Multidimensional study of factors influencing sustainable construction adoption in Yemen: insights for implementing sustainable practices.

Despite political volatility, Yemen's construction sector is gradually progressing to satisfy the country's housing needs. Most construction projects, however, employ traditional construction methods and have yet to be able to adopt sustainable construction, which is economically feasible, socially responsible, and environmentally beneficial. To support sustainable construction, this study analyzes various factors that might drive sustainable practices in construction projects in Yemen. These drivers are discovered from the literature and validated by experts using grey Delphi. Forty-four drivers were approved across three dimensions: economic, social, and environmental. These drivers are assessed using grey AHP. The economic factor is determined to be the most crucial in the adoption of sustainable construction. Competitiveness, improved well-being, and improved indoor environmental quality are rated as the top economic, social, and environmental dimensions, respectively. Overall, competitiveness is acknowledged as the most important driver for the implementation of sustainable practices in Yemen's construction projects. The study's findings were discussed with the experts who were involved in the evaluation. The findings were agreed upon, and it was underlined that a proactive approach from both construction project participants and public authorities can increase the competitiveness of sustainable construction. Additional policies to promote competitiveness of sustainable construction are also advocated.

Green finance, renewable energy, financial development, FDI, and CO2 nexus under the impact of higher education.

This research investigates the relationships between CO2 emissions, the economy, renewable energy consumption, green financing, and foreign direct investment in BRICS nations from 2000 to 2019 under the effect of higher education. The stationarity of the data was evaluated using three unit root tests: ADF-Fisher, Levin, Lin, and Chin and Im, Pesaran, and Shin. The panel autoregressive distributed lag approach identified the long-run and short-run elasticities. The empirical findings demonstrate that variables cointegrate. In the long run, renewable energy, economic growth, green finance, foreign direct investment, and higher education all influence CO2 emissions; however, in the short run, only economic growth, renewable energy, and higher education influence CO2 emissions. The findings also indicate that higher education increases dramatically at the individual and societal levels, reducing CO2 emissions in the short and long term. The overall empirical study of group and economy is supported by the results of robust statistics. In light of the results, the BRICS economies are advised to collaborate for sustainable growth while preserving environmental quality. Moreover, the BRICS countries should prioritize investing in the growth of higher education and enhancing the use of renewable energy for sustainable development.

Smarter and Greener Cities After COVID-19: An Integrated Decision-Making Framework to Prioritize Investment Alternatives.

Locking down cities to curb the transmission of coronavirus brought the global economy to a grinding halt. Cities are like engines of growth; when they stop, so does the growth. Therefore, it becomes paramount to build cities that continue to function and do not collapse amidst any crisis. Since economic recovery is underway, this paper examines priority areas for investment to expedite recovery and build back stronger cities. These areas are evaluated based on their contribution to revitalizing public health, economic, social, energy, and environmental sectors. For the analysis, analytical network process (ANP) and fuzzy-VIKOR are applied. ANP obtains the relative importance of sectors and their respective critical factors after solving a complex relationship among them. The economic sector has the highest weight of 25.8% among the five sectors, while job creation has the highest weight of 10.3% among the fifteen factors. Fuzzy-VIKOR is used to evaluate different areas and it is found that renewable energy has a greater contribution to the sustainable recovery of major sectors and the long-term aim of building inclusive green and resilient cities. These insights shall contribute to the conversations already ongoing among city governments, urban planners, civil society organizations, and city dwellers seeking practical solutions to unprecedented challenges posed by the pandemic.

Analysis of core risk factors and potential policy options for sustainable supply chain: an MCDM analysis of Saudi Arabia's manufacturing industry.

