Computational Framework for Assessing Absorptive Capacity
Abstract
Research Problem: The movement of displaced populations into and through a host region~s territory can place additional demands on critical infrastructure, engendering new, or exacerbating existing, racial, ethnic, or religious animosities as competition for resources intensifies and the network of systems that support food, sheltering, security, healthcare, and sanitation are strained. Host regions face the challenge of providing for the basic needs of the newly arrived populations dislocated either by short-term shocks, such as natural disasters and conflict in neighboring regions, or longer-term economic and environmental trends. Both theoretical development and applied modeling are required to better understand the capacity of a region~s systems to absorb these increasing demands as well as to assess the impact that persistent supply-demand pressures may have on the governance and broader social issues of the host region. The nascent concept of absorptive capacity provide some insight into understanding the dynamics of systems~ stress stemming from population movements, but this concept is necessarily broad and requires more specificity relative supply-demand relationships. There is a need to mature this concept so it can meaningfully guide the informed the dynamic interplay among the displaced-population drivers and regional instability. Objectives: To advance, model, and test the concept of absorptive capacity of displaced populations by developing a computational framework that allows studying and testing of the relationships among supply-demand pressures considering longer-term regional stability. Methods Development of the absorptive capacity computational framework entails a five-component approach: 1) identification of factors/systems components of absorptive capacity; 2) measurement of elasticity and capacity of these critical systems; 3) simulation implementation based on the characterization of absorptive capacity; 4) articulation of population and governance dynamics stemming from natural events and actual and threatened conflicts through the simulation; and 5) the implementation of mechanisms for the framework to be used with new data and extended when required. The conceptualization and measurement of these five components gird the absorptive capacity computational framework. Data: The work will require data capture and modeling at several levels of aggregation and multiple sources. For example, the drivers of population movements stemming from inter-regional and neighboring conflicts draw upon publicly accessible data, host and guest population perceptions and fatigue draw upon fieldwork, and social and political rhetoric draw upon government documents and news outlets. Comparative Studies: Three case studies are used to characterize and provide data for the framework development process: 1) Cape Town, South Africa; 2) Mytilene, Greece and 3) Cucuta, Colombia. These cases are purposively selected due to the dissimilarities in geographies, populations, land area and risk posed by natural- and human-induced disruptions driving population migration. These cases are useful for the development of the computational framework, modeling, and sensitivity testing specifically due to their dissimilarities. Outcomes: If successful, this project shall yield two significant outcomes: this project will advance a theory of absorptive capacity and it will advance the methodological use of simulation for theory generation and knowledge creation. A theory of absorptive capacity will allows us to understand the relationships among supply-demand pressures considering long-term regional stability. A methodology will allow researchers to not only extend the theory through the simulation but also develop new simulations of interest. Broader Implications: This project will provide insights into complex dynamics of population movements and regional instabilities. Such knowledge and insights may allow for the strategic timing of interv
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Nov 26, 2019
- Source ID
- N000141912624
Entities
People
- Jose Padilla
Organizations
- Office of Naval Research
- Old Dominion University
- United States Navy