Ensuring long-term knowledge continuity is a key challenge for organizations managing the long-cycle maintenance of complex infrastructure. This paper explores how agency-led research programs can support dynamic knowledge continuity within the Dutch Directorate-General for Public Works and Water Management (Rijkswaterstaat, RWS), particularly in relation to its storm surge barriers. The long-cycle maintenance of the storm surge barriers faces long redesign cycles which result in a challenging human capital development environment with regards to specialist knowledge domains. Current knowledge of complex barrier systems is of a distributed nature following several decades of intensive outsourcing. At present the agency is investing in research programs aimed to strengthen its knowledge in strategic areas. This article aims to add to the limited literature of leveraging research efforts for long term knowledge continuity in a distributed knowledge environment. The research was conducted using questionnaires and semi-structured interviews. Fourteen respondents comprise of active researchers, research supervisors, and research managers. Researchers acquire high levels of proficiency in critical engineering knowledge domains. This equates to the development of valuable human capital that flows from the program when researchers complete their projects. Researchers were found to be highly motivated to stay on and locally implement their findings or contribute to their domain of engineering knowledge. Results include nine ways in which the research programs contribute to long-term knowledge continuity, of which human capital development is the most important. The study further reveals that while research programs effectively cultivate deep technical expertise, their potential is underutilized due to limited follow-up employment opportunities and a lack of strategic alignment with staffing and insourcing. We argue that research-developed talent should be strategically integrated into local technical teams to strengthen RWS’s internal capabilities, foster standardization, and ensure preparedness for long-cycle maintenance and redesign challenges. Our findings inform both theoretical perspectives on dynamic knowledge management and practical strategies for asset-intensive public organizations.

This research undertakes a systematic literature review to explore the integration and application of ontologies within Business Intelligence (BI) components across a variety of domains. Ontologies, as formal representations of knowledge, have emerged as a key enabler in enhancing the functionality and intelligence of BI systems, particularly in the era of big data and digital transformation. The objective of this study is to analyze how ontologies are designed, implemented, and utilized to improve data integration, semantic interoperability, and system adaptability. The review draws upon data sources from Scopus, IEEE Explore, Science Direct, and Google Scholar, ensuring a rigorous and comprehensive coverage of relevant literature. Following a structured selection process based on inclusion and exclusion criteria, 27 peer-reviewed articles published between 2011 and 2024 were identified as meeting the quality and relevance standards for this study. The selected studies reveal that ontology-driven BI components offer several advantages, including the unification of heterogeneous data sources, improved semantic clarity, and enhanced reasoning capabilities for decision support. Moreover, ontologies contribute significantly to the flexibility and scalability of BI systems, facilitating the development of context-aware and domain-specific analytical tools. Despite these advantages, the review also highlights persistent challenges, such as difficulties in managing large-scale ontologies, real-time processing limitations, and organizational resistance to adoption due to complexity and integration costs. By synthesizing the existing body of knowledge, this review not only consolidates the current understanding of ontology-driven BI but also provides a conceptual framework for future research. It emphasizes the need for innovative approaches that address identified limitations and align ontology development with dynamic organizational requirements. The findings serve as a valuable resource for both researchers and practitioners, offering strategic insights into the design and deployment of advanced BI solutions. Ultimately, this study contributes to the evolving discourse on intelligent decision-making systems by bridging theoretical perspectives with real-world applications.

The growing conceptual complexity and persistent ambiguity surrounding the definition and measurement of the Knowledge Society/Knowledge Economy (KS/KE) and its associated competencies point to an unresolved research gap, which may contribute to fragmented and insufficiently coordinated policy responses. While numerous frameworks describing 21st-century skills and competencies exist, their linkage to macro-level indicators capturing the performance of knowledge-based economies remains limited and methodologically underexplored. This paper addresses this gap by examining the methodological viability of systematically deriving key competencies for the KS/KE from Knowledge Economy Index (KEI) indicators and by assessing whether the resulting competency model demonstrates conceptual congruence with established 21st-century competency frameworks. The primary objective of the study is to develop and apply a novel and robust methodological framework for constructing a key competency model tailored to the contemporary socio-economic context of the KS/KE. The proposed approach is grounded in a systematic content analysis of existing KEIs and their constituent indicators. Specifically, the methodology is applied to a dataset comprising 301 indicators derived from four internationally recognised KEIs: the Global Knowledge Index (GKI), the Global Innovation Index (GII), the European Innovation Scoreboard – Summary Innovation Index (EIS- SII), and the Digital Economy and Society Index (DESI). A central methodological contribution of the study lies in the uniform semantic categorisation of all indicators and their systematic division into input indicators, capturing structural prerequisites and investments, and output indicators, reflecting achieved results and performance. This analytical structure enables the identification of key competencies that mediate the transformation of invested resources into measurable and socially desirable outcomes within KE. To assess the conceptual robustness of the proposed model, the resulting key competency model for KS/KE is validated against a reference database of competencies synthesised from authoritative policy and strategic documents issued by organisations such as the OECD, UNESCO, the European Commission, the Council of the European Union, the World Economic Forum, and the Partnership for 21st Century Learning. The validation confirms a high degree of conceptual alignment between the empirically derived competencies and established 21st-century competency frameworks. In addition, the study exploits an extensive longitudinal dataset of KEI indicators available since 2017 as the empirical basis for a model-based analysis of anticipated trends in key competency development over a forthcoming three-year horizon. Compared to traditional competency modelling approaches based on expert studies, job analyses, behavioural observations, Delphi methods, or surveys, the proposed model leverages dynamically updated KEI indicators, offering greater flexibility and responsiveness to rapid socio-economic change. At the societal level, the resulting KS/KE key competency model provides a foundation for preparing future knowledge workers, while at the organisational level it supports talent management practices and the development of organisation-specific competency models aimed at sustaining competitive advantage.

