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A robust expert decision support system for making real estate location decisions, a case of investor-developer-user organization in industry 4.0 era

Sam Mosallaeipour (Faculty of Technology and Innovation, Technical Business School, NHL Stenden University of Applied Science, Leeuwarden, The Netherlands)
Seyed Mahdi Shavarani (Alliance Manchester Business School, University of Manchester, Manchester, UK)
Charlotte Steens (Faculty of Technology and Innovation, Technical Business School, NHL Stenden University of Applied Science, Leeuwarden, The Netherlands)
Adrienn Eros (Hospitality Business School, Saxion University of Applied Sciences, Deventer, The Netherlands)

Journal of Corporate Real Estate

ISSN: 1463-001X

Article publication date: 28 November 2019

Issue publication date: 19 March 2020

539

Abstract

Purpose

This paper aims to introduce a practical expert decision support system (EDSS) for performing location analysis and making real estate location decisions in the organization’s facility and real estate management (FREM) department in presence of several decision criteria, under risk and uncertainty. This tool is particularly useful for making strategic decisions in facility planning, portfolio management, investment appraisal, development project evaluations and deciding on usage possibilities in an unbiased, objective manner.

Design/methodology/approach

The proposed EDSS uses fuzzy logic and uncertainty theory as two of the most useful tools to deal with uncertainties involved in the problem environment. The system performs an unbiased mathematical analysis on the input data provided by the decision-maker, using a combination of Analytical Hierarchy Process (AHP) and Global Criterion Method; determines a suitable compromise level between the objectives; and delivers a set of locations that complies best with the outlined desires of the management as the final solution. The application of the system is tested on a real case and has delivered satisfactory results.

Findings

The proposed EDSS took the defined objectives, the list of alternative locations, and their attributes as the required input for problem-solving, and used a combination of AHP, Possibilistic approach, and global criterion method to solve the problem. The delivered outcome was a set of proper locations with the right attributes to meet all objectives of the organization at a satisfactory level, confirmed by the problem owners.

Originality/value

The application of such a system with such a degree of preciseness and complexity has been very limited in the literature. The system designed in this study is an Industry 4.0 decision making tool. For designing this system several body of knowledge are used. The present study is particularly useful for making strategic decisions in the domains of portfolio management, investment appraisal, project development evaluations and deciding on property usage possibilities. The proposed EDSS takes the information provided by the experts in the field (through qualitative and quantitative data collecting) as the inputs and operates as an objective decision-making tool using several bodies of knowledge considering the trends and developments in the world of FREM. The strong scientific method used in the core of the proposed EDSS guarantees a highly accurate result.

Keywords

Acknowledgements

We would like to thank the anonymous reviewers of this paper for their invaluable comments and suggestions for improving the current work. Furthermore, we would like to thank Mr Jos van Stratum, and Mr Rene de Boer, the founding members of Industry 4.0 team of the Technische Bedrijfskunde department of NHL Stenden University of applied science for their support for this paper – Authors (2019).

Citation

Mosallaeipour, S., Shavarani, S.M., Steens, C. and Eros, A. (2020), "A robust expert decision support system for making real estate location decisions, a case of investor-developer-user organization in industry 4.0 era", Journal of Corporate Real Estate, Vol. 22 No. 1, pp. 21-47. https://doi.org/10.1108/JCRE-03-2019-0019

Publisher

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Emerald Publishing Limited

Copyright © 2019, Emerald Publishing Limited

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