Search Results (32)

This study investigates the complex and nonlinear interaction between the dual circulation paradigm and high-quality full employment. Moving beyond the limitations of conventional static partial equilibrium frameworks, the analysis conceptualizes this relationship as a system of three interrelated feedback loops. Drawing on system dynamics (SD) theory, a set of nonlinear differential equations is developed, with model parameters calibrated using macroeconomic data from 2010 to 2025. The simulation results yield three main findings. First, international trade, cross-border investment, and technological exchange jointly form a core reinforcing feedback loop that underpins the mutually beneficial interaction between domestic and international circulations. Second, the integrated development of education, technology, and human capital emerges as a critical state variable for overcoming the persistent trade-off between employment quantity and quality. Third, the interplay between horizontal market expansion and vertical technological advancement constitutes a dual driving mechanism that facilitates the system’s transition toward a higher-level equilibrium, with multi-factor interactions generating pronounced nonlinear multiplier effects. Overall, the study provides a quantitative basis for designing adaptive and targeted employment policies within the dual circulation framework. Full article

This article examines the effect of state ownership and regulatory frameworks on internal control weaknesses (ICW) within an emerging economy. Focusing on the Algerian banking sector, we exploit a symmetric pre- and post-regulatory window (2007–2016) surrounding the enactment of Regulation 11-08. Using an asymmetric Gompit panel model on data of 19 Algerian banks, we analyze the interplay between corporate governance mechanisms and regulatory pressures. The empirical results reveal that while state ownership does not significantly affect the prevalence of ICW, the introduction of Regulation 11-08 led to a significant reduction in the weakness. These findings suggest a “substitution effect,” wherein rigorous legal frameworks compensate for the external corporate governance impact, thereby neutralizing the specific impact of ownership structure. This paper provides historically grounded evidence on the efficacy of regulatory reforms, offering valuable insights for policymakers in emerging markets seeking to enhance institutional compliance. Full article

This paper explores how climate risks affect the spillover between cryptocurrency and precious metals markets, given the increased interplay between climate-related threats and financial markets. The dynamic spillovers of the cryptocurrency and precious metals markets are analyzed initially by the TVP-VAR-DY model. Subsequently, it investigates how transition risk and physical risk affect these spillovers using quantile Granger causality (QGC), quantile–quantile regression (QQR), and wavelet quantile regression (WQR), with a particular focus on the differences in the results across the pre- and during-COVID-19 periods. The results show that climate risks significantly affect the spillovers in the cryptocurrency and precious metals markets, and these effects are heterogeneous in nature. Specifically, it is found that, under normal market conditions, both TRI and PRI have the effect of strengthening the spillovers. However, in extreme market states, their influences weaken because of investor distraction. In addition, at extremely low levels of climate risk, both TRI and PRI tend to intensify spillovers, and the impact of PRI is more pronounced. Moreover, during the COVID-19 crisis, climate risks seemed to have a limited effect in the short run, while they were more sustainable in the long run. These findings offer crucial implications for mitigating climate-related systemic risks and fostering a resilient, sustainable financial ecosystem amidst global decarbonization efforts. Full article

This paper explores the dynamic and distributional association between natural gas prices (NGPs) and the green bond market in a sustainable development context. The analysis employs a Quantile-on-Quantile (QQ) approach on monthly data between 2013 and 2025 to capture nonlinear and asymmetric interactions as well as state-dependent interactions between the two markets under varying market conditions. The findings indicate a bilateral intricate relationship. In the short run, NGP rises are likely to have a negative impact on green bond performance, indicating cost impacts and macro-financial risk in traditional energy markets. In the long run, the development of NGP becomes progressively shaped by the rise of sustainable finance together with the stepwise transformation of energy systems toward low-carbon configurations, ultimately bringing about a structural decline in fossil fuel dependence. In contrast, it is observed that the increase in the green bond market has a short-to-medium-term positive impact on NGP, which highlights the significance of natural gas as a transitional fuel in the energy transition. On the whole, the results indicate that, although green bonds are important in supporting sustainable development goals, their interplay with transitional energy markets like natural gas is nonlinear and changes over time. These findings provide key indications on how financial strategies can be realigned to accord with long-term sustainability goals. Full article

