Published In

Portland International Conference on Management of Engineering and Technology: Technology Management For Social Innovation, Proceedings

Document Type

Article

Publication Date

9-1-2016

Subjects

Computer science, Fuzzy sets

Abstract

Fuzzy Cognitive Mapping (FCM) is a semi-quantitative system modeling technique that is used in technology management to capture, synthesize and analyze expert and stakeholder knowledge for the purpose of technology assessment, product planning, and scenario studies. The resulting FCM models are generated in interviews, focus groups, or workshops and represent complex and dynamic systems as elements (so-called concepts) and cause-and-effect relationships. Researchers often compare FCM to investigate cognitive differences between individuals or groups, identify unique perspectives on a specific topic, or track changes in knowledge (i.e. learning). Using a variety of metrics, comparison studies investigate diverse characteristics of FCMs, such as structure, cognitive complexity, and similarity. To date, no consensus on metrics and their interpretation has emerged. To strengthen the scientific value of FCM as a research tool, this study systematically reviews existing metrics for content, structure, and dynamic behavior and applies them to the comparison of two FCM models. It illustrates how these three types of metrics are used for comparison and reveals limitations. In particular, content metrics are needed that are generalizable for all possible weights of causal relationships. Also structural metrics that are suitable for directed and weighted FCMs still need to be developed. © 2016 Portland International Conference on Management of Engineering and Technology, Inc.

Description

This is the publisher's final PDF. Copyright 2016 by PICMET. Paper delivered at the 2016 Proceedings of PICMET '16: Technology Management for Social Innovation.

DOI

10.1109/PICMET.2016.7806755

Persistent Identifier

http://archives.pdx.edu/ds/psu/19741

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