Skip to main content
SpringerLink
Log in

Behavior in Models: A Framework for Representing Human Behavior

  • Chapter
  • First Online:
Behavioral Operational Research

Abstract

This chapter will discuss the challenge of modelling human behavior in a simulation model. A framework is presented of the options available by level of modelling abstraction. At the highest level of abstraction the need to model human behavior is eliminated by simplification. Another approach that avoids the need to incorporate human behavior in the model is to externalize the human aspect through strategies such as representing the behavior as inputs to the model. If human behavior is to be modelled then the options presented are flow, entity, task and individual. These approaches require increasing detail and become increasingly complex. For instance, at the individual level there is a need to consider the many and complex cognitive models of human behavior.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution

Institutional subscriptions

References

  • Ajzen, A. 1991. The theory of planned behavior. Organizational Behavior and Human Decision Processes 50: 179–211.

    Article  Google Scholar 

  • Anderson, J.R., and C. Lebiere. 1998. The atomic components of thought. Mahwah: Erlbaum.

    Google Scholar 

  • Baines, T., S. Mason, P. Siebers, and J. Ladbrook. 2004. Humans: The missing link in manufacturing simulation? Simulation Modeling Practice and Theory 12: 515–526.

    Article  Google Scholar 

  • Baines, T., R. Asch, L. Hadfield, J.P. Mason, S. Fletcher, and J.M. Kay. 2005. Towards a theoretical framework for human performance modelling within manufacturing systems design. Simulation Modelling Practice and Theory 13: 486–504.

    Article  Google Scholar 

  • Benedettini, O., T. Baines, and J. Ladbrook. 2006. Human performance modelling within manufacturing systems design: From theory to practice. Proceedings of the 2006 OR Society Simulation Workshop.

    Google Scholar 

  • Bernhard, W., and A. Schilling. 1997. Simulation of group work processes in manufacturing. Proceedings of the 1997 Winter Simulation Conference, IEEE Computer Society.

    Google Scholar 

  • Brailsford, S.C. 2014. Discrete-event simulation is alive and kicking! Journal of Simulation 8(1): 1–8.

    Google Scholar 

  • Brailsford, S., and B. Schmidt. 2003. Towards incorporating human behavior in models of health care systems: An approach using discrete-event simulation. European Journal of Operational Research 150: 19–31.

    Article  Google Scholar 

  • Cavana, R.Y., P.K. Davies, R.M. Robson, and K.J. Wilson. 1999. Drivers of quality in health services: Different worldviews of clinicians and policy managers revealed. System Dynamics Review 15: 331–340.

    Article  Google Scholar 

  • Croson, R., K. Schultz, E. Siemsen, and M.L. Yeo. 2013. Behavioural operations: The state of the field. Journal of Operations Management 31: 1–5.

    Article  Google Scholar 

  • Elkosantini, S. 2015. Towards a new generic behavior model for human centered system simulation. Simulation Modelling Practice and Theory 52: 108–122.

    Article  Google Scholar 

  • Elliman, T., J. Eatock, and N. Spencer. 2005. Modelling knowledge worker behavior in business process studies. The Journal of Enterprise Information Management 18: 79–94.

    Article  Google Scholar 

  • Forrester, J. 1961. Industrial dynamics. Cambridge, MA: Productivity Press.

    Google Scholar 

  • Greasley, A., and S. Barlow. 1998. Using simulation modelling for BPR: Resource allocation in a police custody process. International Journal of Operations and Production Management 18: 978–988.

    Article  Google Scholar 

  • Greasley, A., and C. Owen. 2015. Implementing an agent-based model with a spatial visual display in discrete-event simulation software. Proceedings of the 5th International Conference on Simulation and Modeling Methodologies, Technologies and Applications (SIMULTECH 2015), Colmar.

    Google Scholar 

  • Hanisch, A., J. Tolujew, K. Richter, and T. Schulze. 2003. Online simulation of pedestrian flow in public buildings. Proceedings of the 2003 Winter Simulation Conference, SCS, New Orleans, pp. 1635–1641.

    Google Scholar 

  • Hayes, C.C. 1999. Agents in a nutshell—A very brief introduction. IEEE Transactions on Knowledge and Data Engineering 11: 127–132.

    Article  Google Scholar 

  • Ilar, T.B.E. 2008. Proceedings of the 40th Conference on Winter Simulation. Winter Simulation Conference, pp. 903–908.

    Google Scholar 

  • Johnson, R.T., J.W. Fowler, and G.T. Mackulak. 2005. A discrete event simulation model simplification technique. Proceedings of the 2005 Winter Simulation Conference, SCS, pp. 2172–2176.

    Google Scholar 

  • Joo, J., N. Kim, R.A. Wysk, L. Rothrock, Y.-J. Son, Y. Oh, and S. Lee. 2013. Agent-based simulation of affordance-based human behaviors in emergency evacuation. Simulation Modelling Practice and Theory 32: 99–115.

    Article  Google Scholar 

  • Keller, J. 2002. Human performance modelling for discrete-event simulation: Workload. Proceedings of the 2002 Winter Simulation Conference, pp. 157–162.

    Google Scholar 

  • Khanna, V.K., P. Vat, R. Shanker, B.S. Sahay, and A. Gautam. 2003. TQM modeling of the automobile manufacturing sector: A system dynamics approach. Work Study 52: 94–101.