Sustainable supply chain management (SSCM) has been a tough challenge for developing economies like Saudi Arabia. Implementation of SSCM practices in the manufacturing industry has been prone to multiple risk factors that need to be identified, evaluated, and prioritized especially considering the dynamics of the manufacturing industry in a developing economy. Moreover, it is also imperative to trace out feasible and sustainable strategies to overcome the risks to SSCM practices adoption. This study serves this purpose and identifies, evaluates, prioritizes the risk factors, sub-factors, and strategies to overcome these risk factors in the implementation of SSCM practices in the manufacturing industry in Saudi Arabia. An integrated multi-criteria decision analysis approach by combining fuzzy AHP and fuzzy WASPAS methods is employed for the analyses. The fuzzy AHP analysis results show that economic risks are dominant risks followed by the managerial policy risks and environmental risks in implementing SSCM. Industrial emissions are the leading risk factors in the overall ranking of the sustainable supply chain sub-risk factors followed by market dynamics, management policy failures, financial constraints, and credit uncertainty. While evaluating the sustainable supply chain strategies using fuzzy WASPAS, it is concluded that commitment and support of top, middle, and lower level management is the most pivotal strategy to deal with the risks to SSCM in Saudi Arabia followed by establishing environmental policies and goals to adopt SSCM, and provision of the financial resources and subsidies.

Non-oil economic transition for economic and environmental sustainability in Saudi Arabia: a multi-factor analysis under fuzzy environment.

In this study, an analysis of Saudi Arabia's economic diversification, particularly non-oil transition, is conducted. Initially, key success factors and sub-factors that provide basis for the analysis are identified through literature survey. Three key factors (economic, labor, and market), twenty-one sub-factors (seven under each factor) are identified. To obtain the relative importance of factors and sub-factors, fuzzy analytical hierarchy process (FAHP) has been used. The economic criterion obtained the highest weight followed respectively by fiscal and labor criteria. The "proportion of Saudis in the workforce" sub-criterion received the highest weight under labor criterion, the "investment-intensive business models" sub-criterion obtained the highest weight under economic criterion, and the "increase non-oil revenue" sub-criterion got the highest weight under fiscal criterion. Overall, increase non-oil revenue sub-criterion (under fiscal criterion) received the highest weight. Later, eight major non-oil sectors are prioritized with respect to criteria and sub-criteria using fuzzy technique for order preference by similarity to the ideal solution. Petrochemicals sector ranked topped in the contribution to achieving non-oil transition. The findings of the study shall enable the government and policymakers to specifically design policies for respective sectors knowing their importance in the transition and subsequently bring a new cycle of prosperity to the Kingdom of Saudi Arabia.

Impact of stock market, renewable energy consumption and urbanization on environmental degradation: new evidence from BRICS countries.

This study examines links between Morgan and Stanley capital Investment (MSCI), foreign direct investment (FDI), renewable energy, urbanization, and trade openness on environmental degradation in (Brazil, Russia, India, China, South Africa) BRICS countries. In this study, generalized method of moment (GMM) estimation is applied on a data set ranging from 1993 to 2018. Results illustrate that stock market index price (MSCI) has negative relationship on CO2 emissions in India, China, Russia, and South Africa and has positive relationship in Brazil. One possible reason for this is strong environmental regulations and their enforcement by Brazilian government. The study also finds that trade openness, FDI, and urbanization have a significant positive relationship on environmental degradation. The impact of stock market development on environmental degradation varies among BRICS countries. Our outcomes have significant policy implications. For example, the policy makers have to initiate effective strategies to promote the renewable energy sources to meet the increasing demand for energy by replacing the use of conventional energy such as coal, gas, and oil. This will help to reduce the CO2 emissions from fossil fuel and ensure sustainable stock market development in the BRICS nations. BRICS countries who have taken the initiative and formulated policies for businesses to conserve the environment play a positive role compared to those who do not.

Dynamic interactive links among sustainable energy investment, air pollution, and sustainable development in regional China.

This research investigates the dynamic interactive associations among sustainable investment in the energy sector, air pollution, and sustainable development. To this end, it employs a "one-step" system-generalized method of moments (GMM) and "one-step" differential-GMM estimators, covering the period between 1996 and 2017. In this context, it utilizes the simultaneous equations of the dynamic panel data model for panel data of 27 Chinese provinces and municipalities. We have developed a new model of sustainable development, which incorporates sustainable investment in the energy sector and air pollution to offer a robust theoretical foundation for considering the underlying relations. The system-GMM estimator is used for the full data set; however, differential-GMM is utilized for the subsets of data, in order to tackle the small sample bias problem. The empirical outcomes provide several vital insights in that they yield mixed findings for the aggregated sample and subsets of data. For example, a two-way causal relationship occurs for all the panels, except the central part (medium development regions), between sustainable investment in the energy sector and sustainable development. Contrary to this, causality runs from air pollution to sustainable investment in the energy sector in a full data set and the central part (medium dev.). Nevertheless, the opposite is true in the case of the eastern part (most developed regions) of China. Still, the same relationship runs in either direction in the case of the western part (least developed regions). On the other way around, the feedback hypothesis of causality is confirmed, across all the samples, between air pollution and sustainable development. Hence, sustainable development and air pollution are overwhelmingly interdependent, in the country as well as the province and municipality level of the Chinese economy.