In the face of increasingly severe global environmental challenges, corporate environmental information disclosure (CEID) has become a critical link connecting national ecological governance goals with firms’ green development practices. From the perspective of green signaling, this study examines whether government environmental concerns (GEC) in China incentivize CEID and the mechanisms underlying this effect. We theoretically elaborate the transmission pathways and moderating effects of GEC, and measure GEC and CEID indicators using text analysis of local government work reports and corporate annual reports. Based on a series of empirical tests on Chinese A-share listed firms from 2008 to 2023, we find that: (1) GEC can significantly enhance CEID by attracting green investors and fostering greater media scrutiny. (2) Green technological innovation exhibits a masking effect, which reveals a counterintuitive mechanism whereby stringent environmental regulation may divert innovation resources toward pollution control investments. (3) The impact of GEC is positively moderated by external volatility such as climate policy and market uncertainty and internal capabilities such as firms’ digital transformation. (4) Further heterogeneity analysis shows that GEC has a more significant impact on non-state-owned enterprises, enterprises in heavily polluting industries, and those in the mature or declining stage. This study provides a new theoretical lens for understanding the dynamic interplay between institutional pressure and corporate behavioral responses, and offers empirical insights for calibrating the intensity of GEC to maximize incentives for firms to engage in sustainable practices. Full article

Financial time-series prediction remains a significant challenge, driven by market volatility, nonlinear dynamic characteristics, and the complex interplay between quantitative indicators and investor sentiment. Traditional time-series models (e.g., ARIMA and GARCH) struggle to capture the nuanced sentiment in textual data, while static deep learning integration methods fail to adapt to market regime transitions (bull markets, bear markets, and consolidation). This study proposes a hybrid framework that integrates investor forum sentiment analysis with adaptive deep reinforcement learning (DRL) for dynamic model integration. By constructing a domain-specific financial sentiment dictionary (containing 16,673 entries) based on the sentiment analysis approach and word-embedding technique, we achieved up to 97.35% accuracy in forum title classification tasks. Historical price data and investor forum sentiment information were then fed into a Support Vector Regressor (SVR) and three Transformer variants (single-layer, multi-layer, and bidirectional variants) for predictions, with a Deep Q-Network (DQN) agent dynamically fusing the prediction results. Comprehensive experiments were conducted on diverse financial datasets, including China Unicom, the CSI 100 index, corn, and Amazon (AMZN). The experimental results demonstrate that our proposed approach, combining textual sentiment with adaptive DRL integration, significantly enhances prediction robustness in volatile markets, achieving the lowest RMSEs across diverse assets. It overcomes the limitations of static methods and multi-market generalization, outperforming both benchmark and state-of-the-art models. Full article

The concept of green cities promotes efficient utilisation of resources, with urban rooftop farms (URFs) being a key initiative involving a series of actions and decisions between stakeholders and the state. The new public governance discourse (NPGD) emphasises this interplay between the state, the market, and civil society to strengthen collaboration and network-driven social innovation and requires a comprehensive understanding of human/stakeholder behaviour. In this study, we explore the connection between organisational rational choice in URF policy development and social innovation. Through a review of the existing literature on URF policies and a case study of Dhaka, Bangladesh, we investigate the development of a comprehensive policy via participation and collaboration, considering the popularity of URFs and the absence of governing mechanisms in Dhaka. The results suggest that, despite the rising popularity of URFs in Dhaka, existing policies and strategies lack clarity. The review findings suggest that a participatory and co-productive approach is optimal for URF policy formulation. This would require active engagement from community members, local governments, and non-governmental organisations and gaining an enhanced understanding of stakeholder dynamics by testing stakeholder salience and co-production theories for successful URF governance. Full article

The partnership between government and market plays a crucial role in allocating green resources and fostering collaboration across organizations and departments. It integrates diverse knowledge types into the green innovation process and offers multifaceted insights into enterprises’ responses to green governance decisions. However, existing research predominantly examines the interplay among government green governance instruments, with insufficient exploration of the synergistic impacts of government and market in green governance. This study constructs a capacity coupling coefficient model to measure the synergy degree of “government–market” green governance (GMGG). Exploiting a balanced dynamic panel of 28,451 firm-year observations for 3807 Chinese listed companies from 2010 to 2020, we estimate the causal effect of GMGG synergy on corporate green innovation (CGI) and further dissect the underlying transmission mechanisms as well as the moderating channels through which the effect operates. Empirical results reveal that the effect of GMGG synergy on CGI is subject to diminishing marginal returns, with the effect being significantly more pronounced for substantive green innovation. Heterogeneity analysis indicates that non-state-owned firms, eastern-region firms, and those in non-heavy-polluting industries respond with markedly greater sensitivity. Mechanism analysis further demonstrates that the extent of marketization serves as a mediating channel, whereas an elevated level of digital-economy development mitigates the impact of GMGG synergy on CGI. This study delineates the effective boundary of GMCC synergy in stimulating CGI, providing empirical benchmarks for the synergistic implementation of effective government and efficient market actions in green governance. It further corroborates the positive roles of marketization and the digital economy as novel governance instruments, thereby offering critical policy insights for the coordinated advancement of the “dual-carbon” goals and high-quality economic development. Full article

