Personality as a predictor of collaborative consumption usage

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Personality as a predictor of Collaborative Consumption

usage.

Final version: 23/06/2017

Student: S.J. Barends 11384670

MSc. In Business Administration – Digital Business track Amsterdam Business School

Supervisor: Mr. J. L. Pletzer PhD Candidate

Jacobs University Bremen, Germany

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Statement of Originality

Statement of originality

This document is written by Samuel Jan Barends 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

This study researches the effect of personality on attitude towards collaborative consumption (CC) and ultimate intention to participate in CC. Much research has been done in the field of both personality and CC separately but individual differences in the study of the drivers of CC have been neglected so far. One of these individual differences is personality. For this study, personality has been divided into the commonly used five dimensions (Openness to experience, Conscientiousness, Extraversion, Agreeableness and Neuroticism). Traits from all five dimensions are compared to important factors of CC, such as trust and collaboration. Data from 335 respondents was collected through a survey and then analysed. The results show that only agreeableness has a significant positive influence on attitude towards CC and intention to participate in CC. Openness to experience had a significant positive influence on attitude towards CC but not on intention to participate in CC. Furthermore, neuroticism was the only personality dimension which was significantly moderated in the relation between personality and intention to participate in CC, mediated by attitude towards CC. This study contributes to current literature because it analyses individual differences in the study of drivers of CC. Furthermore, this study also contributes to managerial implications. Knowing which personalities can predict the usage of CC, can help managers in targeted acquisition.

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Introduction

Data from Google Trends show that the term ‘Sharing Economy’ has increased significantly in popularity over the past three years. Companies like Uber and Airbnb are disrupting traditional industries and completely changing attitudes towards ownership (Bardhi & Eckhardt, 2012). According to Chen (2009), possession is no longer the ultimate desire of consumers. Instead, consumers pool or share services or goods such as cars (Uber, BlaBlaCar) or accommodation (Airbnb). According to PricewaterhouseCoopers (Bothun & Lieberman, 2015), sharing systems comprised a global revenue of roughly US$15 billion per year in 2015, which is believed to grow to US$335 billion by 2025 (Marchi & Parekh, 2015).

These sharing systems are part of a construct called Collaborative Consumption (CC), meaning that people share personal goods or services with other people through a sharing platform, often against a fee. Interestingly, much research has been done about the drivers of sharing economy (Hawlitschek, Teubner, & Gimpel, 2016; Hamari, Sjöklint, & Ukkonen, 2015; Tussyadiah, 2015; Owyang, 2013). People’s motivation to participate in CC could be driven by their perception about improving sustainability and their reputation (Heinrichs, 2013; Tussyadia, 2015). However, individual differences in the study of the drivers of participation have been neglected so far. One of those individual drivers is Personality. To the best of my knowledge, no articles exist about how personality can be a predictor of intention to participate in and attitude to CC. People’s opinion and willingness to share private properties with strangers is possibly dependent on their personality. Personality is most commonly assessed with the Big-Five personality traits, which are Extraversion, Conscientiousness, Openness to experience, Agreeableness and Neuroticism (Goldberg, 1993).

Many models on the acceptance of technology are based on ease of use, complexity and trialability of the technology, which are considered important factors for users to participate in an online platform (Chong, Ooi, & Sohal, 2009). Because CC platforms are facilitated by ICT, Tussyadiah (2015) argues that lack of technology efficacy is the largest deterrent of consumers’

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participation intention in CC. Therefore, lack of technology efficacy could moderate the relationship between personality and attitude towards CC.

Understanding the relationship between personality and intention to participate in CC can pose many advantages. By knowing which people are more likely to participate in CC, corresponding companies can specifically target certain people to increase acquisition rates. But not only companies benefit from CC. Research has shown that CC can also greatly benefit customers through economic, environmental and societal benefits (Hamari, Sjöklint, & Ukkonen, 2015). By, for example, sharing a car, less emission gas, lower gasoline costs and more interaction with others is encouraged.

This has led to the following research question:

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First, insights are given into relevant literature about CC, personality and lack of technology efficacy. These variables will be explained and linked to each other. Second, hypotheses will be formulated. Third, the data and research method will be explained. Fourth, insights into the results gathered from the research will be provided. Some descriptive statistics as well as data analysis of the hypotheses will be framed. And lastly, the discussion and conclusion of the findings will be discussed. The discussion links literature to the results and the conclusion will briefly summarize the complete research.

Collaborative Consumption

Although the concept of CC has been around for a long time (Felson & Spaeth, 1978), the implications and possibilities have evolved significantly over the past years. Advances in information and communication technologies have changed traditional market behaviours by enabling online CC which has been 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, Sjöklint, & Ukkonen, 2015, p. 2047). Owyang (2013) argues in a

market report that there are three market forces which drove Collaborative Economy: Societal, Economical and Technological. Societal market forces include increasing population density, drive for sustainability, desire for community and generational altruism. Economic drivers are monetize excess or idle inventory, increase financial flexibility, access over ownership and influx of venture capital funding. And lastly technology drivers include social networking, mobile devices and platforms, and payment systems.

Many researchers believe CC will be of great impact in the future and will help to solve environmental, economic, and social problems (Belk, 2014; Hamari, Sjöklint, & Ukkonen, 2015; Hawlitschek, Teubner, & Gimpel, 2016).

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This research will focus on the consumers. A difference can be made between providers and consumers of CC (Hawlitschek, Teubner, & Gimpel, 2016). Providers are the people who offer their good or service to be accessed by a consumer. The consumer is the person who gains access to the provider’s good or service. For example with Uber, the driver is the provider of CC and the person who requested a ride, is the consumer. However, a clear distinction has to be made between two exchange categories of CC platforms.

