How the Self-Transcendent Emotion of Awe Affects Cooperation

Home , Awe

How the Self-Transcendent Emotion of Awe Aﬀects Cooperation, Distributional Preferences and Stability in Measurement of the Five Factor Model of Personality Traits

Caleb Lo School of Economics and Finance QUT Business School Queensland University of Technology

Submitted in fulﬁlment of the requirement for the degree of Master of Philosophy (Economics)

2019 Declaration of Authorship

The content of this thesis is the original work of the author. The work has not been previously submitted to meet requirements for an award at this or any other higher education institution. To the best of my knowledge and belief, the thesis contains no material previously published or written by another person except where due reference is made.

Name: Caleb Lo Date: 3rd September, 2019

Signature: QUT Verified Signature Acknowledgements

First of all I would like to thank my supervisors, Professor Uwe Dulleck and Dr. Stephen Whyte. Without your inspirations, support and guidance, this thesis would be impossible. I would like to thank Anthony and Alice for their help, in particular with coding. I would also like to thank Martin and Laura for all the chats we had and ideas you provided. To everyone else in the School of Economics and Finance, Aimee, Azhar, Ben, Jeremy, Naomi, Richard, Ryan, Poli, thank you for all the coﬀees, chats and laughter we had together. Last but certainly not least, I would like to thank my family for your love and support during this research journey. To my parents, Martin and Karen, I never thank you enough for having raised me over all these years. Abstract

The emotion of awe has attracted research interest in the past decade on its particular ability of changing people behaviour. Recent studies have found that experience of awe leads to a sense of “small self”, and therefore leads to increased prosociality, This research aims to further investigate awe’s impact on diﬀerent aspects, including cooperation, distributional preferences and stability in measurement of personality traits. Through a laboratory experiment and exposing participants in a natural awe environment, this study found that individuals exposed to awe exhibited higher cooperation level in the public goods game, and increase in their measurement of agreeableness. Understanding that agreeableness predicts prosociality and cooperation, ﬁndings in this study established an indirect theoretical link between awe and prosociality/ cooperation. Contents

1 Introduction 1

2 Literature Review 6 2.1 Introduction to cooperative behaviour and shared intentionality . . . 6 2.2 Prosocial behaviour and Cooperation ...... 7 2.3 Relational consciousness ...... 8 2.4 The emotion of awe ...... 9 2.4.1 Self-transcendence ...... 13 2.4.2 Individual differences in experiences of awe ...... 16 2.5 Somatic Marker Hypothesis ...... 18 2.6 Stability of the Big Five Personality Traits ...... 20 2.7 Factors affecting Public Goods Game Contribution ...... 22 2.8 Distributional preferences ...... 25 2.9 Gender difference in Behavioural and Experimental Research . . . . . 26 2.10 Summary ...... 28

3 Methodology and Design 29 3.1 The experiment ...... 29 3.2 Design ...... 31 3.2.1 Treatment ...... 31 3.2.2 Emotion labels ...... 32 3.2.3 Appraisal endorsement for target experience ...... 32 3.2.4 Next hour activity ...... 32 3.2.5 Equality Equivalence Test (EET) ...... 33 3.2.6 Bomb Risk Elicitation Task (BRET) ...... 33 3.2.7 Demographics ...... 33 3.2.8 Public Goods Game ...... 34 3.3 Summary ...... 34 4 Results and Discussion 35 4.1 Descriptive Statistics ...... 36 4.2 Awe and Cooperation ...... 40 4.3 Awe and Distributional Preferences ...... 45 4.4 Awe and the Stability in the measurement of the Five Factor Model of Personality Traits ...... 51 4.4.1 OLS Estimation on Measurement of Personality Traits Stability 51 4.4.2 Wilcoxon rank-sum test and Two-sample t-test on Measure- ment of Personality Trait Stability ...... 52 4.4.3 Components of Agreeableness ...... 53 4.4.4 Further Analysis on Stability in the measurement of Agreeable- ness ...... 54 4.4.5 Discussion ...... 58 4.5 Moderating eﬀect of agreeableness on cooperation ...... 59 4.6 General Discussion of Results ...... 61

5 Conclusion 63

A Experiment screenshots i

B Experiment instructions xvii B.1 Task A instructions ...... xvii B.2 Task C instructions ...... xviii

C Other tests xxi

D Experimental treatment xxv

References xxviii List of Figures

4.1 Contribution in the Public Goods Game. (N=126) ...... 41 4.2 Frequency of the (x,y) scores. (N=117) ...... 45

A.1 Welcome page. Participants were to enter their participant label into the box above...... i A.2 Welcome Page. The experimenter presented participants with a brief introduction. This screen captures no data...... i A.3 FFM (Pre-treatment). This is the first screen of the standard FFM questionnaire before the target experience...... ii A.4 FFM (Pre-treatment). This is the second screen of the standard FFM questionnaire before the target experience...... iii A.5 FFM (Pre-treatment). This is the third screen of the standard FFM questionnaire before the target experience...... iv A.6 Demographic questions. This is the first screen of the demographics questions to be answered by the participants. It includes questions such as age, gender, education, marital status, field of study and whether English is their first language...... v A.7 Demographic questions. This is the second screen of the demographics questions to be answered by the participants. It includes questions regarding their ethnic and religious background...... vi A.8 Demographic questions. This is the third screen of the demographics questions to be answered by the participants. It includes questions about their devoutness to religion, interest in politics, political views, next hour activites as in Shiota et al. (2007), life satisfaction, health and comments on the experiment...... vii A.9 Emotional labels (as in Shiota et al., 2007). After the target experience, participants were asked to describe their emotional state according to the emotional labels on a scale of 0-100. Two examples of the emotional labels are shown above...... viii A.10 Instructions for Task A. This screen is to inform participants that Task A is about to start. The instructions for Task A were read aloud by the experimenter. Participants also received a physical copy of the instructions when they reach this screen...... ix A.11 Contribution page for Task A. Participants were to choose their contribution to the joint project on this page. The top of this page shows participants the round they are in...... ix A.12 Results page. This page shows participants the details of all the contributions in the group, as well as the participants earnings for the round...... x A.13 Question on the reasoning behind their decisions. Participants were asked this question about the reasons behind their choice of contribution to the joint project, after round 8...... x A.14 Appraisal endorsement for target experience (as in Shiota et al., 2007). Participants were asked to rate the extent to which they remembered having several appraisals of the target experience, on a scale of 0-100. xi A.15 Question on whether the target experience affected their decision to contribute. Participants in the main treatment were asked this question, whether they felt the target experience affecting their decisions on how much to contribute in the PGG...... xi A.16 Question on participants previous visits to the Gibson Room. Partic- ipants in the main treatment were asked this question, as familiarity may reduce the level of awe during the experience. Participants were to complete the FFM questionnaire the second time after this question. xii A.17 Task B instructions. After the second FFM questionnaire (post-treatment), the instructions for Task B were shown to participants. Participants were told by the experimenter that Task B involves ten decisions of splitting money between you (the participant) and another participant. xii A.18 Decision Task for Task B. This is the decision task from Kerschbamer (2015), with earnings adjusted...... xiii A.19 Task C instructions. This screen is to inform participants that Task C is about to start. The instructions for Task C were read aloud by the experimenter. Participants also received a physical copy of the instructions when they reach this screen...... xiv A.20 Decision screen for Task C. Participants start collecting boxes by pressing the Start button and they can press Stop anytime. Every second before the Stop button a box will be marked by a tick symbol, indicating that the box is collected. Participants press the Solve button to locate the bomb after pressing Stop...... xv A.21 Results screen for Task C. Participants were informed their earnings for Task C, including the number of boxes collected and whether the bomb is located in one of the boxes they collected...... xvi A.22 Payment screen. This is the final screen of the experiment. Partici- pants were informed the details of their earnings from the experiment, including the selected rounds for payment...... xvi Chapter 1

Introduction

“The beauty of the trees, the softness of the air, the fragrance of the grass, speaks to me. The summit of the mountain, the thunder of the sky, speaks to me. The faintness of the stars, the trail of the sun, the strength of ﬁre, and the life that never goes away, they speak to me. And my heart soars.” Chief Dan George

Sunsets, starry skies, mountains, oceans, waterfalls, childbirth, - transformative, un- forgettable once-in-a-lifetime experiences, bring an immense sense of wonder, fascination, and joy. How do these experiences impact, and transform individuals? If these experiences are beneficial to ourselves, how do these experiences benefit the rest of the society, including those who did not experience it? If so, does it have collective implications, where people feel part of a greater community, by making decisions that are beneficial to others, not just beneficial to themselves?

Awe is an emotional response to perceptually vast stimuli that overwhelms and challenges frames of reference. Awe is by no means a new concept, as historic reference

1 of awe can be found in religion, sociology and philosophy. Keltner and Haidt (2003) define the important properties of awe as vastness and accommodation, laying a solid theoretical foundation for later studies and leading to a resurgence in the research on awe. The five essential elements - threat, beauty, ability, virtue and supernatural causality distinguish awe from other positive emotions such as admiration (Keltner & Haidt, 2003). Combining the solitary nature of experience and a seemingly contra- dictory unifying power, awe is neither an other-oriented emotion, nor a self-oriented emotion, but a stimulus-oriented emotion, which is different to other positive emotions such as gratitude (Prade & Saroglou, 2015). The mechanism behind the social function of awe is different to other positive emotions, and requiring further exploration.

Pioneering studies of the social function of awe have only emerged a few years ago, when researchers such as Piff et al. (2015), Prade and Saroglou (2015) and Stellar et al. (2017) examined the relationship between awe and prosocial behaviour. Piff et al. (2015) propose that the sense of diminished self brought by awe experiences will lead to greater prosociality, while Prade and Saroglou (2015) look particularly into the effect of awe on helping behaviour. However, these studies were limited by the simple priming methods they employed in their elicitation of awe. The social function of awe needs to be explored and tested in different dimensions, using different methodologies. Having a well-established link between awe and prosociality also has important implications for the study of cooperation. A problem for this study concerns the distinction between prosociality and cooperation. Chapter 2 will detail the parallels between prosociality and cooperation, in the basis of which this study expects a positive impact of awe on cooperation.

Key Research Question 1. How does the emotion of awe aﬀect cooperation in economic experiments?

Following from Key Research Question 1 and past findings on the social function of awe, it would be interesting to further explore the effect of awe on different types of social preferences.

Key Research Question 2. How does the emotion of awe aﬀect distributional preferences in economic experiments?

2 In addition, this study aims to investigate the eﬀect of an awe experience on individual personality. Understanding that behaviours manifest from one’s personality traits, it would be interesting to study the stability of personality traits with the impact of awe (Ajzen, 1987).

Key Research Question 3. To what extent does the emotion of awe aﬀect personality reporting?

Current literature has divergent views with respect to the stability of personality traits. More traditional theory argues that personality change is intrinsic and is therefore relatively stable throughout adulthood, even in the case of a signiﬁcant life event (eg. McCrae and Costa, 1999), but more recent studies found that environment has an impact on the stability of personality traits (eg. Bleidorn et al., 2009; Hopwood et al., 2011).

To address Key Research Questions 1, 2 and 3, this study examines the relationship between the emotion of awe, cooperation and distributional preferences as well as the stability in the measurement of the ﬁve factor personality traits using a laboratory experiment. Participants in the experiment experienced the emotion of awe through exposure to a natural environment setting - a balcony with panoramic views. This study used a 16-round public goods game as a measurement of cooperation, the Equality Equivalence Test (EET) by Kerschbamer (2015) as a measurement of distributional preferences, and collected data of the participants’ ﬁve factor model of personality traits before and after the target experience as a measurement of personality traits stability.

This study found that controlling for other factors, participants in the Walk/Awe treatment group exhibited higher contributions in the public goods game, in other words, higher levels of cooperation than those who were not exposed to the emotion of awe. The awe experience also impacted participants’ prosocial preferences, shown by their x-scores in the EET. A signiﬁcantly positive treatment eﬀect was also found on trait stability in the measurement of agreeableness. In other words, participants in the Walk/Awe treatment group had a positive change in agreeableness compared to participants in the other treatments. Given the fairly well-established positive relationship between agreeableness and prosociality/cooperation in the literature (eg.

3 Habashi, Graziano & Hoover, 2016; Caprara, Alessandri, Giunta, Panerai & Eisen- berg, 2009; Volk, Thoni & Ruigrok, 2011; Carlo, Okun, Knight & de Guzman, 2005; Kagel & McGee, 2014; Koole et al., 2001), this establishes an indirect theoretical link between awe and prosociality/cooperation: awe experiences increase agreeableness, and a greater level of agreeableness increases prosociality and cooperation.

Our study contributes to the current literature in three ways. Firstly, by adding different dimensions into the social function of awe, our results strengthen the theoretical understanding of awe. Using the natural environment and the public goods game as tools confirmed that exposure to awe experiences leads to better cooperation. The results of this study add to the well-established small self hypothesis of Piff et al. (2015), by establishing an indirect relationship between awe and prosociality/cooperation through the personality trait of agreeableness. The theoretical link between awe and prosocial behaviour/cooperation is further bolstered by showing that exposure to awe experiences lead to an increase in agreeableness, which in turn leads to higher prosociality and cooperation.

Secondly, by using a setting in the natural environment to induce awe, our study contributes to the methodology of awe studies. This can overcome the challenge of stimulating the awe experience in a confined experimental environment. Moreover, the sufficiency and pureness of awe elicited in an experimental setting has been limited, although methodologies with highly controlled stimuli such as recalling a past experience and visual imagery (eg. Piff et al., 2015; Prade & Saroglou, 2015) were able to demonstrate the relationship between awe and prosocial behaviour. Utilising panoramic views in a natural setting is worth considering for future research as a natural stimulus, which more closely approximate a real life awe experience.

Lastly, this study of awe and the change in personality traits contributes to both strands of the literature, proposing a connection between the two. Previous research on the emotion of awe has not looked into any possible impacts awe experiences have on stability in the measurement of personality traits. On the other hand, existing literature show the change in personality traits over years, or periods in life, but few have considered the change after a shock event, in a short period of time (within a single day). Our study showed that in the event of an experience that forces adjust- ment of the mental schema, it is possible for the measurement of personality traits

4 to be unstable. Future studies might consider how experiences aﬀect the stability in the measurement of personality traits over short periods of time.

5 Chapter 2

Literature Review

Before investigating further into the behavioural implications of awe, it is important to understand various underlying concepts. This chapter will provide a summary of the literature surrounding the topics of awe, transcendence and emotions. We will also provide literature background to Key Research Questions 1, 2 & 3, including cooperative behaviour, the public goods game, distributional preferences and the stability of the ﬁve factor model of personality traits.

2.1 Introduction to cooperative behaviour and shared intentionality

Humans are fundamentally isolated. We are born alone and will die alone (Gergen, 2009). However, we live in groups, and rely on groups. Homo sapiens are an unusually cooperative species - we are all social and at least minimally cooperative (Sussman & Cloninger, 2011). In fact, cooperative and altruistic behaviours are the glue that underpins the ability for primates and humans to live in groups. There are competing explanations of the cooperative behaviour of human beings. One explanation argues for group selection, where the groups that cooperate outperform selﬁsh groups. An- other position is Tomasello’s theory of shared intentionality. Shared intentionality refers to the collaborative interactions of sharing psychological states with one another (Tomasello & Carpenter, 2007). It could be a shared goal or a shared action. Tomasello’s perspective is based on the assumption that young, human infants’ ability to share interest and attention are much better than that of our nearest primate relatives, chimpanzees. For example, humans are able to communicate in a unique way, based on some shared common ground (attentional frame). Also, humans’ in-

6 tentions are diﬀerent to those of chimpanzees. Chimpanzees engage in cooperative communication as an individualistic means of manipulating others, while for humans we share experience or even helpful information. In addition, humans may collabo- rate just for the sake of collaborating, where chimpanzees do not. Chimpanzees are much more individualistic, even in learning. Humans would engage in demonstrat- ing and imitative learning, in other words, copying others actions. Humans seem to have the ability to see the collaborative structure of this interactive learning. These diﬀerent examples of sharing psychological states is what Tomasello argued to be the foundation of human interactions, including social behaviours.

