Quantifying the Impact of Perceived Inclusion on Organizational Citizenship Behavior Using Statistical and Machine Learning Approaches in the IT Industry
Abstract
Workplace productivity along with collaboration levels increase through Organizational Citizenship Behavior (OCB) as a major organizational factor. Organizations need to comprehend what motivates IT professionals to practice OCB because this understanding must exist to create an all-inclusive supportive work environment. Traditional statistical models cannot detect the complex interactions existing between the important predictors of OCB that include perceived inclusion and psychological safety and cultural orientation although previous studies identified these elements as essential predictors. This research presents an HSML Model which joins SEM for hypothesis testing and ML for feature selection and DNN for predictive analysis to overcome previous analytical limitations. The research gathered information from 500 IT practitioners who worked in international subsidiaries and local branches through an organized selection process. The research utilized SEM for establishing causal relationships between variables while evaluating feature importance through Random Forest and SHAP when analyzing perceived inclusion and psychological safety and cultural orientation and OCB. Predictive accuracy improved when the selected features were used to train a DNN. The HSML model delivers superior performance compared to conventional approaches because it reaches an R² value of 0.85 alongside a classification accuracy level of 93.1% while outdoing multiple linear regression, random forest as well as standalone deep learning models. Analysis of feature importance reveals perceived inclusion (0.42) together with psychological safety (0.34) to be the most influential predictors of OCB. The research establishes that included workplaces with safe psychological environments drive greater employee engagement outcomes. The HSML model functions as a real-time operational tool that provides useful knowledge for HR managers to enhance workplace inclusivity and employee health.
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