<![CDATA[This study aims to analyze how processing, packaging, and shipping affect the price of mercury waste management services, identifying the most dominant factors. The methodology in this study uses a quantitative design with Partial Least Squares (PLS) regression analysis using Smart PLS 4.1.0.9. Data were collected from four upstream oil and gas operations in Indonesia in 2010-2022 to identify the dominant factors that affect service prices. Mercury waste management data collection was carried out in four locations, with an initial population of 16 unique data according to the contract, which then increased to 43 after being adjusted for the implementation period and contract validity period. The results of the analysis show that indicating processing, packaging, and shipping have a p-value of less than 0.05, indicating that all significantly affect service prices. Among these factors, processing has the highest t-statistic of 16.47, making it the most dominant predictor of mercury waste management services.]]>
Copyrights © 2025
