HFMADM method based on nondimensionalization and its application in the evaluation of inclusive growth

Abstract

Inclusive growth, which encompasses different aspects of life, is a growth pattern that allows all people to participate in and contribute to growth process. In this paper, a novel hesitant fuzzy multiple attribute decision making (HFMADM) approach based on the nondimensionalization of decision making attributes is presented and then applied to the evaluation of inclusive growth in China. Firstly, a novel generalized hesitant fuzzy distance measure is proposed to calculate the difference and deviation between two hesitant fuzzy elements (HFEs) without adding any values into the shorter hesitant fuzzy element. Secondly, the coefficient of variation and efficacy coefficient method are extended to accommodate hesitant fuzzy environment and then used to cope with HFMADM. In the analysis process, non-dimensional treatment for hesitant fuzzy decision data is produced. Lastly, the method proposed in this paper is applied to an example of inclusive growth evaluation problem under hesitant fuzzy environment and the case study illustrates the practicality of the proposed method. Beyond that, a comparative analysis with some other approaches is also conducted to demonstrate the superiority and feasibility of the proposed method.

Keywords:

• hesitant fuzzy set
• multiple attribute decision making
• nondimensionalization
• distance measure
• coefficient of variation
• efficacy coefficient
• inclusive growth

JEL Classification:

• C49
• C61
• D81

Additional information

Notes on contributors

Xiaodi Liu

Xiaodi LIU has an MSc and a PhD degree in pure mathematics from Wuhan University, Management Science from College of Economics and Management at Nanjing University of Aeronautics and Astronautics, China, respectively. He is an Associate Professor in the school of Mathematics and Physics at Anhui University of Technology. His research areas are multiple attribute decision making, clustering analysis and aggregation operators. His articles are published by Journal of Intelligent & Fuzzy Systems, Information Fusion, Symmetry, Journal of Grey System, Mathematical Problems in Engineering, Journal of Intelligent Systems and others.

Zengwen Wang

Zengwen WANG has an MSc and a PhD degree in pure mathematics and public administration from Wuhan University, China, respectively. He is a Professor in the school of Government at Nanjing University and a Senior Researcher in the Researching Center of Social Security at Wuhan University. His research areas are social welfare and economic development, government management decision making, poverty analysis and employment. He has authored two books and published more than 60 articles to professional journals including journals such as Journal of Public Management, Symmetry, Journal of Political Science, The Population of China Science, Journal of Chinese Administrative Management, Journal of Chinese Soft Science and others.

Antoinette Hetzler

Antoinette HETZLER has a PhD degree in Sociology from Lund University, Sweden. She is a Senior Professor in the Department of Sociology at Lund University. Her research areas are social policy, political sociology, working life, global change, organization theory and the public sector. She has published more than 20 articles to professional journals and conference proceedings including journals such as Journal of Sociologisk Forskning, International Journal of Sociology, Acta Sociologica and others.