Research in Globalization最新文献

This study extensively examines crowdfunding to promote and enhance digital financial inclusion. The goal of this research is to investigate the role of crowdfunding in digital financial inclusion and to establish a standardized measure for comparing the level of financial inclusion across various economies worldwide. Through a comprehensive analysis of relevant scholarly literature and empirical data, this research study presents an in-depth investigation. The study shows that crowdfunding can contribute to financial inclusion through various models, including Reward-based CrowdFunding, Community-based CrowdFunding, Segregated Client Model, Notary Model, Guaranteed Return Model, Crowd-funding Asset Securitized Model, Donation-based CrowdFunding, Equity-based CrowdFunding, and Debt-based CrowdFunding. This study also shows that Singapore maintains its top position as the most financially inclusive market. Singapore is positioned at the top regarding the pillars of government assistance, employer support, and financial system support, ranking first, second, and third, respectively. This study will provide valuable insights for organizations seeking to establish their own crowdfunding platforms, as well as individuals interested in showcasing their businesses on such platforms.

In the Gulf Cooperation Council (GCC) region, comprising Saudi Arabia, the United Arab Emirates, Kuwait, Bahrain, Qatar, and Oman, advanced urban planning and cutting-edge projects signify a dedication to modernity and prosperity. These nations, renowned for substantial energy reserves, are crucial players in the global energy landscape, contributing 45% of proven oil reserves, 25% of oil exports, and 18% of proven natural gas reserves. Significant investments in planned cities showcase the GCC region’s commitment to renewable energy with megaprojects serving as key promoters of a nationalist vision for modernization and sustainability. Criticism has been directed at ambitious designs and sustainability rhetoric, as seen in projects like Masdar City, originally envisioned as carbon-neutral but encountering challenges in realization.

The implementation of Smart Cities in Oman is in its early stages, marked by a lack of comprehensive industry-level studies and an absence of an established frameworkbased approach. Limited industry-level studies address citizen-centric Smart governance thereby impacting Quality of Life. Current research emphasizes technology and innovation rather than the cultural sentiments of the local community resulting in gaps in people-centric approach. Moreover, there’s no empirical research to validate the influence of People on Public-Private Partnership enterprises in Smart City development, necessitating the development of a conceptual framework or model to highlight the influence of people on Smart Cities. This deficiency is resulting in a stagnation of innovation and an insufficient quality of life. The goal is to measure the effectiveness of the participatory governance model in improving the quality of life for residents within the smart city. By addressing the identified deficiencies through the application of participatory governance, the research aims to pave the way for a more effective and people-centric approach to smart city development, ultimately fostering innovation, enhancing the quality of life, and promoting sustainable and inclusive outcomes.

Most of the developed and developing nations focus on the transformation of city livelihood through the development of smart cities. Waste management in smart cities is a critical concern for policymakers and smart city administration. The fourth industrial transformation (hereafter Industry 4.0) helps to improve waste management practices in smart cities to improve the sustainability of the city. This paper tries to develop a roadmap for industry 4.0 technologies relevant to managing waste in smart cities. This paper proposes a novel framework for analyzing the deployment enablers of Industry 4.0 technologies, implementation barriers, current best practices, and opportunities for digital technologies (EBPO) for smart city transformation. The proposed EBPO conceptual framework is analyzed in the context of studies conducted in developed and developing countries. The EBPO presents the unique linkages among the technological advancements for managing waste in smart cities. The present research is an early attempt to explore the relevance of industry 4.0 technologies in the smart waste management context for improving environmental sustainability. The keyword and theme mapping analysis proposes three major waste management clusters in smart cities. This paper provides insight for improving EBPO elements for smart cities’ waste management. The policy and theoretical implications are presented for smart city stakeholders. The paper also highlights the different dimensions of the EBPO framework.

