Modelling critical risk factors for Indian construction project using interpretive ranking process (IRP) and system dynamics (SD)

Abstract

Purpose

The purpose of this paper is to employ an integrated approach of interpretive ranking process (IRP) and system dynamics (SD) for modelling the key risk factors for a typical construction project.

Design/methodology/approach

The risk parameters and performance measures applicable in the construction industry have been identified through extensive literature review and discussions with experts from the construction industry. Based on the literature review, a questionnaire was designed and 64 responses were considered. The list of 20 risk parameters and 32 performance measures relevant for a construction industry is reduced to five risk factors and five performance measure factors using factor analysis. IRP modelling is employed to examine the contextual relationships among risk factors and to rank them with respect to performance measure factors. Subsequently, the results of IRP model were utilised as inputs to SD analysis. The SD analysis is conducted for two models, namely, risk factor model and risk variable model to understand the impact of interventions offered by project management team on risk reduction and mitigation.

Findings

The developed IRP model shows that the risk factor dimension “construction management” has a high likeliness to occur during the construction phase.

Research limitations/implications

The research demonstrates an application of proposed approach for a typical construction environment and hence the results cannot be generalised.

Originality/value

This research addresses real life complexities in construction project by modelling critical risk factors using an integrate approach of IRP and SD. The proposed approach would facilitate project managers to devise appropriate risk mitigation strategies for a construction project.

Citation

Mhatre, T.N., Thakkar, J.J. and Maiti, J. (2017), "Modelling critical risk factors for Indian construction project using interpretive ranking process (IRP) and system dynamics (SD)", International Journal of Quality & Reliability Management, Vol. 34 No. 9, pp. 1451-1473. https://doi.org/10.1108/IJQRM-09-2015-0140