Search Results (75)

The goal of this scientific study is to clarify whether and how digital–intelligent integration contributes to urban carbon efficiency and to identify the conditions under which this contribution becomes nonlinear and policy-relevant. Focusing on 39 prefecture-level cities in the middle reaches of the Yellow River Basin during 2011–2022, we adopt an integrated measurement–modelling approach that combines efficiency evaluation, machine-learning interpretation, and dynamic–spatial validation. Specifically, we construct two super-efficiency DEA indicators: an undesirable-output SBM incorporating CO₂ emissions and a conventional super-efficiency CCR index. We then estimate nonlinear city-level relationships using XGBoost and interpret the marginal effects with SHAP, while panel vector autoregression (PVAR) and spatial diagnostics are employed to validate the dynamic responses and spatial dependence. The results show that digital–intelligent integration is positively associated with both carbon-related and conventional efficiency, but its marginal contribution is strongly conditioned by human capital, urbanisation, and environmental regulation, exhibiting threshold-type behaviour and diminishing returns at higher digitalisation levels. Green efficiency reacts more strongly to short-run shocks, whereas conventional efficiency follows a steadier improvement trajectory. Heterogeneity across urban agglomerations and evidence of spatial clustering further suggest that uniform policy packages are unlikely to perform well. These findings highlight the importance of sequencing and policy complementarity: investments in digital infrastructure should be coordinated with institutional and structural measures such as green finance, environmental standards, and industrial upgrading and place-based pilots can help scale effective digital applications toward China’s dual-carbon objectives. The proposed framework is transferable to other regions where the digital–climate nexus is central to smart and sustainable urban development. Full article

Smart cities and innovative cities are important strategies for enhancing city resilience. By using panel data from 285 Chinese cities from 2009 to 2022 and examining “dual pilot” cities via the concurrent implementation of smart and innovative cities as a quasi-natural experiment, this study employs the difference-in-differences model to examine the impact of the “dual pilot” initiative. Furthermore, quantitative assessments are conducted from multiple perspectives through heterogeneity analysis, mechanism analysis, and spatial spillover effect analysis. The findings are as follows: “Dual pilot” cities have the ability to enhance city resilience and have a synergistic effect. The effect on city resilience is significantly greater than that of the “single pilot” design, but policy synergy effects are sensitive to the policy’s implementation sequence. A mechanism test reveals that innovation and development levels and industrial structure upgrading are important paths for “dual pilot” cities to boost city resilience. The heterogeneity study demonstrates that the positive impact of “dual pilot” cities on city resilience is statistically significant only in ordinary cities; non-resource-dependent cities; and cities across eastern, central, and western regions. A spatial spillover analysis demonstrates that “dual pilot” cities exert positive spillover effects on both the implementing cities and their neighboring areas. The above conclusions can serve as a source of reference and inspiration for building “resilient cities”. Full article

Driven by carbon neutrality policies, the cumulative issuance volume of the global green bond market has surpassed $2.5 trillion over the past five years, with China, as the second largest issuer, accounting for 15%. However, there exists a yield difference of up to 0.8% for bonds with the same credit rating across different policy regions, and the premium level fluctuates dramatically with market cycles, severely restricting the efficiency of green resource allocation. This study innovatively constructs a Bayesian hierarchical spatiotemporal model framework to systematically analyze pricing deviations through a three-level data structure: the base level quantifies the impact of bond micro-characteristics (third-party certification reduces financing costs by 0.15%), the temporal level captures market dynamics using autoregressive processes (premium volatility increases by 50% during economic recessions), and the spatial level reveals policy regional dependencies using conditional autoregressive models (carbon trading pilot provinces and cities form premium sinkholes). The core breakthroughs are: 1. Designing spatiotemporal interaction terms to explicitly model the policy diffusion process, with empirical evidence showing that the green finance reform pilot zone policy has a radiation radius of 200 km within three years, leading to a 0.10% increase in premiums in neighboring provinces; 2. Quantifying the posterior distribution of parameters using the Markov Chain Monte Carlo algorithm, demonstrating that the posterior mean of the policy effect in pilot provinces is −0.211%, with a half-life of 0.75 years, and the residual effect in non-pilot provinces is only −0.042%; 3. Establishing a hierarchical shrinkage prior mechanism, which reduces prediction error by 41% compared to traditional models in out-of-sample testing. Key findings include: the contribution of policy pilots is −0.192%, surpassing the effect of issuer credit ratings, and a 10 yuan/ton increase in carbon price can sustainably reduce premiums by 0.117%. In 2021, the “dual carbon” policy contributed 32% to premium changes through spatiotemporal interaction channels. The research results provide quantitative tools for issuers to optimize financing timing, investors to identify cross-regional arbitrage, and regulators to assess policy coordination, promoting the transformation of the green bond market from an efficiency priority to equitable allocation paradigm. Full article

