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• Open Access Article Macroeconomics

  14 Pages Download PDF: Technological Innovation, Governance Institutions, Infrastructure Development, and Economic Complexity in Africa: Evidence from Dynamic Panel Data

  Technological Innovation, Governance Institutions, Infrastructure Development, and Economic Complexity in Africa: Evidence from Dynamic Panel Data

  Obed Ifeanyichukwu Ojonta, Jonathan Emenike Ogbuabor

  2026-03-17 https://doi.org/10.36923/ie-frontiers.v29i1.419

  Africa continues to face persistent development challenges, including poverty, income inequality, limited access to healthcare services, and disparities in education. These challenges contradict the objectives of the Sustainable Development Goals (SDGs), which emphasize the importance of innovation, infrastructure development, and strong institutions. Technological innovation has increasingly been recognized as a key channel for promoting infrastructure development, improving economic complexity, and strengthening institutional performance. Motivated by these considerations, this study examines the combined effects of technological innovation, governance institutions, human capital development, infrastructure, and foreign direct investment on economic complexity in Africa. In addition, the study investigates how technological innovation, governance institutions, remittances, foreign direct investment, and economic complexity influence infrastructure development across African economies. The analysis employs the system generalized method of moments (system GMM) estimator using panel data for 31 African countries covering the period from 2011 to 2020. The results reveal that technological innovation has a positive and statistically significant effect on both economic complexity and infrastructure development in Africa. However, the indicators of governance institutions are largely negative and statistically insignificant in their influence on economic complexity and infrastructure. Furthermore, governance institutions do not significantly moderate the relationship between technological innovation and these development outcomes. These findings highlight the importance of strengthening technological innovation systems while addressing institutional weaknesses to promote sustainable economic development across the African continent.

  pp. 11-24 Abstract views:634 Downloads:581

• Open Access Article Digital Economy

  17 Pages Download PDF: Impact of Urban Digital Economy on ESG Performance: Do Technological and Business Model Innovation Matter

  Impact of Urban Digital Economy on ESG Performance: Do Technological and Business Model Innovation Matter

  Shuhua Zhang

  2024-11-27 https://doi.org/10.36923/iefrontiers.v28i1.278

  The rapid development of the digital economy is a critical national strategy for the Chinese government, with the establishment of digital economy platforms as a key component. Simultaneously, both the government and enterprises have embraced the concept of sustainable development. Since corporate environmental, social, and governance (ESG) performance serves as a crucial micro-indicator of sustainability, it is essential to investigate whether the digital economy platforms developed by the Chinese government can enhance the ESG performance of relevant companies. This paper first examines the impact of urban digital economy platform construction on corporate awareness of ecological and environmental protection, social responsibility, and governance practices. It then proposes two primary mechanisms—technological innovation and business model innovation. Finally, empirical evidence is presented based on a sample of 107 urban CSI 300-listed companies in China, using data from 2015 to 2019. The analysis yields three key findings: (1) the construction of urban digital economy platforms significantly improves the ESG performance of companies in the region; (2) the impact on the social subindex is not significant, but the effect is more pronounced in non-state-owned enterprises, the manufacturing sector, and the eastern region; and (3) business model innovation plays a more significant role in driving ESG performance compared to technological innovation. This study contributes to the understanding of how digital economy platforms influence corporate ESG performance.

  pp. 14-30 Abstract views:702 Downloads:312

• Open Access Article Economics

  16 Pages Download PDF: When Green Accounting Fails to Drive Green Energy: Institutional Quality and China’s Renewable Energy Transition

  When Green Accounting Fails to Drive Green Energy: Institutional Quality and China’s Renewable Energy Transition

  Saqib Munir, Mushab Rashid, Abdul Ghaffar

  2026-05-17 https://doi.org/10.36923/ie-frontiers.v29i1.426

  This study examines how institutional quality, government R&D expenditure, and SEEA-aligned environmental asset indicators are associated with renewable energy adoption in China from 1999 to 2023. It addresses the puzzle that environmental accounting signals and innovation investment do not automatically translate into renewable energy use. Annual data from the World Development Indicators and Worldwide Governance Indicators were analyzed using a hybrid empirical strategy. The Autoregressive Distributed Lag approach was applied to estimate short-run and long-run relationships, while Double Machine Learning, Random Forest, Gradient Boosting, and SHAP interpretability were used as supplementary tools for robustness and predictive importance. Given the limited sample size, machine-learning results are interpreted as orthogonalized associations and as predictive evidence rather than as definitive causal effects. ARDL results show that regulatory quality has a positive and statistically significant long-run association with renewable energy adoption. In contrast, government R&D expenditure and adjusted net savings show negative associations, suggesting that innovation spending and fiscal capacity may not support renewable energy adoption unless directed toward deployment and energy-system substitution. Energy resource depletion is statistically insignificant, while natural resource rents show a weak positive long-run association. Machine-learning results identify government R&D expenditure as the strongest predictor, although its direction remains negative. The findings indicate that China’s renewable energy transition depends less on fiscal or technological inputs alone and more on the institutional capacity to convert these inputs into adoption outcomes. The study implies that SEEA-based indicators should be integrated with regulatory mechanisms, deployment-oriented innovation policy, and outcome-based evaluation of energy transition.

  pp. 25-40 Abstract views:516 Downloads:170