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This study explores the association between market efficiency and speculation. The government of India temporarily banned the futures trading of various commodities several times citing the presence of speculation. Many controversies exist about this topic; thus, this study clarifies the association between market efficiency and speculation and investigates whether market reforms altered this association.

The data for nine commodities is collected from the National Commodity and Derivative Exchange (NCDEX) for 2005–2022. Regression analysis and Automatic Variance Ratio (AVR) were adopted to inspect the informational efficiency and influence of speculation in the commodity market. Furthermore, this study uses different sub-samples to understand the changes in the market microstructure and its effects on market quality.

The results confirm an inverse and significant relationship between information efficiency and speculation and a deviation from the random walk process observed. Therefore, return predictability exists in the market. This study confirms that market reforms do not reduce the influence of speculation on market efficiency. The study concludes that the market is not weak-form efficient.

This study has certain limitations, since this study is empirical in nature, it may possess the limitations of empirical research.

This paper has dual novelty. First, this study investigates the effects of market reforms. Second, this study captures the influence of speculation in the Indian agricultural commodity market by considering the market microstructure aspects.

This paper aims to examine the effect of external Sharia audit on the performance of Islamic banks in Bahrain and Oman, which are countries that implement it. This study aims to explore the role of external Sharia audit in preventing prohibited profits and mitigating the risks of noncompliance with Sharia principles.

This paper opted a quantitative approach and collected data from the employees of the Sharia Supervision Board & Sharia Audit in the Islamic banks. This paper studied how external Sharia audit affects the financial profitability and compliance with Islamic Sharia principles of Islamic banks, using partial least squares structural equation modeling technique.

The results indicated that external Sharia audit had a significant positive effect on both financial profitability and compliance with Islamic Sharia principles in the Islamic banks under study. This means that external Sharia audit enhances the financial performance and the adherence to Islamic Sharia principles of the Islamic banks.

This study has some limitations that suggest directions for future research, such as expanding the sample to other countries and measuring more performance indicators for Islamic banks.

This study suggests that external Sharia audit enhances the performance and compliance of Islamic banks and urges the regulators to adopt it and standardize it.

This study contributes to the literature on Islamic finance and external Sharia audit by providing empirical evidence on the impact of external Sharia audit on the performance of Islamic banks.

We investigate connections between the development of Fintech and the blue economy from September 14th, 2020, to August 11th, 2023.

In this research, we use a cutting-edge model-free connectedness approach to investigate the relationships between FinTech and blue bond volatility. Our work is the first to investigate the effects of unknown events, such as the COVID-19 pandemic and Ukraine–Russia conflicts, on the interconnection of volatility derived from FinTech development and blue bond volatility.

Our results highlight the two-way relationship between the development of Fintech and the blue economy during our sample period. The net total connectedness shows that the blue economy index is a net shock receiver, especially in late 2021 and the second half of 2022, while most of the fintech indexes in our sample are mainly net shock transmitters. The Ukraine–Russia tension threatens the development of a sustainable blue economy. The development of Fintech plays an important role in promoting the blue economy.

Our results have important policy implications for investors and governments, as well as methods from the spillovers across the various indicators and their interconnections. Sharp information on the primary contagions among these indicators aids politicians in designing the most appropriate policies.

Our paper contributes to the literature in at least four ways. First, as previously stated, our article is the first to investigate the relationship between FinTech and blue bond volatility. Second, this study presented a framework for studying volatility interconnections between distinct variables that is more suited to analyzing these interconnections. In this research, we use a cutting-edge model-free connectedness approach to investigate the relationships between FinTech and blue bond volatility. Third, our work is the first to investigate the effects of unknown events such as the COVID-19 pandemic and Ukraine–Russia conflicts on the interconnection of volatility deriving from FinTech development and blue bond volatility. Lastly, our research provides a daily dataset for the BNP Paribas Easy ECPI Global ESG Blue Economy UCITS ETF to analyze 50 businesses from various markets that are at the forefront of the responsible application of ocean resources and other ESG standards. The Global X FinTech ETF (FINX) and the ARK FinTech Innovation ETF (ARKF) seek exposure to companies developing financial technology innovations. The development sectors include insurance, investment, fundraising and third-party lending by utilizing cutting-edge mobile and digital technologies. Our time series runs from September 14th, 2020, to August 11th, 2023. By using this database, we provide a comprehensive analysis of the link between the volatilities arising from various markets.

This study aims to explore the challenges faced by the tourism and hospitality industry following the COVID-19 pandemic and to propose effective strategies for recovery and resilience of this sector.

The study analysed the challenges encountered by the tourism and hospitality industry post-pandemic and identified key strategies for overcoming these challenges. The study utilised the modified Delphi method to finalise the challenges and employed the Best-Worst Method (BWM) to rank these challenges. Additionally, solution strategies are ranked using the Criteria Importance Through Intercriteria Correlation (CRITIC) method.

The study identified significant challenges faced by the tourism and hospitality industry, highlighting the lack of health and hygiene facilities as the foremost concern, followed by increased operational costs. Moreover, it revealed that attracting millennial travellers emerged as the top priority strategy to mitigate the impact of COVID-19 on this industry.

