Sustainability

Water pollution is increasing with rapidly growing industries and world population, which is very harmful for marine life and humans as well. This research has been conducted to introduce novel material with advanced techniques for the effective removal of heavy metals from wastewater. Successful nanofiber membranes have been developed with hemp charcoal (HC) and polyacrylonitrile (PAN), which can remove heavy metals from water efficiently in less time. The nanofiber membranes showed good adsorption capacity for heavy metal ions along with good thermal and mechanical stability. Electrospun nanofibers of HC and PAN were assessed for adsorption capacity by soaking them in metallic suspensions of known concentration for a specific period of time. Nickle, cobalt, and copper metals were selected to assess the adsorption capacity of nanofibrous webs. It was observed that HC played a vital role in removing metal ions from wastewater with an excellent efficiency. The adsorption capacity for nickel, cobalt, and copper was 54 mg/g, 87 mg/g, and 96 mg/g, respectively. Full article

Significant savings in carbon emissions, cost, and time could be achieved via the reduction in maintenance frequency, capital costs of track construction, and land used. Geosynthetic-reinforced soils offer such sustainable solutions. The experimental work presented in this paper investigates the long-term performance of a Geosynthetic-Reinforced Soil Retaining Wall (GRS-RW) system as an alternative to the conventional railway embankment. Full-scale testing was carried out on three sleeper sections of ballasted and slab tracks by simulating train loads cyclically, phased to 360 km/h. The tracks were supported by either a low-level fully confined conventional embankment or a GRS-RW substructure. The substructures were formed of a 1.2 m deep subgrade and frost protection layer, in accordance with high-speed railway design standards. The overall aim was to assess the performance of the tracks, in terms of transient displacements and total settlements. It was observed that once the GRS-RW system reached its active state, it deformed in a very similar way to a conventional embankment despite the fact that the GRS-RW system is less confined than the conventional embankment. The results indicate that the cumulative settlement of the slab track, which is due to the plastic deformation of the soil, is significantly less than that of the ballasted track, which is primarily caused by the movement of the ballast particles. Full article

This study investigates the relationship between the behavioral intention to use e-learning and academic achievement, using self-determination theory (SDT) and critical thinking as one of the 21st century skills. This study also examines how the behavioral intention to use e-learning, which mediates the effects of 21st century skills such as logical thinking and perceived utility, promotes academic performance. The approach is based on structural equation modeling using partial least squares (PLS-SEM). A survey question on the idea of self-determination and critical thinking in the 21st century was given to 346 students at King Saud University as the main method of collecting data. The obtained outcomes of students’ perceived usefulness, critical thinking in the 21st-century skills, and behavioral intention to utilize e-learning indicate a positive effect on their academic achievement in higher education institutes, and all of the surveyed students were completely satisfied with the effect of critical thinking in the 21st-century skills on behavioral intention to use e-learning. This study indicates that self-determination theory and critical thinking in the 21st-century skills, as well as communication skills over e-learning systems, enhance the students learning activities and enable the sharing of knowledge, information, and discussions, and, hence, we recommend that students utilize e-learning systems at educational institutions throughout Saudi Arabia for the purpose of learning and that they should be encouraged to do so through lecturers at higher level education institutions. Full article

This study investigates the impact of the COVID-19 pandemic and the Ever Given ship blockage on the air quality in Suez Canal region. Nitrogen dioxide (NO₂), sulfur dioxide (SO₂), carbon monoxide (CO), and aerosol optical depth (AOD) were studied, and data were obtained from satellite instruments. The study compared monthly average data for 2020, 2021, and 2022 with a baseline period of 2017–2019 to investigate the pandemic’s effect. The study also analyzed the corresponding period of the canal blockage to identify its impact on air pollution levels. The pandemic had a significant role in decreasing NO₂ by 2.5 × 10¹⁴ molecule/cm² and SO₂ by 0.05 DU due to reduced car traffic and industrial activities. A reduction in AOD by 20% and CO concentration in the range from 3.5% to 4.7% was reported in early 2020. During the blockage, NO₂ and SO₂ levels decreased by 14.4% and 66.0%, respectively, while CO and AOD index increased by 12.68% and 51.0%, respectively. The study concludes that the containment measures during the pandemic had a positive impact on the environment, which shows how the reduction in the anthropogenic activities, especially industrial and transportation activities, have improved the air quality. Thus, stricter actions are needed to protect the environment; for example, the transition towards the using of electric vehicle is necessary, which is part of Egypt’s strategy to transition towards a green economy. The government should also adopt a policy to trade carbon emissions reduction certificates to help reduce air pollution. Full article