Stylized heterogeneous dynamic links among healthcare expenditures, land urbanization, and CO2 emissions across economic development levels.

This research examines the heterogeneous dynamic links among healthcare expenditures, land urbanization, and CO2 emissions across the development levels of China. To this end, data of 27 Chinese provinces are considered from 1999 to 2018. Theoretically, this research developed a healthcare expenditures-augmented Stochastic Impacts of Regression by Population, Affluence, and Technology (STIRPAT) model to incorporate healthcare expenditures as a determinant of affluence. Empirically, this research established a system of simultaneous equations based on the healthcare expenditures-augmented STIRPAT model to estimate the links among the variables. As a pre-analysis, second-generation Westerlund cointegration is applied and found the long-term equilibrium association among the variables. The long-run estimations and short-run causality are done by employing dynamic common correlated effects mean group method (DCCEMGM) and Dumitrescu-Hurlin causality. A heterogeneous long-run equilibrium linkage is confirmed to exist among the variables of interest. Concerning the long-run estimates, firstly, the healthcare expenditures growth and land urbanization exhibited a bilateral positive link. Secondly, CO2 emissions and healthcare expenditures growth manifested the existence of a bilateral positive link. And thirdly, a unilateral positive (negative) link is revealed to exist from a linear term (squared term) of land urbanization to CO2 emissions. Concerning the short-run results, firstly, a bilateral causal bond exists between the land urbanization and healthcare expenditures growth. Secondly, a bilateral causal bond prevails between CO2 emissions growth and healthcare expenditures growth. Finally, a unilateral causal bond is operational from land urbanization to CO2 emissions growth. In terms of the nature of the link, the long-run findings are consistent across the data samples. However, considering the degree of influence, heterogeneity is confirmed across the development levels for both long- and short-run. It infers that relatively more (less) developed regions showed relatively strong (weak) influence. Based on empirical findings, relevant policies are recommended.

Regional disparities in Preventive measures of COVID-19 pandemic in China. A study from international students' prior knowledge, perception and vulnerabilities.

The COVID-19 pandemic needs immediate solution before inflicting more devastation. So far, China has successfully controlled transmission of COVID-19 through implementing stringent preventive measures. In this study, we analyze the effectiveness of preventive measures taken in thirteen regions of China based on the feedback provided by 1135 international students studying in China. The study uses factor analysis combined with varimax rotation of variables. It was found that awareness raising and dispersing actionable knowledge regarding trust and adapting measures remained significantly important. Therefore, recognition of information gaps, improvements in the level of alertness, and development of preventive measures in each sector are imperative. The findings of this study revealed that trust, students' health, waste disposal, and the efforts of the Chinese government/international institute of education to prevent this pandemic were significantly and positively associated with preventive measures. The results showed that prior knowledge, global pandemics, and food and grocery purchases were firmly related to the preventive measures of COVID-19. Moreover, anxiety, transportation, and economic status were negatively related to the preventive measures. During this epidemic situation, international students suffered various types of mental stresses and anxiety, especially living in most affected regions of China. The study adopted a mixed (qualitative and quantitative) approach where the findings can act as a set of guidelines for governmental authorities in formulating, assisting in the preparation, instructing, and guiding policies to prevent and control the epidemic COVID-19 at national, local, and divisional levels.

New environmental performance index for measuring sector-wise environmental performance: a case study of major economic sectors in Pakistan.