By mapping 254 CC platforms, Hamari et al. (2015) identify two exchange categories: ‘access over ownership’ and ‘transfer of ownership’. Access over ownership is the most common exchange mode and means that users of a CC platform can offer other users to share their goods or services for a limited amount of time. An example of an access over ownership platform is Airbnb where users can offer their accommodation to others when they are away from home themselves. Often these services are offered against a fee. Access over ownership is in line with theories stating that it is no longer a consumers ultimate desire to own goods but consumers are increasingly likely to access goods for a limited amount of time instead of buying them (Bardhi & Eckhardt, 2012). Transfer of ownership is when ownership of a product or service is transferred between one user to the other. This can be done in different ways such as donating, swapping or purchasing. The difference with traditional purchasing is that with CC, purchasing is done through a peer-to-peer platform. This study will focus on access over ownership because it is most commonly used.

Other research has looked into motivations of why people participate in CC. Hamari et al. (2015) distinguish two categories: intrinsic and extrinsic motivations. The intrinsic motivations they researched are sustainability and enjoyment and the extrinsic motivations are reputation and economic benefits. Their results show that perceived sustainability has a significant effect on predicting someone’s attitude to CC but not on intention to participate in CC. Enjoyment has a significant effect on both prediction as well as intention. For the extrinsic

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motivations, expected increase in reputation did not have significant effects on either attitude to CC nor on participation intention. Furthermore, expected economic benefits did not have a significant effect on attitude but did have a significant positive effect on participation intention. And lastly, attitude towards CC had a significant positive effect on intention to use CC. Attitude towards CC and intention towards CC will both be researched for this study but because expected increase in reputation and expected economic benefits did not have a significant positive effect on participation intention, only perceived sustainability and enjoyment will be researched further.

One of the most discussed variables is trust (Ert, Fleischer, & Magen, 2016; Tussyadiah, 2015; Hawlitschek, Teubner, & Gimpel, 2016; Hamari, Sjöklint, & Ukkonen, 2015) which can also be seen as a barrier to CC. For example, research has shown that consumers are more likely to book accommodation through Airbnb when the choice of listing includes a photo of the host (Ert, Fleischer, & Magen, 2016). This is because a photo positively affects consumer’s perceived trustworthiness even though they are not conscious of this effect themselves. Ert, Fleischer and Magen (2016) even state that in CC platforms like Airbnb, the consumer’s impression of the photo has a greater influence than the review scores of an accommodation. Möhlmann (2015) even argues that CC is for a large part based on trust. Without mutual trust, CC could not exist because people would not be willing to participate. Because trust is such an important variable for CC, it is important to link it with the personality dimensions. Higher levels of trust could possibly improve attitude towards CC and ultimately intention to participate in CC. This will be discussed in further detail later.

Personality

Personality is defined in the Oxford dictionary as “The combination of characteristics or qualities that form an individual's distinctive character” (Oxford, 2017)). There is almost an infinite amount of individual differences which make up one’s personality, yet many of these

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differences are not visible to the daily interactions between people (Goldberg, 1990). Many psychologists have studied personality and the various traits which can be measured. Seventy years ago, Catell (1947) identified at least twelve traits which were replicable. However, these were reduced by many researchers to five factors, also known as the big-five (Tupes & Christal, 1961). These five factors are: 1. Extraversion, 2. Agreeableness, 3. Conscientiousness, 4. Openness to experience, and 5. Neuroticism. Researchers claim that these five factors, in combination or individually, explains almost all variance in personality (Tupes & Christal, 1961).

In the next section, expectation for the relationship between personality and CC will be outlined based on previous research.

Extraversion is measured as the degree to how outgoing or reserved someone is. Personalty traits which are often associated with extraversion are talkability, sociability, activeness and assertiveness (Barrick & Mount, 1991). Extraverts tend to like working with others due to their social and talkative nature, in contrast to introverts, who have a more quiet and private nature (McCrae & John, 1992). Several studies have examined how extraversion affects people’s willingness to collaborate (McLean & Pasupathi, 2006; Doucette, Nevins, & McDonough, 2005; Haberyan & Barnett, 2010). The results show that someone with high extraversion level is more likely to choose working together with someone else rather than working alone. The reason for this is that extraverts are more willing to socialize and talk with others, which is required when collaborating. Furthermore, it is argued that trust towards strangers is controlled by extraversion (Hiraishi, Yamagata, Shikishima, & Ando, 2008). With trust being such an important factor to people’s attitude towards CC, extraverts will probably be more likely to participate.

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The second dimension is known as agreeableness or likability. This dimension is associated with personality traits such as being soft-hearted, courteous, trusting and flexible (Barrick & Mount, 1991). Agreeableness is seen as the compassionate side of humans (Digman, 1990). Additionally, according to Mooradian et al. (2006) it is important to note the difference of interpretation of this personality factor. Where some researchers see this factor as someone being warm and happy other researchers regard as how compliant one is to another (Mooradian, Renzl, & Matzler, 2006). For this research, the degree of warmness and happiness is used. Agreeableness is often linked with sociability and work performance indicating people who score high on this factor have higher satisfaction in life and better performances due to better inter-personal relationships (Asendorpf & Wilpers, 1998; Hurtz & Donovan, 2000). Due to the more trusting nature of agreeable people (Barrick & Mount, 1991) and better inter-personal relationships with others (Asendorpf & Wilpers), it could indicate that people who score high on agreeableness are more likely to participate in CC platforms because it requires trust in the platform to be willing to participate (Tussyadiah, 2015). Agreeableness has also been associated with altruistic and sympathetic natured persons who want to help others (McCrae & John, 1992).

