A Model based Realisation of Actor Model to Conceptualise an Aid for Complex Dynamic Decision-making

Souvik Barat, Vinay Kulkarni, Tony Clark, Balbir Barn

2017

Abstract

Effective decision-making of modern organisation requires deep understanding of various aspects of organisation such as its goals, structure, business-as-usual operational processes etc. The large size and complex structure of organisations, socio-technical characteristics, and fast business dynamics make this decision-making a challenging endeavour. The state-of-practice of decision-making that relies heavily on human experts is often reported as ineffective, imprecise and lacking in agility. This paper evaluates a set of candidate technologies and makes a case for using actor based simulation techniques as an aid for complex dynamic decision-making. The approach is justified by enumeration of basic requirements of complex dynamic decision-making and the conducting a suitability of analysis of state-of-the-art enterprise modelling techniques. The research contributes a conceptual meta-model that represents necessary aspects of organisation for complex dynamic decision-making together with a realisation in terms of a meta model that extends Actor model of computation. The proposed approach is illustrated using a real life case study from business process outsourcing industry.

References

  1. Agha, G.A., 1985. Actors: A model of concurrent computation in distributed systems. Tech. rep., DTIC Document.
  2. Allen, J., 2013. Effective akka. O'Reilly Media, Inc.
  3. Armstrong, J., 1996. Erlang - a survey of the language and its industrial applications. In: Proc. INAP. vol. 96.
  4. Astley, M., 1998. The actor foundry: A java-based actor programming environment. University of Illinois at Urbana-Champaign: Open Systems Laboratory.
  5. Barat, S., Kulkarni, V., Clark, T., Barn, B., 2016a: Enterprise Modeling as a Decision Making Aid: A Systematic Mapping Study. PoEM 2016: 289-298.
  6. Barat, S., Kulkarni, V., Clark, T., Barn, B., 2016b: A Simulation-based Aid for Organisational Decisionmaking. ICSOFT-PT 2016: 109-116.
  7. Borshchev, A., 2013. The big book of simulation modeling: multimethod modeling with AnyLogic 6. AnyLogic North America Chicago.
  8. Camus, B., Bourjot, C., Chevrier, V., 2015. Combining devs with multi-agent concepts to design and simulate multi-models of complex systems. In: Proceedings of the Symposium on Theory of Modeling & Simulation: DEVS Integrative M&S Symposium. pp. 85-90.
  9. Conrath, D.W., 1967. Organizational decision making behavior under varying conditions of uncertainty. Management Science 13(8), B-487.
  10. Cyert, R.M., March, J.G., et al., 1963. A behavioral theory of the firm. Englewood Cliffs, NJ 2).
  11. Daft, R., 2012. Organization theory and design. Nelson Education.
  12. Haller, P., Odersky, M., 2009. Scala actors: Unifying thread-based and event-based programming. Theoretical Computer Science 410(2), 202-220.
  13. Hewitt, C., 2010. Actor model of computation: scalable robust information systems. arXiv:1008.1459.
  14. Iacob, M., Jonkers, D.H., Lankhorst, M., Proper, E., Quartel, D.D., 2012. Archimate 2.0 specification: The open group, Van Haren Publishing.
  15. Kahneman, D., Lovallo, D., Sibony, O., 2011. Before you make that big decision. Harvard business review 89(6).
  16. Kulkarni, V., Barat, S., Clark, T., Barn, B., 2015a: A WideSpectrum Approach to Modelling and Analysis of Organisation for Machine-Assisted Decision-Making. EOMAS@CAiSE 2015: 87-101.
  17. Kulkarni, V., Barat, S., Clark, T., Barn, B., 2015b: Toward overcoming accidental complexity in organisational decision-making. MoDELS 2015: 368-377.
  18. Kulkarni, V., Barat, S., Clark, T., Barn, B., 2015c: Using simulation to address intrinsic complexity in multimodelling of enterprises for decision making. SummerSim 2015: 9:1-9:11.
  19. Locke, E., 2011. Handbook of principles of organizational behavior: Indispensable knowledge for evidence-based management. John Wiley & Sons.
  20. McDermott, T., Rouse, W., Goodman, S., Loper, M., 2013. Multi-level modeling of complex socio-technical systems. Procedia Computer Science 16, 1132-1141.
  21. Meadows, D.H., Wright, D., 2008. Thinking in systems: A primer. Chelsea Green Publishing.
  22. Meissner, P., Sibony, O., Wulf, T., 2016. Are you ready to decide? McKinsey Quarterly, April. 2016.
  23. Mintzberg, H., Raisinghani, D., Theoret, A., 1976. The structure of unstructured decision processes. Administrative science quarterly pp. 246-275.
  24. OMG., 2011. Business Process Model and Notation (BPMN), Version 2.0 (January 2011).
  25. Petersen, K., Feldt, R., Mujtaba, S., Mattsson, M., 2008. Systematic mapping studies in software engineering. In: 12th international conference on evaluation and assessment in software engineering. vol. 17, pp. 1-10.
  26. Shapira, Z., 2002. Organizational decision making. Cambridge University Press.
  27. Siebert, J., Ciarletta, L., Chevrier, V., 2010. Agents and artefacts for multiple models co-evolution: building complex system simulation as a set of interacting models. In: 9th International Conference on Autonomous Agents and Multiagent Systems: 509-516.
  28. Sipp, C.M., Elias, C., 2012. Real Options and Strategic Technology Venturing: A New Paradigm in Decision Making, vol. 31. Springer Science & Business Media.
  29. Srinivasan, S., Mycroft, A., 2008. Kilim: Isolation-typed actors for java. In: European Conference on ObjectOriented Programming. pp. 104-128.
  30. Varela, C., Agha, G., 2001 Programming dynamically reconfigurable open systems with salsa. ACM SIGPLAN Notices 36(12), 20-34.
  31. Van Cutsem, T., Mostinckx, S., Boix, E.G., Dedecker, J., De Meuter, W., 2007. Ambienttalk: object-oriented event-driven programming in mobile ad hoc networks. In: Chilean Society of Computer Science, XXVI International Conference of the. pp. 3-12.
  32. Yu, E., Strohmaier, M., Deng, X., 2006. Exploring intentional modeling and analysis for enterprise architecture. 10th IEEE International Enterprise Distributed Object Computing Conference Workshops.
  33. Zachman, J., et al., 1987. A framework for information systems architecture. IBM systems journal 26(3), 276- 292.
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Paper Citation