Small and Medium-sized Enterprises (SMEs) are key contributors to Indonesia’s economy. E-commerce can assist SMEs in gaining a competitive edge and is expected to be the largest contributor to the country’s digital economy by 2030. However, only 22% of SMEs in Indonesia have adopted E-commerce. Hence this study aims to investigate the criteria that influence E-commerce adoption by Indonesian retail SMEs and select the best strategy using the Decision-Makers, Technological, Organizational, and Environmental (DTOE) Framework and the Diffusion of Innovation (DOI) theory. This study aims to fill the research gap by examining the essential factors in E-commerce adoption by Indonesian SMEs in the retail industry and their key strategy to increase utilization. The influence and priorities between criteria were calculated using the Decision-Making Trial and Evaluation Laboratory (DEMATEL) based Analytic Network Process (ANP) method. Furthermore, an E-commerce adoption strategy was selected using Complex Proportional Assessment (COPRAS) method. This research showed critical criteria for adopting E-commerce technology in retail SMEs, Decision Maker’s IT Knowledge, Innovativeness, and Complexity. In addition, developing or training Information Technology (IT) and E-commerce skills were identified as the best strategy to increase E-commerce adoption. This study can help raise the understanding of policymakers, E-commerce service providers, and retail SME decision-makers on influencing criteria in adopting the best strategy to be applied to increase this technology adoption. Full article

Plastic is a widely used material in daily life that has brought huge social benefits to society with the advantages of low-cost manufacturing and mildness. However, due to their high resistance to degradation and diversity of chemical components, plastics pose a great threat to human health and the living environment. Aiming to address the problem that there is a lot of plastic waste and its impact on the environment, this paper puts forward an effective plan to reduce plastic waste and tests the relevant models. First, based on the pollution index data of plastic waste, it uses the Analytic Hierarchy Process and the entropy weight model to determine the evaluation index weight of plastic waste pollution impact and judge the environmental damage ability and environmental recovery ability. Secondly, in order to measure the level of environmental safety, it establishes an evaluation index system and uses the gray correlation method to determine the weight value of the evaluation index and calculate the environmental safety scores of each country. Thirdly, according to the second index system, it selects the relevant data from 10 countries, establishes a BP neural network model, and calculates the level of security and the intensity of responsibility. Finally, based on the results of the model and the global goal of achieving the minimum level of plastic waste, it offers a memorandum with a schedule and discusses the measures needed to achieve this goal and the factors to be considered. Overall, compared with the existing research, this paper presents a different approach to the assessment and measurement of the use of the environment and its capacity for pollution, combining multi-disciplinary influencing factors. Full article

Currently, there are concerns about the significant increase in the level of night-time light pollution, which has become more dramatic in recent years. This causes several environmental problems and makes it impossible to observe the starry night sky, especially in rural areas where observatories are often located. Incorrect orientation and arrangement of lighting are often responsible for this pollution. This study quantified the level of interference of lighting parameters in the night sky. The influence of other environmental factors which may interfere with observation was also evaluated. A predictive model was developed to determine the level of darkness in rural areas. It was concluded that the distance from the emission point to the observation site is critical for sky observation. A series of guidelines were proposed for designing the lighting around observatories, which could help reduce light pollution and increase the stars’ perception. The conclusions and guidelines obtained could also be applied to designing the lighting in other areas, such as protected natural areas, historical monuments, urban lighting, and computer tools used for lighting. Globally, the results obtained in this study could help to reduce the level of night-time light pollution in rural areas, leading to improvements in the environment and in the observation of the night sky. This finding is of great relevance for astronomical observatories, which are spread around the world in strategic positions for sky observation, usually in rural areas. Full article

Financial literacy is a critical life skill that is essential for achieving financial security and individual well-being, economic growth and overall sustainable development. Based on the analysis of research on financial literacy, we aim to provide a balance sheet of current research and a starting point for future research with the focus on identifying significant predictors of financial literacy, as well as variables that are affected by financial literacy. The main methods of our research are a systematic literature review, and bibliometric and bibliographical analysis. We establish a chronological path of the financial literacy topic in the scientific research. Based on the analysis of the most cited articles, we develop a comprehensive conceptual framework for mapping financial literacy. We identified a large number of predictors of financial literacy starting with education, gender, age, knowledge, etc. Financial literacy also affects variables such as retirement planning, financial inclusion, return on wealth, risk diversification, etc. We discuss in detail the main trends and topics in financial literacy research by involving financial literacy of the youth, financial literacy from the gender perspective, financial inclusion, retirement planning, digital finance and digital financial literacy. Our research can help policymakers in their pursuit of improving the levels of individual financial literacy by enabling individuals to make better financial decisions, avoid financial stress and achieve their financial goals. It can also help governments in their efforts in achieving sustainable development goals (SDGs). Full article

