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This paper aims to analyze the dependence structure between the Green Sukuk Spread in Malaysia and uncertainty factors from January 1, 2017, to May 23, 2023, covering two main periods: the pre-COVID-19 and the COVID-19 periods.

This study contributes to the current literature by explicitly modeling nonlinear dependencies using the Regular vine copula approach to capture asymmetric characteristics of the tail dependence distribution. This study used the Archimedean copula models: Student’s-t, Gumbel, Gaussian, Clayton, Frank and Joe, which exhibit different tail dependence structures.

The empirical results suggest that Green Sukuk and various uncertainty variables have the strongest co-dependency before and during the COVID-19 crisis. Due to external uncertainties (COVID-19), the results reveal that global factors, such as the Infect-EMV-index and the higher financial stress index, significantly affect the spread of Green Sukuk. Interestingly, in times of COVID-19, its dependence on Green Sukuk and the news sentiment seems to be a symmetric tail dependence with a Student’s-t copula. This result is relevant for hedging strategies, as investors can enhance the performance of their portfolio during the COVID-19 crash period.

This study contributes to a better understanding of the dependency structure between Green Sukuk and uncertainty factors. It is relevant for market participants seeking to improve their risk management for Green Sukuk.

The purpose of this paper is to explore the dynamic interdependence structure and risk spillover effect between the Chinese stock market and the US stock market.

This paper mainly uses the multivariate R-vine copula-complex network analysis and the multivariate R-vine copula-CoVaR model and selects stock price indices and their subsector indices as samples.

The empirical results indicate that the Energy, Materials and Financials sectors have leading roles in the interdependent structure of the Chinese and US stock markets, while the Utilities and Real Estate sectors have the least important positions. The comprehensive influence of the Chinese stock market is similar to that of the US stock market but with smaller differences in the influence of different sectors of the US stock market on the overall interdependent structure system. Over time, the interdependent structure of both stock markets changed; the sector status gradually equalized; the contribution of the same sector in different countries to the interdependent structure converged; and the degree of interaction between the two stock markets was positively correlated with the degree of market volatility.

This paper employs the methods of nonlinear cointegration and the R-vine copula function to explore the interactive relationship and risk spillover effect between the Chinese stock market and the US stock market. This paper proposes the R-vine copula-complex network analysis method to creatively construct the interdependent network structure of the two stock markets. This paper combines the generalized CoVaR method with the R-vine copula function, introduces the stock market decline and rise risk and further discusses the risk spillover effect between the two stock markets.

This study aims to introduce and evaluate the COPULA framework, a construction project monitoring solution based on blockchain designed to address the inherent challenges of construction project monitoring and management. This research aims to enhance efficiency, transparency and trust within the dynamic and collaborative environment of the construction industry by leveraging the decentralized, secure and immutable nature of blockchain technology.

This paper employs a comprehensive approach encompassing the formulation of the COPULA model, the development of a digital solution using the ethereum blockchain and extensive testing to assess performance in terms of execution cost, time, integrity, immutability and security. A case analysis is conducted to demonstrate the practical application and benefits of blockchain technology in real-world construction project monitoring scenarios.

The findings reveal that the COPULA framework effectively addresses critical issues such as centralization, privacy and security vulnerabilities in construction project management. It facilitates seamless data exchange among stakeholders, ensuring real-time transparency and the creation of a tamper-proof communication channel. The framework demonstrates the potential to significantly enhance project efficiency and foster trust among all parties involved.

While the study provides promising insights into the application of blockchain technology in construction project monitoring, future research could explore the integration of COPULA with existing project management methodologies to broaden its applicability and impact. Further investigations into the solution’s scalability and adaptation to various construction project types and sizes are also suggested.

This research offers a comprehensive blockchain solution specifically tailored for the construction industry. Unlike prior studies focusing on theoretical aspects, this paper presents a practical, end-to-end solution encompassing model formulation, digital implementation, proof-of-concept testing and validation analysis. The COPULA framework marks a significant advancement in the digital transformation of construction project monitoring, providing a novel approach to overcoming longstanding industry challenges.

