EAGER: Co-Evolution of Social Service Delivery Networks and Population Dynamics

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This EArly Grant for Exploratory Research (EAGER) award provides funding to study the links between population dynamics, evolving social needs and additional structural elements of a large network of social service providers. The study will examine a number of factors including the evolution of the organizational forms in the number of field units, the resources used and quality and quantity of services provided. Moreover, a systematic understanding of social service delivery systems will be developed from a service science theoretical perspective. That is, acknowledging that services are co-produced by providers and recipients, and are intangible, perishable, heterogeneous, and difficult to standardize among many other unique characteristics that differentiate them from manufacturing processes. This project will make use of a complex systems modeling approach that facilitates incorporating organizational policy in the analysis. If successful, the results of this research will help establish a theory of how social services networks co-evolve and change responding to changes in the population they serve. Moreover, it will improve the understanding of phenomena uniquely associated with social service systems such as the nonlinear effects of population changes on community needs, organizational policy, and on system performance. It will also help uncover culturally influenced variations of trajectories of the network triggered by causal chains such as value perceptions, intentions, actions, and outcomes exhibited by clients. Thus, this project will demonstrate how the ecology of service organizations can be modeled with paradigms of tempo-spatial relations. The products of this work will be: i) a dynamic model of a network of distributed human services able to track the co-evolution of the operating environment over space; and, ii) theoretical propositions of how population dynamics affect network form and individual unit performance over time. Eventually, it is expected that this exploratory model will enable the proposition of methods for the evaluation of network dynamic performance and the development of decision support systems for social services.