Modeling the Competencies of Knowledge-Based Companies Using Structural Equation Modeling (Case Study: Incubators and Science and Technology Parks)
Keywords:
structural equations, modeling, knowledge-based companiesAbstract
The purpose of the present research was to model the competencies of knowledge-based companies using structural equation modeling. This study is applied in nature and, in terms of methodology, is a mixed-methods research (qualitative–quantitative). The statistical population of the research consisted of 7 to 12 experts whose opinions were used in the qualitative section to identify categories. For the modeling stage, the statistical population comprised managers and experts familiar with the field of competencies of knowledge-based companies located in incubators and science and technology parks. Cochran’s formula for unknown populations was used, and the sample size was determined to be 384 individuals. The sampling method was available random sampling. To identify the factors, categories and concepts were first extracted through interviews. The result of this stage yielded 31 axial codes and 358 open codes. Next, in the following stage, the Delphi technique was applied, through which causal, contextual, intervening, strategic, and consequential conditions were screened across three rounds. Ultimately, consensus was reached on 102 open codes and 31 selected codes. Finally, structural equation modeling and partial least squares were employed using Smart PLS software for the modeling stage. The findings of the research indicated that the competency model of knowledge-based companies is formed under 7 causal conditions, 4 contextual conditions, 6 intervening factors, and 6 strategies. Ultimately, 7 major consequences for knowledge-based companies located in incubators and science and technology parks were identified. These consequences, in order of priority, include organizational growth, improvement of organizational strategic thinking, resilience of human resource processes, improvement of organizational conditions, organizational outcomes, enhancement of organizational efficiency, and an increase in the level of organizational competitiveness. Based on the results of this research, it can be concluded that in the process of competency modeling for knowledge-based companies located in incubators and science and technology parks, attention should be given to a wide range of factors, criteria, and sub-criteria in order to achieve appropriate results and maximize productivity.
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