Decision-making technique to achieve stratified target performance: Analyze science and technology innovation policy investment of South Korea

Abstract

From the entire multi-criteria decision-making methodology literature review, we begin to understand all the decision-making techniques, which help decision-makers choose the best alternative within specific criteria based on past or current performance levels. But when we use these technologies in investment plans, renewable energy policy plans, strategic plans, and so forth, we should consider future performance values in the decision-making process. As far as the author knows, no decision-making method can rank alternatives with future performance target values. This study article introduced a novel decision-making technique, namely DEcision Making Technique to Achieve Stratified TArget Performance (DEMTASTAP), for ranking the alternatives with the future performance values. In recent years, the concept of stratification has become the central concept in the decision-making process. Here, the target level of each alternative under each factor regard as the stratification level. We validate the introduced DEMTASTAP method by testing the completeness of the ranking, the correlation of the order, the inversion of the scale, and the sensitivity. Demonstrate the efficiency of the DEMTASTAP method by solving the Science and Technology Innovation Policy (STIP) investment issues. Using the introduced method, we have obtained an effective investment rate to achieve the expected growth rate of all alternative (or) regions. Hence, we can quickly establish future STIP investment plans in the direction of amelioration.