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Purpose The purpose of this paper is to employ an emerging phenomenon in China concerning collaborative carbon emission reduction (CCER) to investigate: first, the coordination of suppliers and manufacturers within supply chains to reduce carbon emissions, and second, the role of governmental policy in facilitating this process. Design/methodology/approach This paper draws upon evolutionary game theory to develop an evolutionary game model for CCER for suppliers and manufacturers within supply chains. This includes a detailed analysis of the evolutionary direction and process in different areas, both with, and in the absence of, governmental subsidies. Findings The results demonstrate that CCER is path dependent and that its evolutionary process is influenced by the following four factors: the initial status within supply chains; the cost; the additional benefit; and the investment risk related to CCER. The research also reveals that the reward provided by manufacturers is rational over the long term, due to the excessive cost of incentives potentially preventing the implementation of CCER. Originality/value This study represents the first attempt to investigate CCER within supply chains through the application of an evolutionary game-theoretic model. The investigation of multiple factors in the model will deepen understanding of the collaborative role required for the carbon emission reduction.

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In the inventory financing business, an optimal impawn rate (loan-to-value ratio) can help the inventory financing providers (IFPs, she) maintain competitiveness in the inventory financing market. However, the literature has been silent on how IFPs can optimise the business through the optimisation of the impawn rate. This study examines the role of the optimal impawn rate in the inventory financing business. The key to setting the optimal impawn rate is first evaluating default probability and then incorporating this into the profit function. We use a data-driven approach to explore the copula model in setting the optimal impawn rate. Through numerical analysis, we find that the Clayton canonical vine copula has a better performance for the prediction of default probability than the multivariate normal distribution (MVN) and can thus be used to evaluate default probability. In addition, we uncover that setting multiple impawn rates for different collaterals allows inventory financing to yield a higher profit. Further, although the interest rate, industrial impawn rate, and optimal impawn rate have strong effects on inventory financing profit, interestingly, the relationship between them is marginally diminishing.