Using process tracing to predict charitable donations

Area of Science:

• Behavioral Economics
• Psychology
• Human-Computer Interaction

Background:

• Donors balance prosocial desires with financial self-interest.
• Understanding the dynamics of these conflicting motivations is crucial for charitable giving research.

Purpose of the Study:

• To dynamically examine how prosocial and self-interested motives influence online donation decisions.
• To investigate the predictive power of cursor movement data in understanding donor behavior and conflict.

Main Methods:

• Two laboratory experiments utilized mouse cursor tracking during online donation tasks.
• Analyzed cursor trajectories to assess the timing of prosocial vs. self-interested attribute influence.
• Developed cursor-derived measures of decision conflict to predict donation outcomes.

Main Results:

• Earlier consideration of prosocial attributes correlated with increased donation rates.
• Cursor-derived conflict metrics predicted donation outcomes and identified distinct donor types.
• Cursor movement data demonstrated superior predictive accuracy for donation decisions compared to response times and traditional measures.

Conclusions:

• Cursor-tracking methodology offers valuable, dynamic insights into the complex decision-making processes of donors.
• Dynamic cursor metrics provide a nuanced approach to understanding trade-offs between self-interest and prosociality in charitable giving.
• This approach enhances theoretical understanding and predictive accuracy in donor behavior research.