Digitalization to achieve sustainable development goals: Steps towards a Smart Green Planet

Developing environmental sustainability policy - How financing and subsidies are influencing green innovation in mineral extraction industries in China

Mineral extraction is regarded as a pollution-intensive industry and is confronted with multiple environmental sustainability challenges. This issue poses an existential crisis for mineral extraction due to continued global pressure to adopt more sustainable practices in their functioning. Despite its importance, there is a notable gap in the literature regarding how these companies encounter financial challenges, particularly in the context of high-risk, long development cycles, and the unique double externalities associated with green innovation. This research, leveraging panel data from 2016 to 2023, aims to fill this gap by examining whether Chinese mineral extraction companies demonstrate distinct preferences for specific financing sources and by evaluating the role of government in facilitating their green innovation activities. Our findings indicate that such companies utilize a mix of internal and external financing to support their green innovation projects. It is observed that the influence of external finances channels, namely government subsidies, equity financing and debt financing, on green innovation progressively weakens, a conclusion supported by multiple robustness checks. Furthermore, the study highlights the crucial role of government subsidies in motivating publicly listed companies to enhance their green innovation activities through debt and equity financing, thereby contributing to a more equitable and sustainable development paradigm in the Global South.

Optimizing agricultural data security: harnessing IoT and AI with Latency Aware Accuracy Index (LAAI)

The integration of Internet of Things (IoT) and artificial intelligence (AI) technologies into modern agriculture has profound implications on data collection, management, and decision-making processes. However, ensuring the security of agricultural data has consistently posed a significant challenge. This study presents a novel evaluation metric titled Latency Aware Accuracy Index (LAAI) for the purpose of optimizing data security in the agricultural sector. The LAAI uses the combined capacities of the IoT and AI in addition to the latency aspect. The use of IoT tools for data collection and AI algorithms for analysis makes farming operation more productive. The LAAI metric is a more holistic way to determine data accuracy while considering latency limitations. This ensures that farmers and other end-users are fed trustworthy information in a timely manner. This unified measure not only makes the data more secure but gives farmers the information that helps them to make smart decisions and, thus, drives healthier farming and food security.

Exploring the intersection of digitalization and sustainability in oil palm production: challenges, opportunities, and future research agenda

The increasing global demand for palm oil and its derivatives has led to significant environmental and social concerns, prompting the need for sustainable practices in oil palm production. In recent years, digital technologies have emerged as a potential solution to enhance sustainability in this sector. The objective of this review was to provide insights into the potential benefits and limitations of digital technologies in promoting sustainable practices in the oil palm industry, and to identify key challenges that must be addressed to ensure that digitalization contributes to sustainable development in this sector. To obtain valuable insights on this topic, this review employed a thorough analysis and exploration of relevant literature. Our findings highlight the transformative potential of digital technologies such as precision agriculture, data analytics, blockchain, and robotics to optimize resource utilization, improving efficiency, promoting social welfare, improving supply chain transparency, mitigating environmental impacts, and enhancing sustainability in oil palm production. However, the adoption of these technologies is hindered by several challenges, including high cost, lack of knowledge, and inadequate infrastructure. Our findings emphasize the importance of supportive policies, collaborative efforts, and targeted research to promote technology adoption and ensure equitable benefits across the oil palm industry. Recommendations are provided for industry stakeholders, policymakers, and researchers to leverage digitalization effectively and promote sustainable practices in the oil palm industry, ultimately contributing to global sustainability goals.

Comprehensive analysis of college students' autonomous fitness behavior-a narrative review

Although the physical health of college students is increasingly receiving attention, their autonomous fitness behavior has not been thoroughly investigated. This narrative review conducted a comprehensive literature search through databases such as PubMed, PsycINFO, Web of Science, and the China National Knowledge Infrastructure (CNKI), reviewing studies published up to December 2023. We explored the constructs of autonomy, fitness behavior, and agency, and discussed their integration within the autonomous fitness model. Our findings indicate a lack of comprehensive studies exploring the multifaceted factors influencing autonomous fitness behaviors. Future research should strive to deepen conceptual understanding and further explore the complex dynamics of the transition from autonomy to persistence, employing technological and interdisciplinary methodological perspectives to enhance understanding and promote sustainable fitness habits.

Artificial intelligence and sustainable development during the pandemic: An overview of the scientific debates

The current work aims to analyze the main themes related to artificial intelligence (AI) and sustainable development during the pandemic period. This study provides an overview of the specialized literature related to AI and sustainability from the beginning of the pandemic through 2023. The present paper analyses scientific literature emphasizing both artificial intelligence's positive and negative impacts on sustainable development objectives (SDGs). To conduct the research, we employed bibliometric analysis and text-mining techniques to identify the major themes in the literature indexed in the Web of Science and Scopus databases. Firstly, we used descriptive measures to identify the authors' impact, the article production by country, the main keywords used, and other descriptive data. We further used data reduction methods based on co-word analysis (such as multiple correspondence analysis) on authors' keywords to show patterns in the themes explored in the literature. Bibliometric analysis was supplemented by text mining using Latent Dirichlet allocation (LDA) and structural topic modeling on abstracts to provide a comprehensive view of scientific debates on AI and sustainable development. Our research has identified various themes in the literature related to AI and sustainable development. These themes include social sustainability, health-related issues, AI technologies for energy efficiency, sustainability in industry and innovation, IoT technologies for smart and sustainable cities, urban planning, technologies for education and knowledge production, and the impact of technologies on SDGs. We also found that there is a significant positivity bias in the literature when discussing the impact of AI on sustainable development. Despite acknowledging certain risks, the literature tends to focus on the potential benefits of AI across various sectors. In addition, the analysis shows a growing emphasis on energy efficiency, which is facilitated by the use of AI technologies. Our study contributes to a better understanding of current scholarly discussion trends and emerging scientific avenues regarding AI and sustainable development. It also highlights the areas where research is needed and the implications for practitioners and policymakers.