To achieve the “dual carbon” goals, green construction technologies (GCTs) are in transition from pilot projects to full-scale promotion in the Chengdu–Chongqing Economic Circle. Previous studies have largely overlooked the quantitative analysis of parameters influencing stakeholder decision-making and the consideration of risk preferences in the process of GCTs of application. Based on evolutionary game and prospect theory, this study establishes a tripartite evolutionary game model involving the government, owners, and constructors. Through model derivation and numerical simulation, it analyzes the strategic evolution and parameter sensitivity of each stakeholder at different lifecycle phases of GCTs. Results uncover a three-stage path: strategy adjustment range, fast convergence range, and slow convergence range. Government funds achieve peak efficiency in the fast convergence range. Owners react most strongly to incentives, contractors to cost changes. State-owned enterprises rely on policy signals, whereas private enterprises focus on market returns and risk expectations. Targeted promotion mechanisms and policy recommendations are proposed, offering a theoretical basis and practical route for precise government intervention and low-carbon transformation of the construction industry. Full article

Rapid urbanization has intensified resource and population agglomeration while exacerbating urban-rural disparities. To address the long-standing dual structure, China advocates urban-rural integrated development (URID) to achieve common prosperity. However, the long-term evolutionary patterns and explanatory mechanisms of URID remain insufficiently explored, particularly at the county (district)-level in western China. This study constructed an entropy-weighted TOPSIS evaluation system combined with kernel density estimation and an optimal parameters-based geographical detector (OPGD) model to analyze the spatiotemporal evolution and explanatory mechanisms of URID in 26 counties (districts) of the Xi’an metropolitan area from 2010 to 2022. The results showed that: (1) URID levels increased steadily over the study period, forming a pronounced core-periphery gradient with faster improvement in national URID pilot counties. (2) Factor associations evolved from being dominated by a few dimensions to multidimensional coupling. Socioeconomic and geographical factors remained dominant and relatively stable, demographic influences were clearly stage specific, and the interaction between forest coverage and economic variables weakened over time. (3) Enhancing regional transport accessibility, optimizing land use efficiency, and fostering positive population-industry interaction are key pathways for promoting URID in the study area. Methodologically, this study introduces a “significance testing followed by threshold verification” logic into the OPGD model, refining the parameter-setting process and improving the robustness and q-value of factor detection. The findings enrich URID theory, provide county (district)-scale evidence for western China, and offer policy implications for optimizing factor allocation and promoting coordinated regional development. Full article

Under China’s “dual carbon” targets and deepening global climate governance, this paper investigates whether and how corporate green transformation (GTF) improves carbon performance (CP). Using panel data on Chinese A-share listed firms from 2008 to 2023 and multiple causal identification strategies (fixed effects, RD, DID and PSM), we find that GTF significantly enhances CP, with stronger marginal effects for firms with poorer initial carbon performance. Mechanism analyses show that carbon disclosure (CD) acts as a positive mediator in the GTF–CP nexus, whereas executives’ green perception (EGP) exerts a short-term suppressing effect. Policy analyses further indicate that the 2012 pilot emissions trading schemes and the 2021 national carbon market amplify the positive impact of GTF on CP, but local “compliance traps” around industry medians suggest strategic use of allowance trading. The study integrates EGP and CD into a cognition–disclosure framework linking GTF and CP and provides evidence on the emission-reduction effects of GTF under evolving carbon policies, with implications for carbon market design and corporate low-carbon governance. Full article

Financial supply side structural reform (FSSR) serves as a key for advancing the low-carbon transformation of industrial energy (LTIE) and supporting the dual carbon strategic goals. By using provincial panel data from China for the period of 2008–2022 and leveraging the national financial comprehensive reform pilot zones as a quasi-natural experiment, this study uses the difference-in-differences method to examine empirically the effect of FSSR on the LTIE and the underlying mechanisms. Research findings indicate that, first, FSSR can significantly advance the LTIE, which remained unchanged after other policies, omitted variables, and other potential influencing factors were controlled. Second, the mechanism tests indicate that FSSR can drive the LTIE by increasing green financial support, fostering green industrial development, and promoting green technological innovation. Third, the heterogeneity tests reveal that the benchmark effect is pronounced in regions with weak environmental regulation and a low level of financial development. This study provides theoretical and empirical evidence to understand the crucial role of FSSR in advancing the LTIE and insights for relevant policy formulation. Full article