Their more social nature results in agreeableness predicting higher successfulness in collaborations with others (Mooradian, Renzl, & Matzler, 2006). Therefore, individuals scoring higher on agreeableness are expected to have better attitudes towards CC.

Hypothesis 2: Agreeableness has a positive influence on attitude towards CC.

Openness to experience measures the degree of how curious or cautious one is. Traits which are associated with this factor are, for example, curiosity, intelligence, complexity and

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creativeness (Barrick & Mount, 1991). Research by Lumsden and Mackay (2006) shows that openness to experience has a positive effect on trust meaning that people who score higher on openness to experience are also more trusting. Trust is seen as one of the most important drivers of CC usage (Ert, Fleischer, & Magen, 2016; Hawlitschek, Teubner, & Gimpel, 2016) and therefore the trusting nature of people who score higher on openness to experience has a positive influence on their attitude towards CC. Furthermore, curiosity is one of the traits associated with openness to new experience. Curiosity has also been linked with higher development of learning and engagement (Arnone, Small, Chauncey, & McKenna, 2011). Since lack of technology efficacy is the largest deterrent of CC, people who are more willing to learn, will also be more likely to learn, or have learned, new technologies related to CC platforms. Hypothesis 3: Openness to experience has a positive influence on Attitude towards CC.

Conscientiousness measures how dependent someone is and is linked with personality traits such as organization, carefulness and responsibility which is contrasted with unreliability and negligence (Barrick & Mount, 1991; Goldberg, 1993). The fourth personality factor does not have much resemblance with CC and is therefore difficult to assess beforehand. One article indicates that conscientiousness has a negative relationship with internet usage and therefore people who score high on the corresponding traits use the internet less (Landers & Lounsbury, 2006). Because CC platforms require the use of internet, this could result in a negative influence with individuals scoring high on conscientiousness. Other research shows a positive relationship between conscientiousness and sharing due to the high self-interested nature of conscientous people (Matzler et al., 2008). This could lead to a positive relationship with CC because often collaborative services can save the user time and money or even make a living from it. However, just like agreeableness, there is not enough empirical research related to both

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CC and conscientiousness to clearly assess a relationship beforehand without further emperical research. Hence, this relationship will also be be examined exploratory.

The fifth and last factor is the dimension of Neuroticism which covers personality traits like anxiousness, depression, embarrassment and emotionality or on the contrast emotional stability (Barrick & Mount, 1991; Goldberg, 1993). Due to their stressfull and anxious personality, neuroticism has a negative relationship with technology acceptance meaning that people who score high on neuroticism are less likely to accept new technology (Devaraj et al., 2008). This is because neurotic people find new experiences, such as a new technology, threatening, which makes them stressed (Devaraj et al., 2008). Other research suggests neuroticism also has a negative relationship with trust (Zhou & Lu, 2011). Since trust is such an important factor of CC usage intention (Tussyadiah, 2015), this would indicate that neuroticism has a negative relationship with individual’s attitude towards CC.

Hypothesis 4: Neuroticism has a negative influence on Attitude towards CC.

Lack of technology efficacy

Technologies, like online platforms, are becoming an increasingly important part of everyday life. However, new technologies are not always easy for everyone to adapt to. Models on the acceptance of technology are often based on ease of use, complexity and trialability of the technology (Chong, Ooi, & Sohal, 2009). Especially the perceived ease of use of technology is often used as an important factor of accepting new technologies. This perception has been described as the extent to how much effort a person believes is needed to using a new technology (Venkatesh, 2000). Therefore, the better someone’s efficacy with a new technology,

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the more likely is it that he/she will accept the technology and thereby have a more positive attitude towards the new technology.

Tussyadiah (2015) differentiates lack of trust in three different forms: lack of trust between consumer and provider, lack of trust in technology by users and lack of trust in a company. Tussyadiah (2015) argues the lack of trust in technology comes from a lack of technology efficacy. This means that a consumer is not able to produce a desired result because of technology which can be caused due to high complexity. From the results, it is concluded that lack of technology efficacy seems to be the major barrier, followed by lack of trust and lastly lack of economic benefits (Tussyadiah, 2015).

Therefore, making sure the CC platform is easy to use and not creating a technology barrier is of great importance to increase the consumers’ attitude towards CC. Since technology efficacy can be of such great impact to new technologies, or in this case CC platforms, this study will research the moderating role of lack of technology efficacy between personality and attitude towards CC.

Hypothesis 5: The influence of the personality dimensions on attitude towards CC will be weakened by a lack of technology efficacy.

Hamari et al. (2015) have already studied the relation between attitude towards CC and intention to participate in CC. Therefore, their research is followed and a positive influence of attitude towards CC on intention to participate in CC assumed.

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15 Conceptual model

Note. H = Hypothesis; - = negative influence; + = positive influence; * = will be researched exploratory

Method

The population researched in this study is anyone with the accessibility to internet, which is a requirement to make use of CC platforms. The survey was distributed online through Social Media and via e-mail. Since many of the platforms require a minimum age of 18, any response of a younger respondent was removed. Due to the large possible population and unknown sampling frame, a non-probability convenience sampling method was used. In total, 335 participants filled in the questionnaire of which 258 completed it. Because the survey was mainly distributed through Facebook, it was very difficult to predict the response rate since it was an open message to my connections. These connections will also be asked to share the survey, increasing the difficulty to assess the amount of people reached.

