Search Results (128)

This paper develops a novel modeling framework that integrates time-varying quantile-based spillover effects into a regime-switching realized volatility model. A dynamic spillover factor is constructed by identifying the most influential contributors to Bitcoin’s realized volatility across different quantile levels. This quantile-layered structure enables the model to capture heterogeneous spillover paths under varying market conditions at a macro level while also enhancing the sensitivity of volatility regime identification via its incorporation into a time-varying transition probability (TVTP) Markov-switching mechanism at a micro level. Empirical results based on the cryptocurrency market demonstrate the superior forecasting performance of the proposed TVTP-MS-HAR model relative to standard benchmark models. The model exhibits strong capability in identifying state-dependent spillovers and capturing nonlinear market dynamics. The findings further reveal an asymmetric dual-tail amplification and time-varying interconnectedness in the spillover effects, along with a pronounced asymmetry between market capitalization and systemic importance. Compared to decomposition-based approaches, the X-RV type of models—especially when combined with the proposed quantile-driven factor—offers improved robustness and predictive accuracy in the presence of extreme market behavior. This paper offers a coherent approach that bridges phenomenon identification, source localization, and predictive mechanism construction, contributing to both the academic understanding and practical risk assessment of cryptocurrency markets. Full article

This study focuses on a profound paradox in eco-hotel evaluations: why do consumer ratings for location, a static asset, exhibit dynamic fluctuations? To solve this puzzle, we construct a two-stage signal-processing theoretical framework that integrates Signaling Theory and the Elaboration Likelihood Model (ELM). This framework posits that the dynamic trajectory of a hotel’s green attributes (encompassing eco-facilities, sustainable practices, and ecological experiences) constitutes a high-fidelity market signal about its underlying quality. We utilized natural language processing techniques (Word2Vec and LSA) to conduct a longitudinal analysis of over 60,000 real consumer reviews from Booking.com between 2020 and 2023. This study confirms that continuous improvements in green attributes result in significant positive spillovers to location scores, while any degradation triggers strong negative spillovers. More critically, consumer environmental involvement (CEI) acts as an amplifier in this process, with high-involvement consumers reacting more intensely to both types of signals. The research further uncovers complex non-linear threshold characteristics in the spillover effect, subverting traditional linear management thinking. These findings not only provide a dynamic and psychologically deep theoretical explanation for sustainable consumption behavior but also offer forward-thinking practical implications for hoteliers on how to strategically manage dynamic signals to maximize brand value. Full article

Mitigating traffic-related carbon emissions is pivotal for achieving carbon peaking targets and advancing sustainable urban development. This study employs spatial autocorrelation and high-low clustering analyses to analyze the spatial correlation and clustering patterns of urban road traffic carbon emissions in Shaanxi Province. The spatiotemporal evolution and structural impacts of emissions are quantified through a systematic framework, while the GTWR (Geographically Weighted Temporal Regression) model uncovers the multidimensional and heterogeneous driving mechanisms underlying carbon emissions. Findings reveal that road traffic CO₂ emissions in Shaanxi exhibit an upward trajectory, with a temporal evolution marked by distinct phases: “stable growth—rapid increase—gradual decline”. Emission dynamics vary significantly across transport modes: private vehicles emerge as the primary emission source, taxi/motorcycle emissions remain relatively stable, and bus/electric vehicle emissions persist at low levels. Spatially, the province demonstrates a pronounced high-carbon spillover effect, with persistent high-value clusters concentrated in central Shaanxi and the northern region of Yan’an City, exhibiting spillover effects on adjacent urban areas. Notably, the spatial distribution of CO₂ emissions has evolved significantly: a relatively balanced pattern across cities in 2010 transitioned to a pronounced “M”-shaped gradient along the north–south axis by 2015, stabilizing by 2020. The central urban cluster (Yan’an, Tongchuan, Xianyang, Baoji) initially formed a secondary low-carbon core, which later integrated into the regional emission gradient. By focusing on the micro-level dynamics of urban road traffic and its internal structural complexities—while incorporating built environment factors such as network layout, travel behavior, and infrastructure endowments—this study contributes novel insights to the transportation carbon emission literature, offering a robust framework for regional emission mitigation strategies. Full article

