Behavioral Mechanism Design: Optimal Crowdsourcing Contracts and Prospect Theory

D. Easley, Arpita Ghosh
{"title":"Behavioral Mechanism Design: Optimal Crowdsourcing Contracts and Prospect Theory","authors":"D. Easley, Arpita Ghosh","doi":"10.1145/2764468.2764513","DOIUrl":null,"url":null,"abstract":"Incentive design is more likely to elicit desired outcomes when it is derived based on accurate models of agent behavior. A substantial literature in behavioral economics, however, demonstrates that individuals systematically and consistently deviate from the standard economic model---expected utility theory---for decision-making under uncertainty, %a central component of which is at the core of the equilibrium analysis necessary to facilitate mechanism design. Can these behavioral biases---as modeled by prospect theory [Kahneman and Tversky 1979]---in agents' decision-making make a difference to the optimal design of incentives in these environments? In this paper, we explore this question in the context of markets for online labor and crowdsourcing where workers make strategic choices about whether to undertake a task, but do not strategize over quality conditional on participation. We ask what kind of incentive scheme---amongst a broad class of contracts, including those observed on major crowdsourcing platforms such as fixed prices or base payments with bonuses (as on MTurk or oDesk), or open-entry contests (as on platforms like Kaggle or Topcoder)---a principal might want to employ, and how the answer to this question depends on whether workers behave according to expected utility or prospect theory preferences. We first show that with expected utility agents, the optimal contract---for any increasing objective of the principal---always takes the form of an output-independent fixed payment to some optimally chosen number of agents. In contrast, when agents behave according to prospect theory preferences, we show that a winner-take-all contest can dominate the fixed-payment contract, for large enough total payments, under a certain condition on the preference functions; we show that this condition is satisfied for the parameters given by the literature on econometric estimation of the prospect theory model [Tversky and Kahneman 1992; Bruhin et al. 2010]. Since these estimates are based on fitting the prospect theory model to extensive experimental data, this result provides a strong affirmative answer to our question for 'real' population preferences: a principal might indeed choose a fundamentally different kind of mechanism---an output-contingent contest versus a 'safe' output-independent scheme---and do better as a result, if he accounts for deviations from the standard economic models of decision-making that are typically used in theoretical design.","PeriodicalId":376992,"journal":{"name":"Proceedings of the Sixteenth ACM Conference on Economics and Computation","volume":"81 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"32","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the Sixteenth ACM Conference on Economics and Computation","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2764468.2764513","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 32

Abstract

Incentive design is more likely to elicit desired outcomes when it is derived based on accurate models of agent behavior. A substantial literature in behavioral economics, however, demonstrates that individuals systematically and consistently deviate from the standard economic model---expected utility theory---for decision-making under uncertainty, %a central component of which is at the core of the equilibrium analysis necessary to facilitate mechanism design. Can these behavioral biases---as modeled by prospect theory [Kahneman and Tversky 1979]---in agents' decision-making make a difference to the optimal design of incentives in these environments? In this paper, we explore this question in the context of markets for online labor and crowdsourcing where workers make strategic choices about whether to undertake a task, but do not strategize over quality conditional on participation. We ask what kind of incentive scheme---amongst a broad class of contracts, including those observed on major crowdsourcing platforms such as fixed prices or base payments with bonuses (as on MTurk or oDesk), or open-entry contests (as on platforms like Kaggle or Topcoder)---a principal might want to employ, and how the answer to this question depends on whether workers behave according to expected utility or prospect theory preferences. We first show that with expected utility agents, the optimal contract---for any increasing objective of the principal---always takes the form of an output-independent fixed payment to some optimally chosen number of agents. In contrast, when agents behave according to prospect theory preferences, we show that a winner-take-all contest can dominate the fixed-payment contract, for large enough total payments, under a certain condition on the preference functions; we show that this condition is satisfied for the parameters given by the literature on econometric estimation of the prospect theory model [Tversky and Kahneman 1992; Bruhin et al. 2010]. Since these estimates are based on fitting the prospect theory model to extensive experimental data, this result provides a strong affirmative answer to our question for 'real' population preferences: a principal might indeed choose a fundamentally different kind of mechanism---an output-contingent contest versus a 'safe' output-independent scheme---and do better as a result, if he accounts for deviations from the standard economic models of decision-making that are typically used in theoretical design.
行为机制设计:最优众包契约与前景理论
当激励设计基于准确的代理行为模型时,它更有可能引发期望的结果。然而,行为经济学的大量文献表明,在不确定性下的决策中,个人系统地、持续地偏离标准经济模型——预期效用理论,这是促进机制设计所必需的均衡分析的核心组成部分。这些行为偏差——正如前景理论(Kahneman and Tversky, 1979)所建模的那样——在代理人的决策中会对这些环境中激励的最佳设计产生影响吗?在本文中,我们在在线劳动力和众包市场的背景下探讨了这个问题,在这些市场中,工人对是否承担一项任务做出战略选择,但不以参与为条件对质量进行战略选择。我们的问题是,在广泛的合同类别中,包括那些在主要众包平台上观察到的合同,如固定价格或带奖金的基本支付(如MTurk或oDesk),或开放竞赛(如Kaggle或Topcoder等平台),业主可能希望采用哪种激励方案,以及这个问题的答案如何取决于工人的行为是根据预期效用还是前景理论偏好。我们首先证明,对于期望效用代理人,对于委托人的任何增加目标,最优契约总是采取与产出无关的固定支付形式,支付给一些最优选择的代理人数量。相比之下,当代理人按照前景理论偏好行事时,我们证明了在一定的偏好函数条件下,对于总支付足够大的固定支付合同,赢家通吃的竞争可以占主导地位;我们证明,前景理论模型的计量经济学估计文献给出的参数满足这一条件[Tversky和Kahneman 1992;Bruhin et al. 2010]。由于这些估计是基于将前景理论模型拟合到广泛的实验数据,因此该结果为我们关于“真实”人口偏好的问题提供了强有力的肯定答案:如果委托人考虑到理论设计中通常使用的标准决策经济模型的偏差,他可能确实会选择一种根本不同的机制——产出偶然性竞争与“安全的”产出独立方案——并因此做得更好。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信