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The purpose of this study is to quantify port efficiency assessment indicators to analyze the impact of COVID-19 on Chinese One Belt One Road (OBOR) ports.

This study utilized a grey prediction model GM(1,1) to forecast five relevant indicators for each of the 17 OBOR ports both with and without COVID-19 background conditions. Additionally, the data envelopment analysis (DEA) efficiency assessment approach was used to analyze the impact of COVID-19 on port efficiency.

The results indicate that cargo and container throughput growth rates during the COVID-19 pandemic are reduced by 1.7 and 2.1%, respectively. There was also a noticeable reduction in technological efficiency (TE) as well as pure technological efficiency (PTE), while scale efficiency (SE) remained largely unaffected. Furthermore, the dynamic efficiency MI was mainly negatively impacted by changes in overall efficiency change (EFFCH), where pure efficiency change (PECH) less than one contributed significantly towards overall regression of port efficiencies during this period.

This paper is unique in its use of a combination of the grey prediction model and DEA efficiency assessment to quantify changes in important indicators during pandemic periods. This approach not only provides a quantitative understanding of the impact on port-level efficiency through numerical quantification but also offers readers an intuitive understanding.

This chapter aims to explore the novelty and utility of political economy discourse, termed “neo-statism,” as an analytical lens for comparative research in higher education. Analysis is framed within the context of Hong Kong’s transition from a British colony to a Special Administrative Region under China’s sovereignty, and its shifting academic paradigms from a more or less spontaneous philosophy rooted in liberal capitalist economy to embracing neo-statism, which involves market-conforming and state-sponsored approaches to economic and social restructuring whereby the state regulates higher education in support of national integration and global power projection. The statist regulation depends heavily on its deployment of discursive legitimacy, strategic distribution of resources, organizational synergy, and elite cohesion articulated through higher education policy, research projects, and cross-border academic exchange and cooperation. The Hong Kong case suggests that comparative research in higher education should advance from the methodological aspects of the comparative approach to exploring wider theoretical spectrum, for understanding emerging politico-economic factors shaping academic paradigm in comparative contexts. Moreover, scholars who engage in the trendy internationalization in higher education should move beyond the logics of neo-liberalism, and pay closer attention to the new geopolitical realities that are changing the normative and interactive dimensions of international higher education at large.

Mega-infrastructure development plans pave the way for policies to upgrade the infrastructure, environmental management and different aspects of locals’ well-being. These developmental dynamics can positively affect rural tourism including heritage sites destinations. The quality of life of local people can be linked to this positive developmental change through long-term and sustainable economic revitalization projects. In terms of this process, developing large-scale infrastructure and incorporating tourism sustainability can improve the quality of life-related to different dimensions that are critical to the community's well-being. Therefore, researchers have attempted to address this issue.

Data were collected between September and October 2020. The study sample size was the residents of Zhabagly village, including Zhabagaly, Abaiyl and 115 Railway settlements. Moreover, the residents were older than 18 years. A systematic random sampling technique was utilised to reach the targeted sample size and the researchers received 243 responses from the locals. Structural equation modelling (SEM) was used for analysis.

The findings from the structural equation modelling suggest that sustainable tourism increases due to the positive effect of mega-infrastructure development and positively impacts the locals' quality of life. Notably, no direct effect of mega-infrastructure development on quality of life reveals the pivotal role of sustainable tourism. Therefore, during the COVID-19 period, the dimensions of sustainable tourism – economic, market, socio-cultural and environmental – played a role in securing the positive impact of mega-infrastructure development on the locals’ quality of life.

This research highlighted the fact that when infrastructure projects are implemented to their full potential, they will generate sustainable tourism activities, provide eco-adventure activities, relax, treat signatories and boost the economy of all stakeholders. The study used AMOS to test the hypotheses. Qualitative research methods, including interviews with citizens, government officials and tourism managers, require further study.

The infrastructural development on a mega-scale means building an upscaling tourism ecosystem. This ecosystem is marked by the availability of drinking water, waste and energy management facilities that support the elevation of living material, community, health, safety and emotional well-being. It reflects the policy-level implications for future Belt and Road initiatives (BRIs). The tourism industry's resilience during COVID-19 has practical lessons for other industries.