This study aims to empirically explore and compare the dynamic dependency between health-care sector and Islamic industries before, during and after the COVID-19 pandemic.

Time-varying student-t copula is used for before, during and after COVID-19 periods. The data used are the daily frequency price series of the selected markets from February 2017 to October 2023.

Empirical results found strong evidence of significant impact of the COVID-19 pandemic on the dependence structure of the studied indexes: Co-movements between various sectors are certain. The authors assist also in the birth of new dependence structure with the health-care industry in response to the COVID-19 crisis. This reflects the contagion occurrence from the health-care sector to other sectors.

By specifically examining the Islamic industry, this study sheds light on the resilience, challenges and opportunities within this sector, contributing novel perspectives to the broader discourse on pandemic-related impacts on economies and industries. Also, this paper conducts a comprehensive temporal analysis, examining the dynamics before, during and after the COVID-19 lockdown. Such approach enables an understanding of how the relationship between the health-care sector and the Islamic industry evolves over time, accounting for both short-term disruptions and long-term effects. By considering the pre-pandemic context, the paper adopts a longitudinal perspective, enabling a deeper understanding of how historical trends, structural factors and institutional frameworks shape the interplay between the health-care sector and the Islamic industry.

This paper examines the extreme dependence and asymmetric risk spillovers between crude oil futures and ten US stock sector indices (consumer discretionary, consumer staples, energy, financials, health care, industrials, information technology, materials, telecommunication and utilities) before and during COVID-19 outbreak. This study is based on the rationale that stock sectors exhibit heterogeneity in their response to oil prices depending on whether they are classified as oil-intensive or non-oil-intensive sectors and the possible time variation in the dependence and risk spillover effects.

The authors employ static and dynamic symmetric and asymmetric copula models as well as Conditional Value at Risk (VaR) (CoVaR). Finally, they use robustness tests to validate their results.

Before the COVID-19 pandemic, crude oil returns showed an asymmetric tail dependence with all stock sector returns, except health care and industrials (materials), where an average (symmetric tail) dependence is identified. During the COVID-19 pandemic, crude oil returns exhibit a lower tail dependency with the returns of all stock sectors, except financials and consumer discretionary. Furthermore, there is evidence of downside and upside risk asymmetric spillovers from crude oil to stock sectors and vice versa. Finally, the risk spillovers from stock sectors to crude oil are higher than those from crude oil to stock sectors, and they significantly increase during the pandemic.

There is heterogeneity in the linkages and the asymmetric bidirectional systemic risk between crude oil and US economic sectors during bearish and bullish market conditions; this study is the first to investigate the average and extreme tail dependence and asymmetric spillovers between crude oil and US stock sectors.

Organizational justice and its impact on employee commitment have received a lot of attention these days. The objective of this study is to see the effect of job satisfaction as a mediator in the relationship between organizational justice and employee commitment. Also, the role of academic rank as a moderator in the model is probed.

A moderating mediation structural equation model was used for randomly collected cross-section data on 285 employees from public universities in Ethiopia. Necessary condition analysis (NCA) was employed to check the importance of the variables. The Gaussian copula approach was used to check endogeneity in the structural model.

NCA confirms the importance of organizational justice and employee satisfaction as the independent variables. The Gaussian copula approach reveals no endogeneity problems in the structural model. The results supported the partial mediating role of job satisfaction in organizational justice and academic staff’s commitment. Moreover, though staff rank is not a necessary condition, it plays the role of moderator in the relationship between academic staff’s job satisfaction and commitment.

This paper affirms that public institutions must implement fair initiatives and procedures to promote academic staff satisfaction and commitment.

This is the first study to check the job rank as a moderator in the model comprising organization justice, employee commitment and satisfaction. Moreover, application of NCA and Gaussian copula adds to methodological innovation.

Product discounts have been widely applied in digital commerce as a method to attract and retain customers to purchase in China. Given that digital channels differ in their attributes, customers may behave differently when they respond to the same discount across channels. However, little attention has been paid to explore the heterogeneity of customer responses to discounts across channels. This study aims to fill in the gap by exploring how customers’ purchase responses to price discounts differ across digital channels.

