual reasons that people started participating in the sharing economy? Cost savings seems to be an important motivator in the past literature (Mohlmann, 2015). Belk (2010) assumes that economic motivations in sharing out seem to be central; people in economic needs do more easily rent-out their stuff to earn money with it. Besides, goods can be accessed at a lower cost, taken Zipcar as an example (Lamberton & Rose, 2012). However it could be argued that this is not the main motivator when participating in collaborative consumption. Conclusions are being drawn from what Belk (2014a) calls ‘pseudo-sharing practices’ (practices dissembled as sharing) that has little to do with peer-to peer sharing. These conclusions are based on “sharing platforms” that don’t really meet a more stringent definition of sharing namely that sharing should be between two consumers, temporary and exploit underutilized resources (e.g. Frenken & Schor, 2017).

Motivations are very different when we look into contexts that meet a more stringent definition of sharing (e.g Frenken & Schor, 2017). When you share with an anonymous other person this makes the act of sharing much more personal than when we rent from an

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research asserts that ‘convenience’ and ‘price’ concerns which may indeed be leading in a B2C context (Belk, 2010; 2014a; 2014b) are not driving factors for intentions to participate in P2P contexts. Taken Couchsurfing as an example, Couchsurfing got big because of the highly personal, community-driven feeling that could be derived from their service (Andriotis & Agiomirgianakis, 2014).

Botsman and Rogers (2011) have suggested that social cues are important when it comes to participating, as the possibility of becoming ‘friends’ is an important stimulant. Besides, social cues make sharing norms and values possible as well, which gives people a secure feeling when sharing their belongings. Habibi et al., (2016a) found that in sharing contexts, people are seriously willing to socialize and that people derive value through social interactions. Interestingly, practical evidence indeed suggests that social value is an important ‘trigger’ when it comes to participating in sharing economy services because peer-to-peer sharing creates feelings of social bonding, it even proposes values and norms that people will not act out of self-interest (Belk, 2010). This is something that should be taken into account and be scrutinized.

2.3 Relational models

When participants frame sharing more as an experience and not purely as a transaction, the perception of the relational models Communal Sharing (CS) and Equality Matching (EM) are predominant. However, if participants think other users are mainly on the platform to make profit, then their relationship with other users is mainly characterized and perceived as Market Pricing (MP) (Bridoux & Stoelhorst, 2016). It is important for sharing platforms to manipulate their business models based on the relational models, because specific choices in their business models shape mental representations. When it comes to the various relational models, specific characteristics for each relational model seems to be dominant. In CS

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common interest/gains and community are the most important, value is derived out of the community; in EM, reciprocity and balanced interest/gains are the most important and everything needs to be in balance; and in MP self-interest and individual gains are the most important (Bridoux & Stoelhorst, 2016).

An example of a change in relational models and how this affect sharing intentions can be found in the case study of Molz (2013). This study shows that people mainly participate in a platform like Couchsurfing because they like to engage in ‘caring’ and ‘meaningful’ relationships with others. Recently, Couchsurfing changed its business model from a sharing –for-free business model to a monetized business model and by doing this they lost lots of its loyal customers, as those customers felt the company had ‘sold out’ (Lunden, 2013; Belk, 2014b; Mettavant, 2014).

Fiske’s relational theory is used for framing sharing platforms, because sharing platforms differentiate themselves from normal businesses by having sharing options, which allows interaction with peers (e.g. Hamari et al., 2015). Fiske (1991;1992) has used four relational models to describe how social relationships are perceived and coordinated. Out of those four models, three models are relevant when classifying social relationships with peers in sharing economy contexts; Communal Sharing (CS), Equality Matching (EM) and Market Pricing (MP).

First, CS is based on generalized reciprocity and the relation of unity; a collective identity. Kindness and likability are involved in CS. “CS relations often think of themselves as sharing some common substance (e.g. ‘blood’), and hence think that it is naturally kind and altruistic to be kind to people of their own kind” (Fiske, 1992: 691). CS could be

described as a sharing-for-free model. People participate in this kind of sharing behavior out of personal enjoyment and a desire to help others. People in CS relationships perceive those others as their ‘aggregate extended self’ (Belk, 2014a). An example of an extremely personal,

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communal driven platform can be found in Couchsurfing. Sharing on Couchsurfing can be seen as a communal act as individuals do not even keep track on their sharing activities, neither do they expect something in return (Belk, 2010). Individuals mainly participate in Couchsurfing as this leads to meeting new people and learning from other cultures (Habibi et al., 2016).

Second, EM represents an even balance model. What is important here is one-for-one correspondence (Fiske, 1992). Think of the tit-for-tat; or if “you scratch my back, I scratch yours” relation. In this model, there is an even share of distributions. “People in an EM relationship often mark their relationship with very concrete operations of balancing, comparing or counting-out items in one-for-one correspondence” (Fiske, 1992: 691). EM relationships in sharing behavior can be described as equal reciprocity and people looking for ‘higher’ connections (Chesky, 2014). This could be linked to Airbnb, as Airbnb contains renting with personal interactions. Hosts go out of their way and guests are expected to treat someone’s house as if it were a friends’ house (Habibi et al., 2016). De factor norms of joint possessions (e.g. Belk, 2010) to which people adhere even though they have ample

opportunities to freeride is of importance here.

