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This study aims to empirically connect green logistics performance, renewable energy, non-renewable energy, CO₂ emissions and gross domestic product in Vietnam from 2000 to 2022.

Within this study, the author uses innovative tools, specifically a R2 decomposed linkage method, to scrutinize the connections between green logistics, environmental issues and the use of green and dirty energy.

The results highlight the two-way relationship between green logistics and energy security in Vietnam. Green logistics plays various roles in diverse periods, from a net shock transmitter to a net shock receiver in the designed system. Using a dynamic and contemporaneous dynamic linkage method, this study emphasizes the change in the role and the dominance of green logistics and renewable energy consumption. Notably, the unexpected shocks also lead to changes in these variables’ roles.

This paper presents two significant contributions to the existing body of literature. Firstly, as previously emphasized, this research marks a pioneering effort to examine the connection between green logistics, environmental issues and the use of green and dirty energy when it comes to developing nations such as Vietnam. Secondly, this research introduces a novel approach to investigating the interconnectedness of volatility across diverse markets, offering a more suitable method for such analyses. Within this study, the author uses innovative tools, specifically an R2 decomposed linkage method, to scrutinize the connections between green logistics, environmental issues and the use of green and dirty energy. In this analysis, the author examined data from 2000 through 2022. A thorough analysis is presented using the data, exploring the connections between the volatilities resulting from various problems in Vietnam.

In this study, we aim to investigate the connectedness spillovers among major cryptocurrency markets. Moreover, we also explore to identify factors driving this connectedness, particularly focusing on the sentimentality of total, short-term, and long-term return connectedness spillovers among cryptocurrencies under Twitter-based economic uncertainties and US economic policy uncertainty. Finally, we investigate the extent to which cryptocurrency markets serve as a safe haven, hedge, and diversifier from news-based uncertainties.

This study employs the connectedness approach following the combination of Ando et al. (2022) QVAR and Baruník and Krehlík's (2018) frequency connectedness methodologies into the framework proposed by Diebold and Yilmaz (2012, 2014). The data covered from November 10, 2017, to April 21, 2023, and the factors driving cryptocurrency connectedness spillovers are identified and examined. The sentimentality of total, short-term, and long-term return connectedness spillovers among cryptocurrencies, concerning Twitter-based economic uncertainties and US economic policy uncertainty, are analyzed. We apply the Wavelet quantile correlation (WQC) method developed by Kumar and Padakandla (2022) to explore the effects of Twitter-based economic uncertainties and US economic policy uncertainty on Cryptocurrency market connectedness risk spillovers. Besides, we check and present the robustness of WQC findings with the multivariate stochastic volatility method.

Our findings indicate that Ethereum and Bitcoin are net shock transmitters at the center of the connectedness return network. Ethereum and Bitcoin hold the highest market capitalization and value in the cryptocurrency market, respectively. This suggests that return shocks originating from these two cryptocurrencies have the most significant impact on other cryptocurrencies. Tether and Monero are the net receivers of return shocks, while Cardano and XRP exhibit weak shock-transmitting characteristics through returns. In terms of return spillovers, Ethereum is the most effective, followed by Bitcoin and Stellar. Further analysis reveals that Twitter economic policy uncertainty and US economic policy uncertainty are effective drivers of short-term and total directional spillovers. These uncertainty indices exhibit positive coefficient signs in short-term and total directional spillovers, which turn predominantly negative in different magnitudes and frequency ranges in the long term. In addition, we also document that as the Total Connectedness Index (TCI) value increases, market risk also rises. Also, our empirical findings provide significant evidence of Twitter-based economic uncertainties and US economic policy uncertainty that affect short-term market risks. Hence, we state that risk-connectedness spillovers in cryptocurrency markets enclose permanent or temporary shock variations. Besides, findings of the low value of long-term spillovers suggest that risk shocks in cryptocurrency markets are not permanent, indicating long-term changes require careful monitoring and control over market dynamics.