This article presents a novel methodology for assessing the visibility and reachability of cultural heritage objects within urban structures, tested through a pilot study in Kaunas New Town (Naujamiestis), Lithuania. While heritage protection policies usually emphasize architectural composition, details, and external visual protection zones, interior urban views and functional spatial dynamics remain underexplored. Building upon Space Syntax theory and John Peponis’s concepts of distributive and correlative situational codes, this study integrates detailed visibility analysis with graph-based accessibility modeling. Visibility was quantified through a raster-based viewshed analysis of building footprints and street-based observation points, producing a normalized visibility index. Reachability was examined using a new graph indicator based on the ratio of reachable polygon area to perimeter (A²/P), further weighted by the area of adjacent buildings to reflect the potential for urban activity. Validation against independent datasets (population, companies, and points of interest) confirmed the superior explanatory power of the proposed indicator over traditional centralities. By combining visibility and reachability in a bivariate matrix, the model provides insights into heritage objects’ dual roles as landmarks, everyday hubs, or hidden sites, and offers predictive capacity for evaluating urban transformations and planning interventions. Full article

Using Chinese A-share listed firms from 2011 to 2023, this study develops and tests a dual-engine framework in which digital transformation and green technological innovation constitute two core transmission channels through which digital finance improves corporate ESG performance. Based on the FinTech Innovation Regulatory Pilot Policy in China, we implemented a staggered DID model for causal identification. Then, we further conducted a series of robustness checks, including Bartik IV, to address residual endogeneity concerns. We found that (1) digital finance can enhance corporate ESG performance, with particularly strong effects on the environmental and governance dimensions. (2) Digital transformation and green technological innovation are the primary mechanisms through which digital finance improves ESG performance. (3) The interaction between digital transformation and green technological innovation forms mutually reinforcing “dual engines” that amplify the benefits of digital finance for ESG performance. (4) Higher institutional investors’ shareholding ratio strengthens the positive effect of digital finance on corporate ESG performance, consistent with the role of external governance. (5) The enabling effect of digital finance is more pronounced among firms in the introduction, growth, and maturity stages of the corporate lifecycle, as well as among firms located in eastern and central regions and in non-heavy-polluting industries. This study uncovers the internal logic by which digital finance advances corporate sustainability through technological upgrading and environmental innovation, and it provides theory-driven and empirically grounded evidence for building integrated ESG governance frameworks. The results offer actionable insights for firms worldwide pursuing the twin goals of digitalization and green development under carbon neutrality targets. Full article

Currently, corporate innovation has become a key driver of economic growth and a critical factor in enhancing core competitiveness, which is of great significance for achieving sustainable economic development. Our research is based on panel data from A-share-listed manufacturing companies in China between 2012 and 2022, employing a multi-time point Difference-in-Differences (DID) model and a DID model extended with the Dual Machine Learning (DML) estimation method for empirical testing. We investigate the underlying mechanisms and analyze corporate heterogeneity. The findings reveal that the pilot policy of industry–finance collaboration has a significant positive impact on corporate innovation, particularly for companies facing severe financing constraints, intense market competition, and relatively small scales. Additionally, the study finds that the pilot policy promotes corporate innovation through three channels: reducing information asymmetry, increasing local government fiscal subsidies, and enhancing corporate access to bank credit. Finally, we provide recommendations for the government, enterprises, and financial institutions to further leverage and enhance the effectiveness of the industry–finance collaboration pilot policy in boosting corporate innovation. Full article

As a new engine for promoting the high-quality development of China’s foreign trade, digital trade provides new opportunities for enterprises’ low-carbon transition. Based on samples of export industrial enterprises listed in China from 2010 to 2023, this paper uses the digital trade policy represented by the cross-border e-commerce (CBEC) comprehensive pilot zone as a quasi-natural experiment and employs a multi-period difference-in-differences (DID) model to empirically analyze the policy effect of digital trade development on firms’ carbon emission intensity. This research finds that (1) digital trade policies represented by the pilot policy can significantly reduce firms’ carbon emission intensity and (2) the pilot policy can achieve the emission intensity reduction effect through dual paths of “internal innovation deepening” and “external environment optimization”. The internal innovation deepening refers to the green awareness formation and green production implementation of enterprises. External environment optimization refers to financial support resources for enterprises and institutional safeguards for innovation rights of enterprises. (3) Further analysis indicates that the policy effects are more pronounced in firms with higher risk preference, with larger scale, in heavily polluting and high-tech industries, and in the central and northeastern regions. Additionally, the policy demonstrates synergistic effects with the Belt and Road Initiative and exhibits significant spatial spillover effects, benefiting neighboring non-pilot areas. Full article

