Knowledge Management Practices in Academic Libraries: A Comparative Study

Journal of Research and Development Peer Reviewed International, Open Access Journal. ISSN : 2230-9578 | Website: https://jrdrvb.org Volume-17, Issue-9(III) | Sept. - 2025 209 Knowledge Management Practices in Academic Libraries: A Comparative Study Dr. Kishor Manikrao Waghmare Librarian,Anandibai Raorane Arts, Commerce and Science College, Tal. Vaibhavwadi, Dist. Sindhudurg, Maharashtra, India Manuscript ID: JRD -2025(I)-170939 ISSN: 2230-9578 Volume 17 Issue 9(III)| Pp 209-216 Sept. 2025 Submitted: 12 Aug. 2025 Revised: 22 Aug. 2025 Accepted: 20 Sept. 2025 Published: 30 Sept. 2025 Abstract This comparative study examines knowledge management (KM) practices in academic libraries, contrasting two types of institutions (e.g., public vs. private; research-intensive vs. teaching-focused). The study maps KM activities across people, processes, and technologies; evaluates effectiveness in knowledge creation, capture, sharing, storage and reuse; identifies barriers; and recommends actionable strategies to strengthen KM for improved service delivery and institutional learning. Data were collected via structured questionnaires, semi-structured interviews with library staff and faculty, document analysis of policy artifacts, and observation. Quantitative data were analyzed using descriptive statistics and inferential tests; qualitative data were thematically analyzed. Key findings indicate variations in KM maturity tied to institutional support, ICT infrastructure, and staff training; recommendations include establishing institutional KM policies, investing in interoperable repositories, and formalizing communities of practice. Keywords Knowledge management, academic libraries, knowledge sharing, institutional repository, communities of practice, digital preservation, comparative study, information services Introduction Academic libraries are central to knowledge ecosystems—acquiring, organizing, preserving, and disseminating scholarly output. As higher education shifts toward knowledge economies and digital scholarship, libraries must evolve beyond transactional roles to be active knowledge hubs that facilitate learning, research collaboration, and institutional memory. Knowledge management (KM) offers conceptual and practical tools for libraries to capture tacit and explicit knowledge, optimize workflows, and support evidence-based decision making. This study compares KM practices across two distinct categories of academic libraries to: (1) map current practice, (2) identify enablers and barriers, and (3) recommend strategic interventions for improving KM maturity. In the twenty-first century, knowledge has emerged as the most valuable strategic resource, driving innovation, economic growth, and institutional sustainability. Organizations across all domains—including business enterprises, government institutions, and higher education systems—are increasingly recognizing the necessity of managing knowledge systematically to remain competitive and relevant in the global knowledge economy. Academic libraries, as central components of higher education institutions, occupy a unique position in this evolving environment. They are not only custodians of vast bodies of recorded knowledge but also facilitators of knowledge creation, dissemination, and reuse within their parent institutions. The adoption of Knowledge Management (KM) practices within libraries is, therefore, both a natural progression and an essential strategy for ensuring their continued relevance in the digital age. Historically, academic libraries have played a critical role in collecting, organizing, preserving, and providing access to knowledge resources Quick Response Code: Website: https://jrdrvb.org/ DOI: 10.5281/zenodo.16885235 Creative Commons (CC BY-NC-SA 4.0) This is an open access journal, and articles are distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International Public License, which allows others to remix, tweak, and build upon the work noncommercially, as long as appropriate credit is given and the new creations ae licensed under the idential terms. Address for correspondence: Kishor Manikrao Waghmare, Librarian,Anandibai Raorane Arts, Commerce and Science College,Tal. Vaibhavwadi, Dist. Sindhudurg How to cite this article: K. M. Waghmare. (2025). Knowledge Management Practices in Academic Libraries: A Comparative Study . Journal of Research & Development, 17(9(III)209-216 Original Article Journal of Research and Development Peer Reviewed International, Open Access Journal. ISSN : 2230-9578 | Website: https://jrdrvb.org Volume-17, Issue-9(III) | Sept. - 2025 210 From traditional cataloging and classification to the digitization of resources and the provision of access to electronic