Defense Date

4-9-2018

Graduation Date

Spring 5-11-2018

Availability

Immediate Access

Submission Type

thesis

Degree Name

MS

Department

Computational Mathematics

School

McAnulty College and Graduate School of Liberal Arts

Committee Chair

Rachael Miller Neilan

Committee Member

James B. Schreiber

Keywords

agent-based model, incentive-based motivation, team-based organization, worker productivity, simulation, motive profile

Abstract

Large organizations often divide workers into small teams for the completion of essential tasks. In an effort to maximize the number of tasks completed over time, it is common practice for organizations to hire workers with the highest level of education and experience. However, despite capable workers being hired, the ability of teams to complete tasks may suffer if the workers' individual motivational needs are not satisfied.

To explore the impact of incentive-based motivation on the success of team-based organizations, we developed an agent-based model that stochastically simulates the proficiency of 100 workers with varying abilities and motive profiles to complete time-sensitive tasks in small teams. The model is initialized by randomly assigning each of the 100 workers an ability value (1 through 5) and a motive profile from initial probability distributions. A motive profile is a 3-parameter equation that quantifies a worker's tendency to actualize his or her potential based on the individual's motivational needs for affiliation, achievement, and power. The model creates new tasks as workers become available; each new task is assigned a random difficulty value and a team of 2 to 4 workers. During each time step, each worker contributes to their assigned task at a rate determined by the worker's ability and motive profile. At the end of 365 time steps (1 year), the model outputs the total number of completed tasks, which is the primary measurement of productivity. By simulating the model hundreds of times for different sets of initial distributions and analyzing output, we are able to determine which worker attributes lead to increased team-based productivity. Results aid in understanding optimal hiring and human resource allocation in a team-based organization.

Language

English

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