From structure to emergence: an agent-based simulation of multi-mechanism configurations in online charitable donation

Online charitable donation has become a focus of modern philanthropy, yet the mechanisms underlying stable participation remain insufficiently understood. This gap highlights limitations in existing research, which typically investigates influencing factors in isolation through linear explanatory frameworks. To address this, this study employs agent-based modeling (ABM) to explore how varying intensities and combinations of four widely recognized mechanisms—algorithmic recommendation, information transparency, instant feedback, and social recognition—influence online donation behavior. A NetLogo-based simulation involving 500 heterogeneous agents was conducted across 81 mechanism combinations, with 30 repeated runs for each combination to ensure robustness. Results reveal that: (1) donation emerges only when multiple mechanisms operate in combination; (2) high-intensity triadic combinations form the minimum emergent unit; (3) donation engagement becomes more stable when more mechanisms operate jointly as configurations. These findings contribute to the literature in three ways: (1) theoretically, by extending Bekkers and Wiepking’s mechanism framework through the lens of configurational interdependence; (2) methodologically, by applying the ABM approach to online philanthropy; and (3) practically, by providing insights for the design of complementary platform mechanisms that foster sustained donor participation.