Combine MCDM Methods and PSO to Evaluate Economic Benefits of High-Tech Zones in China
Xiaobing Yu (),
Xuejing Wu () and
Tongzhao Huo ()
Additional contact information
Xiaobing Yu: Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Information Science & Technology, Nanjing 210044, China
Xuejing Wu: School of Management Science and Engineering, Nanjing University of Information Science & Technology, Nanjing 210044, China
Tongzhao Huo: School of Management Science and Engineering, Nanjing University of Information Science & Technology, Nanjing 210044, China
Sustainability, 2020, vol. 12, issue 18, 1-20
High-tech zones (HTZs), as important economic growth poles, have played a key role in China’s economic boom. A method based on multi-criteria decision-making (MCDM) and particle swarm optimization (PSO) is proposed to evaluate economic benefits of HTZs. MCDM involves analytic hierarchy process (AHP) and technique for order preference by similarity to an ideal solution (TOPSIS) as they are easy and simple to calculate. AHP is used to construct judgment matrix. Then, the judgment matrix is converted to a constraint optimization problem. PSO is adopted to optimize the problem and get weights of indicators. TOPSIS is used to make the evaluation. The results from 2012 to 2016 of 105 HTZs are obtained and hierarchical clustering analysis is applied to cluster results. The results have demonstrated that the rankings of Zhongguancun Technology Park and Wuhan East Lake HTZ have always been at the forefront, and the ranking of Kunshan New District has risen rapidly, while Shenyang HTZ has dropped significantly. According to the results, some targeted suggestions have been proposed for the development of HTZs.
Keywords: high-tech zones; AHP; PSO; TOPSIS; evaluation (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
References: View references in EconPapers View complete reference list from CitEc
Citations: Track citations by RSS feed
Downloads: (external link)
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:12:y:2020:i:18:p:7833-:d:417534
Access Statistics for this article
Sustainability is currently edited by Mr. Samuel Li
More articles in Sustainability from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().