Critical Evaluation of Construction Supply Chain Management Using Classification Leaner Model for improved Project Delivery

Abstract

Risk management in supply chain is imperative to avoid delays
and cost overrun that has the potential of derailing the success
of the project. In this research, a structured questionnaire was
used to measure the knowledge and experience of the
respondents in supply chain risk management and find out ways
of effective mitigation methods. Findings indicate that the
supply chain management (SCM) makes a considerable
contribution on the outcome of a project since more than half of
the respondents had more than ten years of experience and
53.3% were project managers in large-scale infrastructure
projects. Interestingly, the shares of participants reporting an
increase in SCM integration was 56.7%, which shows that they
are becoming proactive and prompt in their practices.
Nevertheless, the poor communication with the suppliers
(16.7%) and problem with their delivery (13.3%) are challenges
which remain. Some respondents suggested some solutions in
mitigating the development of such problems such as real time
monitoring (20%) and diversity of suppliers (10%). The
application of machine learning methods and classification
techniques justify the predictive capability of the DT and SVM
models on SCM risk.