A new rough cloud AHP method for risk evaluation of public–private partnership projects

This study mainly focuses on the risk assessment of public–private partnership (PPP) projects. Evaluating the risks of PPP projects precisely is critical to their successful implementation. However, the traditional approaches often lack mechanisms in manipulating imprecise and vague information, and they need auxiliary information or pre-assumptions (e.g., preset fuzzy membership functions). To solve this problem, an integrated method for evaluating risks in public–private partnership projects is proposed. This method is based on the strength of the group analytic hierarchy process (GAHP), rough set theory, and cloud model theory. The proposed approach integrates the strength of rough set theory in coping with vagueness of the information from experts’ assessments without much pre-assumptions, the advantage of cloud model theory in investigating the randomness of experts’ judgments, and the merit of the AHP method in evaluation under multiple criteria and complex situation. Finally, an application in a PPP project in Wuhu, China, is provided to show the feasibility and effectiveness of the proposed method. The proposed approach is effective in modeling hierarchy assessment as well as dealing with vagueness and randomness, and it can help managers to make reasonable and effective decisions in risk management.