Purpose: This study aims to contribute to the understanding of Entrepreneurship and Resource-Based View (RBV) by investigating the research landscape of Innovation Determinants (ID). Through an extensive bibliometric analysis and knowledge mapping, we explore intellectual structures, emerging trends, research hotspots, and future prospects in the field from 1990 to December 2022. Additionally, we focus on identifying top research organizations, authors, collaboration patterns, and commonly used keywords to advance knowledge and awareness in this area.Design/methodology/approach: A comprehensive retrieval strategy was employed to gather 2359 articles on ID from Web of Science, covering the period from 1990 to 2022. Utilizing CiteSpace as a visualization tool, we visually represent authors, institutions, and keywords. By examining knowledge maps using various indicators, we showcase the intellectual foundation and current research frontiers within the domain of ID.Findings: Our findings reveal significant progress in academic research on ID over the past three decades, with a substantial number of 2359 published articles in the field. This signifies considerable advancement in exploring ID. The analysis of the co-authorship network presents a network of 406 authors represented as nodes and 112 collaborative interactions as links. The network's density indicates that only a minute 0.14% of the potential connections in the ID network have been established, highlighting the need for more cohesive and extensive global collaborations in this field.Originality/value: This paper's originality lies in its temporal and dynamic examination of the past thirty years, utilizing CiteSpace for co-citation and co-occurrence network analysis. Additionally, the scientometric analysis reveals key co-occurring keywords, providing insights into the conceptual characteristics within the research field.

Research exploring the integration of knowledge management and artificial intelligence has grown significantly over the past two decades, driven by the transformative potential of intelligent technologies in reshaping how organizations create, share, and apply knowledge. Despite this expansion, the field remains conceptually fragmented, with limited synthesis across theoretical and practical contributions. This study offers a comprehensive bibliometric analysis of 1,650 peer-reviewed publications indexed in the Web of Science from 1975 to 2024. By employing performance metrics, co-citation and keyword co-occurrence analyses, timeline visualizations, and citation burst detection; the study maps the intellectual landscape and thematic evolution of this interdisciplinary domain. The results reveal four core thematic areas: the strategic application of artificial intelligence in human resource management, hybrid decision-making frameworks, innovation-driven supply chain transformation, and the use of intelligent systems in hospitality and service delivery. These clusters illustrate the field's conceptual diversity and the convergence of technological and managerial perspectives. Burst-detection analysis pinpoints 2020–2023 as a tipping period, when landmark publications sharply accelerated theoretical diversification and research momentum across the KM–AI domain. Theoretically, the study refines the Knowledge-Based View by introducing the contingencies of algorithmic transparency and inter‑organizational power asymmetry, advancing a paradox-aware lens that reconciles augmentation vs. transformation and optimization vs. resilience tensions. Practically, cluster-specific evidence is translated into adaptable principles for HR leaders, supply-chain managers, and service innovators, emphasizing phased AI deployment, transparency-driven trust, and balanced efficiency–resilience strategies, while informing sector-specific governance standards and paradox-aware curricula for policymakers and educators. By identifying key research trajectories, influential contributions, and emerging areas of inquiry, this work provides a structured overview of the field's development and lays the foundation for future investigations into the evolving relationship between knowledge management and artificial intelligence. The results reveal four core thematic areas: the strategic application of artificial intelligence in human resource management, hybrid decision-making frameworks, innovation-driven supply chain transformation, and the use of intelligent systems in hospitality and service delivery. These clusters illustrate the field's conceptual diversity and the convergence of technological and managerial perspectives. Burst-detection analysis pinpoints 2020–2023 as a tipping period, when landmark publications sharply accelerated theoretical diversification and research momentum across the KM–AI domain. Theoretically, the study refines the Knowledge-Based View by introducing the contingencies of algorithmic transparency and inter‑organizational power asymmetry, advancing a paradox-aware lens that reconciles augmentation vs. transformation and optimization vs. resilience tensions. Practically, cluster-specific evidence is translated into adaptable principles for HR leaders, supply-chain managers, and service innovators, emphasizing phased AI deployment, transparency-driven trust, and balanced efficiency–resilience strategies, while informing sector-specific governance standards and paradox-aware curricula for policymakers and educators. By identifying key research trajectories, influential contributions, and emerging areas of inquiry, this work provides a structured overview of the field's development and lays the foundation for future investigations into the evolving relationship between knowledge management and artificial intelligence.