The questionnaire starts with asking the respondents their demographics such as Sex, Age, Educational Background and Nationality. Age and gender are used as controlling variables to remove their effects from the equation. The other constructs will be measured with questionnaires used in the following scientific articles:

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For all dimensions of ‘Personality’ (Extraversion, Agreeableness, Openness to experience, Conscientiousness and Neuroticism), the Big Five Inventory was used (John & Srivastava, 1999). All Cronbach alphas are between 0.70 and 0.87. The items range from 1 “disagree strongly” to 5 “agree strongly”. For each item, the participant has to answer the question: ‘I see myself as someone who..’

The first dimension, extraversion, has eight items. An example of an item is: ‘Is talkative’ and ‘Is reserved’. The second dimension, agreeableness, has nine items. An example of an item is: ‘Tends to find fault with others’ and ‘Is helpful and unselfish with others’. The third dimension, conscientiousness, has nine items. An example of an item is: ‘Does a thorough job’ and ‘Can be somewhat careless’. The fourth dimension, neuroticism, has eight items. An example of an item is: ‘Is depressed, blue’ and ‘Is relaxed, handles stress well’. And the last dimension, openness to experience, has ten items. An example of an item is: ‘Is original, comes up with new ideas’ and ‘Is curious about many different things’.

For both the structures ‘Attitude towards CC’ and ‘Intention to participate in CC’, the article by Hamari, Sjöklint and Ukkonen (2015) was used. The structure ‘Attitude towards CC’ (Cronbach alpha = 0.858) contains five items. An example of an item is: ‘All things considered, I find participating in CC to be a wise move.’ and ‘CC is a better mode of consumption than selling and buying individually.’. The structure ‘Intention to Participate in CC’ (Cronbach alpha = 0.863) contains four items and an example of an item is: ‘All things considered, I expect to continue CC often in the future.’ and ‘It is likely that I will frequently participate in CC communities in the future.’. All items for both constructs are on a 7-point Likert scale from 1 (strongly disagree) to 7 (stongly agree).

And lastly, for ‘Lack of Technology Efficacy’, the article by Barbeite and Weiss (2004) was used. For this construct (Cronbach alpha = 0.85), the article provides seventeen items using a 5-point scale, from 1 (strongly disagree) to 5 (strongly agree). The items were adjusted to

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‘technology’ instead of ‘computer’ because in the article by Tussyadiah (2015) it states that Lack of Technology Efficacy is the biggest deterrence of CC usage. An example of an item is: ‘I find working with digital technology very easy.’ and ‘17. When using digital technology I worry I might press the wrong button and damage it.’.

For the data analysis, first the correlations were measured (Appendix 1). Then some predictives were computed (Appendix 1). Next, a reliability analysis was conducted to test the consistency of the data which showed all Cronbach alphas are above the 0.7 mark (Appendix 1). Afterwards, two hierarchical multiple regression models were computed. One for

personality predicting intention to participate in CC (Appendix 2) and one for personality predicting attitude towards CC (Appendix 3). A linear regression model was computed to test the effect of attitude towards CC on intention to participate in CC (Appendix 4). The

mediating effect of attitude towards CC between all five personality factors and intention to participate in CC was computed next (Appendix 5-9). And lastly, a moderated mediation analysis was performed (Appendix 10).

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Results

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Personality predicting intention to participate in CC

A hierarchical multiple regression model was computed to explore to what degree the five personality dimensions; Openness to Experience, Conscientiousness, Extraversion, Agreeableness, and Neuroticism can predict an individual’s intention to participate in CC, after controlling for age and gender (Appendix 1).

For the first step of the hierarchical multiple regression model, two controlling variables were used: age and gender. From the analysis came forth that this first model was statistically significant F (2,255) = 13,731; p < 0,001 and it explained 9,7% of variance in an individual’s intention to participate in CC. For the second step of the model, the five personality dimensions were added. This second model increased the explained variance in an individual’s intention to participate in CC to 20,5%, F (7,250) = 9,200; p < 0,001. That means that by introducing personality, an additional 10,8% of variance in attitude towards CC is explained after controlling for age and gender (R2_{change = 0.108; F (2, 250) = 6,766; p < 0,001). In the second}

and final model, two out of seven predictor variables were statistically significant with agreeableness scoring the highest Beta value (β = 0,266; p < 0,001) after age (β = -0,280; p < 0,001). This means that if an individual’s agreeableness increases by one, his/her intention to participate in CC increases by 0.266. But on the other hand, age has a negative relation with intention to participate in CC meaning that older people have a lower attitude towards CC. It is important to note here that the lowest age group selected was 3 (18 – 24), indicating that the all participants were older than 18.

1_{It is important to note here that the results from SPSS differed from Process (Hayes, 2013). For the correlations}

and regressions, the data from SPSS was assumed. And for the mediations and moderated mediation, data from Process was assumed.

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Personality predicting attitude towards CC

Afterwards, another hierarchical multiple regression model was computed to examine to what degree the same five personality dimensions can predict an individual’s attitude towards CC. Just like the previous analysis, age and gender will be controlled first (Appendix 2).

From the first analysis, with age and gender as controlling variables, came forth that this model was statistically significant F (2,255) = 6,414; p < 0,05 and it explained 4,8% of variance in an individual’s attitude towards CC. Then the five personality dimensions were again added for the second step of the model. This model increased the explained variance in an individual’s attitude towards CC to 15,8%, F (7,250) = 6,681; p < 0,001. By introducing personality, an additional 11% of variance in attitude towards CC is explained after controlling for age and gender (R2_{change = 0.11; F (2, 250) = 6,511; p < 0,001). Three out of seven predictor variables}

were statistically significant with again agreeableness scoring the highest Beta value (β = 0,249;

p < 0,05) after openness to experience (β = 0,158; p < 0,05) and age (β = -0,221; p < 0,05).

