The dual carbon target has been the focus of domestic attention since it was proposed. At the same time, the digital economy based on new technologies such as the Internet and big data has become an important engine to boost China’s high-quality economic development. While the digital economy is promoting the development of the urban economy, can it also promote the low carbon development of cities in China? Based on panel data and multiple econometric models of 26 cities in the Yangtze River Delta urban agglomeration from 2006 to 2020, this paper empirically examines the impact of digital economy development on urban carbon emissions. The results show that the development of the digital economy can not only reduce the carbon emission intensity of this region but also effectively reduce the carbon emission intensity of surrounding areas. Therefore, it is necessary to further promote the construction of digital economy in the urban agglomeration, improve the inclusiveness and flexibility of the implementation of digital economy development strategy, and improve the construction of information infrastructure to give full play to the role of the digital economy in improving carbon emissions in urban agglomeration.

The development of transportation infrastructure can ensure the strong recovery and reconstruction function of a city, and it is an important way to build a resilient city. Studying the impact of the transportation infrastructure level on urban resilience is related to the future development of a city. Based on panel data for China’s three major urban agglomerations from 2008 to 2019, this paper uses the spatial econometric model to explore the spatial spillover effect of transportation infrastructure on urban resilience. The results show that, due to its spillover effect, intra-regional transportation infrastructure promotes the urban resilience of cities around Beijing–Tianjin–Hebei and the Pearl River Delta, while it only promotes the urban resilience of local cities in the Yangtze River Delta. Inter-regional transportation infrastructure not only inhibits the local urban resilience of Beijing–Tianjin–Hebei but also reduces the urban resilience of surrounding cities. However, the impact on the Yangtze River Delta and the Pearl River Delta is not obvious. To promote the overall resilience level in three major urban agglomerations in China, this paper argues that it is urgently required to improve the quality of urban road traffic facilities and optimize the structure of intercity transportation to promote the development of transportation infrastructure and urban resilience. The implementation of several policies is recommended to efficiently improve the transportation infrastructure and urban resilience in these three major urban agglomerations in China.

Green development and the high-quality economic growth model have replaced the extensive growth model in an effort to reduce the large amounts of energy consumption and pollution emissions. Green total factor productivity has become an important indicator to more accurately measure the quality of economic growth. Transportation infrastructure is a fundamental component that may effectively integrate regional resources, increase regional cooperation, and encourage the sensible use of resources, and is a key factor in increasing productivity. At present, transportation infrastructure should focus on the speed of construction and the quality level, expand the radiation range of the transportation system, improve the service level of transportation facilities, and promote the spatial coordination between transportation facilities and resources and the environment in each province. Therefore, it is of great significance to study the spatial effect of the transport infrastructure on green total factor productivity in order to understand the role of transport infrastructure and its impact on the quality of economic growth. In this study, the slacks-based measure (SBM) model and the global Malmquist–Luenberger (GML) index were used to calculate the green total factor productivity of 30 provinces in China, while the spatial effect of the transportation infrastructure on green total factor productivity was investigated based on the spatial Durbin model. At the national level, road density, railway density, and road service level show positive spillover effects. The railway service level inhibits the growth of green total factor productivity, and there is obvious regional heterogeneity in transport infrastructure construction in eastern, central, and western regions. Therefore, in the process of transportation infrastructure construction, we should not only pay attention to the scale of expansion but also pursue the quality of service. At the same time, measures such as the flow of talent and the introduction of foreign capital within the region should be constantly coordinated to promote the improvement of green total factor productivity and achieve a win–win situation between economic growth and environmental protection.

A common perception is lowering the environmental consequences of firms’ supply chain activities is a costly idea that poses a challenge to the corporate world. This study aimed to examine the relationship between green supply chain management (GSCM) and corporate performance among listed firms in Pakistan, using the general panel method of moments (GMM) and ANOVA techniques. At the same time, the Granger causality technique provides robust results. The study focused on manufacturing firms, covering periods from 2009 to 2020. The study engaged a modified balanced scorecard framework to adopt five metrics of corporate performance, namely, gross profit ratio, net profit ratio, customer dimension, learning growth dimension, and efficiency dimension. The study incorporated the two measures of the GSCM initiative and two control variables. The findings from the panel GMM estimates reveal that GSCM positively and negatively impacted the five corporate performance metrics explored. ANOVA results indicate significant differences in customer satisfaction, profitability, and efficiency performance metrics among the top and low GSCM practicing corporations. On the other hand, Granger causality results specify a moderate causal association between GSCM implementation and firm performance in Pakistan. Implying that poor GSCM practice may not yield the expected benefits, instead, conscientious efforts should be put in place to ensure that practicing GSCM initiative should be effectively carried out.

Purpose: The current study aims to achieve two targets. First, examine empirically that whether corporate managers use tax avoidance to influence short-term profitability? Second, investigate the impact of tax avoidance on the value of firms. The tax accounts provide the opportunity to influence temporary/permanent profitability but empirical studies overlooking this matter, particularly in emerging economies.Design/methodology/approach: First, the authors identified unexpected fluctuations of tax avoidance and then examine whether it impacts the profitability signal and firms' value? The unbalanced panel data of 189 non-financial firms for the period 2000–2018 are used for empirical analysis. The estimation biases and results consistency are verified by using two different econometric models including generalized least square and two-stage least squareFindings: The study identifies that managers manipulate the profitability signal through tax avoidance. Tax avoidance practices help in earning management and earning smoothing to avoid negative signals in the stock market. In line with the behavioral finance view, tax avoidance has a positive impact on current stock returns because investors focus on profitability without a detailed screening of cash flows.Originality/value: A limited number of studies investigate the use of tax avoidance for manipulation of the short-term earning signal. Identifying gaps and limitations in the literature, this study provides invaluable insights into tax avoidance and its association with the profitability and value of firms. The findings are important for investors, managers and policymakers in making portfolio decisions and corporate policies.