In this study, we find evidence that Twitter's news-based uncertainty and US economic policy uncertainty have a significant effect on short-term market risk spillovers. Furthermore, we observe that high cryptocurrency market risk spillovers coincide with periods of events such as the US-China trade tensions in January 2018, the Brexit process in February 2019, and the COVID-19 outbreak in November 2019. Next, we observe a decline in cryptocurrency market risk spillovers after March 2020. The reason for this mitigation of market risk spillover may be that the Fed's quantitative easing signals have initiated a relaxation process in the markets. Because the Fed's signal to fight inflation in March 2022 also coincides with the period when risk spillover increased in crypto markets. Based on this, we present evidence that the FED's communication mechanism with the markets can potentially affect both short- and long-term expectations. In this context, we can say that our hypothesis that uncertainty about the news causes short-term risks to increase has been confirmed. Our findings may have investment policy implications for portfolio managers and investors generally in terms of reducing financial risks.

Our paper contributes to the literature by examining the interconnectedness among major cryptocurrencies and the drivers behind them, particularly focusing on the role of news-based economic uncertainties. More broadly, we calculate the utilization of advanced methodologies and the incorporation of real-time economic uncertainty data to enhance the originality and value of the research, which provides insights into the dynamics of cryptocurrency markets.

This study aims to provide empirical evidence on the return and volatility spillover structures between Bitcoin, Fintech stocks and Asian-Pacific equity markets over time and during different market conditions, and their implications for portfolio management.

We use Time-varying parameter vector autoregressive and quantile frequency connectedness approach models for the connectedness framework, in conjunction with Diebold and Yilmaz’s connectivity approach. Additionally, we use the minimum connectedness portfolio model to highlight implications for portfolio management.

Regarding the uncertainty of the whole system, we show a small contribution from Bitcoin and Fintech, with a higher contribution from the four Asian Tigers (Taiwan, Singapore, Hong Kong and Thailand). The quantile and frequency analyses also demonstrate that the link among assets is symmetric, with short-term spillovers having the largest influence. Finally, Bitcoins and Fintech stocks are excellent diversification and hedging instruments for Asian equity investors.

There is an instantaneous, symmetric and dynamic return and volatility spillover between Asian stock markets, Fintech and Bitcoin. This conclusion should be considered by investors and portfolio managers when creating risk diversification strategies, as well as by policymakers when implementing their financial stability policies.

The study’s major contribution is to analyze the volatility spillover between Bitcoin, Fintech and Asian stock markets, which is dynamic, symmetric and immediate.

This paper investigates potential safe haven assets for Middle East and North Africa (MENA) stock markets during the uncertainty period of the COVID-19 pandemic.

This study applies the dynamic conditional correlation–generalized autoregressive conditionally heteroskedastic (DCC-GARCH) model and the Diebold–Yilmaz spillover index for ten MENA stock markets, three precious metals and Bitcoin for the period 2013–2021.

Empirical results show, on the one hand, that the COVID-19 crisis risk has been transmitted to MENA stock markets through volatility spillover across markets. This has increased the conditional volatility for all markets. On the other hand, findings point out that the dynamic correlation between the precious metals/Bitcoin and stock markets is not stable and switches between low positive and negative values during the period under studies. Extending analysis to portfolio management, results reveal that investors should include precious metals/Bitcoin in their portfolio of stocks in order to reduce the risk of the portfolio. Finally, for the period of COVID-19, the analysis concludes that gold preserves its traditional role as a safe haven for MENA stock markets during the pandemic, while Bitcoin fails to provide this property.

These results have several implications for international investors, risk managers and financial analysts in terms of portfolio diversifications and hedging strategies. Indeed, the exploration of the volatility connectedness between financial, commodity and cryptocurrency markets becomes an essential task for all market participants during the COVID-19 outbreak. Such analysis can help investors and portfolio managers to evaluate the risk of investments in the MENA stock markets during the crisis period and to achieve the optimal diversification strategy and hedging instruments.

The paper interests MENA stock markets that experienced the last decade a substantial development in terms of market capitalization and number of listed firms. To the author’s knowledge, this is the first study that investigates the dynamic correlation between MENA stock markets and four potential safe haven assets, including three precious metals and Bitcoin. In addition, the paper employs two types of models, namely the DCC-GARCH model and the Diebold-Yilmaz spillover index.

We phrase our analysis around the connectedness effects and portfolio allocation in the “Carbon-Energy-Green economy” system.

This paper utilizes the TVP-VAR method provided by Antonakakis et al. (2020) and Chatziantoniou et al. (2021), and portfolio back-testing models, including bivariate portfolios and multivariate portfolios.

