Analysis of the impact of foreign direct investment on urbanization in China from the perspective of "circular economy"

Determinants that attract and discourage foreign direct investment in GCC countries: Do macroeconomic and environmental factors matter?

In general, foreign direct investments (FDIs) play a crucial role in driving a country's economic development, promoting diversification, and enhancing competitiveness. The Gulf Cooperation Council (GCC) countries, which heavily rely on the oil and gas sectors, are particularly vulnerable to fluctuations in commodity prices. However, these countries have recognized the imperative of economic diversification and have increasingly turned to inward FDIs to achieve it. By attracting capital, advanced technology, and expertise from foreign investors, FDIs enable the GCC countries to expand their economic base beyond the oil and gas sectors. This diversification not only creates employment opportunities but also fosters resilient economic growth, ultimately leading to an improvement in the living standards of the local population. This study investigates the macroeconomic and environmental factors that potentially attract foreign direct investment (FDI) inflows into the Gulf Cooperation Council (GCC) countries in the long run. Additionally, the study explores the causal relationship between these factors and FDI inflows. The panel autoregressive distributed lag (ARDL) approach to co-integration is the primary analytical technique used, utilizing long time-series data from six GCC countries, including Bahrain, Kuwait, Oman, Qatar, Saudi Arabia, and the United Arab Emirates (UAE) during the period 1990-2019. The empirical results indicate that, in the long run, almost all independent variables significantly influence FDI in GCC countries. Variables such as GDP growth (GDPG), inflation (INFL), carbon dioxide emissions (CO2), and urbanization (URB) are found to be highly significant (p≤0.01) in their impact on FDI. Moreover, unemployment (UNEMP) also positively and significantly influences FDI in these countries in the long run. Based on the key findings, strategies aimed at reducing persistently high unemployment rates, maintaining population growth, viewing FDI as a driver for GDP growth, and continuing with infrastructure development and urbanization are expected to attract more FDI inflows into GCC countries in the long run. Additionally, fostering both long-term economic incentives and creating a conducive business infrastructure for investors are vital for attracting inward FDI into any nation, including those in the GCC. This research would benefit various stakeholders, including governments, local businesses, investors, academia, and the local society, by providing valuable knowledge and informing decision-making processes related to economic development, diversification, and investment promotion.

Bibliometric Analysis of Current Status of Circular Economy during 2012–2021: Case of Foods

Food is usually recognized as a limited resource in sustainability, recognized by the United Nations (UN) Sustainable Development Goal (SDG) 2, which aims to achieve zero hunger. It is expected that the circular economy (CE) can improve processes related to food production. The objective of the present study was to apply a bibliometric approach using VOSviewer visualization software as a research tool to analyze the relevant literature from the Scopus database in the field of circular economy and its relation to improvements in food issues throughout 2012–2021. A total of 1316 articles were analyzed. Italy was the most productive country with 313 articles, with Wageningen University & Research the organization with the most publications with 39 articles. The top 10 institutions originated from Italy, The Netherlands, France, and Denmark. Sustainability was the most productive journal with 107 articles. Bioresource Technology had the highest average citation frequency (44.68). The study helps initiate investigations to adapt the results obtained and create new strategies for increasing food circular economy efforts.

The nexus between environmental regulation and ecological footprint in OECD countries: empirical evidence using panel quantile regression

Environmental regulation is an important tool for policymakers to achieve environmental goals. To better understand the role of environmental regulation in protecting the ecosystem, this paper offers a new perspective on exploring the heterogeneous impact of environmental policy stringency on the ecological footprint in 27 OECD countries during the period 1990-2015. An advanced economic method, panel quantile regression, is conducted to deal with the non-normality and unobserved individual heterogeneity across countries. The estimation outcomes indicate that the environmental effect of policy stringency is heterogeneous along the quantiles and different between the ecological footprint of consumption and production. The beneficial role of environmental regulation in reducing consumption ecological footprint is achieved at quantiles under 80th but the harmful effect starts occurring at extreme high quantiles. In contrast, environmental policy stringency plays a consistently useful role in mitigating production ecological footprint. In addition, the results disclose that the effects of other driving factors such as international trade, energy efficiency, renewable energy, and income are heterogeneous at different quantiles of ecological footprint. These findings help explain the inconsistencies in previous empirical studies on the nexus between environmental regulation and environmental quality in OECD countries. Finally, the current study gives policymakers useful recommendations on how to strengthen the beneficial impacts of environmental policies on the ecosystem.

