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The purpose of this paper is to examine volatility spillover from the Chinese stock market to E7 and G7 stock markets. Using the estimated results, the authors also analyze the optimal weights and optimal hedge ratios for the portfolios including stocks from E7 and G7 countries.

The authors employed generalized vector autoregressive-generalized autoregressive conditional heteroskedasticity approach, developed by Ling and McAleer (2003), in order to analyze daily data on the national stock indices. Considering the late establishment of some E7 stock markets, the sampling covers the period from 1995 through 2015.

The findings indicate significant volatility spillover from the Chinese stock market to E7 and G7 stock markets. In particular, the Chinese stocks highly co-move with the stocks of countries within a same geographical region. While the highest volatility spillover occurs between China and India among E7 countries, the highest volatility spillover occurs between China and Japan among G7 countries. Furthermore, the examination of optimal weights and hedge ratios suggest that investors should hold more stocks from G7 countries than E7 countries for their portfolios.

To the best of the authors’ knowledge, this is the first study which investigates the volatility spillover in the stock markets of G7 and E7 countries. Moreover, the current study contributes particularly to the existing limited literature on the Chinese stock market. Since the Chinese stock market is not fully integrated to other markets and it is subject to intense government interventions, there is a widely accepted belief that the contagion effects from the Chinese stock market to other stock markets are not influential. This view discourages and limits the prospect studies. However, the findings of this paper refute this view and indicate significant interaction among the Chinese stock market and E7 and G7 stock markets.

Higher economic growth accompanied by rising energy demand poses severe challenges to the long-term environmental sustainability of E7 economies, including Brazil, China, India, Indonesia, Mexico, Russia and Turkey. Thus, this paper explores the influence of foreign direct investment (FDI) inflows on energy diversification for E7 economies.

The dataset is panel data for emerging seven (E7) economies, covering the period 1992–2017. The empirical investigation relies on econometric techniques: panel cointegration test and panel autoregressive distributed lag model.

The findings reveal that energy diversification and FDI inflows are cointegrated. In the long run, higher FDI inflows encourage energy diversification, but energy efficiency improvements discourage energy diversification. In the short run, the effects of FDI inflows on energy diversification vary across E7 economies, highlighting the role of country-specific factors in determining the short-run influence of FDI inflows on energy diversification.

The findings suggested that FDI policies should encourage the adoption of nonconventional energy resources to stimulate energy diversification in E7 economies. Besides, better coordination between energy diversification and energy efficiency policies is required in the long run for a successful transition towards low-carbon economy goals.

This study is a unique empirical exercise that uncovers a cointegrating relationship between energy diversification and FDI inflows for E7 economies. Moreover, the analysis provides homogenous long-run and heterogeneous (country-specific) short-run coefficient estimates for the effect of FDI inflows on energy diversification.

The existence of long memory and persistent volatility characteristics of cryptocurrencies justifies the investigation of return and volatility/shock spillovers between traditional financial market asset classes and cryptocurrencies. The purpose of this paper is to investigate the dynamic relationship between the cryptocurrencies, namely Bitcoin and Ethereum, and stock market indices of G7 and E7 countries to analyze the return and volatility spillover patterns among these markets by means of multivariate (MGARCH) approach.

Applying the newly developed VAR-GARCH-in mean framework with the BEKK representation, the empirical results reveal that there exists an evidence of mean and volatility spillover effects among Bitcoin and Ethereum as the proxies for the cryptocurrencies, and stock markets reviewed.

Interestingly, the direction of the return and volatility spillover effects is unidirectional in most E7 countries, but bidirectional relationship was found in most G7 countries. This can be explained as the presence of a strong return and volatility interaction among G7 stock markets and crypto market.

Overall, the results of this study are of particular interest for portfolio management since it provides insights for financial market participants to make better portfolio allocation decisions. It is also increasingly important to understand the volatility transmission mechanism across these markets to provide policymakers and regulatory bodies with guidance to eliminate the negative impact of cryptocurrency's volatility on the stability of financial markets.