Firstly, the connectedness within the “Carbon-Energy-Green economy” system is strong, and is mainly driven by short-term (weekly) connectedness. Notably, the COVID-19 pandemic leads to a vertical increase in the connectedness of this system. Secondly, in the “Carbon-Energy-Green economy” system, most of the sectors in the green economy stocks tend to be the transmitters of shocks to other markets (particularly the energy efficiency sector), while the carbon and energy markets are always the recipients of shocks from other markets (particularly the crude oil market). Thirdly, Green economy sector stocks have satisfactory hedging effects on the market risk of carbon and energy assets. Interestingly, hedging risks in relatively “dirty” assets requires more green economy stocks than in relatively “clean” assets. Finally, the results indicate that portfolios that include green economy stocks significantly outperform portfolios that do not contain green economy stocks, further demonstrating the crucial role of green economy stocks in this system.

Understanding the interactions and portfolio allocation in the “Carbon-Energy-Green economy” system, especially identifying the role of the green economy performance in this system, is important for investors and policymakers.

We examined the dynamic volatility connectedness and diversification strategies among US real estate investment trusts (REITs) and green finance indices.

The DCC-GARCH dynamic connectedness framework and he DCC-GARCH t-copula model were employed in this study.

Using daily data from 2,206 observations spanning from 2 January 2015 to 31 January 2023 this paper presents the following findings: (1) cross-market spillovers exhibited a high correlation and significant fluctuations, particularly during extreme events; (2) our analysis confirmed that REIT acted as net receivers from other green indices, with the S&P North America Large-MidCap Carbon Efficient Index dominating the in-network volatility spillover; (3) this observation suggests asymmetric spillovers between the two markets and (4) a portfolio analysis was conducted using the DCC-GARCH t-copula framework to estimate hedging ratios and portfolio weights for these indices. When REIT and the Dow Jones US Select ESG REIT Index were simultaneously added to a risk-hedged portfolio, our findings indicated that no risk-hedging effect could be achieved. Moreover, the cost and performance of hedging green assets using REIT were found to be comparable.

We first examined the dynamic volatility connectedness and diversification strategies among US REITs and green finance indices. The outcomes of this study carry practical implications for market participants.

Social networking sites have become breeding grounds for the spread of fake news and misinformation. At the height of the Covid-19 pandemic, the spread of fake news intensified, causing complications for health communicators by drowning authentic information from verifiable official sources. Looking at the impact of this growing phenomenon on people’s attitudes and behaviour during the pandemic, research in the area must be populated to help governments, supranational organisations, non-governmental organisations as well as civil society organisations to formulate policies to curb the menace. This study was therefore undertaken to unravel current gaps and future research avenues to empower academia in achieving the desired scholarly impact.

The study adopted the systematic review approach, relying on 56 peer-reviewed articles on social media, fake news and misinformation in the Covid-19 pandemic.

The study found that the use of social media during the height of the pandemic led to unhelpful information creation and sharing behaviours such that people’s self-awareness reduced drastically, thereby impeding the fight against the pandemic. The study also established that Entertainment motives, Ignorance and Altruism motives were the dominant factors that influenced the spread of fake news. There was evidence of the marginalization of research on the subject matter from contexts such as Africa, South America and Oceania.

This study has established existing gaps in issues and evidence, methodology, theory and context and consequently discussed future research avenues for social media use and the spread of fake news. The study has also provided practical implications for both governmental and non-governmental organisations in curbing the phenomenon of fake news and misinformation.

The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-07-2022-0366.

As part of the 5G rollout, small cell base stations will be deployed across cities. This paper aims to identify an international effort to remove regulatory barriers around deployment and outline emerging strategies Australian local governments are developing to ensure urban amenity in a deregulatory context.

This paper analyses existing legislation, policy frameworks and grey literature and has conducted eight interviews with participants from the local government sector.

This paper identifies a global deregulatory trend around small cell deployment and that councils are trying to renegotiate their relationship with telecommunications carriers as 5G is rolled out. Three strategies are identified: the design and installation of smart poles, network sharing and partnerships.

This research contributes to scholarship focused on the 5G rollout and offers one of the first accounts of the emerging tensions between regulatory frameworks, commercial imperatives and municipal authorities, identifying urban amenity as a key area of concern.