2.2 Prosocial behaviour and Cooperation

The term prosocial behaviour broadly refers to behaviours that benefit others. Coop- eration refers to the action of two or more individuals helping one another to reach the same end, but at a cost to the individual (Hinde & Groebel, 1991). Both prosociality and cooperation belong to the general category of positive social behaviour, and they both increase others’ positive outcomes (Derlega & Grzelak, 1982). However, the nature of interdependence, and the underlying motivations are two key distinguishing factors . The like nature generally defines prosocial behaviour by its unilateral dependence in contrast to the mutual dependence of cooperation . However, Schwartz and Howard (1982) argue that mutual dependence is central to both, and that the difference is instead in the nature of the jointly determined costs and benefits. Unlike the general view of prosocial behaviour that the costs are borne by the helper and the benefits are gained by the receiver, Schwartz and Howard’s (1982) model proposes that both parties gain rewards and incur costs from their decisions. The helper incurs material or social costs, but potentially gains psychological, social or material rewards. The receiver gains material rewards, but potentially incurs social or psychological costs. In the case of prosocial behaviour where the costs and benefits of both parties are dependent on the other parties’ decisions, this mutual dependency is similar to cooperative behaviour. Cooperative behaviour implies that a person’s decision will affect others, and others decision will affect that person. Whether or not the interests of the person and other parties are correspondent (or aligned), cooperation simply means acting in a way that maximises both the person and the other parties’ interests. Rewards, on the other hand, play an important role in any interdependence situation.

7 Theories generally classify the intention of a social act into exocentric (external rewards) motivation or endocentric motivation (no external reinforcement) (Karylowski, 1982). Yet, largely inﬂuenced by game theory, most theories of cooperation, have focused on the external, situational structure instead of the internal, motivational structure (Derlega & Grzelak, 1982). Psychologists such as Kelley and Thibaut (1978) reinterpreted interdependence, showing that it is not formed by the external structure but the individual perception of the situation, the subjective evaluation of outcome. If in fact the internal structure, is what constitutes interdependence, then the psychological analysis of cooperation and prosocial behaviour are identical. Although the prosocial behaviour and cooperation cannot be integrated directly, Derlega and Grzelak (1982) argue there is a huge overlap in the research domain of the two, and diﬀerence in theoretical approach will gradually converge.

2.3 Relational consciousness

Hay and Nye (1998) introduced the idea of relational consciousness in their book The Spirit of the Child. The term relational consciousness broadly refers to the awareness of our interrelationship with other beings, including people, the environment and also God for religious believers. It is made popular by Hay and Nye’s study into the spirituality of children in the 1990s. There are three central themes: Awareness of here and now, Awareness of value, and Awareness of mystery. It is an experiential awareness, and a feeling of the sensitivity of the connection between all creatures, not merely from an intellectual level. Contrasting to Western individualism, relational consciousness stresses that a person’s primary identity is from their relationship with other beings. There are four key relationships: Self and God, Self and people, Self and World, and Self and Self. In particular, self and people is about interpersonal relations, and self and world is about the sensitivity of beauty and nature. ‘Worldly’ possessions are relatively less important under this concept, and supernatural, spiritual or nonmaterial realities are all important as a part of our knowledge. In fact, diﬀerent people have diﬀerent contexts for their relational consciousness (Hay & Nye, 1998). To many, relating to the natural world is a common context - they experience wonder and meaning in connecting with the world. Hay (2000) believes that relational consciousness is a biologically inbuilt aspect which underlies every altruistic behaviour. When the psychological distance between the self and reality is shortened or disappears, they realise they are an inextricable part of the manifold reality (Hay & Nye, 1998). This sense of shared humanity, a perception of self at one with all

8 mankind, can help explain prosocial behaviour and cooperation, as relational consciousness by deﬁnition is always concerned with self-transcendence.

2.4 The emotion of awe

Early examples of awe can be found in sociology, philosophy, and religious texts. Ref- erences of awe can be found in many religious texts, for example in the Bible:

“When Jacob awoke from his sleep, he thought, Surely the Lord is in this place, and I was not aware of it. He was afraid and said, How awesome is this place! This is none other than the house of God; this is the gate of heaven. (Genesis 18:16-17, New International Version)

In sociology, Emile Durkheim (1972) brought into attention the impact of powerful emotions on political, social and religious movements. He proposed two classes of emotions by their social eﬀects, the ﬁrst, such as love, fear and respect binds individuals together. The second is collective sentiments that possess transformative powers and bind individuals with social entities, closely resembling awe:

“Following the collectivity, the individual forgets himself for the common end and his conduct is directed by reference to a standard outside himself.” (Durkheim, 1972, p.228, as cited in Keltner & Haidt, 2003).

An important record of awe in philosophy is Irish philosopher Edmund Burke’s deﬁni- tion of the sublime, an aesthetic experience similar to awe. In his book A Philosophical Enquiry into the Origin of Our Ideas of the Sublime and Beautiful, Burke proposed two key properties to the sublime - power and obscurity. He also suggested thun- derstorm, art, symphony as stimuli, bringing a wider perspective into the aesthetic emotion.

More recent studies on awe have emerged around 2000, and the study by Keltner and Haidt (2003) well deﬁnes it. Keltner and Haidt (2003) describes awe as the emotion a lower status individual feels towards a more powerful other. They stated that perceptual vastness and a need for accommodation are two central themes and conditions for a state of awe. Perceptual vastness refers to the encounter of something tremendous in size, number, scope, complexity, power, ability, social bearing, or

9 greater than one’s frame of reference in general (Rudd, Vohs & Aaker, 2012; Stellar et al., 2018). Without perception of vastness the emotion becomes admiration instead of awe. Accommodation, on the other hand, is the Piagetian process of adjusting mental structures which could not otherwise assimilate this new experience (Keltner & Haidt, 2003). Awe challenges our mental structures as we fail to make sense of the experience. Stellar et al. (2018, p.260) defines the need for accommodation as the process by which a person revises his or her mental schemas or creates a new one to account for the deviation between the stimuli and one’s current understanding of the world. If one fails to understand and satisfy the need for accommodation, the awe experience can be terrifying. Contrarily, the awe experience can be enlightening if one is successful in satisfying the need for accommodation. The two are interconnected to expand one’s usual frame of reference, stimulating new mental models (Rudd et al., 2012; Shiota et al., 2007). Lazarus (1991) describes awe as ambiguous as it can either be positive or negative. An awe experience floods consciousness rapidly but it can be ‘switched off’ by diverting attention (Konecni, 2005). Awe usually also includes the factor of unexpectedness, or surprise (Colantonio & Bonawitz, 2018). Frijda (1986) believes this sense of wonder is a passive, receptive mode of attention in the presence of something unexpected. It involves a sense of suspense, interesting, and pleasing degree of risk (Konecni, 2005). However, the individual’s existential security cannot be threatened. In that moment one is overwhelmed but is still safe.

Awe has certain distinctive features in diﬀerent aspects. People in experience of awe involves pulling their lips apart, dropping their jaws and stretching their mouths (Campos et al., 2013). Shiota, Campos and Keltner (2006) also found facial displays of slightly raised inner eyebrows, upper lid raise, and raised head and eyes. Physically, goosebumps are commonly observed (Maruskin, Thrash & Elliot, 2012). Vocal displays is another aspect to distinguish awe from other emotions, where Simon-Thomas et al. (2009) discovered vocal bursts unique to awe.

Experiences of awe also brings various psychological and epistemological consequences or beneﬁts. Griskevicius, Shiota and Neufeld’s (2010) study revealed that awe increases people’s ability to systematically process information-rich stimuli (Zhang & Keltner, 2016). Berger and Milkman (2010) tested and proved the virality of videos involving high arousal of awe based on the assumption that awe stimulates curiosity and interest. Saroglou, Buxant and Tilquin (2008) and Valdesolo and Graham (2014)

10 found that participants primed with awe were more likely to endorse spiritual and supernatural beliefs. In addition, they show greater spiritual eagerness, shown by their desire to visit a spiritual destination rather than a hedonistic one (Van Cappellen & Saroglou, 2012). More recently, Chirico et al. (2018) showed that awe enhances creative thinking. Awe expands mental frames, and enables people to ﬁnd new con- nections among objects and ideas.

In addition to being a stimulus-oriented emotion, from another perspective, awe is a collective emotion which brings about certain cognitive and behavioural tendencies and transformation of the self, which binds the individual with broader social entities and engage in collective action (Keltner & Haidt, 2003; Piff et al., 2015). In the state of awe, individuals develop stronger interest and connectedness with the world around them. In other words, greater relational consciousness, and less focus on their self-interest and personal goals (Keltner & Haidt, 1999; Zhang & Keltner, 2016; Stellar et al., 2018; Colantonio & Bonawitz, 2018). In that moment, people forget momentarily their individual identity, the thoughts that were occupying their mind, where they are and what they are doing afterwards (Stegemoeller, Quinn & Graupmann, 2016). The emotion of awe draws attention away from one-self unlike many other emotions, and shifts attention towards the needs and concerns of others (Piff et al., 2015; Stellar et al., 2017). Awe could lead to lower ego defensiveness and even a shift in one’s self-concept (Stellar et al., 2018). Although awe stimuli like natural wonders, panoramic views, music and art are asocial in nature, experience of awe also brings along the drive to treat others better. It could then lead to prosocial outcomes, such as increased sharing, assistance and generosity (Shiota et al., 2007; Piff et al., 2015; Stellar et al., 2018). Piff et al.’s (2015) study found that awe arouses prosocial tendencies. Individuals who experienced awe were found to be more generous in a dictator game, and also exhibit greater ethicality and de- creased entitlement. Prade and Saroglou (2015) found the induction of awe leads to increased helpfulness and generosity in daily settings. In Stellar et al.’s (2018) study, they found that the diminished self led by awe brings greater humility. The trait of honesty-humility can then lead to higher cooperation in economic games in Hilbig and Zettler’s (2009) study. Rudd et al. (2012) found that awe expands time perception and reduces impatience. People are also more willing to volunteer their time helping others and they even get a momentary boost in life satisfaction. Following the proven linkage between awe and prosociality, Yang et al. (2015) hypothesized that the sense of small self can reduce aggression. Although the casual relationship through

11 small self to reduced aggression has not been proven, Yang et al. (2015) nonetheless had shown that awe has a mediating effect on aggression. Another study by Koh, Tong and Yuen (2019) found that awe has a buffering effect towards possession loss. The recent research on awe raises the question of how to elicit awe, and eliciting an adequate amount of awe in experimental settings. Keltner and Haidt (2003) listed five criteria that could lead to awe: beauty, ability, virtue, threat and supernatural ability. Stellar et al. (2017) believes the largest category of awe elicitor to be other focused appraisals, which relates to the physical and psychological actions of others. Shiota et al. (2007) find that feeling awe towards another person enhances group co- hesion through devotion and commitment to the leader and group, and also through creating feelings of interconnectedness and common humanity. The second largest category following would be nature. Shiota et al. (2007) believe that nature scenes brings a feeling of smallness to an individual. In nature, people feel connected to the surrounding world, forget their day-to-day concerns and they would wish to prolong and memorise the experience.

The first approach to inducing awe in laboratory settings is personal narratives. Sh- iota et al. (2007), Rudd et al. (2012) and Piff et al. (2015) all employed a priming method to elicit awe by asking participants to recall a personal experience of awe, either verbal or written. However, the biggest problem with priming is the emotional intensity when recalled compared to the original experience, especially with awe being a complex emotional state. The second approach is using visual imagery of images and videos: for example, the use of videos, images of waterfalls, animals and even astronauts in space in Rudd et al. (2012), Van Cappellen and Saroglou (2012) and Piff et al.’s (2015) studies. The clear advantage of this method is the standardised and highly controlled stimuli, however, the intensity of the emotions induced is still under question. The third method is to situate participants in natural awe-inspiring environments. Examples include Shiota et al. (2007) asking participants to look at a full-sized replica of a Tyrannosaurus rex skeleton for a minute, and Piff et al. (2015) asking participants to stare at a grove of tall eucalyptus trees for a minute. This method avoids the above limitations, but it is necessary to control for any possible factors of influence. A more recent step forward is Chirico et al.’s (2017) use of immersive videos using Virtual Reality (VR). The use of VR brings greater intensity, further reaching the expectancy violating nature of awe. It also allows experimenters to test different subcomponents of awe. However, this methodology is still in its preliminary phase and needs further empirical testing. Overall, the ongoing challenge of

12 eliciting awe in experimental settings is ﬁnding a stimulus that generates a suﬃcient intensity and a pure measure of awe.

2.4.1 Self-transcendence

A concept closely related to awe is self-transcendence (also known as spiritual transcendence). Not only are these two emotions’ definition and theoretical construct similar, their research findings are also similar (Landis et al., 2009). Piedmont (1999, p.4) describes spiritual transcendence as “The capacity of individuals to stand outside their immediate sense of time and place to view life from a larger, more objective perspective”. Transcendence is also a fundamental capacity of a person, and this innate motivation drives and directs our decision-making. According to Deikman (1982, p.21), transcendent experiences takes one momentarily into a mystical consciousness which “involves a different perspective on time, causality, and self - a different reality, considered from our ordinary point of view”. Similar to awe, self-transcendence involves a subjective experience of self loss and dissolution of the body sense (Yaden et al., 2017). It involves two subcomponents, annihilation and relation. During self- transcendent experiences (STEs), the sense of self could disappear. It leads to a reduction of self-centredness and selfish motivations. The experience may also bring an increase in the sense of interpersonal connectedness. From the transcendent perspective, an individual discovers fundamental unity between beings, with a feeling of greater bonding with others (Piedmont, 1999). They realise the synchronicity to life, leading to a sense of commitment to others. According to Yaden et al. (2017), the enhanced sense of social connection occurs via two major mechanisms. Firstly, neuropeptides such as oxytocin and vasopressin, together with alterations to parasym- pathetic activity and vagal tone, increase the level of self-other overlap. Second, STEs may increase social-cognitive processes. Interpersonal connection is potentially enhanced through perceived similarity, leading to increased prosociality and possibly societal well-being. Transcendent experiences can also lead to enhanced psychological functioning and integration and manifestation of the world (Waldron, 1999).

