Purpose: Our study investigates the combined effects of financial technologies (fintech) and the digital economy on sustainable development, considering geopolitical risks as a moderating factor. Origin: While sustainable development is a global imperative, the integrated roles of digital transformation and fintech remain insufficiently explored. Our research addresses this gap by analyzing their impacts on socioeconomic advancement and environmental sustainability across diverse contexts. Methodology: Employing panel data from 30 developed and developing countries between 1990 and 2023, we assess sustainable development using the Environmental Performance Index (EPI) and the Human Development Index (HDI). Independent variables include proxies for the digital economy (e.g., internet usage, mobile subscriptions, and high-tech exports) and fintech (e.g., digital payments, digital currency, and peer-to-peer lending). The Geopolitical Risk Index (GPRI) is used to evaluate the effect of political instability. We apply generalized least squares (GLS) and fixed-effects estimation (within) to ensure robustness. Findings: Our results indicate that digital transformation and fintech significantly foster socioeconomic development and environmental performance, even amidst geopolitical instability. Key variables such as digital payments and internet access show substantial positive impacts, providing valuable insights for policymakers aiming to enhance resilience and sustainability. Contributions: Our article offers a comprehensive evaluation of how the digital economy and fintech jointly influence sustainable development under geopolitical risks, providing a nuanced understanding for policymakers and researchers.
This study examines the impact of Internet Banking on banking profitability in Saudi Arabia in a sample of conventional and Islamic banks. The study uses Return on Assets (ROA) and Return on Equity (ROE) as key metrics to measure profitability in a sample of 10 Saudi conventional and Islamic banks observed over the 2013–2022 period. The used regression analysis reveals a significant effect of Internet Banking on the profitability of both conventional and Islamic banks, as indicated by the ROA and ROE metrics. These findings have implications that underscore the strategic importance of adopting Internet Banking, emphasizing its substantial contribution to the financial performance of both conventional and Islamic banks in the Saudi Arabian banking landscape. This study offers critical insights into the strategic significance of Internet Banking for Saudi Arabian banks’ profitability and future planning, in line with the 2030 Vision goals. This research also supports informed decision making in the digital era, emphasizing the pivotal role of Internet Banking in shaping the future of the Saudi Arabian banking industry.
In this study, we delve into the financial market to compare the performance of prominent AI and robotics-related stocks against traditional IT indices, such as the Nasdaq, and specialized AI and robotics ETFs. We evaluate the role of these stocks in diversifying portfolios, analyzing their return potential and risk profiles. Our analysis includes various investment scenarios, focusing on common AI-related stocks in the United States. We explore the influence of risk management strategies, ranging from “buy and hold” to daily rebalancing, on AI stock portfolios. This involves investigating long-term strategies like buy and hold, as well as short-term approaches, such as daily rebalancing. Our findings, covering the period from 30 April 2021, to 15 September 2023, show that AI-related stocks have not only outperformed in recent years but also highlight the growing “AI bubble” and the increasing significance of AI in investment decisions. The study reveals that these stocks have delivered superior performance, as indicated by metrics like Sharpe and Treynor ratios, providing insights into market trends and financial returns in the technology and robotics sectors. The results are particularly relevant for investors and traders in the AI sector, offering a balanced view of potential returns against the risks in this rapidly evolving market. This paper adds to the financial market literature by demonstrating that investing in emerging trends, such as AI, can be more advantageous in the short term compared to traditional markets like the Nasdaq.
Artificial intelligence (AI) is transforming the internationalisation activities of multinational corporations (MNCs) through enhanced operational efficiencies and optimised decision-making; though the moderating factors influencing its impact on export-led internationalisation remain underexplored. This research adopts a Resource-Based View (RBV) approach to examine the complex relationship between AI capabilities and the export performance of Indian MNCs, with cultural distance serving as a moderating factor, analysing how AI adoption influences export intensity, trade expansion, and market penetration strategies. Data from a 2024 survey of 449 Indian exporters across various industries, analysed using Structural Equation Modelling, reveal that AI capabilities positively impact export performance particularly in markets characterised by high institutional uncertainty and complex regulatory environments. Moreover, cultural distance acts as a significant moderator, amplifying the role of AI in navigating consumer preferences, language barriers, and localised business practices. AI-powered analytics help firms better understand foreign markets, adapt to cultural differences, and optimise international operations. This study advances the scholarly understanding and contributes to internationalisation theory by integrating AI-driven trade strategies with institutional and cultural moderating factors and offers a structured framework for corporate managers and policymakers to formulate AI-based strategic decisions that leverage AI to mitigate trade-related uncertainties, improve their compliance with international regulations, and strengthen global trade competitiveness in emerging economies.
The research concentrates on determining the degree of internationalization of born global SMEs, believing that some push factors determine internationalization, pull factors, and internal firm-specific factors. Three important factors were found in looking into the causes of internationalization in born global firms: push, pull, and internal firm-specific factors. The study used a survey instrument with a sample of 280 manufacturing-related SMEs chosen from manufacturing clusters in India. A metric called the “index of internationalization” is used to gauge how internationalization in SMEs takes shape. The results demonstrated that internal firm-specific factors influence the internationalization of firms relatively highly compared to push and pull factors. The results unequivocally demonstrate that developing economies have distinct factors that cause internationalization, opening up new avenues for further study. The research aids in the identification of the elements that will enhance early internationalization and tries to draw the attention of young entrepreneurs. This research also helps prioritize the factors responsible for early internationalization. These findings are pertinent for the practitioners and researchers working in this area. This research is helpful for start-ups looking for global opportunities; this research categorizes factors significant in the global journey of the born global firms.
In this study, we explored the impact of bank leverage and financial frictions on the transmission of real and financial shocks. Two new Keynesian dynamic stochastic general equilibrium (DSGE) models, with and without financial frictions, were employed in the context of the Tunisian economy. In the analysis, we considered three types of shocks—productivity, monetary, and adverse bank capital shocks. The findings reveal that, in the model with financial frictions, the response of macroeconomic and financial variables to demand and supply shocks was more pronounced than in the baseline model, where frictions primarily exist at the borrower level. In this study, we underscored the significance of financial shocks, particularly negative bank capital shocks, in triggering substantial macroeconomic and financial fluctuations, especially when banks operate with higher leverage ratios. Additionally, the inclusion of financial frictions in the DSGE model enhanced its ability to capture the empirical features of real and financial shocks, providing valuable insights for effective monetary policymaking. The results provide foundational insights for Tunisian policymakers to assess the impact of financial frictions in the context of the Tunisian economy. This is significant for the Central Bank of Tunisia, which has not yet adopted a specific DSGE model. Therefore, through our analysis, we determined the amplificatory role of financial frictions in the dynamics of macroeconomic and financial variables in Tunisia and examined the main transmission channels of shock propagation.