| # | Document title | Authors | Year | Source | Cited by |
| 1 | Economic outcomes of rubber-based agroforestry systems: a systematic review and narrative synthesis | Huang I.Y., James K., Thamthanakoon N., Pinitjitsamut P., Rattanamanee N., Pinitjitsamut M., Yamklin S., Lowenberg-DeBoer J. | 2022 | Agroforestry Systems | 45 |
| 2 | A challenge of incentive for small hydropower commercial investment in Thailand | Supriyasilp T., Pinitjitsamut M., Pongput K., Wanaset A., Boonyanupong S., Rakthai S., Boonyasirikul T. | 2017 | Renewable Energy,
111, pp. 861-869 | 8 |
| 3 | The techno-economic feasibility of providing solar photovoltaic backup power | Pillai G., Hodgson J., Insaurralde C., Pinitjitsamut M., Deepa S. | 2016 | International Symposium on Technology and Society, Proceedings,
2016-December, pp. 62-67, 7764051 | 3 |
| 4 | Dynamic Price Transmission from SHFE to Thai Rubber Markets: A Cointegration–ECM and Machine-Learning Analysis | Pinitjitsamut M. | 2026 | Economies,
14(1), 9 | 2 |
| 5 | Multi-Scale Forecasting of Natural Rubber Prices Using VMD-Augmented BiLSTM: A Hybrid Architecture Ablation Study | Pinitjitsamut M. | 2026 | Forecasting,
8(3), 43 | 1 |
| 6 | Oil Price Transmission, Synthetic-Rubber Substitution, and Inventory Regimes in China–Thailand Rubber Markets | Pinitjitsamut M. | 2026 | Economies,
14(6), 222 | 0 |
| 7 | Post-Access Barriers to Digital Market Reach: Motivational and Capability Non-Adoption in Thailand’s Near-Saturated Digital Economy | Pinitjitsamut M. | 2026 | Journal of Theoretical and Applied Electronic Commerce Research,
21(7), 199 | 0 |
| 8 | A Modular Knowledge-Extraction Framework for Deep Learning Forecasts of Multi-Tier Commodity Prices | Pinitjitsamut M. | 2026 | Machine Learning and Knowledge Extraction,
8(7), 185 | 0 |
| 9 | Timing commodity sales under tail-risk control: State-dependent rules and global price signals in rubber markets | Pinitjitsamut M. | 2026 | International Review of Economics and Finance,
111, 105622 | 0 |
| 10 | Decomposing the Welfare Consequences of Population Aging in Thailand: Labor, Saving, and Fiscal Channels in a Multi-Household CGE Model | Pinitjitsamut M. | 2026 | Economies,
14(4), 131 | 0 |
| 11 | Development of a forecasting model for global rubber demand and supply using LSTM neural networks combined with two-stage least squares (2SLS) | Pinitjitsamut M. | 2026 | Journal of Rubber Research | 0 |
| 12 | Geopolitical Shock Transmission in Thailand: A Narrative SVAR–CGE Framework for Macroeconomic and Distributional Analysis | Pinitjitsamut M. | 2026 | Economies,
14(6), 209 | 0 |
| 13 | Household energy consumption and its demand elasticity in Thailand | Pinitjitsamut M. | 2012 | International Journal of Energy Technology and Policy,
8(3-6), pp. 286-304 | 0 |