Decision models for volunteer management in nonprofits: enhancing engagement, satisfaction, and retention
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Authors
Kaur, Milan Preet
Issue Date
2025-08
Type
Electronic thesis
Thesis
Thesis
Language
en_US
Keywords
Decision sciences and engineering systems
Alternative Title
Abstract
Nonprofit organizations (NPOs) rely heavily on volunteers to support community needs and provide a variety of essential services. However, they face challenges in effectively utilizing limited volunteer and employee resources while navigating uncertainties in volunteer motivations, task preferences, and participation behaviors. A central challenge is making volunteer-to-task assignment decisions that can accommodate the needs of all three stakeholders (nonprofit, community members, volunteers), in environments representing different volunteer behaviors. The difficulty in quantifying volunteer motivations and satisfaction further complicates these decisions, making it challenging to align organizational and community benefits with volunteer retention. To address these complexities, this dissertation develops multiple optimization approaches that enhance volunteer management strategies while assessing their impact through computational studies capturing diverse volunteer populations with varying preferences and arrival patterns. The first study presents a deterministic multi-period integer linear program for optimizing task assignments for volunteers and NPO employees, balancing factors such as task urgency, volunteer training, and task or location preferences. Using a food bank case study, the model incorporates uncertainties in volunteer task preferences and retention. It highlights the trade-offs between operational performance and the impact of current assignments on future volunteer retention. Simulation experiments examine factors like volunteer availability, preferences, and retention uncertainties. Results demonstrate that the proposed model significantly improves key performance indicators compared to a benchmark policy that ignores retention considerations. The proposed approach is found to be beneficial to NPOs, even when an NPO has uncertainty in their estimates for volunteer preferences and volunteer retention threshold values.
The second study explores how integrating characteristics of both volunteers and NPO tasks can enhance strategic volunteer-to-task assignments and improve volunteer satisfaction. Drawing on insights from qualitative literature, the study incorporates key motivators—such as opportunities for skill development, contributing to a meaningful cause, collaboration, and networking—into a static integer programming framework.
A key challenge in NPOs is balancing volunteer autonomy with effective task assignments, as existing methodologies rarely incorporate volunteer-driven task selection. To address this, the study develops a personalized task recommendation system (Menu Creation Integer Program), which generates personalized task menus (i.e., a subset of tasks) for each volunteer based on demographic information and preferences collected during onboarding. A multi-scenario approach simulates volunteer selections across multiple iterations, and a consensus algorithm refines the final menus to be presented to volunteers to encourage task selection. At this stage, volunteer’s task selections (willingness) are collected. The study then implements the Group Creation Integer Program, which forms homogeneous volunteer groups by considering skill alignment and interpersonal affinity.
Existing research often overlooks structured group formation for complex NPO tasks, focusing instead on one-time assignments. By developing a systematic approach to strategic group creation, this study bridges a critical gap in volunteer management. Given the combinatorial complexity of group formation and the inherent uncertainty in volunteer availability, the framework prioritizes both organizational efficiency and volunteer experience. Empirical data from a partner NPO informs the design of experiments, demonstrating that personalized task recommendations and strategic group formation significantly enhance both volunteer satisfaction and NPO effectiveness, even when volunteers are highly selective. A case study on a remote NPO with online volunteers further illustrates the benefits and trade-offs of incorporating structured volunteer groups into assignment strategies. The findings highlight the trade-offs between organizational goals and volunteer preferences, offering a scalable approach to optimizing volunteer management in NPOs.
The third study extends the static methodology from Study 2 by developing a dynamic rolling horizon model to assess the long-term impact of group-task assignments on volunteer retention. This model incorporates past volunteer assignments and group compositions to inform strategic assignments over multiple periods while capturing retention. A scenario-based dynamic approach is used to account for uncertainty in volunteer-to-task assignments, with multiple scenarios and associated probabilities capturing variations in menu offerings and task allocations. Chance constraints are incorporated to ensure optimal assignments remain feasible under uncertainty. The focus of this methodology is to enhance both immediate satisfaction and long-term engagement, ultimately boosting nonprofit sustainability and operational efficiency.
This dissertation advances the field of nonprofit operations management by providing actionable methodologies to enhance task completion, resource utilization, and long-term volunteer engagement through volunteer group creation, helping NPOs sustain their vital role in addressing community needs.
Description
August2025
School of Engineering
School of Engineering
Full Citation
Publisher
Rensselaer Polytechnic Institute, Troy, NY