Cognition, Technology & Work

, Volume 21, Issue 2, pp 301–316 | Cite as

Human-centered modeling framework of multiple interdependency in urban systems for simulation of post-disaster recovery processes

  • T. KannoEmail author
  • S. Koike
  • T. Suzuki
  • K. Furuta
Original Article


This paper presents a human-centered modeling framework of urban systems to capture various types of interdependency underlying urban sociotechnical and socioeconomic systems. The proposed framework consists of three major subsystems: civil life, manufacturing/service industry, and lifeline infrastructure. This framework classifies nine different types of interdependencies existing within and between these three subsystems. This paper also presents a computer simulation of the post-disaster recovery process of urban systems considering various interdependencies captured by the modeling framework. We adopt an agent-based model incorporating a network model for implementing the three subsystems as well as the various types of interdependencies. A sensitivity analysis was conducted based on the R4 framework of disaster resilience to verify and validate the simulation model. The simulation results were generally consistent with the predictions made by the R4 framework, suggesting that the model was implemented properly and can capture the multiple interdependencies behind the urban systems.


Disaster resilience Critical infrastructure Interdependency Agent-based model Network model 



This study was partly supported by Research Institute of Science and Technology for Society (RISTEX), Japan Science and Technology Agency (JST).

Compliance with ethical standards

Human and/or animals rights

This study is not involving human participants and/or animals.

Conflict of interest

The authors declare that they have no conflict of interest.


