From Walking Libraries to Answer Engines: Optimizing Knowledge Internalization in Public Financing with RAG-Based AI Chatbots

Authors

DOI:

https://doi.org/10.33096/jmb.v13i1.1366

Keywords:

RAG, AI Chatbot, SECI Model, KMS Success Model, Knowledge Management, Knowledge Internalization

Abstract

This research arises from the critical need to optimize knowledge internalization within the SECI Model, especially in organizations handling complex and regulated information such as public financing. The study aims to identify the limitations of the existing Knowledge Management System (KMS), implement a Retrieval-Augmented Generation (RAG)-based AI Chatbot prototype, and evaluate its effectiveness in facilitating knowledge internalization. A qualitative case study approach was employed using the Design Science Research Method (DSRM). Data were collected through in-depth interviews and prototype testing involving 10 purposively selected respondents from the Public Financing Division of PT SMI. Findings indicate that the conventional KMS is suboptimal, leading to high dependency on social learning and the "walking library" phenomenon, where critical knowledge is siloed within specific individuals rather than being institutionalized. The implemented AI Chatbot prototype successfully accelerated the learning curve for new employees, reduced cognitive load – the mental effort required to search for and synthesize information, and received positive evaluation based on the KMS Success Model dimensions. The study implies that organizations should transition their knowledge-sharing culture from individual dependency to smart system-based interactions.

Downloads

Download data is not yet available.

Author Biographies

  • Debrian Ruhut Saragih, Universitas Telkom

    Debrian Ruhut Saragih is a researcher affiliated with Universitas Telkom, Bandung, Indonesia. His research interests focus on Knowledge Management Systems (KMS), particularly the integration of Artificial Intelligence and Retrieval-Augmented Generation (RAG) technology within the public sector. His current work explores the application of the SECI Model to enhance knowledge internalization and organizational learning in infrastructure financing institutions.

  • Grisna Anggadwita, Universitas Telkom

    Grisna Anggadwita is a lecturer and researcher at Universitas Telkom, Bandung, Indonesia. She holds a Doctoral degree (Dr.) and holds S.T. and M.S.M. degrees. Her research expertise encompasses Knowledge Management, Service Innovation, and Organizational Performance. She has published various studies in reputable journals covering topics such as knowledge leakage, collaborative innovation, and knowledge management practices in both public and private sectors.

References

Abu Shawar, B., & Atwell, E. (2007). Chatbots: Are they Really Useful?. Journal for Language Technology and Computational Linguistics, 22(1), 29–49. https://doi.org/10.21248/jlcl.22.2007.88.

Alavi, M., & Leidner, D. E. (2001). Review: Knowledge Management and Knowledge Management Systems: Conceptual Foundations and Research Issues. MIS Quarterly, 25(1), 107-136. https://doi.org/10.2307/3250961.

Anggadwita, G. and Dhewanto, W. (2013). Service innovation in public sector: a case study on PT. Kereta Api Indonesia. Journal of Social and Development Sciences, 4(7), 308-315. https://doi.org/10.22610/jsds.v4i7.766.

Bawack, R. E., Wamba, S. F., & Carillo, K. D. A. (2021). Artificial intelligence in practice: Implications for information systems research. Journal of Enterprise Information Management, 34(1), 228-262. https://doi.org/10.1108/JEIM-11-2020-0448.

Boyce, C., & Neale, P. (2006). Conducting in-depth interviews: A guide for designing and conducting in-depth interviews for evaluation input (Vol. 2). Watertown, MA: Pathfinder international.

Chakraborty, S., Misra, B., Dey, N. (2024). AI-Based Knowledge Management Applications. In: AI-Empowered Knowledge Management in Education. SpringerBriefs in Applied Sciences and Technology(), 59-75. https://doi.org/10.1007/978-981-97-2574-8_4.

Chen, L., Zhang, X., & Xu, Y. (2022). Integrating chatbots into knowledge management: A case study of organizational learning. Journal of Knowledge Management, 26(3), 567–582. https://doi.org/10.1108/JKM-05-2021-0397.

Davenport, T. H., & Prusak, L. (1998). Working knowledge: How organizations manage what they know. Harvard Business School Press.

DeLone, W.H., & McLean, E.R. (2003). The DeLone and McLean Model of Information Systems Success: A Ten-Year Update. Journal of Management Information Systems, 19(4), 9 - 30. https://doi.org/10.1080/07421222.2003.11045748.