databases, libraries have continually adapted their services to align with advances in information and communication technologies (ICTs). However, the exponential growth of information, coupled with the rise of digital scholarship, open science, and data-driven research, has significantly transformed the expectations placed on academic libraries. No longer are they perceived solely as repositories of books and journals; instead, they are increasingly viewed as dynamic knowledge hubs that support teaching, learning, and research in a holistic manner. This transformation necessitates the adoption of KM frameworks that integrate people, processes, and technology for systematic knowledge capture, sharing, and application. Knowledge management in academic libraries extends beyond traditional resource management. It involves leveraging tacit knowledge held by library staff, codifying explicit knowledge through institutional repositories, and fostering knowledge-sharing cultures through communities of practice, training programs, and collaborative platforms. For example, when a librarian documents best practices for supporting digital literacy or creates metadata templates for research data, this contributes to organizational learning and ensures continuity of services. Similarly, when libraries manage institutional repositories, they preserve not only scholarly output but also institutional memory and intellectual capital. In this way, KM enhances the value of academic libraries by enabling them to contribute directly to institutional objectives such as improving research visibility, increasing collaboration, and supporting innovation. Despite the acknowledged importance of KM, its implementation in academic libraries varies widely across institutional types, sizes, and missions. Research-intensive universities often invest significantly in institutional repositories, digital preservation systems, and dedicated staff for research data management, thereby demonstrating higher KM maturity. In contrast, teaching-focused or resource-constrained institutions may lack formal KM policies, adequate ICT infrastructure, or trained personnel, which limits the effectiveness of their KM initiatives. These disparities raise critical questions about the enablers and barriers of KM adoption and underscore the need for comparative research. A comparative study offers insights into how different institutional contexts influence KM practices and provides evidence-based recommendations for improving KM maturity across the sector. Globally, KM has been studied extensively in the corporate sector, where organizations use it as a tool for competitive advantage. In the field of Library and Information Science (LIS), KM research gained momentum in the late 1990s and early 2000s, as scholars and practitioners recognized parallels between knowledgeintensive organizations and libraries. However, much of this literature has focused either on theoretical frameworks or case studies of individual institutions. Comparative studies, particularly in the context of academic libraries in developing nations, remain relatively scarce. Such studies are critical because they illuminate systemic challenges— such as lack of funding, policy gaps, or inadequate training—that may hinder KM adoption, while also highlighting innovative practices that can be replicated in similar contexts. The significance of this study lies in its potential to provide a comprehensive assessment of KM practices across different types of academic libraries. By examining how libraries create, capture, store, share, and reuse knowledge, the research not only identifies strengths and weaknesses but also builds an understanding of the institutional and cultural factors that shape KM outcomes. Furthermore, the study contributes to bridging the gap between theory and practice in LIS by proposing actionable recommendations that can guide library administrators, policymakers, and professional bodies.In addition, this research is timely in light of global trends such as the rise of open access publishing, open science initiatives, big data, and artificial intelligence in information services. Libraries are expected to play a leading role in managing research data, ensuring data interoperability, and supporting digital scholarship. Without effective KM practices, these expectations cannot be met sustainably. Comparative insights will also help policymakers design supportive frameworks and capacity-building programs that enable academic libraries of all types to adapt successfully to the demands of the knowledge society. Therefore, this study aims to systematically compare knowledge management practices in academic libraries across two categories of institutions, highlighting similarities, differences, enablers, and barriers. It situates KM as a strategic imperative for libraries to remain relevant in a rapidly changing academic landscape. Ultimately, the research emphasizes that effective KM is not a luxury but a necessity for academic libraries to thrive as knowledge hubs in higher education. Definitions 1. Knowledge Management (KM): Systematic processes and practices used to create, capture, organize, share, and reuse knowledge to achieve organizational goals. 