Abstract
Public-Private-Partnership (PPP) as an efficient mode to provide public services through the government and social capital’s cooperation has been in China for more than 30 years. In this paper, we propose an approach to evaluate PPP’s advancement in different areas based on the subjective and objective information fusion. At first, we establish an index system from the perspective of the stakeholder. Then, considering that double hierarchy hesitant fuzzy linguistic term set (DHHFLTS) that has two hierarchies of linguistic term sets can describe the subjective linguistic information more accurately, it is applied in the paper to depict the subjective information. By applying the entropy of the DHHFLTS, a programming model is proposed to derive the attribute weight through combining subjective evaluation with objective data. In addition, we develop the double hierarchy hesitant fuzzy linguistic PROMETHEE combining the subjective and objective information (DHHFL-PROMETHEE-S&O) method. At last, we illustrate the index system and the method with the PPP’s advancement evaluation problem, and we can find the best choice based on the ranking result. Meanwhile, we also find that the objective information and the subjective information are complementary in the evaluation process.
Highlights
Public-Private-Partnership (PPP), which can be dated back to 1980s, has become popular in China recently
The rest of this paper is organized as follows: In Section 1, we review some basic concepts related to the double hierarchy hesitant fuzzy linguistic term set (DHHFLTS) and the related previous researches
In the double hierarchy hesitant fuzzy linguistic (DHHFL)- PROMETHEE-S&O method, we derive the attribute weights by combining the subjective and objective information, which is better than the DHHFL-MULTIMOORA method
Summary
Public-Private-Partnership (PPP), which can be dated back to 1980s, has become popular in China recently. To reduce uncertain parameters and the uncertainty of the whole decision-making matrix, we define the double hierarchy hesitant fuzzy linguistic (DHHFL) entropy and establish a programming model according to the minimum entropy principle. We combine the subjective and objective information to calculate the attribute weights and develop the DHHFL-PROMETHEE- S&O method to rank alternatives. Aiming to minimize the entropy of the subjective evaluation and the objective information, we design a programming model to obtain the attribute weights, which is helpful to reduce the uncertainty. The PROMETHEE method applied in this paper can make full use of information It combines the subjective and objective information in the attribute weights deriving process and the alternatives ranking process. The paper ends with some conclusions, research limitations and future research directions
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
