Digital twins are now used for more things than before, not only engineering design and maintenance. In many factories, it is being integrated with energy systems, product development tools, and supply chain platforms. However, a factory can be highly digital, yet its business model may remain largely unchanged. This paper examines this problem through three manufacturing cases in Asia: Haier interconnected washing-machine factory in Qingdao, Siemens Chengdu plant, and LG Smart Park in Changwon. Dynamic capabilities theory and natural-resource-based view are used to explain the cases. The analysis mainly looks at what information the twin provides, how managers use this information, what routines are changed, and whether the change affects customer value, delivery activities, or the way economic returns are captured. The three companies do not follow a single path. Haier put digital information into order-driven mass customization. Siemens connects factory and product twins with eco-design and internal testing of solutions. LG first builds flexible production, then some practices are copied to other plants, and later part of this capability is sold to outside customers. The strongest evidence concerns energy, carbon emissions, materials, and waste. Social and governance evidence is more uneven, as it depends heavily on work arrangements, data rules, and management. The cases show that a digital twin alone is not sufficient. It requires complementary investment, organizational change, and sufficiently reliable data; otherwise, low-carbon business model change and ESG outcomes are difficult to confirm. Also, better production efficiency does not always mean better ESG outcomes in the long term.