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Based on strategic choice theory, this study examines the impact and mechanisms of intellectual property demonstration city (IPDC) policy in China on corporate ESG performance.

This study uses China’s A-share listed companies’ data from 2009 to 2019 and conducts a difference-in-differences (DID) to explore the causal relationship between IPDC policy and corporate ESG performance.

Baseline regression results indicate that the IPDC policy can significantly improve corporate ESG performance. Mechanism tests reveal that the IPDC policy expands firm green technology innovation, enhances firm human capital investment and increases government innovation subsidies, thereby promoting corporate ESG performance. Moderating effect results show that the promotion impact on corporate ESG performance of the IPDC policy is diminished by government fiscal pressure. Heterogeneity analyses indicate that the IPDC policy has a stronger impact on corporate ESG performance in key cities, firms in high-tech industries, firms with a higher reliance on intellectual property protection (IPP) and state-owned enterprises (SOEs).

The findings enrich the theoretical research on the influencing factors of corporate ESG performance and provide practical references to strengthen IPP and implement a more thorough intellectual property development strategy.

This research explores support vector machine (SVM) with Gaussian radial basis function kernel (RBF) as the model and Analysis of Variance (ANOVA) for forecasting the invalidation re-examination decisions of China invention patents, it is beneficial to support patent monetization for corporate intellectual capital.

There were 8,666 China invention patents with their existing invalidation re-examination decisions during 2000∼2021 chosen to conduct classification model training and prediction for the accuracy of invalidation re-examination decisions through SVM with RBF. Statistical significance was performed by ANOVA to identify indicators for these invention patents selected in this research. These selected 8,666 China invention patents were divided into two groups based on their invalidation re-examination decisions during 2000∼2021 in Table 1, which Group 1 included 5,974 invention patents with all valid or partially valid claims, and Group 0 included 2,692 invention patents with all invalid claims. Thereafter, each group was further divided into sub-groups based on 13 major regions where the applicants filed invalidation re-examination. The training sets for Group 1, Group 0 and the sub-groups were selected based on the patent issued in January, February, April, May, July, August, October and November; while the prediction sets were selected from the invention patents issued in March, June, September and December.

The training and prediction accuracies were compared to the existing invalidation re-examination decisions. Accuracies of training sets were ranged from 100% in region 7 (Beijing) and region 9 (Shanghai) to 95.95% in region 1 (US), and the average accuracy of invalidation re-examination decisions was 98.95%. While the accuracies of prediction sets for Group 1 were ranged from 100.00% in region 7 (Beijing) to 90.78% in region 13 (Overseas-others), and the average accuracy of classification was 95.96%, this research’s outcomes confirmed the purpose of applying SVM with RBF to predict the patentability sustainability.

This research developed an empirical method through SVM with RBF to predict patentability sustainability which is crucial for corporate intellectual capital on patents. In particular, the investments on patents are huge, including the patent cultivation and maintenance, developments into products or services, patent litigations and dispute managements. Therefore, this research is beneficial not only for corporation, but also for research organisations to perform cost-effective and profitable patent strategies on intellectual capital.

This study examined the impact of the Glasgow Climate Pact on the abnormal returns of global clean energy stocks. Further, this study examines which country-specific and firm-specific variables drive the cumulative abnormal returns (CARs) of clean energy stocks.

The authors used the event study method and cross-sectional multivariate regression model. The clean energy stocks in this study are limited to 81 constituent firms of the S&P Global Clean Energy Index across 17 nations. The final sample includes 80 firms and the sample period ranges from January 26, 2021, to December 07, 2021.

The study finds that the Glasgow Climate Pact negatively affects the stock returns of clean energy firms. Moreover, the climate change performance index (CCPI) positively impacts cumulative abnormal returns (CARs), signifying that clean energy investors react positively to firms in nations with good CCPI scores. The environmental, social and governance (ESG) measure for the shorter window (−1, +1) exhibited a negative relationship with CARs. The firm-specific variables (BTM, stock liquidity, size and past returns) exhibit a negative relationship with CARs in different event windows.

The authors use the CCPI as a proxy for the stringency of environmental policies in any nation. The authors extend the existing literature by employing firm-specific variables and supporting previous findings. Their findings have policy implications for clean energy investors, policymakers and other market participants.

Climate risks impact the global financial market, so the findings have implications for global regulatory bodies. Currently, there are bankruptcy cases due to climate risks. Because financial markets must play a critical role in shifting the economy toward a green one, regulators can use the cross-sectional drivers of this study to shape policy. It is also critical for regulators to reduce stock price volatility in the event of the implementation of environmental regulations and improve environmental disclosures by publicly traded companies. Furthermore, governments are interested in researching the effects of environmental regulations to protect stakeholders' interests. These regulations significantly impact emerging markets because they lack the same solid institutional frameworks as developed markets.

The authors provide evidence that firms with better ESG scores and larger firm sizes have experienced fewer abnormal returns, as these firms have stable financial and non-financial fundamentals. This timely study on the ongoing regulatory shift in environmental policy will help investors, policymakers, firms and other stakeholders make relevant decisions.

