This paper develops and demonstrates a combined set of models to capture regional development decision processes. The results of the models are then integrated along with other socio-political factors within a policy relevant decision methodology framework. The Haynes and Dinc (1997) extension of the shift-share model identifies regional industrial sectors for analysis based on their scale, productivity and sources of productivity change. By employing Data Envelopment Analysis (DEA), the efficiency of these lead sectors is investigated and the future competitiveness of these sectors is evaluated. By incorporating input-output analysis the impact of inter-sectoral transactions on sectoral efficiency is assessed. Since in most cases state economic development planning and implementation processes also involve political judgements, based on the findings of the above models, the study suggests a decision support framework which combines the above mentioned quantitative tools with other qualitative decision factors. An Analytical Hierarchy Process (AHP) is employed as a multi-objective decision making device to integrate the relevant policy components.