This paper developed a new framework for better knowledge management through computational simulations, enabling both human knowledge creation and updating simulation models. The framework was developed based on the concepts of the socialization, externalization, combination, and internalization (SECI) model, and it contains a structured workshop that includes the four types of Ba the model requires. To evaluate this framework, the planning of post-disaster restoration of water distribution networks was employed as a case study. In addition, a new optimization method was developed using empirical heuristics obtained from practitioners, aiming for meaningful feedback from the practitioners working in a water management company. Based on our simulation, three workshops were conducted to create new knowledge, and new features were added to the simulation. In these workshops, practitioners performed simulation-based training in planning the restoration and then discussed their decisions. Afterward, it was concluded that the proposed framework was sufficient for updating the simulation. However, it required additional methods to provide practitioners with opportunities to obtain new insights.

1. [1] Y. Kawata, “The Great Hanshin-Awaji Earthquake Disaster: Damage, social response, and recovery,” J. Nat. Disaster Sci., Vol.17, No.2, pp. 1-12, 1995.
2. [2] N. Nojima, “Restoration processes of utility lifelines in the Great East Japan Earthquake Disaster, 2011,” 15th World Conf. on Earthquake Engineering (WCEE), 2012.
3. [3] Japanese Ministry of Health, Labour Standards (in Japanese). https://www.mhlw.go.jp/content/10601000/000476640.pdf [Accessed August 18, 2022]
4. [4] I. Nonaka and H. Takeuchi, “The knowledge-creating company: How Japanese companies create the dynamics of innovation,” Oxford University Press, 1995.
5. [5] I. Nonaka and N. Konno, “The concept of ‘Ba’: Building a foundation for knowledge creation,” Calif. Manag. Rev., Vol.40, No.3, pp. 40-54, 1998.
6. [6] I. Nonaka, R. Toyama, and N. Konno, “SECI, Ba, and leadership: A unified model of dynamic knowledge creation,” Long Range Plan., Vol.33, No.1, pp. 5-34, 2000.
7. [7] P. Canonico, E. De Nito, V. Esposito, M. P. Iacono, and S. Consiglio, “Knowledge creation in the automotive industry: Analysing obeya-oriented practices using the SECI model,” J. Bus. Res., Vol.112, pp. 450-457, 2020.
8. [8] W. C. Salmon, “Causality and explanation,” Oxford University Press, 1998.
9. [9] S. Nakamura, K. Furuta, T. Kanno, S. Yoshihara, and T. Mase, “Multi-agent simulation of ground aircraft operations at a large airport,” Proc. of the 3rd Int. ICST Conf. on Simulation Tools and Techniques (SIMUTools’10), 28, 2010.
10. [10] P. M. Gollwitzer, “Implementation intentions: Strong effects of simple plans,” Am. Psychol., Vol.54, No.7, pp. 493-503, 1999.
11. [11] S. Sela-Smith, “Heuristic research: A review and critique of Moustakas’s method,” J. Humanist. Psychol., Vol.42, No.3, pp. 53-88, 2002.
12. [12] W. Liu and Z. Song, “Post-earthquake restoration of water distribution network: A resilience framework,” 13th Int. Conf. on Applications of Statistics and Probability in Civil Engineering (ICASP13), 2019.
13. [13] Z. Han, D. Ma, B. Hou, and W. Wang, “Seismic resilience enhancement of urban water distribution system using restoration priority of pipeline damages,” Sustainability, Vol.12, No.3, 914, 2020.
14. [14] T. Kanno, S. Koike, T. Suzuki, and K. Furuta, “Human-centered modeling framework of multiple interdependency in urban systems for simulation of post-disaster recovery processes,” Cogn. Technol. Work, Vol.21, No.2, pp. 301-316, 2019.
15. [15] K. Wakayama, T. Kanno, Y. Kawase, H. Takahashi, and K. Furuta, “Comparison of the post-disaster recovery of water supply system by GA optimization and heuristics,” Proc. of the 30th European Safety and Reliability Conf. and the 15th Probabilistic Safety Assessment and Management Conf., 2020. https://doi.org/10.3850/978-981-14-8593-0_3862-cd
16. [16] Japan Water Works Association, “Damage prediction of water supply pipeline by earthquake,” 1998 (in Japanese).
17. [17] H. Sugimoto, T. Tamura, M. Arimura, and K. Saito, “The restoration model of the damaged road network based on the cooperation of the improvement teams,” Doboku Gakkai Ronbunshu, Vol.1999, No.625, pp. 135-148, 1999 (in Japanese).
18. [18] H. Furuta, K. Nakatsu, and Y. Nomura, “Optimal restoration scheduling of damaged networks in uncertain environment,” Doboku Gakkai Ronbunshuu A, Vol.64, No.2, pp. 434-445, 2008.
19. [19] Fire and Disaster Management Agency, 2018 (in Japanese). https://www.fdma.go.jp/pressrelease/houdou/items/h20/200428/200428-3houdou4.pdf [Accessed September 9, 2022]