  1. Albara-Bertrand JM (2013) Disasters and Networked Economy, 2013. Routledge, OxonCrossRefGoogle Scholar
  2. Amantini A, Choras M, D’Antonio A, Egozcue E, Germanus D, Hutter R (2012) The human role in tools for improving robustness and resilience of critical infrastructures. Cognit Technol Work 14:143–155CrossRefGoogle Scholar
  3. Bruneau M, Chang SE, Eguchi RT, Lee GC, O’Rourke TD, Reinhorm AM, Shinozuka M, Tierney K, Wallace WA, von Winterfeld D (2003) A framework to quantitatively assess and enhance the seismic resilience of communities. Earthq Spectra 19(4):737–738CrossRefGoogle Scholar
  4. Central Disaster Prevention Council (2013) Disaster preparedness for Nankai trough earthquake. Accessed 26 July 2018 (in Japanese)
  5. Dundenhoeffer DD, Permann MR, Boring RL, 2006, Decision consequence in complex environments: visualizing decision impact. In: Proc. Decision Consequence in Complex Environments, pp 211–218Google Scholar
  6. Enjalbert S, Vanderhaegen F (2017) A hybrid reinforced learning system to estimate resilience indicators. Eng Appl Artif Intell 64:295–301CrossRefGoogle Scholar
  7. Folke C (2006) Resilience: the emergence of a perspective for social-ecological systems analyses. Glob Environ Change 16:253–267CrossRefGoogle Scholar
  8. Furuta K, Kanno T, 2013, Issues in service system resilience. In: Proc. 43rd Annual IEEE/IFIP Conf. Dependable Systems and Networks WorkshopGoogle Scholar
  9. Furuta H, Nakatsu K, Nomura Y (2005) Optimal restoration scheduling of damaged networks in uncertain environment. Doboku Gakkai Ronbunshuu A 64(2):434–445CrossRefGoogle Scholar
  10. Guidotti R, Chmielewski H, Unnikrishnan V, Gardoni P, McAllister T, de Lindt J (2016) Modeling the resilience of critical infrastructure: the role of network dependencies. Sustain Resil Infrastruct 1(3–4):153–168CrossRefGoogle Scholar
  11. Hasan S, Foliente G (2015) Modeling infrastructure system interdependencies and socioeconomic impacts of failure in extreme events: emerging R&D challenges. Nat Hazards 78(3):2143–2168CrossRefGoogle Scholar
  12. Hayashi H, Kameda H, Nojima N (1994) Troubles people have to suffer when lifelines fail to function after earthquake. In: Proceedings from the Fifth US-Japan Workshop on earthquake resistant design of lifeline facilities and countermeasures against soil liquefaction, pp 593–599Google Scholar
  13. Holling C (1973) Resilience and stability of ecological systems. Annu Rev Ecol Syst 4:1–23CrossRefGoogle Scholar
  14. Hollnagel E (2011) RAG—the resilience analysis grid. In: Hollnagel E, Pariès J, Woods DD, Wreathall J (eds) Resilience engineering in practice. A Guidebook. Ashgate, Surrey, EnglandGoogle Scholar
  15. Hollnagel D, Woods DD, Leveson N (2006) Resilience engineering, concepts and precepts. Ashgate, Hampshire, EnglandGoogle Scholar
  16. Hollnagel E, Nemeth CP, Dekker S (2008) Resilience engineering perspectives. Ashgate, Hampshire, EnglandGoogle Scholar
  17. Johansen C, Tien I (2018) Probabilistic multi-scale modeling of interdependencies between critical infrastructure systems for resilience. Sustain Resil Infrastruct 3(1):1–15CrossRefGoogle Scholar
  18. Johnson J, Wood AM (2017) Integrating positive and clinical psychology: viewing human functioning as continua from positive to negative can benefit clinical assessment. Interv Underst Resil 41:335–349Google Scholar
  19. Jovanovic AS, Schmid N, Klimek P (2016) Use of indicators for assessing resilience of smart critical infrastructures. In: Linkov I, Florin MV (eds) IRGC resource guide on resilience. IRGC, LausanneGoogle Scholar
  20. Kanno T, Suzuki T, Yoshida Y, Furuta K, 2016, Simulation of post-disaster recovery for building a resilient Tokyo. In: Proc. 6th. Int’l Conf. Building Resilience, Paper No.14Google Scholar
  21. Kasthurirangan G, Srinivas P (eds) (2010) Sustainable and resilient critical infrastructure systems. Springer, Berlin, HeidelbergGoogle Scholar
  22. Kito T, Ueda K (2014) The Implications of automobile parts supply network structures: a complex network approach. CIRP Ann Manuf Technol 63(1):393–396CrossRefGoogle Scholar
  23. Krackhardt D, Carley KM (1998) A PCANS model of structure in organizations. In: Proc. Int’l Symp. Command and control research and technology, pp 113–119Google Scholar
  24. Maslow A (1954) Motivation and personality. Harper & Brothers, New YorkGoogle Scholar
  25. Multidisciplinary Center for Earthquake Engineering Research (2018) Accessed 14 June 2018
  26. National Academies (2012) Disaster resilience. National Academies Press, Washington DCGoogle Scholar
  27. Okuyama Y, Santos JR (2014) Disaster impact and input-output analysis. Econ Syst Res 26(1):1–12CrossRefGoogle Scholar
  28. Ouderaogo KA, Enjalbert S, Vanderhaegen F (2013) How to learn from the resilience of human-machine systems? Eng Appl Artif Intell 26:24–34CrossRefGoogle Scholar
  29. Ouyang M (2014) Review on modeling and simulation of interdependent critical infrastructure system. Reliab Eng Syst Saf 121:43–60CrossRefGoogle Scholar
  30. Patriarca R, Bergstrom J, Gravio GD, Costantino F (2018) Resilience engineering: current status of the research and future challenges. Saf Sci 102:79–100CrossRefGoogle Scholar
  31. Putnik GD, Skulj G, Vrabic R, Varela L, Butala P (2015) Simulation study of large production network robustness in uncertain environment. CIRP Ann Manuf Technol 64(1):439–442CrossRefGoogle Scholar
  32. Regt A, Siegel AW, Schraagen JM (2016) Toward quantifying metrics for rail-system resilience: identification and analysis of performance weak resilience signals. Cognit Technol Work 18:319–331CrossRefGoogle Scholar
  33. Reiner M, McElvaney K (2017) Foundational infrastructure framework for city resilience. Sustain Resil Infrastruct 2(1–7):1–7Google Scholar
  34. Resilience (2018) The Oxford English Dictionary (OED Online). Accessed 20 June 2018
  35. Rigi AW, Saurin TA, Wachs P (2015) A systematic literature review of resilience engineering: research areas and a research agenda proposal. Reliab Eng Syst Saf 141:142–152CrossRefGoogle Scholar
  36. Rinaldi SM, Peerenboom JP, Kelly TK (2001) Identifying, understanding, and analyzing critical infrastructure interdependencies. IEEE Control Syst Mag 21(6):11–25CrossRefGoogle Scholar
  37. Rouse WB (2003) Engineering complex systems: implications for research in systems engineering. IEEE Trans Syst Man Cybernet Part C Appl Rev 33(2):183–196CrossRefGoogle Scholar
  38. Rouse WB (2015) Modeling and visualization of complex systems and enterprises: explorations of physical, human, economic, and social phenomena. Wiley, Hoboken, New JerseyzbMATHCrossRefGoogle Scholar
  39. Shirali GA, Motamedzade M, Mohammadfam I, Ebrahimipour V (2016) Assessment of resilience engineering factors based on system properties in a process industry. Cognit Technol Work 18:19–31CrossRefGoogle Scholar
  40. Sugimoto H, Tamura T, Arimura K, Saito K (1999) The restoration model of the damaged road network based on the cooperation of the improvement teams. Doboku Gakkai Ronbunshuu 625(IV–44):135–148CrossRefGoogle Scholar
  41. Tang L, Jing K, He J, Stanley HE (2016) Complex interdependent supply chain networks: cascading failure and robustness. Phys A 443:58–69MathSciNetzbMATHCrossRefGoogle Scholar
  42. Tierney K, Bruneau M (2007) Conceptualizing and measuring resilience: a key to disaster loss reduction. TR News 250:14–15Google Scholar
  43. Togawa T, Mimuro A, Kato H, Hayashi Y, Nishino S, Takano T, 2011, Evaluation post-disaster reconstruction and improvement management from QOL standards in disasters In: Proc. Joint Intl Symp. On social management systems, pp 362–369Google Scholar
  44. Wei D, Ji K (2010) Resilient industrial control system (RICS): concepts, formulation, metrics and insights. In: Proc. Int’l Symp. on Resilient Control Systems, pp 15–22Google Scholar
  45. Zhang W, Wang N, Nicholson C (2017) Resilience-based post-disaster recovery strategies for road-bridge networks. Struct Infrastruct Eng 13(11):1404–1413CrossRefGoogle Scholar
  46. Zio E (2016) Challenges in the vulnerability and risk analyses of critical infrastructures. Reliab Eng Syst Saf 152:137–150CrossRefGoogle Scholar

Copyright information

© Springer-Verlag London Ltd., part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of Systems Innovation, School of EngineeringThe University of TokyoTokyoJapan
  2. 2.Resilience Engineering Research Center, School of EngineeringThe University of TokyoTokyoJapan

Personalised recommendations