An integrated approach to modeling the influence of critical factors in low-carbon technology adoption by chemical enterprises in China.

Adopting low-carbon technology has become a critical method for enterprises to reduce carbon emissions and combat global warming. However, the willingness of high-energy-consuming and high-emission enterprises, such as those in the chemical industry, to adopt this technology is not high. Therefore, how to effectively stimulate these enterprises to develop and apply low-carbon technology has become an urgent challenge. This paper adopts a three-phase integrated approach to explore the influence of critical factors in the adoption of low-carbon technology by chemical enterprises. Firstly, based on the technology-organization-environment framework, the main influencing factors are identified. Critical influences are then extracted by the interpretive structural modeling-analytic network process method. Finally, the dynamic changes of key factors are simulated and analyzed using an evolutionary game model based on the realistic data of Sinopec Shanghai Petrochemical Co., Ltd. And Industrial and Commercial Bank of China. The findings identify adoption cost, adoption benefit, environmental regulation, and green credit as four key factors of low-carbon technology adoption. Adoption probability is related negatively to adoption cost but positively to adoption benefit, government subsidies and penalties, and green credit. Adoption probability is related to adoption benefit and green credit; it is least sensitive to adoption benefit and most sensitive to green credit. That is, relying only on the enterprises' own efforts and without the support of subsidies and green credit, the adoption process will be very long. When green credit works, the enterprise can use technology without subsidies and penalties. Moreover, the adoption probability has a higher sensitivity to penalties than to subsidies. In other words, the enterprise will only adopt and apply the relevant technology when subsidies are large, whereas strengthening penalties can rapidly increase the adoption probability. These findings provide a valuable reference for enhancing enterprises' adoption willingness and establishing an efficient incentive mechanism of low-carbon technology adoption.