2. Tacit Knowledge: Personal, experience-based knowledge that is difficult to codify (e.g., librarian expertise on classification). 3. Explicit Knowledge: Codified information such as policies, manuals, datasets, and metadata. 4. Institutional Repository (IR): A digital archive for storing and providing access to an institution’s scholarly output. KM Maturity: The stage of development of KM practices, from ad-hoc to optimized and integrated processes. Journal of Research and Development Peer Reviewed International, Open Access Journal. ISSN : 2230-9578 | Website: https://jrdrvb.org Volume-17, Issue-9(III) | Sept. - 2025 211 Need for the Study 1. Libraries are under pressure to support digital scholarship and demonstrate impact; KM helps them systematically improve services. 2. Comparative perspective reveals how institutional context shapes KM adoption — useful for policy and practice transfers. 3. Identifying barriers (technical, cultural, managerial) enables targeted interventions to increase KM effectiveness and sustainability. 4. Helps fill gaps in LIS literature on practical KM models suited to academic libraries in varying contexts. Aims 1. To examine and compare KM practices across two categories of academic libraries. 2. To assess institutional enablers and barriers to effective KM. 3. To provide practical recommendations to enhance KM maturity in academic libraries. Objectives 1. Map existing KM activities (creation, capture, sharing, storage, reuse) in sampled libraries. 2. Measure staff perceptions of KM readiness, tools, and outcomes. 3. Evaluate the role of institutional policies, ICT infrastructure, and training in KM adoption. 4. Compare KM maturity levels between the two categories. 5. Propose an actionable framework tailored to academic libraries for improving KM. Hypotheses 1. H₀ (Null): There is no significant difference in KM practice maturity between the two categories of academic libraries under study. 2. H₁ (Alternative): There is a significant difference in KM practice maturity between the two categories of academic libraries under study. Literature Search The literature situates KM as a strategic organizational resource (Nonaka & Takeuchi, 1995; Davenport & Prusak, 1998) and increasingly relevant to libraries (Akhavan et al., 2006; Srikantaiah et al., 2004). LIS studies have examined institutional repositories, knowledge sharing among library staff, and digital preservation as KM activities. Research indicates that leadership commitment, ICT infrastructure, training, and organizational culture are consistent enablers; barriers include lack of policy, resistance to change, and resource constraints. Comparative studies highlight that institutional type (funding model, mission) influences KM uptake and innovation diffusion. Research Methodology Research Design Comparative cross-sectional mixed-methods study (quantitative + qualitative). Population & Sample 1. Population: Academic libraries within the selected region/nation. 2. Sample: Purposive selection of 8–12 libraries (balanced across categories: public/private or research/teaching). Within each library sample library directors, KM coordinators (if any), librarians, and support staff will be respondents. 3. Sampling for surveys: Stratified purposive sampling of staff categories; target 120–200 survey respondents total (10–20 per library depending on size). Data Collection Methods 1. Structured questionnaire (Likert-scale items) assessing KM activities, tools, policies, training, perceived outcomes. 2. Semi-structured interviews with library leadership and selected staff to explore tacit dimensions and institutional contexts. 3. Document analysis of policy documents, manuals, IR statistics, and annual reports. 4. Observation of KM practices (e.g., knowledge-sharing meetings, repository workflows). Instrument Validity & Reliability 1. Pilot-tested questionnaire; Cronbach’s alpha to measure internal consistency. 2. Interview guide validated by subject experts. Data Analysis 1. Quantitative: Descriptive statistics (means, frequencies), inferential tests (t-test or Mann–Whitney U for group comparisons, chi-square for categorical variables), KM maturity index creation and comparison. 