A Longitudinal Analysis of the Impact of Digital Technologies on Sustainable Food Production and Consumption in the European Union

In today's landscape, digital technologies hold immense potential in tackling challenges associated with food sustainability. This study aims to contextualize a broader investigation of food sustainability and digitalization within the agricultural sector. Its objective is to explore the influence of digital technologies on sustainable food production and consumption, particularly examining relationships among digital technologies, municipal waste, agricultural output, nitrogen emissions, methane emissions from agriculture, and Goal 12 Responsible Consumption and Production (SDG12). Through the use of Structural Equation Modeling, the empirical investigation scrutinizes the relationships between digital technology use and critical variables linked to food sustainability in a longitudinal analysis. The results highlight the significant impact of extensive digital technology use on municipal waste, sustainable production, and consumption, indirectly influencing greenhouse gas (GHG) emissions. Empirical research findings reveal a negative influence of digital technologies on responsible consumption and production (path coefficient -0.349, p values < 0.001), suggesting an impact of digital technologies on diminishing sustainability in consumption and production. The relationship between digital technologies and municipal solid waste is also negative (path coefficient -0.360, p values < 0.001), suggesting that the use of digital technologies can contribute to reducing the amount of municipal solid waste. Digitalization has the potential to improve the sustainability of supply chains by reducing resource consumption and greenhouse gas emissions associated with production and distribution operations.

Unveiling Digital Transformation: A Catalyst for Enhancing Food Security and Achieving Sustainable Development Goals at the European Union Level

The digital revolution is reshaping various aspects of society, including having a profound impact on food security and the advancement of Sustainable Development Goals (SDGs). This study investigates the relationship between digital transformation, quantified through the components of the Digital Economy and Society Index (DESI), and SDGs related to food (SDG1, SDG2, SDG3, and SDG10), along with the overall SDG Index score. The data used for investigation are sourced from reports issued by the European Commission concerning DESI, as well as the SDG reports for the period from 2017 to 2022. The paper elucidates how different components of digitalization, such as connectivity, digital skills, internet usage, and digital public services, influence the attainment of food security objectives and broader sustainable development targets using structural equation modeling and cluster analysis. The findings underscore the pivotal role of digital technologies in enhancing poverty alleviation, health and well-being, and, in particular, mitigating inequality. This study contributes to understanding the complex relationship between digital transformation and food security, offering insights for policymakers, practitioners, and stakeholders aiming to leverage technology for advancing SDGs and fostering a more equitable and sustainable future.

Expectation management in AI: A framework for understanding stakeholder trust and acceptance of artificial intelligence systems

As artificial intelligence systems gain traction, their trustworthiness becomes paramount to harness their benefits and mitigate risks. This study underscores the pressing need for an expectation management framework to align stakeholder anticipations before any system-related activities, such as data collection, modeling, or implementation. To this end, we introduce a comprehensive framework tailored to capture end-user expectations specifically for trustworthy artificial intelligence systems. To ensure its relevance and robustness, we validated the framework via semi-structured interviews, encompassing questions rooted in the framework's constructs and principles. These interviews engaged fourteen diverse end users across the healthcare and education sectors, including physicians, teachers, and students. Through a meticulous qualitative analysis of the interview transcripts, we unearthed pivotal themes and discerned varying perspectives among the interviewee groups. Ultimately, our framework stands as a pivotal tool, paving the way for in-depth discussions about user expectations, illuminating the significance of various system attributes, and spotlighting potential challenges that might jeopardize the system's efficacy.

Digitalization and SMEs development in the context of sustainable development: A China perspective

Worldwide economies are determined to achieve sustainable development. In this pursuit, the role of SMEs and ICT has emerged as an inevitable choice for sustainable development. The literature on the impact of SMEs and ICT on sustainable development, particularly in China's context, is scarce. Therefore, the analysis aims to investigate the impact of SMEs and ICT on sustainable development in China for the period of 1998-2020. We have applied the ARDL model for empirical analysis. The short and long-run estimates attached to SMEs are significant and positive, confirming that SMEs help to achieve sustainable development. Similarly, the estimates attached to ICT are positive and significant both in the short and long run, confirming the beneficial role of ICT in achieving sustainable development. The estimates attached to institutional quality and R&D control variables are positive and significant in the long run, but only R&D estimates are significant in the short run. In particular, digitalization and SMEs development provide a win-win situation for China to mitigate climate change in the long run and become more environmentally sustainable.

Real-time water quality prediction in water distribution networks using graph neural networks with sparse monitoring data

Ensuring the safety and reliability of drinking water supply requires accurate prediction of water quality in water distribution networks (WDNs). However, existing hydraulic model-based approaches for system state prediction face challenges in model calibration with limited sensor data and intensive computing requirements, while current machine learning models are lack of capacity to predict the system states at sites that are not monitored or included in model training. To address these gaps, this study proposes a novel gated graph neural network (GGNN) model for real-time water quality prediction in WDNs. The GGNN model integrates hydraulic flow directions and water quality data to represent the topology and system dynamics, and employs a masking operation for training to enhance prediction accuracy. Evaluation results from a real-world WDN demonstrate that the GGNN model is capable to achieve accurate water quality prediction across the entire WDN. Despite being trained with water quality data from a limited number of sensor sites, the model can achieve high predictive accuracies (Mean Absolute Error = 0.07 mg L-1 and Mean Absolute Percentage Error = 10.0 %) across the entire network including those unmonitored sites. Furthermore, water quality-based sensor placement significantly improves predictive accuracy, emphasizing the importance of careful sensor location selection. This research advances water quality prediction in WDNs by offering a practical and effective machine learning solution to address challenges related to limited sensor data and network complexity. This study provides a first step towards developing machine learning models to replace hydraulic models in WDN modelling.

