Analysis of Food Hub Commerce and Participation Using Agent-Based Modeling: Integrating Financial and Social Drivers
Authored by Caroline C Krejci, Richard T Stone, Michael C Dorneich, Stephen B Gilbert
Date Published: 2016
DOI: 10.1177/0018720815621173
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Abstract
Objective: Factors influencing long-term viability of an intermediated
regional food supply network (food hub) were modeled using agent-based
modeling techniques informed by interview data gathered from food hub
participants.
Background: Previous analyses of food hub dynamics focused primarily on
financial drivers rather than social factors and have not used
mathematical models.
Method: Based on qualitative and quantitative data gathered from 22
customers and 11 vendors at a midwestern food hub, an agent-based model
(ABM) was created with distinct consumer personas characterizing the
range of consumer priorities. A comparison study determined if the ABM
behaved differently than a model based on traditional economic
assumptions. Further simulation studies assessed the effect of changes
in parameters, such as producer reliability and the consumer profiles, on long-term food hub sustainability.
Results: The persona-based ABM model produced different and more
resilient results than the more traditional way of modeling consumers.
Reduced producer reliability significantly reduced trade; in some
instances, a modest reduction in reliability threatened the
sustainability of the system. Finally, a modest increase in price-driven
consumers at the outset of the simulation quickly resulted in those
consumers becoming a majority of the overall customer base.
Conclusion: Results suggest that social factors, such as desire to
support the community, can be more important than financial factors.
Application: An ABM of food hub dynamics, based on human factors data
gathered from the field, can be a useful tool for policy decisions.
Similar approaches can be used for modeling customer dynamics with other
sustainable organizations.
Tags
Management
Complex adaptive systems
Supply Networks
Chain