Fuzzy synthesis analysis of social network risk factors in supply chains of African megaprojects

Purpose: Megaproject supply chains involve multiple layers of stakeholders, leading to complex relationships and risks. The role of social interactions within these networks is unexplored. Therefore, an analysis of construction supply chain risk management from the perspective of social networks is essential to identify related stakeholders, their relationships and the social network risk factors. Design/methodology/approach: About 65 risk factors, identified from literature and interviews, informed the development of a questionnaire for the study. Online questionnaires administered in Ghana and South Africa produced 120 valid responses. Feedback from the responses was ranked and assessed to determine the overall social network risk levels using the Normalised Mean and Fuzzy synthesis analysis methods. Findings: About 24 risk factors were identified and classified into six groups: Client/Consultant-related, Community-related, Government-related, Industry Perception-related, Supplier-related and Stakeholder Opportunism. The top five social network risks identified include bribery, supplier monopoly, incomplete design teams, poor communication and lack of collaboration. Practical implications: The study provides detailed evaluations of social network risks in Africa, and the findings will help in developing strategies to mitigate supply chain disruptions caused by these challenges. Originality/value: This study contributes to the literature on supply chain risk management by offering context-specific insights into the social network perspective of megaprojects in Africa, which differs from those in developed countries.