Designing Evidence-Based Policy in Global Dynamic Environments
(Tools of Analysis: Methods, Data, Informatics and Research Design)
Thursday, November 12, 2015: 3:30 PM-5:00 PM
Foster I (Hyatt Regency Miami)
*Names in bold indicate Presenter
Panel Organizers: Louise Comfort, University of Pittsburgh
Panel Chairs: Andy Pugh, University of Pittsburgh
Discussants: Naim Kapucu, University of Central Florida
Designing evidence-based policy to support decision making in dynamic environments presents a special set of challenges. Not only are the actors changing in interaction with one another, but also the context of operations, available resources, and relevant knowledge required for effective action are also changing, often under urgent conditions. Adapting to changing conditions is a task is common to policy makers across the globe, but the degree of change and the capacity for adaptation varies by the initial cultural, political, economic, and technological conditions that characterize local operational environments. When the number of actors in an urgent situation increases, the heterogeneity of participants in knowledge and skills increases, or the divergence in available resources increases, the potential for building collective action toward a common goal decreases. Identifying the threshold points of change in complex, dynamic situations requires systematic monitoring, analysis, reporting, and exchange among participating members. This is essentially an iterative process of data collection and analysis by mixed methods, with the added requirement of integration of often disparate sources of information to produce a common profile of a changing situation.
In such environments, emerging networks of organizations interacting, collaborating, competing, and disintegrating can be identified, and serve as dynamic profiles of organizations in action. Consequently, these policy environments require models and metrics that can be used to estimate uncertainty, and anticipate consequences that may or may not occur. Standard methods of linear measurement do not fit the actual conditions of practice, but innovative models that estimate interdependent conditions may provide insight into the processes of change as the actors adapt or resist in practice.
This panel presents four papers that explore different forms of data collection, methods of analysis, and means of information search and exchange to produce evidence-based policy recommendations in dynamic environments. The contributing authors employ a range of methods to produce systematic evidence to inform decision makers coping with change. These methods include: network analysis and its multiple forms, qualitative and quantitative analyses, Bayesian modeling, Poisson regression, and sociotechnical experiments
All four papers examine processes to identify critical requirements for action in changing conditions, and illustrate different models for designing effective strategies in dynamic environments. The first paper examines “Evidence-Based Evaluation and Adaptation of Emergent Collective Action Systems in Immigration and Multiculturalism Policy and Practice, South Korea.” The second paper explores “Organizational Learning in Adapting Dynamic Nature of Disaster Environments in Southern Turkey.” The third paper addresses the process of “Implementing evidence-based policy to respond to large-scale international crises: Lessons from the Ebola outbreak in West Africa.” The fourth paper presents a sociotechnical perspective on “Mobilizing Collective Action in Communities Exposed to Tsunami Risk: Using Adaptive Information Technologies to Support Evacuation Policy in Padang, Indonesia.”
Together, the set of four papers demonstrates different approaches for monitoring and measuring organizational interaction, adaptation, and change in dynamic environments that produce evidence-based research to inform decision making for communities at risk.