Attitude towards CC predicting intention to participate in CC

A linear regression model was computed to measure the degree to which an individual’s attitude towards CC can predict their intention to participate in CC, after again controlling for age and gender (Appendix 3).

Age and gender were again used as controlling variables for the first step. The first model is statistically significant F (2,255) = 13,731; p < 0,001 and it explained 9,7% of the variance of an individual’s intention to participate in CC. The variable attitude towards CC was added in the model and was also statistically significant F (3,254) = 176,404; p < 0,001 and increased the explained variance of intention to participate in CC to 67,6%. Two out of three variables in the second model are statistically significant, namely age and attitude to CC.

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Attitude towards CC had by far the highest Beta value (β = 0,779; p < 0,001) after age (β = -0,122; p < 0,05).

Mediations

Next the mediating effect of attitude towards CC between all five personality dimensions and intention to participate in CC was researched using ‘process’ by Hayes (2012). However, since agreeableness was the only dimension which significantly effected both intention to participate in CC and attitude towards CC, the other four dimensions will not be discussed in depth regarding the mediation.

The indirect effect of agreeableness on intention to participate in CC is 0.36 which means that when two individuals have a difference of one unit in their noted agreeableness, the will differ 0.36 units in their intention to participate in CC due to individuals with more agreeing nature having a more positive attitude towards CC. As indicated by a 95% BC bootstrap confidence interval, agreeableness has a statistically different indirect effect than zero because the interval is entirely above zero (0.1793 to 0.5619).

Interestingly, openness to experience and extraversion also had a statistically different indirect effect than zero because their interval were also entirely above zero (0.25 to 0.73 and 0.04 to 0.42 respectively). The other two dimensions, neuroticism and conscientiousness did not have a statistically different indirect effect than zero (-0.11 to 0.21 and -0.33 to 0.09 respectively). However, as mentioned before, these dimensions will not be analysed further.

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Moderated mediation

Lastly, a moderated mediation analysis was performed to research the moderating effect of lack of technology efficacy on the mediating effect of attitude towards CC between the five personality dimensions and intention to participate in CC (Appendix 10). For this analysis

‘process’ by Hayes (2012) was again used.

The results show that there is only statistical evidence of a moderated mediation taking place between neuroticism and attitude towards CC (b=0,27; p<0,05). The other four dimensions all had a p-value of higher than 0.05 and were therefore not researched further. In other words, lack of technology efficacy significantly moderates the relationship between neuroticism and attitude towards CC.

Figure 1. Significant results of conceptual model

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Overview of results

The results show Hypothesis 2, 3 and 6 are accepted, Hypothesis 1 and 4 are rejected and Hypothesis 5 is only accepted for neuroticism.

Table 1. Overview of hypotheses

Number of Hypotheses Hypotheses Results

Hypothesis 1 Extraversion has a positive influence on Attitude towards CC.

Rejected

Hypothesis 2 Agreeableness has a positive influence on attitude towards CC.

Accepted

Hypothesis 3 Openness to experience has a positive influence on Attitude towards CC.

Accepted

Hypothesis 4 Neuroticism has a negative influence on Attitude towards CC.

Rejected

Hypothesis 5 The influence of the personality dimensions on attitude towards CC will be weakened by a lack of technology efficacy.

Only accepted for neuroticism

Hypothesis 6 Attitude towards CC has a positive influence on intention to participate in CC.

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Discussion

This study researched the effect of personality on attitude and participation intention to CC. Five personality dimensions as described by Goldberg (1993) have been analysed. Interestingly, only agreeableness and openness to experience had a significant influence on attitude towards CC. Additionally, agreeableness was also the only dimension which had a significant influence on intention to participate in CC. In both cases, agreeableness had the highest standardized coefficient (Appendix 2 and 3). To answer the research question “What is

the effect of personality on attitude and participation intention to CC?”, all five dimensions

have been analysed.

Extraversion. This research shows that extraversion does not have an influence on

either attitude towards CC or intention to participate in CC. However, even though it was insignificant, it was still positive. This is in line with several other researchers, who argue that extraverts are more likely to collaborate with other individuals (McLean & Pasupathi, 2006; Doucette, Nevins, & McDonough, 2005; Haberyan & Barnett, 2010). Furthermore, researchers argue extraversion controls an individual’s trust towards a stranger (Hiraishi, Yamagata, Shikishima, & Ando, 2008). Both collaborating and trust are important factors of CC. Therefore the positive influence can be explained.

Agreeableness. The analysis proved agreeableness has a positive influence on an

individual’s attitude towards CC. Not only is it positive, it is also significant. This was as expected because previous research suggests more agreeable individuals have better inter-personal relationships (Asendorpf & Wilpers, 1998; Hurtz & Donovan, 2000). Inter-inter-personal relationships are an important part of the collaborative aspect of CC. Furthermore, agreeableness has been positively linked with trust (Barrick & Mount, 1991), which is also an important factor of CC (Tussyadiah, 2015). And lastly, higher scores of agreeableness are positively related to altruism and sympathy (McCrae & John, 1992). These traits give agreeable

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individuals a higher sense of helping others. All these aspects lead to a better attitude towards CC.

