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Arid Land Geography ›› 2019, Vol. 42 ›› Issue (2): 452-457.doi: 10.12118/j.issn.1000-6060.2019.02.25

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Risk acceptability of urban NIMBY facilities based on structural equation model:A case of Tianchang City

LUO Li1,2, WU Yun-qing1   

  1. (1. School of Geomatics Science and Technology of Nanjing Tech University, Jiangsu 211810, Nanjing,China;
    2. Jiangsu SUDIRENHE Real Estate Appraisal, Consultation, Mapping and Construction Limited Company, Jiangsu 210029, Nanjing, China)
  • Online:2019-03-25 Published:2019-03-07

Abstract: Based on the results of 1250 questionnaires in Tianchang City, Anhui Province, China, four variables including “risk cognition”, “government trust”, “public participation” and “compensation measures” were defined as latent variables to assess the risk acceptability of the public to the urban NIMBY (not in my back yard) facilities using SPSS for validity and factor analysis. The original hypothesis was determined through the literature review. The software AMOS 21.0 was used to establish a structural equation model to test whether the original hypothesis is true or not; and the relationship between each latent variable and “acceptability” was analyzed. The results showed that the "risk recognition" had an influence coefficient of -0.262 on the "acceptability"; and the variable "public participation" had the influence coefficient of -0.242. Both were negative correlation. The variables "Government trust" and "compensation measures" had a positive impact on "acceptability." Besides, there was a certain positive effect among the four latent variables. The age and level of education in the demographic variables had some influence on the "acceptability". Through this study, the influence factors were quantified and the importance of the factors can be compared objectively. The results had provided some information for the government and related workers when they formulate relevant policies and measures in setting up urban NIMBY facilities.

Key words: NIMBY facilities, risk awareness, acceptability, Tianchang City, AMOS structural equation model