This study investigates the cross-country spillover effects of investor sentiment, specifically Fear and Greed, between the United States and South Africa, within the broader context of increasing global financial integration and behavioral finance. Using monthly data from June 2007 to June 2024, this research constructs and tests the validity of a South African Fear and Greed Index, adapted from CNN’s U.S.-centric index, to better capture the unique dynamics and contribute to an alternate sentiment index for an emerging market. Employing the Diebold and Yilmaz (DY) connectedness framework, this study quantifies both static and dynamic spillover effects via a vector autoregression-based variance decomposition model. The results reveal significant bidirectional sentiment transmission, with the U.S. acting as a dominant net transmitter and South Africa as a net receiver, along with notable cross-country effects closely linked to the global economic trend. Spillover intensity escalates during periods of global economic stress, such as the 2008 financial crisis and the COVID-19 pandemic. The findings highlight that the USA significantly influences South Africa and that the adapted SA Fear and Greed Index better accounts for South African market conditions. Full article

The objective of this paper is to examine the game-theoretic relationship between local governments and coal mining enterprises with regard to the issue of coal mine intelligent construction. Firstly, this paper employs prospect theory to construct the value perception function and the decision weight function, which are then used to optimize the parameters of the traditional income matrix. The equilibrium point is then analyzed for stability under different conditions. Subsequently, Vensim PLE and MATLAB simulation software are employed to substantiate the impact of spillover penalties and associated parameters on the value perception equilibrium of the two parties. The results of the simulation demonstrate that, in addition to the initial strategy selected, the spillover penalty exerts a considerable inhibitory effect on the process of enterprise intelligence construction. Secondly, from the perspective of value perception, the lower the costs to enterprises of carrying out intelligent construction in terms of labor and mental effort, the more enterprises are inclined to engage in this construction. The higher the costs to enterprises of complying with strict government regulation, and the lower the costs to enterprises of deregulation, the more the government can govern by non-interference. Finally, the behavioral trends of local government departments are also correlated with additional revenue they receive from firms and the factor of fines linked to government performance. Full article

In the globalized economic system, environmental, social, and governance (ESG) factors have emerged as critical dimensions for assessing non-financial performance and ensuring the long-term sustainable development of businesses, influencing corporate behavior, investor expectations, and regulatory landscapes. This article applies the VAR-DY network analysis method to construct a large-scale financial volatility spillover network covering all Chinese stocks. It explores the risk transmission paths among different ESG-rated groups and analyzes the patterns and impacts of risk transmission during extreme market volatility. The study finds that as ESG ratings decrease from AAA to C, the network’s average shortest path length and average connectedness strength decreases, indicating that highly rated companies play a central role in the network and maintain their ESG ratings through close connections, positively affecting market stability. However, analyses of the 2015 Chinese stock market crash and the COVID-19 pandemic show a general increase in volatility spillover effects. Notably, the direction of risk spillover in relation to ESG ratings was opposite in these two events, reflecting differences in the underlying drivers of market volatility. This suggests that under extreme market conditions, traditional risk management tools need to be optimized by incorporating ESG factors to better address risk contagion. Full article

This study employs the TVP-VAR-BK-DY spillover index model to investigate the risk spillover effects between China’s carbon emission trading system (ETS) pilots and A-share listed emission-regulated enterprises. The findings reveal that, due to the nascent stage of China’s carbon market, the overall risk spillover level within the “carbon-stock” system remains low; however, dynamic risk spillovers have shown an upward trend driven by the advancement of ETS pilots. In particular, during compliance periods, enterprises that exceed their emission limits must purchase sufficient allowances on the carbon trading market to avoid high penalties for non-compliance. This creates substantial demand, which drives a rapid increase in the spot prices of carbon allowances, triggering intense short-term price fluctuations and risk spillovers—a pronounced “compliance-driven trading” effect. Frequency domain analysis indicates that long-term shocks have a significantly greater impact on the market than short-term oscillations, reflecting moderate information processing efficiency within the “carbon-stock” system. Directional spillover analysis shows that A-share enterprises initially absorb risks from the carbon market in the short term, but over the long term, they transmit part of these risks back to the carbon market, forming a significant bidirectional risk transmission relationship. Furthermore, heterogeneity analysis reveals marked differences in risk spillover contributions among firms associated with different ETS pilots, as well as between enterprises with polluting behaviors and those with high ESG scores, with the latter contributing considerably higher spillovers to the overall carbon market. These findings offer nuanced insights into the dynamic, structural, and firm-level characteristics of risk spillovers, providing valuable guidance for policymakers and investors to enhance market stability and optimize investment strategies. Full article

