Model for Increasing Exports of Petrochemical Derivatives with a Hyper-Automation Approach in Industry 4 For Iranian Petrochemical Holdings

Document Type : Original Article

Authors

1 PhD student, Faculty of Humanities, Islamic Azad University, Sanandaj Branch

2 Assistant Professor, Faculty of engineering, Islamic Azad University, Sanandaj Branch

3 Assistant Professor, Faculty of Humanities, , Islamic Azad University, Sanandaj Branch

Abstract

Hyperautomation is not a choice‌، but a competitive necessity for the petrochemical industry in the era of Industry 4.0. By combining the power of data‌، automation‌، and artificial intelligence‌، these technologies help petrochemical companies make their operations safer‌، more efficient‌، and more profitable‌، and as a result‌، be ready for future target markets that are built with data and automation. The purpose of the present study was to design a model for the model of increasing the export of petrochemical derivatives with the hyperautomation approach in Industry 4 for Iranian petrochemical holdings. The method of this research is mixed (qualitative-quantitative). The qualitative part of the research was conducted using interviews with 21 experts and analyzing the resulting data using the content analysis method (theme)‌، and 19 indicators of increasing the export of petrochemical derivatives with the hyperautomation approach in Industry 4 were identified and extracted. Then‌، in the quantitative part‌، the combined method of DEMETL-ISM was used to design the model. In the DEMATL section‌، the relationship and effectiveness of the extracted indicators were collected with the help of experts. The collected data were analyzed in the form of a self-interaction matrix using ISM Matlab software‌، and a four-level model was obtained. The data required for this section was also collected using a self-interaction matrix. Analysis of the collected data using Matlab software led to the formation of four levels‌، of which the establishment‌، promotion‌، and development of the Internet of Things level in production and distribution lines were the most effective indicators in this model.

Keywords

Main Subjects

References

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Journal of International Businesses Administration
Volume 8, Issue 4
May 2026
Pages 31-58

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History

  • Receive Date: 08 January 2026
  • Revise Date: 27 February 2026
  • Accept Date: 06 April 2026

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