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Stephen Whyte Thesis DECISION MAKING IN MATE CHOICE MARKETS Stephen Whyte BBus(Econ) with Distinction, MRes(Econ) Principal Supervisor: Prof. Benno Torgler Associate Supervisor: Prof. Uwe Dulleck Associate Supervisor: Dr David A. Savage Submitted in fulfilment of the requirements for Doctor of Philosophy (Economics) School of Economics & Finance QUT Business School Queensland University of Technology 2018 1 Abstract This thesis contributes to the behavioural economic and behavioural science literature by providing empirical evidence of factors that impact large scale decision making in mate choice settings. The thesis consists of five studies. The first three explore human decision making in the online dating market. They utilise both stated preference and actual decision outcomes to explore differences between preference and choice, positive assortment, and specificity of preference for different sexes. Studies four and five concern male and female behaviour in the clinical and informal (online) sperm donation markets. These studies explore factors that impact female’s decision to choose specific donors, and the characteristics, personality and behaviour of males who choose to donate. 2 3 Keywords Decision making; Mate choice; Sex differences; Online dating; Online sperm donor; Nonbinary gender; Parental investment theory; Positive assortment; Homogamy; Preference; Choice. 4 5 Acknowledgments Thank you to Benno Torgler and Uwe Dulleck for your incredible support and encouragement across my research journey. Your generosity, knowledge, wisdom, empathy, leadership, humour and understanding has inspired me every day. No words can express how much I appreciate all that you have done for myself and my family, and how dearly I value our friendship. To all the QUT Econ team, past and present, thank you for listening, helping, crying with, laughing at and with, drinking with, bitching and whinging, and most of all supporting me in any and every way that you did. I hope you enjoyed it, because I loved every second and I had an absolute blast working with you all. Thank you to Ben, Naomi, David, Marco, Sam, Juliana, Suzanne, AKK, Dr Mueller, Jieyang, Harry, Azhar, Jonas, Louisa, Tommy, Tony, Lionel, Megan, Jason, Gaurav, Chris, Poli, Lisa, Alice, Zili, Vlad, and anyone else I’ve missed. To Pascalis, Michelle, Kristin, Katalina, my best buds in Finance Mary and Alice, Gareth, Lee, Diane, Brian, Takae, Maria, and any and all other QUT admin I’ve missed, thank you for all your support and help. To all of the amazingly talented scientists who have been gracious enough to give their time in supporting me and my research along the way. Thank you to Douglas T. Kenrick, Steven Neuberg, Dan Conroy-Beam, Todd K. Shackelford, Jaimie Krems, Jordan Moon, Bill von Hippel, Karin Hammarberg, Khandis Blake, Dax Kellie, Mike Kasumovic, Amany Gouda-Vossos, Ahmed Skali, Gigi Foster, Barnaby J. Dixon, David Stadelman, and Robert C. Brooks. Thank you to Marilyn Healy and all the Kelvin Grove QUT Human Research Ethics Team. Thank you for being the Batman to my Joker, or the Joker to my Batman, I often got confused who was playing which role in the soap opera that was my research journey. Your feedback on my work taught me so much about myself, thank you. 6 I would like to recognize and thank Lifeline for its valued role in Australian human behavioural research support, as well as acknowledge funding support from an Australian Government Research Training Program Scholarship. Thank you to all the external stakeholders who took a chance on me and helped me do something great. Erika Tranfield at PrideAngel, James Templeman at GIGA, Dave Heyson at RSVP and Keith Harrison at QFG. Without your faith in me and your passion for science I wouldn’t have had any data. Thank you for the trust and belief in my ability that you showed. Thank you to the more than 50,000 people globally that willingly provided data for the studies in this thesis. Thank you to Ash, Ethan, Will and Poppy for all your support and encouragement. I’m sorry that my PhD took so much time away from you all. I hope all my hard work has inspired you to follow your dream, no matter what that may be. I will always be your biggest supporter. I hope you believe in yourself as much as I believe in you, the future will always be bright for you. Thank you to my mum Carmel for sticking by me through thick and thin, you never stopped believing in me. Thank you to Diz, Avi, Leela, for all your love and support. Thank you to Ciara and Emily for being a special part of our family at a time when we needed it most. And finally thank you to Priscilla, who is the reason I started this journey a decade ago. Thank you for helping me to realise my dream, I will always be thankful for all of your support across the last nine years, I couldn’t have done it without you. 7 Table of Contents List of Figures 10 List of Tables 12 List of Publications 15 Statement of Authorship 16 Chapter 