An Integrated Model to Develop Semi-Quantitative Scenarios Using a hybrid Method Based on Fuzzy Cognitive Map: A Case Study of Iranian Oil Production

Document Type : Industry Article

Authors

1 Department of Industrial Engineering, Arak Branch, Islamic Azad University, Arak, Iran

2 Technology Foresight group, Department of Management, Science and Technology, Amirkabir University of Technology (Tehran Polytechnic), Tehran, Iran.

3 Mechanical Engineering Department, Noshirvani University of Technology, Babol, Iran

4 Technology Foresight Group, Department of Management, Science and Technology, Amirkabir University of Technology (Tehran Polytechnic), Tehran, Iran

5 sama Technical vocational school Islamic Azad University, Arak Branch, Arak, Iran

Abstract

In today's competitive dynamic world/markets, providing a desirable framework for exploring future perspectives is a crucial challenge to support robust decision making and proper policy making. This research proposes a novel framework that develops plausible future energy scenarios through the Fuzzy Cognitive Map (FCM) technique. As a new method in scenario planning, FCM model attempts to present a set of rational, reliable and credible plausible scenarios together with analyzing dynamic behaviors of parameters. The integrated FCM-based approach encompasses STEEP analysis to identify parameters, Cross Impact Analysis (CIA) to determine key drivers, Morphological analysis for scenario selection, and FCM model to develop semi-quantitative scenarios. This new approach for scenario development brings together the benefits of both quantitative and qualitative analysis and it is not limited to the investigation of few pre-defined scenario drivers. As a research case, the proposed methodology is examined to detect plausible trends for Iran's oil production in the post sanction era. The implemented FCM simulations indicate that in three scenarios oil production increases and growth will be significant in the first two scenarios. The fourth projection is the most pessimistic scenario that can be imagined in the post-sanction era where the country faces massive investment backlogs.

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References

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Journal of Modeling in Engineering
Volume 17, Issue 56
April 2019
Pages 157-168

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History

  • Receive Date: 30 May 2017
  • Revise Date: 22 July 2018
  • Accept Date: 03 September 2018

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