Large-scale infrastructure construction must create favourable conditions for the rapid development of tourism. The availability of clean water, waste and energy management facilities contributes to the food production, social cohesion, physical and mental health and general well-being of the ecosystem. This is one of the few studies that used sustainable tourism as a mediator between the impact of large infrastructure projects and their impact on the quality of life of locals during the COVID-19 pandemic. Aksu-Zhabagly, a World Heritage Site in Kazakhstan, was the site of this field study.

This study aims to examine connections between five variables, including innovation in environment-related technology (EI), trade openness (TRADE), CO₂ emissions (CO₂) and foreign direct investment (FDI) from 1994 to 2019.

This study used an extended joint connectedness technique and the time-varying parameter vector autoregression (TVP-VAR) method. The analysis focuses on the variables of innovation in environment-related technology (EI), trade openness (TRADE), CO₂ emissions (CO₂) and foreign direct investment (FDI) using data from 1994 to 2019.

The results demonstrate that innovation in environment-related technology and an openness to the global network captured by FDI are identified as crucial net transmitters of shocks. In addition, an openness to the global trade network captured by TRADE turns from a transmitter to a receiver of shocks and vice versa. Moreover, it can be seen that the impact of EI was significant in the first five years of the observed period, and it transmitted the largest shock in 1997.

With regard to policy implications, the findings offer valuable insights for investors and policymakers. As the tradeoff between business efficiency and environmental sustainability diminishes, it is essential for Vietnam’s economy and enterprises to embrace green and sustainable growth in line with global trends. In a world characterized by uncertainties and risks, enterprises need to develop strategies to manage risks and shocks arising from geopolitical tensions, input material supply, financial–monetary instability and natural disasters.

This study contributes to the existing literature in two significant ways. First, as previously emphasized, this paper represents the first attempt to investigate the relationship between economic globalization and environmental innovation. Second, this study proposes a novel methodology that is better suited for analyzing volatility interlinkages across different market types.

This study aims to analyse the efficiency effects of institutional distance on Chinese outward foreign direct investment (FDI) in Africa.

The study utilised the true fixed-effect stochastic frontier analysis (SFA) model. Data from 2003 to 2016 (14 years) were acquired from 42 targeted African countries, which are included in the analysis.

The results reveal that FDI flow efficiency can be maximised with a high institutional distance between China and African countries. Contrariwise, comparable institutional distance, measured by the rule of law, regulatory quality and government effectiveness between the host and home countries, reflected a significant positive impact for Chinese outward foreign direct investment (OFDIs), indicating Chinese MNEs can invest directly in a country with comparable institutional characteristics.

There have been limited exceptional studies that assessed the effect of institutional distance between emerging countries. However, none of these studies investigated the effect of institutional distance between China and Africa at a national level. Using the advantage of the SFA model, this study assesses the efficiency effects of institutional distance between the host and home country.

The China’s Belt and Road Initiative (BRI, hereafter) has reenergized the Silk Road concept, with most literature focusing on the political and economic effects of the BRI. While certain aspects of the Digital Silk Road (DSR), digital component of BRI, have been researched, much less focus has been placed on the technological development, tech transfer and information diffusion aspects of the BRI. The aim of this study is to investigate the opportunities, issues and critiques that have arisen as a result of the Belt and Road Initiative’s implications on innovation, knowledge transfer and dissemination.

Research in its nature is descriptive. Literature reviews are a significant part of the development of a field. Therefore, secondary sources were considered.

The literature and the study have highlighted several opportunities, problems and criticism that decision-makers and the relevant agencies and institutions should take into account when deciding how to move forward with BRI and its digital component DSR.

This paper contributes to the research literature on BRI and its subset DSR’s impacts on innovation, knowledge transfer and information diffusion. In fact, the DSR’s primary aim is to strengthen international cooperation in the digital economy. Furthermore, digital platforms now play a significant role in global trade, emphasizing the necessity of DSR.

