Online Dispute Resolution: value of bid revision, algorithmic closure, and mechanism transparency

Participants are randomly assigned to one of four dispute-resolution procedures that differ in how settlements are reached after the two sides state how much of a fixed 100-point pie they want. Each participant has an outside option between 0 and 100, uniformlly drawn. Participant knows her outside option, but not the one of the opponent. Barg is direct bargaining without platform mediation. ODR is a one-shot structured procedure that converts the two requests into a nonbinding settlement recommendation when the requests are jointly feasible using second-best mechanism (Chaterjee and Samuelson,1983; Compte and Jehiel, 2009). SeqODR adds one opportunity to revise requests after an initial impasse. AlgODR allows the platform to use an internal rule to generate a compromise recommendation in some cases when the initial requests are incompatible.

2026-06-09

2026-06-30

The primary outcome variables are: breakdown at the pair-round level; individual realized payoff in points; the initial submitted request in ODR, SeqODR, and AlgODR, the revised request in SeqODR; and acceptance or rejection of the platform recommendation in the mechanism-based treatments. The main outcome is payoff.
The outcomes only analyzed for markets where agreement is feasible, namely sum of outside option is below 100.

This is an online experiment conducted on Prolific. Participants are randomly assigned to one of four treatment arms and remain in that arm for all four rounds. Within each treatment arm, participants are organized into groups of four and are randomly rematched into bargaining pairs in each round. In every round, a pair decides how to divide 100 points while each participant privately knows their own outside option, which is independently drawn from a uniform distribution between 0 and 100. One point equals £0.02.
We exclude participants who finish the round faster than 5 seconds.

Not available

Randomization is done by the experimental software using OTree random assignment. At study entry, participants are assigned with equal probability to Barg, ODR, SeqODR,or AlgODR. Within each treatment arm, the software then forms groups of four and randomly rematches participants into pairs in each of the four rounds.

Primary unit of randomization: groups of 4 individual participants.

Yes

200 groups per treatment

3,200 participants in total, corresponding to 12,800 participant-round observations. In expectation, 6,400 could be used for analyses as the sum of outside options will be below 100.

200 groups of four per treatment arm, that is 800 participants in each of Barg, ODR, SeqODR, and AlgODR.
Additionally 150 for sophisticated Algorithm treatment will be collected later.

For continuous individual-level outcomes, including realized payoff and submitted requests, the study has approximately 80 percent power to detect effects of about 0.12 to 0.15 standard deviations for pairwise comparisons between two arms when the intra-cluster correlation is between 0.05 and 0.20. If the standard deviation of realized payoffs is approximately 25 points, this corresponds to a minimum detectable effect of approximately 3 to 4 payoff points. For binary pair-level outcomes such as breakdown, using the conservative benchmark of a 50 percent baseline breakdown rate, the study has approximately 80 percent power to detect differences of about 7.5 to 9 percentage points for pairwise comparisons between two arms when the intra-cluster correlation is between 0.05 and 0.20. For binary individual-level outcomes such as acceptance of a recommendation, the corresponding minimum detectable effect is approximately 6 to 8 percentage points, although the effective sample size for acceptance outcomes may be smaller because acceptance is only observed when a platform recommendation is made. These calculations are intended to guide the main pairwise comparisons and will be complemented by regression specifications that use all feasible observations and include clustered standard errors at the group level. The primary inference will focus on effect sizes and confidence intervals, not only on statistical significance.