Multi-Criteria Decision-Making Approach for Analyzing Competency Model of Technology Managers

Abstract

The economies of all the countries are growing with the passage of time. In order to promote the businesses in the global markets, technology managers/technical brokers play a key role such as in the optimal allocation of scientific and technological resources. The industrialization of scientific and technological achievements is also possible due to optimal utilization of resources and a balance between exports and imports. The technology managers should be competent enough to bridge the gaps between the resource requirements and the availability of the resources required to run the businesses smoothly. This paper is using multi-criteria methods for analyzing the qualities in the technical managers which can assist the managers to run the businesses in an efficient manner to compete in the global markets. The interviews and questionnaire are used to collect the primary data. The opinion of experts is also considered. Then, SPSS 22.0 statistical analysis software is used to analyze the reliability and validity of the factors considered in the questionnaire. Then by using statistical techniques, a quantifiable competency model of technology managers is constructed. The multi-criteria AHP (analytical hierarchical process) method is used to compare the competency characteristic indexes of each level in pairs and quantitatively describe their importance of the criteria. It also assigns weights to judge the importance of each competency characteristic index. Since the evaluation of technical managers’ competency will be affected by various factors as mentioned in the paper, the fuzzy comprehensive evaluation method is also used to transform the evaluation dimension to accurately evaluate the competency of the technical manager which assists to judge the effectiveness of model evaluation. The proposed method provides theoretical and practical basis for the selection, evaluation, and cultivation of technical managers. It provides accuracy in results by 94% by adopting the statistical techniques.