Abstract
The literature on mining community preferences for mineral development, which is the basis for engaging local communities, mainly focuses on rural communities, and may not provide enough insight into an urban community's needs, concerns, and preferences. To bridge this gap, this work uses Salt Lake City, Utah in the United States of America (USA) as a case study to understand an urban population's preferences for mineral resource development. The work considered 16 mining project attributes and four demographic factors (gender, age, education, and income), which have previously been identified as important for explaining individual preferences for mining projects in the USA. The study recruited 628 participants from Salt Lake City to participate in a survey and used a discrete choice model to examine their preferences.
The results show that 15 of the 16 attributes have statistically significant influence on the preferences of these urban dwellers. The probability of the respondents preferring mineral development increases with job opportunities, availability of independent information, income increase, infrastructure improvement, and mine buffer but decreases with noise pollution, air pollution, increase in housing costs, and crime increase. Older, male respondents with higher levels of income and education are more likely to prefer mineral development. The issues that drive the preferences of these urban dwellers are generally similar to those of rural dwellers. However, the study finds that job and housing cost are more important for our urban dwellers than for rural dwellers in other studies. The results suggests that our respondents prefer mines with longer lives.
| Original language | American English |
|---|---|
| Pages (from-to) | 30-39 |
| Number of pages | 10 |
| Journal | Journal of Cleaner Production |
| Volume | 189 |
| DOIs | |
| State | Published - Jul 1 2018 |
Keywords
- Individual preferences
- Discrete choice experiment
- Sustainable mining
- Stakeholder analysis
Disciplines
- Mathematics
- Mining Engineering
- Psychology
- Statistics and Probability
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