The BCD of response time analysis in experimental economics.
The BCD of response time analysis in experimental economics.
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DOI：
10.1007/s10683-017-9528-1
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发表时间：
2018
影响因子：
2.3
通讯作者：
Ortmann A
中科院分区：
文献类型：
--
作者：
Spiliopoulos L;Ortmann A
对于野外的决策来说，时间是至关重要的。可用的决策时间往往由于自然或人为的限制而缩短，或者受到时间机会成本的影响。实验经济学家直到最近才开始进行有时间限制的实验，并分析反应时间（RT）数据，这与实验心理学家相反。RT分析已被证明是有价值的个人和战略决策过程的识别，包括识别社会偏好在后一种情况下，模型比较/选择，并通过利用环境干扰的联合收割机的速度和性能的竞争力的调查。在这里，我们专注于RT分析在战略决策中的好处，挑战和迫切需要。我们认为，释放RT分析的潜力需要采用基于过程的模型，而不是基于结果的模型，并讨论了如何在野外RT可以在实验室的时间限制的实验中捕获。我们的结论是RT分析具有相当大的潜力，实验经济学，值得更多的关注作为一种方法论工具，并承诺在自然发生的环境中的战略决策的重要见解。
For decisions in the wild, time is of the essence. Available decision time is often cut short through natural or artificial constraints, or is impinged upon by the opportunity cost of time. Experimental economists have only recently begun to conduct experiments with time constraints and to analyze response time (RT) data, in contrast to experimental psychologists. RT analysis has proven valuable for the identification of individual and strategic decision processes including identification of social preferences in the latter case, model comparison/selection, and the investigation of heuristics that combine speed and performance by exploiting environmental regularities. Here we focus on the benefits, challenges, and desiderata of RT analysis in strategic decision making. We argue that unlocking the potential of RT analysis requires the adoption of process-based models instead of outcome-based models, and discuss how RT in the wild can be captured by time-constrained experiments in the lab. We conclude that RT analysis holds considerable potential for experimental economics, deserves greater attention as a methodological tool, and promises important insights on strategic decision making in naturally occurring environments.
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影响因子：
2
作者：
Alos-Ferrer, Carlos
通讯作者：
Alos-Ferrer, Carlos
影响因子：
2.5
作者：
Ahn, Woo-Young;Busemeyer, Jerome R.;Stout, Julie C.
通讯作者：
Stout, Julie C.
DOI：
10.1007/s40881-015-0003-5
发表时间：
2015-12-01
影响因子：
1.9
作者：
Agranov, Marina;Caplin, Andrew;Tergiman, Chloe
通讯作者：
Tergiman, Chloe
影响因子：
3.5
作者：
Alos-Ferrer, Carlos;Strack, Fritz
通讯作者：
Strack, Fritz
影响因子：
5.4
作者：
Achtziger, Anja;Alos-Ferrer, Carlos
通讯作者：
Alos-Ferrer, Carlos