Openness to experience. Just like agreeableness, the results indicate openness to

experience has a significant positive influence on attitude towards CC. Again trust plays an important factor. Due to their curious and intelligent nature (Barrick & Mount, 1991), individuals with a higher level of openness to experience are also more trusting (Lumsden & Mackay, 2006). Not only trust, but also a higher development of learning and engagement contributes to a positive influence on attitude towards CC. The concept of CC is still fairly new and lack of technology efficacy is seen as the largest deterrent of these sharing systems (Tussyadiah, 2015). Therefore, individuals who are higher developed in learning and engagement of new experiences, such as CC and technology, will also have a more positive attitude towards CC.

Conscientiousness. The fourth personality dimension, conscientiousness, does not have

much resemblance with CC. Conscientiousness has been associated with traits such as carefulness, organization and responsibility (Barrick & Mount, 1991; Goldberg, 1993). Arguments can be found for both a positive and negative relationship with attitude towards CC. Research by Landers & Lounsbury (2006) argues conscientious individuals are less fond of internet. Because CC platforms require usage of internet, this could indicate a negative influence on attitude towards CC. However, on the other side, conscientiousness has been positively associated with sharing (Matzler et al., 2008). The reason for this positive association is because conscientious individuals have a high self-interest. CC has proven to be able to save time and money by sharing services and goods (Hamari, Sjöklint, & Ukkonen, 2015). Therefore, conscientiousness could also positively influence attitude towards CC.

The results of this research show there is a negative influence of conscientiousness on attitude towards CC. However, this negative influence is not significant. This could indicate that the

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negative influences, such as aversion to internet, outweighs the positive influences, such as the benefits of CC to users’ self-interest.

Neuroticism. From the results we find that neuroticism actually had a positive influence

on attitude towards CC, though it was insignificant. This is on the contrary of what previous research expected. Neuroticism has been negatively linked with trust (Zhou & Lu, 2011) and acceptance of new technologies (Devaraj et al., 2008). Because trust is an important factor of CC (Ert, Fleischer, & Magen, 2016; Hawlitschek, Teubner, & Gimpel, 2016) and it is still seen as a relatively new market behaviour based on technological advances (Hamari, Sjöklint, & Ukkonen, 2015), prior to this research it was expected neuroticism would have a negative influence on CC. Also, because trust and technology acceptance are two important factors of CC (Tussyadiah, 2015), it was expected to have a significant influence on attitude towards CC. However, the results from Process indicate there is indeed a negative relation between neuroticism and attitude towards CC. Therefore further research is required to analyse this relationship because all previous research, to my knowledge, indicates a negative influence.

Attitude towards CC and intention to participate in CC. Hamari et al. (2015) had

already researched the relationship between attitude towards CC and intention to participate in CC. They concluded there was a significant positive relationship. This is in line with the results from this research. However, the correlation between these two variables was on the high side. Some participants might therefore not have interpreted the two variables as different from each other. But based on the findings of this research and the research by Hamari et al. (2015), it is evident there is a significant positive relation between attitude towards CC and intention to participate in CC.

Accordingly, it can be concluded that personality in total does not have a very significant influence on attitude towards CC and ultimately intention to participate in CC. Only two out of

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five dimension directly significantly influence intention to participate in CC and only one dimension significantly influences attitude towards CC.

Moderated mediation effect. This study did not only research the effect of personality

on attitude towards CC and ultimately intention to participate in CC, but also the moderating effect of lack of technology efficacy on the relationship between personality and intention to participate in CC, mediated by attitude towards CC. According to Tussyadiah (2015), lack of technology efficacy is the largest barrier of individuals to make use of CC platforms. Ease of use, complexity and trialability of technology are often described as the three most important factors of technology acceptance (Chong, Ooi, & Sohal, 2009). From the results we can see that only one personality dimension was significantly moderated by lack of technology, namely neuroticism. It is important to note here that, unlike in SPSS, the results in process show neuroticism has a negative influence on attitude towards CC. Based on the negative influence of neuroticism on attitude towards CC as in Process, the result is in line with prior research. According to the results in Process, individuals scoring high in neuroticism will have a low attitude towards CC which is moderated by lack of technology efficacy. This means that if an individual is familiar with technology, his/her attitude towards CC will improve as well and vice versa.

However, the other four personality dimensions were insignificantly moderated by lack of technology efficacy. There could be several reasons for this. The mean age group of the participants is 4,12 (Appendix 1). Age group 4 is between 25 and 34 years old. This means they belong to the ‘Millennials’, who, according to Google Consumer Barometer, don’t go online but live online (Google, 2017). They are born with the current technologies and are therefore often experienced with it. The mean lack of technology efficacy was 2,030 (Appendix 1), which means that on average, the participants did not think they have a technology efficacy. However, this does not explain why only neuroticism was significantly moderated by lack of technology

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efficacy. A possible explanation could be that neuroticism was, according to the results from Process, the only dimension which negatively influenced attitude towards CC (Appendix 10). Or in other words, lack of technology efficacy only moderates the personality dimensions which themselves have a negative influence on attitude towards CC.

Theoretical implications.

Much research has been conducted on the drivers and advantages of CC (Hawlitschek, Teubner, & Gimpel, 2016; Hamari, Sjöklint, & Ukkonen, 2015; Tussyadiah, 2015; Owyang, 2013). However, little to none research has been conducted on how personality can predict the usage of CC platforms. This paper has researched which personalities are more likely to make use of said platforms. The results show that agreeableness is the only personality dimension which positively influences both attitude towards CC and intention to participate in CC.

Additionally, the moderating effect of lack of technology efficacy on the relationship between personality and intention to participate in CC, mediated by attitude towards CC. has been researched. This study shows that only neuroticism is the only personality dimension which is significantly moderated by lack of technology efficacy.