Last, MP is the most distant relationship out of these three relational models. You will only engage in something when it is in your self-interest. Money is the prototypical

norm/medium of MP relationships. “People in a MP relationship usually reduce all the relevant features and components under consideration to a single value or utility metric that allows the comparison of many qualitative and quantitative diverse factors” (Fiske, 1992: 692). In MP relationships, self-interest is expected and accepted behavior (Fiske, 1991). MP relationships can be defined as renting and lending without personal interaction and

cooperation. Zipcar can be taken as an example when it comes to MP relationships, as Zipcar is a profit-oriented car sharing service that is beneficial for shareholders and not for users.

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Besides, self-interest is the main motivation for people to participate in Zipcar (Gorenflo, 2012).

Each of the different models involves distinct relational norms; this in turn leads to different perceptions and to different actions and responses in relationships (Bowles & Polonia-Reyes, 2012). Business models of sharing platforms are typically expected to frame the type of relationships people have with their peers. The type of business model of the sharing economy can be one of the three relational types described above. By adapting a certain positioning, a specific type of relationship can be triggered and perceived by the individual. Based on a specific business model, participants’ frame their relationship with others on a platform. These different relational values trigger different subjective responses of the peer-to-peer based relationship (Bowles & Polonia-Reyes, 2012).

While it is easy to see how relational models can trigger different norms and expected behavior, less is known about how marketing can trigger different models. According to Bridoux and Stoelhorst (2016) CS can be triggered by insisting on a common identification and by highlighting words like ‘we’ and ‘us’, as this will meet individuals’ needs to belong to a collective and to derive communal gains. If we take Couchsurfing as an example, they position themselves as a platform with CS cues, by highlighting their global community: “Couchsurfing connects travelers with a global network of people willing to share in profound and meaningful ways” (www.couchsurfing.com).

Further, EM relationships can be fostered by marking reciprocity and equality among participants, by for example highlighting equalities in decisions and equalities in the input they give and the output they derive. It is also important to accentuate the sensitivity of communal obligations. By doing this, the need of an balanced relationship (equal reciprocity) and equal gains are highlighted. Airbnb can be taken as an example as they position

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by monetizing their extra space, and by doing this they help the community out (www.airbnb.com).

However, MP could be provoked by minimalizing social cues, featuring personal gains and featuring monetary incentives. By doing this, individuals’ desire for gaining economic self-interest - which is solely based on individual gains - will be fulfilled. The Zipcar platform can be taken as an example, as they position their platform with MP-cues. Zipcar focuses on personal and individual gains by highlighting sentences like “simply reserve cars by the hour or day, all for one low rate” (www.zipcar.com).

When looking at the relational models and participation in the sharing economy, it is important to remember that participants almost always deal with strangers when participating in this economy. They mainly interpret other peers by the value proposition / business model of the platform (Gorenflo, 2012). Therefore, it is expected that sharing platforms that will be perceived as CS or EM will be more attractive to participants than platforms that will be perceived as MP. This expectation is based on the fact that the relational value retrieved from CS or EM relationships is usually higher than the relational value derived from MP

relationships (Bridoux & Stoelhorst, 2016). MP relationships in collaborative consumption can even be defined as a renting/lending platform without personal interactions. However CS and EM relationships both consist of personal interactions and being part of a collective, which means that relationships are perceived as interpersonal.

It has been argued that individuals’ sharing intentions in the sharing economy can be seen as an intention to contribute to joint value creations, as the value is created by multiple individuals and this value creation is highly interdependent (Bridoux & Stoelhorst, 2016). It is expected that perceptions of CS and perceptions of EM lead to higher levels of sharing intentions than perceptions of MP. This is because individuals that identify themselves with a collective (CS) or who care about the welfare of others (EM) will be more likely to partake in

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actions that helps the collective (e.g. Dukerich, Golden & Shortell, 2002) than individuals who are mainly in it for transactional relationships (MP) (Brickson, 2007).

2.4 Trust and relational models

There have been some disputes about why people participate in the sharing economy, and if these activities generate social capital and generalized trust (Codagnone & Martens, 2016). Trust is considered something important when it comes to online sharing platforms; it is an important mechanism for people to participate, and keep participating, in the sharing economy (Mohlmann, 2016).

Trust is of essence because the sharing economy can also be assumed to have a dark side. This dark side can be illustrated by the fact that individuals might not look after ‘your’ possessions as you take care of it; it is the risk that others do not treat your stuff with care (Brunning, 2015). In sharing environments, this risk of others not treating your possessions how you would like them to will never vanish. However trust can be of importance when it comes to reducing this risk (Gefen, 2002; Ufford, 2015). Trust seems to be an important mechanism, as it is a crucial factor in relations and transactions where uncertainty and risk plays a role (e.g. the “dark side of lending and sharing”). This is often the case in online markets and sharing platforms (e.g. Gefen, 2002; Luo, 2002). It is absolutely certain that trust is essential to ensure the growth of the sharing economy (Vaughan, 2017). “Trust will remain the hot topic in the sharing economy” (Vaughan, 2017: 1). Trust can be defined as “the willingness of a party to be vulnerable to the actions of another party based on the

expectation that the other will perform a particular action important to the trustor, irrespective of the ability to monitor or control that other party” (Mayer, Davis & Schoorman, 1995: 712).