Regulation of microclimate and shading effects of microalgal photobioreactors on rooftops: Microalgae as a promising emergent for green roof technology

Urban areas remarkably affect global public health due to their emissions of greenhouse gases and poor air quality. Although urban areas only cover 2% of the Earth's surface, they are responsible for 80% of greenhouse gas emissions. Dense buildings limit vegetation, leading to increased air pollution and disruption of the local and regional carbon cycle. The substitution of urban gray roofs with microalgal green roofs has the potential to improve the carbon cycle by sequestering CO2 from the atmosphere. Microalgae can fix 15-50 times more CO2 than other types of vegetation. Advanced microalgal-based green roof technology may significantly accelerate the reduction of atmospheric CO2 in a more effective way. Microalgal green roofs also enhance air quality, oxygen production, acoustic isolation, sunlight absorption, and biomass production. This endeavor yields the advantage of simultaneously generating protein, lipids, vitamins, and a spectrum of valuable bioactive compounds, including astaxanthin, carotenoids, polysaccharides, and phycocyanin, thus contributing to a green economy. The primary focus of the current work is on analyzing the ecological advantages and CO2 bio-fixation efficiency attained through microalgal cultivation on urban rooftops. This study also briefly examines the idea of green roofs, clarifies the ecological benefits associated with them, discusses the practice of growing microalgae on rooftops, identifies the difficulties involved, and the positive aspects of this novel strategy.

Digitalization, new business Startups, information and Communication Technologies and product innovation: Evidence From China in the lens of sustainability

The global economies and international organizations are inclined towards sustainable growth, technological advancements and product innovations. China is the leading economy in information and communication technologies and among the major industrially expanded economies covering a substantial share of the global market in exports. The prime objective of this study is to explore the role of digitalization and Information and communication technologies (ICT) for product innovation (PIN). In doing so, the study also attempts to draw some novel implications regarding business, entrepreneurship, and product innovation in the lens of sustainability. This current study use the annual data of China from 1990-2020. The empirical analysis was conducted using the stationarity testing and the Johansen cointegration test. In addition, due to the data's asymmetrical distribution, the non-parametric "quantile regression" is used. For robustness, this study employs the Fully Modified Ordinary Least Square, Canonical Cointegration, and Dynamic Ordinary Least Square methods. The empirical results reveal that economic progress and financial development are substantial factors of product innovation. The robust analysis reveals that medium and high-tech industries and information and communication technology adversely affect product innovation. Further, the presence of financial development transforms the negative influence of information and communication technology into a positive. The current study concludes more investments in the technological industry are required to encourage product innovation in China. The study discusses some policy-related implications in the context of business sustainability and product innovation.

Global Food Security and Sustainability Issues: The Road to 2030 from Nutrition and Sustainable Healthy Diets to Food Systems Change

The accomplishment of food/nutrition security for all across sustainable food systems (SFS) is tied to the Sustainable Development Goals (SDGs). SFS is connected to all SDGs via the traditional framework of social inclusion, economic development, environmental safety, inclusivity, and the development of sustainable food systems. We suggest that, for the world to achieve sustainable development, a shift to SFS is necessary to guarantee food/nutrition security for all, while operating within planetary boundaries to protect ecosystems and adapt to and mitigate climate change. Therefore, there is a requirement for original approaches that implement systemic and more participatory methods to engage with a wider range of food system stakeholders. However, the lack of skills and tools regarding novel methodologies for food system transformation is a key obstacle to the deployment of such approaches in practice. In the first part of this review, a summary of some challenges that occur in the governance of food system transformation is given. Through a case study of plant-based proteins and their biological and chemical modification as diets shift towards alternative proteins, we demonstrate that resource-efficient food systems and food waste, through system transformation, are useful in understanding both (i) how food system transformation has ensued and (ii) how the required transformation is prohibited. Finally, we discuss the implications of food system transformation in terms of nutrition and sustainable healthy diets, which are needed to achieve changes in food safety systems in the future. The linkage of food and the environment is evident, focusing on nutrition and sustainable healthy diets. This cannot be accomplished without system change and research towards new foods and, more specifically, new proteins such as plant-based ones and their biological and chemical modification.

Waste metrics in the framework of circular economy

There are several sustainability issues that the linear economy of today's society cannot adequately tackle (i.e. resource depletion, waste treatment, etc.). As a result, the scientific community and policymakers give high priority to the implementation of the circular economy concept. The sustainable development goals of the United Nations are in line with the European Union's (EU) commitment to a smooth transition to a circular economy. Circular business models require a shift in technical elements involving R strategies to replace traditional business models (i.e. reuse, reduce, recycle, etc.). Monitoring circular economy to provide quantifiable, measurable data is necessary for a successful transition. Monitoring tools (i.e. Key Performance Indicators, quality protocols) enable decision-makers to measure circular economy performance and identify circularity's advantages and disadvantages. To stimulate the adoption of a circularity model addressing critical issues of excessive waste production and resource use, this mini review aims to address the literature gap of waste metrics in the framework of circular economy and offer insights on circular economy indicators to aid for a seamless transition to a more sustainable society. For this purpose, Preferred Reporting Items for Systematic Reviews and Meta-Analysis method was chosen to assess literature. The authors collected and analysed data from 101 records, 70 articles and 31 reports related to the topic under consideration. Through the literature review, it is obvious that moving away from linear production model frequently leads to the development of new internal capabilities along the value chain and, eventually, high efficiency that reduces costs, increasing productivity, encourages brand names, minimizes threats, creates new products and fulfils regulations and green consumer expectations.

