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This study aims to analyze the efficient market hypothesis (EMH) of cryptocurrencies on multiple platforms by observing whether there is a discrepancy in the levels of efficiency between different exchanges. Additionally, EMH is tested in a multivariate way: whether the prices of the same cryptocurrencies traded on different exchanges are temporally related to each other. ADF and KPSS tests, whereas the vector autoregression model of order p – VAR(p) – for multivariate system.

Both Bitcoin and Ethereum show efficiency in the weak form on the main platforms in each market alone. However, when estimating a VAR(p) between prices among exchanges, there was evidence of Granger causality between cryptocurrencies in all exchanges, suggesting that EMH is not adequate due to cross information.

It is essential to assess the cryptocurrency market in a multivariate way, not only to favor its maturation process, but also to promote a broad understanding of its inherent risks. Thus, it will be possible to develop financial products that are actively managed in a more sophisticated cryptocurrency market.

There is a possibility of performing arbitrage on different exchanges and market assets through cross-exchanges. Thus, emphasizing the need for regulation of exchanges in the digital asset market, as an eventual price manipulation on a single platform can impact others, which generates various distortions.

This study is the first to find evidence of cross-information for the same (and other) cryptocurrencies among different exchanges.

This study aims to investigate the possibilities of cryptocurrencies as hedges and diversifiers in the Indian stock market before and during financial crisis due to the pandemic and the Russia–Ukraine war.

Researchers have used daily data on cryptocurrencies and Indian stock prices from March 10, 2015 to August 26, 2022. The researchers have used the dynamic conditional correlations (DCC)-GARCH model to determine the volatility spillover and dynamic correlation between stocks and digital currencies. Further, researchers have explored hedge ratio, portfolio weight and hedging effectiveness using the estimates of the DCC-GARCH model.

The findings indicate a negative conditional correlation between equities and cryptocurrencies before the crisis and a positive conditional correlation except for Tether during the crisis. Which implies that cryptocurrencies serve as a hedging asset in the stock market before a crisis but are not more than a diversifier during the crisis, except for Tether. Notably, Tether serves as a safe haven during times of crisis. Finally, the study suggests that Bitcoin, Ethereum, Binance Coin and Ripple are the most effective diversifiers for Indian stocks during the crisis.

This study makes several contributions to the existing literature. First, it compares the hedge and diversification roles of cryptocurrencies in the Indian stock market before and during crisis. Second, the study findings provide insights on risk hedging and can serve as a guide for investors. Third, it may help rational investors avoid underestimating risk while constructing portfolios, particularly in times of financial turmoil.

Owing to highly volatile and chaotic external events, predicting future movements of cryptocurrencies is a challenging task. This paper advances a granular hybrid predictive modeling framework for predicting the future figures of Bitcoin (BTC), Litecoin (LTC), Ethereum (ETH), Stellar (XLM) and Tether (USDT) during normal and pandemic regimes.

Initially, the major temporal characteristics of the price series are examined. In the second stage, ensemble empirical mode decomposition (EEMD) and maximal overlap discrete wavelet transformation (MODWT) are used to decompose the original time series into two distinct sets of granular subseries. In the third stage, long- and short-term memory network (LSTM) and extreme gradient boosting (XGB) are applied to the decomposed subseries to estimate the initial forecasts. Lastly, sequential quadratic programming (SQP) is used to fetch the forecast by combining the initial forecasts.

Rigorous performance assessment and the outcome of the Diebold-Mariano’s pairwise statistical test demonstrate the efficacy of the suggested predictive framework. The framework yields commendable predictive performance during the COVID-19 pandemic timeline explicitly as well. Future trends of BTC and ETH are found to be relatively easier to predict, while USDT is relatively difficult to predict.

The robustness of the proposed framework can be leveraged for practical trading and managing investment in crypto market. Empirical properties of the temporal dynamics of chosen cryptocurrencies provide deeper insights.

This study aims to identify the determinants of customer disengagement (CD) and negative customer engagement (NCE) behaviours following service failure.

This study distributed a survey on negative service experiences to 404 customers in Vietnam and analysed the data using structural equation modelling.

Based on the findings, this paper developed a comprehensive model of the determinants of CD and NCE behaviours. CD manifests as “neglect”, while NCE manifests as vindictive, third-party and online complaints and negative word of mouth. The key drivers of CD and NCE are negative expectancy disconfirmation and perceived injustice, mediated by customer outrage. A novel finding is that self-efficacy and risk-taking traits enhance NCE behaviours. Vietnamese customers tend to adopt less confrontational NCE behaviours.