This paper aims to examine the influence of supply chain management by assessing the relationship between internal and external integration and small and medium enterprises (SMEs) owners’ Islamic practices in enhancing halal supply chain integrity (HSCI) and SMEs’ performance.

A total of 176 SMEs were surveyed using a self-administered questionnaire. The sample was selected using convenience sampling from two major halal exhibition events in Malaysia. Structural equation modeling (SEM) was used to analyze the data and test the hypotheses.

The findings showed that supply chain integration (SCI), Islamic human capital and HSCI have a significant relationship with SMEs’ performance. It was also found that HSCI mediated the relationship between both SCI and Islamic human capital and SMEs’ performance.

SME owners or managers should be committed to developing the internal processes within the organization and strategizing to link these processes with the external processes to obtain the full benefits of integration. Furthermore, as the upper management, owners and managers must understand the supply chain challenges, priorities and practices thoroughly, as they are responsible for Islamic business ethics. They should work to provide support to increase religious orientation in the SMEs, as this would likely enhance all other factors.

This is one of the few types of research to use HSCI as a mediator in halal food studies in addition to improving SMEs’ performance.

The study aims to examine the impact of six events related to the escalating Indo-China border conflicts in 2020 on the Indian stock market, including the role of firm-specific variables.

This study employs an event-study method on a sample of 481 firms from August 23, 2019 to March 3, 2022. A cross-sectional regression is employed to examine the association between event-led abnormal returns and firm characteristics.

The results show that, although the individual events reflect heterogeneous effects on stock market returns, the average impact of the event categories is negative. The study also found that net working capital, current ratio, financial leverage and operating cash flows are significant financial performance indicators and drive cumulative abnormal returns. Further, size anomaly is absent, indicating that more prominent firms are resilient to new information.

The ongoing conflict between Russia and Ukraine is an example of how these disagreements can devolve into a disaster for the parties to the war. Although wars have an impact on markets at the global level, the impacts of border disputes are local. Border disputes are ongoing, and the study's findings can be used to empower investors to make risk-averting decisions that make their portfolios resilient to such events.

This study provides firm-level insight into the impacts of border conflicts on stock markets. The authors compare the magnitude of such impacts on two types of events, namely injuries and casualties due to country-specific border tensions and a government ban on Chinese apps. Key implications for policymakers, stakeholders and academics are presented.

The purpose of this study is to examine the impacts of the Glasgow Climate Pact on global oil and gas sector stocks. Further, this study also examines if the nations' Climate Change Performance Index (CCPI) and World Energy Trilemma Index (WETI) drive the abnormal returns around the event.

The authors apply the event study analysis to 691 global oil and gas firms across 52 countries. Further, they apply the cross-sectional examination of cumulative abnormal returns (CARs) across 502 firms.

The emerging markets experienced significant negative abnormal returns on the event day. The CCPI negatively affects longer pre-event CARs, while WETI significantly negatively associates with CARs during longer pre- and post-event windows. Volatility is negatively related to pre- and post-event abnormal returns, while past returns positively drive pre-event period CARs but negatively drive post-event window CARs. This study finds an interesting association between liquidity (CACL) and CARs, as CACL positively drives pre-event CARs, but post-event CARs are negatively associated with CACL. The CARs do not significantly correlate with leverage, size and book-to-market ratio.

This study's findings on the impact of climate risks on financial markets have significant implications for global regulatory bodies. Policymakers should reduce stock volatility and enhance environmental disclosures by publicly traded companies to accurately price and assess the potential impacts of climate risks. Governments should examine the effects of environmental restrictions on investor behavior, especially in developing countries with limited access to capital. Therefore, policymakers need to consider the far-reaching impacts of environmental regulations while introducing them.

Climate risks are expected to impact the global financial market significantly. Prior studies provide limited evidence on how such climate pacts impact the oil and gas sector. Hence, this study, while bridging this gap, provides important implications for policymakers and stakeholders, particularly the emerging markets that are more sensitive.

This study aims to analyze the volatility spillover effects of crude oil, gold price, interest rate (yield) and the exchange rate (USD (United States Dollar)/INR (Indian National Rupee)) on inflation volatility in India.

This study uses the multivariate Generalized Autoregressive Conditional Heteroscedasticity (GARCH) models (Baba, Engle, Kraft and Kroner [BEKK]-GARCH and dynamic conditional correlation [DCC]-GARCH) to examine the volatility spillover effect of macroeconomic indicators and strategic commodities on inflation in India. The monthly data are collected from January 2000 till December 2020 for the crude oil price, gold price, interest rate (5-year Indian bond yield), exchange rate (USD/INR) and inflation (wholesale price index [WPI] and consumer price index [CPI]).

In BEKK-GARCH, the results reveal that crude oil price volatility has a long time spillover effect on inflation (WPI). Furthermore, no significant short-term volatility effect exists from crude oil market to inflation (WPI). However, the short-term volatility effect exists from crude oil to inflation while considering CPI as inflation. Gold price volatility has a bidirectional and negative spillover effect on inflation in the case of WPI. However, there is no price volatility spillover effect from gold to inflation in the case of CPI. The price volatility in the exchange rate also has a negative spillover effect on inflation (but only on CPI). Furthermore, volatility of interest rates has no spillover effect on inflation in WPI or CPI. In DCC-GARCH, a short-term volatility impact from all four macroeconomic indicators to inflation is found. Only crude oil and exchange rate have long-term volatility effect on inflation (CPI).

