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.

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.

The use of theory of planned behavior to systemically study the integrative-qualitative intentional behavior in Romanian preschool education with network analysis.

Predicting preschool teachers' intention to adopt qualitative and inclusive early childhood intentional behaviors represents an important research field. The objective of this research is first to develop and validate a scale to assess the integrative-qualitative intentional behavior (IQIB-ECEC) of preschool teachers in order to achieve SDG4.2's objective of ensuring that all children have access to high-quality pre-primary education and then to systemically analyze the relationship between variables with Network Analysis. The theory of planned behavior (TPB) describes key individual beliefs (attitudes, subjective norms, and perceived behavior control) that affect people's intentions to engage in a certain conduct and has previously been used with success in evaluating people's intentions to adopt a certain behavior. This research represents one of the first Romanian attempts to use the theory of planned behavior to study the Integrative-Qualitative Intentional Behavior in Romanian Preschool Education and systemically analyze results with Network Analysis approach. This study used a randomized 300 Romanian preschool teachers enrolled in a National Training Program entitled Qualitative and Inclusive Early Childhood Education managed by the Romanian Educational Ministry. Data were collected via an online questionnaire. The scale validation followed a confirmatory factor analysis (CFA). The fitting of the IQIB-ECEC 19-item scale showed that all coefficients CFI (0.942), TLI (0.920), SRMR (0.0452), and RMSEA (0.0451) bring strong evidence in the favor of the statistical validity of the scale. The final IQIB-ECEC 19 items and 8 factors scale obtained a Cronbach's alpha of 0.77. The systemic Network Analysis approach was used in interpreting data. The centrality of the network model was further investigated and the clustering coefficients index were calculated. According to the results, perceived power/control beliefs and behavioral intention were detected as the most important dimensions, whereas behavioral beliefs were less important. These findings were discussed in terms of their theoretical and practical significance.