1: General Introduction 17 Outline of Thesis 20 Chapter 2: Things change with age: Educational assortment in online dating 22 Introduction 23 Background 24 Methods 27 Participant Pool 27 Data Collection 29 Experimental Model 29 Results 31 Discussion 38 Conclusion 40 Chapter 3: Preference vs. Choice in online dating 42 Introduction 43 Method 45 Participants 45 Procedures 46 Results 47 Discussion 52 Conclusion 54 Chapter 4: Do women know what they want? Sex differences in online daters 57 educational preferences Introduction 58 Method 59 Participants 59 Data collection and ethical practice 60 Measures 61 Preference specificity 61 Preference for homogamy or hypergamy 62 Minimum acceptable level of education 63 Empirical analysis 63 Results 64 Discussion 71 8 Chapter 5: What women want in their sperm donor: A study of more than 73 1000 women’s sperm donor selections Introduction 74 Method 77 Data 77 Results 82 Discussion 88 Limitations 90 Conclusion 93 Chapter 6: Online sperm donors: The impact of family, friends, personality 95 and risk perception on behaviour Introduction 96 Method 100 Data collection 100 Multivariate analysis 108 Results 109 Discussion 113 Chapter 7: Summary and Conclusion 119 Summary of findings 119 Limitations 121 Chapter 2, 3 & 4: Online dating 121 Chapter 5 & 6: Sperm donation in clinical and informal markets 121 Directions for future research 122 Bibliography 125 Appendices: Statement of author contribution 134 9 List of Figures Figure 1. Age distribution 28 Figure 2. Educational hypergamy to hypogamy 30 Figure 3. Predicted margins for assortative mating, with a focus on age slopes as a 35 function of education (linear prediction). Figure 4 Predicted margins for educational hypergamy, with a focus on age slopes by 37 gender (linear prediction). Figure 5. Predicted margins for educational hypogamy, with a focus on age slopes by 37 gender (linear prediction). Figure 6. Percentage of participants contacted matching up to 7 characterist ics 47 Figure 7. Average marginal effect: Age and Gender 51 Figure 8. Average Marginal effect: Age and Education 52 Figure 9. Age distribution differentiated by sex 60 Figure 10. Percentage of sample stating an explicit educational preference 65 Figure 11. Marginal effects of sex and member’s age on the probability of stating an 68 explicit educational preference with effects of control variables reported in Table 1 taken out Figure 12. Specificity of educational preference: Pickiness 68 Figure 13. Preference for educational homogamy or hypergamy in ideal partner by 69 Figure 14. Lowest minimum acceptable educational preference in ideal mate 70 Figure 15. Frequency of sperm sample reservation (90.82% of sample) 80 Figure 16. Frequency of sperm sample reservation (49.48% of sample) 80 Figure 17. Average days elapsed between reservations (N = 1546) 81 Figure 18. Average days elapsed between reservations (49.48% of sample) 82 Figure 19. Average marginal effects: age and reservation order 87 Figure 20. Distribution of donor age 102 10 Figure 21. Distribution of donor risk perception towards informal donation 102 Figure 22a. Predicted margins for total number of women donated to 112 Figure 22b. Predicted margins for number of years informally donating 112 11 List of Tables Table 1. Descriptive statistics on participant and contact’s educational background 29 Table 2. Positive educational assortment (based on OLS & probit regressions) 33 Table 3. Educational hypogamy and hypergamy 34 Table 4. OLS analyzing matches of stated preference and actual choice 49 Table 5. Negative binomial model analyzing matches of stated preference and actual choice 50 Table 6. Regression Coefficients from Multivariate Models of Participant Educational 66 Preference Table 7. Factors influencing number of days until reservation 84 Table 8. Interaction effects: Donor Age and reservation order 86 Table 9. Average Marginal Effects: age and reservation order 88 Table 10. Donor descriptive statistics 101 Table 11. Factors impacting number of average monthly informal donations (Nbreg) 103 Table 12. Factors impacting number of years donating informally (Nbreg) 104 Table 13. Factors impacting total number of women informally donated to in lifetime (Nbreg) 105 Table 14. Factors impacting number of offspring from donation (Nbreg) 106 Table 15. Factors impacting risk attitudes to informal donation (OLS) 107 12 List of Publications This thesis is presented in the form of peer reviewed published papers. The thesis is comprised of the following five manuscripts. 1. Whyte, S., & Torgler, B. (2017). Things change with age: Educational assortment in online dating. Personality and Individual Differences, 109, 5-11. 2. Whyte, S., & Torgler, B. (2017). Preference versus choice in online dating. Cyberpsychology, Behavior, and Social Networking, 20(3), 150-156. 3. Whyte, S., Chan, H.F., & Torgler, B. (2018) Do women know what they want? Sex differences in online daters educational preferences.
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