Modelling of risk factors for defence aircraft industry using interpretive structural modelling, interpretive ranking process and system dynamics

Abstract

Purpose

Risk management in defence aircraft industry has considerable interest among academics and practitioners. The purpose of this paper is to develop interactions among risk factors dimensions (RFDs) and inspect the importance relationship among the performance measures in Indian aircraft industry and, finally, understand the effect of involvements provided by the managerial team on risk reduction process.

Design/methodology/approach

An extensive literature review was carried out to identify 26 risk parameters and 13 performance measure indices relevant for an aircraft industry. Survey method was used to obtain the importance of these parameters and measures. Further, these factors are grouped into five risk dimensions based on the brain storming session by the project managers. Initially, Risk factors for defense aircraft industry (RFDs) analyzed by Interpretative structural model (ISM) to know the contextual relationship among the RFDs and then applied Interpretive ranking process (IRP) to inspect the pre-eminence relationship among them. Finally, SD is applied to understand the effect of involvements provided by the managerial team on risk reduction process.

Findings

Government policy and legal RFDs has emerged as the key driving RFDs. In IRP modelling, technology RFD has emerged as more influential RFD which is the more relevant factor with respect to performance measure indices and this result is supported by detailed sensitivity analysis of system dynamic model.

Originality/value

The outcomes of this research can help project management team to identify the high severity risk factors which need immediate risk reduction/mitigation action.

Citation

Pitchaimuthu, S., Thakkar, J.J. and Gopal, P.R.C. (2019), "Modelling of risk factors for defence aircraft industry using interpretive structural modelling, interpretive ranking process and system dynamics", Measuring Business Excellence, Vol. 23 No. 3, pp. 217-239. https://doi.org/10.1108/MBE-05-2018-0028