Melecio-Viñales, Joymariel

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    Dynamic performance evaluation of a spatially-distributed network
    (2011) Melecio-Viñales, Joymariel; Medina-Borja, Alexandra; College of Engineering; Medín, Joaquín; Cesaní, Viviana; Department of Industrial Engineering; Lorenzo, Edgardo
    The operational environment of non-profit organizations is affected significantly by changes in population demographics such as births, migration, community wealth, etc. Our interest is in demonstrating how the performance of a networked service organization is affected by these external elements, by modeling the direct impact these factors have on the organization’s revenue generation capacity. One might think that the overall performance goal is that all service points are efficient at the same time, so the whole network can be efficient as well. But, is that even possible? A dynamic model that describes this organization operating under a network structure has been developed and an optimization algorithm has been incorporated into this model with a pre-calculated desired state of the system to be achieved. The desired state was defined by an efficient frontier calculated from the production possibility set using Data Envelopment Analysis. By executing the model we explored whether the network can reach that state when all the external factors are changing over time. The results suggest that this desired state is achievable but the length of time required by the system to accomplish this state is questionable. Also, we demonstrated that once the desired state is reached by a unit this unit not necessarily would maintain this state until the whole system finds equilibrium. This research contributes to three bodies of knowledge: to the performance measurement field through the identification of the efficient hyperplanes of a production possibility set and by analyzing the system’s behavior over time using the targets recommended by DEA; to service science through the development of the dynamic service delivery axioms; and to complex systems analysis by modeling a large service network organization using the system dynamics simulation paradigm with a spatial component seeking to optimize the network.