Abstract
The performance evaluation index system was established on the basis of 4E (Efficiency, Economic, Effectiveness, Equity) theory to improve performance evaluation of Public-Private Partnership Projects for Residential Renovation (4P2R). Moreover, the index weighting model was demonstrated based on Ordered Weighted Averaging (OWA). Finally, the cloud model was used for performance evaluation, through the cloud uncertainty reasoning to determine the quantitative performance evaluation index value, the positive reverse cloud to calculate the qualitative performance evaluation index value, and the normal cloud to measure the project performance. The proof-of-concept application shows that the performance evaluation index system and evaluation model can better identify the deficiencies in the project, and provide targeted improvement measures for similar projects in the future.
Highlights
Local governments in China have been establishing Public-Private Partnership (PPP) projects owing to the increasing popularity and applicability of PPP model since September 2014
The Ordered Weighted Averaging (OWA) operator weighting method was employed for determining the performance evaluation indicators weights
The performance evaluation of 4P2R can identify the shortcomings in the project, and provide means of analysis for the causes of the problems and related improvement measures
Summary
Local governments in China have been establishing Public-Private Partnership (PPP) projects owing to the increasing popularity and applicability of PPP model since September 2014. Social capital has a significant role in PPP for the renovation of old residential areas (4P2R) through broadening the project financing channels, solving the project funding gap, and resolving the local government financial risks [4]. The above problems may cause quality risk, cost risk, and schedule risk in PPP projects These risks may lead to issues such as quality defects, project funds waste, and delays in construction schedules [5]. Analytic Hierarchy Process (AHP) [16], FANP-TOPSIS [17], Electre Tri-nC [18], and Grey Relational Analysis (GRA) [19] methods have been applied for evaluating PPP projects’ performance Most of these methods use the scores that are subjectively determined by experts, relying on experts’ personal experience to calculate the weights. We built a novel performance evaluation method by using the cloud model to overcome the existing methods’ inadequacy to determine index values
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