Past studies have looked at self-transcendence from diﬀerent perspectives. The two major deﬁnitions of self-transcendence are by Reed (1991, 2003) and Tornstam (1996, 1997). According to Reed (2003), self-transcendence is the “ability to expand self- boundaries intrapersonally (toward greater awareness of one’s philosophy, values, and dreams), interpersonally (to relate to others and one’s environment), temporally (to

13 integrate one’s past and future in a way that has meaning for the present), and transpersonally (to connect with dimensions beyond the typically discernible world)” (2003, p. 147). Although Reed’s definition has been evolving since 1991, his main idea is that self-transcendence influences a person’s relationship with self, others, the outside environment and unseen cosmic forces. Meanwhile, Tornstam’s (1996) perspective draws similarities with Reed’s theory. He describes self-transcendence as “a shift in metaperspective, from a midlife materialistic and rational vision to a more cosmic and transcendent one, accompanied by an increase in life satisfaction” (p.38). Earlier studies such as Frankl (1966), who referred to self-transcendence as a prioritization of other people over self-focus, and Erikson (1982), who described self- transcendence as a non-egocentric understanding of the world, have laid the forefront foundation of the study of self-transcendence. Considering behaviour philosophies such as patriotism, altruism and secular humanism, all of them can be viewed as alternative expressions, or outlets of our innate motivation of transcendence (Piedmont, 1999). They all require individuals to sacrifice their personal benefits for the greater benefit of the society. The reason behind these appeals unquestionably relates to our intrinsic motivation of searching for deeper sense of meaning and motivation.

In fact, Maslow (1969) over the years has recognised self-transcendence as a part of Maslow’s hierarchy, beyond self-actualisation. He defines it as “seeks to further a cause beyond the self and to experience a communion beyond the boundaries of the self through peak experience”, and he calls this special cognitive activity as “being- cognition”. He argues that a developed and fortunate human being seeks to go beyond self-actualization and looks for benefits beyond the pure personal. Through mystical/transpersonal experiences, or engaging in services to others, a person iden- tifies with something greater than the self. Differences between self-actualization and self-transcendence, as Maslow explains, is that the former is self-oriented and the latter is others-oriented. Self-actualization is the working to actualize one’s potential, whereas self-transcendence puts aside personal needs to help others, or with reasons outside the personal self. Decades later, Maslow (1993) found that not only self- actualizing, fortunate beings can transcend, but in fact people who has not reached the self-actualization stage can also transcend. He said that many individuals have transcendent experiences regardless of their position on the hierarchy: self-actualizing individuals may or may not have peak/transcendent experiences, and individuals who have peak/transcendent experiences may or may not be self-actualizing.

14 This humanistic and transpersonal approach to psychology was developed from the 1960s, and Abraham Maslow was one of the pioneers in this field. He addressed the importance of peak experiences in various papers and lectures in the 1950s and 1960s, which include for example mystical experiences, aesthetic experiences, and emotional experiences involving nature. Over the years, spiritual transcendence and the field of transpersonal psychology have been largely ignored by conventional psychology (Frankl, 1966). Transcendence, however, is an integral part of our ability to create meaning which has an important impact on societal well-being. Pargament and Mahoney (2005) found that spirituality affects mental health, drug and alcohol use, marital functioning, parenting, stress, as well as morbidity and mortality. Comparing to other strivings, spiritual strivings were found to be more highly correlated with measures of well-being in Emmons et al.’s (1998) study. Psychologists found that those with a positive perception of an external agency report higher levels of personal well-being (Kirkpatrick & Shaver, 1992; Pargament, Smith, Koenig & Perez, 1998; Pollner, 1989). In comparison, those with a more negative or punitive views of the external agency report greater psychological distress (Pargament et al., 1998; Schwab & Petersen, 1990). Spirituality is also a cultural fact. According to Pargament (1999, p.12), spirituality is defined as a search for the sacred. It is centred around perception of the sacred, and covers different approaches of spiritual expressions. The search for the sacred is a common desire across different countries, cultures and ethnic back- grounds. It is a highly individualized process of discovering, conserving, and rediscovering. It should be noted that this process is not without risks, and some fail in the search. Yet, for many people, the search gives them better understandings of themselves, better relationships with others, and a greater feeling of interconnectedness. It is also important to note the differences between transcendence and religiousness. Piedmont (1999) believes that the scope of transcendence is larger than religiousness, including a broader domain of motivations. Some fundamental elements of transcendence includes connectedness, universality, prayer fulfillment, tolerance of paradoxes, non-judgementality, existentiality and gratefulness. For example, universality is referred to as the unitive nature of life, and prayer fulfillment is the feelings of joy and contentment that result from personal encounters with a transcendent reality (p.5). In addition, Piedmont states that self-transcendence is a personal journey searching for larger sacredness, where religiousness has a more social approach.

The question then extends to when this journey of searching for the sacred starts. In many diﬀerent studies including Coles (1990), children are found to be spiritual

15 pilgrims. Although Goldman (1964), for example, questioned children’s ability to comprehend religious abstractions, social scientists have found many cases of children seeking the divine (Pargament & Mahoney, 2005). There are diﬀerent explanations for children spirituality. Some suggests that it is innate and genetic - children are born with this desire, or the perception of external agency is embedded in a child’s intrapsychic capacity (Bouchard et al., 1990; Rizzuto, 1979). Some argue that spiritual desire comes from challenges in life where human limitations are exposed (Pargament, 1997). Others such as Kaufman (1981) highlight the role social context plays as the child grows. It is important to note that the search for the sacred is an unending process in a person’s life (Pargament & Mahoney, 2005).

An important issue regarding transcendence is the lack of a comprehensive, orga- nized paradigm, resulting in a conceptual disarray in the ﬁeld. Apart from Maslow’s inclusion of transcendence into his hierarchy of needs, Piedmont (1999) proposed that spiritual transcendence is the sixth factor of human personality, extending from the Five Factor Model (FFM). Although there are parallels between transcendence and the personality domains of extraversion, openness and agreeableness, the theoretical construct of transcendence also contains solitude, simplicity and structure. In short, the above domains embody some qualities of transcendence. There lacks a separate measure of transcendence, and thus supports the case for transcendence to be an individual domain of personality. Piedmont points out that having transcendence as the sixth personality factor helps us understand why people seek transcendence, and how we interact with ourselves and other beings.

2.4.2 Individual diﬀerences in experiences of awe

Known as an aesthetic emotion, the emotion of awe is closely connected to amazement, elevation, fascination, and wonder (Silvia, Fayn, Nusbaum & Beaty, 2015). However, different individuals have different tendencies in enjoying these aesthetic experiences. One possible explanation for the heterogeneity in awe-proneness is the difference in personality traits, and psychologists such as Silvia et al. (2015) inves- tigated into whether individual differences in the Five Factor Model of Personality (FFM) accounts for any difference in awe-proneness. One factor in particular, Open- ness to Experience, draws similarities with the emotion of awe in construct. Added to the FFM by Costa and McCrae (1980), it is the least understood and most dis- puted personality factor of the five, involving scholarly debates over the past decades

16 regarding its construct. Commonly deemed as an intrapsychic dimension, McCrae (1994) proposed that Openness to Experience has a broad construct that includes re- ceptivity to many varieties of experience and a permeable structure of consciousness. Openness also implies welcoming of new input, which could be sensory, cognitive or aﬀective. Open people are often curious, independent thinkers who are sensitive to aesthetics (McCrae & Costa, 1997). In fact, Silvia et al. (2015) proposed Openness to Experience as an aesthetic trait. Instead of being passive receivers of new experiences, they are characterised by an active pursuit of novelty, which Canaday (1980, p.5) describes as a quest to “clarify, intensify, or otherwise enlarge our experience”. Open individuals are also likely to be reﬂective and thoughtful about the experience.

Unsurprisingly, Silvia et al. (2015) found that Openness to Experience has the strongest positive correlation with awe-proneness. People who score high in this factor experience a wider range and complexity of emotions, feelings and thoughts, and tend to be more creative (McCrae & Costa, 1997; Terracciano, McCrae, Hagemann & Costa, 2003; Kaufman, 2013; Nettle, 2009; Swami & Furnham, 2014). Those who are lower in this factor experience a narrower, simpler range of emotions, and tend to be more factual, practical and down-to-earth. Other possible hallmarks of openness include tolerance of ambiguity, emotional ambivalence, and perceptual synathesia, potentially leading to a greater capacity for absorption. McCrae & Costa (1997) also ﬁnds that open individuals have more artistic and investigative interests, often shown by their appreciation of arts, and they tend to make more mid-career shifts. It therefore implies that those who are higher on the particular factor of openness to experience are more likely to experience aesthetic emotions, including awe.

The other important factor aﬀecting awe-proneness is religion. Awe has an essential role in religious and spiritual experiences, and many early records of awe were found in religious texts, such as the Mahabarata in the Hindu Itihasa and the Bible, where the characters experience an encounter with a greater power (Keltner & Haidt, 2003). This strong, overwhelming sensory experience not only lead to confusion and amazement, it also led to a transformation. Closely related with concepts such as spirituality and transcendence, it is reasonable to assume some level of relationship between religion and awe. For example, Van Cappellen and Saroglou (2011) found that induction of awe endorses spirituality for religious individuals, and Valdesolo and Graham’s (2014) study which found that induction of awe endorses supernatural

17 control and belief in God. Zhang and Keltner (2016) suggests that awe activate religious feelings, spiritual desire, and a belief in supernatural forms. However, contrary to the stereotypical belief that non-religious individuals are less awe-prone, recent studies such as Caldwell-Harris et al. (2011) suggest that atheists also seek and value experiences of awe and wonder. Findings by Caldwell-Harris et al. (2011) shows that although the notion of a transcendent entity is rejected by most atheists, they embrace the use of spirituality in psychological and experiential contexts. Overall, there is little consensus in the literature on whether religious individuals are more prone to experiencing awe.

2.5 Somatic Marker Hypothesis

Most neo-classical economic theories largely neglects the role emotions play on decision- making (Bechara & Damasio, 2005). Decision-making was traditionally viewed as a cognitive process, one of choosing the best actions to maximise utility through eval- uating the consequences of each action (Loewenstein & Lerner, 2003). The economic assumption of rational maximisation expects individuals, knowing the possible outcomes, to make rational decisions that are logical and consistent. In the 1960s, critiques of the traditional decision theory focused on the people’s cognitive errors and the heuristics that are involved. However, in recent decades, research began to question whether emotional processes, aside from cognitive processes, guide decision making. A famous example from neuroscience and psychology is the Somatic Marker Hypothesis (SMH), introduced by Damasio (1994) in his book Descartes’ Er- ror (Bechara et al., 1994, 1997, 1999, 2000). Damasio proposed that decision-making processes are aﬀected by marker signals, brought by emotions and feelings, providing a neuroanatomical and cognitive framework of emotions’ impact on decision-making (Bechara, 2004). According to Damasio (1994), somatic markers are instances of feelings generated from secondary emotions, and are bodily states that correspond to emotional reactions to diﬀerent possible courses of action. On a conscious level, somatic states would mark outcomes of responses as positive or negative, where sub- sequent decisions of avoidance or pursuit are based on. Through learning, emotions and feelings are connected to predict future outcomes of certain options or scenarios. These somatic states are generated by the neural machinery, which we were born with, in response to stimuli. During education and socialisation, our brains connects certain stimuli with certain somatic states, creating somatic markers that we use for rational decision-making based on secondary emotions. This hypothesis also argues

18 for the importance and potential beneﬁts of emotions in decision-making.

The hypothesis is originated from Bechara et al.’s (1994) study into patients with a frontal lobe damage, especially to the Ventromedial prefrontal cortex (VMPC). The original experiment compares the skin conductance responses (SCRs, which in this case is used as an index of the activation of somatic states) between patients with frontal damage and normal individuals, in a setting where they view a set of projected slides (Damasio, 1994). Most of the slides are banal, but every once in a while there would be a disturbing slide. They found that normal individuals generated SCRs when the disturbing pictures are shown, but not the bland pictures. On the other hand, patients with a frontal lobe damage did not generate any SCRs to any pictures throughout the entire set of pictures. Although those patients are attentive in the entire experiment and possess factual knowledge, Damasio (1994) believes and suggests that they failed to produce a somatic state, and that is the reason they failed to feel the disturbance from the pictures.

Extending from this experiment, Damasio and colleagues sought to discover whether and how this lack of somatic markers aﬀect decision making, through the Iowa Gam- bling Task (IGT). The task requires participants to choose between four decks of cards. Each deck contains cards of reward or punishment. Some decks will contain more reward than punishment, hence the good deck’, and some decks will contain more punishment than reward, hence the bad deck’. The majority of normal, healthy participants were able to choose the good decks’ over the course of the game, however, participants with a damaged VM were found to be incapable of avoiding the decks that lead to serious monetary losses - they tend to cling to the bad decks’. In other words, they are unable to learn from their mistakes, bringing negative consequences (Bechara et al., 1994). Their behaviour in the IGT resembles their behaviour in real- life. Although these patients have normal intellect and normal results in standard neuropsychological tests, damage in their VMPC impairs their decision-making on both personal and social level. In other words, abnormalities in their emotions and feelings, in particular their failure in registering losses, damage their decision-making abilities.

Maia and McClelland (2004) carried out a replication of Bechara et al.’s (1994) study, suggesting diﬀerent interpretations and raising several questions regarding the SMH. Firstly, Maia and McClelland suggest that VMPC patients’ performance in the IGT

19 could be due to an inability to reverse a learned contingency (Bechara et al., 2005). They found that a vast majority of participants who behaved advantageously also possess conscious, reportable knowledge of the advantageous strategy, which they argue provides suﬃcient basis for their decisions. Therefore Maia and McClelland do not believe Bechara et al.’s (1994) claim of nonconscious biases that guide behaviour before conscious knowledge does. Maia and McClelland also questioned Bechara et al.’s (1994) claim that anticipatory SCRs reﬂect somatic markers. They believe that the higher SCRs correspond to the higher variance in the bad decks, but not neces- sarily to the negative outcomes, or negative somatic states. Bechara et al. (2005) disagree with the above arguments, stating that the important notion of the SMH is to address the possible physiological processes between knowledge and behaviour, and to highlight the role of emotions, whereas consciousness is relatively less important. Although the SMH is frequently under question, by bridging the mechanisms of conditioning and cognition, the pioneering hypothesis still provides great insights into the understanding of decision-making and reasoning processes.

2.6 Stability of the Big Five Personality Traits

In recent years, personality has attracted more attention in economics. Economists view it as a type of non-cognitive skill, and it aﬀects the economic decisions individuals make and therefore the outcomes (Cobb-Clark & Schurer, 2012). Past literature has mixed debates regarding the stability of personality traits, and whether personality development is mainly driven by exogenous or endogenous factors. The original Five Factor Theory by McCrae and Costa (1999) suggests that personality traits are essentially temperaments - they remain stable in adulthood and are unaﬀected by the external environment. The Five Factor theory states that traits are shaped by biological (intrinsic) maturation- they develop through childhood, mature at adulthood, and are thenceforth stable. It implies that genetic factors are the major determinants of personality development, not external environments or experiences (eg. McCrae and Costa, 1999). Costa et al. (2000) argues that changes in personality traits are subtle, whether it is led by an intrinsic process or various environmental factors. Per- sonality remains largely resilient even in the case of a life event, regardless positive or negative. Most empirical studies into the economic returns of personality also make the same assumption.

However, in the case that personality traits are not in fact stable over time, results

20 can be biased. Many longitudinal studies showed that personality traits change in mean-levels throughout the entire lifetime (eg. Haan, Millsap, & Hartka, 1986; Hel- son & Moane, 1987; Helson & Wink, 1992; Roberts, Caspi, & Moﬃtt, 2001; Robins, Fraley, Roberts, & Trzesniewski, 2001). Contrary to McCrae and Costa’s (1999) theory, some studies found that the change in personality traits also occurs in middle and old age (Helson, Jones, & Kwan, 2002; Helson & Kwan, 2000; Srivastava, John, Gosling, & Potter, 2003).