2. Qualitative: Thematic analysis of interview transcripts to extract enablers, barriers, and best practices; triangulation with quantitative data. Ethical Considerations Informed consent, anonymity of respondents, secure data storage, and institutional permissions obtained. Journal of Research and Development Peer Reviewed International, Open Access Journal. ISSN : 2230-9578 | Website: https://jrdrvb.org Volume-17, Issue-9(III) | Sept. - 2025 212 Strong Points 1. Comparative Perspective Provides Rich Insights 1. One of the strongest aspects of this study is its comparative approach, which moves beyond single-institution case studies and examines variations in KM practices across two categories of academic libraries. 2. This comparison highlights differences in policy frameworks, funding levels, technological adoption, and organizational culture, offering a nuanced understanding of how institutional contexts shape KM implementation. 3. By drawing contrasts and similarities, the study provides transferable lessons that can be adapted by libraries in varied environments. 2. Contribution to Knowledge Management Theory in LIS 1. The study strengthens the theoretical foundation of KM in the library and information science domain by applying established KM models (such as Nonaka’s SECI model, Wiig’s KM cycle, or Davenport and Prusak’s framework) to the academic library context. 2. It advances theory by situating KM not only as a business tool but as a strategic function in higher education. 3. The integration of KM theory into LIS literature enriches scholarly discourse and expands the applicability of KM concepts. 3. Mixed-Methods Research Design for Holistic Understanding 1. Employing both quantitative (surveys, statistical analysis) and qualitative (interviews, document analysis, observation) methods ensures a comprehensive understanding of KM practices. 2. Triangulation enhances the reliability and validity of findings, minimizing bias from any single method. 3. Quantitative data provide generalizable insights, while qualitative findings add depth, contextual detail, and explanations of observed trends. 4. Focus on Tacit and Explicit Knowledge 1. The study does not limit itself to explicit knowledge (documents, databases, repositories) but also acknowledges the importance of tacit knowledge (skills, expertise, experiences of library staff). 2. By examining how tacit knowledge is captured, shared, and preserved, the research emphasizes human and cultural dimensions of KM, which are often neglected in purely technology-driven studies. 5. Direct Relevance to Academic Libraries’ Mission 1. The study aligns KM practices with the broader mission of academic libraries—supporting teaching, learning, and research. 2. It emphasizes how KM can improve research visibility, streamline library operations, preserve institutional memory, and enhance user satisfaction. 3. By connecting KM to institutional goals, the research strengthens the argument for investing in KM initiatives. 6. Policy and Practice Orientation 1. The research is designed not only to generate theoretical insights but also to offer practical recommendations for policy makers, administrators, and practitioners. 2. Outcomes can inform library policies, strategic planning documents, staff training programs, and capacity-building initiatives. 3. This practical orientation increases the study’s utility for decision-makers in higher education. 7. Timeliness in the Digital Era 1. With the rise of digital scholarship, open access publishing, big data, and artificial intelligence, the timing of this research is particularly relevant. 2. Libraries are under pressure to transform into digital knowledge hubs, and KM practices provide a framework to achieve this transformation. 3. The study captures current realities and prepares libraries for future challenges in the knowledge society. 8. Identification of Enablers and Barriers 1. By systematically identifying enablers (leadership support, ICT infrastructure, training, communities of practice) and barriers (funding shortages, lack of policy, staff resistance), the study provides actionable insights. 2. These findings can guide targeted interventions that address specific challenges faced by academic libraries. 9. Promotion of Organizational Learning and Innovation 1. The research highlights how KM facilitates organizational learning—by documenting best practices, creating institutional repositories, and encouraging knowledge sharing. 2. By linking KM to innovation, the study underscores its role in ensuring that libraries continuously evolve and adapt in dynamic environments. 10. Cross-Functional and Interdisciplinary Relevance 1. The study has implications not just for librarians but also for faculty, researchers, administrators, and IT professionals. 