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Research Journal of Business Management
  Year: 2014 | Volume: 8 | Issue: 4 | Page No.: 523-537
DOI: 10.3923/rjbm.2014.523.537
 
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ASEAN Biomass Energy a Thai Environmental Impact Analysis by use of a Structural Equation Model (SEM)

Somboon Aueatchasai and Wanno Fongsuwan

Abstract:
Thailand’s economic growth is in many respects determined by power generation with the demand for electricity moving hand-in-hand with rapidly expanding economic growth. With the doubling of Thailand’s population since the 1960s, the necessity for rural electricity coverage has also increased dramatically. This however is at times difficult and expensive to achieve in these remote rural locations with their sparsely populated areas. However, power must be available nationwide and when areas are not appropriate for a large-scale power plant investment, smaller and less expensive local power plants need to be chosen. In these rural cases, biomass power plants can be considered as one alternative. Since, Thailand outside the main metropolitan areas is still mostly rural and agricultural, there is a ready source of raw material for biomass power plant conversion. The purpose of this research therefore was to determine the environmental impact of certain variables on the environmental impact on the local community. This study concerns the modeling and analysis of Thailand’s biomass power industry using both quantitative and qualitative research methods. Quantitative data was obtained using stratified sampling from 323 biomass power community members and qualitative data from in-depth research of 10 community leaders using simple random sampling while using Partial Least Square (PLS-Graph) software to apply Structural Equations Modeling (SEM) analysis. Results showed from the hypotheses that government policy and community participation had a significant and direct contribution on the overall environmental impact of the local community.
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How to cite this article:

Somboon Aueatchasai and Wanno Fongsuwan, 2014. ASEAN Biomass Energy a Thai Environmental Impact Analysis by use of a Structural Equation Model (SEM). Research Journal of Business Management, 8: 523-537.

DOI: 10.3923/rjbm.2014.523.537

URL: https://scialert.net/abstract/?doi=rjbm.2014.523.537

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