The purpose of this article is to examine Cairo's master plans during the past 70 years, including the establishment of the New Administrative Capital City—which is based on two fundamental courses on the phenomenon of urbanisation—and other initiatives to address Cairo's Plans based on the thoughts of three planning schools—Chicago, Los Angeles and Liverpool. The aim is to determine if the right time to relocate Egypt's capital to a different place makes sense.

Cairo has experienced significant urban challenges throughout its millennial history due to the continually shifting socioeconomic and political changes. This research uses prospective and retrospective methods to examine how planning theories have historically influenced building Cairo’s urban fabric and provides insight into the city’s master plans from the July Revolution of 1952.

It is assumed that Cairo's socio-spatial transitions over time were caused by scattered expansion, leading to contemporary Cairo's socio-spatial evolution. The paper ends with some questions about the future of the city. Should planning policies change to cope with socioeconomic, spatial and political transitions?

The article's significance stems from the necessity of adaptable and considerate ideas that move Cairo's communities towards a better setting and provide a crucial route for enhancing their environments. Using digital technologies to implement new capital while creating platform urbanism may be accomplished even with constrained budgets and short course lengths.

This study aims to find the impact of the trade war between the USA and China on Asian economies. Apart from macroeconomic variables associated with trade, this study explicitly creates a trade war scenario and trade war participant dummies. Using the neural network multilayer perceptron, this study checks for the causal linkages between the predictors and target output for the panel of Asian economies and the USA.

A conceptual model of the after effects of trade war in a quadrant is developed. Variables related to trade and tariffs are included in the study for a panel of 19 Asian economies. The feedforward structure of neural network analysis is used to identify strong and weak predictors of trade war.

The hidden layers of the multilayer perceptron reveal the inconsistency in linkages for the predictors’ services exports, tariff measures, anti-dumping measures, trade war scenario dummy with gross domestic product. The findings suggest that to curtail the impact of the trade war on Asian economies, predictors with neural evidence must be paid due weightage in policy determination and trade agreements.

The study applies a novel and little explored AI/ML technique of Neural Network analysis with training of 70% observations. The paper will provide opportunity for other researchers to explore techniques of AI/ML in trade studies.

This study aims to examine the relationship between financial development (FD), financial risk, green finance and innovation related to carbon emissions in the G7 economies.

This quantitative study examines the roles that financial development [FD: Domestic credit to private sector by banks as percentage of gross domestic product (GDP)], economic growth (GDP: Constant US$ 2015), financial risk index (FRI), green finance (GFIN: Renewable energy public research development and demonstration (RD&D) budget as percentage of total RD&D budget), development of environment-related technologies (DERTI: percentage of all technologies) and human capital (HCI: index) have on the environmental quality of developed economies. Based on panel data, the study uses a novel approach method of moments quantile regression as a main method to tackle the issue of cross-sectional dependency, slope heterogeneity and nonnormality of the data.

The study confirms that increasing economic development increases emissions and negatively impacts the environment. However, efficient resource allocation, improved financial systems, and green innovation are likely to contribute to emission mitigation and the overall development of a sustainable viable economy. Furthermore, the study highlights the importance of risk management in financial systems for future emissions prevention.

The study uses a reliable estimation procedure, which extends the discussion on climate policy from a COP-27 perspective and offers practical implications for policymakers in developing more effective emission mitigation strategies.

The study offers policy suggestions for a sustainable economy, focusing on both COP-27 and the G7 countries. Recommendations include implementing carbon pricing, developing carbon capture and storage technologies, investing in renewables and energy efficiency and introducing financial instruments for emission mitigation. From a COP-27 standpoint, the G7 should prioritize transitioning to low-carbon economies and supporting developing nations in their sustainability efforts to address the pressing challenges of climate change and global warming.

In comparison to the literature, this study examines the importance of financial risk for G7 economies in promoting a sustainable environment. More specifically, in the context of FD and national income with carbon emissions, previous researchers have disregarded the importance of green innovation and human capital, so the current study fills the gap in the literature related to G7 economies by exploring the link between the identified variables related to carbon emissions.