KMAN Publication Inc. (KMANPUB) International Journal of Innovation Management and Organizational Behavior (IJIMOB) 3041-8992 6 Serial Number 25 2026 04 01 Applying Machine Learning to Examine Psychological Ownership and Work Passion in Innovation Processes Applying Machine Learning to Examine Psychological Ownership and Work Passion in Innovation Processes 1 11 10.61838/kman.ijimob.5257 EN Journal Article 2025 09 12 <table> <tbody> <tr> <td> <p><strong>Objective:</strong> This study aims to apply supervised machine learning algorithms to evaluate the non-linear predictive power of psychological ownership and work passion on employee engagement in organizational innovation processes.</p> <p><strong>Methods and Materials:</strong> A quantitative, cross-sectional design was employed, utilizing a self-administered questionnaire to collect data from a sample of Moroccan professionals. To capture complex, non-linear interactions without the constraints of traditional linear models, the data was analyzed using advanced supervised machine learning algorithms, specifically Random Forest, Support Vector Machine (SVM), and Gradient Boosting Regressor.</p> <p><strong>Findings:</strong> The Gradient Boosting regressor demonstrated the highest predictive accuracy, successfully explaining of the variance in innovation process engagement ( , ). Feature importance analysis identified self-efficacy as the most critical predictor, accounting for of the variance, followed closely by harmonious work passion ( ), belongingness ( ), and identity ( ). Obsessive work passion contributed to the model and exhibited a non-linear threshold effect, indicating that excessive obsession diminishes innovative output, while demographic variables (age, tenure) collectively contributed less than to the predictive power.</p> <p><strong>Conclusion:</strong> Cultivating intrinsic psychological states—specifically high self-efficacy and harmonious passion—is significantly more critical for driving organizational innovation than demographic factors, highlighting the need for compassionate, autonomy-supportive human resource strategies.</p> </td> </tr> </tbody> </table> https://journals.kmanpub.com/index.php/ijimob/article/download/5257/9550