Interestingly, trust seems to regulate and determine the behavior of consumers (Papadopoulou et al., 2001). Trust is of major importance when conducting online

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transactions (Pavlou & Gefen, 2004). This is due to the absence of human interaction and the electronic nature of the service (Gefen, 2002). Consumers are hesitant when making

purchases in an online environment unless they trust the seller. Trust also lowers the effect of perceived risk when conducting an online transaction (Gefen, 2002). Even though individuals like the idea of the sharing economy, trust seems to be the main barrier/inhibitor when it comes to participation in the sharing economy. This can be explained by the fact that the sharing economy “allows someone to take a ride from a stranger or rent a room in a house from someone they’ve never met.” (Ufford, 2015: 1). This lack of trust seems to be one of the biggest obstacles when it comes to participation in the sharing economy.

Trust is of great essence when it comes to long-term relationships, and it is the key element of relational commitment (e.g. Sirdeshmukh, Singh & Sabol, 2002; Stofberg, 2017). Past research proves that relational value is a strong predictor of trust (Stofberg, 2017) and in turn, trust is a determinant of online sharing behavior (Martin, Guttierez & Camarero, 2004; Mohlmann, 2015). This is why trust is expected to be a key mediator in explaining the impact of perceiving relationships as CS, EM and MP on the dependent variable the intention to participate in the sharing economy. This thesis proposes that utilitarian motivations are counterproductive to the inducement of trust because these motivations send out the message that people are doing something out of self-interested reasons, which creates an interpersonal reserve and the idea that people will only act in their own interests and hence misbehave (Schaeffers et al., 2016).

First, CS is defined as the self-interest of the group before one’s own self-interest (Fiske, 1991). When sharing is viewed as a communal step, individuals generally feel a deep connection with each other. When individuals feel that they are part of a community, they do not act out of self-interest but in favor of the interest of the group. This is exactly why trust-levels are expected to be high (Belk, 2010). In a CS relationship individuals have the feeling

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that they belong to a collective, and so it is trusted that others that belong to this collective will more or less act in the same ‘selfless way’ because their own identity is connected to that of the collective (e.g. Bridoux & Stoelhorst, 2016). Trust levels are expected to be high in perceived CS relationships.

Second, EM fulfills the need for equality. This is regulated by norms of honesty and balanced/equal reciprocity (Fiske, 1991). In this relational model, people expect to be treated with the same respect they show others. As stated earlier EM relationships trigger a ‘tit-for-tat reciprocity’; people in such relationships expect others to share the same cooperative vision (Bridoux & Stoelhorst, 2016). In an EM relationship people feel they belong to a community which is based on interdependency (Sheppard & Sherman, 1998); individuals like to contribute to joint value creation (Belk, 2010). Therefore, in an EM relationship people expect and trust others to treat their belongings with respect. Because balanced/equal

reciprocity is a relationship that is based on an equal mutual exchange and interdependency, individuals look after each other’s interest instead of their own. This means that individuals expect and trust others would to act in exactly the same way; this is where trust comes in. In EM relationships, there is a connection with others on a platform; however, this connection is not as deep as in CS relationships. Because of this, trust levels are expected to be high – although maybe not as high as in perceived CS – in perceived EM relationships.

In MP relationships people “reduce all relevant features and components of the relationship into a single value of utility metric” (Giessner & Van Quaquebeke, 2010: 727). This makes acting out of self-interest a relevant and accepted behavior. In MP relationships trust is reduced to a very low level, because relational cues are reduced to a very low level as well. The expected and behavioral group norm is to look after and maximize your own self-interest (Bridoux & Stoelhorst, 2016). People place less value on social and relational aspects as convenience and making money is what is important to them. This means that in MP

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relationships individuals place less value on taking care of the shared resource; there are no norms of joint possessions (Belk, 2010). If people could get away with it, they would probably not treat a shared car with respect. Take Zipcar as an example. For Zipcar there is an interpersonal reserve, individuals don’t think about the interests of the other party and this makes freeriding acceptable and the norm: “Don’t be gentle, it’s a rental” (Bardhi &

Eckhardt, 2012; Schaefers et al., 2016). This is fatal when it comes to the sharing economy. In perceived MP relationships, acting out of self-interest is appropriate and expected

behavior. This is why trust levels are expected to be low. Further, when it comes to intentions to share, these are also supposed to be low in perceived MP relationships.

2.5 Prosociality

The past literature has indicated that individuals “differ in a systematic, trait-like manner in their tendencies to employ the models in making sense of their interpersonal worlds” (Haslam, 2004: 44). It has been suggested that individuals are inclined to use a specific relational model as a part of their social behavior. Individuals who are high in prosociality or individuals who easily engage in prosocial behavior2 derive positive feelings from helping others (Anik, Aknin, Norton & Dunn, 2009). Besides, people who are prosocial will be more sensitive to cues that other people also care about others’ interests and wont freeride on their good intentions. As such they will be more vulnerable to platforms that send out cues that others’ care about and act in accordance to the interest of the group, rather than their own (Bridoux, Stofberg & Hartog, 2016). It is expected that individuals who are high in

prosociality are inclined to have a preference for using or perceiving relational models with social cues (CS and EM) more than that they would perceive the relational model as MP, as this model reduces all social cues.