in Harvard Style

Barat S., Kulkarni V., Clark T. and Barn B. (2017). A Model based Realisation of Actor Model to Conceptualise an Aid for Complex Dynamic Decision-making . In Proceedings of the 5th International Conference on Model-Driven Engineering and Software Development - Volume 1: IndTrackMODELSWARD, (MODELSWARD 2017) ISBN 978-989-758-210-3, pages 605-616. DOI: 10.5220/0006216306050616


in Bibtex Style

@conference{indtrackmodelsward17,
author={Souvik Barat and Vinay Kulkarni and Tony Clark and Balbir Barn},
title={A Model based Realisation of Actor Model to Conceptualise an Aid for Complex Dynamic Decision-making},
booktitle={Proceedings of the 5th International Conference on Model-Driven Engineering and Software Development - Volume 1: IndTrackMODELSWARD, (MODELSWARD 2017)},
year={2017},
pages={605-616},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006216306050616},
isbn={978-989-758-210-3},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 5th International Conference on Model-Driven Engineering and Software Development - Volume 1: IndTrackMODELSWARD, (MODELSWARD 2017)
TI - A Model based Realisation of Actor Model to Conceptualise an Aid for Complex Dynamic Decision-making
SN - 978-989-758-210-3
AU - Barat S.
AU - Kulkarni V.
AU - Clark T.
AU - Barn B.
PY - 2017
SP - 605
EP - 616
DO - 10.5220/0006216306050616