Digital inclusion to enhance energy sustainability: public participation and environmental governance in the new media era to achieve energy sustainable goals

Renewable energy not only helps to safeguard the environment and slow down climate change but also supports economic growth and energy security. The significance of renewable energy sources is expanding as more people throughout the globe understand how important it is to switch to clean energy sources. Therefore, empirics are in search of the factors that can promote renewable energy production. This analysis investigates some of the novel determinants of renewable energy production, such as digital inclusion, public participation, and environmental governance, which have not been examined previously in any study. For empirical analysis, the study employs the ARDL and QARDL estimation techniques using Chinese data from 1998Q1 to 2021Q4. The analysis findings confirm that digital financial inclusion, ICT, and GDP are vital in boosting both short and long-run renewable production. Green investment, environmental governance, and carbon emissions also significantly and favourably impact long-run renewable energy production. In the Quantile ARDL model, digital financial inclusion is positively linked to renewable energy production at most of its quantiles in the short and long run, while the ICT, GDP, environmental governance, and carbon emissions are positively linked to renewable energy in most quantiles in the long-run only. The Wald test confirms the asymmetric impact for all variables in the long run, which implies that policymakers should consider the positive and negative changes in these factors while devising policies for enhancing renewable energy production.

Recent advances in green technology and Industrial Revolution 4.0 for a sustainable future

This review gives concise information on green technology (GT) and Industrial Revolution 4.0 (IR 4.0). Climate change has begun showing its impacts on the environment, and the change is real. The devastating COVID-19 pandemic has negatively affected lives and the world from the deadly consequences at a social, economic, and environmental level. In order to balance this crisis, there is a need to transition toward green, sustainable forms of living and practices. We need green innovative technologies (GTI) and Internet of Things (IoT) technologies to develop green, durable, biodegradable, and eco-friendly products for a sustainable future. GTI encompasses all innovations that contribute to developing significant products, services, or processes that lower environmental harm, impact, and worsening while augmenting natural resource utilization. Sensors are typically used in IoT environmental monitoring applications to aid ecological safety by nursing air or water quality, atmospheric or soil conditions, and even monitoring species' movements and habitats. The industries and the governments are working together, have come up with solutions-the Green New Deal, carbon pricing, use of bio-based products as biopesticides, in biopharmaceuticals, green building materials, bio-based membrane filters for removing pollutants, bioenergy, biofuels and are essential for the green recovery of world economies. Environmental biotechnology, Green Chemical Engineering, more bio-based materials to separate pollutants, and product engineering of advanced materials and environmental economies are discussed here to pave the way toward the Sustainable Development Goals (SDGs) set by the UN and achieve the much-needed IR 4.0 for a greener-balanced environment and a sustainable future.

Assessing the carbon emission performance of digital greening synergistic transformation: evidence from the dual pilot projects in China

Digital greening synergistic transformation (DGST) is a new engine for achieving dual carbon targets. Using panel data from 281 Chinese cities between 2003 and 2019, this study investigates the effect and transmission mechanism of the DGST on carbon emission performance. It is based on the quasi-natural experiments of the dual pilot projects "Broadband China" and "Low-carbon City", as well as the multi-period difference-in-difference method. The empirical findings are as follows: (1) DGST, represented by the dual pilot projects, effectively enhances carbon emission performance. Compared to the isolated "Broadband China" and "Low-Carbon City" pilot projects, establishing dual pilot projects generates a more pronounced carbon emission reduction effect through synergistic effects. (2) In terms of dynamic effects, the carbon emission reduction effect in dual pilot cities appears in the first year following initiation, indicating a certain temporal aspect to this effect. (3) Mechanism analysis reveals that the impact of DGST on carbon emission performance is channeled through two pathways: industrial structural adjustment and low-carbon technology innovation. (4) The positive impact of DGST on carbon emission performance exhibits heterogeneity, primarily present in cities with higher levels of financial technology, human capital, and new infrastructure development. It implies that the implementation of DGST necessitates adequate human, financial, and material support. In conclusion, this research contributes empirical evidence for further exploring policy synergies, offering support for achieving dual carbon targets through DGST.

Do clean energy technologies, ecotourism, health policy, and green education help in achieving sustainability in China?

Sustainable development has become the foremost requirement for sustainable economic conditions all around the globe, and this aspect demands new literature and regulators' emphasis. Hence, the present research investigates the impact of clean energy technologies, human development, health policies, green education, and ecotourism policy on sustainable development in China from 1991 to 2021. The researchers investigate the association among the variables using dynamic autoregressive distributed lag (DARDL). The outcomes revealed that clean energy technologies, human development, health policies, green education, and ecotourism policy have positive linkages with sustainable development in China. The article provides guidelines to the policymakers in developing policies related to attain sustainable development using effective clean energy technologies, human development, health policies, green education, and ecotourism policy.

Dynamics of soil properties as impacted by contrasting lithology, slope class, and land use types: a case study in semi-arid highlands of northern Ethiopia

Soil characterization is crucial in creating sustainable platforms for land users to identify areas vulnerable to anthropogenic activities. This study was conducted to investigate the impacts of lithology, slope, and land use on soil properties of a semi-arid highland in northern Ethiopia. Disturbed and undisturbed soil samples collected from 0 to 30 cm depth were analyzed. Most of the assessed physical and biochemical soil properties varied significantly (p < 0.05) with lithology, slope class, and land use type. Shale-originated soils were richer in nutrients than soils of other lithologies. A decrease in slope gradient accounted for an increase in most soil properties, while a reverse trend was observed for sand content, bulk density (BD), water stable aggregates (WSA), mean weight diameter (MWD), structural stability index (SSI), soil organic carbon (SOC), total nitrogen (TN), and available phosphorus (AP). Silt and clay fractions, total porosity, moisture content at field capacity and wilting point, visual evaluation of soil structure, pH, electrical conductivity, calcium carbonate, exchangeable bases, cation exchange capacity, and percent base saturation were found to be higher for cultivated land soils compared to grass land and shrub land soils. Shrub land soils, in contrast, had higher WSA, MWD, SSI, SOC, TN, and AP relative to grass land and cultivated land soils. In summary, slope class and land use type stood out as the major drivers influencing the dynamics and distribution of soil properties other than lithology and their interactions in semi-arid highlands of northern Ethiopia. Thus, from sustainability point of view and in the light of their nutrient retention capability and limitation, more attention should be paid toward ensuring periodic assessment and sustainable management of soils in steep cultivated lands.

