The increasing epileptic electricity supply, mainly in the residential areas of Nigerian cities, has been linked to the incorrect knowledge of the numerous socio-economic and physical indices that influence household electricity usage. Most of the seemingly identified explanatory factors were done at macro level which does not give a clear estimate of this electricity demand. The thrust of the study is to analyse empirically the household electricity determinants in Nigerian cities with a view to evolving a more informed and sustainable energy policy decision. Multistage area cluster sampling method was adopted in the study where 769 copies of structured questionnaire were distributed to electricity users of prepaid meters in five major Nigerian cities. The research hypothesis was tested using the multiple linear regression statistical tool. The result revealed that nine variables which include age (r = 0.05, p-value: 0.05), household income (r = 0.00, p-value: 0.05), number of hours that people stay outside the house (r = 0.043, p-value: 0.05), number of teenagers at home, (r = 0.006, p-value: 0.01) number of electrical appliances (r = 0.016, p-value: 0.01), type of house (r = 0.012, p-value: 0.01), hours that the electrical appliances are used (r = 0.043, p-value: 0.05), weather condition, (r = 0.011, p-value: 0.05) and the location of the building (r = 0.045, p-value: 0.05) were significant in determining the household electricity consumption. Policies based on the findings will give energy and urban planners an empirical basis for accurate and robust forecasting of the determinants that influence household electricity consumption in Nigeria that is devoid of any speculation or unfounded predictions.

Agriculture is an industry that plays an essential role in economic development towards eliminating poverty issues, but foreign direct investment (FDI) inflows to this sector remain modest in Vietnam. This study analyzed the determinants of foreign direct investment in the agricultural sector into the Southern Key Economic Zone (KEZ) of Vietnam, which is considered the foreign direct investment magnet of Vietnam, but its FDI inflows into the agricultural sector have been consistently low, and has shown a downward trend in recent years. The study was based on a sample of 129 foreign investors of a total of 164 multinational enterprises (MNEs) in the agricultural sector, including representatives of the Board of Directors and representatives at the department level. The Partial Least Squares Structural Equation modeling (PLS-SEM) approach was used to test the hypotheses. Findings indicated that FDI attraction policies have the strongest impact on FDI inflows. This was followed by infrastructure, regional agriculture policies, public service quality, natural conditions, and human resources. This study suggests policy recommendations to improve foreign direct investment inflows into the agricultural sector of the Southern Key Economic Zone (KEZ) of Vietnam.

Transitioning to a green economy is a global concern, considered a pathway to sustainable development. This paper aims to investigate the effect of the transition into a green economy on Vietnam’s sustainable development and its two economic and environmental dimensions, with consideration of several essential issues including renewable energy, technological innovation, natural resource rents (oils, forest, and minerals), foreign direct investment, and trade. This paper utilizes data from 1996 to 2020 and then applies the autoregressive distributed lag (ARDL) method for analysis. The results conclude that renewable energy is a driving key to reducing environmental degradation, but it hampers economic growth, while the contrast occurs with technology. Our results emphasize the dependence on non-renewable energy, whereas the innovation of technology does not show a green orientation in Vietnam. Furthermore, there is a lack of sustainability in the effect of natural resource rents, foreign direct investment, and trade. Overall, the transition into a green economy in Vietnam does not illustrate the sustainable orientation. The findings of this research provide empirical evidence to clarify the relationship between this transition and its driving factor, with sustainable development and the two economic environment dimensions. In addition, this study will bring worthwhile implications for the policymakers and scholars on whether the transition to a green economy fulfills the orientation towards sustainability, then enhancing the economy's efficiency to achieve green growth, following the pathway to sustainable development.

Our previous research on social innovation examined the process, levels, and stakeholders of social innovation, as well as its relationship with technical and technological innovation. The present study analyzes the spatial image created by the social innovation potential and investigates its relationship with the economic power of the neighborhoods. The most important conclusion of the study is that the basic territorial inequality dimensions are the same in the case of both the social innovation potential and the district’s economic strength. The difference is primarily to be found in concentration, as economic power is much more concentrated in the capital and the most important economic and tourism centers than the social innovation potential. We can therefore state that developments based on social innovation can solve a lot of the highly concentrated spatial structure in Hungary.

The economic complexity approach presents a shift from quantitative to qualitative measures of economic performance, while economic complexity refers to the accumulation of know-how. Economic complexity is considered a predictor of economic growth and research evidences a positive relationship between economic complexity and economic growth. In the EU countries, economic convergence is observed. Hence the question of economic complexity convergence arises, too. The paper aims to analyze the convergence of 27 EU countries considering their economic complexity from 1999 to 2021 computing the beta convergence. Using the Barro-type regressions, the econometric estimations focus on four indices of economic complexity—the economic complexity index published by Harvard’s Growth Lab, and economic complexity indices on research, trade, and technology published by the Observatory of Economic Complexity. The absolute beta convergence is observed in the EU except for the economic complexity index referring to trade. When including the dummy referring to the location of EU countries in the West or East of the EU considering their wealth, the conditional beta convergence is observed except for the trade-economic complexity index, again. When altering the condition of location by the GDP per capita and other controls, the conditional beta convergence of economic complexity in the EU is observed when estimating both fixed-effect models and dynamic panel data models based on the system generalized method of moments (GMM) estimator.