Escalating global environmental challenges have intensified pressure on businesses to adopt sustainable practices, particularly within Small and Medium-sized Enterprises (SMEs). While leadership is recognized as a pivotal driver of this transition, the specific internal organizational mechanisms through which leadership influences green outcomes remain underexplored. This study examined the impact of transformational leadership on green business performance in SMEs, focusing specifically on the mediating roles of knowledge management practices and cultural infrastructure. A quantitative research design was employed, utilizing survey data collected from 135 SMEs across diverse manufacturing and service sectors in Southeast Asia. Structural equation modeling was used to test the hypothesized relationships in the study. The findings indicate a significant positive relationship between transformational leadership and green business performance. Crucially, both knowledge management practices and cultural infrastructure were found to mediate this relationship significantly, both individually and in concert. This study underscores the strategic importance of nurturing robust knowledge management systems and a supportive cultural environment to translate transformational leadership initiatives into tangible green outcomes within SME. This study contributes to a more nuanced understanding of the pathways through which leadership fosters sustainability, offering interdisciplinary insights relevant to management, economics, and environmental studies.

Knowledge-sharing practices is crucial for communities striving to combat poverty. The paper explores knowledge-sharing practices for poverty eradication among rural women in Ghana and makes recommendations to improve knowledge sharing. It adopted the interpretive paradigm and a qualitative research approach. The primary data were obtained from 111 rural women in the Northern region, Ghana. Face-to-face interviews, focus-group discussions and observations were used to collect data. The study was guided by the following question: “What are the knowledge-sharing practices for poverty eradication among rural women in the northern region of Ghana?” Thematic analysis was conducted based on Braun and Clarke’s (2006) framework. The findings revealed that rural women engage in a variety of knowledge-sharing practices such as social interactions with extension officers, interactions between family and friends, interactions with social cliques and self-proclaimed experts, village meetings, religious leaders and institutions meetings, Communities of Practice and knowledge sharing programmes. The study recommends the need for rural women to seek professional knowledge from established knowledge centers. A dedicated mobile phone helpline project is also recommended, as well as the training and motivation of extension officers to improve the quality of extension services provided to rural women. Additionally, elements such as literacy programs, appropriate leadership, stakeholder participation, trust and respect for culture, ICT technology, gender-equity campaigns, behavioral change, social amenities and resource availability and ongoing knowledge-sharing programmes were also considered crucial for enhancing knowledge sharing practices. The study contributes to knowledge management by demonstrating how tacit knowledge flows are sustained through informal networks, trust, and reciprocity in rural contexts. By foregrounding these socially embedded and community-driven practices, it broadens knowledge management theory beyond corporate settings and highlights their relevance for poverty eradication and women’s empowerment. The study is timely as it seeks to leverage knowledge management practices to eradicate poverty, empower women, and address gender inequality in line with Goals 1 and 5 of the Sustainable Development Goals.

Knowledge management (KM) is recognized as being vital for organizational competitiveness and sustainability for both private and public organizations. A great myriad of theories, frameworks, and tools have been developed, many of which have been developed with private organizations in mind, given their dependence on maintaining competitiveness in the market for their survival. However, the stakes for public organizations could be considered greater, as their decisions and actions affect a wide range of stakeholders, and their management, in general, faces important challenges, such as the high turnover of their employees. For this reason, numerous efforts have been made to improve the way knowledge is managed in public institutions, yet its effective implementation in public entities remains a challenge. In Latin America, one of the countries where explicit efforts have been made to foster KM in public institutions is Colombia. The country has developed an Integrated Planning and Management Model (IPMM), which includes a specific mandate for KM implementation in all the public institutions of the country. Although the IPMM includes this KM mandate, Colombian public entities have been facing several difficulties in achieving the KM implementation. In fact, KM adoption has been slow and its impact limited, signalling the need for systemic solutions. This research employs a systemic approach, grounded in the ISO 30401 standard and a comprehensive literature analysis, to develop a KM implementation strategy tailored to the IPMM. The proposed strategy, emphasizing strategic, human, and operational factors, positions KM as the central organizing principle of the IPMM and, at the same time, is aligned with ISO 30401 guidelines. This integration aims to ease the implementation of KM within a KM system that leads to enhancing the performance of public entities in Colombia. Although being developed for Colombian public entities, the proposed strategy offers valuable insights for public administrations globally seeking to leverage KM for strategic advantage to better fulfil their mandates for the benefit of society as a whole.

