Ranking of business process simulation tools with DEX/QQ hierarchical decision model

Damij, Nadja, Boskoski, Pavle, Bohanec, Marko and Boshkoska Mileva, Biljana (2016) Ranking of business process simulation tools with DEX/QQ hierarchical decision model. PLoS ONE, 11 (2). e0148391. ISSN 1932-6203

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Official URL: https://doi.org/10.1371/journal.pone.0148391


The omnipresent need for optimisation requires constant improvements of companies’ business processes (BPs). Minimising the risk of inappropriate BP being implemented is usually performed by simulating the newly developed BP under various initial conditions and “what-if” scenarios. An effectual business process simulations software (BPSS) is a prerequisite for accurate analysis of an BP. Characterisation of an BPSS tool is a challenging task due to the complex selection criteria that includes quality of visual aspects, simulation capabilities, statistical facilities, quality reporting etc. Under such circumstances, making an optimal decision is challenging. Therefore, various decision support models are employed aiding the BPSS tool selection. The currently established decision support models are either proprietary or comprise only a limited subset of criteria, which affects their accuracy. Addressing this issue, this paper proposes a new hierarchical decision support model for ranking of BPSS based on their technical characteristics by employing DEX and qualitative to quantitative (QQ) methodology. Consequently, the decision expert feeds the required information in a systematic and user friendly manner. There are three significant contributions of the proposed approach. Firstly, the proposed hierarchical model is easily extendible for adding new criteria in the hierarchical structure. Secondly, a fully operational decision support system (DSS) tool that implements the proposed hierarchical model is presented. Finally, the effectiveness of the proposed hierarchical model is assessed by comparing the resulting rankings of BPSS with respect to currently available results.

Item Type: Article
Additional Information: Funding information: The authors acknowledge the support of the Slovenian Research Agency through Research Programme P1-0383, and Research Project J1-5454. The work was also supported by the Creative Core FISNM-3330-13-500033 "Simulations’’ project funded by the European Union, the European Regional Development Fund.
Uncontrolled Keywords: software tools, open source software, decision trees, optimization
Subjects: G500 Information Systems
N100 Business studies
Department: Faculties > Business and Law > Newcastle Business School
Depositing User: Dr Nadja Damij
Date Deposited: 23 Jan 2017 15:07
Last Modified: 31 Jul 2021 16:15
URI: http://nrl.northumbria.ac.uk/id/eprint/29271

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