The findings provide brand managers with insights into unfavourable customer responses to service failure, including CD and NCE behaviours. Customers in Vietnam were predominantly found to disengage. Fulfilling the firm’s promises and treating customers fairly are paramount for preventing customer outrage, CD and NCE.

This study identifies the determinants of CD and NCE, namely, disconfirmation of service quality expectations and perceived injustice, in the context of an emerging market.

The unexpected and rapid outbreak of the COVID-19 pandemic increased the vulnerability of forcibly displaced (migrant) women, who were a social group already at risk of health inequities and poorer health outcomes. This study aims to examine the health literacy of forcibly displaced (migrant) women during the COVID-19 pandemic in Germany using a multidimensional health literacy model as a framework.

A grounded theory methodology was implemented including interviews with 33 forcibly displaced (migrant) women from July to September 2021. An experienced female researcher interviewed all forcibly displaced (migrant) women, and apart from one telephone interview, all interviews were conducted in person.

Following data analysis, the category, “Use of health information in the context of the COVID-19 pandemic of forcibly displaced (migrant) women”, was identified as a core category. The findings provide valuable insight into the health literacy of forcibly displaced (migrant) women during the COVID-19 pandemic. Societal and environmental determinants, personal determinants and situational determinants were identified as factors impacting health literacy. Furthermore, health literacy was distinguished as competence to make informed decisions in the health domains “health care” and “disease prevention”.

Although previous research often focuses on the deficits of forcibly displaced (migrants), this study highlights the resources forcibly displaced (migrant) women use to deal with health-related difficulties, especially during a crisis such as the COVID-19 pandemic. Importantly, such resources were available even if the study participants did not speak the language of the immigration country.

This study is designed to examine the dynamic interrelationships between four cryptocurrencies (Bitcoin, Ethereum, Dogecoin and Cardano) and the Indian equity market. Additionally, the study seeks to investigate the potential safe haven, hedge and diversification uses of these digital currencies within the Indian equity market.

This study employs the wavelet approach to examine the time-varying volatility of the studied assets and the lead-lag relationship between stocks and cryptocurrencies. The authors execute the entire analysis using daily data from 1st October 2017 to 30th September 2023.

The result of the study shows that financial distress due to the pandemic and the Russian invasion of Ukraine have a negative effect on the Indian equities and cryptocurrency markets, escalating their price volatility. Also, the connectedness between the returns of stock and digital currency exhibits a strong positive relationship during periods of financial distress. Additionally, cryptocurrencies serve as a tool of diversification or hedging in the Indian equities markets during normal financial circumstances, but they do not serve as a diversifier or safe haven during periods of financial turmoil.

This study contributes to understanding the relationship between the Indian equity market and four cryptocurrencies using wavelet techniques in the time and frequency domains, considering both normal and crisis times. This can offer valuable insights into the potential of cryptocurrencies inside the Indian equities markets, mainly with respect to varying financial conditions and investment horizons.

This study aims to supplement the international knowledge on factors determining retention in the teaching profession with findings from the Czech Republic. The study aims to answer the question of what factors on the part of schools and teachers are related to teachers’ decision to leave the teaching profession, either temporarily or permanently. It also examines the differences between teachers at the beginning and end of their professional careers.

This study presents a secondary analysis of the data collected in a survey of 1,230 Czech secondary school teachers implemented in 2021 in the same schools as the TALIS survey in 2018. The longitudinal design makes it possible to observe the impact of school variables on teachers’ willingness to remain in the profession. Data are analysed through logistic regression.

The analysis shows the importance of sufficient financial evaluation, the composition of the student body, instructional leadership, and school innovativeness for the retention of teachers in the profession. The analysis further shows that the factors causing teachers to leave the profession differ for those at the beginning and at the end of their teaching careers.

The limitations of the study lie in the fact that this is a secondary analysis. The questionnaires were not designed in accordance with the aim of our study, and so the variables were constructed from existing data to best fit our chosen framework.

