Decoding Public Preferences in Volunteer Service Projects: An Empirical Study Based on Conjoint Experiment and Machine Learning Approaches

Volunteer engagement is essential for the sustainable service provision of nonprofit organizations (NPOs), yet existing research has provided limited guidance on how organizations can design volunteer programs to attract participants. This study addresses this gap by examining volunteer engagement from the perspective of NPO volunteer project design. Drawing on qualitative interviews, the study first identifies eight key attributes that influence volunteer decision‐making, encompassing both instrumental dimensions (training plans, time arrangements, service modes, and compensation policies) and symbolic dimensions (information disclosure, project objectives, recruitment slogans, and political connections). Through a conjoint experiment, the study then determines the combinations of volunteer service program attributes most preferred by the Chinese public, revealing that instrumental attributes carry significantly more weight than symbolic ones in volunteer recruitment decisions. Finally, employing uplift modeling, the study identifies several demotivator levels that consistently exhibit negative appeal across all subgroups. These findings provide evidence‐based guidance for NPOs to enhance citizen engagement.