Developing A Short-Term Comparative Optimization Forecasting Model For Operational Units' Strategic Planning

Data drain for peer active units operating in the same sector is a major factor that prevents policy makers from developing flawless strategic plans for their organisation. This paper introduces a hybrid model that incorporates a purely deterministic method, Data Envelopment Analysis (DEA), and a semi-parametric technique, Artificial Neural Networks (ANNs), to provide a strategic planning tool for efficiency optimization applicable to short-term lag of data availability. For consecutive time instances, t and t +1, the developed DEANN model returns optimum "Regression-type" input and output levels for every sample operational unit, even for the fully efficient ones, that may decide to alter the levels of the efficiency determinants, respecting the t -time efficiency frontier.

Provided by: Munich Personal Repec Archive Topic: Project Management Date Added: May 2011 Format: PDF

Find By Topic