BEHAVIOURAL DATA MINING FOR ORGANIZATION NETWORKS: OPTIMIZING KNOWLEDGE SHARING AND COLLABORATION

Purpose: This study utilizes behavioural data mining techniques to analyze knowledge sharing and cooperation dynamics within the organizational network.The article focuses on understanding network composition through employee digital interactions, analyzing communication patterns and factors affecting effectiveness, developing a predictive behavioral model, and proposing strategic data-driven recommendations for knowledge management.The article aims to enhance organizational understanding and strategic decision-making.Design/methodology/approach: By utilizing a mixed-method approach, this study seeks to leverage behavioural data for improved insights and choices.The method uses digital data mining to extract conversational, informational, and knowledge-consuming patterns from organizational platforms.Key actors and structural barriers are then identified through creating and analyzing organizational knowledge networks using social network analysis.Digital footprints are used in this method to comprehend the corporate knowledge network.Knowledge management principles and social network theory are part of the theoretical framework.Findings: The study seeks to uncover knowledge brokers and bottlenecks, uncover patterns of behaviours associated with successful information sharing, and provide guidance for adaptation techniques aimed at improving collaboration and knowledge sharing inside organizations.The results will guide suggestions for process improvement by offering a data-driven understanding of the behaviours, important participants, and roadblocks in the knowledge network. Research limitations/implications:The research acknowledges the fundamental limitations of concentrating on digital data.It also identifies significant implications to further the field of knowledge management by offering a basis for data-driven strategies and proposing significant avenues for future study, such as addressing ethical concepts.Practical implications: This study offers strategies and insights from examining existing digital activities.They are context-specific, encourage collaboration, and enable adjustments to technology for better business outcomes. Social implications:The article estimates significant effects on society, including improved innovation, problem-solving, inclusive knowledge access within organizations, positive public perception indirectly, and better Corporate Social Responsibility practices related to environmental issues.Originality/value: The study applies behavioural data mining techniques to organizational knowledge management, offering a new approach to optimizing knowledge networks.It provides empirical evidence for using data-driven insights to enhance knowledge sharing and cooperation.By integrating qualitative insights with behavioural data mining and network analysis, it offers a comprehensive understanding of organizational knowledge networks.Additionally, it provides practical guidance for researchers and practitioners.