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Algorithm development based on an integrated approach for identifying cause and effect relationships between different factors

  • Neeraj Bhanot and Parth Padalkar
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Abstract

Cause-effect analysis is crucial for studying any complex system with various factors affecting the output. The software aims to provide a more straightforward approach for cause-effect analysis on many factors in any chosen system. This has been made possible by integrating the algorithm of special decision-making techniques, that is, “decision making trial and evaluation laboratory,” “maximum mean de-entropy,” and “interpretive structural modeling” into one program. The software takes the number of factors and their relation as input and gives the final reachability matrix and a level-wise directed graph of all factors portraying the most dependent factor at the top and most driving factor at the bottom. This software application is immense and can be found in industries ranging from production to IT domain. This software will be particularly very useful for management scholars in their research.

Abstract

Cause-effect analysis is crucial for studying any complex system with various factors affecting the output. The software aims to provide a more straightforward approach for cause-effect analysis on many factors in any chosen system. This has been made possible by integrating the algorithm of special decision-making techniques, that is, “decision making trial and evaluation laboratory,” “maximum mean de-entropy,” and “interpretive structural modeling” into one program. The software takes the number of factors and their relation as input and gives the final reachability matrix and a level-wise directed graph of all factors portraying the most dependent factor at the top and most driving factor at the bottom. This software application is immense and can be found in industries ranging from production to IT domain. This software will be particularly very useful for management scholars in their research.

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