Strategic Management Thought

Designing an Intelligent Model for Industrial Project Feasibility Using Green Industry Approach

Document Type : Research Paper

Authors

1 Assistant Professor, Faculty of Islamic Studies and Management, ISU

2 Professor of Management, Tarbiat Modares University (corresponding author)

3 Professor at Technical College, Tarbiat Modares University

4 Associate Professor, Faculty of Islamic Studies and Management, ISU

Abstract

Full implementation of projects and ideas, innovativeness in launching businesses, and running industrial projects, all depend on correct and comprehensive feasibility assessment beforehand. The classic approach to this focuses on the industrial projects' financial aspect and profitability and also their justifications in terms of technical and market conditions. In the recent decade, with the rise of green ideas and the necessity for projects to offer an environmental supplement, the projects' justifications have been subjected to revisions. Green management and applying green approach in the development of industrial projects are new paradigms in management that can guarantee environmental criteria in the development of industrial projects. The goal of this article is developing a fuzzy expert system for total feasibility study of industrial projects. This system involves five aspects, namely, financial, technological, economical, market and environmental criteria. After defining the criteria for projects' feasibility assessment and the rules using fuzzy expert system methodology based on expert opinions for determining the validity of the developed model, the project of constructing the sewage treatment plant in the south of Tehran was selected and the obtained data were input in it. The subsequent analysis of the system's output confirmed expert opinion about the issue.

Keywords

Main Subjects

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Strategic Management Thought
Volume 11, Issue 1 - Serial Number 1
June 2017
Pages 201-242
  • Receive Date: 02 March 2015
  • Revise Date: 30 July 2016
  • Accept Date: 19 January 2017