This study aims to examine the volatility spillover effects between oil and stock returns in the emerging seven economies.

In this study, the Granger causality test and vector autoregression-generalized autoregressive conditional heteroskedasticity approach to analyze the volatility spillover from 1995 to 2019 were used. The findings provide evidence of significant volatility spillover between oil and Brazil, China, India, Indonesia, Mexico, Russia and Turkey (E7) stock markets.

All emerging seven stock markets exhibit positive and low constant conditional correlations with oil assets. The magnitude of the correlation changes in respond to the country’s net position in the crude oil market. While a relatively high level of correlation exists between oil and the stock markets of net oil-exporting countries, a relatively low level of correlation exists between oil and the stock markets of net oil-importing countries.

The findings suggest that oil asset improves the risk-adjusted performance of a well-diversified portfolio of stocks. However, investors should invest a larger portion of their portfolios in E7 stock markets than in oil.

This study sought to further develop the growing body of qualitative evidence exploring the content, duration and triggers of cognitive distortions and deviant sexual fantasies in perpetrators who offend against adult women, using grounded theory techniques. Detailed accounts of the thoughts and fantasies of 10 rapists pre‐ and post‐intervention were analysed. All participants reported having benefited from the programme. Nine participants reported that the victim‐focused work had the most impact on them. It was also found that after treatment: (a) there was a reduction in the level of cognitive distortions around victim blaming, other justifications for offending (such as alcohol use) and the acknowledgment of the impact that their offences has had upon their victims; (b) reductions in denial of fantasising about the offences prior to their offences. The implications of this study, for the improvement of intervention programmes for this group of offenders, are discussed.

The purpose of this research is to study the relationship between exchange rate fluctuations and stock market returns of the seven highest economic performing emerging countries (E7).

The study is conducted using the daily data for exchange rates and stock market returns in each of the E7 countries from January 1, 2019, to January 1, 2022. The study employs the ordinary least squares, autoregressive distributed lag error correction regression and generalized autoregressive conditional heteroskedasticity (GARCH (1,1)) regression models to fully investigate the impact of exchange rate on stock markets. For further investigation, the GARCH (1,1) model is run twice for each country with and without the inclusion of exchange rate to determine its effect on the volatility of stock returns.

The findings support the presence of cointegration relationship between the variables for all countries. The results reveal significant positive long-run relationship between exchange rates and stock market returns in all countries except for Indonesia, which evidenced a significant negative impact. The results of the GARCH (1,1) add that the inclusion of exchange rate in the model accounts for a slight change in the volatility of stock returns.

The research provides empirical evidence that appreciating currencies are perceived positively by investors leading to better performing capital markets. The outcomes of this study may assist policy makers in understanding to what degree changes in exchange rates can influence capital markets, as well as narrow the gap in literature regarding which theory is more relevant in explaining how exchange rate fluctuations impact market values.

This paper aims to examine the choices made by the hotel industry about what to include, and who to be accountable to, in their sustainability reports; a process defined as materiality assessment.

The paper is based on the findings of semi-structured interviews with eight sustainability managers (from eight of the world’s 50 largest hotel groups) to explore their understanding of, and use of, materiality and any barriers to its uptake and eight industry sustainability experts to assess the general industry-wide application of materiality.

Sustainability managers from large hotel groups are evasive when disclosing their materiality criteria, their decision-making processes and how they aggregate stakeholder feedback; they limit their disclosure to the reporting process. Sustainability managers are disempowered, with limited resources, time, knowledge and skills to apply to materiality assessment. Experts confirm that hotel groups are unsystematic and opaque about their decision-making and how they control their materiality assessments.

Materiality assessment is concealed from the public and may be constructed around business imperatives with high managerial capture. The hospitality industry needs to improve its sustainability reporting by examining how it defines and applies materiality and by addressing the barriers identified, if it is to demonstrate an enduring commitment to sustainability and organisational legitimacy.

