Sustainable Volunteer Engagement: Ensuring Potential Retention and Skill Diversity for Balanced Workforce Composition in Crowdsourcing Paradigm

Abstract

Crowdsourcing (CS) faces the challenge of managing complex, skill-demanding tasks, which requires effective task assignment and retention strategies to sustain a balanced workforce. This challenge has become more significant in Volunteer Crowdsourcing Services (VCS). This study introduces Workforce Composition Balance (WCB), a novel framework designed to maintain workforce diversity in VCS by dynamically adjusting retention decisions. The WCB framework integrates the Volunteer Retention and Value Enhancement (VRAVE) algorithm with advanced skill-based task assignment methods. It ensures efficient remuneration policy for both assigned and unassigned potential volunteers by incorporating their potential levels, participation dividends, and satisfaction scores. Comparative analysis with three state-of-the-art baselines on real dataset shows that our WCB framework achieves 1.4 times better volunteer satisfaction and a 20% higher task retention rate, with only a 12% increase in remuneration. The effectiveness of the proposed WCB approach is to enhance the volunteer engagement and their long-term retention, thus making it suitable for functioning of social good applications where a potential and skilled volunteer workforce is crucial for sustainable community services.