There is a very short list of theoretical and empirical studies on the role of management accounting tools in the sustainability of smart cities. While the majority of these studies have addressed this role from the perspective of openness, participation, and hybridisation, others have addressed it in terms of economic, social, and environmental sustainability. Despite their early efforts often focusing on institutionalisation and governmentality processes, their analyses did not address how management accounting tools can be used to achieve sustainable goals, particularly in developing countries with a political and cultural character. This study aims to explore how an activity-based costing/ABC system is configured within urban development organisations to internalise cultural and political sustainability values at the smart city level. It applies a politico-cultural model and uses a case study approach from an Egyptian state-owned smart city enterprise. The findings reveal smart city culture and political/government compliance in the implementation of the ABC system, enabled by enterprise resource planning/ERP technology, within state-owned enterprises/SOEs. This system, seen as an emerging field, was created as a multi-lens reporting system on their political and cultural sustainability in smart cities. While political sustainability refers to SOEs’ compliance with the ABC system, cultural sustainability refers to the embodiment of national smart city values in their system implementation. This sustainability costing system of a political and cultural nature has also created recursive dynamics, exemplified by the powerful role of ERP-ABC reports in making participatory sustainability decisions at various organisational and governmental levels for smart cities. Full article

The variation of droplet parameters during the spray breakup process affects the droplet deposition behavior and accurate application. The aim of this study was to experimentally investigate droplet behaviors along the penetration direction with respect to spray propagation. Particle image analysis (PIA) was applied to obtain the characteristics of droplets at three representative stages (namely, initial, quasi-steady, and end stages) after the start of injection (ASOI). The effects of timing and location on the spray characteristics were thoroughly investigated. First, different morphological changes of spray (droplets, ligaments, and bags) during spray breakup were observed. The experimental results show that droplet size and velocity distinctly increase from upstream to downstream at the initial stage. However, at the quasi-steady and end stages, droplet velocities are similar, and the effects of location are not evident. This indicates that location has a significant effect on droplet behaviors at the initial stage. The mean minimum distance (MD) of droplets first increases considerably and then decreases from upstream to downstream, suggesting that the droplets disperse better at midstream. Moreover, the mean MD at the initial stage exceeds that at the quasi-steady and end stages, denoting that the droplets disperse better with time. Finally, the geometric parameter of droplets and the key stage selection are important for predicting the interaction between the droplets and surfaces. Full article

As an emerging research area since generative artificial intelligence (represented by Chat Generative Pre-trained Transformer (ChatGPT)) has been accessible to the public, especially in education, appropriate AI application could bring numerous benefits to education; however, its abuse has the potential to be harmful. In this paper, we aimed to explore the potential of AI in the future of education with the analytical method of evolutionary game analysis (EGA). By studying the behavior of two agents, the school and the students, EGA can be used to identify strategies that can be used to improve the effectiveness of the education model in the context of the AI era. A stable evolutionary strategy for the school and students was devised under a variety of scenarios. Additionally, we conducted a numerical analysis to further explore the impact of several key factors on the stable strategy. The results indicated that schools should adopt positive supervision to standardize the use of AI in education, and students should be more active in becoming involved in AI technology. Based on this study, we believe that the school has the ability to provide effective suggestions and practical guidelines to help students succeed academically and embrace future trends in AI education. Full article

Accurate carbon price index prediction can delve deeply into the internal law of carbon price changes, provide helpful information to managers and decision makers, as well as improve the carbon market system. Nevertheless, existing methods for combination forecasting typically arbitrarily choose a certain set of single forecasting models. However, a particular selection of forecasting models do not apply to all data sets due to the nonlinearity and nonsmoothness of the carbon trading price series. Therefore, choosing suitable single forecasting models for the combination is crucial. Considering the limitations of the current study, this study constructs a combined carbon trading forecasting model based on Lasso regression and optimal integration. By invoking the Lasso regression model, we can select suitable single forecasting models for combination forecasting based on the variation patterns of different training sets. Meanwhile, ARIMA, NARNN, LSTM, and 11 other single forecasting models are screened in this study, including both traditional statistical forecasting models and artificial intelligence forecasting models. First, the carbon price index is predicted using 11 single prediction models. Furthermore, given the multi-collinearity of the single prediction series, this study employs Lasso regression to reduce the dimensions of the single prediction models, which are then used to construct an optimal combination prediction model. Finally, the proposed model is applied to SZA-2017 and SZA-2019 carbon price data in Shenzhen. The results demonstrate that the model developed in this study outperforms other benchmark prediction models in terms of prediction error and direction accuracy, showing the efficacy of the proposed method. Full article

