During the planning and controlling of the construction process, most attention is focu sed on risk analysis, especially in the context of final costs and deadlines of the investment. In this analysis, the primary and most significant concern is the proper identification and quantification of events, which on a certain level of probability may affect the development process. This paper presents the result of a risk analysis for a particular building object, made after completion of the investment and accepting it for use. Knowledge of the planned values and the actual investment process allowed for the identification of the events and their effects that in this case have significantly disrupted the investment process. The limited total cost of the investment project in question had a considerable impact on the progress of the project execution. Despite three transitions of administrative procedures, the opening date of the shopping centre was delayed by only three weeks.
Overseas mining investment generally faces considerable risk due to a variety of complex risk factors. Therefore, indexes are often based on conditions of uncertainty and cannot be fully quantified. Guided by set pair analysis (SPA) theory, this study constructs a risk evaluation index system based on an analysis of the risk factors of overseas mining investment and determines the weights of factors using entropy weighting methods. In addition, this study constructs an identity-discrepancycontrary risk assessment model based on the 5-element connection number. Both the certainty and uncertainty of the various risks are treated uniformly in this model and it is possible to mathematically describe and quantitatively express complex system decisions to evaluate projects. Overseas mining investment risk and its changing trends are synthetically evaluated by calculating the adjacent connection number and analyzing the set pair potential. Using an actual overseas mining investment project as an example, the risk of overseas mining investment can be separated into five categories according to the risk field, and then the evaluation model is quantified and specific risk assessment results are obtained. Compared to the field investigation, the practicability and effectiveness of the evaluation method are illustrated. This new model combines static and dynamic factors and qualitative and quantitative information, which improves the reliability and accuracy of risk evaluation. Furthermore, this evaluation method can also be applied to other similar evaluations and has a certain scalability.