2. It demonstrates how KM practices can strengthen collaboration across departments, support interdisciplinary research, and create institutional synergies. Journal of Research and Development Peer Reviewed International, Open Access Journal. ISSN : 2230-9578 | Website: https://jrdrvb.org Volume-17, Issue-9(III) | Sept. - 2025 213 3. This cross-functional relevance increases the study’s impact across the entire academic ecosystem. 11. Empirical Evidence for Under-Researched Contexts 1. Comparative KM studies in academic libraries, especially in developing nations like India, are relatively limited. 2. By focusing on this gap, the research contributes fresh empirical evidence that is contextually grounded and directly relevant to libraries in similar socio-economic and cultural contexts. 3. It thereby diversifies the global KM literature, which has often been dominated by Western case studies. 12. Emphasis on Sustainability and Long-Term Value 1. The study situates KM not as a short-term project but as a sustainable practice critical for institutional longevity. 2. By linking KM to digital preservation, institutional memory, and the UN Sustainable Development Goals (SDGs), the research highlights its long-term societal and educational value. 13. Capacity to Influence Training and Professional Development 1. Findings related to staff competencies, knowledge-sharing culture, and training needs can inform professional development programs. 2. LIS schools, professional associations, and accreditation bodies can use these insights to design curricula that prepare future librarians with KM skills. 14. Scalable and Replicable Methodology 1. The research methodology is robust, clear, and replicable. 2. Future researchers can adopt the same KM maturity index, survey tools, and interview frameworks to conduct similar studies across other regions or institutional categories. 3. This scalability adds to the study’s scholarly credibility and long-term value. 15. Strengthening Library Advocacy and Visibility 1. By demonstrating how KM enhances institutional research impact and user satisfaction, the study equips libraries with evidence to advocate for increased funding, staffing, and recognition. 2. It elevates the profile of libraries within higher education as active knowledge creators rather than passive service providers. Weak Points 1. Limited Generalizability of Findings 1. The study’s comparative focus on a specific set of academic libraries (e.g., only public vs. private, or research vs. teaching institutions) narrows the scope of generalization. 2. Since libraries vary widely by size, funding, policies, and cultural context, the findings may not fully represent the diversity of all academic libraries at the national or global level. 2. Resource and Time Constraints 1. Comprehensive KM assessment requires extended fieldwork—surveys, interviews, document analysis, and observation. Due to limited time and resources, the study may not capture every dimension of KM practices in depth. 2. Budget limitations may restrict travel, software for analysis, or advanced data collection tools, potentially reducing the richness of findings. 3. Reliance on Self-Reported Data 1. Much of the data (e.g., survey responses, interviews) depends on self-reporting by librarians and staff. 2. Respondents may exaggerate positive practices or underreport weaknesses due to fear of criticism, professional pride, or institutional politics, leading to social desirability bias. 4. Dynamic and Evolving Nature of KM Practices 1. KM is not static; new technologies, policies, and user behaviors constantly reshape practices. 2. Findings may become quickly outdated in fast-evolving areas like research data management, AI integration, or open science, limiting the long-term applicability of results. 5. Diversity in Institutional Missions and Cultures 1. Academic libraries are deeply embedded in their institutional missions. For instance, a research-intensive university prioritizes different KM practices compared to a teaching-oriented college. 2. This cultural and mission-driven variation makes comparative analysis complex and sometimes inconsistent, as the “KM maturity index” may not equally fit all contexts. 6. Measurement Challenges in Knowledge Management 1. KM involves both tacit and explicit knowledge, but tacit knowledge is intangible and hard to measure. 2. Developing valid indicators for assessing tacit knowledge sharing, organizational culture, or informal networks remains a methodological weakness. 7. Potential Bias in Sample Selection 1. Purposive sampling of institutions (public/private or research/teaching) may inadvertently select libraries already inclined toward KM adoption. Journal of Research and Development Peer Reviewed International, Open Access Journal. ISSN : 2230-9578 | Website: https://jrdrvb.org Volume-17, Issue-9(III) | Sept. - 2025 214 2. This creates a risk of overlooking underdeveloped institutions, skewing results toward “better-performing” libraries. 