Current status and future challenges of genotoxicity OECD Test Guidelines for nanomaterials: a workshop report

Genotoxicity testing for nanomaterials remains challenging as standard testing approaches require some adaptation, and further development of nano-specific OECD Test Guidelines (TGs) and Guidance Documents (GDs) are needed. However, the field of genotoxicology continues to progress and new approach methodologies (NAMs) are being developed that could provide relevant information on the range of mechanisms of genotoxic action that may be imparted by nanomaterials. There is a recognition of the need for implementation of new and/or adapted OECD TGs, new OECD GDs, and utilization of NAMs within a genotoxicity testing framework for nanomaterials. As such, the requirements to apply new experimental approaches and data for genotoxicity assessment of nanomaterials in a regulatory context is neither clear, nor used in practice. Thus, an international workshop with representatives from regulatory agencies, industry, government, and academic scientists was convened to discuss these issues. The expert discussion highlighted the current deficiencies that exist in standard testing approaches within exposure regimes, insufficient physicochemical characterization, lack of demonstration of cell or tissue uptake and internalization, and limitations in the coverage of genotoxic modes of action. Regarding the latter aspect, a consensus was reached on the importance of using NAMs to support the genotoxicity assessment of nanomaterials. Also highlighted was the need for close engagement between scientists and regulators to (i) provide clarity on the regulatory needs, (ii) improve the acceptance and use of NAM-generated data, and (iii) define how NAMs may be used as part of weight of evidence approaches for use in regulatory risk assessments.

Health professionals' readiness to implement electronic medical record system in Gamo zone public hospitals, southern Ethiopia: an institution based cross-sectional study

BACKGROUND

The adoption of Electronic Medical Records (EMR) by the healthcare sector can improve patient care and safety, facilitate structured research, and effectively plan, monitor, and assess disease. EMR adoptions in low-income countries like Ethiopia were delayed and failing more frequently, despite their critical necessity. The most popular way to solve the issue is to evaluate user preparedness prior to the adoption of EMR. However, little is known regarding the EMR readiness of healthcare professionals in this study setting. Therefore, the objective of this study was to assess the readiness and factors associated with health professional readiness toward EMR in Gamo Zone, Ethiopia.

METHODS

An institution-based cross-sectional survey was conducted by using a pretested self-administered questionnaire on 416 study participants at public hospital hospitals in southern Ethiopia. STAT version 14 software was used to conduct the analysis after the data was entered using Epi-data version 3.2. A binary logistic regression model was fitted to identify factors associated with readiness. Finally, the results were interpreted using an adjusted odds ratio (AOR) with a 95% confidence interval (CI) and p-value less than 0.05.

RESULTS

A total of 400 participants enrolled in the study, with a response rate of 97.1%. A total of 65.25% (n = 261) [95% CI: 0.60, 0.69] participants had overall readiness, 68.75% (n = 275) [95% CI: 0.64, 0.73] had engagement readiness, and (69.75%) (n = 279) [95% CI: 0.65, 0.74] had core EMR readiness. Computer skills (AOR: 3.06; 95% CI: 1.49-6.29), EMR training (AOR: 2.00; 95% CI: 1.06-3.67), good EMR knowledge (AOR: 2.021; 95% CI: 1.19-3.39), and favorable attitude (AOR: 3.00; 95% CI: 1.76-4.97) were factors significantly associated with EMR readiness.

CONCLUSION

Although it was deemed insufficient, more than half of the respondents indicated a satisfactory level of overall readiness for the adoption of EMR. Moreover, having computer skills, having EMR training, good EMR knowledge, and favorable EMR attitude were all significantly and positively related to EMR readiness.

Regional unevenness in the construction of digital villages: A case study of China

In regard to the comprehensive promotion of rural revitalization, the construction of digital villages is a crucial development. Because the construction of digital villages is considerably novel, the existing studies mainly focus on the theoretical aspects pertaining to the rational and practical robustness of digital villages, and with regard to regional unevenness, the number of studies that consider the current characteristics, absolute gaps, and impact mechanisms pertaining to the construction of digital villages is insufficient. Based on the regional unevenness that characterizes digital village construction, this study proposes a research framework for digital technology-enabled village construction, which integrates three major factors, namely technology, institutions, and human resources; thus, the comprehensive assessment pertaining to the level of digital village construction is enhanced. This study, which applies the aforementioned research framework, constructs an index system for evaluating the construction level of digital villages, and to reveal the characteristics pertaining to regional heterogeneity and the main influencing factors pertaining to the construction level of digital villages in China (study period; 2015-2020), it utilizes the Dagum Gini coefficient method and the spatial econometric model. Consequently, the researchers observe the following: First, the level of digital village construction in China exhibits a "W-shaped" recovery growth. Second, with respect to the regional level, the eastern region exhibits the highest level of digital village construction, followed by central and western regions; furthermore, we observe that the eastern and western regions account for the greatest intra-regional variation, and that with regard to the overall difference, the inter-regional gap represents the main causative factor. Finally, with regard to influencing factors, technology and innovation capabilities, occupational differentiation of farmers, economic development significantly contribute to the level of digital village construction, whereas fiscal autonomy exerts a significant inhibiting effect. In regard to the level of digital village construction, the research framework and results may provide a novel analytical framework for examining the main sources of regional unevenness, and it may also provide a reference for decision-making, which can influence the construction of digital villages in China as well as in other countries.