There are models that look at the role of other factors in the development of personality traits. For example, Zelli and Dodge’s (1999) model looks at the role of environment and proposes that personality consistency comes within social roles, through a person’s interactions with the social environment. A similar set of developmental model such as Levinson’s (1978) highlights the interplays between the traits and contexts of life. The model emphasises the building of life structures, which represents the relationship between self-driven goals and societal and age-graded roles. Another model by Baltes (1997) and Baltes, Lindenberger and Staudinger (1998) focuses on adaptation. Taking a life span development approach, it proposes that we humans are open systems, and we demonstrate both continuity and change in personality across the whole of our lifetime. More recently, Roberts and Caspi (2003) introduced a similar alternative to Baltes’s (1997) approach, stressing the importance of identity processes in explaining the continuity and change in personality. This theory states that as we get older, we become more capable at interacting with the environment in ways that lead to consistency of personality. To put differently, development of a person’s identity is clearer and strengthened with age, thus explaining the increasing continuity of traits. In addition, commitments to social institutions, such as work and family, which provide a sense of identity, facilitates psychological maturity. Recent studies such as Bleidorn et al. (2009) and Hopwood et al. (2011) have found both genetic and environmental influences on the stability of personality. According to Roberts, Wood and Caspi (2008), people have different preferences and perceptions regarding their environments. Individuals also change environments to suit their per- sonalities. This model of person-environment transactions focuses on the impacts of social roles, normative changes and major life events (Specht, Egloff & Schmukle, 2011).

The concept of personality change is multifaceted. There are two main measures of change in the literature, mean-level change and rank-order changes. Mean-level

21 stability is also known as normative or absolute change, representing shifts of groups of people to higher or lower values over time on a specific trait (Specht et al., 2011). Rank-order stability, also known as differential stability, is the degree of consistency in the rank ordering of individuals over time on a given trait (Hopwood et al., 2011). To put differently, it is whether groups of people maintain their relative placement over time. There are studies that look for the developmental course of personality perceptions, for example, Cobb-Clark and Schurer (2011) showed that personality is relatively stable across a 4 year period for working-age adults. Numerous studies have looked into whether major life events and experiences change personality traits, but the results are mixed. For example, Bleidorn, Hopwood and Lucas (2018) and Specht et al. (2011) support the claim, but Costa et al. (2000) and Sutin et al. (2010) rejects it.

2.7 Factors aﬀecting Public Goods Game Contri- bution

The public goods game is a widely used experiment exploring cooperation in economics. There are many other factors affecting the level of cooperation in this social dilemma game, and it is important to consider these factors when designing the experiment and carrying out analyses. The first group of factors is individual differences. Differences in social motives exist, where people can be categorised into types of individualistic, competitive and cooperative (Kuhlman & Marshello, 1975). Cooperators often consider from the viewpoint of the group, while individualists think more ego- centrically, from the standpoint of their individual rationality. Differences in social motives not only associate with different choice behaviour, but also relate to different perceptions of rationality and intelligence (Kopelman, Weber & Messick, 2002). Cul- ture also plays a part in this context, where people from individualistic cultures tend to be more task-oriented, fixated on their personal goals, whereas people from collec- tivist cultures tend to cooperate with those in their in-group, but compete with those perceived as their out-group. However, the influence of culture on social motives is complex, for example, Gärling’s(1999) study found that not all cultural values have a direct relationship with social motives. For gender, although its impact in social dilemma games has not been widely studied, it could impact cooperation as male and female differ in understanding, reacting and responding to actions, resources, group interactions and discussions (Stockard et al., 1988; Cadsby & Maynes, 1998; Sell et

22 al., 1993). Van Lange et al. (1997) found a weak but reliable relationship, where the percentage of prosocials is higher in female than in male, and the percentage of pros- elves is higher among males. Yet, the findings by different public goods games studies showed mixed results: the effect of gender on cooperation is likely to be unpredictable and weak. The impact of religiosity and ethnicity on public goods experiments have also been studied. Religion has long been believed by social scientists as a key factor of determining behaviour and outcomes. However, studies such as Anderson, Mellor and Milyo (2010) found little correlation between religious affiliation and contributions in the public goods game. Ethnic diversity, on the other hand, has a negative impact on public goods provision, and this finding is largely accepted in the literature (Banerjee et al., 2005). However, the overall empirical results on social heterogeneity’s impact on cooperation is mixed. Bardhan and Dayton-Johnson’s (2002) study and Cardenas’s (2000) field study finds that economic heterogeneity inhibits cooperation, but a general consensus in the field is still lacking.

The second group of factors is the decision structure of the task. Literature shows that the monetary payoff structure of the task, including rewards and punishments, affects individuals’ decisions. While Gächter and Fehr (1999) took a step forward and studied the effect of social rewards, they found the effect social approval has on contribution in collective actions to be insignificant, in a situation where the participants are strangers to one another. However, if group identity is created, forming weak social ties and reducing social distance, it may act as a “lubricant” for social exchange and thus reduce free-riding. On the other hand, uncertainty makes cooperation more difficult in most cases. Young (1994) argues that uncertainty strengthens coalitions, other studies such as Iida (1993) argues that uncertainty weakens coalitions, while Burger and Kolstad (2009) found no effect on coalition size. However, most studies such as Burger and Kolstad (2009) found that uncertainty hinders cooperation, and in environmental contexts, uncertainty impedes the emergence and sustainment of a common resource (Agrawal, 2002; McCay, 2002).

The third group of factors is the social structure of the task. Firstly, the ﬁnding that groups with the same individuals, interacting repeatedly, have higher tendencies to cooperate than groups that are shuﬄed every round is fairly well-established (Keser & van Winden, 2000). This ties into the previous conclusion regarding social distances. Apart from that, power and status, group size and communication are all possible factors in social dilemma settings. Mannix (1993) argues that power imbalances in

23 groups will cause group members to focus on protecting their self-interests rather than mutual gains, and even form coalitions. Members of these groups are also likely to retaliate and behave competitively. In relation to leadership and administration in commons-related decisions, Wit and Wilke’s (1990) study explored the role of who, and to whom, were the rewards and punishment presented. For the undergraduate participants, whether the rewards or punishments were presented by the government or by their parent companies, they found no differences between the effectiveness of the two. Whereas for the managers, rewards presented by their parent companies were effective, and those presented by the government were counterproductive. The results from this study raise the question regarding the source of rewards and sanc- tions and their impact on potential decision-makers. In addition, small groups are usually more cooperative than larger groups. Kerr (1989) offered an explanation that small groups have higher self-efficacy than larger groups: smaller groups were found to be higher in self and collective efficacy than larger groups when the provision point is low. Allison et al. (1992) suggest that small groups often divide resources more equally. Yet, Isaac et al.’s (1994) findings contradicted this proposition, where Issac and his colleagues found that groups of 40 and 100 provided the public good more efficiently than groups of 4 and 10. While this violates the standard game theoretical model, Ledyard’s (1993) alternative approach serves as another possible explanation, proposing that individuals obtain satisfaction (a warm glow) from being a part of a cooperative group. For communication, its positive effects on cooperation are widely confirmed in the literature. Bohnet (1999) found that not only two-way communication, but one-way communication is sufficient to enhance cooperation. However, the underlying reasoning of communication’s effect on cooperation is still under debate. Both attempts to the answer to that discussion creates group identity and fosters commitments to cooperate were proven insufficient by Kerr and Kaufman-Gilliland (1994) and Bouas and Komorita (1996). The form of communication also makes a difference, where Frohlich and Oppenheimer (1998) study on emails versus face-to-face communication found no differences in simple tasks, but in more complex tasks, face-to-face communication leads to greater cooperation. It provides implications for researchers regarding the choice of communication medium in the provision of common resources.

The fourth set of factors is perceptual factors, for example, framing. Kahneman and Tversky’s (1979) famous Prospect Theory states that the description of the outcome as a gain or a loss can aﬀect people’s decisions, as people have diﬀerent risk attitudes towards gains and losses. Describing the task as a Business Transaction

24 Study instead of social exchange, as found by Batson and Moran (1999), also changes people’s cooperative behaviour. Van Dijk and Wilke (2000) suggests that even simply describing the choices as taking, keeping, leaving or giving changes people’s other- regarding preferences and therefore the decisions they make (Kopelman, Weber & Messick, 2002).

Some additional factors such as other-regarding behaviour can also play a role in aﬀecting people’s cooperative behaviour. Reciprocity and social history, for example, is an important consideration for many individuals (Kopelman, Weber & Messick, 2002). People evaluate others’ behaviour before making their decisions: if they behave cooperatively, then so will I.

2.8 Distributional preferences

The neo-classical economics assumption is that agents’ decisions are entirely driven by selfish motives. However, psychologists and economists have realised that this assumption does not reflect the reality of micro-level decision-making. In reality, many agents take into account of other agent’s payoff in their decision-making. Re- sultantly, researchers proposed models of other-regarding preferences, for example, unselfish and altruistic behaviour (Becker, 1974; Andreoni & Miller, 2002), where a decision maker’s utility increases as the payoff of others increases, efficiency loving and surplus maximising (Engelmann & Strobel, 2004), where the decision maker looks to maximise the sum of payoffs, inequality aversion (Fehr & Schmidt 1999; Bolton & Ockenfels, 2000), difference aversion (Charness & Rabin, 2002; Fisman et al., 2007) or egalitarian (Dawes et al., 2007; Fehr et al., 2008), where fairness motives play a part, or oppositely equality aversion (Hennig-Schmidt, 2002; Charness & Rabin, 2002; Fershtman et al., 2012), maximin (Engelmann & Strobel, 2004), Rawlsian (Charness & Rabin, 2002) or Leontief preferences (Andreoni & Miller, 2002), maximising the minimal payoff in the group, spiteful (Levine, 1998), competitive (Charness & Rabin, 2002) or status seeking (Duesenberry, 1949), where an agent’s utility decreases as the payoff of others increases, envious (Bolton, 1991; Kirchsteiger, 1994; Mui, 1995), which is similar to a spiteful agent, but an envious agent’s utlity is unaffected by the payoff of agents. However, there is little agreement in the literature on the list of distributional preferences, and these models require strong structural assumptions. Nevertheless, the behavioural implications of distributional preferences are proven in different aspects of decision making. such as donation (Derin-Gure & Uler, 2010;

25 Kamas & Preston, 2015), bargaining (Bolton, 1991; De Bruyn and Bolton, 2008), voting (H¨ochtl, Sausgruber & Tyran, 2012; Paetzel, Sausgruber & Traub, 2014; Fis- man, Jakiela & Kariv, 2015), public goods contributions (Oﬀerman, Sonnemans & Schram, 1996), competitive behavior (Balafoutas, Kerschbamer & Sutter, 2012), bidding in auctions (Flynn, Kah, & Kerschbamer, 2016; Bartling, Gesche, & Netzer, 2017), provision in credence goods (Kerschbamer, Sutter & Dulleck, 2017).

2.9 Gender diﬀerence in Behavioural and Experi- mental Research

Males and females are fundamentally different in their biological and social roles. The biological theory explains the gender differences in personality traits by the difference in hormones, and genetic predispositions. Social psychology theory focuses on the difference in social roles (eg. Eagly 1987). For example, males are often expected to be the initiator in mate choice settings, and therefore should exhibit higher levels of aggression and assertiveness (Trivers, 1972; Buss, 2008). Females, on the other hand, carry the role of raising offsprings, and are therefore assumed to be more agreeable and emotionally involved. Such a disproportionate opportunity cost in reproduc- tion also suggests key differences in both preference and choice in decision settings. Behavioural economics research has shown as such with females exhibiting greater preference for resource acquisition (Whyte & Torgler, 2017; Whyte et al., 2018) and more risk averse personality traits that reflect cooperative behaviours (Whyte & Tor- gler, 2016; Whyte et al., 2016; Whyte et al., 2017). A further example is Feingold’s (1994) artefact model which argues the role of sociocultural factors, for example gender stereotypes, therefore some traits are viewed by a particular gender to be more (or less) desirable. Certainly males and females have been shown to favour different personality traits at different life reproductive stages (Whyte et al., 2019). Such fundamental sex differences lead to the question of how much males and females differ psychologically in terms of traits, and how this impacts their decision process.

Understanding the psychological diﬀerences provide implications on the diﬀerence in their behaviour. Weisberg, DeYoung and Hirsh (2011) found females to be higher in agreeableness, extraversion and neuroticism, while Schmitt, Realo, Voracek and Allik (2008) found females to be higher in agreeableness, conscientiousness, extraversion and neuroticism across nations. Over the years females were found to be higher

26 on agreeableness, inferring higher tendency of altruistic behaviour, cooperation, empathy and kindness (Feingold, 1994; Costa et al., 2001). Females were also found to score consistently higher on neuroticism, which relates to anxiety, depression, anger, self-consciousness, and emotional lability (Weisberg et al., 2011; Costa et al., 2001). However for anger, a facet under neuroticism, females do not always score higher than males (Costa et al., 2001). For the different facets of extraversion, males tend to score higher on assertiveness and excitement seeking, while females tend to score higher on warmth, gregariousness, and positive emotions (Feingold, 1994; Costa et al., 2001). The overall results of gender differences on the domain of extraversion is mixed. Conscientiousness on the other hand reflects ones self-discipline and organization, but no significant gender differences have been found (Costa et al., 2001). Openness to experience relates to imagination, creativity, intellectual curiosity, and appreciation of esthetic experiences, and while males often scored higher on the ideas facet, and females scored higher on the esthetics and feelings facet, no significantly gender difference is found at the domain level of the trait (Weisberg et al., 2011; Feingold, 1994; Costa et al., 2001).

Gender difference in social roles and personality traits suggest gender differences are also intertwined in social behaviour. The stereotypical view perceives males as more selfish and females as more selfless. The sociocultural view considers social roles, biological differences, or gender hierarchy as the important determinants of social behaviour. Similar to the above arguments for personality traits, the social roles rather assume females to be more caring, friendly, and less selfish, while males are assumed to be more independent and dominant (Eagly, 2009). These gender assumptions and stereotypes penetrate into one’s self-concept and thus affect their social behaviour. The evolutionary perspective looks at the processes of natural and sexual selection and its impact on sex-differentiated adaptations, and how evolved dispositions affects decision making (Schmitt et al., 2008). These adaptations (or survival skills) play an important role in attracting sexual partners. For instance, according to Wood and Eagly (2002), males search for large packaged resources while females search for low-variance resources, through hunting and gathering respectively. As a consequence, males and females evolve to possess different psychological adaptation in order to perform and complete these sex-differentiated tasks. However, studies over the years in the context of economic games have reported mixed results. Earlier studies by Rapoport and Chammah (1965) in prisoner dilemma games found mixed results. More recent studies surround public goods games and ultimatum/dictator

27 experiments. In public goods experiments, Nowell and Tinkler (1994) and Seguino et al. (1996) found that females contributed significantly higher amounts to the public good, while Brown-Kruse and Hummels (1993), Sell and Wilson (1991) and Sell et al. (1993) found the opposite. On the other hand, the studies by Cadsby and Maynes (1998) and Sell (1997) yielded mixed results. In ultimatum bargaining experiments, neither Sohnick (2001) and Eckel and Grossman (2001) found significant difference between the mean offers by males and female. However, Solnick (2001) found higher rejection rates of offers made by females than males, while Eckel and Grossman (2001) found higher rejection rates of offers made by males than females. In dictator games, Eckel and Grossman (1998) and Andreoni and Vesterlund (2001) found significantly higher donation by females, while Bolton and Katok (1995) results were not significant in their restrictive experimental design (participants could only choose to give zero or half of the sum). The inconsistency in the results between studies can be possibly explained by the differences in methodology and experimental design, where the payoff structure plays a role. However in experiments that involve exposure to risk, no systematic gender differences was observed. In experiments without exposure to risk, females were found to be more others-oriented.