The study develops slack-based environmental performance index (SBEPI) to conduct the environmental performance of Pakistan's major sectors of the economy, which include agriculture, manufacturing, transport, power, construction, and mining and quarrying (M&Q) sectors. The index computes environmental efficiency scores based on three critical indicators, total primary energy consumption (input indicator), gross domestic product (desirable output), and CO2 emission (undesirable output). The study undertakes analysis for a period of 10 years from 2008 to 2017. SBEPI score of 1 is set to indicate efficient performance, while score of 0 translates inefficient performance. The results of the studied period reveal that all the sectors underperform for considered indicators. For instance, the top-performing agriculture sector could only achieve an SBEPI score of 0.00008275. The analysis also does not reflect any signs of performance improvement for the studied sectors. To validate the results of this study and highlight the advantages of SBEPI, the study compared SBEPI results with conventional environmental index (EI). The comparison results reveal that SEBPI results are more realistic and the index holds higher discriminatory power than conventional EI. Based on this study's results, some policy recommendations for the government and other sectoral leaders to improve sectoral environmental performance are provided.

Evaluating renewable energy sources for implementing the hydrogen economy in Pakistan: a two-stage fuzzy MCDM approach.

Hydrogen can play a crucial role in increasing energy security and reducing greenhouse gases in Pakistan. Hydrogen can only be a clean and sustainable fuel if it is generated from renewable energy sources (RES). Thus, it is important to evaluate viability of RES for hydrogen production. This study developed a two-stage fuzzy MCDM (Multi-criteria decision-making) approach to select the most efficient RES. In the first stage, fuzzy analytical hierarchy process (AHP) obtained the relative weights of four criteria for the selection of best RES. These criteria included commercial potential, environmental impacts, economic benefits, and social acceptance. In the second stage, data envelopment analysis (DEA) measured the relative efficiency of RES using weights of criteria as outputs, and the cost of RES-based electricity generation as input. The results indicated that wind and solar are the most efficient sources of hydrogen production in Pakistan. Municipal solid waste (MSW) and biomass can also be considered a feedstock for the hydrogen economy. Geothermal reported to be the less efficient source and thus is not recommended at present. Sensitivity analysis confirmed the robustness of results obtained using the developed framework.

A sustainable solution for electricity crisis in Pakistan: opportunities, barriers, and policy implications for 100% renewable energy.

This study aims to explore the potential of renewable energy resources to attain a 100% renewable electricity system in Pakistan. Currently, most of the electricity supply comes from fossil fuel, which is imported because Pakistan lacks its own resources. The imports of fossil fuel cost a huge amount and therefore afflict the already fragile economy. Further, the policy to rely on fossil fuel has significantly failed to address the energy crisis that has been lingering for the past two decades, and an acute shortage of electricity hinders the progress of various sectors of the economy. In addition, the global climate index has listed Pakistan among the top 10 climate-vulnerable countries, which makes it pertinent for the country to take precautionary measures for climate change mitigation. Pakistan has abundant renewable energy resources, which are more than sufficient to meet 100% of the present and future electricity demands. On the basis of the existing literature and the dilemma of the energy crisis and climate vulnerability, this study argues that transition to a 100% renewable electricity system is not only an option but also an urgent requirement. Further, we list the potential barriers, in the context of Pakistan, and put forward the policy implications for a swift transition to an entirely renewable electricity system.

Assessing the solar PV power project site selection in Pakistan: based on AHP-fuzzy VIKOR approach.

Pakistan has an abundant solar power potential which can be effectively utilized for the electricity generation. There are various sites across the country which have sufficient solar irradiation across the year, and thus, suitable for the installation of solar photovoltaic (PV) power projects. This study, therefore, aims to undertake research on the establishment of solar power project site selection in Pakistan. In this context, 14 promising cities of Pakistan are considered as alternatives and studied in terms of economic, environmental, social, location, climate, and orography criteria and further supplemented with 20 sub-criteria. Initially, the analytical hierarchy process (AHP) method has been used to prioritize each of the main criteria and sub-criteria. Later, fuzzy VlseKriterijuska Optimizacija I Komoromisno Resenje (F-VIKOR) method has been employed to prioritize the 14 alternatives. The present investigation reveals that Khuzdar (C2), Badin (C3), and Mastung (C7) are the most suitable cities for the installation of solar PV power projects in Pakistan. Finally, the outcome of the sensitivity analysis revealed that obtained results are reliable and robust for the installation of solar PV power projects in Pakistan. This study shall assist government, energy planners, and policymakers in making cities sustainable by establishing solar power projects in Pakistan.