This study investigates the relationship between higher education and mortality rates from chronic and fatal diseases in MENA countries from 2000 to 2020. Utilizing a robust panel econometric framework with Generalized Least Square, Fully Modified Ordinary Least Squares (FMOLS), and Dynamic Ordinary Least Squares (DOLS), we analyze empirical data while controlling for globalization, CO2 emissions, and GDP per capita. Our findings reveal a significant negative correlation between education and mortality rates, paralleled by similar trends for globalization and GDP per capita. Conversely, CO2 emissions are found to increase mortality rates, highlighting the detrimental impact of environmental degradation on public health. This underscores the pivotal role of education, globalization, and economic development in reducing mortality rates associated with chronic and fatal diseases. The study advocates for increased investments in education and healthcare infrastructure to address disparities and enhance public health outcomes, alongside promoting responsible globalization practices to further improve health metrics.

In developing nations, remittances play a vital role in the development of the society. Remittances serve as a substantial income stream for rural households, empowering them to invest in farming activities, procure resources, and enhance their overall quality of life. This study focuses on investigating remittance utilization patterns in agriculture and how do socio-economic, demographic and migration factors influence remittance utilization patterns in agriculture in the Middle Ganga Plain region (Eastern Uttar Pradesh and Bihar) of India? The study utilizes the data from the Middle Ganga Plain (MGP) migration survey (2021) conducted by the International Institute for Population Sciences, Mumbai. With the help of bivariate analysis, the study explores the relationship between socioeconomic and migration characteristics and the utilization of remittances in the agricultural sector. The Chi-Square test validates the findings, followed by a Binomial Logistic Regression Model for further analysis. The study reveals that marginalized social groups are more inclined to use remittances for agriculture due to their active involvement in agriculture. Furthermore, households with larger landholdings demonstrate an increased likelihood of remittance utilization across all agricultural sectors. Additionally, it was observed that remittances in agriculture were more prevalent among female-headed households. Moreover, parents who are recipients of remittances tend to allocate their funds to agricultural activities. The significant positive correlation between monthly remittance receivers and total agricultural expenses underscores the importance of remittances in rural development. This study provides valuable insights into remittance utilization patterns and associated factors in the agricultural sector, highlighting the need for targeted policies and interventions to enhance the efficient and effective use of remittances in agriculture, ultimately contributing to rural economic growth and development.

Despite Kenya dominating trade volumes in the East African Community (EAC), it has been trading below its potential within the region. This is also in spite of the increased scope of the country’s trade opportunities resulting from the region’s increased market integration. Empirical evidence has shown that macroeconomic policies influence international trade flows. However, there is limited empirical evidence on the effect of macroeconomic policies on trade efficiency. The few existing studies on this topic have also used estimation techniques that depict efficiency as being drawn from an average level of trade and not the optimal level of trade, as well as also not separating the effects of inefficiencies from the statistical noises. This, therefore, creates a knowledge gap that this study aims at investigating by using the stochastic frontier gravity model (SFGM), to determine the effect of Kenya’s macroeconomic policies on its trade efficiency within the EAC. The study used annual panel secondary data for the period 2000 to 2021. This study finds that the GDP of Kenya and that of its EAC trading partners, the geographical distance and border significantly affects trade volume. It also finds that globalization plays a significant role in influencing Kenya’s trade. For the inefficiency model variables, exchange rate depreciation was found to significantly increase trade efficiency, while increase in tariff rate had an adverse and significant effect. Further, the study included corruption as a control variable and found that it significantly increases trade inefficiency. Kenya, though trading at an average efficiency level of 86.91 percent, was found to have high unexploited trade potentials within the region especially with Tanzania and Uganda. The study recommends that Kenya’s policymakers deliberately advance the macroeconomic policies that promote trade efficiency while at the same time closely monitor the ones that hinder efficiency.

Methane (CH4), an often-overlooked greenhouse gas (GHG), has a significant impact on the environment. Although it receives less attention than carbon dioxide (CO2), it is the second most important GHG in terms of its ability to trap heat in the atmosphere. Few studies have analyzed the determinants of CH4 emissions, especially those from the energy sector. Therefore, this study provides relevant information on the impact of GDP, primary and renewable energy consumption, human development index and trade openness on methane emissions in OECD countries. Using advanced cointegration approaches, we find that GDP and primary energy consumption increase CH4 emissions, while renewable energy consumption and human development mitigate their growth. However, the impact of these variables varied over time. No significant effect of trade openness on methane emissions was found. We recommend specific policies for OECD countries to reduce methane emissions, especially for the most polluting countries. Governments should promote renewable energy sources (solar, wind, hydro) to reduce reliance on fossil fuels, thereby minimizing methane leakage during extraction and transport. In addition, investing in human development can promote sustainable behaviors and further reduce emissions, addressing both environmental and social concerns.

