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This paper aims to investigate the safe haven feature of Bitcoin, gold and two gold-backed cryptocurrencies (DGX and PAXG) against energy and agricultural commodities (crude oil, natural gas and wheat) during the COVID-19 pandemic, the Russia–Ukraine conflict and the Silicon Valley Bank (SVB) collapse.

The authors use the threshold GARCH (T-GARCH)-asymmetric dynamic conditional correlation (ADCC) model to evaluate the asymmetric dynamic conditional correlation between the return series and compare the diversifying, hedging and safe-haven ability of Bitcoin, gold and the two gold-backed cryptocurrencies (DGX and PAXG) against financial swings in the commodity market during the COVID-19 outbreak, the Russian–Ukrainian military conflict and SVB collapse. The authors also calculate the hedging ratios (HR) and hedging effectiveness index (HE). The authors finally use the wavelet coherence (WC) approach to check our results’ robustness and further investigate the impact of the three crises on the relationship between Bitcoin, gold gold-backed cryptocurrencies and commodities.

The results show that PAXG serves as a strong hedging instrument while gold, Bitcoin and DGX act as strong diversifiers during normal times. During crises, gold outperforms Bitcoin as a diversifier and a safe haven against commodities. Gold-backed cryptocurrencies also exhibit strong performance as diversifiers and safe havens. HR results indicate that Bitcoin and DGX are more cost-effective for commodities risk mitigation than gold and PAXG. In terms of hedging effectiveness, gold and PAXG emerge as the best hedging instruments for commodities, while DGX is considered the worst one. Bitcoin shows superior hedging against oil compared to wheat and gas risks. Moreover, the results of the WC approach confirm those of the T-GARCH-ADCC results in both the short and long run.

This paper provides a comprehensive analysis of the diversification ability of gold, Bitcoin and gold-backed cryptocurrencies during different crises (the COVID-19 pandemic, the Russia–Ukraine conflict and the SVB collapse). By taking into consideration gold-backed cryptocurrencies, the authors expand the understanding of safe havens beyond conventional assets.

This study aims to investigate the impact of blockchain use on the performance of supply chain in the high-tech industry and to elucidate the main factors that drive managers to adopt blockchain in high-tech firms.

This study adopts the unified theory of acceptance and usage model and extends it with external constructs such as “Trust,” “Technology Readiness,” “Compatibility” and “Awareness.” The paper uses a quantitative and exploratory approach, collecting and analyzing data from 250 high-tech firms worldwide, using the partial least squares structural equation modeling approach.

The findings emphasize the strategic importance of blockchain for supply chain performance in these firms. Furthermore, the results indicate that facilitating conditions, ease of use, technology readiness, compatibility and subjective norms are key enablers for blockchain adoption in high-tech firms.

This research advances the literature on technology adoption in the supply chain field, with special focus on blockchain. The field is strengthened by investigating the determinants and barriers to adopting technology within high-tech firms, emphasizing the necessity of developing blockchain literacy for successful international transactions.

The objective of this paper is to investigate the pandemic’s function as a driver of investor herding in international stock markets, given that the current coronavirus disease 2019 (COVID-19) crisis has caused a large rise in uncertainty.

The paper investigates the presence of herding behavior among the developed and BRICS (Brazil, Russia, India, China and South Africa) stock market indices during the COVID-19 crisis, by using a modified Cross-Sectional Absolute Deviation (CSAD) measure which is considered a proxy for herding and the wavelet coherence (WC) analysis between CSAD that captures the different inter-linkages between stock markets.

Using the CSAD model, the authors' findings indicate that the herding behavior of investors is present in stock markets during the four waves of COVID-19 crisis. The results also demonstrate that the transaction volume improve the herding behavior in the stock markets. As for the news concerning the number of cases caused by the pandemic, the results show that the pandemic does not stimulate herding; however, the number of deaths caused by this pandemic turns out to be a great stimulator of herding. By using the WC analysis, the authors' findings indicate the presence of herding behavior between the Chinese and stock markets (developed and emerging), especially during the first wave of the crisis and the presence of herding behavior between the Indian and stock markets (developed and emerging) in the medium and long run, especially during the third wave of the COVID-19 crisis.

The authors' study is among the first that examines the influence of the recent COVID-19 pandemic as a stimulator of herding behavior between stock markets. The study also uses the WC analysis next to the CSAD model to obtain robust results. The authors' results are consistent with the mental bias of behavioral finance where herding behavior is considered effective in volatility predictions and decision-making for international investors, specifically during the COVID-19 crisis.