QualGames: A Qualtrics implementation and a database of behavioral game theory tasks

Area of Science:

• Behavioral Economics
• Computational Social Science
• Decision Theory

Background:

• Behavioral decision-making tasks are crucial for studying individual and social preferences.
• Scripting complexity on platforms like Qualtrics limits the widespread implementation of these tasks.
• A need exists for accessible tools to conduct large-scale behavioral studies online.

Purpose of the Study:

• To provide a detailed protocol and source code for implementing a modular decision-making task battery in Qualtrics.
• To enable the study of various preferences, including risk-taking, temporal discounting, and social cooperation.
• To facilitate large-scale behavioral game theory research through accessible tools and data.

Main Methods:

• Developed a modular decision-making battery with tasks like social value orientation, prisoner's dilemma, trust game, and risk preference.
• Implemented the battery within the Qualtrics survey platform.
• Collected and analyzed data from 392 participants in Singapore and 94 in the US to validate the battery.

Main Results:

• The task battery demonstrated good data quality and high convergent and divergent validity.
• Participant responses aligned with established behavioral and social decision-making theories, including loss aversion and betrayal aversion.
• Validated the implementation of complex decision-making tasks on a popular online survey platform.

Conclusions:

• The shared protocol and source code enable modular implementation of decision-making tasks in Qualtrics.
• The validated battery supports large-scale behavioral research and hypothesis testing.
• Facilitates cross-population comparisons and the development of simulated agents for asynchronous experiments.