The water-energy-food nexus in biodiversity conservation: A systematic review around sustainability transitions of agricultural systems

The Water Energy Food nexus is a powerful topic in agricultural systems to elucidate threats to biodiversity conservation and culture. This paper aimed to recapitulate nexus thinking research, focusing on social-ecological transitions of agriculture systems and biodiversity management within the Water-Energy-Food nexus. We developed a systematic review and a bibliometric analysis derived from 529 documents in the Scopus database. The ToS method identified a total of 81 relevant information in the sample of documents (529) categorised into roots (10), trunks (9) and leaves (62). This review paper situates types, focus, and highlights regarding biodiversity and prevalent thematic research areas such as "Food Nexus", "Environmental Flows", "Sustainability", "Transitions", and "Governance". Our results suggest that future research should focus on the nexus of "Water-Energy-Food-Biodiversity" and propose a transdisciplinary approach to elucidate the state of sustainability transitions in the agricultural systems at the landscape level. It could increase stakeholder interest in conservation, and sustainability management, to reverse biodiversity losses in ecosystems.

Assessment of the correlation between the nutrient load from migratory bird excrement and water quality by principal component analysis in a freshwater habitat

Waterbirds depend on a dispersed network of wetlands for their annual life cycle during migration. Climate and land use changes raise new concerns about the sustainability of these habitat networks, as water scarcity triggers ecological and socioeconomic impacts threatening wetland availability and quality. During the migration period, birds can be present in large enough numbers to influence water quality themselves linking them and water management in efforts to conserve habitats for endangered populations. Despite this, the guidelines within laws do not properly account for the annual change of water quality due to natural factors such as the migration periods of birds. Principal component analysis and principal component regression was used to analyze the correlations between the presence of a multitude of migratory waterbird communities and water quality metrics based on a dataset collected over four years in the Dumbrăvița section of the Homoród stream in Transylvania. The results reveal a correlation between the presence and numbers of various bird species and the seasonal changes in water quality. Piscivorous birds tended to increase the phosphorus load, herbivorous waterbirds the nitrogen load, while benthivorous duck species influenced a variety of parameters. The established PCR water quality prediction model showed accurate prediction capabilities for the water quality index of the observed region. For the tested data set, the method provided an R² value of 0.81 and a mean squared prediction error of 0.17.

How do carbon emissions, economic growth, population growth, trade openness and employment influence food security? Recent evidence from the East Africa

East Africa has a substantially greater rate of food insecurity than other regions of the world. Scenarios of climate change and other macroeconomic variables are important contributors to food insecurity in East Africa. Using data spanning from 1990 to 2020, this study looked into the influence of carbon dioxide (CO₂) emissions, economic growth, population growth, trade openness, and agricultural employment on food security in the East Africa. The fully modified ordinary least square (FMOLS) and dynamic ordinary least square (DOLS) models were used in this study. The heterogeneous panel cointegration test's findings indicated that the study variables have an equilibrium long-term connections. The estimation findings from the FMOLS and DOLS models showed that an increase in CO₂ emissions increases food security in the East Africa over the long term. According to other findings, long-term food security is positively impacted by economic expansion, population growth, trade openness, and employment in agriculture. However, trade openness has a detrimental long-lasting effect on food security. Future research directions, research limitations, and policy implications are discussed.

Evaluation of Digital’s Role in Sustainable Built Environment

The construction industry has been evolving, embracing the delicate balance between the Fourth Industry Revolution and sustainable construction to create a sustainable and resilient built environment. Integrating digital tools and technologies in a renowned conventional construction industry is challenging, mainly due to the complex interaction between heterogeneous but heuristic construction processes, building systems, and workflows in achieving a common goal. This study took the initiative to review digital tool adoption and its role in the sustainable built environment by examining the impact of digital adoption in a sustainable built environment in terms of societal and industry impacts. A quantitative analysis is conducted, collecting 63 industry practitioners analysed through regression analysis. The result reveals that energy conservation is the most significant element in the sustainable built environment, which brought the greatest impact on both society and industry in Malaysia. Based on the results, it is found that the digital adoption level in the Malaysian construction industry is still at a minimal level. Through the introduction of Indutry4wrd, National 4IR and Construction 4.0 Strategic Plan (2021–2025), the importance of digital tools and technologies is slowly being acknowledged. The result of the study is significant to benchmark the current digital tools adoption in the Malaysian sustainable built environment. Moreover, the contribution could be made in terms of better understanding and facilitating, where relevant, greater usage of digital tools in the construction industry to promote efficiency.

Management of Climate Resilience: Exploring the Potential of Digital Twin Technology, 3D City Modelling, and Early Warning Systems

Cities, and in particular those in coastal low-lying areas, are becoming increasingly susceptible to climate change, the impact of which is worsened by the tendency for population concentration in these areas. Therefore, comprehensive early warning systems are necessary to minimize harm from extreme climate events on communities. Ideally, such a system would allow all stakeholders to acquire accurate up-to-date information and respond effectively. This paper presents a systematic review that highlights the significance, potential, and future directions of 3D city modelling, early warning systems, and digital twins in the creation of technology for building climate resilience through the effective management of smart cities. In total, 68 papers were identified through the PRISMA approach. A total of 37 case studies were included, among which (n = 10) define the framework for a digital twin technology, (n = 14) involve the design of 3D virtual city models, and (n = 13) entail the generation of early warning alerts using the real-time sensor data. This review concludes that the bidirectional flow of data between a digital model and the real physical environment is an emerging concept for enhancing climate resilience. However, the research is primarily in the phase of theoretical concepts and discussion, and numerous research gaps remain regarding the implementation and use of a bidirectional data flow in a true digital twin. Nonetheless, ongoing innovative research projects are exploring the potential of digital twin technology to address the challenges faced by communities in vulnerable areas, which will hopefully lead to practical solutions for enhancing climate resilience in the near future.

