Multi-objective model for intelligence evaluation and selection of enterprise systems

Saeed Rouhani and Ahad Zare Ravasan

International Journal of Business Information Systems, 2015, vol. 20, issue 4, 397-426

Abstract: Most organisations still experience a lack of business intelligence (BI) in their decision-making processes when implementing enterprise systems. The current state-of-the-art in decision support takes the intelligence requirements of enterprise systems as important quality aspects into consideration, along with their functional and non-functional needs, but the literature lacks studies on the evaluation of these intelligence requirements. This paper proposes a fuzzy, multi-criteria decision-making procedure and a multi-objective programming model to evaluate and make final decisions about the selection of enterprise systems that also include the requirements of business intelligence in addition to their other goals and requirements. In order to validate the model with a real application, all phases of the approach were applied in the evaluation of the enterprise systems of a company in the oil industry. Companies can use this model to evaluate, select and implement enterprise software and systems that will provide better decision support for their organisational environment.

Keywords: enterprise systems; business intelligence; multi-objective programming; fuzzy evaluation; modelling; fuzzy logic; fuzzy MCDM; multicriteria decision making; enterprise system selection; oil industry; enterprise software. (search for similar items in EconPapers)
Date: 2015
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.inderscience.com/link.php?id=72736 (text/html)
Access to full text is restricted to subscribers.

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:ids:ijbisy:v:20:y:2015:i:4:p:397-426

Access Statistics for this article

More articles in International Journal of Business Information Systems from Inderscience Enterprises Ltd
Bibliographic data for series maintained by Sarah Parker ().