Black gold, dark realities: Unpacking the socio-economic and environmental fallout of unauthorized oil extraction (Investigation in East Aceh, Indonesia)
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DOIhttp://dx.doi.org/10.21511/ee.15(2).2024.05
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Article InfoVolume 15 2024, Issue #2, pp. 64-76
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Creative Commons Attribution 4.0 International License
Environmental degradation can lead to climate change, air and water quality degradation, and biodiversity loss. The study aims to assess the impact of illegal oil extraction on environmental, social, economic, and public health dimensions in Peurelak, East Aceh, Indonesia. Using proportional random sampling techniques, 245 respondents were selected, representing owners and investors (9), tenant investors (18), workers/laborers (68), melters (6), public figures/community leaders (3), the community (138), and village government officials (3). Data were analyzed using structural equation modeling (SEM) with AMOS software. The results revealed a significant negative effect of illegal oil mining on social, environmental, and health performance (p-values = 0.031, 0.029, and 0.010, respectively, at a 95% confidence level). Additionally, informal leadership and government support were found to positively influence illegal oil mining (p-values = .017 and .035, respectively, below the significance threshold of .05). Furthermore, illegal oil mining significantly affects economic performance (p-value = .021). This paper emphasizes the adverse impacts of unauthorized oil extraction on community well-being while highlighting the collusive role of informal leaders and government authorities. Additionally, the study reveals a worrisome positive relationship between illegal oil mining and economic performance in Indonesia.
- Keywords
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JEL Classification (Paper profile tab)L71, Q51, Q56
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References32
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Tables5
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Figures2
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- Figure 1. Research model
- Figure. 2. Measurement model
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- Table 1. Population distribution and research sample
- Table 2. Respondent characteristics
- Table 3. Standardized regression weights
- Table 4. Goodness of fit indices
- Table 5. Structural model testing results
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