The COVID-19 pandemic has reshaped regional economic landscapes. However, academic research has not yet sufficiently addressed how external investment in regions has been transformed under the impact of the COVID-19 pandemic and its influence on industrial evolution patterns. In this paper, we integrate insights from economic geography literature and develop a conceptual framework to further theorise the relationship between external shocks, changes in the industrial heterogeneity of investment from regional core cities, and local industrial dynamics. Using the COVID-19 pandemic and the Yangtze River Delta region as a case study, we employ an intensity-based Difference-in-Differences (DID) approach and draw on business registration and enterprise investment databases to estimate the impact of the pandemic shock on the evolution of local industrial dynamics between 2018 and 2024. Our findings indicate that after the core cities underwent the shock of the COVID-19 pandemic, the path dependence of industrial evolution in their surrounding areas significantly increased. The stronger the economic linkage with Shanghai, the more pronounced this effect. However, this impact also exhibits spatial heterogeneity across the Yangtze River Delta, associated with regional industrial division of labour and cooperation. This paper offers an innovative examination of how changes in the industrial heterogeneity of investment inflows from core cities—specifically, dimensions such as relatedness to local industries, industrial upgrading, and diversification—shape the mechanisms of local industrial evolution following the COVID-19 shock. Our findings offer important implications for regional development and adaptive responses in the post-pandemic era.

Regional carbon emission efficiency has differentiated characteristics under different economic development stages and patterns, and it is significant to identify such characteristics and formulate corresponding policies for high-quality regional development. Based on input-output data related to economic development and energy consumption, a comprehensive evaluation model of Super-SBM and Malmquist-Luenberger (ML) index was constructed to evaluate the spatial and temporal changes and driving forces of CEE, on the basis of which a proposal for collaborative carbon emission reduction zoning is proposed. The results indicated that the carbon emission efficiency (CEE) of the YRD shows a fluctuating upward trend with obvious spatial agglomeration characteristics, and the changes in CEE were closely related to the stage of economic development. The annual average CEE value during each period exhibited positive changes, indicating that economic development gradually shifted toward low carbonization. Moreover, the improvement of CEE gradually shifted from being driven by efficiency change to being driven by technological change. Finally, based on the carbon emissions and CEE characteristics of different cities, a carbon-neutral synergistic path is proposed in terms of industrial transformation, green development and technological support.