A Cognitive Systems Engineering Approach Using Unsupervised Fuzzy C-Means Technique, Exploratory Factor Analysis and Network Analysis—A Preliminary Statistical Investigation of the Bean Counter Profiling Scale Robustness

Dana Rad, Lavinia Denisia Cuc (), Ramona Lile, Valentina Balas, Cornel Barna (), Mioara Florina Pantea, Graziella Corina Bâtcă-Dumitru, Silviu Gabriel Szentesi and Gavril Rad
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Dana Rad: Center of Research Development and Innovation in Psychology, Faculty of Educational Sciences Psychology and Social Sciences, Aurel Vlaicu University of Arad, 310096 Arad, Romania
Lavinia Denisia Cuc: Faculty of Economics, Aurel Vlaicu University of Arad, 310096 Arad, Romania
Ramona Lile: Faculty of Economics, Aurel Vlaicu University of Arad, 310096 Arad, Romania
Cornel Barna: Faculty of Exact Sciences, Aurel Vlaicu University of Arad, 310096 Arad, Romania
Mioara Florina Pantea: Faculty of Economics, Aurel Vlaicu University of Arad, 310096 Arad, Romania
Graziella Corina Bâtcă-Dumitru: Faculty of Accounting and Management Informatics, Department of Accounting and Audit, Bucharest University of Economic Studies, 010374 Bucharest, Romania
Silviu Gabriel Szentesi: Faculty of Economics, Aurel Vlaicu University of Arad, 310096 Arad, Romania
Gavril Rad: Center of Research Development and Innovation in Psychology, Faculty of Educational Sciences Psychology and Social Sciences, Aurel Vlaicu University of Arad, 310096 Arad, Romania

IJERPH, 2022, vol. 19, issue 19, 1-19

Abstract: A bean counter is defined as an accountant or economist who makes financial decisions for a company or government, especially someone who wants to severely limit the amount of money spent. The rise of the bean counter in both public and private companies has motivated us to develop a Bean Counter Profiling Scale in order to further depict this personality typology in real organizational contexts. Since there are no scales to measure such traits in personnel, we have followed the methodological steps for elaborating the scale’s items from the available qualitative literature and further employed a cognitive systems engineering approach based on statistical architecture, employing cluster, factor and items network analysis to statistically depict the best mathematical design of the scale. The statistical architecture will further employ a hierarchical clustering analysis using the unsupervised fuzzy c-means technique, an exploratory factor analysis and items network analysis technique. The network analysis which employs the use of networks and graph theory is used to depict relations among items and to analyze the structures that emerge from the recurrence of these relations. During this preliminary investigation, all statistical techniques employed yielded a six-element structural architecture of the 68 items of the Bean Counter Profiling Scale. This research represents one of the first scale validation studies employing the fuzzy c-means technique along with a factor analysis comparative design.

Keywords: bean counter; cognitive systems engineering; unsupervised learning; fuzzy c-means; exploratory factor analysis; network analysis; scale statistical architecture (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2022
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