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With refineries contributing 68% of CO₂ emissions from stationary combustion sources alone, smart technologies and the circular economy (CE) model for resource loop optimization can be a solution for carbon neutrality, especially within petroleum. Thus, this study aims to explore energy conservation by green technology improvement as a CE strategy for resource loop optimization and digital incorporation to maximize reprocessing lead ability rate and carbon-neutral benefits.

A game theory approach with Stackelberg equilibrium is considered under government cap-and-trade regulation to stimulate green technology improvement. The refinery acts as a Stackelberg leader and invests in green technology and the retailer as the Stackelberg follower, collects end-of-life lubricants against refund price and offers a two-part-tariff contract to the manufacturer having a significant role in smart technologies.

First, green technology improvement is directly influenced by the reprocessing capability and refund price and digital technologies are significant to consider. Second, a two-part-tariff contract coordinates the supply chain for limited reprocessing capability by the retailer. Lastly, the government can effectively manipulate the development of green technology by changing the permit price depending on the intentions.

The primary limitation is this study has focused on the petroleum sector and data was referenced from the oil refineries of a single country.

Overall, this study provides empirical guidance for policymakers on how to leverage energy-efficient smart technologies for lubricant reprocessing, enabling resource optimization as part of a CE strategy in the petroleum industry and advancing sustainable development goals.

The suggested model responds to the contemporary literature related to CO₂ emissions and CE initiatives across the petroleum sector with the extended role of smart technologies and government cap-and-trade regulations.

The objective of this paper is to investigate the impact of the information sharing of the dynamic demand on green technology innovation and profits in supply chain from a long-term perspective.

The authors consider a supply chain consisting of a manufacturer and a retailer. The retailer has access to the information of dynamic demand of the green product, whereas the manufacturer invests in green technology innovation. Differential game theory is adopted to establish three models under three different scenarios, namely (1) decentralized decision without information sharing of dynamic demand (Model N-D), (2) decentralized decision with information sharing of dynamic demand (Model S-D) and (3) centralized decision with information sharing of dynamic demand (Model S-C).

The optimal equilibrium results show that information sharing of dynamic demand can improve the green technology innovation level and increase the green technology stocks only in centralized supply chain. In the long term, the information sharing of dynamic demand can make the retailer more profitable. If the influence of green technology innovation on green technology stocks is great enough or the cost coefficient of green technology innovation is small enough, the manufacturer and decentralized supply chain can benefit from information sharing. In centralized supply chain, the value of demand information sharing is greater than that of decentralized supply chain.

The authors used game theory to investigate demand information sharing and the green technology innovation in a supply chain. Specially, the demand information is dynamic, which is a variable that changes over time. Moreover, our research is based on a long-term perspective. Thus, differential game is adopted in this paper.