Exploring the Intersection of Human-Computer Interaction and Organisational Behaviour: A Multidisciplinary Approach to Management and Communication

Abstract

This research aims to join Human-Computer Interaction (HCI) and Organisational Behaviour (OB) in an effort to strengthen management and communication in modern organizations. Researchers link computational algorithms and organizational concepts to find out how technology influences communication and teamwork among employees. Researchers used four algorithms—Support Vector Machine, Random Forest, K-Nearest Neighbors, and Neural Networks—to study how communication is carried out within organizations and to predict effective communication using the datasets. Results from experiments revealed that Neural Networks achieved the greatest accuracy, at 89.5%, while Random Forest came in second with 85.2%, followed by SVM at 82.7%, and KNN achieved the least accuracy at 78.4%. This shows that deep learning models are better suited to model human-computer interaction. When compared to previous studies, the team finds that HCI and OB approaches improve communication prediction accuracy by 7–10 percentage points. The research proves that using the latest in AI will promote adaptability in workplace communication and make communication more suitable to each situation. This research adds to our knowledge of how technology and people’s behaviors can combine to create smooth, open, and tough environments for organizations. Future studies should focus on ethics, privacy, and the part humans still play in job environments assisted by AI.