    Article  Google Scholar 

  • Lam, R.B. 2007. Agent-based simulations of service policy decisions. Proceedings of the 2007 Winter Simulation Conference, SCS, pp. 2241–2246.

    Google Scholar 

  • Macal, C.M., and M.J. North. 2006. Tutorial on agent-based modeling and simulation part 2: How to model with agents. Proceedings of the 2006 Winter Simulation Conference, SCS, pp. 73–83.

    Google Scholar 

  • Neuman, W.P., and P. Medbo. 2009. Integrating human factors into discrete event simulations of parallel flow strategies. Production Planning and Control 20: 3–16.

    Article  Google Scholar 

  • Newell, A. 1990. Unified theories of cognition. Cambridge, MA: Harvard University Press.

    Google Scholar 

  • Pegden, C.D., R.E. Shannon, and R.P. Sadowski. 1995. Introduction to simulation using SIMAN, 2nd ed. New York: McGraw-Hill.

    Google Scholar 

  • Pew, R.W. 2008. More than 50 years of history and accomplishments in human performance model development. Human Factors 50: 489–496.

    Article  Google Scholar 

  • Pidd, M. 2003. Tools for thinking: Modelling in management science, 2nd ed. Hoboken: Wiley.

    Google Scholar 

  • Prichett, A.R., S.M. Lee, and D. Goldsman. 2001. Hybrid-system simulation for national airspace safety systems analysis. AIAA Journal of Aircraft 38: 835–840.

    Article  Google Scholar 

  • Robinson, S. 2015. Modelling without queues: Adapting discrete-event simulation for service operations. Journal of Simulation 9: 195–205.

    Article  Google Scholar 

  • Robinson, S., J.S. Edwards, and W. Yongfa. 2003. Linking the witness simulation software to an expert system to represent a decision-making process. Journal of Computing and Information Technology 11: 123–133.

    Article  Google Scholar 

  • Robinson, S., T. Alifantis, J.S. Edwards, J. Ladbrook, and T. Waller. 2005. Knowledge based improvement: Simulation and artificial intelligence for identifying and improving human decision-making in an operations system. Journal of the Operational Research Society 56: 912–921.

    Article  Google Scholar 

  • Schmidt, B. 2000. The modelling of human behavior. Erlangen: SCS Publications.

    Google Scholar 

  • Schmidt, B. 2005. Human factors in complex systems: The modeling of human behavior. Proceedings 19th European Conference of Modelling and Simulation, ECMS.

    Google Scholar 

  • Shaw, A.P., and R. Pritchett. 2005. Agent-based modeling and simulation of socio-technical systems. In Organizational simulation, ed. W.B. Rouse and K.R. Boff. New Jersey: Wiley.

    Google Scholar 

  • Siebers, P., U. Aickelin, H. Celia, and C.W. Clegg. 2007. Using intelligent agents to understand management practices and retail productivity. Proceedings of the 2007 Winter Simulation Conference, SCS, pp. 2212–2220.

    Google Scholar 

  • Siebers, P.O., C.M. Macal, J. Garnett, D. Buxton, and M. Pidd. 2010. Discrete-event simulation is dead, long live agent-based simulation! Journal of Simulation 4: 204–210.

    Article  Google Scholar 

  • Silverman, B.G. 1991. Expert critics: Operationalising the judgement/decision making literature as a theory of “bugs” and repair strategies. Knowledge Acquisition 3: 175–214.

    Article  Google Scholar 

  • Silverman, B.G. 2004. Toward realism in human performance simulation. In The science and simulation of human performance, ed. J.W. Ness, V. Tepe, and D.R. Rizer. Oxford: Elsevier.

    Google Scholar 

  • Stahl, I. 1995. New product development: When discrete simulation is preferable to system dynamics. Proceedings of the 1995 EUROSIM Conference, Elsevier Science B.V.

    Google Scholar 

  • Sterman, J.D., N.P. Repenning, and F. Kofman. 1997. Unanticipated side effects of successful quality programs: Exploring a paradox of organizational improvement. Management Science 43: 503–521.

    Article  Google Scholar 

  • Warren, R., D.E. Diller, A. Leung, and W. Ferguson. 2005. Simulating scenarios for research on culture and cognition using a commercial role-play game. Proceedings of the 2005 Winter Simulation Conference, SCS, pp. 1109–1117.

    Google Scholar 

  • Wickens, C.D. 1984. Engineering psychology and human performance. New York: HarperCollins Publishers.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Aston Business School, Aston University, Aston Triangle, Birmingham, B4 7ET, UK

    Andrew Greasley & Chris Owen

Authors
  1. Andrew Greasley
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Chris Owen
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Warwick Business School, University of Warwick, Coventry, UK

    Martin Kunc

  2. BT Technology Service & Operations, Martlesham Heath, UK

    Jonathan Malpass

  3. Warwick Business School, University of Warwick, Coventry, UK

    Leroy White

Copyright information

© 2016 The Author(s)

About this chapter

Cite this chapter

Greasley, A., Owen, C. (2016). Behavior in Models: A Framework for Representing Human Behavior. In: Kunc, M., Malpass, J., White, L. (eds) Behavioral Operational Research. Palgrave Macmillan, London. https://doi.org/10.1057/978-1-137-53551-1_3

Download citation

Publish with us

Policies and ethics

Search

Navigation