The online laboratory: conducting experiments in a real labor market
The online laboratory: conducting experiments in a real labor market
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DOI：
10.1007/s10683-011-9273-9
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发表时间：
2011-09-01
影响因子：
2.3
通讯作者：
Zeckhauser, Richard J.
中科院分区：
文献类型：
--
作者：
Horton, John J.;Rand, David G.;Zeckhauser, Richard J.
在线劳动力市场作为进行实验的平台具有巨大的潜力。它们提供了对大量和多样化的受试者的即时访问，并允许研究人员控制实验环境。我们发现，无论是在内部还是在外部，在线实验都可以与实验室和现场实验一样有效，而设计和实施往往需要更少的资金和时间。为了证明它们的价值，我们使用了一个在线劳动力市场来复制三个经典的实验。第一项研究发现，在网上和物理实验室中扮演的囚徒困境中，合作水平之间存在数量上的一致性。第二个实验显示--与传统实验室中的行为一致--在线受试者通过改变自己的选择来回应启动。第三个证明了，当一个相同的决定被不同地框定时，个人会改变他们的选择，从而复制了著名的Tversky-Kahneman结果。然后，我们进行了现场实验，发现工人的劳动供给曲线呈向上倾斜的趋势。最后，我们分析了在线实验面临的挑战，提出了应对在线环境下有效性的独特威胁的方法，并检查了围绕在线结果外部有效性的概念性问题。最后，我们提出了我们对在线实验在社会科学中可能扮演的角色的看法，然后建议软件开发的优先事项和最佳实践。
Online labor markets have great potential as platforms for conducting experiments. They provide immediate access to a large and diverse subject pool, and allow researchers to control the experimental context. Online experiments, we show, can be just as valid-both internally and externally-as laboratory and field experiments, while often requiring far less money and time to design and conduct. To demonstrate their value, we use an online labor market to replicate three classic experiments. The first finds quantitative agreement between levels of cooperation in a prisoner's dilemma played online and in the physical laboratory. The second shows-consistent with behavior in the traditional laboratory-that online subjects respond to priming by altering their choices. The third demonstrates that when an identical decision is framed differently, individuals reverse their choice, thus replicating a famed Tversky-Kahneman result. Then we conduct a field experiment showing that workers have upward-sloping labor supply curves. Finally, we analyze the challenges to online experiments, proposing methods to cope with the unique threats to validity in an online setting, and examining the conceptual issues surrounding the external validity of online results. We conclude by presenting our views on the potential role that online experiments can play within the social sciences, and then recommend software development priorities and best practices.