This study addresses the limited knowledge of how hotel groups undertake materiality assessments. It identifies gaps in the conception and application of materiality by pinpointing barriers to its uptake and recommending areas in need of further research.

Over the past decades, Islamic finance has expanded its presence to many countries including post-Soviet region. The purpose of this paper is to empirically investigate this phenomenon in Kazakhstan by adopting qualitative sociological approach. The study also aims to provide vital information and propose recommendations for market participants to contribute to the development of Islamic finance industry in Kazakhstan.

Primary data were gathered using the qualitative method of in-depth expert interviews with nine Islamic finance professionals representing Islamic banks, ijarah companies, funds and development institutions in Kazakhstan who occupy senior positions (directors, managers, heads of departments, etc.). Furthermore, the primary data of interviews were analyzed and processed using another qualitative method of cognitive mapping, the essence of which is to graphically display the concepts that are most often used by informants.

The study has shown that first there is a demand for Islamic finance among Kazakh business and population. At the same time, Muslims are not the only consumers of Islamic financial services; therefore, it is affordability rather than religiosity that is an important criterion for choosing Islamic finance. Second, murabaha and ijarah are the two most popular Islamic financial products in Kazakhstan, while equity-based instruments are hardly ever used. Third, Kazakhstan government policy toward Islamic finance received controversial assessments of experts: the state support is declared, but specific actions required by the market participants are not taken. Fourth, key factors that significantly limit the development of the Islamic finance market in Kazakhstan include a shortage of supply, which, in turn, is strongly associated with the second factor – limited funding of local Islamic finance institutions, the absence of insurance (or guaranteeing) system of investment accounts of the local Islamic banks, insufficient economy of scale, lack of convenient service and weak marketing policy of the existing Islamic banks and, finally, lack of educational programs.

The study reveals the potential development of Islamic finance in Kazakhstan which is a rarely studied topic. The findings and recommendations of this study can be used by the regulators, market players and policymakers of Islamic finance industry in Kazakhstan, post-Soviet and other Islamic finance-oriented countries.

This study offers new insights on the future of Islamic finance in Kazakhstan: in long term, the development will be determined by new financial technologies – Islamic FinTech, but in short term – by Islamic windows (currently not allowed by Central Bank) that will help to significantly expand the audience, increase awareness and demand for Islamic finance among local businesses and public. The current study is original, important and up-to-date, as it uses an approach that sources primary data in the form of experts’ point of view instead of relying on literature or document analysis. It is not a mere theoretical study of the literature but an empirical investigation of the problem. Moreover, it seeks to contribute to the Islamic finance literature in the post-Soviet region, particularly from the experts’ perspective.

E-commerce companies often manipulate customer decisions through dark patterns to meet their interests. Therefore, this study aims to identify, model and rank the enablers behind dark patterns usage in e-commerce companies.

Dark pattern enablers were identified from existing literature and validated by industry experts. Total interpretive structural modeling (TISM) was used to model the enablers. In addition, “matriced impacts croisés multiplication appliquée á un classement” (MICMAC) analysis categorized and ranked the enablers into four groups.

Partial human command over cognitive biases, fighting market competition and partial human command over emotional triggers were ranked as the most influential enablers of dark patterns in e-commerce companies. At the same time, meeting long-term economic goals was identified as the most challenging enabler of dark patterns, which has the lowest dependency and impact over the other enablers.

TISM results are reliant on the opinion of industry experts. Therefore, alternative statistical approaches could be used for validation.

The insights of this study could be used by business managers to eliminate dark patterns from their platforms and meet the motivations of the enablers of dark patterns with alternate strategies. Furthermore, this research would aid legal agencies and online communities in developing methods to combat dark patterns.

Although a few studies have developed taxonomies and classified dark patterns, to the best of the authors’ knowledge, no study has identified the enablers behind the use of dark patterns by e-commerce organizations. The study further models the enablers and explains the mutual relationships.