The advent of the Fourth Industrial Revolution and the spread of infectious diseases have increased people’s reliance on information and communication technology (ICT). However, older adults are the most marginalized group affected by ICT, and their activities and daily life have become more difficult than ever during the pandemic. Based on the theory of the TAM, this study analyzed the effect of ICT use on life satisfaction among older adults during the pandemic, and examined the mediating role of social capital. The partial least squares structural equation modeling (PLS-SEM) was applied to test the relationships among ICT use, social capital, and life satisfaction, and the Sobel test was used to test the mediating effect and statistical significance of social capital. The results of the analysis confirmed the positive effects of technology’s perceived usefulness and self-efficacy on attitudes and ICT use among older adults. ICT use had a positive effect on life satisfaction. In addition, it was found that social capital had a mediating effect on the relationship between ICT use and life satisfaction. During the pandemic, ICT use not only had a direct effect on life satisfaction but also had an indirect effect through social capital among older adults. The results of this study have implications for research on ICT use and life satisfaction among older adults, and have implications for formulating public policies for active aging. The results of this study can facilitate a comprehensive understanding of the antecedents and consequential factors of the use of digital information among older adults, which not only complements previous studies but also provides a theoretical basis for systematic research on digital literacy and well-being in older adults. Full article

The transition of a business to a circular business model (CBM) calls for significant and ongoing shifts in different business management models and strategies. However, there is a lack of research focused on the technological, financial, societal, and institutional influences on the CBM transition in small and/or medium-sized enterprises (SMEs). To address this gap, our study develops a theoretical framework for the transition towards CBM. We conducted a systematic literature review with the objective of determining the relationships among technological, financial, societal, and institutional influences for CBMs. Following this, we then established a conceptual framework that comprises these four key influences for a transition plan in the context of an innovative business model with a focus on the value proposition, value creation, and value delivery. An illustrative case example of the manufacturing industry for the transition plan to CBM was presented as well. The proposed framework is designed to lead the shift towards circular economy-oriented business models that aim to promote sustainability in business. In addition, we uncovered several potential avenues for further investigation. We expect the framework towards both contribute to the expansion of the existing body of research in the field and provide business practitioners with guidelines on the CBMs’ transition for SMEs. Full article

In many regions of the world, water consumption exceeds the limits of sustainable water use. A commonly used method to examine the relationship between global water consumption and production is input–output analysis. However, between approximately 70% and 90% of freshwater consumption occurs in agricultural primary production, which is often represented by only a small percentage of the total number of sectors in input–output databases. As a result, water-related assessments based on input–output analysis are limited in their accuracy and substance. In addition, the assessment of the impact of water consumption is usually carried out at the national level, which can further contribute to the imprecision of the results. Therefore, the primary objective of this work was to develop an approach to better assess water use and its impacts in input–output analysis. In order to achieve this objective, a novel approach was adopted by integrating a global spatial model of agricultural primary production (MapSPAM) into an existing input–output database via prorating. In addition, the utilisation of MapSPAM allowed the calculation of water environmental extensions with unprecedented accuracy. The resulting Input–Output Global Hybrid Analysis of Agricultural Primary Production (IO-GHAAPP) approach includes (1) a novel input–output database and (2) novel environmental extensions for freshwater consumption and scarcity. The IO-GHAAPP database consists of 150 categories and 164 regions, resulting in a total of 24,600 region–category combinations. Forty-two of the categories are dedicated to agricultural primary production (28%). In comparison, the source input–output data consist of 120 categories and 164 regions, resulting in a total of 19,680 region–category combinations, of which 14 are dedicated to agricultural primary production (12%). The Python code and IO-GHAAPP database are openly available via Zenodo. The IO-GHAAPP approach is presented in a comparative analysis of agricultural primary production, along with the associated water consumption and water footprint, at both the global level and for the United States and India. Both countries are among the most important in the world in terms of agricultural primary production as well as associated water consumption and water scarcity. Furthermore, the IO-GHAAPP approach is applied in a simple case study of Germany, which stands in contrast as one of the largest importers of agricultural primary production on a global scale. The results show that the IO-GHAAPP approach adds a valuable layer of information to the disaggregated input–output data, allowing crop-specific analyses to be carried out that would otherwise not be possible, e.g., for specific leguminous or beverage crops. The results are relevant to practitioners of input–output analysis who are concerned with the impacts of agricultural primary production and who need highly resolved data, as well as to policy-makers who rely on such studies. The demonstrated IO-GHAAPP approach could be extended to other externalities relevant to agricultural primary production, such as land use, soil degradation or pollution. Full article

