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The authors examine the volatility connections between the equity markets of China and its trading partners from developed and emerging markets during the various crises episodes (i.e. the Asian Crisis of 1997, the Global Financial Crisis, the Chinese Market Crash of 2015 and the COVID-19 outbreak).

The authors use the GARCH and Wavelet approaches to estimate causalities and connectedness.

According to the findings, China and developed equity markets are connected via risk transmission in the long term across various crisis episodes. In contrast, China and emerging equity markets are linked in short and long terms. The authors observe that China leads the stock markets of India, Indonesia and Malaysia at higher frequencies. Even China influences the French, Japanese and American equity markets despite the Chinese crisis. Finally, these causality findings reveal a bi-directional causality among China and its developed trading partners over short- and long-time scales. The connectedness varies across crisis episodes and frequency (short and long run). The study's findings provide helpful information for portfolio hedging, especially during various crises.

The authors examine the volatility connections between the equity markets of China and its trading partners from developed and emerging markets during the various crisis episodes (i.e. the Asian Crisis of 1997, the Global Financial Crisis, the Chinese Market Crash of 2015 and the COVID-19 outbreak). Previously, none of the studies have examined the connectedness between Chinese and its trading partners' equity markets during these all crises.

The growing concern for food safety and quality, especially after the COVID-19 pandemic and the new normal situation, motivates governments and private sectors to improve consumers’ confidence in food systems by adopting certifications and traceability systems. The recent emergence of diverse food labeling schemes in food systems in emerging countries has sparked questions about consumers’ valuation of such labels. Nonetheless, little is known about how familiarity with, trust in and knowledge of these food labels affect consumers’ utility. This study aims to reveal consumers’ preferences for agrifood assurance to accelerate food safety practices. Specifically, we examine in what ways agrifood attributes (traceability, certification, selling places and price) impact consumers’ selection.

Data were gathered from surveying 1,365 consumers and then discrete choice experiment methodology was applied to measure consumers’ willingness to pay for safety attributes displayed on food labels in different market outlets.

Empirical evidence shows that certification is the most preferred safety attribute, with the highest level of WTP hovering around 50% more for both USDA and VietGap certificates. The second rank belongs to the traceability system, where consumers express particular interest in farming and processing information rather than more complicated information. Meanwhile, the food purchasing venue has less effect on consumers’ WTP for a certain food label. Consumers’ demographic factors, familiarity, knowledge and trust also play an important role in explaining their heterogeneity.

The findings may not be generalizable because the current study only included data from Vietnamese consumers.

Our findings provide managerial implications for food policymakers and providers in governing the food market to restore consumer confidence.

This paper aims to conduct a systematic literature review of Socially Conscious Investment (SCI) articles published in premier journals. Its objective is to shed light on the publication trend, leading authors, journals, countries and themes in contemporary SCI research. The article also provides a conceptual model of SCI to enhance understanding of the knowledge structure and the future research direction.

A systematic review followed the PRISMA guidelines and encompasses 264 full-text articles indexed in A* and A category journals listed in ABDC is reviewed. The literature synthesis adopts the theories, contexts, characteristics and methodology (TCCM) framework.

The article has identified the research trends related to author impact, journal impact, article impact and the outcomes derived from the TCCM framework. Additionally, it highlights three key themes: Performance of SCI, Behavioural issues and SCI development literature.

The insight on various aspects of SCI was explored for a comprehensive understanding. The authors also developed a conceptual model for socially conscious investment.

The purpose of this paper is to analyse the dynamic and evolving relationship between Bitcoin mining (BTC) and climate policy uncertainty. By using the newly developed U.S. Climate Policy Uncertainty (CPU) indicator by Gavriilidis (2021) as a proxy for global climate-related transition risk, this study aims to explore the complex bidirectional causality between these two critical phenomena in climate-related finance. Further, we explore how economic and market factors influence the cryptocurrency market, focusing on the relationship between CPU and Bitcoin mining.

We employ a linear and non-linear rolling window sub-sample Granger causality approach combined with a probit model to examine the time-varying causalities between Bitcoin mining and the U.S. Climate Policy Uncertainty (CPU) indicator. This method captures asymmetric effects and dynamic interactions that are often missed by linear and static models. It also allows for the endogenous determination of key drivers in the BTC–CPU nexus, ensuring that the results are not influenced by ad-hoc assumptions but are instead grounded in the data’s inherent properties.