The discourse surrounding artificial intelligence (AI) and its repercussions on skilled employment merits careful consideration. While AI technologies have the potential to result in job displacement within specific sectors, they concurrently usher in new employment opportunities, especially for individuals possessing advanced skills. The primary objective of this paper is to thoroughly evaluate the impact of AI on skilled employment within the South African economy. To achieve this objective, the study employs the Autoregressive Distributed Lag (ARDL) model and Granger causality analysis, spanning from 2012Q1 to 2021Q4. The results derived from the ARDL estimation reveal a substantial and positive contribution of artificial intelligence to skilled employment in South Africa, a trend observed in both the long and short run. However, two structural breaks were identified in the data, hence a re-estimation of the ARDL model. The re-estimated ARDL model revealed a negative and significant relationship between AI and skilled employment. In light of these findings, this study advocates implementing regulations and labor market policies that promote the responsible deployment of AI technology while safeguarding workers’ rights and job security. This could include establishing guidelines for AI deployment in the workplace, ensuring transparency and accountability in AI systems, and implementing social safety nets to support workers during job transitions.

This paper examines the dynamic relationship between education, governance and economic growth in 28 sub-Saharan African (SSA) countries from 2002 to 2018 using the generalized method of moments (GMM) approach. The study first examines the effect of education on economic growth and, thereafter, examines the modulating effect of governance quality on the nexus between education and economic growth. Two proxies of education, namely primary and secondary education, and five proxies of governance quality, namely a) corruption control, b) government effectiveness, c) regulations, d) rule of law, and e) voice and accountability, have been used to examine this linkage. Overall, the study found that the impact of education on economic growth is largely insignificant in all the specifications, with the exception of secondary education, which has an unconditional positive effect on economic growth in one of the five specifications of governance quality (i.e., regulatory quality). The study also found that, although governance quality spurs economic growth in seven of the ten specifications, it interacts with education to foster growth in only one specification (i.e., regulatory quality in the case of secondary education). When primary education specifications are considered, governance does not interact with education to spur economic growth in any of the specifications. These findings, though contrary to some of the previous studies, are not surprising given the primary and secondary education landscape in some SSA countries. According to UNESCO, SSA has the highest rates of education exclusion in the world.

Rationale

The COVID-19 pandemic along with its devastating impact on human lives has disrupted the socioeconomic situation worldwide. Rwanda has adopted lockdowns and other measures to prevent the spread of the COVID-19 pandemic. Recent studies documented the macro-level socio-economic pandemic impact but the impact on a household’s daily life has been scarcely documented especially in low-and-middle-income countries.

Objective

This work describes the interplay between multiple factors to assess the socio-economic impact of COVID-19 on the Rwandan population at the micro-level (household).

Methods

Data from a country-wide community survey conducted in Rwanda between December 2021 and March 2022 were used. A total of 26,412 response forms were received from around 4400 participants surveyed in 6 recurrent bi-weekly phases where participants were randomly selected. The Multivariable Logistic regression model was fitted to data with a backward stepwise elimination algorithm to assess the socioeconomic impact of COVID-19 on households’ income. Factors considered in this study are gender, age group, residence, level of education, occupation, change in employment status, socioeconomic status, and marital status.

Results

The multivariable logistic regression model provided the factors associated with the decline in income due to COVID-19. The results show that people living without a partner are more likely to experience income decline due to COVID-19 than people living with their partner. It is seen that the higher the number of children in a household, the higher the risk of experiencing a decrease in income. Taking into consideration the education level and comparing people with post-secondary and university level vis-a-vis people who did not attend school, the latter are 27 times more likely to experience a decrease in their income, those who attended primary school are 5 times more likely to experience a decrease in income, and those who attended secondary school are almost 2 times more likely to experience a decrease in income.

Conclusions

The findings from this research will be used by policymakers and other stakeholders to design and implement preventive and responsive measures for future pandemics that should be multifactorial and tailored to transversal parameters like gender and residence.