Unexpected Effects of Sulfate and Sodium Chloride Application on Yield Qualitative Characteristics and Symmetry Indicators of Hard and Soft Wheat Kernels

The heterogeneity of grain quality can lead to limited predictability of qualitative and quantitative characteristics of the wheat yield, especially with an increase in the importance of drought and salinity caused by climate change. This study was undertaken with the aim of creating basic tools for phenotyping and assessing the sensitivity of genotypes to salt effects at the level of some wheat kernel attributes. The study considers 36 variants of the experiment, including four wheat cultivars-Zolotaya, Ulyanovskaya 105, Orenburgskaya 10, Orenburgskaya 23; three treatment variants-control (without salt) and two salts exposure (NaCl at a concentration of 1.1 g L^-1 and Na₂SO₄ at a concentration of 0.4 g L^-1); as well as three options for the arrangement of kernels in a simple spikelet-left, middle, and right. It has been established that the salt exposure had a positive effect on the percentage of kernel fulfilling in the cultivars Zolotaya, Ulyanovskaya 105, and Orenburgskaya 23 compared to control. The kernels of the Orenburgskaya 10 variety matured better in the experiment with Na₂SO₄ exposure, while the control variant and NaCl gave the same effect. When exposed to NaCl, significantly greater values of weight, transverse section area, and transverse section perimeter of the kernel were noted in the cv Zolotaya and Ulyanovskaya 105. Cv Orenburgskaya 10 responded positively to the use of Na₂SO₄. This salt caused an increase in the area, length, and width of the kernel. The fluctuating asymmetry of the left, middle, and right kernels in the spikelet was calculated. In the cv Orenburgskaya 23 the salts affected only the kernel perimeter among parameters examined. The indicators of the general (fluctuating) asymmetry were lower in the experiments with the use of salts, i.e., kernels were more symmetrical than in the control variant, both for the cultivar as a whole and when compared taking into account the kernel location in spikelet. However, this result was unexpected, since salt stress inhibited a number of morphological parameters: the number and average length of embryonic, adventitious, and nodal roots, flag leaf area, plant height, dry biomass accumulation, and plant productivity indicators. The study showed that low concentrations of salts can positively affect the fulfilling of kernels (the absence of a cavity inside the kernel) and the symmetry of the left and right sides of the kernel.

Unfolding sustainable auditing ecosystem formation path through digitalization transformation: How digital intelligence of accountant fosters the digitalization capabilities

This research aims at indulging a consistent image of how Digitalization Capabilities (DC) demonstrates an impact on Sustainable Auditing Ecosystem (SAE) within public sector organizations (PSOs) in developing countries, especial in an emerging market, and gives insights regarding to divergent impacts of the interconnection between DC and SAE moderated by different levels of Accountants' Digital Intelligence (ADI). The state-of-the-art structural equation modelling (SEM) was employed to statistically analyze the survey data collected from self-administered questionnaire distributed to a convenient sample of 323 respondents. Additionally, multi-group analysis (MGA) was implemented to explore the heterogeneity of data and examined substance of the difference in the parameters caused by the moderating variable. The obtained results advocated that it was paramount for PSOs to increase DC for SAE formulation. The MGA findings highlighted a statistically significant difference in the impacts of DC on SAE between various levels of ADI. The insights acquired from final model emerged as a foundation which might buttress policymakers and PSOs' practitioners in initiatives development pertaining to digitalization for SAE formulation.

Does Digital Capability Promote Sustainable Development of New Ventures? The Dual Impact of Green Knowledge Creation and Green Pressure

With the environmental problems brought about by the extensive economic development model attracting more and more global attention, sustainable development has become a hot topic in transformation and development of contemporary enterprises. In the context of the digital economy, there is a lack of conclusive evidence regarding whether and how enterprises rely on digital capabilities to improve green efficiency and achieve sustainable development, especially for new ventures. Therefore, based on the knowledge creation spiral theory, this paper examines the relationship between digital capabilities, green knowledge creation, and sustainable development of new ventures. The study tested its hypotheses on a sample of 316 Chinese new ventures. The results showed that digital capabilities can positively affect environmental, economic, and social performance of new ventures and support their sustainable development; green knowledge creation plays a mediating role in the relationship between digital capabilities and sustainable development, and green pressure positively moderates the relationship between green knowledge creation and sustainable development; furthermore, green pressure also moderates the process of digital capabilities influencing sustainable development through green knowledge creation, and that moderated mediation role is significant. According to the bootstrap mediating effect test, both the direct effect and indirect effect are significant. Overall, our research results provide important insights for new ventures to promote sustainable development through digitalization. Therefore, managers should pay more attention to digital construction in the strategic layout of new ventures, and they should advocate the concept of green knowledge so that the goal of sustainable development can be achieved with the drive for digitalization.