The results of our analysis indicate that the Czech education policy should focus not only on general increases in teachers’ salaries, but also on the adjustment of increases over the course of a teacher’s career. The starting salary may be important for retaining young teachers in the profession, while at later stages in their careers their decision to stay may be more influenced by other factors. Our research also showed the importance of leadership. In schools where the principal supports his or her teachers and takes care of their professional development, teachers have a greater tendency to stay in the profession than in schools where the management does not perform this function.

The study enriched international knowledge about factors affecting teachers' retention in the profession with findings from the Czech educational system characterized by high school autonomy and low teacher salaries.

The purpose of this paper is to develop an inorganic-organic hybrid emulsion polymer using grafted hyperbranched alkyd modified with nanometal oxide and to study the performance of the developed hybrid emulsion in paint formulation with respect to antimicrobial and other properties.

A novel hybrid emulsion polymer was synthesized by grafting of vinyl acetate (VAM), vinyl ester of versatic acid (VeoVa 10) monomers onto hyperbranched alkyd resin and incorporation of nano magnesium oxide (MgO) into the hybrid resin matrix during dispersion of resin in water. Subsequently, paint was prepared by using this hybrid emulsion followed by a performance study.

The performance of nano MgO modified into VAM and VeoVa 10 grafted hyperbranched alkyd resulted in unique properties of coating especially antimicrobial activity.

In the present study, soya fatty acid, polyol and di basic acid have been used to prepare hyperbranched alkyd by condensation polymerization. Monomers like VAM and VeoVa 10 used for grafting onto hyperbranched alkyd and nano MgO have been incorporated into hybrid resin matrix during emulsification of hybrid resin in water.

Grafting of VAM and VeoVa 10 onto hyperbranched alkyd along with in situ incorporation of nano MgO in resin matrix is an effective technique to achieve excellent coating properties.

Nano MgO modified VAM and VeoVa 10 grafted hyperbranched alkyd-based hybrid emulsion can be used as binder in water-based metal primer, direct to metal (DTM) coating as well as topcoat application. The developed system has antimicrobial properties as well as superior mechanical properties.

The manufacture of polymer composites with a lower environmental footprint requires incorporation of sustainably sourced components. In addition, the incorporation of novel components should not compromise the material properties. The purpose of this paper is to demonstrate the use of a synthetic amine functional toluidine acetaldehyde condensate (AFTAC) as a modifier for fiber-reinforced epoxy composites. One of the fiber components was sourced from agricultural byproducts, and glass fiber was used as the fiber component for comparison.

The AFTAC condensate was synthesized via an acid-catalyzed reaction between o-toluidine and acetaldehyde. To demonstrate its efficacy as a toughening agent for diglycidyl ether bisphenol A resin composites and for the comparison of reinforcing materials of interest, composites were fabricated using a natural fiber (mat stick) and a synthetic glass fiber as the reinforcing material. A matched metal die technique was used to fabricate the composites. Composites were prepared and their mechanical and thermal properties were evaluated.

The inclusion of AFTAC led to an improvement in the mechanical strengths of these composites without any significant deterioration of the thermal stability. It was also observed that the fracture strengths for mat stick fiber-reinforced composites were lower than that of glass fiber-reinforced composites.

To the best of the authors’ knowledge, the use of the AFTAC modifier as well as incorporation of mat stick fibers in epoxy composites has not been demonstrated previously.

Through activism, brands participate in the sociopolitical controversies that shape society today. Based on social identity theory, this study aims to examine the moderating effects of consumer–brand identification (CBI) and political ideology in explaining consumer responses to brand activism. Furthermore, the role of perceived marginalization that can arise in the case of consumer–brand disagreement is explored.

The hypothesized effects were tested in three experiments. Study 1 (n = 262) and Study 2 (n = 322) used a moderation analysis, which was supplemented by a mixed design analysis with repeated measures in Study 1. In Study 3 (n = 383), the mediating effect of perceived marginalization by the brand was tested using a moderated mediation model.

The results show that strong CBI as well as a conservative ideology buffer the negative effects of consumer–brand disagreement on brand attitude and word-of-mouth intentions. In the case of agreement with a brand’s stance, no direct or interactive effects of brand activism on consumer responses occur. Perceived marginalization by a brand mediates the effects of brand activism.

This study extends the “love is blind” versus “love becomes hate” debate to the realm of brand activism and finds evidence for the former effect. It also contributes to the research on political consumption by highlighting the role of political ideology as an important boundary condition for brand activism. Perceived marginalization is identified as a relevant risk for activist brands.