2.10 Summary

The above chapter provided a brief summary of the literature relevant to answering the three Key Research Questions. The social function of awe is widely agreed upon, and more of its psychological beneﬁts and implications on well-being are continuing to be discovered. Although recent studies began to establish the relationship between awe and prosociality, the theoretical link between the two needs to be further strengthened. In addition, a theoretical gap exists with no previous studies looking into whether external stimuli cause sudden changes in personality traits. This chapter also covered several factors that needs to be given careful consideration to when designing a public goods experiment. Further discussion regarding the experimental setup and design will be detailed in the next chapter.

28 Chapter 3

Methodology and Design

3.1 The experiment

126 participants were recruited via the QUT ORSEE system (Greiner, 2015) to take part in the experiment. There were 9 sessions of the experiment in total, including 3 sessions of the Walk/Awe treatment (N=42), 3 sessions of the Walk/No Awe treatment (N=42), and 3 sessions of the baseline treatment (N=42). Participants were from various diﬀerent study areas. Each participant only participated in one of the treatment conditions. The experiment took place in the BEST (Behavioural Eco- nomics, Society and Technology) lab of Queensland University of Technology, from 21 September 2018 to 25 February 2019. There are 20 widely separated computer terminals in the laboratory. oTree was the experimental software used in the study (Chen, Schonger & Wickens, 2016).

After signing and returning the informed consent form, participants were asked to fill in some survey questions. It includes a Big Five Personality Test and some demographic questions. Upon completion of the pre-treatment questionnaire, the experimenter went for a walk with the participants. The Walk/Awe treatment included a walk to a balcony on the tenth floor (Gibson Room), with panoramic views of the Brisbane city and the Brisbane river (see Appendix D). The Walk/No Awe treatment included a walk to the university library and back, in between buildings, without any spectacular views. Walks in both the Walk/Awe and Walk/No Awe treatment took approximately 8 minutes. Participants were told that they can do whatever they wish during the walk. After the walk, participants were asked to complete an emotional scale of current feelings and emotional states as in Shiota et al. (2007), but from 0 to 100. The baseline treatment did not include a walk and participants were to fill in

29 the emotional scale immediately after completing the demographic questionnaire.

The experiment consisted of three main tasks. Before each task, the instructions were distributed to each participant, displayed on the computer screen and read aloud by the experimenter. Task A is a standard public goods game for 16 rounds. Partic- ipants were allocated into random groups of 3. Each participant is endowed with 100 Experimental Currency Units (ECUs) at the start of every round, and they can choose to contribute ci ∈ [0,100] to a joint project in each round. Total contribution in the group for the round will be multiplied by a factor of 1.5, and split evenly among all three participants in the group. Participants payoﬀ for the round equals their earnings from the joint project, plus the amount they did not contribute. The payoﬀ n P function for subject i in each round is as follows: πi = 100 − ci + 0.5 cj, where 100 j=1 is the endowment at the start of each round, c is the contribution to the joint project n P by subject i, and cj is the total contribution to the project in a group. One round j=1 was randomly selected as their payment for the task. During round 8, participants were asked the reason behind their decisions on how much to contribute to the project.

After Task A, participants were asked a set of questions about appraisals during the target experience. They were then to ﬁll in another Big Five Personality Test (which was identical to the one before).

Task B consisted of ten decisions tasks from the Equality Equivalence Test (EET) by Kerschbamer (2015). It was an independent task. A participant’s decision did not aﬀect other participants’ payoﬀs. One of ten decisions was randomly chosen as their payment for Task B.

Task C was the Bomb Risk Elicitation Task (BRET) by Crosetto and Filippin (2013). For each box collected, participants earn 2 ECUs if none of their boxes contains a bomb. The number of boxes collected represents their risk attitudes. Details on the EET and the BRET will follow in later sections.

At the end of the session participants payoﬀs from all three tasks were added up and converted into AUD at a rate of 20 ECUs to AUD $1. Each session lasted about 50 minutes. Average earnings was $15.37, where highest earnings was $23.4 and the lowest $10.

30 3.2 Design

3.2.1 Treatment

Since situating participants in a natural environment gives an experience that is similar to an original awe experience, this was deemed to be the most suitable treatment methodology for this experiment. Similar methods of eliciting awe had been used by Shiota et al. (2007) and Piﬀ et al. (2015), asking participants to look at a full-sized replica of a Tyrannosaurus rex skeleton and a grove of tall eucalyptus trees respectively. But apart from nature, which itself had been shown by Weinstein, Przybylski and Ryan (2009) and Zhang, Piﬀ, Iyer, Koleva and Keltner (2014) to increase prosociality, this study is interested in looking into another elicitor of awe - panoramic views. Understanding the intensity of an awe experience decreases with time, the location of the target experience is a potential factor. The fact that the location of the balcony is close to the laboratory (3 levels apart) allows participants to complete the tasks after the awe experience with minimal time in between (approximately 2 minutes), and minimises the interference of other factors.

Using panoramic views as an instrument to elicit awe requires control for the effect of the walk, and the potential group experience during the walk. Therefore, the Walk/No Awe treatment group in comparison should have a similar group experience but without the natural awe environment. In order for the target experience in the Walk/No Awe treatment to be as mundane as possible, the walk is designed to be to the library and back to the laboratory, in between buildings. The downside of this route is, participants had to walk up the stairs from the second floor to the seventh floor. Another limitation, and a major difference between the Walk/Awe and Walk/No Awe treatment is that participants in the main treatment spent most of their time standing still in the awe environment, where those in the Walk/No Awe treatment continued walking for the entire target experience, as there was nothing that captures their attention like the awe experience so that they could stand still for a few minutes. This tiring physical activity could have a potential effect on individuals’ behaviour in the Walk/No Awe treatment.

Thus, a baseline treatment with no target experience or activity was necessary. Com- paring the results from the Walk/Awe treatment with the Walk/No Awe treatment and then to the baseline treatment is interesting, as it may indicate the signiﬁcance of the group experience, or reﬂect the nature of the Walk/No Awe treatment.

31 3.2.2 Emotion labels

It is important to capture participants’ emotions immediately after the target experience. Here the set of emotion labels from Shiota et al. (2007) was used. In the original paper, participants in the nature condition were higher on awe, love, rapture and contentment, while participants in the accomplishment condition were higher on pride, surprise, fear and excitement. Diﬀerent to the original paper asking participants to rate the appropriateness of the words for describing emotions during the target experience, here the question was instead asking participants the appropriateness of the words for describing their current feelings/ emotional state. The advantage of Shiota et al.’s (2007) choice of wording is to remind subjects of their emotions during their awe experience (since in the original task participants were asked to recall a recent awe event), but since in this case the target experience happened just before this survey, participants were expected to have a fresh memory of the experience. Instead of priming participants again of the experience by asking them to recall the experience, it would be interesting to study the eﬀect of the awe experience has on cooperation without further priming. In addition, these emotion labels were all on separate pages, leading participants to evaluate each item individually without having reference to another.

3.2.3 Appraisal endorsement for target experience

Diﬀerent to the emotion labels, the survey here was completed after Task A. This task did not have the immediacy comparing to the emotion label, together with the fact that it requires priming, it was designed to be after a lengthy and somewhat monotonous Task A to remind participants of the awe experience before Tasks B and C. In the original paper, participants in the nature condition rated higher on “Felt small or insigniﬁcant”, “Felt presence of something greater than self”, “Unaware of day-to-day concerns”, “Felt connected with the world around me” and “Did not want the experience to end”, while participants in the accomplishment condition rated higher on “Challenging”, “Tiring”, “Felt connected with my personal values” and “Felt connected with my culture”.

3.2.4 Next hour activity

Literature of awe (eg. Keltner and Haidt, 2003) suggests that individuals who experienced awe would want to repeat the experience, or be in the same environment again. Shiota et al. (2007) has found that participants in the awe treatment are more

32 likely to choose creative activities or to spend time in nature for their next hour It would be interesting to study that as well in this study.

3.2.5 Equality Equivalence Test (EET)

The Equality Equivalence Test (EET) is an experimental task by Kerschbamer (2015) to classify individuals into different distributional preference types. It includes a set of 10 binary choices. The switching point implies an individual’s willingness to pay for equality, which allows the classification into different types. The purpose of the EET here is to study whether the awe experience has any effect on individuals’ more complex distributional preferences. The EET task used in the experiment is the same as that in the original paper by Kerschbamer (2015), but with adjusted payoffs of ECUs instead of Euros. Instead of e = 10, g = 3, s = 1, t = 2 (in euros) in the original task, in this task, e = 50, g = 15, s = 5, t = 2 (in ECUs), where e, g and s were scaled with the common factor of 5, and the multiplier t which is 2 remains unchanged.

Calculating the (x,y) scores requires Step 1 in the original paper of eliminating preferences that violate the strict m-monotonicity assumption, meaning that holding the payoff of the other player constant, a decision maker should strictly prefer higher own payoff than lower own payoff. That is, letting m denote ”my” payoff and o for the

”other” person’s payoﬀ, given that (m, o) ∈ A and ∆ ∈ <++, the decision maker’s utility u(m+∆, o) > u(m, o). Then the participants’ (x,y) scores were calculated from the row number which they decide for the asymmetric allocation (left-hand side).

3.2.6 Bomb Risk Elicitation Task (BRET)

The Bomb Risk Elicitation Task (BRET) is an experimental task by Crosetto and Filippin (2013) to elicit risk preferences. No prior theory of awe has established a relationship between awe and risk preferences, therefore the task was carried out only to serve as a possible control variable. Due to technical issues with this task, 27 observations were lost in the experimental process.

3.2.7 Demographics

Demographic data was collected before the target experience, after the pre-treatment FFM questionnaire. Collecting data regarding participants’ religion and their devoutness was particularly necessary, to study whether that has any eﬀect on their

33 awe-proneness and tendency to cooperate. Diﬀerent to many laboratory experiments, demographic data here was collected at the start of the experiment, as participants’ report of their happiness, health, devoutness in religious activities and interest in politics would potentially be aﬀected by the treatment.

3.2.8 Public Goods Game

The public goods game in this experiment consisted of 16 rounds. A multiple-round public goods game captures the decay in cooperation, as a decline in contribution levels is often observed in repeated play of the game. In many cases players in the game withdraw from cooperation as they learn how behaviour aﬀects payoﬀs, and also as a form of punishment to the defectors.

The groups were shuﬄed after half of the rounds to observe any restart eﬀect (An- dreoni, 1988; Croson, 1996).

3.3 Summary

This chapter covered the experimental design and setup, as well as a simple theoretical framework of the approach and methodologies used. The main focus of the experimental design is to create an experience of awe that allows studying of the behavioural implications brought by it.

34 Chapter 4

Results and Discussion

This chapter will present and discuss all the relevant findings from the experiment. Section 4.1 presents descriptive statistics collected from the experiment, including demographic data, emotion labels after the treatment, thoughts/ appraisals during target experience, ideal next hour activities, as well as pre and post treatment FFM Scores. Section 4.2 attempts to answer Key Research Question 1: How does the emotion of awe affect cooperation in economic experiments? using results from Task A. Regression analysis were completed to identify whether a treatment effect is present on cooperation: whether individuals with the experience of awe exhibit higher cooperation in the public goods game. Section 4.3 explores Key Research Ques- tion 2: How does the emotion of awe affect distributional preferences in economic experiments? using the results from the EET. Section 4.4 examines the mean-level and rank-order stability in the measurement the Five Factor Model of Personality Traits. The comparison of the pre and post treatment FFM scores across treatments attempts to answer Key Research Question 3: To what extent does the emotion of awe affect the stability in the measurement of personality traits?. Section 4.5 examines the moderating effect of agreeableness on cooperation, originally proposed by Prade and Saroglou (2015). Finally, Section 4.6 gives a general discussion of all results.

35 4.1 Descriptive Statistics

Table 4.1: Demographics statistics.

Demographics (% of participants in treatment) Baseline Walk/No Walk/Awe Total Awe Gender Male 14 (34.15%) 20 (48.78%) 19 (45.24%) 53 (42.74%) Female 27 (65.85%) 21 (51.22%) 23 (54.76%) 71 (57.26%) Age Under 18 3 (7.32%) 3 (2.42%) 18-21 17 (41.46%) 16 (39.02%) 17 (40.48%) 50 (40.32%) 22-25 6 (14.63%) 16 (39.02%) 12 (28.57%) 34 (27.42%) 26-29 6 (14.63%) 1 (2.44%) 4 (9.52%) 11 (8.87%) 30 or above 9 (21.95%) 8 (19.51%) 9 (21.43%) 26 (20.97%) Ethnicity Asian 21 (51.22%) 20 (48.78%) 23 (54.76%) 64 (51.61%) Caucasian 9 (21.95%) 10 (24.39%) 9 (21.43%) 28 (22.58%) Latin 2 (4.88%) 2 (4.88%) 4 (3.23%) Middle- 1 (2.44%) 3 (7.14%) 4 (3.23%) Eastern Sub- 7 (17.07%) 7 (17.07%) 6 (14.29%) 20 (16.13%) continental Other 2 (4.88%) 1 (2.44%) 1 (2.38%) 4 (3.23%) Continuation of Table 4.1 Religion Atheist 6 (14.63%) 6 (14.63%) 3 (7.14%) 15 (12.10%) Buddhist 10 (24.39%) 5 (12.2%) 7 (16.67%) 22 (17.74%) Catholic 6 (14.63%) 1 (2.44%) 6 (14.29%) 13 (10.48%) Christian 4 (9.76%) 3 (7.32%) 4 (9.52%) 11 (8.87%) (Protes- tant) Christian 4 (9.76%) 4 (9.76%) 3 (7.14%) 11 (8.87%) (Other) Hindu 5 (12.2%) 1 (2.38%) 6 (4.84%) Muslim 3 (7.32%) 5 (12.2%) 10 (23.81%) 18 (14.52%) Sikh 1 (2.44%) 1 (0.81%) Taoism 1 (2.44%) 1 (2.38%) 2 (1.61%) Other 5 (12.2%) 6 (14.63%) 5 (11.9%) 16 (12.9%)

Table 4.1 reports the demographics statistics of the subjects. One participant from the Walk/No Awe treatment and one participant from the baseline treatment did not complete the demographics survey. Most of the participants in the experiment fell into the age group of 18 to 25. 57.26% of participants were female, 52% Asian, 23% Caucasian, 16% Sub-Continental, 3% Latino/Latina, 3% Middle-Eastern and 3% of another ethnicity. Of religion, there is a higher proportion of atheists in the

36 Walk/No Awe and the baseline treatments. Given the possible eﬀect religion has on transcendence, awe-proneness and prosociality, this factor has to be considered in later sections.