The rapid evolution of Integrated Energy Systems (IESs) demands robust management of information transmission, which is critical for real-time monitoring, coordination, and operational efficiency. However, the increasing complexity and costs associated with information exchange necessitate effective pricing mechanisms to ensure economic sustainability and optimal resource allocation. This paper presents an evolutionary game-theoretic framework to analyze regulatory strategies governing information transmission within IES. In the context of market dynamics, both market regulators and communication network operators are considered as actors with bounded rationality, emphasizing their strategic interplay within the system. The main contributions include formulating a model that treats communication network operators as independent entities, enhancing the understanding of IES member diversity and interactivity. This study introduces evolutionary game dynamics, providing new insights into optimizing regulatory policies. This paper also innovates by considering asset utilization in defining effective assets, potentially curbing excessive investment by communication network operators and preventing information transmission prices from soaring. A case study is provided to reveal the dynamics and equilibrium states of the regulatory game, offering theoretical support for refining regulatory strategies in IESs. Full article

This study investigates how ESG (environmental, social, and governance) performance influences the corporate value of publicly listed sports companies in China, with a focus on the mediating role of intangible assets and the moderating effect of the policy environment. Analyzing panel data from 41 A-share sports firms over 2009–2023 using a two-way fixed-effects model, the findings reveal that a robust ESG performance significantly enhances corporate value by strengthening brand equity and optimizing resource allocation. Intangible assets, particularly brand value, serve as pivotal mediators in translating ESG efforts into market value. Furthermore, the policy environment plays a critical moderating role: state-owned enterprises (SOEs) exhibit amplified ESG-driven value creation due to stronger policy support and resource advantages. Robustness checks, including an instrumental variable analysis, reinforce the reliability of these conclusions, highlighting the interplay of ESG, intangible assets, and policy in driving long-term competitiveness within the sports sector. By addressing the unique dynamics of ESG in the sports industry, this research bridges a gap in the sector-specific literature and underscores ESG’s strategic importance in fostering sustainable business growth. The results provide actionable insights for corporate managers to align ESG strategies with brand development and for policymakers to design targeted frameworks that incentivize sustainable practices. Full article

The success of a cluster depends on the interplay between intra- and inter-regional collaboration, while empirical research on the mechanisms through which intra- and inter-regional collaborations trigger cluster growth is rarely focused. Based on the local buzz–global pipelines framework and incorporating an evolutionary perspective, we explore how intra- and inter-regional innovation networks can be integrated to drive the growth of emerging industries. We draw on Zhangjiang, China’s most advanced AI industry cluster, using social network analysis and qualitative methods, combining patent data with semi-structured interviews. The results indicate that with the return of multinational corporations and the limitation of Western technology, universities have become the primary source of AI innovation in Zhangjiang. The government has played a pivotal role in propelling the accelerated growth of China’s AI industry, particularly through the backing of pioneering AI private enterprises and the calibration of the potential inefficiencies associated with a state-led model with the dynamism of market forces. The ‘Buzz-and-pipeline’ dynamics in the AI innovation network are shaped by four processes: local networking, market demand, resource integration, and policy synergy. This underscores the intricate interconnections between the national and local scales in AI innovation networks. Full article