This study applies a Poisson regression to an unbalanced data set of purchasing history from Chinese footwear brands with 3,510 customers in a two-year time window across the three digital channels (i.e. personal computer [PC], app and mobile website), with a correction for endogeneity by using the Gaussian copula method.

This paper finds that price discounts have the strongest positive effect on consumers’ purchase volumes on the PC channel, followed by the app channel, while discounts show the weakest impact in the mobile website channel. By so, this paper demonstrates that customers respond differently to online and mobile channels, and they also respond differently within mobile channels when they purchase products with price discounts.

This study is original in analyzing the difference in customers’ discount responses across digital channels, offering valuable contributions to existing research on multichannel marketing as well as mobile marketing and providing helpful insights for multichannel merchants to design digital discount strategies.

The aim of this paper is to document the effect of analyst coverage on the ex ante probability of stock price crash and the ex ante probability stock price jump.

This paper uses the data of non-financial firms from France to test the arguments presented in this paper during the period between 1997 and 2019. The paper also uses flexible quadrants copulas to compute the ex ante probabilities of crashes and jumps.

The results show that the extent of analyst coverage is positively associated with the ex ante probability of crash and negatively associated with the ex ante probability of jump. The results remain qualitatively the same after several sensitivity checks. The results also show that the relationship between the extent of analyst coverage and the probability of cash and the probability of jump holds when ex post probability of stock price crash and stock price jump is used.

Unlike most of the earlier papers on this topic, this paper uses the ex ante probability of crash and jump. This proxy is better suited than the ones used in the prior literature because it is a forward-looking measure.

This study aims to examine the relationship between audit committee (AC) effectiveness and firm performance (FP) with the moderation of knowledge intensity while observing the varying effect of each AC characteristic’s influence on its effectiveness.

This study examines 133 companies covering five years from 2016 to 2020 using the partial least squares-structural equation model and weighing AC effectiveness-related characteristics through multiple regression between AC characteristics and the AC effectiveness construct.

The results indicate that the knowledge intensity of the firms negatively influences the relationship between their AC effectiveness and FP, implying that the ACs are not sophisticated enough to monitor the knowledge component of the firm’s assets. Among AC characteristics, six attributes have a significant positive impact, two have a negative impact and three have no significant influence on AC effectiveness while influencing FP.

Apart from guiding the regulators, managers and other stakeholders to choose an appropriate mix of AC characteristics for enhancing FP, the study contributes to the existing literature by providing evidence that ACs are ineffective in monitoring the knowledge assets of the company compared to physical assets.

This study is pioneering in investigating the moderation role of knowledge intensity on the relationship between AC effectiveness and FP. While providing a comprehensive and holistic view of AC effectiveness by considering 11 AC characteristics’ individual as well as aggregate effects on FP, it removes the obsolescence of earlier research in the Indian context owing to the latest regulatory reforms.

This study aims to understand what primary relationship problem mechanisms can exist in the franchise channel and how exchange partners respond to them. This study demonstrates how the franchisor’s relationship problem mechanisms (threat, contract enforcement) affect the franchisee’s negative active responses (venting, threatened withdrawal).

This study tested hypotheses through multiple regression analysis using data from 200 franchisees in Korea-based food franchise systems.

The results indicated that threat increases venting and threatened withdrawal, while contract enforcement only increases venting. Venting increases threatened withdrawal. In addition, the results indicated that the franchisor’s behavior monitoring positively moderates the relationship between relationship problem mechanisms and negative active responses.

This study helps strategically manage responses to relationship problems by categorizing ‘relationship problem mechanisms’ into intentional relationship problem mechanisms based on communication (threat) and unintentional relationship problem mechanisms based on action (contract enforcement). This study finds that both relationship problem mechanisms, intentional or unintentional, eventually cause threatened withdrawal directly or indirectly. Even if the threat is merely communication, not action, it is more likely to cause relationship dissolution than contract enforcement by directly triggering any negative active response. This study also finds that behavior monitoring can affect exchange partners through interaction with other management mechanisms rather than directly affecting them.