Table 4.2: Emotion labels. Emotion labels (S.D. in parentheses) Baseline Walk/No Walk/Awe t t Awe (Walk/Awe (Walk/Awe vs Base- vs line) Walk/No Awe) Awe 41.83 60.74 60.69 -2.96*** 0.01 (31.47) (26.2) (26.72) Love 47.21 49.60 62.55 -2.59** -2.21** (30.15) (29.8) (23.62) Rapture 39.33 47.17 49.55 -1.74* -0.42 (28.78) (27.16) (24.98) Contentment 59.62 55.60 61.69 -0.42 -1.19 (25.46) (26.31) (20.37) Pride 40.69 40.69 46.29 -0.98 0.51 (27.33) (27.32) (25.09) Surprise 33.12 69.14 58.10 -4.01*** 1.76* (28.11) (28.66) (28.89) Fear 29.98 23.83 23.90 1.03 -0.01 (29.76) (26.57) (23.97) Excitement 60.79 51.21 57.74 0.53 -1.08 (25.52) (27.46) (27.85) Joy 54.19 49.69 61.86 -1.48 -2.22** (25.52) (27.9) (21.97) Sadness 29.10 23.10 24.79 0.75 -0.32 (29.81) (26.73) (22.03) All t-tests are two-tailed. *** p<0.01, ** p<0.05, * p<0.1

Table 4.2 shows the mean word ratings from the post treatment emotion labels adapted from Shiota et al. (2007). Of interest to note is the similar level of self- reported awe in the Walk/Awe and Walk/No Awe treatment. Given that the self- reported awe level in the baseline is signiﬁcantly lower than that in the Walk/Awe

37 treatment, it gives indication about the design of the Walk/No Awe treatment. Par- ticipants in the Walk/Awe treatment also reported higher levels of joy comparing to the Walk/No Awe treatment, and higher levels love comparing to the Walk/No Awe and the baseline.

Table 4.3: Thoughts/appraisals during target experience. Thoughts/appraisals during target experience. (S.D. in parentheses) Walk/No Walk/Awe t Awe (Walk/Awe vs Walk/No Awe) Novel 54.90 (21.78) 54.05 (22.36) 0.27 Meaningful 49.63 (28.78) 50.45 (22.57) 0.49 Intense 46.73 (29.27) 41.12 (24.8) 0.87 Felt connected with my culture 29.73 (26.84) 32.60 (23.54) -0.39 Felt connected with my personal values 43.29 (29) 44.55 (23.86) 0.66 Tiring 40.44 (32.84) 34.69 (27.36) 0.29 Challenging 41.32 (28) 37.02 (26.81) 0.43 Did not want the experience to end 29.98 (23.72) 36.95 (27.03) -0.72 Felt connected with the world around me 42.83 (29.86) 44.00 (25.49) -0.68 Unaware of day-to-day concerns 45.59 (27.48)) 45.02 (21.95) 0.44 Felt presence of something greater than self 38.20 (28.19) 41.83 (24.34) -0.42 Felt small or insigniﬁcant 28.05 (26.77) 40.45 (30.35) -1.49

Table 4.3 presents the mean endorsements of thoughts/appraisals during the target experience as from Shiota et al. (2007). No signiﬁcant statistical diﬀerences were found comparing between the two treatments.

38 Table 4.4: Next hour activity. Next hour activity (Count) Baseline Walk/No Walk/Awe Awe Next hour activity Contact loved ones 7 11 9 Creative activity 18 6 13 Play sports 6 10 6 Sleep 4 9 5 Spend time in nature 6 5 9

The ideal next hour activities as from Shiota et al. (2007) are presented in Table 4.4.

39 Table 4.5: Average FFM Scores. Average FFM Scores (S.D. in parentheses) Baseline WN WA t t (WA (WA vs B) vs WN) Before Agreeableness 5.15 5.19 5.12 0.17 0.42 treat- (0.79) (0.79) (0.71) ment Conscientiousness 5.07 4.96 4.82 1.35 0.78 (0.99) (0.86) (0.73) Extraversion 4.20 4.29 4.18 0.09 0.55 (0.89) (0.83) (0.87) Neuroticism 4.32 4.34 4.41 -0.51 -0.37 (0.87) (0.85) (0.84) Openness 4.78 4.67 4.64 0.72 0.13 (0.85) (0.92) (0.93) After Agreeableness 4.99 5.11 5.18 -1.13 -0.40 treat- (0.87) (0.90) (0.72) ment Conscientiousness 5.18 4.91 4.82 1.93 0.46 (0.93) (0.89) (0.76) Extraversion 4.18 4.22 4.21 -0.16 0.09 (0.85) (0.92) (0.80) Neuroticism 4.42 4.46 4.65 -1.16 -0.91 (0.90) (0.94) (0.93) Openness 4.73 4.65 4.54 0.95 0.54 (0.90) (0.87) (1.00) Note: WA=Walk/Awe, WN=Walk/No Awe, B=Baseline

Table 4.5 reports the average pre and post treatment FFM Scores. T-tests found no significant differences comparing each of the five factors across treatments.

4.2 Awe and Cooperation

Based on the previous findings of awe’s positive effect on prosociality and helping by Piff et al. (2015) and Prade and Saroglou (2015), awe’s positive impact on cooperation in the public goods game is expected.

40 Figure 4.1: Contribution in the Public Goods Game. (N=126)

Figure 4.1 shows the contribution levels in the public goods game across different treatments. From the figure it appears that participants in the baseline treatment started with the highest contribution levels, but exhibited the greatest magnitude of decline. With the groups shuffled at round 8, a slight restart effect was observed in the participants’ contribution in round 9.

Using Stata 15, regression analyses were conducted using different estimation tech- niques. The dependent variable here is the participants contribution in the public goods game, as a measure of cooperation. The independent variable of focus here is the treatment dummy, which allows investigation of whether a treatment effect is present. The first group of variables is demographic variables of age and gender, as well as age’s interaction effect with the treatment dummy, to control for any gender and age effects. The second group of control variables is related to the payoff structure of the task, controlling for round number, individual payoff in the previous round and the group contribution in the previous round. Including round number as an independent variable controls for the decay in the level of contribution over rounds, while the groups contribution and the participants payoff in the previous round are important predictors of the individuals contribution in the current round.

41 The remaining control variables are self-reported awe and its interaction eﬀect with the treatment dummy.

Five different regression models are used in the above estimation. Model 1 is a Pooled OLS regression, mainly for comparison purposes. Model 2 is a standard random effects model. Model 4 is a panel random effects tobit model, with 0 and 100 as the censoring points for the dependent variable. The censoring is suitable in this context, as the contribution in the PGG can only fall between 0 to 100. Model 5 is a fractional probit model, where the dependent variable takes values between 0 and 1. From another perspective, contribution in the PGG can be seen as a proportion, and scaled to be in [0,1]. Different to the previous random effects estimators, this is a quasi-likelihood estimator. However with a clustered data structure, the most appropriate model of estimation is Model 3, which is a multilevel mixed-effects regression. The fact that individuals play the game in groups and the groups are shuffled at round 8 means that the data needs to be nested in two different levels, individual and group (each player has one individual id and two group ids). It is important to note that the individuals choice of contribution in the PGG has a level of dependence on other group members decisions (and past decisions). Without clustering for groups, standard errors will likely be underestimated and statistical significance will therefore be overstated. With two different group ids for a single individual (for the first and second half of the rounds), the multilevel mixed-effects regression model is a model that allows a correct clustering of data in this scenario.

42 Table 4.6: Public Goods Game (Walk/Awe vs Walk/No Awe) (1) (2) (3) (4) (5) Depvar: PGG Contribution OLS RE ME Tobit Fractional

Treatment (dummy) 9.230** 9.230** 14.37* 30.02 0.340** (4.571) (4.571) (8.443) (19.98) (0.148) Self-reported awe -0.0480 -0.0480 -0.0688 -0.168 -0.00141 (0.0428) (0.0428) (0.0823) (0.191) (0.00152) Treatment x self-reported awe -0.0321 -0.0321 -0.0620 -0.241 -0.00155 (0.0590) (0.0590) (0.107) (0.262) (0.00209) Payoﬀ (previous round) -0.434*** -0.434*** -0.220*** -0.241*** -0.0121*** (0.0304) (0.0304) (0.0615) (0.0574) (0.00125) Group contribution 0.363*** 0.363*** 0.272*** 0.388*** 0.0113*** (previous round) (0.0104) (0.0104) (0.0176) (0.0252) (0.000449) Round no. -0.355** -0.355** -0.625*** -1.044*** -0.0134** (0.180) (0.180) (0.222) (0.285) (0.00654) Age 2.900*** 2.900*** 4.387*** 11.00** 0.108*** (1.034) (1.034) (1.524) (4.665) (0.0408) Treatment x Age -3.895*** -3.895*** -6.123** -11.08* -0.143*** (1.398) (1.398) (2.600) (6.214) (0.0520) Gender -2.821* -2.821* -2.412 -5.636 -0.126** (1.532) (1.532) (2.468) (6.769) (0.0560) Constant 52.97*** 52.97*** 40.43*** 30.85* -0.0385 (5.433) (5.433) (9.986) (18.40) (0.204) Observations 1,245 1,245 1,245 1,245 1,245 R-squared 0.545 Number of id 83 83 Number of groups 56 56 56 56 Standard errors in parentheses *** p<0.01, ** p<0.05, * p<0.1

Table 4.6 shows the estimation output from analysing only the Walk/Awe and Walk/No Awe treatments. A significant treatment effect was found with Model 2 and 5, but not with Model 4. With Model 3, the treatment effect is only significant at a 10% level. The awe experience appears to have a borderline significant impact on cooperation when comparing the Walk/Awe treatment with the Walk/No Awe treatment. Of interest to note is that age and its interaction effect with the treatment dummy is significant across all models.

43 Table 4.7: Public Goods Game (Walk/Awe vs Baseline) (1) (2) (3) (4) (5) Depvar: PGG Contribution OLS RE ME Tobit Fractional

Treatment (dummy) 9.358** 9.358** 17.79** 34.15** 0.325*** (3.961) (3.961) (8.555) (17.36) (0.120) Self-reported awe 0.0376 0.0376 0.0462 0.135 0.00127 (0.0356) (0.0356) (0.0658) (0.155) (0.00101) Treatment x self-reported awe -0.119** -0.119** -0.214** -0.548** -0.00433** (0.0532) (0.0532) (0.107) (0.234) (0.00175) Payoﬀ (previous round) -0.452*** -0.452*** -0.113** -0.116** -0.0126*** (0.0297) (0.0297) (0.0556) (0.0473) (0.00117) Group contribution 0.361*** 0.361*** 0.196*** 0.268*** 0.0108*** (previous round) (0.0112) (0.0112) (0.0207) (0.0205) (0.000461) Round no. -0.399** -0.399** -1.102*** -1.081*** -0.0135** (0.178) (0.178) (0.215) (0.228) (0.00633) Age -0.292 -0.292 0.0417 0.589 -0.0134 (0.785) (0.785) (1.498) (3.429) (0.0259) Treatment x Age -0.728 -0.728 -2.283 -1.369 -0.0246 (1.191) (1.191) (2.870) (5.232) (0.0402) Gender -2.397 -2.397 -2.765 -5.149 -0.0939* (1.527) (1.527) (3.082) (6.713) (0.0533) Constant 55.28*** 55.28*** 42.08*** 29.49** 0.0778 (4.857) (4.857) (7.616) (14.37) (0.173)

Observations 1,245 1,245 1,245 1,245 1,245 R-squared 0.497 Number of id 83 83 Number of groups 56 56 56 56 Standard errors in parentheses *** p<0.01, ** p<0.05, * p<0.1

Table 4.7 shows the estimation output from analysing only the Walk/Awe and baseline treatments. Different to the results from Table 4.6, here a significant treatment effect with all models was found. In this estimation, age is not a significant variable, but the significance of the interaction between self-reported awe and the treatment dummy is something noteworthy given the results from Table 4.2.

44 Result 1. Awe has a signiﬁcant positive impact on cooperation.

The above estimations have confirmed the finding that the emotion of awe enhances cooperation. Given the proven social function of awe in relation to prosociality, generosity and helping, it is within expectation that awe also leads to higher cooperation in groups. The finding by Campos et al. (2013) and Piff et al. (2015) that awe induction leads to the “small self” is a reasonable explanation for the increased contribution levels in the awe treatments in this study. Individuals experiencing awe are likely to feel less significant, reducing their attachment to their personal success and goals.

4.3 Awe and Distributional Preferences

This section attempts to answer Key Research Question 2 using the results obtained from the EET in Task B.

Figure 4.2: Frequency of the (x,y) scores. (N=117)

Figure 4.2 presents a jittered scatterplot of the (x,y) scores of the remaining 117 participants (9 out of 126 participants’ responses were eliminated due to inconsistent

45 preferences). According to Kerschbamer (2015), an individual’s x-score is deﬁned by (t+1.5) points minus the row number in which the individual switches from right to left (the asymmetric allocation), and an individual’s y-score is calculated by the row number in which the individual makes the switch minus (t+1.5) points. From the graph it is apparent that most participants are consistent with the selﬁsh type, and the second and third most common are the inequality averse and altruistic types.

Table 4.8: Frequency of Distributional Types. Frequency of Distributional Types Total Baseline Walk/No Walk/Awe Awe Altruistic 13 2 4 7 Equality Averse 2 1 1 0 Inequality Averse 24 9 9 6 Spiteful 6 2 1 3 Selﬁsh 51 18 18 15

Table 4.8 shows the frequency of the ﬁve distributional types across treatments. In the Walk/Awe treatment, there seems to be a higher proportion of altruists, and slightly fewer number of equality averse, inequality averse and selﬁsh individuals.

Table 4.9: Test of Proportions for the Distributional Types Test of Proportions for the Distributional Types Walk/Awe vs Walk/Awe vs Baseline Walk/No Awe (z-score) (z-score) Altruistic -1.76* -0.97 Equality Averse 1.01 1.01 Inequality Averse 0.85 0.85 Spiteful -0.46 -1.02 Selﬁsh 0.67 0.67 *** p<0.01, ** p<0.05, * p<0.1

Table 4.9 formally tests the frequency of the five distributional types across treatments. The only significant difference if found in the number of altruists between the Walk/Awe treatment and the baseline treatment.

46 Table 4.10: Rank Correlation Tests for x,y scores Rank Correlation Tests for x,y scores Walk/Awe vs Walk/Awe vs Baseline Walk/No Awe (z-score) (z-score) x-score -1.90* -1.32 y-score -0.50 -0.63 *** p<0.01, ** p<0.05, * p<0.1

Table 4.10 presents the rank correlation z-scores for the (x, y) scores between treatments. It shows that individuals in the Walk/Awe treatment has higher x-scores than those in the baseline with weak signiﬁcance. In other words, between being inequality averse and altruistic, individuals with the awe experience have a slight tendency towards altruism.

Table 4.11: OLS Regression on x scores (Walk/Awe vs Baseline) (1) (2) Depvar: xscore xscore

Treatment dummy 0.583** 0.777*** (0.286) (0.291) Self-reported awe -0.0136*** (0.00486) Gender 0.512* (0.277) Age -0.0823 (0.105) Constant -0.775*** -0.733 (0.201) (0.496)

Observations 79 79 R-squared 0.051 0.191 Standard errors in parentheses *** p<0.01, ** p<0.05, * p<0.1

To further analyse the diﬀerence in x-scores, OLS estimations were performed with respect to treatment, as shown in Table 4.11. Without controlling for other factors, the treatment dummy is signiﬁcant at 5% level. While controlling for self-reported

47 awe, gender, and age, the signiﬁcance of the treatment dummy rises to 1% level. This suggests that awe has an eﬀect on participants’ x-scores in the Walk/Awe and baseline treatments. Participants with the awe experience are more likely to be altruistic than being inequality averse.

