Validation of Petrochemical Company Observatory Model in Large–Level (Case Study: Persian Gulf Petrochemical Industries Co.)

Managers have always sought to predict the future of the company so that they may take an effective step in building or changing the future. This has led scholars in various fields to look for solutions to overcome the growing uncertainty phenomenon, with a particular focus on foresight and future studies. The purpose of the research is to increase the ability of companies to predict the future of the petrochemical industry and validation of different dimensions of the macro-level observatory model.

 This research is of mixed method, Interviewed in a qualitative section of managers with more than ten years in petrochemical industry and continued until the theoretical saturation, that included 20 interviews. The statements extracted from the interviews were extracted using the Charmaz approach and analyzed by MAXQDA software. The statistical population comprises 462 managers of the Persian Gulf Petrochemical Industries Company. The number of samples was determined by the Cochran formula at the error rate of 1%, 80 individuals. In the quantitative part, a researcher-made questionnaire was distributed among 90 managers of different companies in different levels, finally, 82 questionnaires were analyzed for analysis. Factor analysis was performed using SPSS and WarpPLS software for quantitative data analysis.

The Petrochemical Industry Observatory model was presented in the form of 7 main concepts, 21 axial concepts and 127 propositions. The validity of the developed model was measured in this respect the dimensions of the observatory model were confirmed. Model dimensions and significance coefficient for each of the dimensions of the macro level of the petrochemical industry include: Political (0.791), economic (0.952), environmental (0.596), social (0.402), technological (0.720), legal (0.842), and international (0.682). The identified dimensions of the macro level of the petrochemical industry as observatory data will lead to more knowledge and wisdom in order to make better decision makers.