Aim/Purpose: To design and validate a knowledge management model to improve business performance in knowledge-based enterprises (KBEs). Background: In recent years, KBEs have become essential drivers of economic development, particularly in Iran. These enterprises face unique challenges, such as intense competition and limited access to advanced knowledge management practices. Addressing these challenges through effective management models is critical for enhancing their performance. This study aims to design and validate a knowledge management model tailored to the specific needs of KBEs in Iran, fostering improved business performance and competitiveness. Methodology: This research adopts an exploratory mixed-methods approach, integrating both qualitative and quantitative techniques. The qualitative phase involved in-depth interviews with 21 managers from knowledge-based enterprises in Iran, selected through theoretical sampling. In the quantitative phase, data were collected from 140 experts from these enterprises, chosen using simple random sampling. Data collection was carried out via interviews and questionnaires. The qualitative data were analyzed using grounded theory methodology, while the quantitative data were analyzed using Partial Least Squares (PLS) analysis to validate the proposed knowledge management model. Contribution: This study is the first of its kind in Iran to develop a knowledge management model specifically designed for knowledge-based enterprises and to evaluate its impact on business performance. The results offer valuable insights for policymakers and managers, enabling them to refine competitive strategies and foster sustainable growth. Furthermore, the study introduces a validated paradigmatic model of knowledge management, underscoring its pivotal role in enhancing business performance across financial, marketing, innovation, and social domains. Findings: The findings indicate that the implementation of the knowledge management model can significantly improve the performance of knowledge-based enterprises in Iran. This model focuses on enhancing knowledge repositories, streamlining business processes, and strengthening competitive capabilities. Key factors influencing knowledge management include managerial leadership, knowledge workers, a knowledge-oriented culture, and organizational learning. The knowledge management infrastructure in these enterprises acts as a foundational element, while business support factors and environmental uncertainty serve as mediating variables. Recommendations for Practitioners: Organizations should prioritize the development of robust knowledge management infrastructures to enhance business performance. This includes fostering a knowledge-driven culture, investing in collaborative tools, and ensuring effective leadership to create sustainable competitive advantages. Recommendation for Researchers: Future research should investigate the integration of knowledge management strategies in diverse organizational contexts and evaluate their long-term effects on innovation. Exploring how these practices contribute to organizational agility and resilience is also recommended. Impact on Society: The findings highlight the pivotal role of knowledge management in driving societal and organizational progress, particularly in knowledge-driven economies. By optimizing knowledge flow, organizations can contribute to sustainable development and address complex societal challenges. Future Research: Further research should explore the impact of emerging technologies, such as artificial intelligence (AI) and machine learning, on the enhancement of knowledge management practices. Investigating their potential to automate knowledge processes, optimize decision-making, and facilitate real-time knowledge sharing will be crucial for advancing the field. Additionally, examining the ethical implications of integrating these technologies into knowledge management systems represents a critical area for future inquiry.
Hatami et al. (Wed,) studied this question.