The vigorous development of green finance has become a national strategy in China. Green finance is gradually becoming a key driver of high-quality economic development and a key area of concern for China’s economy and ecological environment. Based on the panel data of 30 Chinese provinces from 2001 to 2019, we analyzed the impact and mechanism of vertical fiscal imbalance (VFI) and green finance (GF) on high-quality economic development (HQD) and then used the fixed-effect model and spatial Durbin model for empirical testing. We found that GF can significantly contribute to HQD, but VFI has a negative moderating effect in contrast to the positive effect of GF on HQD. This negative moderating effect is strongest in the central region. According to the analysis of the spatial econometric model based on geography, economy, and the nested spatial weight matrix, we found that the local GF has a negative spatial transmission effect on the HQD of other regions. Therefore, it is recommended that the coordinated development of green finance among regions be promoted, while affairs and expenditure responsibilities be reasonably distributed between the central and local governments to drive HQD effectively. Full article

To meet the growing demand for sustainable education, many universities have begun to integrate sustainability into their curricula. Additionally, universities are increasingly investing in digital technologies that enable them to deliver educational content in a more sustainable manner. The research results showed that students’ interactions with teachers in a hybrid environment, such as in a STEM university, can have a significant impact on student performance. The research results indicated a positive relationship between the educational environment and the well-being perceived by the students. The results showed that when the educational environment was improved, the students felt a greater sense of well-being. Furthermore, the results showed that students who felt a greater sense of well-being also perceived the educational environment to be more positive, and an improved educational environment can lead to an increased sense of well-being for students. This could be achieved by creating a more supportive and motivating educational environment, which could, in turn, lead to improved academic performance and mental health. The research found that there was a negative correlation between the students’ perceived assessment and evaluation related to their well-being. This suggests that students who felt that their assessment and evaluation were unfair or inappropriate were more likely to have poorer well-being than those who perceived their assessment and evaluation as fair and appropriate. Full article

The use of FACTS devices in power systems has become increasingly popular in recent years, as they offer a number of benefits, including improved voltage profile, reduced power losses, and increased system reliability and safety. However, determining the optimal type, location, and size of FACTS devices can be a challenging optimization problem, as it involves mixed integer, nonlinear, and nonconvex constraints. To address this issue, researchers have applied various optimization techniques to determine the optimal configuration of FACTS devices in power systems. The paper provides an in-depth and comprehensive review of the various optimization techniques that have been used in published works in this field. The review classifies the optimization techniques into four main groups: classical optimization techniques, metaheuristic methods, analytic methods, and mixed or hybrid methods. Classical optimization techniques are conventional optimization approaches that are widely used in optimization problems. Metaheuristic methods are stochastic search algorithms that can be effective for nonconvex constraints. Analytic methods involve sensitivity analysis and gradient-based optimization techniques. Mixed or hybrid methods combine different optimization techniques to improve the solution quality. The paper also provides a performance comparison of these different optimization techniques, which can be useful in selecting an appropriate method for a specific problem. Finally, the paper offers some advice for future research in this field, such as developing new optimization techniques that can handle the complexity of the optimization problem and incorporating uncertainties into the optimization model. Overall, the paper provides a valuable resource for researchers and practitioners in the field of power systems optimization, as it summarizes the various optimization techniques that have been used to solve the FACTS optimization problem and provides insights into their performance and applicability. Full article

The existing research on critical peak price (CPP) decision-making ignores the difference in risk appetite between industries within the consumer population, resulting in a serious lag in the enthusiasm of some users to respond to CPP, and unsatisfactory improvement of power systems and carbon emission reduction on the supply and demand side. Firstly, the problem of consumer risk appetite was comprehensively analyzed, and the industrial consumer population was secondarily stratified according to the influencing factors and the enthusiasm of responding to CPP, namely: stubborn, active and conformist, and quantitatively verified by cluster analysis. Secondly, by combing the relevant paths of CPP decision-making, the critical-peak window determination model and CPP multi-objective optimization model were constructed, and the calculation of relevant indicators was introduced. Finally, taking 10 industrial enterprises in a city in Sichuan Province as an example, the clustering method was used to verify the stratification results, and the index analysis method was used to measure the load and carbon emission improvement of two typical enterprises after CPP optimization. The results showed that the stubborn users insist on using electricity, the improvement effect of load and carbon emission reduction was poor, and additional production costs will be caused. The conformist and active users had high sensitivity to electricity price fluctuations, good load and carbon emission reduction improvement effects, and significantly reduced electricity costs. Full article