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Prosociality or prosocial behavior can be distinguished from other forms of behavior because it is a response or action based on the interpretation of the need of another individual (Dunfield et al., 2011). “Prosocial behavior generally has been defined as voluntary,

intentional behavior that results in benefits for another; the motive is unspecified and may be positive, negative or both” (Eisenber & Miller, 1987: 92). When a person is considered to be prosocial, he or she aims to help others to become informed of a ‘group deal’ opportunity they confront. Besides making them aware of this opportunity, he or she wants to experience the benefits of this certain deal together even if this person doesn’t know the other person personally (Chen, Phang & Zhang, 2017).

In reality, some people are more willing than others to conduct behavior that is useful for others: prosocial behavior differs across people. Traits, values, and self-efficacy beliefs are all strong predictors of prosocial behavior (Caprara, et al. 2012). These predictors are valid across time and situations (Caprara et al., 2010). These predictors might partially hamper or devote one’s intention to participate in the sharing economy (Piscicelli, et al. 2015). Additionally, psychologists suggest that parts of the Big Five personality traits account for major differences in personality and this could be seen as a major determinant of

prosocial behavior (Graziano, Bruce, Sheese, & Tobin, 2007). It can be stated that

prosociality differs because of personality. As mentioned above, different findings suggest that people differ in engaging in activities that results in others’ wellbeing based on

individual differences in prosociality (Caprara et al., 2010). This can be linked to the sharing economy.

3. Theoretical framework and hypothesis

This thesis shows how sharing economy platforms can position their platform and trigger a specific relational model so that one of the three relational model is perceived and peers can

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frame their relationship with other peers in terms of CS, EM or MP. Bridoux and Stoelhorst (2016) hypothesize that platforms where communal gains are highlighted will be perceived as CS; platforms where equal gains are highlighted will be perceived as EM and platforms where individual gains are highlighted will be perceived as MP. No research to date looked into how different positioning results in different frames of mind and this study firstly addresses this gap. Secondly, this study argues that the relational models are paramount to overcome trust barriers and increase intentions to participate. Lastly this will result in a self-selection effect in which people who are more predisposed to share will fell more attraction. The conceptual model of this studies can be found in figure 1.

3.1 Conceptual Model

Figure 1. Conceptual model

3.2 (Perceived) relational models

Different cues are used to trigger the relational models CS, EM and MP. However individuals are also capable of framing relationships themselves (Fiske, 1991). In CS, common interest

Perceptions of Communal Sharing Sharing Intention Trust Prosociality Perceptions of Equality Matching Perceptions of Market Pricing Platform Positioning: Communal gains (CS) Platform Positioning: Equal gains (EM)

Platform Positioning: Individual gains (MP)

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and community is central; when it comes to EM reciprocity is the most important and everything needs to be in balance; however, when it comes to MP self-interest is the key (Bridoux & Stoelhorst, 2016). As peer to peer platforms facilitate temporary transactions between strangers the (non)social cues a platform sends out are paramount to signal

relationships. These (non)social cues affect how (expected) participants perceive the peer-to-peer relationship on sharing platforms and this helps to explain that some platforms may be more attractive than others (Stofberg, 2017).

Not much is known about how marketing can trigger different relational models and when participants perceive cues as a specific relational model. Based on the research of Bridoux and Stoelhorst (2016) we believe that the relational model CS could be triggered by using cues like ‘we’ or ‘us’ and by emphasizing the participants’ commonalities. This would make the participant feel part of a community. By doing this communal identity will be highlighted and personal identity will be pushed to the background, in turn CS would be perceived. Additionally, EM relational models can be triggered by highlighting cues like ‘partners’, focusing on equal reciprocity and balanced interactions. By doing this, participants derive an equal relationship out of the platform, and EM relationships are perceived. Finally, MP relational models can be triggered by focusing on monetary incentives and reducing social cues. As those relationships are coordinated by prices and the self is expressed at the individual level; individuals are motivated by individual gains and pay-offs. This would make participants perceive the platform as MP as they can easily place self-interest above group interest. Based on the above-mentioned relational models and the assumption that individuals frame relationships themselves, the following hypotheses are construed:

H1a: When sharing platforms use terms like ‘we’ or ‘us’ and cues of a community are present, CS perceptions are perceived.

