Project pathogens network: New approach to analyzing construction-defects- generation mechanisms

Hamad Aljassmi, Sangwon Han, Steven Davis

Research output: Contribution to journalArticlepeer-review

35 Scopus citations


Construction defects can exert significant impacts on project performance. These defects are typically traced back to their initiating root causes, formulated as infectious decisions, practices, or circumstances. The root causes often act as pathogens that propagate to spread numerous other risky conditions, thereby making projects prone to defects. Accordingly, it is essential to quantify the pathogenic capacity held by each root cause to determine the scope of potential risk associated with its existence. Although several studies have striven to identify project pathogens, research on determining the most pathogenic causes to develop further defect management efforts is lacking. To address this deficiency, the aim of this study was to develop a methodology that captures the complex mechanisms of defect generation and quantifies their pathogenic capacities in accordance to their position within the network of sequential events leading to defects. Specifically, the study uses a social network analysis (SNA) approach as a platform to formulate the interrelationships of defect causes, and review SNA metrics to develop a formal mathematical expression of pathogenicity, forming a new project pathogens network (PPN) methodology. Application to four residential projects in Dubai confirmed that PPN has great potential for revealing the pathogenic capacities held by the infectious conditions resulting in construction defects. This paper contributes to knowledge in the area of construction engineering and management by proposing a methodology that is deliberated to providing both mathematical and visualization analyses needed to address the complex mechanisms of defect generation, which thus enables project practitioners and academics to better understand the vulnerability of a construction-project system to pathogenic conditions.

Original languageEnglish
Article number04013028
JournalJournal of Construction Engineering and Management - ASCE
Issue number1
StatePublished - Jan 2014


  • Defect
  • Error
  • Pathogens
  • Quantitative methods
  • Risk
  • Social network analysis


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