This study addresses the urgent need to reduce carbon emissions in the power sector, a major contributor to global greenhouse gas emissions, by employing system engineering principles coupled with machine learning techniques. It analyzes the interplay between regional marginal prices (LMP) and carbon emissions within electricity markets. The paper explores how market designs and operational strategies influence carbon output by leveraging a dataset that encompasses hourly LMP and carbon emissions data across various regions of New York State. The analysis utilizes neural networks to simulate and predict the effects of different market scenarios on carbon emissions, highlighting the role of LMP, loss costs, and congestion costs in environmental policy effectiveness. The results underscore the potential of system engineering to provide a holistic framework that integrates market dynamics, policy adjustments, and environmental impacts, thereby offering actionable insights into optimizing market designs for reduced carbon footprints. This approach not only enhances the understanding of the complex interactions within electricity markets but also supports the development of targeted strategies for achieving sustainable energy transitions. Full article

The proper allocation of corporate capital is critical to sustainable business development, and misallocation of resources can impede sustainable economic growth and competitive markets. This study investigates the relationship between market power and capital misallocation in Chinese A-share listed companies, with a novel focus on the mediating role of total factor productivity (TFP). Using a comprehensive dataset of 20,818 firm-year observations from 2009 to 2021, we employ linear regression analysis to elucidate the mechanisms through which market power influences capital allocation efficiency. The results reveal a significant positive correlation between market power and capital misallocation, with TFP partially mediating this relationship. Specifically, a one-unit increase in the market power index is associated with a 1.106 unit decrease in TFP, and a 0.028 unit increase in the capital misallocation, indicating potential threats to long-term sustainability. This effect is more pronounced in non-state-owned enterprises, firms located in eastern regions, and those without shareholdings in financial institutions. These results contribute to the literature on market structure and resource allocation by providing empirical evidence of the detrimental effects of market power on capital allocation efficiency, operating through the channel of reduced productivity. Our findings have important implications for policymakers and firm managers, suggesting the need for targeted antitrust measures, promotion of market competition, and strategies to enhance TFP. This research advances our understanding of the complex interplay between market power, productivity, and capital allocation in emerging economies, offering valuable insights for addressing market failures, improving allocative efficiency and actively promoting sustainable business and sustainable socio-economic development in the Chinese context. Full article

The global transition towards environmentally friendly energy sources plays a major role in addressing both energy security and climate change. Brazil is at the forefront of this transition due to its rich natural resources and increasing investments in biofuels. Therefore, this investigation examines the consumption patterns and interactions between ethanol, primarily sourced from sugarcane, and gasoline within Brazil’s energy framework. Ethanol’s renewability, reduced environmental impact, and superior combustion characteristics position it as a feasible substitute for traditional fossil fuels. Nonetheless, obstacles like competition for land use and inadequate distribution infrastructure impede its widespread acceptance. This study explores the economic interaction between ethanol and gasoline, focusing on pricing dynamics and regional influences. Using consumer preferences and the accessibility of ethanol, this research identifies a range of price ratios within which consumer preferences shift from gasoline to ethanol in various Brazilian regions. The study also classifies Brazilian states into three distinct ranges based on the ethanol-to-gasoline price ratio in 2023 for a granular analysis of the economic dynamics influencing fuel choice. The research identifies states with competitive and dominant ethanol markets by examining the interplay between ethanol market share, fuel prices, and the adoption of flex-fuel vehicles (FFVs) in the country. Lastly, the findings support the importance of regional economic conditions and the influence of price ratios on consumer behavior, highlighting that ethanol’s market share does not always correlate with favorable pricing. Full article

This study examines the impact of spatial parameters on urban well-being by comparing the urban design and housing policies of Roosevelt Island in New York City and Bat Yam in the Tel Aviv metropolitan area, Israel. Despite their distinct political and cultural contexts, these cities exhibit similar urban design approaches that integrate physical well-being parameters—such as density, building height, open spaces, and walkability—alongside social well-being parameters including age distribution, income levels, and ethnic diversity. The research traces the evolution of affordable housing through various historical phases, including Urban Renewal, Community Development, and Neoliberal Urbanism, and explores how different residential ownership structures have influenced demographic shifts, gentrification, and neighborhood transformation over the past decades. Using a mixed-methods approach that combines historical analysis with spatial and demographic data, this study highlights the contrasting impacts of Roosevelt Island’s affordable housing program and Bat Yam’s state-led urban renewal policies. The results illustrate how distinct housing models affect community resilience, social stability, and overall urban well-being. By uncovering parallel narratives and extracting valuable insights, this analysis offers lessons for other cities navigating similar market-led pressures and policy shifts. The findings underscore the importance of understanding the interplay between spatial design, housing policies, and ownership structures in shaping the long-term sustainability and quality of life in urban neighborhoods. Full article