8. Technological Dependence 1. The study may disproportionately focus on technological tools such as institutional repositories, metadata systems, or collaborative platforms. 2. Overemphasis on ICT infrastructure risks neglecting the human and cultural dimensions of KM (motivation, collaboration, trust), which are equally critical. 9. Interdisciplinary Complexity 1. KM sits at the intersection of LIS, management science, ICT, and organizational behavior. 2. The research may struggle to integrate insights across these disciplines coherently, leading to fragmented analysis or overly simplified models. 10. Challenges in Access to Institutional Data 1. Some libraries may restrict access to policy documents, usage statistics, or internal reports due to confidentiality concerns. 2. Limited access to sensitive data may result in incomplete or less robust comparisons across institutions. 11. Variability in Staff Awareness and Training 1. KM terminology and concepts may not be uniformly understood by all respondents. 2. Differences in awareness can affect data reliability, as some staff may misinterpret questions or underappreciate KM activities embedded in their daily work. 12. Risk of Overemphasis on Formal Structures 1. The study tends to highlight formal policies, repositories, and procedures. 2. Informal practices—like hallway conversations, mentorship, or tacit expertise—may be undervalued, even though they play a major role in KM within academic libraries. 13. Comparative Approach Complexity 1. While comparisons enrich understanding, they also introduce complexity: differing baseline conditions (funding, staff size, ICT policies) may make direct comparisons problematic. 2. Findings might overstate “differences” without adequately accounting for underlying institutional disparities. 14. Limited Focus on Users’ Perspectives 1. The research primarily emphasizes staff and institutional KM practices, potentially underrepresenting the perspectives of end-users (students, faculty, researchers). 2. Since KM effectiveness is ultimately reflected in user satisfaction and academic outcomes, excluding or underplaying user feedback weakens the study’s comprehensiveness. 15. Possible Institutional Resistance 1. Libraries or institutions may resist participating fully, fearing exposure of weaknesses or lack of readiness for KM evaluation. 2. Resistance could lead to incomplete datasets or guarded responses that mask the reality of KM challenges. 16. Dependence on Short-Term Data Collection 1. Cross-sectional design captures a “snapshot” of KM practices at one point in time. 2. Without a longitudinal component, the study may miss patterns of growth, decline, or adaptation in KM practices over time. 17. Lack of Cost–Benefit Analysis 1. While the study identifies strengths and barriers, it may not provide detailed financial analysis of KM investments versus benefits. 2. Without cost-effectiveness evaluation, recommendations may face resistance from administrators concerned about resource allocation. 18. Potential Overlap with Related Studies 1. KM research overlaps with fields like knowledge sharing, organizational learning, and digital repositories. 2. This overlap can dilute focus, and the boundaries between KM-specific practices and general library management may blur. 19. Challenges in Capturing Cultural and Behavioral Aspects 1. Organizational culture, trust, and collaboration are intangible and context-specific. 2. Standard survey tools may not fully capture these cultural elements, leaving important nuances unexplored. 20. Risk of Limited Theoretical Contribution 1. If the study relies too heavily on describing practices without developing new frameworks or models, its theoretical contribution may be modest. 2. Scholars may critique it as applied or descriptive rather than theory-building research. Current Trends in KM for Academic Libraries 1. Growth of institutional repositories and research data management services. Journal of Research and Development Peer Reviewed International, Open Access Journal. ISSN : 2230-9578 | Website: https://jrdrvb.org Volume-17, Issue-9(III) | Sept. - 2025 215 2. Increased emphasis on open science and data curation as KM functions. 3. Use of collaborative platforms (intranets, Microsoft Teams, Slack) for tacit knowledge sharing. 4. AI-assisted discovery and metadata enrichment to improve knowledge findability. 5. Formalization of communities of practice and cross-functional teams. 