In an economy, inflation management is an essential task. The findings of the current study can be beneficial in this endeavor. The knowledge of the volatility spillover effect of all the four markets undertaken in the study can be significantly helpful in inflation management, especially for inflation-targeting policy.

It is observed that no other study has addressed this issue. We do not find any other research which studies the volatility spillover effect of gold, crude oil, interest rate and exchange rate on the inflation volatility. The current study is novel with a significant contribution to the vast knowledge in this context.

The main aim of the study is to explore the volatility spillover effect of cryptocurrencies (Bitcoin, Ethereum and Litecoin) on inflation volatility in India.

A popular tool, the Bivariate GARCH model (BEKK-GARCH), to study the volatility spillover effect, is applied in the study. Monthly data of cryptocurrencies and inflation (WPI and CPI indices) are gathered from 2015 to 2021.

Significant short-term responsiveness of volatility of cryptocurrencies on the inflation volatility is found. In addition to this, the significant volatility spillover effect from the cryptocurrencies to the inflation volatility is found.

The findings of the current paper can be of use for inflation management, target inflation policies and policies to contain the volatility of cryptocurrencies. The significance of the current paper is relevant as governments worldwide are officially recognizing cryptocurrencies and starting the process of launching their official virtual currency.

No other study is observed on the topic. Hence, the contribution and novelty of the findings of the current paper are very high and add value to the nonexistent literature on the topic. Lack of the number of inflation observations (data of CPI and WPI are available only in monthly frequency) crimps the model estimation. As the cryptocurrencies become old, more data points will be available by design, and such problems can be resolved, and better model estimation may be possible.

Environmental concerns are gaining traction with every passing day. Moreover, post Covid 19, similar to many sectors, the tourism sector is also trying to revive itself. Theoretically, the environment and tourism complement each other. However, empirical vetting is not adequate. This study is motivated to determine how the environment impacts tourism. In addition, the moderating influence of the growth rate of the nations on the impact of the nations on tourism is also investigated.

We have gathered clear and balanced panel data on tourism and the environment for 106 nations for 10 years. The difficulty in measuring environment status is managed by estimating environment efficiency using Data Envelopment Analysis (DEA).

Surprisingly, we find a significant impact of environmental efficiency on inbound tourism across the nations used in the study. Such findings are rarely observed in the earlier studies as very less studies look for the association of environmental efficiency with tourism. However, the findings are supportive of the principles of the Faro convention and ICOMOS (“International Council on Monuments and Sites”) charter to promote environmental quality for tourism attraction. The current research findings can change the future course of action regarding the environment for tourism. The findings of the study establish financial materiality for the tourism sector. These findings give a boost to the theory of sustainable tourism.

The study’s inconsistent outcome (as the literature finds significant association) regarding the insignificant influence of GDP growth rate is a limitation of the study. The insignificant association needs to be further investigated. This limitation can be a future scope on the topic.

The authors do not find many studies on the environment’s impact on inbound tourism. In addition, a few studies on the topic, which exist provide contradictory outcomes. Above all, the literature does not observe the moderation of the GDP growth rate on the environment’s impact on inbound tourism. This lack of studies in literature, to the best of our knowledge, is the unique contribution of the current study.

The study aims to explore the impact of ownership concentration (OC) on bank financial distress (FD). Furthermore, the bank’s financial stability levels determine the association between the two.

Bank data of 33 Indian commercial banks are procured for ten years (2013–2022). The panel data econometrics is applied for empirical estimations. The quantile regression approach is used to determine the association between OC and FD at different quantiles of the FD. Non-normalcy of the data is checked and ensured before applying the quantile regression.

Surprisingly, it is found that promoters have a nonlinear impact on the firm’s stability. The inverted U-shape result implies that as promoters cross a threshold level, the benefit of increasing promoters’ stake takes a beating and a further increase in promoters’ stakes adversely impacts the stability of the banks. Moreover, this threshold value increases while moving from low to high levels of stability in a quantile regression application.

This study uses promoters as the proxy for OC. Other existing definitions of OC are not used in the study, which can further improve the robustness of the results. Additionally, the use of the type of ownership (private, public or foreign) is also not adopted in the present study. Both the limitations can be the study’s future scope on the topic.

The high OC is supposed to influence corporate governance adversely. Therefore, policymakers recommend low OC for better governance. However, the present study finds evidence that a higher OC (high threshold of OC as the stability increases) would be better for financial stability. This situation demands a trade-off between governance and financial stability regarding OC.

The authors do not observe any study having the nonlinear impact of OC on financial stability (opposite of FD). Moreover, the threshold of OC for the optimum level of financial stability increases as stability goes high. This evidence using quantile regression and finding the turning point using a quadratic equation is also not seen in the literature.