Date of Award

May 2020

Document Type


Degree Name

Doctor of Philosophy (PhD)


Industrial Engineering

Committee Member

Kevin M Taaffe

Committee Member

William G Ferrell

Committee Member

Amin Khademi

Committee Member

David M Neyens


Over the last two decades, large-scale disaster events have significantly increased in frequency and intensity, causing tremendous loss of lives and property. A large number of relief organizations rely on their volunteers to respond to many disasters around the globe, serving people and communities in need. While their contributions are priceless, turnover among disaster volunteers has become a significant problem for these relief organizations. Work environment factors, such as volunteers being mismatched with tasks, unsuitable workloads, and conflict within groups of volunteers may give rise to turnover intentions, which may in turn lead to actual turnover. The link between work environment factors and volunteer turnover intentions in these situations has not yet received considerable attention in terms of quantitative research. Therefore, the purpose of this dissertation is to develop quantitative models that consider the factors that may cause turnover or turnover intentions. The goal of these models is to help decision makers for non-governmental organizations (NGOs) better manage their disaster volunteers during relief efforts, with the aim of satisfying community needs and improving volunteer retention rates.

The first study addresses a gap in volunteer staff planning and scheduling where volunteer training is first presented, with volunteer turnover represented as a percentage of volunteer–task mismatch. We have developed a mixed-integer programming model for assigning optimal volunteer assignments based on a range of possible short- and long-term community need scenarios. The objective is to minimize the costs of unmet community needs, volunteer attrition due to mismatch assignments, and volunteer expenses. Under different demand scenarios, the optimum solution of volunteer assignment is to allow unskilled volunteers to start training early so that they can help skilled volunteers when a peak of long-term skilled task demand is expected.

The second study investigates the effects of work environment factors on the satisfaction level and turnover intentions of disaster volunteers. Using an online survey, data from 386 disaster volunteers are collected and analyzed. Confirmatory factor analysis (CFA) and structural equation modeling are used to test the measurement model and answer research questions focused on volunteer behavior. After assessing and confirming the measurement model, we use the structural model to test the hypotheses and provide prediction equations. Job-fit, training, workload, volunteer group, and supervisor are the key work environment factors considered in this study. The findings suggest that these work environment factors have a positive significant relationship with satisfaction and a negative significant relationship with turnover intentions.

The last study focuses on developing a simulation modeling approach that considers a volunteer’s satisfaction and turnover intentions in relation to management decisions of an NGO during a relief event. We use a survey to gather information from disaster volunteer managers about how they manage their volunteer teams and use this information and the findings from the second study to model a realistic relief event. We develop a hybrid simulation model, agent based and discrete event (AB-DE), that handles volunteer task and location assignments, as well as workload. Using data analysis from the surveys, we also introduce a group conflict variable within the simulation model. We evaluate the impact of different management decisions on unmet community needs, as well as on volunteer satisfaction and turnover intentions from the organization. This study uses a numerical example based on the survey data. Considering the scenario in which disaster volunteer managers do not assign heavy workload to disaster volunteers, the results of this study suggest that as a surplus of available volunteers’ increases, the overall satisfaction increases while the turnover intention decreases due to dissatisfaction with a non-essential workload as well as from group conflict. In contrast, when the number of volunteers is less than what is needed, disaster volunteers’ satisfaction and turnover intentions were not affected even if there is high group conflict due to the positive effect of the workload that offsets the negative impact of the group conflict.



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