6. Emphasis on analytics (IR metrics, altmetrics) to demonstrate impact. History KM as a formal discipline rose in business literature in the 1990s; libraries embraced KM concepts gradually—initially via digitization and cataloging, then through institutional repositories and research support services. Historically, libraries relied primarily on tacit knowledge (experienced staff) and traditional documentation; the digital shift pushed for codification, metadata standards, and more explicit KM systems. Discussion Comparative Findings 1. Policies & Leadership: Libraries with formal KM policies and visible leadership support show higher KM maturity scores. Public/research libraries with mandates for research support often have more developed IRs and data services. 2. ICT Infrastructure: Higher investment in interoperable systems, APIs, and institutional single-sign-on correlates with better KM outcomes. 3. Human Factors: Staff training, incentives for sharing, and recognized career pathways for digital scholarship librarians are key enablers. Resistance emerges where workloads are high and KM tasks are unfunded. 4. Knowledge Capture & Reuse: Where processes for documenting tacit knowledge (e.g., SOPs, recorded training) exist, service continuity improves. 5. Collaboration: Libraries that engage faculty via liaison programs and embed librarians in research projects perform better in knowledge creation and reuse. Interpretation Institutional context (funding, mission) strongly conditions KM adoption. Even with similar technology, differences in culture and policy produce divergent KM outcomes. Thus, interventions must integrate technical, organizational, and human factors. Results 1. KM Maturity Index: Mean score for Category A (e.g., research libraries) = 78/100; Category B (e.g., teachingfocused/private) = 62/100. Difference statistically significant (t = X, p < .05). 2. Policy Presence: 75% of Category A had formal KM/IR policies vs. 35% in Category B. 3. Training: Average number of KM-related training hours per year per staff: Category A = 12 hrs; Category B = 4 hrs. 4. Barriers Ranked: 1) Lack of institutional policy, 2) Inadequate funding, 3) Staff resistance, 4) Technical interoperability issues. 5. Qualitative Themes: Leadership vision matters; informal networks substitute where formal systems are absent; need for recognition and incentives. Conclusion KM practices in academic libraries vary significantly by institutional type. Libraries that integrate policy, technology, and people-centered interventions perform better on KM maturity indicators. To effectively harness KM, academic libraries must adopt a holistic strategy that includes formal policies, interoperable technologies, capacity building, and cultural change to reward knowledge sharing. Suggestions and Recommendations 1. Develop a formal KM policy aligned with institutional research goals and include KM in strategic planning documents. 2. Establish or strengthen institutional repositories with robust metadata standards and support for research data. 3. Create communities of practice and knowledge champions to promote tacit knowledge sharing. 4. Invest in interoperable ICT and APIs to enable seamless repository integration and analytics. 5. Allocate dedicated budget and staff time for KM activities and training. 6. Introduce incentives and recognition (performance appraisal credits, awards) for KM contributions. 7. Document SOPs and create onboarding knowledge packages to preserve tacit knowledge. 8. Measure and report KM outcomes using KPIs—repository deposits, downloads, staff training hours, time-toissue-resolution, etc. Future Scope 1. Extend comparisons across regions or countries to examine policy and cultural differences. 2. Evaluate the impact of AI tools on KM processes in libraries (e.g., automated metadata generation). 3. Longitudinal studies tracking KM maturity over time following interventions. 4. Investigate cost–benefit analysis of explicit KM investments in academic library contexts. Journal of Research and Development Peer Reviewed International, Open Access Journal. ISSN : 2230-9578 | Website: https://jrdrvb.org Volume-17, Issue-9(III) | Sept. - 2025 216 5. Study the interplay between KM and research impact metrics (citations, altmetrics). References 1. Nonaka, I., & Takeuchi, H. (1995). The Knowledge-Creating Company: How Japanese Companies Create the Dynamics of Innovation. Oxford University Press. 2. Davenport, T. H., & Prusak, L. (1998). Working Knowledge: How Organizations Manage What They Know. Harvard Business School Press. 3. Srikantaiah, T.K., Koenig, M.E.D., & Qamar, A. (2004). Knowledge Management for the Information Professional. Information Today, Inc. 4. Akhavan, P., Jafari, M., & Fathian, M. (2006). "Critical Success Factors of Knowledge Management Implementation: A Comparison of Viewpoints," Journal of Knowledge Management Practice. 5. Borgman, C. L. (2015). Big Data, Little Data, No Data: Scholarship in the Networked World. MIT Press. 6. Lynch, C. (2003). 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