Table 4.12: OLS Regression on x scores (Walk/Awe vs Walk/No Awe) (1) (2) Depvar: xscore xscore

Treatment dummy 0.413 0.415 (0.295) (0.290) Self-reported awe 0.000548 (0.00551) Gender 0.551* (0.290) Age -0.191 (0.126) Constant -0.605*** -1.033 (0.210) (0.657)

Observations 77 76 R-squared 0.025 0.096 Standard errors in parentheses *** p<0.01, ** p<0.05, * p<0.1

48 Table 4.13: OLS Regression on y scores (Walk/Awe vs Baseline) (1) (2) Depvar: yscore yscore

Treatment dummy 0.0885 0.0632 (0.294) (0.321) Self-reported awe -0.00127 (0.00537) Gender 0.233 (0.306) Age -0.101 (0.116) Constant 0.950*** 0.928* (0.207) (0.548)

Observations 79 79 R-squared 0.001 0.020 Standard errors in parentheses *** p<0.01, ** p<0.05, * p<0.1

49 Table 4.14: OLS Regression on y scores (Walk/Awe vs Walk/No Awe) (1) (2) Depvar: yscore yscore

Treatment dummy 0.144 0.159 (0.308) (0.313) Self-reported awe -0.00612 (0.00593) Gender -0.105 (0.313) Age 0.127 (0.136) Constant 0.895*** 1.123 (0.219) (0.708)

Observations 77 76 R-squared 0.003 0.030 Standard errors in parentheses *** p<0.01, ** p<0.05, * p<0.1

Carrying out the same regression in Table 4.12 between the Walk/Awe and Walk/No Awe treatments for x scores, and y-scores in Tables 4.13 and 4.14 between the Walk/Awe and Baseline and Walk/Awe and Walk/No Awe treatments, no signiﬁ- cant treatment eﬀect was found.

Result 2. Awe has a signiﬁcant positive impact on altruistic preferences

Summing up the findings in this section, the regression outputs showed that individuals in the Walk/Awe treatment had significantly higher x-scores than those in the baseline treatment. Participants in the Walk/Awe treatment are likely to be more concerned about the sum of payoffs than being concerned about the inequality in payoffs (the utility of an altruistic individual increases as the payoff of the other individual increases). In other words, if the other player has higher payoffs than the individual, the individual with the experience of awe are less likely to take away from the other player’s payoff. This ties into the finding in Section 4.2 that participants in the Walk/Awe treatment exhibited higher levels of cooperation.

50 4.4 Awe and the Stability in the measurement of the Five Factor Model of Personality Traits

This section attempts to answer Key Research Question 3 using the the pre and post treatment Five Factor Model questionnaire results. OLS regressions, two sample t- tests, and the Wilcoxon rank-sum test were employed to study whether there is a treatment eﬀect on the stability in the measurement of the Five Factors. In other words, whether awe experience changes people’s personality traits.

4.4.1 OLS Estimation on Measurement of Personality Traits Stability

The OLS regressions below study the mean-level stability in the measurement of personality traits. Here the difference between the Five Factor scores before and after the treatment were calculated (as the measure of personality trait stability), and use that difference in the scores as the dependent variable. The independent variable is the treatment dummy, indicating whether a treatment effect is present.

Table 4.15: FFM Personality Traits Stability (Walk/Awe vs Walk/No Awe) Depvar: Diﬀerence (1) (2) (3) (4) (5) in personality traits A C E N O

Treatment dummy 0.187** 0.0243 0.0696 0.123 -0.133* (0.0806) (0.0844) (0.0733) (0.0881) (0.0768) Constant -0.122** -0.0209 -0.0488 0.115* 0.0314 (0.0574) (0.0600) (0.0521) (0.0627) (0.0546)

Observations 83 83 83 83 83 R-squared 0.062 0.001 0.011 0.024 0.036 (A = Agreeableness, C=Conscientiousness, E=Extraversion , N=Neuroticism, O=Openness) Standard errors in parentheses *** p<0.01, ** p<0.05, * p<0.1

Table 4.15 reports the estimation including only Walk/Awe and Walk/No Awe treatments. From the regression table it appears that the emotion of awe has a significantly positive impact on agreeableness, whereas the treatment effect on openness is nega- tively significant at 10% level. Other factors remain stable on the mean level. Further

51 testings are required to examine the validity of the ﬁndings from this estimation.

Table 4.16: FFM Personality Traits Stability (Walk/Awe vs Baseline) Depvar: Diﬀerence (1) (2) (3) (4) (5) in personality traits A C E N O

Treatment dummy 0.224** -0.102 0.0476 0.136 -0.0578 (0.0938) (0.0919) (0.0661) (0.0894) (0.0777) Constant -0.160** 0.105 -0.0268 0.102 -0.0442 (0.0663) (0.0650) (0.0467) (0.0632) (0.0549)

Observations 84 84 84 84 84 R-squared 0.065 0.015 0.006 0.027 0.007 (A = Agreeableness, C=Conscientiousness, E=Extraversion , N=Neuroticism, O=Openness) Standard errors in parentheses *** p<0.01, ** p<0.05, * p<0.1

Table 4.16 reports the estimation including only Walk/Awe and baseline treatments. Again a signiﬁcant positive treatment eﬀect on agreeableness is apparent. Other measurements of personality traits were stable on the mean level, including openness to experience.

4.4.2 Wilcoxon rank-sum test and Two-sample t-test on Mea- surement of Personality Trait Stability

The above results were further examined by a Wilcoxon rank-sum test, which examines the mean-level stability in the measurement of personality traits.

Table 4.17: FFM Personality Traits (Walk/Awe vs Walk/No Awe) FFM Personality Traits (Walk/Awe vs Walk/No Awe) Rank Correlation z-score Agreeableness 2.12** Conscientiousness 0.69 Extraversion 0.96 Neuroticism 1.29 Openness -1.95* *** p<0.01, ** p<0.05, * p<0.1

52 Table 4.17 confirms the findings in Table 4.15. Comparing the Walk/Awe and Walk/No Awe treatments, there is a significant positive change in agreeableness for individuals who experienced awe, in both absolute and differential level. The negative change in Openness here at 10% significance also corresponds to that in Table 4.15.

Table 4.18: FFM Personality Traits (Walk/Awe vs Baseline) FFM Personality Traits (Walk/Awe vs Baseline) Rank Correlation z-score Agreeableness 2.15** Conscientiousness -0.15 Extraversion 0.77 Neuroticism 1.56 Openness -1.09 *** p<0.01, ** p<0.05, * p<0.1

Similarly, Table 4.18 confirms the findings in Table 4.16. The positive treatment effect on the measurement of agreeableness is again verified by the Wilcoxon rank-sum test and a two sample t-test.

4.4.3 Components of Agreeableness

To analyse the factors that are driving the change in the measurement of agreeableness, it is necessary to dissect the change in diﬀerent components of agreeableness.

Table 4.19: Rank Correlation Tests for change in components of Agreeableness Rank Correlation Tests for change in components of Agreeableness Walk/Awe vs Walk/Awe vs Walk/No Awe Baseline (z-score) (z-score) Sympathetic -0.01 -0.42 Kind -1.94* -0.49 Cooperative -0.79 -0.33 Warm 1.09 1.46 Harsh 0.81 2.40** Cold 2.26** 2.66*** Selﬁsh 1.94* 2.66*** *** p<0.01, ** p<0.05, * p<0.1

53 From the rank correlation test results in Table 4.19 it appears that cold and selﬁsh are the two common components driving the change in the Walk/Awe treatment.

4.4.4 Further Analysis on Stability in the measurement of Agreeableness

To further investigate the change in the measurement of agreeableness, it is necessary to break down the mean-level change with respect to diﬀerent demographic factors. Estimation 1 is an OLS regression similar to Table 4.15 and 4.16, but included an interaction term between gender and the treatment dummy. Estimation 2 analysed the change in the measurement of agreeableness with respect to Age. Estimation 3 broke down the change with respect to religiosity.

54 Table 4.20: Further Analysis for Stability (Walk/Awe vs Walk/No Awe) (1) (2) (3) (4) Indepvars: Gender Age Religiousness All

18-21#1 0.239* -0.217 (0.128) (0.150) 22-25#0 0.140 0.135 (0.130) (0.126) 22-25#1 0.271* -0.239 (0.140) (0.154) 26-29#0 -0.181 -0.132 (0.375) (0.368) 26-29#1 0.319 -0.0977 (0.204) (0.214) 30 or above#0 0.337** 0.305* (0.159) (0.153) 30 or above#1 0.502*** (0.153) Female#1 -0.0355 0.324* (0.106) (0.181) Male#0 -0.228** -0.210* (0.111) (0.112) Male#1 0.231** 0.591*** (0.111) (0.174) Non-religious#1 0.191 0.0299 (0.148) (0.140) Religious#0 0.137 0.135 (0.118) (0.114) Religious#1 0.295** (0.112) Constant -0.0204 -0.248*** -0.205** -0.221* (0.0766) (0.0936) (0.0919) (0.119)

Observations 82 82 83 82 R-squared 0.174 0.162 0.085 0.269 #0: Non-treatment, #1: Treatment Standard errors in parentheses *** p<0.01, ** p<0.05, * p<0.1

55 Table 4.20 shows that males in the Walk/No Awe treatment exhibited a significant reduction in their measurements of agreeableness, where males in the Walk/Awe treatment exhibited a significant increase in their measurements of agreeableness. For females, no significant changes were found. With student participants as subjects in this experiment, age was relatively homogeneous, therefore it is within expectation that little insightful results with regards to age is found. The only interesting finding with regards to age is that participants aged 30 or above increased in their measurements of agreeableness in both treatments. Religious individuals in the Walk/Awe treatment, on the other hand, exhibited a significantly positive change. Putting gender, age and religiosity together in the same estimation (in 4), it is shown that the significant factor that continue to stand out is the treatment effect on male participants.

56 Table 4.21: Further Analysis for Stability (Walk/Awe vs Baseline) (1) (2) (3) (4) Indepvars: Gender Age Religiousness All

18-21#1 0.0672 -0.217 (0.138) (0.172) 22-25#0 -0.0434 -0.0431 (0.191) (0.191) 22-25#1 0.0994 -0.239 (0.152) (0.177) 26-29#0 -0.401** -0.398** (0.191) (0.194) 26-29#1 0.147 -0.0977 (0.223) (0.246) 30 or above#0 0.171 0.169 (0.166) (0.166) 30 or above#1 0.330* (0.166) Under 18#0 -0.782*** -0.786*** (0.252) (0.259) Female#1 0.103 0.204 (0.121) (0.211) Male#0 -0.00454 0.0358 (0.141) (0.136) Male#1 0.369*** 0.471** (0.128) (0.203) Non-religious#1 0.205 0.0299 (0.182) (0.161) Religious#0 0.0868 0.0202 (0.145) (0.140) Religious#1 0.309** (0.142) Constant -0.159* -0.0756 -0.220* -0.101 (0.0822) (0.0975) (0.120) (0.141) Observations 83 83 84 83 R-squared 0.110 0.263 0.074 0.305 Standard errors in parentheses #0: Non-treatment, #1: Treatment *** p<0.01, ** p<0.05, * p<0.1 57 Table 4.21 analyses the change in the Walk/Awe and baseline treatments, with respect to the same demographic factors as above. Similar to Table 4.20, males in the Walk/Awe treatment demonstrated a significant increase in their measurements of agreeableness. Participants aged 26-29 showed a decrease in their measurements of agreeableness in the baseline treatment, while those aged 30 or above increased in their measurements of agreeableness at 10% significance level. Meanwhile, similar to above, religious individuals in the Walk/Awe treatment showed a significant increase. In estimation 4, males in the Walk/Awe treatment continue to be the one significant factor throughout the analysis.

4.4.5 Discussion

Result 3. Awe has a signiﬁcant positive impact on the personality trait of agreeableness.

As shown from the above tables, treatment effect does not seem evident on other personality trait factors. This change can be explained in different ways, especially given that the second FFM measure is after 16 rounds of the PGG. A possible explanation of the change in agreeableness ties into the findings by Yang et al. (2016), where they found that awe reduces aggression. Studies such as Barlett and Anderson (2012), Gleason, Jensen-Campbell and South Richardson (2004) and Trninic, Baran- cic and Nazor (2008) all found a significantly negative correlation between aggression and agreeableness. It is possible that individuals in the awe treatment have reduced levels of aggression and is therefore is comparatively higher on agreeableness.

It is also important to address the potential critique that the increase in the measurement of agreeableness arose from the increased level of contribution in the public goods game. Whilst that could be true to a certain extent, the appraisal endorsement for target experience was intentionally placed immediately after the 16-round PGG. It was done in order to prime participants of the target experience before completing the post treatment FFM questionnaire. The following regressions attempt to address this critique:

58 Table 4.22: Stability of Agreeableness Depvar: (1) (2) Diﬀerence in Agreeableness Walk/Awe vs Walk/No Awe Walk/Awe vs Baseline

Contribution in PGG #0 0.000708 -0.000656 (0.000920) (0.00137) Contribution in PGG #1 0.00311*** 0.00285*** (0.000868) (0.000941) Constant -0.116** -0.0968 (0.0571) (0.0629)

Observations 1,328 1,344 R-squared 0.069 0.062 #0: Non-treatment, #1: Treatment Robust standard errors in parentheses *** p<0.01, ** p<0.05, * p<0.1

Table 4.22 shows the OLS regressions with change in measurement of agreeableness as the dependent variable and the interaction between contribution in the PGG and the treatment dummy as the independent variable. It is clear that with individual contribution in the PGG as the independent variable, the treatment eﬀect is still strongly signiﬁcant when comparing the Walk/Awe treatment to both Walk/No Awe and baseline treatments.

4.5 Moderating eﬀect of agreeableness on cooperation

According to the ﬁnding by Prade and Saroglou (2015, p.258)

“the eﬀect (of generosity) was present mainly among those low in agreeableness ... For people who are dispositionally low in agreeableness, awe may be a speciﬁc self- transcendent, stimulus-oriented, positive emotion that stimulates them and facilitates prosocial behavior ... people low in agreeableness may exhibit, thanks to awe, prosocial behavior at similar levels to those high in agreeableness, who may need less of the emotion of awe to express their personal prosocial dispositions in agreeableness”

It would be interesting to investigate into the role of agreeableness in cooperation

59 in the public goods game. As the mean score of agreeableness is our data collected is 5.15 (median is 5.14), individuals who score higher than 5.15 were considered to be high in agreeableness and those who were lower than 5.15 were considered low in agreeableness. The following regressions were estimated with the multilevel mixed- eﬀects model in section 4.2 with individuals who are high in agreeableness and low in agreeableness respectively.

Table 4.23: Public Goods Game Contribution with respect to Agreeableness (1) (2) (3) (4) High Low High Low WA vs WN WA vs WN WA vs B WA vs B Treatment (dummy) 11.02 14.52* 15.61 17.53** (10.90) (7.721) (12.06) (8.099) Self-reported awe -0.0654 -0.0650 0.0399 0.0435 (0.0759) (0.0754) (0.0637) (0.0620) Treatment x self-reported awe 0.0234 -0.113 -0.129 -0.260** (0.110) (0.104) (0.128) (0.109) Payoﬀ (previous round) -0.279*** -0.273*** -0.134** -0.152*** (0.0726) (0.0652) (0.0656) (0.0590) Group contribution 0.297*** 0.303*** 0.205*** 0.226*** (previous round) (0.0197) (0.0185) (0.0249) (0.0226) Round no. -0.730*** -0.501** -1.364*** -0.982*** (0.260) (0.256) (0.227) (0.255) Age 3.981*** 3.914*** 0.0122 -0.0155 (1.465) (1.442) (1.488) (1.398) Treatment x Age -5.897 -5.104** -2.036 -1.696 (3.867) (2.471) (4.691) (2.780) Gender -2.636 -2.847 -3.406 -3.198 (2.651) (2.262) (3.641) (2.948) Constant 45.77*** 42.53*** 46.85*** 42.47*** (11.25) (10.39) (8.991) (7.997)

Observations 885 975 885 975 Number of groups 49 53 49 53 WA=Walk/Awe, WN=Walk/No Awe, B=Baseline High=High in Agreeableness, Low=Low in Agreeableness Robust standard errors in parentheses *** p<0.01, ** p<0.05, * p<0.1

60 The results in Table 4.23 agrees with the finding by Prade and Saroglou (2015). In this experiment, the effect of awe on cooperation was mostly found among individuals who are low in agreeableness, and not among those who are high in agreeableness. It thus suggests that for individuals that are low in agreeableness, experience of awe increases their agreeableness and enhances their cooperation. However the difference between those who are high and low in agreeableness is small and insignificant.

