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The Antecedents to CEO Political Stances
Initial registration date
July 06, 2020
July 08, 2020 5:10 PM EDT
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University of Toronto, Rotman School of Management
Other Primary Investigator(s)
Additional Trial Information
What factors lead CEOs to take political stances as part of a business strategy? Prior research has found that CEO political stances have strategic implications for stakeholders (such as workers and consumers), while politically motivated social agitation from outside groups can impact board departures. In this study, I plan on running a lab-in-the-field experiment examining the role of personal profits, cause-CEO value alignment, and sustained stakeholder pushback on participants’ willingness to take a costly political stand as part of a business strategy. This project aims to contribute causal antecedents to literature on the strategic implications of CEO sociopolitical stances.
This intervention involves the impact of cause-participant values alignment and stakeholder pushback on participants' decision to take a costly political stance for a cause as part of a business strategy.
Intervention Start Date
Intervention End Date
Primary Outcomes (end points)
(1) Participant choice to take a costly political stand and (2) participant choice to persist in stand-taking
Primary Outcomes (explanation)
(1) will be constructed as a binary variable that takes the value 1 when the participant donates in a period and 0 otherwise. (2) will be constructed as a binary that takes the value 1 if the participant switches between donating / not donating either one or zero times throughout the experiment and 0 otherwise.
Secondary Outcomes (end points)
(1) Participant performance
Secondary Outcomes (explanation)
(1) will be measured both as the sum of total earnings and donations and total earnings net of donations.
This experimental project will consist of two studies run with American participants on Prolific.
The first study will examine the impact of cause-participant values alignment on stand-taking. Stance taking is operationalized as a costly donation from the participant's period earnings to the cause (10% of period earnings). I will recruit equal numbers of American liberals and conservatives who will be randomly assigned to one of three political causes: a social liberal cause (Everytown for Gun Safety), a social conservative cause (the National Rifle Association), and an apolitical cause (the American Red Cross). This experiment, therefore, will have 6 randomized cells. At the beginning of the game, participants will be shown one reference point of personal earnings they could make from not taking a stance. Participants will then play 5 periods of a game in which they will vary the production inputs (including political stances), each of which is associated with a personal earnings value. After 5 periods, participants will be shown a reference point of personal earnings they could make from taking a stance; this earnings reference point is roughly 20% higher than the original, no-stance reference point. Participants will complete 5 more periods, be asked a short questionnaire on demographics, ethics, and beliefs, and will be paid from two randomly chosen periods (one from the first 5 periods, one from the second 5 periods). The show-up fee (i.e., payment floor) is $3.00. Participants will be paid any extra money they earn above $3.00 as bonus. The experiment will take roughly 15 minutes to complete.
The second study will be identical to the first except for two changes. First, the experiment will add a "reputation penalty", in which prospective participant earnings from strategies where they do not take a stand are reduced by $0.50 for each previous period in which they took a stand. This penalty is meant to approximate reputation penalties from stakeholders who able to punish the firm when the firm attempts to "reverse" their stance. Second, this study will only recruit American liberals (due to a lack of predicted differences between the political groups using the treatment).
Experimental Design Details
randomization done in office by a computer
Was the treatment clustered?
Sample size: planned number of clusters
800 subjects in total; clustering at individual level
Sample size: planned number of observations
800 subjects in total
Sample size (or number of clusters) by treatment arms
100 subjects per cell
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
Sample sizing estimates come from a similar prominent study. The first, Ederer and Manso (2013), use a very similar economic game to understand how incentive structures impact exploration. They measure a binary choice variable for exiting an exploration phase, which is similar to the binary targets that I plan to use. They target 70 participants per cell in their experiment. Using their study as a guide, I conservatively estimate in my study that the two means of the stance-taking binary variable will be 0.6 and 0.8, with a standard deviation of 0.5. Using 80% power and 5% significance and 50-50 balance, the sample size needed for this minimum detectable effect size is 99 per cell, so I will target 100 participants per cell.
INSTITUTIONAL REVIEW BOARDS (IRBs)
University of Toronto Research Ethics Board
IRB Approval Date
IRB Approval Number