| Popis: |
The objective of this research is to analyze the impact of causal factors relationship over the changes in future scenario management under the sustainability policy of Thailand by creating a model with validity called “Partial Least Square Path Modeling based on Autoregressive Integrated Moving Average with Observed Variables (PLS Path Modeling-ARIMAx). The results showed that the three latent variables (economic, social, and environmental) were found to be causal related. From the PLS Path Modeling-ARIMAx (1,1,1), it is characterized as the best linear unbiased estimator (BLUE) with highest performance, where mean absolute percentage error (MAPE) equals to 1.55%, and root mean square error (RMSE) equals to 1.97% upon comparing them to other models. If the government implements this model to define a new scenario policy by stipulating future total energy consumption (2020-2039) below the national carrying capacity, with minimal error correction mechanism and great impact on model relationship, the future CO2 emission (2020-2039) is expected to drop a growth rate continuously. When a new scenario policy is determined, CO2 emission was found to increase at a growth rate of only 8.95% (2020/2039) or by 78.99 Mt CO2 Eq. (from 2020-2039) going below carrying capacity set off at 90.05 Mt CO2 Eq. (from 2020-2039). The result is clearly different in the absence of the new scenario policy. |
