Search results

Recent studies on construction supply chain management (CSCM) evaluated its vulnerability and challenging factors, but studies that have identified and examined the possible corrective measures of CSCM are rare. This study sets out to bridge this gap by identifying and evaluating the most effective CSCM corrective measures that will benefit the global construction industry.

A methodology was designed to obtain the corrective measures of CSCM. Data were collected from 68 experts who served as research participants in this study, through a questionnaire survey and were analyzed statistically using the severity index analysis, Mann–Whitney test and factor analysis which includes KMO and Barlett's test, commonalities, total variance pattern matrix.

The findings of the study revealed that free exchange of information between parties from both suppliers and site/firm is the best CSCM corrective measures, according to the research participant's opinion using the severity index analysis. Further analysis revealed seven underlying factors of CSCM corrective measures.

The findings of this study have identified the most critical solutions to the lapses of CSCM. These will serve as adequate corrective measures to the challenges of CSCM and benefit the global construction industry.

This study contributed seven underlying factors of CSCM corrective measures which can be adopted as adequate corrective measures to the lapses of CSCM. The study further contributed to CSCM research theory.

The growing demand for housing and infrastructure, as well as the requirement for affordable housing, has been a significant factor, necessitating investigation for sustainable approaches and implementation of alternative construction innovations. Hence, this study aims to identify and assess the drivers for implementing modular construction systems (MCS) in developing countries.

The study adopts a quantitative research approach to seek respondents’ opinions on the factors that can drive the implementation of MCS in developing countries. Accordingly, a structured questionnaire was used as an instrument of data collection based on five Likert scales. The data was analysed using the mean score, one sample t-test, Kruskal–Wallis, factor analysis (FA) and Pearson correlation analysis.

Results show that 15 of the 16 major identified drivers were statistically significant towards implementing MCS, which indicates that the drivers are crucial for implementing MCS in developing countries. However, the Kruskal–Wallis test reveals that the respondents have varying opinions on the identified drivers. FA categorised the drivers into four categories, namely, “management and sustainability”, “key performance”, “know-how and logistics” and “regulations and policies”. A strong relationship among the four categories of drivers was established using Pearson correlation, which indicated that all the drivers’ categories are essential for implementing MCS in developing countries.

This study identified and assessed the drivers towards implementing MCS in developing countries. The study concludes that the identified drivers are essential for implementing MCS in developing countries. Also, the study considers the government the most placed player in driving the implementation of MCS in developing countries.