Automatic dependent surveillance-broadcast (ADS-B) is the foundational technology of the next generation air transportation system defined by Federal Aviation Authority and is one of the most precise ways for tracking aircraft position. ADS-B is intended to provide greater situational awareness to the pilots by displaying the traffic information like aircraft ID, altitude, speed and other critical parameters on the Cockpit Display of Traffic Information displays in the cockpit. Unfortunately, due to the initial proposed nature of ADS-B protocol, it is neither encrypted nor has any other innate security mechanisms, which makes it an easy target for malicious attacks. The system is vulnerable to various active and passive attacks like message ingestion, message deletion, eavesdropping, jamming, etc., which has become an area of concern for the aviation industry. The purpose of this study is to propose a method based on modified advanced encryption standard (AES) algorithm to secure the ADS=B messages and increase the integrity of ADS-B data transmissions.

Though there are various cryptographic and non-cryptographic methods proposed to secure ADS-B data transmissions, it is evident that most of these systems have limitations in terms of cost, implementation or feasibility. The new proposed method implements AES encryption techniques on the ADS-B data on the sender side and correlated decryption mechanism at the receiver end. The system is designed based on the flight schedule data available from any flight planning systems and implementing the AES algorithm on the ADS-B data from each aircraft in the flight schedule.

The suitable hardware was developed using Raspberry pi, ESP32 and Ra-02. Several runs were done to verify the original message, transmitted data and received data. During transmission, encryption algorithm was being developed, which has got very high secured transmission, and during the reception, the data was secured. Field test was conducted to validate the transmission and quality. Several trials were done to validate the transmission process. The authors have successfully shown that the ADS-B data can be encrypted using AES algorithm. The authors are successful in transmitting and receiving the ADS-B data packet using the discussed hardware and software methodology. One major advantage of using the proposed solution is that the information received is encrypted, and the receiver ADS-B system can decrypt the messages on the receiving end. This clearly proves that when the data is received by an unknown receiver, the messages cannot be decrypted, as the receiver is not capable of decrypting the AES-authenticated messages transmitted by the authenticated source. Also, AES encryption is highly unlikely to be decrypted if the encryption key and the associated decryption key are not known.

Implementation of the developed solution in actual onboard avionics systems is not within the scope of this research. Hence, assessing in the real-time distances is not covered.

The authors propose to extend this as a software solution to the onboard avionics systems by considering the required architectural changes. This solution can also bring in positive results for unmanned air vehicles in addition to the commercial aircrafts. Enhancement of security to the key operational and navigation data elements is going to be invaluable for future air traffic management and saving lives of people.

The proposed solution has been practically implemented by developing the hardware and software as part of this research. This has been clearly brought out in the paper. The implementation has been tested using the actual ADS-B data/messages received from using the ADS-B receiver. The solution works perfectly, and this brings immense value to the aircraft-to-aircraft and aircraft-to-ground communications, specifically while using ADS-B data for communicating the position information. With the proposed architecture and minor software updates to the onboard avionics, this solution can enhance safety of flights.

This study examines herding behaviour in commodity markets amid two major global upheavals: the Russo–Ukraine conflict and the COVID-19 pandemic.

By analysing 18 commodity futures worldwide, the study examines herding trends in metals, livestock, energy and grains sectors. The applied methodology combines static and dynamic approaches by incorporating cross-sectional absolute deviations (CSAD) and a time-varying parameter (TVP) regression model extended by Markov Chain Monte Carlo (MCMC) sampling to adequately reflect the complexity of herding behaviour in different market scenarios.

Our results show clear differences in herd behaviour during these crises. The Russia–Ukraine war led to relatively subdued herding behaviour in commodities, suggesting a limited impact of geopolitical turmoil on collective market behaviour. In stark contrast, the outbreak of the COVID-19 pandemic significantly amplified herding behaviour, particularly in the energy and livestock sectors.

This discrepancy emphasises the different impact of a health crisis versus a geopolitical conflict on market dynamics. This study makes an important contribution to the existing literature as it is one of the first studies to contrast herding behaviour in commodity markets during these two crises. Our results show that not all crises produce comparable market reactions, which underlines the importance of the crisis context when analysing financial market behaviour.