A method for effective use of enterprise modelling techniques in complex dynamic decision making

Tony Clark, Souvik Barat*, Vinay Kulkarni, Balbir Barn

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Effective organisational decision-making requires information pertaining to various organisational aspects, precise analysis capabilities, and a systematic method to capture and interpret the required information. The existing Enterprise Modelling (EM) and actor technologies together seem suitable for the specification and analysis needs of decision making. However, in absence of a method to capture required information and perform analyses, the decision-making remains a complex endeavour. This paper presents a method that captures required information in the form of models and performs what-if calculations in a systematic manner.

Original languageEnglish
Title of host publicationThe Practice of Enterprise Modeling - 10th IFIP WG 8.1. Working Conference, PoEM 2017, Proceedings
PublisherSpringer
Pages319-330
Number of pages12
Volume305
ISBN (Print)9783319702407
DOIs
Publication statusE-pub ahead of print - 31 Oct 2017
Event10th IFIP WG 8.1 Working Conference on the Practice of Enterprise Modelling, PoEM 2017 - Leuven, Belgium
Duration: 22 Nov 201724 Nov 2017

Publication series

NameLecture Notes in Business Information Processing
Volume305
ISSN (Print)1865-1348

Conference

Conference10th IFIP WG 8.1 Working Conference on the Practice of Enterprise Modelling, PoEM 2017
CountryBelgium
CityLeuven
Period22/11/1724/11/17

    Fingerprint

Keywords

  • Bottom-up simulation
  • Enterprise decision making
  • Method

Cite this

Clark, T., Barat, S., Kulkarni, V., & Barn, B. (2017). A method for effective use of enterprise modelling techniques in complex dynamic decision making. In The Practice of Enterprise Modeling - 10th IFIP WG 8.1. Working Conference, PoEM 2017, Proceedings (Vol. 305, pp. 319-330). (Lecture Notes in Business Information Processing; Vol. 305). Springer. https://doi.org/10.1007/978-3-319-70241-4_21