Application of case-based reasoning in developing a claim management model for construction projects
Wei Zhao et al.
What the paper says
Purpose Claims occur frequently in construction projects. Claim management is challenging owing to its complexity and demand of project resources. Given the experiential nature of the construction industry, valuable insights from similar historical cases are crucial as important references. However, research on construction claim management models from a knowledge management perspective is limited. This study addressed this gap by the following: (1) developing a practical model for construction claim management based on case-based reasoning (CBR) and (2) validating the claim management model using a specific construction claim case. Design/methodology/approach Historical cases were collected and key attributes were extracted to represent the case characteristics. A combination of the subjective analytic hierarchy process and objective entropy weight method was employed to determine the composite weights of these attributes. Gray relation analysis (GRA) was used to calculate the similarity between cases. Finally, a claim case was employed to show the application of the developed model. Findings Results indicated that the two first-level attributes, “claim type” and “claim reason”, and a second-level attribute, “claim liability” being “contractor,” had the most effect on the calculation of case similarity. The results of the claim case analyzed using the developed CBR model aligned well with the actual claim settlement outcomes. Originality/value This innovative CBR model enriches the theoretical framework of construction claim management and facilitates the storage and transfer of tacit knowledge to improve construction management efficiency.
Evidence weight
Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40
| F · citation impact | 0.50 × 0.4 = 0.20 |
| M · momentum | 0.50 × 0.15 = 0.07 |
| V · venue signal | 0.50 × 0.05 = 0.03 |
| R · text relevance † | 0.50 × 0.4 = 0.20 |
† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.