The findings indicate that Bitcoin mining is negatively impacted by climate policy uncertainty during periods of increased environmental concern, while its energy-intensive nature contributes to increasing climate policy uncertainty. In addition to market factors, such as Bitcoin halving, and alternative assets, such as green equity, five main macroeconomic factors influence these relationships: financial instability, economic policy uncertainty, rising oil prices and increasing industrial production. Furthermore, two non-linear dynamics in the relationship between climate policy uncertainty and Bitcoin (CPU-BTC nexus) are identified: the “anticipatory regulatory decline effect”, when miners boost activity ahead of expected regulatory changes, but this increase is unsustainable due to stricter regulations, compliance costs, investor scrutiny and reputational risks linked to high energy use.

This study is the first in the literature to examine the time-varying and asymmetric relationships between Bitcoin mining and climate policy uncertainty, aspects often overlooked by static causality and average-based coefficient models used in previous research. It uncovers two previously unidentified non-linear effects in the BTC-CPU nexus: the “anticipatory regulatory decline effect” and the “mining-driven regulatory surge”, and identifies major market factors macro-determinants of this nexus. The implications are substantial, aiding policymakers in formulating effective regulatory frameworks, helping investors develop more sustainable investment strategies and enabling industry stakeholders to better manage the environmental challenges facing the Bitcoin mining sector.

Topologically ordered functionally graded composite (TOFGC) biodegradable materials are needed in the field of metallic degradable implants, as they degrade over a period of time avoiding the necessity of another surgery for implant removal. Also, their rate of degradation can be tailored to match the requirement of the patient. These biomaterials also have the functionality to assist bone growth and eliminate stress shielding in orthopaedic implants.

In this study, TOFGC biomaterials were developed for the first time using additive manufacturing, pressureless microwave sintering and casting methods, and their cytocompatibility, hemocompatibility and in vitro degradation evaluations were done. Also, pure dense iron and iron scaffolds were included in the study, for the comparison of results with the iron-hydroxyapatite-zinc functionally graded composite biomaterial.

The maximum weight loss and corrosion rate were found to be 6.98% and 2.38 mmpy, respectively, in the immersion test and electrochemical test for Fe-3.5HAp-54Zn biomaterial. Zinc-infiltrated composite biomaterials exhibited excellent cytocompatibility and hemocompatibility as compared to pure dense iron and iron scaffolds. A comparative analysis was conducted, taking into account relevant literature, and it was determined that the fabricated iron-hydroxyapatite-zinc biomaterial demonstrated desirable degradation and biological characteristics, customized to meet the specific requirements of bone tissue engineering applications.

TOFGC iron-hydroxyapatite-zinc biomaterial has been fabricated for the first time using the developed novel methodology and their degradation and biological characterizations were performed.

This study aims to examine Africa’s environment, social and governance (ESG) research through a systematic literature review (SLR). The authors aim to identify and discuss influential aspects of ESG accounting in Africa, focusing on prominent themes, authors and journals in published articles using Africa’s setting. It also constructs agendas for future research to advance the literature and contribute to the ESG accounting practices in Africa.

This study uses an SLR approach, where accounting research journal articles are collated and compiled according to pre-determined criteria and analysed using bibliometric techniques. After carefully reviewing 1,387 articles, the authors selected and examined 246 academic articles published from 2006 to 2024 in 32 accounting journals indexed in the Web of Science.

The authors identify four main streams of ESG accounting research in Africa, namely, ESG disclosure in primary-based economies; corporate governance dynamics in Africa; internal mechanisms in ESG reporting; and external mechanisms in ESG disclosure. According to the analysis, the authors propose future research agendas to discuss institutional perspective of ESG reporting standards implementation and enforcement; value creation impact on sustainability performance; ESG reporting effect on conflict resolution; and ESG reporting quality and environmental sustainability.

This study assists policymakers, academics, managers, accounting professionals and investors in comprehensively understanding the current state and projecting future actions to develop ESG accounting in Africa.

To the best of the authors’ knowledge, this study is perhaps the first to examine Africa’s ESG research through an SLR. This study contributes to the body of knowledge by providing a comprehensive analysis of the existing ESG accounting landscape and tailoring future research agendas based on the distinctive characteristics of Africa.

During the postpandemic era, owing to the widespread integration of technology, a greater abundance of information is circulating among young consumers compared to any previous period. Consequently, there exists a possibility that the disseminated information may not be accurate and ultimately prove to be fake. The purpose of this study is to conceptualize fake news, the definition and drivers of fake news from the perspective of young consumers in the postpandemic period.

A qualitative study was undertaken in the current study. A total of 30 interviews were conducted utilizing semistructured questionnaires. The interviews were audio recorded and subsequently transcribed. The data was analyzed using the Gioia methodology.

The study proposes a definition of fake news from the perspective of young consumers. Further, drawing on attribution theory, the three categories of reasons for sharing fake news were delineated: content related, source related and user related.