Managerial implications.

Nowadays, the amount of collaborating services is increasing. It is disrupting traditional market forces and the way consumers think about possession of goods and services. Also, due to the benefits to sustainability, governments and companies are increasingly interested in CC platforms. By finding an answer to how personality affects participation intention and attitude towards CC, corresponding companies can improve their performances by adjusting their services to fit customer needs. The results indicate that individuals who score high on agreeableness have a significant positive influence on both attitude towards CC and intention

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to participate in CC. Therefore, by studying how agreeable consumers behave, it is possible to target these individuals and thereby increase acquisition rates of CC platforms. Not only can companies benefit from this research, also consumers and many other people since researchers believe CC can positively influence environmental, economic and social problems. A better understanding of the topic can lead to improved economies, better sustainability and improvements to society (Belk, 2014; Hamari, Sjöklint, & Ukkonen, 2015; Hawlitschek, Teubner, & Gimpel, 2016).

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Conclusion

The main goal of this study was to find an answer to the question: “What is the effect of

personality on attitude and participation intention to CC?”. Personality has been divided into

five dimension (Openness to experience, conscientiousness, extraversion, agreeableness and neuroticism). No previous studies had researched this relation before. However, personality traits corresponding to the five dimensions were compared with factors of CC to find resemblances such as collaboration and trust.

Previous research suggests openness to experience has a positive influence on intention to participate in CC due to higher levels of trust (Lumsden & Mackay, 2006) and curiosity (Barrick & Mount, 1991). Conscientiousness does not have much resemblance with CC and is therefore further researched in this paper. Extraversion is also expected to positively influence intention to participate in CC because extraverts tend be social and trusting towards others, both needed when collaborating (McLean & Pasupathi, 2006; Doucette, Nevins, & McDonough, 2005; Haberyan & Barnett, 2010). Agreeableness is likewise expected to positively influence intention to participate in CC because agreeable individuals tend to have better inter-personal relationships with others (Asendorpf & Wilpers) and a high trusting nature (Barrick & Mount, 1991). And lastly, neuroticism is the only dimension which is expected to negatively influence intention to participate in CC. Individuals with high scores in neuroticism are less likely to accept new technologies (Devaraj et al., 2008), such as CC platforms. They are also distrusting in strangers (Zhou & Lu, 2011), which does not benefit participation intention in CC.

In order to find an answer to this question and the hypotheses, a survey is used. 335 responses were recorded through social media platforms and email. The recorded data is then analysed to find the answers.

The results show that only two dimensions had a significant influence on attitude towards CC, namely agreeableness and openness to experience. Both dimensions had a positive

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influence. Furthermore, only one dimension had a significant influence on intention to participate in CC, namely agreeableness. Furthermore, only neuroticism is significantly moderated in the relationship between personality and intention to participate in CC, mediated by attitude towards CC.

No prior studies have researched these relations and thereby this study contributes to the current theories. Furthermore, companies can benefit from the results of this study because it shows agreeableness is the only personality dimension which significantly positively influences both intention to participate in CC and attitude towards CC.

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Limitations and future research

This study has researched the effect of personality on attitude towards CC and intention to participate in CC. However, a few limitations exist.

First, even though the five dimensions of personality are often used, a limitation of this measurement is that the dimensions are measured through self-assessment. Individuals might evaluate themselves differently than they really are or how others perceive them. Additionally, as an example of CC platforms only Uber and AirBnB were named in the survey. This can affect perceptions because these two companies are the largest examples at the moment. These companies also entail transportation and accommodation respectively. Other sectors might find different results. Another limitation is that because CC is still a fairly new concept, many individuals might not exactly understand what it is (even though it was briefly explained in the survey). Also, no distinction was made between users who have and users who do not have experience with CC platforms. And lastly, attitude towards CC had a correlation of 0,81 with intention to participate in CC which might show that people did not perceive the two questions as compellingly different.

Future research should control other sectors and provide different examples than Uber and AirBnB. Also, solely studying individuals who not have any experience with or knowledge of CC can provide different results. Follow-up studies should also make a better differentiation between attitude towards CC and intention to participate in CC.

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Appendices

Appendix 1: Variables M SD 1 2 3 4 5 6 7 8 9 Gender 1,45 ,498 Age 4,12 1,524 -,197 Openness to Experience 3,762 ,541 ,018 -,115 (,725) Conscientiousness 3,653 ,637 ,079 ,372 ,1 (,778) Extraversion 3,710 ,675 ,029 ,009 ,269 ,154 (,816) Agreeableness 3,854 ,618 ,105 ,24 ,209 ,264 ,178 (,769) Neuroticism 2,630 ,817 ,263 -,428 -,101 -,272 -,298 -,317 (,857) Attitude Towards CC 5,421 1,104 ,071 -,217 ,252 -,069 ,145 ,213 ,035 (,931) Intention to Participate in CC 5,076 1,298 ,135 -,302 ,226 -,145 ,141 ,199 ,088 ,81 (,951) Technology Efficacy 2,030 ,722 ,193 ,089 -,174 -,053 -,034 -,111 ,202 -,186 -,14 (,932)

Note. N = 258. Age coding = (1 = under 12; 2 = 12-17; 3 = 18-24; 4 = 25-34; 5 = 35-44; 6 = 45 – 54; 7 = 55 – 64; 8 = 65 – 74; 9 = 75 years or older), Gender coding (1 = male; 2 = female). Cronbach alpha values are in brackets on the diagonal. M = Mean; SD = Standard deviation.