Dwivedi, Y. K., Kshetri, N., Hughes, L., Slade, E. L., Jeyaraj, A., Kar, A. K., Baabdullah, A. M., Koohang, A., Raghavan, V., Ahuja, M., Albanna, H., Albashrawi, M. A., Al-Busaidi, A. S., Balakrishnan, J., Barlette, Y., Basu, S., Bose, I., Brooks, L., Buhalis, D., … Wright, R. (2023). Opinion paper: “so what if chatgpt wrote it?” multidisciplinary perspectives on opportunities, challenges and implications of Generative Conversational AI for Research, practice and policy. International Journal of Information Management, 71, 102642. https://doi.org/10.1016/j.ijinfomgt.2023.102642.

Edmondson, A. (1999). Psychological Safety and Learning Behavior in Work Teams. Administrative Science Quarterly, 44(2), 350-383.

Elmasri, R., & Navathe, S. B. (2020). Fundamentals of Database Systems (7th ed.). Pearson.

Gao, J., Galley, M., & Li, L. (2019). Neural approaches to conversational AI: Question answering, task-oriented dialogues and social chatbots. Foundations and Trends in Information Retrieval, 13(2-3), 127-298. https://doi.org/10.1561/1500000074.

Grant, R. M. (1996). Toward a Knowledge-Based Theory of the Firm. Strategic Management Journal, 17(S2), 109-122. https://doi.org/10.1002/smj.4250171110.

Gregor, S., & Hevner, A. R. (2013). Positioning and Presenting Design Science Research for Maximum Impact. MIS Quarterly, 37 (2), 337–355. https://doi.org/10.25300/MISQ/2013/37.2.01.

Guest, G., Bunce, A., & Johnson, L. (2006). How Many Interviews Are Enough?: An Experiment with Data Saturation and Variability. Field Methods, 18(1), 59–82. https://doi.org/10.1177/1525822X05279903.

Jais, R., Ngah, AH. (2024). The moderating role of government support in chatbot adoption intentions among Malaysian government agencies. Transforming Government: People, Process and Policy, 18(3), 417–433. https://doi.org/10.1108/TG-02-2023-0026.

Jarrahi, M.H. et al. (2022). Artificial intelligence: a strategy to harness its power through organizational learning. Journal of Business Strategy, 44(3), pp. 126–135. https://doi.org/10.1108/jbs-11-2021-0182.

Jennex, M.E. and Olfman, L. (2004). Modeling Knowledge Management Success. Conference on Information Science and Technology Management, CISTM.

Kumar, A., & Singh, R. (2020). Software Testing: Principles and Practices. Pearson.

Laihonen, H., Kork, A. A., & Sinervo, L. M. (2023). Advancing public sector knowledge management: towards an understanding of knowledge formation in public administration. Knowledge Management Research & Practice, 22(3), 223–233. https://doi.org/10.1080/14778238.2023.2187719.

Lam, L., Nguyen, P., Le, N., & Tran, K. (2021). The Relation among Organizational Culture, Knowledge Management, and Innovation Capability; Its Implication for Open Innovation. Journal of Open Innovation: Technology, Market, and Complexity, 7, 66. https://doi.org/10.3390/joitmc7010066.

Lewis, P., Perez, E., Piktus, A., Petroni, F., Karpukhin, V., Goyal, N., Küttler, H., Lewis, M., Yih, W., Rocktäschel, T., Riedel, S. and Kiela, D. (2020). Retrieval-augmented generation for knowledge-intensive NLP tasks. In: Proceedings of the 34th international conference on neural information processing systems, Curran, Red Hook, NIPS ’20, 9459–9474. https://doi.org/10.5555/3495724.3496517.

Miles, M. B., & Huberman, A. M. (1994). Qualitative Data Analysis: An Expanded Sourcebook. 2nd ed. Sage Publications.

Moghadam, M. R., & Sadeghi, H. (2022). The impact of AI-based chatbots on knowledge management in organizations. Journal of Artificial Intelligence Research, 45(4), 789–812.

Moleong, Lexy. (2021). Metodologi Penelitian Kualitatif. PT Remaja Rosdakarya.

Nonaka, I., & Takeuchi, H. (1995). The knowledge-creating company: How Japanese companies create the dynamics of innovation. Oxford University Press: New York, NY.

Patton, M. Q. (2015). Qualitative Research & Evaluation Methods: Integrating Theory and Practice (4th ed.). SAGE Publications.