This study investigates the spillover effects of physicians’ prosocial behavior, specifically knowledge sharing, on the paid consultations of other physicians within the same specialty and offline hospital. Using data from an online healthcare platform, we apply propensity score matching to explore how the sharing of medical knowledge by physicians influences the consultation outcomes of their colleagues. The results reveal significant positive spillover effects, indicating that prosocial behavior benefits other physicians within the same specialty and healthcare institution, thereby enhancing collaboration within the healthcare ecosystem. The spillover effect is stronger within the same offline hospital’s physicians on the online healthcare platform, suggesting that knowledge sharing has a more localized impact within the same healthcare institution. Furthermore, the study examines heterogeneity across both physician-level characteristics (e.g., popularity, title, price, gender) and contextual factors (e.g., specialty type, hospital level, wait time, regional GDP). The findings show that the magnitude and direction of spillover effects differ by subgroup, shaped by professional visibility, authority, and organizational structure. These insights contribute to the understanding of how prosocial behavior can foster collaboration and benefit healthcare networks beyond individual physicians, offering practical implications for healthcare platforms, administrators, and policymakers. Full article

China is one of the world’s leading producers and exporters of wood-based panels and plays a crucial role in ensuring a stable global supply of wood products. But China’s wood product exports have recently diminished, potentially due to the retraction of foreign investment. This behavior remains unexamined mechanistically in the current literature. This study investigates the impact of FDI on the export performance of China’s wood processing industry and explores the potential for leveraging foreign investment to reverse the downward trend in export growth. Our findings indicate that FDI alleviates export constraints by enhancing wood resource efficiency, which suggests a substantive response to industry challenges rather than a mere strategic adjustment. However, FDI inflows have decreased in recent years, negatively affecting export performance and highlighting the need for policy improvements. We further examine the differential effects of FDI on exports across port and non-port regions, given that the urgency of attracting FDI varies spatially. Our analysis reveals that the export spillover effect of FDI in port areas is approximately 165% higher than in non-port areas, largely due to China’s high dependence on wood product imports. In regions with extensive artificial forests, the impact is lower, possibly due to a stronger focus on domestic markets. In particular, Eastern China, benefiting from early market liberalization and a history of successful foreign collaborations, demonstrates significant improvements in export performance. To mitigate the export pressures on China’s wood processing industry, we recommend targeted industrial policies, particularly for port areas, to attract high-quality FDI that supports global supply chain stability and sustainable development. Full article

The acceleration of global climate change presents unprecedented challenges to market stability and sustainable social development. Understanding how market dynamics are impacted by perceptions of climate risk is essential to creating risk management plans that work. Current research frequently concentrates on static evaluations of how climate risk is perceived, ignoring its dynamic influence on clean energy markets and the intricate channels via which these risks spread. To examine the dynamic influence of climate risk perceptions on clean energy markets, this study builds a spillover network model. We determine the main risk transmission pathways and their temporal variations by looking at changes in market connection over time. Our results demonstrate that climate risk perceptions have a substantial direct and indirect impact on the volatility of clean energy markets. Specifically, the ‘Risk Concern Index (GCTC and GCPC) → Clean Energy Market Index → Climate Policy Uncertainty Index (CPU) → Risk Indices (GCTRI and GCPRI)’ pathway highlights how public and policymaker concerns about climate risk significantly influence market behavior and overall dynamics. Furthermore, the dynamic analysis demonstrates that market spillovers are significantly amplified by economic and geopolitical events, highlighting the necessity of taking external shocks into account when designing policies. This study offers fresh perspectives on how climate risk perception affects clean energy markets, serves as a useful resource for investors and policymakers, and encourages the creation of robust risk management plans and market mechanisms. Full article

Using a sample of S&P 500 stocks, this paper examines the investor sentiment spillover network between firms and assesses how the sentiment connectedness in the network impacts stock price crash risk. We demonstrate that firms with higher sentiment connectedness are more likely to crash as they spread more irrational sentiment signals and are more sensitive to investor behaviors. Notably, we find that the effect of investor sentiment on crash risk mainly stems from sentiment connectedness among firms rather than firms’ individual sentiment, especially when market sentiment is surging or declining. These findings remain robust after controlling for other determinants of crash risk, including stock price synchronicity, accounting conservatism, and internal corporate governance strength. Our results underscore the importance of sentiment connectedness among firms and provide valuable insights for risk management among investors and regulatory authorities involved in monitoring risk. Full article

Based on the quasi-natural experiment of “the pilot policy of combining science and technology with finance” (Sci-Tech Finance pilot policy) carried out in China in recent years, this paper constructs a multi-stage difference-in-differences model to explore its impact on corporate ESG performance and the influence mechanisms. The main research findings of this paper are as follows: (1) The Sci-Tech Finance pilot policy significantly enhances corporate ESG performance, a finding that remains consistent after conducting parallel trends testing, propensity score matching, and placebo tests. (2) The policy promotes the corporate ESG performance through three intermediary channels, namely alleviating financial constraints, improving total factor productivity, and enhancing green technology innovation. Notably, the first two intermediary channels exhibit the most prominent effects. (3) The impact of the pilot policy on the corporate ESG performance exhibits heterogeneity at both the regional and corporate levels; it demonstrates a more pronounced impact on corporates located in the Eastern Region, within high digital economic zones, and among high-tech, capital-intensive, heavily polluting, and state-owned corporates. (4) The policy has apparent spatial spillover effects on corporate ESG performance, accounting for about 8% of the direct effect in the pilot areas. This study enriches the literature on the impacts of Sci-Tech Finance on corporate behaviors, providing insights for government regulatory authorities to leverage Sci-Tech Finance policies to promote corporate ESG performance and sustainable development. Full article