A scoping review was conducted in order to systematically map the research featuring Project Based Organizations (PBOs) in relation to knowledge transfer. This scoping review considered over 50 years of research to ascertain how PBOs transfer knowledge by using an interpretative structural model (ISM) to illustrate the outcomes of the investigation via the Systemic Lessons Learned Knowledge (Syllk) Model, created by Duffield and Whitty (2015). We wanted to illustrate what knowledge transfer elements from the authors’ original model outlining six key themes were sustained and prevalent in literature as representative of this knowledge transfer process. The six elements are: learning, culture, social, technology, process and infrastructure. Employing an ISM also helped identify gaps in existing knowledge. The following research questions formed the basis of our study: Research Question 1: How does the Syllk model help interpret and categorize knowledge transfer dynamics in PBO contexts? Research Question 2: What adaptations are required, if any, to the Syllk Model (Duffield & Whitty, 2015) to better facilitate knowledge transfer within PBOs? Research Question 3: What are the key barriers to knowledge transfer in PBOs? Findings: Extant literature indicated that knowledge sharing depends on the willingness of individuals to participate, without which lessons cannot be learned. The results of this scoping review illustrated how some of the elements within the original Syllk Model by Duffield and Whitty (2015) are not fully exploited by organizations. Moreover, several terms possess hazy definitions which further disadvantaged outcomes as it makes some reserch outputs open to question because concensus on the ideology for each element considered as a key theme is subject to interpretation. We propose the Aspirational Syllk (ASyllk) Model as a reconceptualized ISM that enables PBOs to systematically capture and assess experiential learning outcomes. Methodology: A scoping review was undertaken looking at 202 peer reviewed journal papers: Scoping reviews differ from a systematic review in that the former maps a broad body of literature on relevant topic areas and provides tabular outputs, as well as identifying gaps. Whereas the latter considers a far narrower range of research material as it possesses a dedicated synthesis. We subscribed to the scoping review protocol advocated by Bragge et al. (2011) in that we delineated our area of exploration, thereafter we conducted an extensive literature review and then we reported upon these sources to accurately assess the barriers to organizational learning and, thus, identify the gaps in literature. We also considered the antecedents that go into knowledge transfer in PBOs. Significance: Despite a half century of research on knowledge transfer, our findings indicated that knowledge transfer is not intrinsic to PBOs, thus illustrating the need for robust project termination processes to garner key lessons learned for subsequent organizational learning capacity. Through our extensive examination of existing literature, covering over 200 sources, we illustrated a detailed understanding of the barriers to knowledge transfer within PBOs. This scoping review serves as a powerful resource for researchers and practitioners by offering insights into an ammended model to test in future research.

In the fast-moving industrial environment of the world today, the importance of promoting innovation has clearly increased as a key driver of business performance. Nowhere is this more obvious than in the pharmaceutical industry, where the quest for advances in Research and development is viewed as crucial. Developing an awareness of the drivers of innovative working behavior among workforce members is of the highest priority, and this study investigates the link between knowledge sharing and innovative work behavior among pharmaceutical engineers in Morocco. Despite the increasing relevance of innovation in the pharmaceutical sector, studies on the effects of knowledge sharing in non-Western contexts are limited. This gap demonstrates the necessity for further research aimed at the Moroccan environment, where hierarchical structures and limited R&D capabilities influence knowledge-sharing practices. A sample of 286 pharmaceutical engineers contributed to a quantitative research study. The findings indicate that knowledge donating and knowledge collecting positively impact innovative work behavior, with knowledge donating exerts a greater influence. The paper highlights the value of promoting a culture of knowledge sharing to stimulate innovation. Limitations identified relate to the choice of convenience sampling and the restriction to a single sector. Additional investigation could be conducted in other sectors to better understand the links between knowledge sharing and innovative work behavior.

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.

This study examines the cultural dynamics that influence knowledge-sharing in Philippine higher education institutions (HEIs). It addresses the gap in understanding the impact of national, organizational, and local (institutional) cultural factors on educators' intentions to share knowledge. The research employs a mixed-methods approach, integrating quantitative analysis via multiple regression and ANOVA with qualitative insights from follow-up interviews. This comprehensive methodology suggests that cultural dimensions, such as power distance and collectivism, have a significant influence on knowledge-sharing intentions. The findings indicate that diminishing power distance and formalizing knowledge-sharing processes enhance the knowledge ecosystem within HEIs. These insights are valuable for educational practitioners, administrators, and policymakers who aspire to cultivate a collaborative and knowledge-rich environment. By customizing strategies to align with local cultural contexts, institutions can enhance teaching, research, and application, thereby advancing the domains of learning and organizational competitiveness.