Peffers, K., Tuunanen, T., Rothenberger, M. A., & Chatterjee, S. (2007). A design science research methodology for information systems research. Journal of Management Information Systems, 24(3), 45-77. https://doi.org/10.2753/MIS0742-1222240302.

PT SMI. (2025). Mendorong pertumbuhan berkelanjutan lewat pembiayaan infrastruktur. Diakses 7 Maret 2025, dari https://www.ptsmi.co.id/mendorong-pertumbuhan-berkelanjutan-lewat-pembiayaan-infrastruktur

Purandare, S. V., & Patil, R. D. (2023). Open ended questionnaire for qualitative research. Journal of Advanced Multidisciplinary Research Studies and Development, 2(2).

Rapley, T. J. (2001). The art(fulness) of open-ended interviewing: Some considerations on analysing interviews. Qualitative Research, 1(3), 303–323. https://doi.org/10.1177/146879410100100303.

Ritala, P., Ruokonen, M. and Ramaul, L. (2024). Transforming boundaries: how does ChatGPT change knowledge work?. Journal of Business Strategy, 45(3), 214-220. https://doi.org/10.1108/jbs-05-2023-0094.

Satzinger, J. W., Jackson, R. B., & Burd, S. D. (2019). Systems analysis and design in a changing world (7th ed.). Cengage Learning.

Saunders, M. N. K., Lewis, P., & Thornhill, A. (2015). Research Methods for Business Students (7th ed.). Essex, England: Pearson Education Limited.

Sekaran, U. and Bougie, R. (2016). Research Methods for Business: A Skill-Building Approach. 7th Edition. Wiley & Sons, West Sussex.

Sitalaksmi, S., Indarti, N., Anggadwita, G., & Sambudi, A. D. (2024). Knowledge leakage and collaborative innovation: a systematic literature review. Knowledge Management Research & Practice, 23(6), 732–748. https://doi.org/10.1080/14778238.2024.2431111.

Sugiyono. (2020). Metode penelitian kuantitatif, kualitatif dan R&D (2nd ed.). CV Alfabeta.

Sundaresan, S., & Zhang, Z. (2021). AI-enabled knowledge sharing and learning: Redesigning roles and processes. The International Journal of Organizational Analysis, 30(4), 983–999. https://doi.org/10.1108/IJOA-12-2020-2558.

Susanty, A. I., Yuningsih, Y., & Anggadwita, G. (2019). Knowledge management practices and innovation performance: A study at Indonesian Government apparatus research and training center. Journal of Science and Technology Policy Management, 10(2), 301–318. https://doi.org/10.1108/JSTPM-03-2018-0030.

Taherdoost, H., & Madanchian, M. (2023). Artificial intelligence and knowledge management: Impacts, benefits, and implementation. Computers, 12(4), 72. https://doi.org/10.3390/computers12040072.

Tornatzky, L. G., & Fleischer, M. (1990). The processes of technological innovation. Lexington Books.

Virzi, R. A. (1992). Refining the Test Phase of Usability Evaluation: How Many Subjects Is Enough? Human Factors: The Journal of the Human Factors and Ergonomics Society, 34(4), 457-468. https://doi.org/ 10.1177/001872089203400407.

Wang, M., & Yang, T. (2016). Investigating the success of knowledge management: An empirical study of small- and medium-sized enterprises. Asia Pacific Management Review, 21(2), 79–91. https://doi.org/10.1016/j.apmrv.2015.12.003.

Yin, R. K. (2014). Case study research: Design and methods (5th ed.). Sage.

Zhang, Y., & Sun, A. (2020). A Survey on Retrieval-Augmented Generation Models for Text Generation. ACM Computing Surveys, 53(6), 1-35. https://doi.org/10.1145/3414686.

Zhao, L., Wang, Y., & Li, X. (2023). Enhancing knowledge management through chatbot integration: A study on decision-making processes. Information Systems Frontiers, 25(3), 765–780. https://doi.org/10.1007/s10796-022-10279-0.

Downloads

Published

2026-02-02

Issue

Vol. 13 No. 1 (2026): March

Section

Articles

License

Copyright (c) 2025 Jurnal Manajemen Bisnis

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

From Walking Libraries to Answer Engines: Optimizing Knowledge Internalization in Public Financing with RAG-Based AI Chatbots. (2026). Jurnal Manajemen Bisnis, 13(1), 189-207. https://doi.org/10.33096/jmb.v13i1.1366