Making decision toward overseas construction projects: An application based on adaptive neuro fuzzy system
Engineering, Construction and Architectural Management
ISSN: 0969-9988
Article publication date: 28 February 2019
Issue publication date: 26 March 2019
Abstract
Purpose
The purpose of this paper is to introduce a decision support aid for deciding an overseas construction project (OCP) using an adaptive neuro fuzzy inference system (ANFIS).
Design/methodology/approach
This study presents an ANFIS approach as a decision support aid for assessment of OCPs. The processing data were derived from 110 simulation cases of OCPs. In total, 21 international factors observed from a Delphi survey were determined as assessment variables to examine the cases. The experts were involved to evaluate and judge whether the company should Go or Not Go for an OCP, based on the different parameter scenarios given. To measure the performance of the ANFIS model, root mean square error (RMSE) and coefficient of correlation (R) were employed.
Findings
The result shows that optimum ANFIS model indicating RMSE and R scores adequately near between 0 and 1, respectively, was obtained from parameter set of network algorithm with two input membership functions, Gaussian type of membership function and hybrid optimization method. When the model tested to nine real OCPs data, the result indicates 88.89 percent accurate.
Research limitations/implications
The use of simulation cases as data set in development the model has several advantages. This technique can be replicated to generate other case scenarios which are not available publicly or limited in terms of quantity.
Originality/value
This study evidences that the developed ANFIS model can predict the decision satisfactorily. Therefore, it can help companies’ management to make preliminary assessment of an OCP.
Keywords
Citation
Utama, W.P., Chan, A.P.C., Zahoor, H., Gao, R. and Jumas, D.Y. (2019), "Making decision toward overseas construction projects: An application based on adaptive neuro fuzzy system", Engineering, Construction and Architectural Management, Vol. 26 No. 2, pp. 285-302. https://doi.org/10.1108/ECAM-01-2018-0016
Publisher
:Emerald Publishing Limited
Copyright © 2019, Emerald Publishing Limited