EconPapers    
Economics at your fingertips  
 

Assessing candidate industrial technologies utilising hierarchical fuzzy decision making systems

Ivan Vrana and Shady Aly

International Journal of Industrial and Systems Engineering, 2010, vol. 6, issue 2, 187-206

Abstract: The adoption of new industrial technology is a type of critical decisions. Important characteristics of such significant decision problem are ill-structuredness, subjectivity and vagueness of input and output factors and their relationships. Most of past researches have considered only the quantitative view, and little or even no researches have treated inherent ambiguity in determining exact values of quantitative inputs and in quantifying subjective ones. In this paper, a hierarchical fuzzy decision making model is proposed for handling vagueness and subjectivity associated with the problem's inputs (i.e. technology performance factors), and for structuring the relationships between them at one side and a technology evaluation score at the other side. The inputs to the model are groups of technical, economical and transferability-related measures. The output of the model is a crisp score for comparing merits of candidate technologies. Finally, a hypothetical illustrative example is provided.

Keywords: fuzzy logic; hierarchical fuzzy systems; technology transfer; hierarchical fuzzy decision making; analytical hierarchy process; AHP; vagueness; subjectivity; technology evaluation; technology adoption. (search for similar items in EconPapers)
Date: 2010
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.inderscience.com/link.php?id=34336 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ids:ijisen:v:6:y:2010:i:2:p:187-206

Access Statistics for this article

More articles in International Journal of Industrial and Systems Engineering from Inderscience Enterprises Ltd
Bibliographic data for series maintained by Sarah Parker ().

 
Page updated 2025-03-19
Handle: RePEc:ids:ijisen:v:6:y:2010:i:2:p:187-206