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H1b: When sharing platforms use terms like ‘partners’ or they mark reciprocity and equality among the participants, EM perceptions are perceived

H1c: When sharing platforms use only a transactional approach with individual monetary incentives and personal cues are minimized, MP perceptions are perceived

3.3 Perceived relational models and sharing intentions

It is argued that individuals’ sharing intentions in the sharing economy indicates an intention to contribute to joint value creation, as the sharing economy is highly interdependent

(Bridoux & Stoelhorst, 2016). CS and EM perceptions are expected to lead to a higher level of sharing intentions than MP perceptions. This is because individuals that identify

themselves with a collective (CS) or who care about the welfare of others (EM) will be more likely to partake in actions that helps the collective (e.g. Dukerich, Golden & Shortell, 2002). In contrast an MP model sends out a signal that individuals are mainly in it for themselves, as social cues and personal interactions are minimized, which makes freeriding a more

appropriate behavior and people intend to participate less as individuals’ are in it for their own profit. Furthermore, as individuals are mainly focused on personal gains, it is expected that perceived MP perceptions lead to lower sharing intentions than perceived CS or EM perceptions. As individuals who perceive the MP relational model, exclusively focus on individual self-gain and not on communal or equal gains, which is the case when CS or EM is perceived (Brickson, 2007). Brickson (2007: 878) states that perceived MP relationships make individuals “perceive events to be under their own control, rather than controlled by others or by external circumstances”. This is why the following hypotheses are constructed:

H2a: Perceived CS perceptions leads to a higher sharing intention than perceived MP perceptions

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H2b: Perceived EM perceptions leads to a higher sharing intention than perceived MP perceptions

3.4 Trust and sharing intentions

An important mechanism that explains a higher likelihood to participate when CS and EM perceptions are primed is trust (Bardhi & Echkhardt, 2012). When participating in the sharing economy, individuals share their own valuable possessions with others. This carries risk; the risk that others might not handle one’s goods with the same amount of care (e.g. Schaeffers et al., 2017). To overcome this ‘dark side of sharing’ and other barriers that accompany

participation in the sharing economy, trust is needed, as trust reduces the uncertainties and risk perceptions that go with online sharing behavior (e.g. Gefen, 2002; Luo, 2002; Pavlou & Geven, 2004; Mohlmann, 2015;Ufford, 2015).

It could be indicated that trust could facilitate participation in the sharing economy (Tussyadiah, 2015) as trust influences future sharing intentions through perceived relational values (Stofberg, 2017). This is due to the fact that EM and CS relationships trigger different norms and values than MP relationships, and this in turn influences sharing intentions. In CS and EM perceived relationships, sharing is expected to be a communal act or an

interdependent behavior that is guided by balanced reciprocity. This goes together with high trust levels, as in both cases the other party is expected to act in the same way. However for MP relationships, it is all about maximizing individual values irrespective of the other party. This goes hand in hand with low trust levels as retrieving individual gains is the norm and expected behavior (Sheppard & Sherman, 1998). It is of necessity to understand how the relational models establish positive trust perceptions and if this increases sharing intentions (e.g. Mohlmann, 2015; Tussyadiah, 2015). In a step to investigate the relationship between

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trust, the perceived relational models and sharing intentions in the sharing economy, the following hypothesis is constructed:

H3: Customers’ trust increases customers’ sharing intentions

Building on the evidence found in the past literature, CS and EM perceptions of the platform are expected to positively influence people’s participation in the sharing economy through trust. This is expected for CS because individuals who frame their relationship as CS connect their own identity with that of the collective, and by doing, they trust others to act in the same ‘selfless’ way (e.g. Bridoux & Stoelhorst, 2016). This would mean that the

relationship between perceptions of CS and sharing intentions will be positively mediated by trust, as people trust their goods to be in ‘good’ hands of the community they belong to. In CS relationships trust levels are expected to be high as individuals trust the community they belong to. For perceptions of EM, trust levels are expected to be high as individuals engage in a balanced relationship. This relationship is based on an equal exchange and behavior is guided by norms of balanced reciprocity. Therefore, people trust others to be mindful of their stuff, as the relationship is interdependent and this goes together with high trust levels. Furthermore in EM relationships people trust to be treated with the same respect they treat others (Stofberg, 2017). Thus it can be assumed that the relationship between perceived EM and sharing intentions is positively mediated by trust. Based on the above-mentioned

arguments the following hypotheses are constructed:

H4a: Trust positively mediates the relationship between perceived CS perceptions and sharing intentions

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H4b: Trust positively mediates the relationship between perceived EM perceptions and sharing intentions

On the other hand, is expected that the perception of MP relationships goes together with low trust levels and low sharing intentions; it is also expected that the relationship between perceived MP and sharing intentions is negatively mediated by trust. In MP relationships people place less value on taking care of the possessions of others, this goes together with low trust levels, as people mainly act out of self-interest and only think about maximizing their own value irrespective of the other party. Individuals do not care about the value that could be derived from the collective. In perceived MP relationships there are no norms of joint possessions. Individuals do not trust others to bring back their possessions in the same condition they received it, as this is the norm (Belk, 2010; Habibi et al., 2016). This means that perceived MP relationships, leads to low trust levels and low sharing intentions. Perceived MP relationships can even be assumed to be dangerous for the sharing economy. This is why the following hypothesis is constructed:

H5: Trust negatively mediates the relationship between perceived MP perceptions and sharing intentions

3.5 Prosociality and sharing intentions

Participation in the sharing economy can be seen as a form of prosocial behavior since the output is mainly valuable or favorable for others (Hwang & Griffiths, 2017). People who are high in prosociality derive positive feelings from helping others. It even seems that people high in prosociality look to enlarge payoffs for others, regardless of their own outcomes (Fehr & Schmidt, 2006). When a person is attempting to behave in a more prosocial way, this

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means that this person cares more about the welfare of ohters than a person who does not behave in a prosocial way. Furthermore, individuals that score high on prosociality would be more vulnerable to a perceived CS and EM positioning than a perceived MP positioning as individuals high in prosociality are sensitive to cues that other people also care about the interest of others (Bridoux, Stofberg & Hartog, 2016).

