## 5 Conclusions  
This study investigates the relationship between economic growth and energy consumption, utilizing the EKC theory. It utilizes data from government agencies and satellite sources to identify additional factors influencing energy consumption. Additionally, we employed hot spot analysis to identify clusters of energy consumption per capita across various regions. We also used the Generalized Additive Model (GAM) to evaluate the combined effects of influential factors. This analytical approach enhances the interpretability of the SDPD IV results, providing deeper insights. These techniques offer greater value for policy implications than relying solely on the SDPD IV model. The study results indicate that energy consumption in Thailand is spatially clustered, meaning it tends to spill over into nearby provinces and is concentrated in specific regions. Factors that positively influence energy consumption include GPP per capita, population density, and road density. The EKC analysis also reveals a U-shape relationship between GPP per capita and energy consumption in the BKK&VIC, CE, EA, WE, and NE regions. In the early stages of economic growth, energy consumption tends to decrease as GPP per capita increases. However, once the economy surpasses a certain threshold, further increases in GPP per capita lead to higher energy consumption. As shown in Appendix G, Table 10, these regions are experiencing continuous increases in energy consumption, reflecting inefficient energy use and contributing to various environmental problems due to the reliance on non-renewable sources for that generation. For reference, the average GRP per capita in 2022 was USD 40,857 for the BKK&VIC, CE, EA, and WE regions, and USD 2724 for the NE region. Moreover, areas with favorable climate conditions, well-developed infrastructure, and high levels of economic activity tend to exhibit higher energy consumption per capita. For policy implications, Thailand's current environmental policies are largely informal and decentralized. Therefore, the country should develop rigorous, long-term plans for efficient and sustainable energy use, similar to those implemented in developed countries [43], particularly in regions with high-energy-consumption clusters and in provinces characterized by high levels of urbanization, economic activity, and industrial production (such as BKK&VIC, CE, EA, WE, and NE) that align with the results of this study. Moreover, policies should promote the increased use of renewable energy sources, such as solar, wind, hydro, geothermal, and biomass, to reduce dependence on electricity generated by conventional government-operated systems. Since electricity in Thailand is primarily generated from fossil fuels and natural gas, a significant amount of electricity is produced to meet population demand and support economic development. As a result, this leads to the release of large quantities of pollutants that harm the environment. The use of renewable energy can help alleviate the challenges associated with high energy consumption and mitigate environmental problems related to electricity production [84; 85; 86; 87]. Additionally, the transfer of advanced technology from developed countries through investment by multinational companies in Thailand will enable the country to acquire more modern, energy-efficient, and environmentally friendly technologies. Future studies should explore alternative methods to identify strategies for efficient energy consumption. Forecasting future energy consumption trends is crucial and should be included to better understand how energy demand may evolve over time. Moreover, the application of machine learning algorithms to examine the relationship between economic growth and energy consumption is expected to become increasingly important in the future. This approach enables a comparison of the accuracy between econometric analysis methods and machine learning techniques, ultimately leading to more concrete findings.