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The purpose of this paper is to examine the potential of applying Petri nets to improve construction material logistics analysis and modelling.

The characteristics of construction logistics are unveiled by analysing the existing practices of logistics management. In views of the dynamic nature of construction logistics problem, a stochastic Petri nets (SPNs) approach is proposed to tackle the time‐evolution property. Using a simulation package called PetriTool™ a simulation model is developed. Finally, a case example is applied to illustrate the way in which SPNs is used for analysing and modelling construction material logistics problems.

The results indicate that the impacts triggered by variations in delivery lead‐time and changes in delivery quantities can be approximated thereby facilitating decision makers to devise a more reliable and optimal materials management plan for construction projects.

The complex routing patterns in demand analysis and materials procurement methods that results in the enlarged supply chains have not been considered in this paper.

The lack of a simple but powerful formalism to analyse and model the decision process under a dynamic environment hinders the implementation of efficient logistics systems in the construction industry. The SPNs model presented in this paper can support planners and managers in making construction logistics management decisions under dynamic environment.

This paper demonstrates that the time‐based SPNs can offer more enriched solutions especially when modelling the time‐evolution behaviours of construction logistics.

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.