Experimental dataset on public bad dilemmas: effects of cost level and framing on decision-making

Description

This dataset contains data from a repeated-measures factorial experiment on decision-making in public bad dilemmas. The experimental design follows a 3 × 3 × 3 × 2 structure, manipulating cost level (low, medium, high), available decision time (7, 4, 1), public bad state (25%, 55%, 85%), and task framing (environmental vs. neutral). The dataset includes observations from 51 participants. Each row corresponds to an individual participant and contains: (a) an anonymized participant identifier, (b) experimental condition indicators, and (c) responses recorded for each combination of factor levels. Responses are organized in a wide (horizontal) format, where each variable represents a specific combination of factor levels (e.g., public bad state × time × cost × framing). Variable names follow a structured naming convention encoding these dimensions. All data have been anonymized and do not contain personally identifiable information. A codebook is included to document variable names, factor levels, and coding schemes, facilitating interpretation and reuse of the dataset. This dataset enables replication of the experimental design and supports further analysis of decision-making patterns across factorial conditions.

Steps to reproduce

Data were collected through a computerized experimental task designed to simulate decision-making in public bad dilemmas. Participants completed a repeated-measures task in which they made consumption decisions across multiple trials under systematically varied experimental conditions. The study followed a 3 × 3 × 3 × 2 factorial design manipulating cost level (low, medium, high), available decision time (7, 4, 1), public bad state (25%, 55%, 85%), and task framing (environmental vs. neutral). All participants were exposed to all conditions. On each trial, participants were presented with information about the current state of the public bad, the available time to make a decision, and the cost level associated with their choice. Based on this information, they selected a level of consumption contributing to the public bad. The task was implemented using a computerized interface, and responses were recorded automatically. Data were exported and structured in a wide format, where each variable corresponds to a specific combination of experimental conditions. Data preprocessing involved anonymization of participant identifiers and organization of responses for analysis. No additional data transformations were applied beyond structuring the dataset for analysis. This description, together with the provided dataset and codebook, allows for replication of the experimental structure and analytical procedures.

Institutions

• Universidad Nacional Autónoma de México

  Mexico City, Mexico City
• National Autonomous University of Honduras

  Francisco Morazán Department, Tegucigalpa

Categories

Funders

• Universidad Nacional Autónoma de México

  Mexico City, Mexico City
• Secretaría de Ciencia, Humanidades, Tecnología e Innovación

  Mexico City, Mexico City

  Grant ID: unam

Licence