This research contributes to understanding the challenges faced by the tourism and hospitality industry in the wake of the COVID-19 pandemic. It offers valuable insights into practical strategies for recovery. The findings provide beneficial recommendations for policymakers aiming to revive and support these industries.

This research aims to determine the impact of the agriculture, fishing, and livestock sector (AFL sector) on the gross domestic product (GDP) of the United Arab Emirates (UAE) from 1975 to 2022. The authors use the Augmented Dickey–Fuller test (ADF), Granger causality, Vector autoregression (VAR), Ordinary least squares (OLS), and Autoregressive conditional heteroskedasticity (ARCH) techniques. The causal relationship between the UAE AFL sector and the GDP and its main sectors was studied in the short and long terms. The research concludes that the total GDP, oil GDP, and nonoil GDP respond to changes in the AFL sector and vice versa, which explains the positive role played by such a sector in the UAE's economy in the short and long terms. The study recommends that the government direct attention to the AFL sector as an additional source of income for the state, which will reduce dependence on the country's oil sector. The study also emphasizes the necessity of economic development in the AFL sector and at the level of all economic sectors to achieve the country's comprehensive long-term Sustainable Development Goals (SDGs).

This paper makes a novel attempt to estimate the potential impact of credit risk on foreign direct investment (FDI hereafter), thereby focusing on a completely unexplored area in the existing empirical literature.

To provide a comprehensive understanding of the relationship between credit risk and FDI inflows, the study incorporates all the eight-member economies of the South Asian Association of Regional Cooperation (SAARC hereafter) and analyzes a panel data set, over the period 2011 to 2019, extracted from the World Development Indicators, using the suitable econometric techniques for the efficient estimations of the specified models.

The results indicate a negative and statistically significant relationship between the credit risk of the banking sectors and FDI inflows. Similarly, market size and inflation rate appear to be the two other main factors behind the increasing FDI inflows in the SAARC member economies. Interestingly, the size of the market became irrelevant in attracting FDI inflows when the Indian economy is excluded from the sample due to its higher economic weight. On the other hand, FDI inflows are not dependent on the level of trade openness, with most of the specifications showing either an insignificant or negative coefficient of the variable.

The obtained results are unique and robust to alternative methodologies, and hence, the SAARC economies could consider them as the critical inputs in formulating the appropriate policies on FDI inflows.

The findings are unique and original. The authors have established a relationship between credit risk and FDI for the first time in the SAARC context.

The authors construct two time-varying political connection (PC) indexes to measure a firm's political tendencies toward ruling and opposing parties and analyze whether a firm with ruling party tendencies obtains better bank loan contracts compared to the contracts obtained by a firm with opposing party tendencies and a firm with fixed PC tendencies.

Linguistic text mining is used to construct the two time-varying PC indexes from news sources that reflect the tone and frequencies of characteristic texts to determine a firm's tendencies to favor the ruling or opposing parties.

The results show that varying PC firms connected to the ruling party receive preferential loan contracts when their political tendencies increase but varying PC firms connected to the opposition party do not. In contrast, fixed PC firms gain similar benefits only when the connection is determined in the presidential election year but not in other years. Firms supporting two parties receive minimal financial rewards in terms of loan terms.

In past studies, once a firm is identified as having a connection with a political party, it is assumed to have PC throughout the sample period (i.e. fixed PC firms). The authors lift this assumption and examine how varying PC affect bank loan contracts. The two time-varying PC indexes can identify a firm's more immediate party tendencies and more precise effects of a firm's party tendencies on bank loan contracts.

In this work, the authors analyze the dynamic interdependencies between military expenditures and the real economy for the period 1970–2018, and the authors' approach allows for the existence of dominant economies in the system.

In this study, the authors employ a Network General Equilibrium GVAR (global vector autoregressive) model.

By accounting for the interconnection among the top twelve military spenders, the authors' findings show that China acts as a leader in the global military scene based on the respective centrality measures. Meanwhile, statistically significant deviations from equilibrium are observed in most of the economies' military expenses, when subjected to an unanticipated unit shock of other countries. Nonetheless, in the medium run, the shocks tend to die out and economies converge to an equilibrium position.

With the authors' methodology the authors are able to capture not only the effect of nearness on a country's military spending, as the past literature has documented, but also a country's defense and economic dependencies with other countries and how a unit's military expenses could shape the spending of the rest. Using state-to-the-art quantitative and econometric techniques, the authors provide robust and comprehensive analysis.

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.

The study aims to investigate the relationship between E-government and corruption. It also examines the moderator role of national culture through Hofstede’s dimensions on the association between E-government and corruption.

In addition to panel regression techniques, the authors use the random forest method to assess the order of importance of all significant variables in determining corruption. The sample of this study consists of 55 countries during 2008–2020 period.

The results show that E-government is negatively correlated with corruption. The authors also find that both economic and cultural variables play an important role in determining corruption. However, religion has no impact on corruption. The results can potentially assist regulators and policy-makers when trying to control corruption as they should take into consideration the cultural background of citizens when making rules and procedures that aim at reducing corruption.

The current study uses random forests model, which allows the regression of variables based on the construction of a multitude of decision trees. The main contribution of using this model compared to the other regression models used in prior studies is to extract the relative importance of each significant variable. More precisely, it evaluates the rank of importance for each significant variable that drives corruption rather than merely identifying variables that drive corruption regardless of their relative importance.