Individual vs Strategic Decision-Making: A Key to Work Performance

Last registered on July 19, 2023

Pre-Trial

Trial Information

General Information

Title
Individual vs Strategic Decision-Making: A Key to Work Performance
RCT ID
AEARCTR-0010284
Initial registration date
July 13, 2023

Initial registration date is when the trial was registered.

It corresponds to when the registration was submitted to the Registry to be reviewed for publication.

First published
July 19, 2023, 2:28 PM EDT

First published corresponds to when the trial was first made public on the Registry after being reviewed.

Locations

Region

Primary Investigator

Affiliation

Other Primary Investigator(s)

PI Affiliation
School of Economics and Management, Tsinghua University
PI Affiliation
School of Economics and Management, Tsinghua University
PI Affiliation
Division of Social Science, New York University Abu Dhabi

Additional Trial Information

Status
Completed
Start date
2022-11-09
End date
2022-11-16
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
Abstract

We always make decisions, sometimes on individuals, like shopping, allocating time to different task, etc., and sometimes strategically, like promoting goods to customers, playing tennis, etc. Theoretically, we often assume that people do maximization in these decisions. These assumptions of rationalities are prominent in economics. However, empirically, the quality of these decisions is mixed and depends on the ability whether people do their maximization. We believe that most people are not rational, do non-optimal behavior, i.e., not maximizing their utilities. However, little is known when we look at them in a general decision-making mechanism including these two kinds of irrationality. How common and how heterogeneous is it for people to exhibit multiple irrationality? How are rationalities correlated and interact within-people and how distinct are they? What do they imply or affect field behaviors in real lives?

We address such questions with evidence, from a large national real estate brokerage firm, on the brokers' experimental data from multiple task on rationality and their field behaviors of multiple real estate brokerage. For each of 10000+ broker agents, we measure a set of decision makings quality. Specifically, we measure GARP consistency in standard convex budget sets of risk preference, violations of choices in an evaluating real estates task as proxy variables for individual decision-making rationality. We measure strategic decision-making rationality in 11-20 Game, as proxy variables for strategic decision makings skills. We also measure cognitive skills in Raven's IQ Test, theory of mind ability in Reading the Minds of Eyes, personality traits in Big Five and demographics. Then we try to link these experimental results to their field behaviors, like performance of real estate brokerage transactions.
External Link(s)

Registration Citation

Citation
Liu, Tracy Xiao et al. 2023. "Individual vs Strategic Decision-Making: A Key to Work Performance." AEA RCT Registry. July 19. https://doi.org/10.1257/rct.10284-1.0
Experimental Details

Interventions

Intervention(s)
We measure individual decision-making rationality and strategic decision-making rationality. As such, we do not have an experimental intervention. Rather, we rely in natural variation on subject's characteristics.
Intervention (Hidden)
Intervention Start Date
2022-11-09
Intervention End Date
2022-11-16

Primary Outcomes

Primary Outcomes (end points)
1. Individual decision-making rationality
We use revealed preference analysis to check whether subjects’ behavior comply with utility maximization hypothesis. It will be done by checking whether individual behavior is consistent with the Generalized Axiom of Revealed Preferences (GARP) and measuring the extent to which it violates GARP. We use various indices of measuring GARP violations, including Afriat’s Critical Cost Efficiency Index (CCEI). This will be separately done in domains of decision-making under risk preference, house preference.

2. Strategic decision-making rationality
We use level-k model to check subjects’ choices from 11-20 game. The behaviors in 11-20 game reflect the interaction between the ability of steps reasoning and the ability of predicting opponents' behavior. We firstly measure strategic sophistication, depth of reasoning ability, by the average guessing number in rounds of 11-20 game. We secondly measure strategic intelligence, predicting opponents' behavior, by the payoff in rounds of 11-20 game.

Primary Outcomes (explanation)
1. Individual rationality in risk preference
Following Choi et al. (2007, 2014), Subjects have 100 points to allocate between two accounts where a point has different RMB value in 22 rounds. With these decisions, we can observe violations of GARP (Generalized Axiom of Revealed Preferences) and compute their Critical Cost Effective Index and Money Pump Index.

2. Individual rationality in house preference
We design a novel transitivity paradigm to obtain measurements of decision-making in real estate, where
we ask participants to make pairwise decisions between options. In the survey, subjects are presented with 21 trials which are consisted of all pairwise non-repeating combinations of 7 housing options. In each round, A subject is asked to select the option with higher list price. With these decisions, we can observe the number of transitivity violation, the minimum number of choices that need to be removed to restore transitivity in all choices, how much the choices deviate from real price rankings.

3. Strategic rationality in 11-20 Game
We design an incentivized competitive game of a variant of Arad and Rubinstein (2012)’s 11-20 Money Request game, which is designed to trigger level-k thinking. The subjects face 5 rounds of 11-20 game, varying incentives games. We firstly measure the average guessing number in rounds of 11-20 game and the payoff in rounds of 11-20 game.

Secondary Outcomes

Secondary Outcomes (end points)
Our secondary outcomes include (1) individuals' IQ, (2) individual CRT scores, (3) big five personality traits and (4) Reading the Mind in the Eyes Test scores.
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
We design a survey experiment in leading real estate agency platform in China. The experiment consists of four sections. In Section 1, in the risk task, subjects are asked to allocate a budget between two risky assets, each one of which obtains with a probability of 0.5. The assets have different payoffs, so that allocations give an indication of risk preferences. There are 22 questions in this task. In Section 2, in the house task, subjects are presented with 21 trials which are consisted of all pairwise non-repeating combinations of 7 housing options. A subject is asked to select the option with higher list price. In Section 3, subjects play an incentivized competitive game of a variant of Arad and Rubinstein (2012)’s 11-20 Money Request game. We randomly rematched subjects and gave subjects no feedback about their performance during the course of the experiment. The subjects face 5 rounds of 11-20 game of varying incentives. In Section 4, we measure 5 Big personality of subjects, subjects' IQ by Raven Test, CRT scores, and Reading the Mind in the Eyes Test scores.
Experimental Design Details
Randomization Method
Subjects were randomly assigned to different versions of the survey. The difference of survey is the order of questions and order of tasks. This randomization was done by the software used to conduct the survey.
Randomization Unit
15000 Subjects
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
15000 Subjects
Sample size: planned number of observations
15000 Subjects
Sample size (or number of clusters) by treatment arms
15000 Subjects
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
IRB

Institutional Review Boards (IRBs)

IRB Name
IRB Approval Date
IRB Approval Number

Post-Trial

Post Trial Information

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Intervention

Is the intervention completed?
No
Data Collection Complete
Data Publication

Data Publication

Is public data available?
No

Program Files

Program Files
Reports, Papers & Other Materials

Relevant Paper(s)

Reports & Other Materials