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Field Before After
Trial Status in_development completed
Last Published April 12, 2022 08:17 AM June 12, 2026 12:32 AM
Primary Outcomes (End Points) sell: dummy variable = 1 if seller decides to offer a product for sale buy: dummy variable = 1 if buyer decides to purchase a product price: price at which product was purchased STUDY 1: sell: dummy variable = 1 if seller decides to offer a product for sale buy: dummy variable = 1 if buyer decides to purchase a product price: price at which product was purchased STUDY 2: offer: whether the Seller offers a product for sale offer price: the price at which the Seller offers the product for sale buy: whether the Buyer chooses to buy a product wtp: the Buyer's willingness to pay belief_maxwtp: the Seller's beliefs about the Buyer's wtp
Experimental Design (Public) Participants will engage in a laboratory market game with real stakes for themselves and a bystander. Sessions are randomly assigned to one of three experimental conditions - a control and two treatments. In the two treatments, the framing of the negative externality produced by the players is altered. STUDY 1 Participants will engage in a laboratory market game with real stakes for themselves and a bystander. Sessions are randomly assigned to one of three experimental conditions - a control and two treatments. In the two treatments, the framing of the negative externality produced by the players is altered. STUDY 2 Study 2 implements a similar design but using an online asynchronous market on Qualtrics.
Randomization Method Assignment of conditions to sessions is done non-randomly to ensure even spread across days/times; participants sign up for days/times according to their schedule preferences; payment round is determined randomly by the computer STUDY 1: Assignment of conditions to sessions is done non-randomly to ensure even spread across days/times; participants sign up for days/times according to their schedule preferences; payment round is determined randomly by the computer STUDY 2: Randomization of condition assignment is performed using Qualtrics' built-in functions.
Randomization Unit experimental sessions STUDY 1 experimental sessions STUDY 2 individual
Planned Number of Clusters approximately 18 - will depend upon group size and interest at recruitment STUDY 1 approximately 18 - will depend upon group size and interest at recruitment STUDY 2 Plan to recruit 2,158 participants
Planned Number of Observations As many as can be recruited - up to 600 students. STUDY 1 As many as can be recruited - up to 600 students. STUDY 2 Plan to recruit 2,158 participants - each will make 2 decisions = 4,316 observations
Sample size (or number of clusters) by treatment arms Approximately 200 depending upon scheduling. If sessions get out of balance due to cancellations, etc., we will err on the side of oversampling experimental sessions. STUDY 1 Approximately 200 depending upon scheduling. If sessions get out of balance due to cancellations, etc., we will err on the side of oversampling experimental sessions. STUDY 2 T1: 120 Sellers, 96 Buyers, 96 Bystanders T2: 55 Sellers, 44 Buyers, 44 Bystanders T3: 55 Sellers, 44 Buyers, 44 Bystanders T4: 120 Sellers, 96 Buyers, 96 Bystanders T5: 120 Sellers, 96 Buyers, 96 Bystanders T6: 120 Sellers, 96 Buyers, 96 Bystanders T7: 120 Sellers, 96 Buyers, 96 Bystanders T8: 120 Sellers, 96 Buyers, 96 Bystanders
Power calculation: Minimum Detectable Effect Size for Main Outcomes Assuming an alpha of 0.01, power of 0.80, a minimum effect size of 0.15 and approximately four predictors, we expect to need approximately 120 participants in our buyer analysis (online a priori sample size calculator for multiple regression: https://www.danielsoper.com/statcalc/calculator.aspx). This would require a sample size of approximately 500 participants due to the study design. We plan to attempt to recruit up to approximately 600 participants overall. STUDY 1 Assuming an alpha of 0.01, power of 0.80, a minimum effect size of 0.15 and approximately four predictors, we expect to need approximately 120 participants in our buyer analysis (online a priori sample size calculator for multiple regression: https://www.danielsoper.com/statcalc/calculator.aspx). This would require a sample size of approximately 500 participants due to the study design. We plan to attempt to recruit up to approximately 600 participants overall. STUDY 2 Although we found statistically significant treatment effects (profit vs. control) in Study 1, the study was underpowered due to logistical issues. For example, the effect size when assessing the average offer price (averaged across all regular rounds) across treatment group, we find that the observed effect size was large – d = 2.22. Analysis using gpower demonstrates that our sample sizes in Study 1 allow us to identify a medium effect size (d = 0.5; a difference of approximately 2 experimental points) with a power of just 0.36 at 𝛼=0.01. Assuming similar means and standard deviations in the online study, 96 participants per role per treatment are needed to identify a medium effect size at 𝛼=0.01 and a power of 0.80 (T1, T4, T5, T6, T7, T8). For within-subjects analysis (T2, T3), we need only 43 participants per role to identify a medium effect size at 𝛼=0.01 and a power of 0.80.
Intervention (Hidden) Experimental conditions in the study vary the conceptual frame of the negative externality. In the control (control), the outcomes of the bystander are not reframed for the participants – payoffs associated with choices are simply provided. In the first treatment (reduced), the outcome of the bystander is framed as a reduction in the bystander’s payoff. In the second treatment (profit), the buyer and seller are described as profiting at the expense of the bystander. We examine whether subjects’ willingness to sell and buy this “unfair” product is impacted by the conceptual frame. STUDY 1: Experimental conditions in the study vary the conceptual frame of the negative externality. In the control (control), the outcomes of the bystander are not reframed for the participants – payoffs associated with choices are simply provided. In the first treatment (reduced), the outcome of the bystander is framed as a reduction in the bystander’s payoff. In the second treatment (profit), the buyer and seller are described as profiting at the expense of the bystander. We examine whether subjects’ willingness to sell and buy this “unfair” product is impacted by the conceptual frame. STUDY 2: This study uses a similar set of interventions. In the placebo, participants are given a brief summary of what the Buyer, Seller, and Bystander do in the study. In the byproduct statement, the effects of the market outcome are framed as byproducts. In the profit statement the buyer and seller are described as profiting at the expense of the bystander.
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Irbs

Field Before After
IRB Name Santa Clara Univesi
IRB Approval Date May 08, 2026
IRB Approval Number 20-02-1424
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