Perceptions of CS and EM go hand in hand with an individual framing relationships as balanced and equal. Besides, perceived social cues tend to be high in perceptions of CS and EM. Since individuals high in prosociality tend to derive value from helping others, it is expected that sharing intentions are higher when perceptions of CS and EM are high.

However, people who score high on prosociality are expected to have a lower intention to share when perceptions of MP are high, as individuals high in prosociality do not derive value from individual rewards. Generally, perceived MP goes together with personal gains, and this is not what individuals high in prosociality are looking for (Dawling & Falk, 2011). This is why the following hypotheses are constructed.

H6: People who score high on prosociality traits have a higher intention to share when perceptions of a)EM and b) CS are high than when they are low

H7: people who score high on prosociality traits have a lower intention to share when perceptions of MP are high than when they are low

4. Methodology

To test whether a) a more social positioning results into higher sharing intentions and b) this translates into higher sharing perceptions and c) the mediating role of trust and moderating role of personal dispositions herein, this research set up a vignette experiment embedded in a survey (see appendix 2 and 3). This research was conducted by using a factorial survey.

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Factorial surveys deliver data at the individual level and at the vignette level; both of the data need to be taken into account (Aitking & Longford, 1986). In a vignette experiment

respondents evoke judgements about a certain situation after seeing a short description about that situation (Rooks, Raub, Selten & Tazelaar, 2000). To increase external validity this research worked with an actual platform ‘parkflyrent’ rather than a hypothetical one. The use of parkflyrent and the special manipulation of the vignette leads to realistic scenarios that were represented to the respondents (Atzmuller & Steiner, 2010). The current positioning of parkflyrent is very functionally oriented as their slogan is “park for free at the airport and rent out your car fully secured, without any hassle” (www.parkflyrent.nl). ParkFlyRent can be described as a car sharing service near Schiphol Airport that enables a car rental service by using parked cars of individuals who indicated that their cars could be used for sharing with others while they were on holidays.

This research set out to investigate whether a different positioning of ParkFlyRent would alter potential participants’ expectations of group members’ participation and ultimately whether this would make them more likely to join. The manipulation of the

relational models (CS, EM and MP) and the depended variable sharing intention resulted in a simple between subjects experimental design with 3 treatments.

4.1 Stimuli development (pre-test)

To conduct this study, the platform of ParkFlyRent had to be transformed in three different versions of the platform (either CS, EM or MP). The platform positioning’s were different in terms of their slogan and the reason why individuals would join the platform. Positioning the platform as CS (communal gains) was mainly focused on communal gains of the individual, so that individuals would derive value from the collective (Bridoux & Stoelhorst, 2016). For CS cues like “sharing your car with the nicest holiday people” and “social and sustainable car

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sharing: we use other cars that otherwise would have stand still. Make someone else happy with your car” were dominant (see appendix 3; section 9.1). This was done to highlight communal identity. Positioning the platform as EM (equal gains) was focused on equal gains of the individual, cues of balanced gains were highlighted so that individuals would derive value from an equal relationship (Bridoux & Stoelhorst, 2016). For EM cues like “together we give each-other a better holiday” and “no parking expenses for you, another person happy with your car” were dominant (see appendix 3; section 9.2). These cues mainly focus on equal gains. Moreover, the platform positioning as MP (individual gains) was mainly emphasized on self and individual gains, as individuals in MP relationships would derive value from individual rewards (Bridoux & Stoelhorst, 2016). In this condition cues like “park your car for free, with no extra hassle” and “we make sure you will be quickly at your

departure gate at Schiphol to have a comfortable start of your holidays” were dominant (see appendix 3; section 9.3). These cues were dominant to highlight individual gains.

The pre-test was conducted by using online questionnaires. The goal of the pre-test was to check if the respondents perceived the different vignettes/interfaces of ParkFlyRent as CS, EM or MP. The pre-test was conducted to check if the manipulation for the different conditions (CS, EM and MP) of the independent variable would work. The pre-test sample consisted of 30 respondents who were mainly reached through social and personal networks. The pre-test was online for a week in mid-May. All participants were Dutch-speaking.

Participants in the pre-test saw the three different vignettes, one for CS, one for MP and one for EM. All of them got to see the three different conditions. After every vignette the respondents had to answer 3 questions to review the condition they were in. To check for CS this question was: “This type of platform is one on which transactions are characterized by a high degree of generosity. People have the feeling of belonging to a group and have a lot in common”. To check for EM this question was: “This type of platform is one that manages

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transactions based on equality and reciprocity. People on this platform try to maintain a healthy balance in terms of the benefits everyone gets on the platform (money or stuff)”. To check for MP this question was: “This type of platform is one that manages transactions based on individual utility, where people believe they are entitled to a good return on their investment (money or stuff). This is a bit like a business relationship”. These items were all measured on a 7-point Likert scale (1 = not at all true, 7 = very true). Respondents could also leave comments.

