Scholars usually unconsciously employ the Tapio decoupling model with a static perspective and results-oriented philosophy, which often leads to errors. Therefore, we propose an improved Tapio decoupling model that adopts a dynamic perspective and process-oriented philosophy. Taking China, the world's largest carbon emitter, as a case study, we investigate the decoupling of its provincial industrial carbon emissions (ICE) from industrial value-added (IVA) during 2005–2020 using both the conventional and improved decoupling model, followed by a comparative analysis of their results. Our findings are as follows: (1) Both China's ICE and IVA exhibited a general upward trend during the study period, with non-linear annual ICE and IVA variations observed across all provinces. (2) Overall, China's provincial IVA increasingly decoupled from ICE, with some provinces achieving a strong decoupling state during 2015–2020; however, from the long-term perspective spanning the entire study period, most provinces remained in a weak decoupling state. (3) The conventional decoupling model tends to yield overly optimistic results in empirical study of China, with the decoupling indices during the periods of 2005–2010 and 2005–2020 determined by the conventional model even had significant statistical difference between those determined by the improved model. (4) To ensure equity, differentiated carbon reduction policies should be tailored to each province, considering factors such as absolute carbon emissions, short-term decoupling states, and long-term decoupling states. The improved Tapio decoupling model is proposed as a valuable framework for researchers engaged in related studies.