How do varying socio-economic factors affect the scale of land transfer? Evidence from 287 cities in China

With the rapid development of China's social economy, the scale of land transfer has also increased, which has led to a new pattern of urban land space. This article uses global regression of ordinary least squares (OLS), spatial lag model (SLM), spatial error regression model (SEM) and local regression of geographically weighted regression model (GWR), and multi-scale geographically weighted regression model (MGWR) to explore the influence of socio-economic factors on the scale of land transfer. The relationship between these factors and the scale of land transfer varies greatly from region to region. The local model (MGWR) can express the non-stationary relationship between variables, and the regression estimation results are more robust. The results show that total investment in fixed assets (TIFA) and the non-agricultural population (NAP) had significant effects on the scale of land transfer in 2005, with regression coefficients of 0.964 and -0.247, respectively. In 2010, per capita GDP (PCG), population density (PD), proportion of tertiary industry in GDP (PTIG), and TIFA had significant impacts on the scale of land transfer, and the corresponding impact coefficients were 0.413, -0.085, -0.081, and 0.322. In 2015, the variable of PCG had significant impact on land transfer, with the coefficient of 0.048. The influencing factors of the scale of land transfer are changing at different points in time, and the formulation of land transfer policies should be treated differently according to the different socio-economic conditions in each period.

A Roadmap for Innovation Capacity in Developing Countries

Innovation capacity is a dynamic capacity linked with the achievement of competitive advantage. Several mechanisms have been proposed to evaluate this capacity. However, developing innovation capacity is a complex process, particularly for developing countries, due to the intricacy of its determinants. Hence, this research analyzes the interlinkages between the key determinants driving this capacity to further propose a continuous path for its growth. A comprehensive review of the literature regarding assessing mechanisms for innovation capacity was conducted, which included 14 key innovation determinants. From a contextual and systematic approach, interpretive structural modelling was employed to determine the interlinkages of these determinants and classified as drivers or dependent. Ten levels or steps were drawn from level partitioning of the final reachability matrix. The results show the relevance of promoting and protecting innovation and intellectual property as the ground to develop this capacity. In addition, R&D investment and university–industry collaboration contribute to the consolidation of innovation systems. Utility models, patents, trademarks, and institution prominence are the result of this loop of innovation capacity development. From these findings, policymakers, practitioners, and scholars can draw a sustained roadmap to enhance this dynamic capacity in their countries.

How does green technology innovation affect urbanization? An empirical study from provinces of China

The construction of new-type urbanization with the theme of innovation, green, and smart development is becoming the endogenous driving force of China's economic transformation and upgrading, and green technological innovation is a key factor in cracking the problems of development motivation and environmental constraints in urbanization construction. This paper investigates the impact of green technology innovation on urbanization based on a panel dataset covering 30 provinces in China from 2005 to 2019. First, we use the entropy method and the super-efficiency DEA method to measure the level of urbanization and green technology innovation, respectively. Moreover, on this basis, we use panel regression model and FGLS model to estimate the direct impact of green technological innovation on urbanization and its three dimensions-population urbanization, industrial urbanization, and ecological urbanization. Then, the mediating effect model is used to further study the indirect impact of green technological innovation on urbanization. The results indicate that green technological innovation is the most effective way to promote the development of new urbanization currently. In addition, green technology innovation can indirectly affect urbanization through the effects of foreign capital, energy consumption and information development, while the effect of industrial structure optimization effects is not significant. Finally, some policy suggestions are discussed to better promote the development of urbanization in China.