| Title | Classifying critical factors that influence community acceptance of mining projects for discrete choice experiments in the United States |
|---|---|
| ID_Doc | 67508 |
| Authors | Que, SS; Awuah-Offei, K; Samaranayake, VA |
| Title | Classifying critical factors that influence community acceptance of mining projects for discrete choice experiments in the United States |
| Year | 2015 |
| Published | |
| Abstract | Local community acceptance is a key indicator of the socio-political risk associated with a mining project. Discrete choice modeling could enhance stakeholder analysis, a critical step in community engagement. This paper seeks to identify and classify key mining project characteristics and demographic factors that influence individual acceptance of mining projects for discrete choice experiments. Six demographic factors were selected and project characteristics were classified into 16 characteristics, based on the literature. A survey of residents of mining and non-mining communities was used to test the hypothesis that these mine characteristics and demographic factors will influence respondents' decision to accept a proposed mining project. Four (age, gender, income and education) of the six demographic factors were confirmed to be significantly (p < 0.05) correlated to respondent's ranking of the importance of the mine characteristics. These demographic factors are likely to be important explanatory variables of an individual's decision to support a mining project. All sixteen project characteristics are identified as important factors. The most important mining project characteristics were found to be job opportunities, water shortage or pollution, air pollution, and land pollution. Both groups of respondents reported similar opinions on 12 of the mining characteristics and differed, marginally, on infrastructure improvement, labor shortage for other businesses, noise pollution, and mine life. This result serve as a starting point for efficient choice experiment (survey) design and effective discrete choice modeling. These models can provide a viable framework for data-driven community engagement and sustainable mine management. (C) 2014 Elsevier Ltd. All rights reserved. |
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