Using Markov Theory to Deliver Informed Decisions in Partially Observable Business Processes Operation

Sérgio Guerreiro
Additional contact information
Sérgio Guerreiro: Instituto Superior Técnico, University of Lisbon, Portugal / INESC-ID, Lisbon, Portugal

International Journal of Operations Research and Information Systems (IJORIS), 2018, vol. 9, issue 2, 53-72

Abstract: This article explores the stochastic capabilities offered by Markov theories combined with business transaction models, from the Enterprise Engineering field, to contribute to the decision-making body of knowledge. An agro-food case study shows the utility of this solution and the evaluation argues the management decisions value in situations where is not possible to fully observe the state of the reality, or to be fully aware about it. A full policy graph that forecasts the belief states from observations and enacted actions is delivered.

Date: 2018
References: Add references at CitEc
Citations:

Downloads: (external link)
http://services.igi-global.com/resolvedoi/resolve. ... 18/IJORIS.2018040103 (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:igg:joris0:v:9:y:2018:i:2:p:53-72

Access Statistics for this article

International Journal of Operations Research and Information Systems (IJORIS) is currently edited by John Wang

More articles in International Journal of Operations Research and Information Systems (IJORIS) from IGI Global
Bibliographic data for series maintained by Journal Editor ().