A New Hybrid Fuzzy Cognitive Map-based Scenario Planning Approach for Iran's Oil Production Pathways in the Post-sanction Period

Published In

Energy

Document Type

Citation

Publication Date

9-1-2017

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 process. 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 attempts to present a set of rational, reliable and credible scenarios together with analyzing dynamic behaviors of parameters. The integrated approach encompasses STEEP analysis to identify parameters, Cross Impact Analysis (CIA) to determine key drivers, Morphological analysis for scenario selection, and FCM to develop semi- quantitative scenarios. The new proposed scenario development approach brings the benefits of both quantitative and qualitative analysis together, which is not limited to the investigation of few pre-defined scenario drivers. As a research case, the proposed methodology was examined to detect plausible trends for Iran's oil production in the post-sanction era. The implemented FCM simulations indicated that in three scenarios oil production rises, as growth would be significant for the first two. The fourth projection is the most pessimistic future that can be imagined in the post-sanction era where the country faces massive investment backlogs.

Description

© 2017 Elsevier Ltd. All rights reserved.

DOI

10.1016/j.energy.2017.06.069

Persistent Identifier

https://archives.pdx.edu/ds/psu/25976

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