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Loss Aversion in Facebook Games
1. Perspective from Behavioral Economics to Analyzing Game Design Patterns: Loss aversion in Facebook games Juho Hamari Helsinki Institute for InformationTechnology HIIT The papercanbefoundhere
2. “a [good] game is a series of interesting choices” – Sid Meier (the father of Civ games)
3. But what happens when games are designed to direct “real-world” choices? Gamification
8. In the following slides some of the most common game mechanics in Facebook games are linked to decision making biases that have been found to nudge our decision It becomes increasingly important to think how game mechanics affect our decision making
9. One perspective:Behavioral economics Behavioral economics = the study of human decision making Prospect theory = the perceived value is based on changes in wealth (reference-dependent) Loss aversion = “Losses loom larger than corresponding gains” Kahneman & Tversky (1979)
12. Endowment effect (Kahneman, Knetsch & Thaler 1991) People feel losses directed to owned goods more strongly than losses which ownership has not been established Implementation: The player is more likely to return to tend the endowments than in a situation where the player would have been simply given the same good(s). (The value function of prospect theory would suggest that) A stick has a bigger impact than a carrot
13. Sunk-cost fallacy(Kahneman & Tversky 1979; Arkes & Blumer 1985) Rational player would: Not account for (sunk)costs which have already incurred What happens: When we put effort to an activity we are reluctant to discontinue it
14. Sunk-cost fallacy(Kahneman & Tversky 1979; Arkes & Blumer 1985) Implementation: “Appointment dynamic” The sunk-cost in plowing the field and planting seeds increases the perceived desirability of returning to the game Enticing players to buy keys to open crates in Team Fortress 2 Enticing players to come back before crops wither away
15. Status-quo effect (Kahneman, Knetsch & Thaler 1991; Samuelson & Zeckhauser 1988) Status-quo effect: People have a tendency to select an alternative that is anchored as the default for them Implementation: “Would you like to share wealth with friends [x] Yes, [] No.” Price anchoring in CityVille
16. Insensitivity to income changes(Bowman et al. 1999 in Camerer 2001) Bias: People have a tendency to continue the same rate of consumption regardless of negative income changes Implementation: Free “starter” currency The expectation is that the player gets used to the level of currency and tends to continue the same level of consumption regardless of negative changes is available currency
18. Quota anchoring(Camerer et al. 1997) Bias:People have a tendency to adhere to quotas they set themselves or that are set for them Implementation: Daily quests anchor a daily quota for players. Not completing the suggested set of daily quests would yield strong dissatisfaction, making the player more likely to spend more time playing
19. Goal-gradient effect(Hull 1932, Kivetz et al. 2006) Bias: The nearer to a completion of a goalplayergets the quickershecompletesit Mechanic: Leveling, progression Games use different kinds of progression metrics to reinforce this effect
20. Endowment progress effect(Nunes & Drèze 2006) Bias:If a player has already gained some progression for free, the more likely she is to complete the challenge Mechanic: Free experience points or XP bonus (e.g. rested in World of Warcraft) In many games players are given some initial progress for free
21. a humble note The presented decision making biases are presented here as hypotheses to how some of the game mechanics affect our decision making. To be absolutely certain about which biases and to what degree they affect our decision making in game contexts, we have to conduct empirical test.
23. References (behavioral economics) Arkes, H. R., & Blumer, C. (1985). The psychology of sunk cost. Organizational Behavior and Human Decision Processes 35(1),124-140. Camerer, C, F. (2001). Prospect theory in the wild: Evidence from the field. In Choices, Values, and Frames, 288-300. Cambridge: Cambridge University Press. Camerer, C, F., Babcock, L., Loewenstein, G., & Thaler, R. (1997). Labor Supply of New York City Cab Drivers: One Day at a Time. Quarterly Journal of Economics, 111, 408-41. Hull, C. L. (1932).The Goal Gradient Hypothesis and Maze Learning. Psychological Review, 39, 25-43 Kahneman, D., Knetsch, J., & Thaler, R. (1991). The Endowment Effect, Loss Aversion, and Status Quo Bias: Anomalies. Journal of Economic Perspectives, American Economic Association, 5(1), 193-206. Kahneman, D. & Tversky, A. (1979). Prospect theory: An analysis of decisions under risk. Econometrica, 47, 313–327. Kivetz, R., Urminsky, O., & Zheng, Y. (2006). The Goal-Gradient Hypothesis Resurrected: Purchase Acceleration, Illusionary Goal Progress, and Customer Retention. Journal of Marketing Research, (February 2006), 39-58. Nunes, J., & Drèze, X. The Endowed Progress Effect: How Artificial Advancement Increases Effort. Journal of Consumer Research, 2006, 32 (4), 504-12. Samuelson, W., & Zeckhauser, R. (1988). Status quo bias in decision making. Journalof Risk and Uncertainty 1 7-59.
24. References(marketing in social games) Hamari, J. (2011). Perspectives from behavioral economics to analyzing game design patterns: loss aversion in social games. CHI'2011 Social games workshop. Hamari, J., & Järvinen, A. (2011). Building Customer Relationship through Game Mechanics in Social Games. In M. Cruz-Cunha, V. Carvalho & P. Tavares (Eds.),Business, Technological and Social Dimensions of Computer Games: Multidisciplinary Developments. Hershey, PA: IGI Global. Hamari, J., & Lehdonvirta, V. (2010). Game design as marketing: How game mechanics create demand for virtual goods. International Journal of Business Science & Applied Management, 5(1), 14-29.