Drawing on the findings of the study, policymakers and other stakeholders working on the issues of fake news can acquaint themselves with the underlying reasons. Furthermore, they can devise policies to prevent the sharing of fake news.

It is important for practitioners and society to understand the reasons behind the sharing of fake news among young consumers to combat the spread.

The present study will contribute to the literature by understanding the perspective of young consumers who intentionally or unintentionally share fake news. Additionally, attribution theory is used in the context of fake news to understand the dissemination behavior.

This paper aims to predict Dogecoin price by using artificial intelligence (AI) methods and comparing the results with the econometrics models.

An artificial neural network (ANN) was applied as a prediction method without any optimization techniques. Additionally, the genetic algorithm (GA) is used to select the most appropriate input variables. Additionally, based on the literature review and the relationships between crypto-price and global indices, 20 economic indicators, such as Coinbase Bitcoin, Coinbase Litecoin and US dollars, along with main global stock indices such as FTSE100 and NIFTY50, are identified as input variables for the model. Lichtenberg algorithm (LA) and aquila optimization (AO) algorithm are used to make the ANN more robust. To validate our algorithms, they have been implemented on daily data for the last three years. To demonstrate the superiority of the models over traditional methods such as econometrics, regression analysis and curve fitting techniques are used. The effectiveness of these models is then evaluated and compared using criteria such as recall, accuracy and precision.

The results indicate that AI-based algorithms not only enhance the accuracy, recall and precision of calculations but also expedite the process without requiring the numerous and restrictive assumptions associated with time series and econometric models.

The main contribution of this paper is the application of novel approaches such as AO and LA to improve the predictive capabilities of the ANN method for various cryptocurrencies’ prices. It demonstrates the superiority of the proposed algorithms over traditional econometric models using real-life data.

The objective of this study is to determine the impact of GHG assurance on firms’ carbon emissions performance (CEP) regarding curbing carbon emissions and the effect on such by the GHG assurance provider’s affiliation and reputation. It also explores whether the affiliation and reputation of GHG assurance providers imply the relationship between GHG assurance and the firm’s CEP. Further, this study examines the moderating effect of the country’s development level on the relationship.

Based on a sample of international firms from 56 countries spanning the period from 2012 to 2020, this study utilizes the ordinary least squares (OLS) regression. We also run the OLS regression at times t+1 and t+2 to verify the baseline results. To address the endogeneity concerns arising from self-selection bias and the causality effect, this study applies the generalized method of moment (GMM) and the Heckman test.

This study finds that GHG assurance leads to better CEP by firms. We also find that engaging with accounting assurance providers leads firms to a better CEP than non-accounting assurance providers. Our results show that Big Four auditors can help firms decrease carbon emissions. We also find that the positive effect of GHG assurance is prevalent in firms operating in developed countries.

Our study only considers the influence of the assuror’s reputation and affiliation on CEP without examining other factors that may influence the quality of assurance services provided.

Our study provides a practical implication related to the influence of a GHG assurance provider’s affiliation and reputation globally by providing evidence that accounting and Big Four assurance providers do play a significant role in a firm’s carbon emission performance. This study offers great insights into the GHG assurance impact on CEP with the interplay between the assuror’s affiliation and reputation and the country’s development.

This paper enriches the limit evidence on GHG assurance and CEP by providing novel evidence on the relationship between GHG assurance and a firm’s CEP. Moreover, this study provides insights into the implication of a country’s development level on the role of GHG assurance in CEP.

As financial markets for environmentally friendly investment grow in both scope and size, analyzing the relationship between green financial markets and African stocks becomes an important issue. Therefore, this paper examines the role of infectious disease-based uncertainty on the dynamic spillovers between African stock markets and clean energy stocks.

The authors employ the dynamic spillover in time and frequency domains and the nonparametric causality-in-quantiles approach over the period of November 30, 2010, to August 18, 2021.

These findings are discernible in this study's analysis. First, the authors find evidence of strong connectedness between the African stock markets and the clean energy market, and long-lived but weak in the short and medium investment horizons. Second, the BDS test shows that nonlinearity is crucial when examining the role of infectious disease-based equity market volatility in affecting the interactions between clean energy stocks and African stock markets. Third, the causal analysis provides evidence in support of a nonlinear causal relationship between uncertainties due to infectious diseases and the connection between both markets, mostly at lower and median quantiles.

Considering the global and recent use of clean energy equities and the stock markets for hedging and speculative purposes, one may argue that rising uncertainties may significantly influence risk transmissions across these markets. This study, therefore, is the first to examine the role of pandemic uncertainty on the connection between clean stocks and the African stock markets.