The results of the pre-test are presented in table 1. The results show that the

respondents were able to recognize the differences between the conditions CS (M = 4.83, SD = 1.03), EM (M = 5.36, SD =1.03) and MP (M = 5.56, SD = 0.88). However, table 1 also shows that all of the different conditions scored pretty high on perceptions of MP, When looked at the comments it shows that participants in EM and CS conditions also recognized the financial benefits for the car-owners. Importantly the CS condition scores also high on the perception of EM, this makes sense because of the monetary exchange that is conducted in the CS condition, which triggers EM perceptions.

In conclusion, the scores of the pre-test show us that participations indeed recognized the different conditions. So the different manipulations of the ParkFlyRent vignettes can be used in this research.

Table 1. Results of the pre-test

Condition Communal Sharing perception Equality Matching perception Market Pricing perception N M SD M SD M SD CS priming 10 4.83 1.03 5.42 1.08 4.92 1.08 EM priming 11 4.45 1.21 5.36 1.03 4.72 1.01

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Note. CS = Communal Sharing, EM = Equality Matching, MP = Market Pricing

4.2 Research design

Three groups were created (CS, EM and MP) due to the categorical variable condition that has 3 levels. Participants were randomly allocated to one of the three conditions, to make this research more reliable. In table 2 the allocation of the participants over the three conditions is provided.

Table 2. Allocation of participants over three conditions

Condition N Percentage

CS Positioning 95 31.5%

EM positioning 107 35.4%

MP positioning 100 33.1%

Total 302 100%

In this study, the vignette aroused individuals to think of a situation that they were going on holidays and they flew from Schiphol airport; they were asked to imagine they were going to Schiphol airport by car. While looking for parking sports, they came across the platform ParkFlyRent as a parking option.

The survey that went with the vignettes facilitated to measure the perceptions of the platform positioning on sharing intentions, trust, prosociality and control variables. Perceived CS, EM and MP are measured on continuous scales. The variables trust, prosociality and sharing intentions are also measured on continuous scales. The scales will be explained in the measurement of variables section.

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4.3 Measurement of variables

This section will discuss the different variables that are used in this research. There will be explained why these variables are measured and which scales are used. Existing measurement scales were borrowed (and adapted) to ensure reliability and internal validity of this research. Besides, an overview of the Cronbach alpha score of each construct will be given in the result section and can therefore be found in table 6.

4.3.1 The independent variable: Perceived relational models (CS, EM and MP) The different conditions of the relational models were classified based on the pre-test.

However to find out how these different relational models were perceived by the respondents the perception of the relational model was measured (either CS, EM or MP). The 3 scales all consisted of 6 items that were measured on a 7-point Likert scale (1 = not at all true, 7 = very true). The questions were modified and adapted from Haslam & Fiske (1999). The

modification was done to apply the questions to the context of the sharing economy and to the context of a group. For all of the three perceived relational models representative items are picked: For CS, questions like: “Participants of ParkFlyRent together, form a community: they belong to each-other” were asked. For EM, questions like: “Participants of ParkFlyRent treat each-other equivalent” were asked and for MP, questions like: “Participants of

ParkFlyRent see each-other as business-partners” were asked.

4.3.2 The dependent variable: Sharing intention

Sharing intention was measured to find out how the sharing intention per respondent differed per perceived relational model. Sharing intention was measured on a 4-item 7 point Likert scale (1 = not at all agree, 7 = totally agree). This scale was adapted from White,

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MacDonnell, & Ellard (2012), the scale was fit to the context of ParkFlyRent. Questions like: “I would possibly park my car via ParkFlyRent” were asked.

4.3.3 The mediator: Trust

Trust was the mediating variable in this research and trust was measured to indicate to what extend people need to trust the platform in order to participate in sharing behavior. It was expected that if trust levels were high, respondents sharing intention would increase. Trust was measured on a 6-item 7 point Likert scale (1 = not at all agree, 7 = totally agree), adapted from Pavlou & Geven. (2004). Questions like: “I expect that ParkFlyRent is open and honest with me” were asked.

4.3.4 The moderator: Prosociality

Prosociality was the moderator variable in this research and it was measured to indicate how prosocial respondents would behave generally. This was done since it was assumed that prosocial behavior would increase sharing intentions. Prosociality was measured on a 16-item 5 point Likert scale (1 = not at all agree, 5 = totally agree), adapted from Caprara, Steca, Zelli, & Capanna (2005). Questions like: “I try to be close to and take care of those who are in need” were asked.

4.3.5 Demographic variables

Participants were asked to fill out their gender, age, where they lived (one of the 4 big cities, urban areas, suburban areas or village) and if they owned a car. These demographics were used as other studies have shown that those variables could possibly have an influence on sharing behavior (e.g. Schiel, 2015). It is decided that all results of the study are controlled by

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these four variables, as those demographics seem to influence sharing behavior of cars (Frick, Hauser & Gurtler, 2013; Zipcar, 2014).