4.6 General Discussion of Results

The overall findings in this studies builds on the “Small self” hypothesis, and confirms previous findings by Piff et al. (2015) and Prade and Saroglou (2015), that the emotion of awe has a positive impact on prosociality. It also aligns with the vast literature on the impact of positive emotions on prosociality. Taking a slightly different approach, and based on the findings by Piff et al. (2015) and Prade and Saroglou (2015), Result 1 adds to the literature about the social function of awe by proving its impact on cooperation.

Key Research Question 2 aims to further investigate how the social preferences of individuals change with the impact of awe. From previous studies, participants with the experience of awe are expected to be less selfish and more altruistic. However, it is interesting to see the effect of awe on other distributional types. Overall no statistically significant results were found between the Walk/Awe and Walk/No Awe treatments, but significant difference is found in the x-scores between participants in the Walk/Awe and the baseline treatments. The findings here agree with Result 1, where participants in the Walk/Awe treatment care more about the sum of total payoffs than the relative “fairness” in payoffs.

Key Research Question 3 explores the rather open question of the stability in the measurement of personality traits after an awe experience. Result 2 shows that the awe treatment increases individuals’ agreeableness. In fact, Peterson and Seligman (2004) have shown that agreeableness links with appreciation of beauty and excel- lence, and that subjective experience of beauty was proven to be associated with greater empathy and charitable giving by Einolf (2011). Prade and Saroglou’s (2015) ﬁndings of the moderating eﬀect of agreeableness have also been replicated with respect to cooperation in the public goods game, suggesting that awe leads to higher agreeableness and higher cooperation levels for individuals who are low in agreeableness. This study agrees with Prade and Saroglou’s (2015) proposition that individuals who are high in agreeableness do not require the same level of awe as those who are

61 low in agreeableness to exhibit a high level of prosociality or cooperation, therefore the effect of awe on prosociality/cooperation is more substantial to the latter. On a side note, this does not imply that the low agreeableness group is more awe-prone - it simply means that the effect of awe on prosociality/cooperation is maybe more significant on the low agreeableness group.

There is an evident parallel in the above ﬁndings. In answering KRQs 1 and 2, participants with the awe experience behaved more cooperatively and prosocially in purely economic tasks. Their behaviour in those tasks can then be explained by the increase in their psychological measurement of agreeableness. Through exploring the stability of personality traits with the eﬀect of the awe treatment, the social function of awe is further bolstered on both the individual level and the group level.

62 Chapter 5

Conclusion

Understanding the factors that aﬀect cooperation and social preferences is an important topic in economics. Previous studies on awe have given a glimpse of the transformative power of awe on both the individual level and the group level. Building from the existing literature, this study provides insights on how the emotion of awe aﬀects behaviour, in particular, cooperation, distributional preferences and stability in the measurement of personality traits. Chapter 1 posed the three research questions and motivated the research problem. Chapter 2 provided background literature of awe and key dependent variables of interest such as cooperation, distributional preferences and stability in the measurement of personality traits. Chapter 3 outlined the details of the experimental treatments and tasks employed to answer the key research questions. Chapter 4 provided the answers to the following key research questions

Key Research Question 1. How does the emotion of awe aﬀect cooperation in economic experiments?

In a 16-round public goods game, participants in the Walk/Awe treatment (balcony with panoramic views) exhibited higher levels of cooperation. This result suggests that the self-transcendent ability of awe shifts one’s focus, brings a greater sense of community and therefore enhances cooperation.

Key Research Question 2. How does the emotion of awe aﬀect distributional preferences in economic experiments?

Participants in the Walk/Awe treatment were found to have higher x-scores than those in the baseline treatment. This indicates that after an awe experience individuals tend to be more altruistic.

63 Key Research Question 3. To what extent does the emotion of awe aﬀect personality reporting?

The personality trait of agreeableness increased in participants after the awe experience. Given that agreeableness is a predictor of cooperation and prosocial behaviour (Habashi et al., 2016; Caprara et al., 2009; Volk et al., 2011; Carlo et al., 2005; Kagel & McGee, 2014), the results here establish a potential indirect relationship between awe and prosocial behaviour/ cooperation.

However this key ﬁnding is not without limitations. To the best of the author’s knowledge, there were no previous studies showing that a shock experience like awe can lead to a sudden change in the measurement of personality traits. For the results to be robust, this ﬁnding has to be replicated in future studies.

In this study, the emotion control in Walk/ No Awe appeared to be unsuccessful. According to Table 12, self-reported awe in the Walk/Awe treatment (M=60.69) is significantly higher than that in the Baseline treatment (M=41.83), with a t-statistic of 2.96 (two-tailed p=0.004). However, it is not significant different to the Walk/No Awe treatment (M=60.73), with a t-statistic of -0.0082 (two-tailed p=0.9934). There is no clear explanation of why the level of self-reported awe in the Walk/No Awe treatment is higher than the anticipated level. It may also imply that the design of an appropriate baseline treatment could be improved.

The design of the Walk/No Awe treatment in this experiment is a potential limitation of this study. The appropriateness of the Walk/No Awe treatment design aﬀects the signiﬁcance and validity of the results, as the main results were produced by comparing the Walk/Awe treatment to the Walk/No Awe treatment.

As with most laboratory experiments, one of the limitations of the study is external validity. Even though the natural environment bears a closer resemblance to a real life awe experience, the intensity and complexity of experimentally elicited awe does differ from a real life awe experience. It is also possible that participants experienced less awe, as they may have felt less relaxed because they were in an experimental environment. As in many other studies conducted with student participants, there are questions as to the extent to which a student sample reflects the entire population. However these limitations point to opportunities for future studies to be carried out in the field, especially given the surprisingly scarce number of studies on the emotion of awe done in the field.

64 The question of how long does the impact of awe experiences last requires further exploration. Understanding that awe experiences generally occur within a short period of time, and understanding whether experiences of awe have a lasting impact on personality reporting is still yet to be studied.

From a neuro-biological standpoint, it would be interesting for future studies to measure the Heart Rate Variability (HRV) or brain activities of participants with the impact of an awe experience. Unfortunately, the scope and duration of this study did not allow inclusion of these factors.

Overall, this study has more ﬁrmly established the social function of awe, and the role of personality traits in the social function of awe. It has facilitated further understanding of awe on both individual and group level. There are important theoretical implications especially for social preferences in decision making.

65 Appendix A

Experiment screenshots

Figure A.1: Welcome page. Participants were to enter their participant label into the box above.

Figure A.2: Welcome Page. The experimenter presented participants with a brief introduction. This screen captures no data.

i Figure A.3: FFM (Pre-treatment). This is the ﬁrst screen of the standard FFM questionnaire before the target experience.

ii Figure A.4: FFM (Pre-treatment). This is the second screen of the standard FFM questionnaire before the target experience.

iii Figure A.5: FFM (Pre-treatment). This is the third screen of the standard FFM questionnaire before the target experience.

iv Figure A.6: Demographic questions. This is the first screen of the demographics questions to be answered by the participants. It includes questions such as age, gender, education, marital status, field of study and whether English is their first language.

v Figure A.7: Demographic questions. This is the second screen of the demographics questions to be answered by the participants. It includes questions regarding their ethnic and religious background.

vi Figure A.8: Demographic questions. This is the third screen of the demographics questions to be answered by the participants.vii It includes questions about their devoutness to religion, interest in politics, political views, next hour activites as in Shiota et al. (2007), life satisfaction, health and comments on the experiment. Figure A.9: Emotional labels (as in Shiota et al., 2007). After the target experience, participants were asked to describe their emotional state according to the emotional labels on a scale of 0-100. Two examples of the emotional labels are shown above.

viii Figure A.10: Instructions for Task A. This screen is to inform participants that Task A is about to start. The instructions for Task A were read aloud by the experimenter. Participants also received a physical copy of the instructions when they reach this screen.

Figure A.11: Contribution page for Task A. Participants were to choose their contribution to the joint project on this page. The top of this page shows participants the round they are in.

ix Figure A.12: Results page. This page shows participants the details of all the contributions in the group, as well as the participants earnings for the round.

Figure A.13: Question on the reasoning behind their decisions. Participants were asked this question about the reasons behind their choice of contribution to the joint project, after round 8.

x Figure A.14: Appraisal endorsement for target experience (as in Shiota et al., 2007). Participants were asked to rate the extent to which they remembered having several appraisals of the target experience, on a scale of 0-100.

Figure A.15: Question on whether the target experience aﬀected their decision to contribute. Participants in the main treatment were asked this question, whether they felt the target experience aﬀecting their decisions on how much to contribute in the PGG.

xi Figure A.16: Question on participants previous visits to the Gibson Room. Partici- pants in the main treatment were asked this question, as familiarity may reduce the level of awe during the experience. Participants were to complete the FFM questionnaire the second time after this question.

Figure A.17: Task B instructions. After the second FFM questionnaire (post- treatment), the instructions for Task B were shown to participants. Participants were told by the experimenter that Task B involves ten decisions of splitting money between you (the participant) and another participant.

xii Figure A.18: Decision Task for Task B. This is the decision task from Kerschbamer (2015), with earnings adjusted.

xiii Figure A.19: Task C instructions. This screen is to inform participants that Task C is about to start. The instructions for Task C were read aloud by the experimenter. Participants also received a physical copy of the instructions when they reach this screen.

xiv Figure A.20: Decision screen for Task C. Participants start collecting boxes by pressing the Start button and they can press Stop anytime. Every second before the Stop button a box will be marked by a tick symbol, indicating that the box is collected. Participants press the Solve button to locate the bomb after pressing Stop.

xv Figure A.21: Results screen for Task C. Participants were informed their earnings for Task C, including the number of boxes collected and whether the bomb is located in one of the boxes they collected.

Figure A.22: Payment screen. This is the ﬁnal screen of the experiment. Participants were informed the details of their earnings from the experiment, including the selected rounds for payment.

xvi Appendix B

Experiment instructions

B.1 Task A instructions

Thank you for participating in this experiment. Please end all conversations now and switch oﬀ your mobile phone.

Please read the following instructions carefully.

Your earnings in this experiment will depend on the choices you make. Please think carefully when making decisions. Your earning will be paid to you in cash at the end of the experiment. The conversion rate of Experimental Cur- rency Units (ECUs) to Australian dollars (AUD) will be 20ECU to $1 AUD.

Task A Task A comprises 16 rounds. You will be in random groups of 3. Each group will be undertaking a joint project Each group member will be endowed with 100 ECUs for every round. In each round, you will be asked to choose how much to contribute to the joint project.

For each round, the contributions of all participants are added up, and multiplied by the factor of 1.5. That resulting amount will be evenly split among all members in the group. Your payoﬀ for that round equals your earnings from the project, plus the amount you did not contribute.

After each round you will see a screen as follows:

xvii ONE round of the game will be randomly selected by the end of the experiment and you will be paid according to your earnings in that round.

B.2 Task C instructions

In the following, you will see a 10x10 matrix containing 100 boxes on your screen. As soon as you start the task by hitting the ’Start’ button, one of the boxes is collected per second, starting from the top-left corner. Once collected, the box marked by a tick symbol. For each box collected you earn 2 ECUs.

xviii Behind one of the boxes hides a bomb that destroys everything that has been collected. You do not know where the bomb is located.

You only know that the bomb can be in any place with equal probability. The longer the collecting process, the more likely it is that one of your ticked boxes contains the bomb but also the more money you will potentially receive.

Your task is to choose when to stop this collecting process. You do so by hitting ’Stop’ at any time. If you collect the box where the bomb is located, the bomb will explode and you will earn zero. If you stop before collecting the bomb, you gain the amount accumulated that far and this is added to your ﬁnal payoﬀ for today.

Please note that you will not know if one of your ticked boxes contains the bomb until AFTER you have pressed the ’Stop’ button.

xix At the end of the task boxes are toggled by hitting the ’Solve’ button. A dollar sign or a ﬁre symbol (for the bomb) will be shown on each of your collected boxes.

xx Appendix C

Other tests

Table C.1: FFM Personality Traits Stability in measurement (Walk/No Awe vs Base- line) FFM Personality Traits Stability in measurement (Walk/No Awe vs Baseline) Rank Correlation z-score Two sample t-test t-stat Agreeableness 0.02 -0.40 Conscientiousness 0.94 1.46 Extraversion 0.20 0.33 Neuroticism -0.43 -0.15 Openness -0.85 -0.99 *** p<0.01, ** p<0.05, * p<0.1

xxi Table C.2: FFM Personality Traits Stability (Walk/No Awe vs Baseline) Depvar: Diﬀerence (1) (2) (3) (4) (5) in personality traits A C E N O

Dummy for Walk/No Awe 0.0379 -0.126 -0.0220 0.0129 0.0756 (0.0946) (0.0866) (0.0673) (0.0853) (0.0762) Constant -0.160** 0.105* -0.0268 0.102* -0.0442 (0.0665) (0.0609) (0.0473) (0.0599) (0.0535)

Observations 83 83 83 83 83 R-squared 0.002 0.026 0.001 0.000 0.012 (A = Agreeableness, C=Conscientiousness, E=Extraversion , N=Neuroticism, O=Openness) Standard errors in parentheses *** p<0.01, ** p<0.05, * p<0.1

No significant effect was found in any measure of the five factors when comparing the Walk/No Awe treatment to the Baseline.

xxii Table C.3: Public Goods Game (Walk/No Awe vs Baseline) (1) Depvar: PGG Contribution ME

Treatment dummy for Walk/No Awe 0.592 (5.327) Self-reported awe 0.0415 (0.0499) Treatment x self-reported awe -0.107 (0.0863) Payoﬀ (previous round) -0.310*** (0.0564) Group contribution (previous round) 0.309*** (0.0166) Round no. -0.833*** (0.208) Age -0.142 (1.077) Treatment x Age 3.911** (1.759) Gender -3.502* (2.114) Constant 49.76*** (6.913)

Observations 1,230 Number of groups 56 Robust standard errors in parentheses *** p<0.01, ** p<0.05, * p<0.1

No signiﬁcant eﬀect was found comparing the contribution levels between the Walk/No Awe treatment to the Baseline.

xxiii Table C.4: Rank Correlation Coeﬃcients (Five Factors Before vs After) Rank Correlation Coeﬃcients (Five Factors Before vs After) (Before and after Baseline Walk/No Walk/ All treatment) Awe Awe Agreeableness 0.86 0.91 0.85 0.87 Conscientiousness 0.88 0.90 0.82 0.88 Extraversion 0.94 0.91 0.92 0.93 Neuroticism 0.91 0.89 0.88 0.90 Openness 0.92 0.90 0.94 0.93

All of the above measures of the five factors before and after the treatment have a significantly positive correlation according to Spearman’s rank correlation coefficients. It shows that the treatment itself does not have an effect on the base measurement of the five factors.

xxiv Appendix D

Experimental treatment

The following pictures show the view from the balcony (Walk/Awe treatment)

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