As global climate change intensifies, achieving the dual goals of economic efficiency and low-carbon development has become a pressing challenge. Using panel data for 269 Chinese cities from 2010 to 2021, based on their carbon emission efficiencies (CEEs) measured using the DEA-SBM model, a staggered difference-in-differences (SDID) model is employed to identify the policy impacts, which is further extended into a triple-difference (DDD) framework to examine the causal impact of the dual-pilot policy. The results show that (1) China’s CEE has improved gradually but remains relatively low, with significant regional disparities. (2) Empirical results indicate that the dual-pilot policy leads to a significant improvement in CEE, raising it by approximately 4.06%. The positive impact is particularly pronounced in cities characterized by more advanced industrial structures and stricter environmental regulatory frameworks. (3) Industrial upgrading and green technological innovation serve as key mediating channels, contributing 2%, 7%, and 10.7% to the total mediation effect. (4) The positive impacts are particularly evident in eastern, large-scale cities. These results underscore that the integration of digitalization and low-carbon initiatives serves as an effective pathway to improving CEE. Therefore, policymakers are encouraged to further advance the dual-pilot programs, foster green technological innovation, and accelerate industrial upgrading toward a digitally empowered and low-carbon development model. Full article

China’s ecological civilization construction and the “dual-carbon” strategy highlight the urgent need for coordinated governance of pollution and carbon reduction. Whether data elements and artificial intelligence integration (DEAII) can serve as a new pathway to achieve this goal remains to be explored. This study investigates the dynamic effects of DEAII on pollution and carbon reduction using panel data from 275 prefecture-level cities in China during 2009–2021. An evaluation index system and a modified coupled coordination degree model are developed to measure DEAII, while an ordinary least squares (OLS) fixed effects model is applied to assess its impacts. The results show stage-specific effects of DEAII, including the phenomenon of “pollution reduction but carbon increase”. Mechanism analysis indicates that improvements in green energy technology efficiency (GETE) and optimization of urban spatial structure are the main channels for achieving synergy. Heterogeneity analysis reveals that although government attention to environmental protection strengthens pollution control, it has limited effects on short-term carbon reduction. Moreover, the carbon reduction benefits of green energy transition pilots exhibit a time lag, and the “digital intelligence divide” generates negative spatial spillovers. These findings provide new evidence for the dilemma of “environmental protection without low-carbon benefits” and suggest policy directions for enhancing the coordinated governance of pollution and carbon reduction. Full article

Macroprudential policy, as an important instrument for counter-cyclical regulation, plays a crucial role in enhancing urban economic resilience. Based on this, this paper empirically examines the influence of macroprudential policy on urban economic resilience and its optimization paths using data from 284 prefecture-level cities in China from 2011 to 2023. The research findings indicate that macroprudential policy significantly enhances urban economic resilience, and the conclusion still holds after various robustness tests. Further analysis reveals that the main transmission channels include stimulating digital finance development, promoting industrial structure upgrading, and deepening regional integration. Notably, this effect is particularly pronounced in smart cities, big data pilot zones, and cities with less fiscal pressure. Additionally, the test results of spatial spillover effects show that the direct effect of macroprudential policy on the economic resilience of cities is relatively significant, while the indirect effect is relatively weak. Finally, empirical tests have proved that the improvement of urban economic resilience can further drive regional innovation capability. This study provides empirical support and theoretical references for improving China’s “dual-pillar” regulatory framework and enhancing urban economic resilience. Full article

Pilot policies are key determinants of urban ecological resilience, while the corresponding results are inconsistent. Moreover, existing research on the synergistic effects of policies on ecological resilience remains insufficient. Thus, this study selects low-carbon pilot policies and smart city pilot policies to explore the possible channels through which they affect ecological resilience. Consequently, using the sample data of China’s prefecture-level cities during the period of 2005–2022, we employ a multi-period difference-in-differences approach and two-step regression to examine the relationship between dual pilot policies and ecological resilience. We find that dual pilot policies have a significant positive impact on ecological resilience, and the conclusion is still held after a series of robustness tests. We also find that regional and population size heterogeneity effects exist. Furthermore, the sequences of pilots significantly influence ecological resilience, where the sequence of implementing low-carbon pilot programs earlier than smart city pilot programs has a greater impact on ecological resilience. Finally, the dual pilot policies enhance ecological resilience through channels of technological innovation and industrial structure upgrading. Overall, this study reveals the relationship between policies and ecological resilience, providing policy insights for building resilient cities. Full article