4.4 The set-up of the survey

Participants could partake in this research by using an online anonymous link which leaded to the vignette and the questionnaire. This link was distributed via online channels. In first the participants saw a welcoming message and a short introduction. Afterwards they got to see a vignette of ParkFlyRent, this vignette had either CS, EM or MP cues. Which condition the respondents were in, was based on randomization.

In first respondents were asked what their overall impression of the platform was and if they would intend to park their car via ParkFlyRent. Afterwards was asked if they found the vignette they saw believable and wat kind of cues they perceived, this was done to do a manipulation check. Also was asked if the respondents were familiar with or had used ParkFlyRent before. The following questions that were asked were based on the relational models, trust and prosociality in combination with ParkFlyRent.

The last questions consisted of control variables like: gender, age, where they live and car ownership as other studies have shown that those variables influence sharing behavior (Schiel, 2015). When it comes to gender past research shows that women tend to be more socially driven than men (Hellwig et al., 2015). Besides, when it comes to age older people seem to be more motivated by function benefits than younger people are (Bocker & Meelen, 2016). Controlled is for living area since people who live in urban areas are more willing to participate in sharing in general than people who lived in less populated areas (Thebault-Spieker, Terveen & Hecht, 2015). Last but not least for this research, controlled is for car ownership as this research is about a car sharing platform.

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4.5 Sample of the survey

Respondents that did not fill out all the questions were deleted from the sample. The completion rate of the questionnaires was about 66% and only fully filled in questionnaires were taken into account. Eventually 302 respondents participated in our survey (N=302). The survey was online from the 3th of May until the 20th of May. All respondents were Dutch-speaking. The male/female ratio is not equal, 38% of the respondents were male (114) and 62 % of the respondents were female (188). The youngest respondent was 18 years old and the oldest respondent was 75 years old. The average age in our sample was 34 (M = 34, SD = .84). Almost halve of the respondents owned a car (51%, N = 154). If we look at the cities were the respondents live, most of them live in Amsterdam (44.7%, N = 135). For a total overview of the demographic variables of the respondents, see table 3.

Table 3. Frequencies and percentages of demographic variables of all respondents (N = 302)

Variable Level N Percentage (%)

Gender Male 114 38%

Female 188 62%

Educational level High School 21 7%

MBO 16 5.3%

HBO 86 28.5%

WO 175 57.9%

Different 4 1.3%

Car ownership Yes 154 51%

No 148 49%

Living area Rotterdam 5 1.7%

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4.6 Population and procedure

For this research it was important to gather as much respondents with a car. However, it was also important to gather a general public in order to generalize this research. The

questionnaire was distributed via online channels (Facebook and emails). Respondents were gathered through online however they were also gathered at parking lots, to make sure as much respondents were care owners. In either way, they filled out the questionnaire online. To protect reliability and validity, respondents could only fill out the questionnaire once.

The questionnaire was completely anonymous and the data was only used for the purpose of his research. Respondents also didn’t receive an award for completing our

questionnaire. The questionnaire was constructed via qualtrics, so the data was automatically gathered through qualtrics, afterwards the data was exported to SPSS statistics. All of the questions of our survey were professionally translated from English into Dutch. This was done since ParkFlyRent is a Dutch platform.

4.7 Dataset

Since the relational models are categorical variables, dummy variables needed to be created. As this research uses a multi categorical approach with 3 variables; two dummies were created (Field, 2009). For CS and MP dummies were created. Dummy_CS: CS(1) other (0) and Dummy_EM: EM(1) other (0). MP is always used as the baseline in this research.

Amsterdam 135 44.7%

The Hague 8 2.6%

The agglomeration 75 24.8%

Not in agglomeration 35 11.6%

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However to use the variables gender, car ownership and living area as control variables, these also were transformed into dummy variables. Three dummy variables for the demographics were created: DummyFemale: Female(1) Male(0), DummyAmsterdam: Amsterdam(1) other (0) and DummyCar: Yes(1) No(0)

Recoding into different variables was only needed for 2 items of trust. This was done since these items were phrased so that an agreement with the items represents a low level of the construct being measured. Trustplatform4 and Trustplatform5 were recoded into

REC4_Trustplatform and REC5_Trustplatform. These recoded items were used in the trust platform scale.

5. Results

In this chapter the different analysis are presented. First, the descriptive analysis is

elaborated, to check the distribution of the variables of interest. Afterwards the reliability of the scales, the manipulation check and the correlation matrix will be shown. This is a prerequisite for testing the hypothesis and make sure the outcomes of the analysis are valid. At last the hypotheses are tested. To check hypothesis 1 the manipulation check in

combination with the correlation table will be used. To check hypothesis 3, a hierarchical regressions will be conducted; to check hypothesis 2a and 2b a hierarchical multiple

regression will be conducted; to test hypothesis 3 a hierarchical multiple regression was used; to test hypotheses 4a,b and 5 the PROCESS method model 4 was used. Finally, to test

hypotheses 6a and b and hypothesis 7 the PROCESS method model 5 was used.

5.1 Descriptive Statistics

A descriptive statistics analysis was done to check how the variables were distributed, mean and standard deviation are described. Afterwards skewness, kurtosis and normality test were

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