Policy and Complex Systems
and Wildavsky ( 1984 ), financial capital flows that ensue from federal legislative actions to states and local governments typically entail development and execution of discrete projects . Since projects are the fundamental unit of analysis in the ABM presented in this study , similar contextspecific ABMs could also be developed in other policy domains , e . g ., energy , health , watershed , education , environment , and international development .
7 . Conclusions
In this study , we introduced patternoriented agent-based modeling as a complex adaptive system-based policy informatics tool to compare alternate institutional designs of intergovernmental decision-making processes and assess transportation system resiliency under different shocks to the policy system . An ABM of transportation governance network in the state of Vermont has been presented to demonstrate an application of intergovernmental policy implementation network analysis in real-world public policy settings . This ABM enables simulation of the dynamics of transportation project prioritization processes under alternate intergovernmental institutional rule structures and variable frequencies of shocks to the policy system . Furthermore , this ABM enables decision makers to visualize the impacts of alternate intergovernmental institutional rules on the emergent patterns of financial investment flows from federal to state , regional , and local scale governments . The ABM presented in this study could be extended to test systemwide effects of alternate institutional designs on the differential emergence of project prioritization patterns by adding and / or re-weighting transport project prioritization criteria . Furthermore , if the goal were to extend the ABM to other states or countries , the probability distributions for these parameters would need to be empirically estimated for calibrating ABM to that particular geographical scope . Such computational models could also be developed to simulate public policy implementation processes in other policy domains for informing the governance of policy implementation networks . The ABM model parameters could be redefined and re-calculated to adapt the model design to any intergovernmental policy implementation network in the United States that , for example , governs energy or food policy implementation systems . The computational modeling of intergovernmental policy implementation networks can improve our understanding about the apparently chaotic emergent patterns that arise due to overlapping and sometimes competing interests among different levels of the government , vertically ; and among governments , markets , and societies , horizontally . Experimental simulations generated through such computational models could be harnessed as policy informatics tools in a wide variety of policy domains across multiple scales of governance and can be potentially used to inform the design of resilient infrastructures in the face of climate change induced extreme events and funding uncertainties under different political cycles .
Acknowledgments
We acknowledge funding support from NSF grant # EPS-1556770 . Findings reported in this paper are solely the responsibility of the authors and not the funding agencies .
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