At present, the high complexity of the environment, the uncertainty of income, and the choice of strategies have attracted extensive attention from all walks of life who are committed to studying the game of collaborative innovation between government and industry–university–research. Based on this, first of all, with the help of stochastic evolutionary game theory and fuzzy theory, this paper constructs a multi-party stochastic evolutionary game model of green technology innovation about the government guidelines and the joint promotion of industry, universities, and research institutes. Secondly, it discusses the evolution law of behavior strategies of each game subject and the main factors to maintain the alliance’s stability under fuzzy income. The numerical simulation results show the following: (1) Reputation gains have a significant positive correlation with the evolution stability of alliance behavior, and the incorporation of reputation gains or losses will effectively maintain the cooperation stability of the alliance. (2) Under the influence of product greenness, government subsidies, and long-term benefits, it will promote the pace consistency of cooperative decision-making between industry, universities, and research institutes, and accelerate the evolution of alliances. (3) The enterprise’s ability and the research party’s ability will restrict each other. When one party’s ability is low, its willingness to choose a cooperation strategy may be slightly low due to technology spillover and other reasons. When the two parties’ abilities match, their behavior strategies will increase their willingness to cooperate with their abilities. Compared with the traditional evolutionary game, this study fully considers the uncertainty of the environment and provides theoretical support and practical guidance for the high-quality development strategy of the industry–university–research green technology innovation alliance. Full article

This study assesses the informational usefulness of several uncertainty metrics in predicting the monetary policy and actual economic activity of Tunisia. We use a Bayesian time-varying vector autoregressive (VAR) model to identify uncertainty shocks sequentially. We complement the analysis with the use of local projections (LPs), a recently flexible and simple method that accommodates the effect of an exogenous intervention on policy outcomes. The findings suggest that shocks to global and spillover uncertainty are important in elucidating the dynamics of industrial production and consumer prices. The impulse response functions (IRFs) show that the central bank does not follow a linear-rule-based monetary strategy. The irreversibility theory, or the “precautionary” behavior, is tested in a vector error correction model (VECM). The money market rate impacts industrial production and consumer prices differently during high versus low uncertainty, depending on the uncertainty variable and the horizon (short versus long run). The effects can be insignificant or significantly dampened during high uncertainty, indicating that conventional monetary policy may be ineffective or less influential. The “wait and see” strategy adopted by economic agents implies that they do not take timely actions until additional pieces of information arrive. While this could not be the sole explanation of our findings, it conveys the importance of dealing with uncertainty in decision-making and highlights the necessity of a clear and credible communication strategy. Importantly, the central bank should complement interest rates with the use of unconventional monetary policy instruments for better flexibility. Our work provides a comprehensive and clear picture of the Tunisian economy and a focal guide for the central bank’s future practices to achieve macroeconomic objectives. Full article

Existing online review research has not fully captured consumer purchasing behavior in complex decision-making environments, particularly in contexts involving multiple product comparisons and conflicting review perspectives. This study thoroughly investigates the impact on focal product purchase decisions when consumers compare multiple products and face information inconsistency. Based on online review data from JD.com, we propose a semi-supervised deep learning model to analyze consumers’ sentiment polarity toward product attributes. The method establishes implicit relationships between labeled and unlabeled data through consistency regularization. Subsequently, we conceptualize three types of online review dissimilarity factors, rating-sentiment dissimilarity, cross-review dissimilarity, and brand dissimilarity, and employ regression models to examine the impact of competing products’ online reviews on focal product sales. The results indicate that by employing a semi-supervised deep learning approach, unlabeled data are annotated with pseudo-labels and utilized for model training, achieving more accurate sentiment classification than using labeled data alone. Moreover, positive (negative) sentiment attributes of competing products have a significant negative (positive) effect on focal product purchases. Online review dissimilarity moderates the spillover effects of competing products. Notably, these spillover effects are more pronounced when competing products are from the same brand compared to different brands. The research findings not only highlight the heterogeneous effects of positive and negative sentiments but also provide a new perspective for examining dissimilarity, enriching the understanding of online review spillover effects and the role of dissimilarity, while offering practical guidance for resource allocation decisions by companies and platforms. Full article