Strategic Allocations in Weighted Networks

Last registered on March 06, 2024


Trial Information

General Information

Strategic Allocations in Weighted Networks
Initial registration date
February 20, 2024

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
March 06, 2024, 3:07 PM EST

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


Primary Investigator

University of Birmingham

Other Primary Investigator(s)

PI Affiliation
University of Leicester

Additional Trial Information

In development
Start date
End date
Secondary IDs
Prior work
This trial does not extend or rely on any prior RCTs.
This project aims to investigate how individuals allocate scarce resources across differently weighted connections within networks. Existing literature highlights the effect of influential, resilient, or valuable connections on decision-making. However, empirical evidence in this area is lacking. Utilizing economic experiments, we seek to explore this phenomenon, contributing both theoretically and experimentally. We have designed a novel experiment to induce weighted networks and analyze allocations in various conflict scenarios. Our methodology ensures unique equilibrium predictions, eliminating potential confounds. Our study's findings will be disseminated widely, enriching the understanding of actual strategic resource allocation in network contexts.
External Link(s)

Registration Citation

Cortes Corrales, Sebastian and David Rojo Arjona. 2024. "Strategic Allocations in Weighted Networks." AEA RCT Registry. March 06.
Experimental Details


Intervention Start Date
Intervention End Date

Primary Outcomes

Primary Outcomes (end points)
1) Individual allocation per decision-problem.
2) Average allocation per decision-problem.
Primary Outcomes (explanation)

Secondary Outcomes

Secondary Outcomes (end points)
1) Individual expected payoff per decision-problem.
2) Average expected payoff per decision-problem.
Secondary Outcomes (explanation)

Experimental Design

Experimental Design
Our experiment implements a series of decision problems in networks of bilateral conflicts. Each connection represents a bilateral conflict between two rivals, and a connection weight represents the value of winning that conflict. To win a conflict, agents simultaneously allocate a scarce resource (i.e., budget of 100 tokens) across their rivals. The value of the remaining budget, which is not allocated, is normalized to zero. The winner of each conflict is determined by a lottery contest success function, where an additional unit of resources allocated to a given conflict increases the likelihood of wining that conflict.

In every decision problem, each subject is matched to another three players at random. The experiment consists of 4 blocks of 18 decision problems each. Within a block, subjects face different decision problems each one associated to a different position in various networks. In particular, we consider six non-isomorphic strongly connected network structures that can be built with a set of four nodes (i.e., complete, diagonal, kite, ring, line, and star networks). Across blocks, the only change is the value of the connection between nodes 2 and 3 while all other values remains the same (300 points). The value of the connection changing across blocks is either 300, 600, 900, or 1200 points. And the order in which subjects face these values is randomized for every session.
Experimental Design Details
Not available
Randomization Method
All randomizations are done by the computer.
Randomization Unit
The unit of randomization is at the experimental session level and individual level.
Was the treatment clustered?

Experiment Characteristics

Sample size: planned number of clusters
Sample size: planned number of observations
10,368 observations.
Sample size (or number of clusters) by treatment arms
144 participants (9 sessions each with 16 participants).
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)

Institutional Review Boards (IRBs)

IRB Name
Humanities and Social Sciences Committee, University of Birmingham
IRB Approval Date
IRB Approval Number