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36 Appendix 2: Hierarchical regression model of Intention to participate in CC

R R² R² Change B SE β t Step 1 0,312 0,097 Age -,244 ,052 -,287 -4,722 Gender ,205 ,158 ,079 1,297 Step 2 0,453 0,205 0,108 Age* -,239 ,058 -,280 -4,109 Gender ,114 ,160 ,044 ,711 Openness to Experience ,281 ,145 ,117 1,938 Conscientiousness -,239 ,129 -,117 -1,852 Extraversion ,185 ,119 ,096 1,553 Agreeableness* ,560 ,133 ,266 4,201 Neuroticism ,078 ,112 ,049 ,700

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37 Appendix 3: Hierarchical regression model of Attitude towards CC

R R² R² Change B SE β t Step 1 0,219 0,048 Age -,153 ,045 -,211 -3,391 Gender ,064 ,138 ,029 ,462 Step 2 0,397 0,158 0,11 Age* -,16 ,051 -,221 -3,155 Gender -,03 ,14 -,013 -,212 Openness to Experience* ,323 ,127 ,158 2,544 Conscientiousness -,091 ,113 -,053 -,806 Extraversion ,136 ,104 ,083 1,298 Agreeableness* ,446 ,117 ,249 3,822 Neuroticism ,067 ,098 ,049 ,684

Note. These are standardized regression coefficients. *p<0.05

Appendix 4: Linear regression model of Intention to participate in CC

R R² R² Change B SE β t Step 1 ,312 ,097 Age -,244 ,052 -,287 -4,722 Gender ,205 ,158 ,079 1,297 Step 2 ,822 ,676 ,579 Age* -,104 ,032 -,122 -3,270 Gender ,146 ,095 ,056 1,543 Attitude towards CC* ,916 ,043 ,779 21,285

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38 Appendix 5: Mediation effect openness to experience

Consequent

Attitude towards CC (M) Intention to participate in CC (Y)

Antecedent Coeff. SE p Coeff. SE p

Openness to experience (X) a1 ,515 ,123 ,000 c1' ,054 ,091 ,551 Attitude towards CC (M) --- --- --- b1 ,945 ,045 ,000 constant i1 3,484 0,468 ,000 i2 -,252 ,369 ,494 R2_{= ,063} _R2_{= ,656} F(1,256) = 17,425; p < 0,001 F(2,255) = 243,554; p < 0,001 Effect SE p Direct effect c1' ,0543 ,091 ,551 Total effect c1 ,541 ,146 ,000 Boot SE Boot LLCI Boot ULCI

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Indirect effect a1b1 ,486 ,125 ,246 ,729

Appendix 6: Mediation effect conscientiousness

Consequent

Conscientiousness (X) a1 -,119 ,108 ,268 c1' -,182 ,074 ,014 Attitude towards CC (M) --- --- --- b1 ,945 ,043 ,000 constant i1 5,859 ,401 ,000 i2 ,621 ,371 ,096 R2_{= ,005} _R2_{= ,664} F(1,256) = 1,229; p < ,268 F(2,255) = 251,834; p < 0,001 Effect SE p Direct effect c1' -,182 ,074 ,014 Total effect c1 -,296 ,126 ,019 Boot SE Boot LLCI Boot ULCI

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Indirect effect a1b1 -,113 ,106 -,329 ,089

Appendix 7: Mediation effect extraversion

Consequent

Extraversion (X) a1 ,237 ,101 ,020 c1' ,047 ,071 ,507 Attitude towards CC (M) --- --- --- b1 ,948 ,044 ,000 constant i1 4,543 ,381 ,000 i2 -,237 ,332 ,474 R2_{= ,064} _R2_{= ,656} F(1,256) = 5,471; p < ,05 F(2,255) = 243,678; p < 0,001 Effect SE p Direct effect c1' ,047 ,071 ,507 Total effect c1 ,272 ,119 ,023 Boot SE Boot LLCI Boot ULCI

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Appendix 8: Mediation effect agreeableness

Consequent

Agreeableness (X) a1 ,381 ,109 ,001 c1' ,057 ,079 ,469 Attitude towards CC (M) --- --- --- b1 ,945 ,044 ,000 constant i1 3,952 ,426 ,000 i2 -,268 ,348 ,441 R2_{= ,045} _R2 = ,6566 F(1,256) = 12,188; p < 0,001 F(2,255) = 243,803; p < 0,001 Effect SE p Direct effect c1' ,054 ,091 ,551 Total effect c1 ,057 ,079 ,469 Boot SE Boot LLCI Boot ULCI

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Appendix 9: Mediation effect neuroticism

Consequent

Neuroticism (X) a1 ,048 ,084 ,573 c1' ,094 ,058 ,108 Attitude towards CC (M) --- --- --- b1 ,949 ,043 ,000 constant i1 5,295 ,232 ,000 i2 -,318 ,278 ,254 R2_{= ,064} _R2_{= ,656} F(1,256) = ,319; p < ,573 F(2,255) = 246,824; p < 0,001 Effect SE p Direct effect c1' ,094 ,058 ,108 Total effect c1 ,139 ,099 ,161 Boot SE Boot LLCI Boot ULCI

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Indirect effect a1b1 ,045 ,079 -,109 ,206

Appendix 10: Moderating mediation

Variable DV = Attitude towards CC DV = Intention to participate in CC

Constant 7,258 -0,318

Independent variables

Neuroticism -0,472 0,094

Attitude towards CC 0,949

Lack of technology efficacy -1,029

Interaction neuroticism x lack

of technology efficacy 0,273

R2 0,060 0,659

Personality as a predictor of collaborative consumption usage