Advanced digitalization and financial technology have of recent times become among the most crucial tools. Data mining and sentiment analysis have revealed the importance of digitalization in modern times. This study examines the influence of Google search activity on the volatility of digital assets. We analyzed six digital asset prices for Bitcoin, Bitcoin Cash, Ethereum, Ethereum Classic, Litecoin, and Ripple from the Coinmarketcap database. We used tweets on Twitter to survey users’ sentiment by using the Twitter search Application Programming Interface and Google trend search from web searches, news searches, and YouTube searches data using RStudio software. The study spanned 1 September 2019 to 31 January 2020 and employed the Vector Autoregression (VAR) approach for analysis. The VAR estimation revealed that Google search variables have significantly influenced the volatility of Bitcoin, Ethereum, Litecoin, and Ripple, as supported by the Granger causality test and impulse response function. The results of this study could be useful for investors and policymakers in drawing up strategies to reduce market volatility. These results should thus be useful to investors in developing profitable investment strategies to mitigate the impact of market turbulence.

This study provides new evidence regarding the nonlinear relationship between energy consumption and economic growth in the Middle East and North Africa (MENA) region for the 1990–2014 period. The empirical estimation is conducted using a dynamic panel threshold model. We found one threshold in the relationship between energy consumption and economic growth and one threshold in the relationship between carbon dioxide (CO₂) emissions and economic growth. The results indicate that energy consumption positively and significantly affects economic growth in the low energy consumption regime. In contrast, it has a negative and significant impact on economic growth in the high energy consumption regime. Moreover, CO₂ emissions are positively and significantly related to economic growth in the low regime of CO₂ emissions. Nevertheless, the relationship between CO₂ emissions and economic growth in the high CO₂ emissions regime is negative and significant. Therefore, policymakers should implement other effective energy policies, such as stricter regulations on CO₂ emissions, increase energy efficiency, and replace fossil fuels with cleaner energy sources to avoid unnecessary CO₂ emissions and combat global warming. Future studies should identify the root causes of failures and issues in real time for inflation and link the energy–growth nexus to achieving the 2030 Sustainable Development Goals (SDGs) Agenda, Goal 7: Affordable and Clean Energy.

The effects of climate change are diverse and impact several aspects of the environment, coastal activities, social dynamics, economic factors, and drivers of growth. This paper investigates the vulnerability assessment caused by climate change in one of Malaysia's coastal areas. We analyze the relationships between indicators of vulnerability by correlating the perceptions of a community characterised by both identified and anticipated climate change situations, whereby we develop a risk perception index that comprises cognitive, contextual, and affective factors as one of the indicators under exposure indices. The Composite Vulnerability Index (CVI) methodology was used to provide a comprehensive assessment of the community's vulnerability to climate change in Kuala Gula. The area is very vulnerable to dwindling fresh water supplies, changing climate, and poor socioeconomic resources of the local population. Data on three components of CVI (exposure, sensitivity, and adaptive capacity) were collected from household members using a close-ended questionnaire-based survey. Our analysis demonstrates that these coastal communities are prone to vulnerability and greater consequences regarding threats associated with climate change, as the CVI of Kuala Gula was considerably high. In addition, the results indicated that the exposure index was high, while the sensitivity and adaptive capacity indices were at moderate levels. From the statistical analysis of the exposure and perceptions indices, we found that an increased level of vulnerability to the impacts of climate change led to greater perceptions among Kuala Gula coastline communities regarding climate change. Furthermore, a lack of financial capital and low-income households has a detrimental impact on the overall adaptive ability of the local community. As a result, the methodology may assist local policymakers in integrating and enhancing local multi-hazard knowledge in relation to the concepts of exposure, sensitivity, and adaptive ability, as well as in making information usable for mitigation and adaptation of climate change within these communities.

A ban on palm oil imports by the European Union has become a problematic issue, especially for palm oil producers’ countries. Oil palm has been widely used in many sub-sectors, and any changes in the production side may affect many sectors that use oil palm as an input factor in their productions. This study explores the chain of the oil palm sector on the other sub-sectors in Malaysia by using a value-added multiplier method and network modeling. The study focuses on the specific oil palm sub-sector and oils and fats sub-sector in the Malaysian economic structure based on the Malaysian Input-Output 2015 Table. Network visualization and all the analyses involving network methods were developed and performed using UCINET and GEPHI software. The value-added multiplier results explained that the net value between output multiplier and import multiplier is vital to depict the real impact of net resources used as an input factor in the oils and fats and oil palm sub-sectors. The high-density value level shows that the Malaysian oil palm sector has high connectivity in the economic system. From the network visualization analysis, the oils and fats sub-sector has a high level of integration with other sectors within the network. Meanwhile, the oil palm sub-sector categorized in the periphery structure group has a low level of integration in the input-output network. This is due to the high value-added demand for oil palm in the oils and fats sub-sector in the manufacturing sector. Overall, most of the sub-sectors in Malaysia are highly interconnected due to the high clustering ratio. Therefore, ensuring sufficient oil palm production is vital for sustainable production of other sub-sectors.

The sudden expansion in financial technology (FinTech) has altered conventional banking immensely by transforming operations, customer services, and risk management systems. This research therefore employs a systematic literature review (SLR) approach that adheres to Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) standards to assess the influence of FinTech on three bank performance indicators: operating efficiency, risk management, and customer service. A total of 41 peer-reviewed articles, published between 2018 and 2024, were shortlisted from Scopus and Web of Science (WoS). Out of these, 19 utilized frontier efficiency techniques like stochastic frontier analysis (SFA) and data envelopment analysis (DEA). The results indicate that FinTech improves operating efficiency when integrated optimally, as noted by Allen et al. (2022). Yet, outcomes differ by region and type of bank, as some Chinese banks have seen a decline in efficiency (Lee et al., 2023). In risk management, FinTech technologies such as artificial intelligence (AI) have been shown to decrease operational risk (Cheng & Qu, 2023). Customer satisfaction is enhanced further with digital services and personalization (Barbu et al., 2021). Although adoption poses additional risks, the research concludes that FinTech implementation, if managed strategically, will increase bank performance. This review thus offers actionable advice for policymakers and financial institutions to navigate digital transformation.