Analysing associations between digitalization and the accomplishment of the Sustainable Development Goals

Sustainability is a very complex concept made up of a multitude of interacting aspects that do not necessarily work synergistically with each other. The consequential outcome of cross-cutting drivers, such as digitalisation, is often difficult to assess, as the achievement of certain targets may also inadvertently hinder progress towards others. This investigation describes a comprehensive and systematic country-based analysis of statistical associations between digitalization and sustainability indicators operating at three different levels (i.e., index, goal and indicators). Results showed strong correlations between the composite indices for digitalization (IDI Development Index), sustainability (SDG Index from) and economic growth (GCI and GDP). However, the analysis of lower-level indicators provides a more ambiguous picture, with 2 of the sustainability goals and 22 % of the sustainability indicators included in the SDG Index showing negative associations with digitalisation. It appears that while synergies are generated in aspects related to economic and social sustainability, trade-offs occur in areas related to environmental protection such as climate change, depletion of natural resources and waste generation due to their negative associations with existing economic development models. These structural obstacles need to be acknowledged and adequately managed in order to ensuring harmonious and integral progress towards effective sustainability.

A Multilevel Model of Older Adults' Appropriation of ICT and Acquisition of Digital Literacy

Digital literacy refers to a set of competencies related to the skilled use of computers and information technology. Low digital skills can be a barrier for older adults' full participation in a digital society, and COVID-19 has increased this risk of social exclusion. Older adults' digital inclusion is a complex process that consists of the interplay of structural and individual factors. The ACCESS project unwrapped the complexity of the process and developed an innovative, multilevel model that illustrates how societal, institutional, material and pedagogical aspects shape adults' appropriation of digital literacy. A holistic model describes factors contributing to older adults' digital literacy, acknowledging sociocultural contexts, environments, learning settings and instruction practices for learning digital literacy. Instead of seeing older adults' reasons for learning digital skills purely as individual choice, this model recognizes the interpersonal, institutional and societal aspects that implicitly or explicitly influence older adults' acquisition of digital literacy. The results offer a tool for stakeholders, the research community, companies, designers and other relevant stakeholders to consider digital skills and the given support. It demands diverse communication between different stakeholders about the things that should be discussed when organizing digital support in digitalized societies.

Coupling Coordination Measurement and Evaluation of Urban Digitalization and Green Development in China

The coordinated promotion of urban digitalization and green development is an inevitable requirement for sustainable development in the digital age. Based on the coupling mechanism of urban digitalization and green development, in this study, we took 282 cities at the prefecture level and above in China from 2011 to 2019 as the research object, and we constructed the evaluation index system and calculated the coupling coordination degree (CD&GDD) of the two through the coupling coordination degree model. We further used the Dagum Gini coefficient, kernel density estimation, Markov chain and Moran's I to assess the spatial effects of the regional differences, dynamic evolution trends and degree of coupling coordination. The results show the following: (1) The level of urban digitalization and green development show a fluctuating upward trend, and the interaction between the two is obvious. (2) Although the CD&GDD of most cities is continuously improving, it is still at a low level. There are large differences in the levels between the regions. (3) The inter-regional differences are the main source of the large overall differences in the CD&GDD in China, and these are mainly composed of the hypervariable density and net differences between the regions. (4) The phenomenon of "club convergence" exists in the CD&GDD. (5) The coupling coordination relationship between cities has a substantial spatial effect, and the spatial effect has obvious regional heterogeneity. The results and conclusions provide a reference for developing countries to promote green and low-carbon urban development.

Electrochemical oxidation of fipronil pesticide is effective under environmental relevant concentrations

Pesticide overuse has posed a threat to agricultural community as well as for the environment. In order to treat this pollution at its source, decentralized and selective technologies such as electrochemical processes appear especially relevant to avoid the possible generation of toxic degradation products. Electrochemical oxidation (ECO) is a promising electrochemically-driven process, but most studies evaluate performance under pollutant concentrations that are orders of magnitude higher than environmental relevant conditions. This work explores ECO treatment of fipronil using boron-doped diamond (BDD) as anode and titanium plate as cathode at small concentrations found in agricultural run-off. The effect of applied current density and initial contaminant concentrations were also studied. For a current density of 20 mA cm^-2 the decrease of COD and fipronil were about 97% and 100% after 360 min of electrolysis, respectively. Engineering figures of merit were evaluated to assess competitiveness of ECO decentralized propositions. Results suggest effective and feasible treatment of fipronil by ECO.

Digital transformation of peatland eco-innovations ('Paludiculture'): Enabling a paradigm shift towards the real-time sustainable production of 'green-friendly' products and services

The world is heading in the wrong direction on carbon emissions where we are not on track to limit global warming to 1.5 °C; Ireland is among the countries where overall emissions have continued to rise. The development of wettable peatland products and services (termed 'Paludiculture') present significant opportunities for enabling a transition away from peat-harvesting (fossil fuels) to developing 'green' eco-innovations. However, this must be balanced with sustainable carbon sequestration and environmental protection. This complex transition from 'brown to green' must be met in real time by enabling digital technologies across the full value chain. This will potentially necessitate creation of new green-business models with the potential to support disruptive innovation. This timely paper describes digital transformation of paludiculture-based eco-innovation that will potentially lead to a paradigm shift towards using smart digital technologies to address efficiency of products and services along with future-proofing for climate change. Digital transform of paludiculture also aligns with the 'Industry 5.0 - a human-centric solution'. However, companies supporting peatland innovation may lack necessary standards, data-sharing or capabilities that can also affect viable business model propositions that can jeopardize economic, political and social sustainability. Digital solutions may reduce costs, increase productivity, improve produce develop, and achieve faster time to market for paludiculture. Digitisation also enables information systems to be open, interoperable, and user-friendly. This constitutes the first study to describe the digital transformation of paludiculture, both vertically and horizontally, in order to inform sustainability that includes process automation via AI, machine learning, IoT-Cloud informed sensors and robotics, virtual and augmented reality, and blockchain for cyber-physical systems. Thus, the aim of this paper is to describe the applicability of digital transformation to actualize the benefits and opportunities of paludiculture activities and enterprises in the Irish midlands with a global orientation.

Case of study on a sustainability building: Environmental risk assessment related with allergenicity from air quality considering meteorological and urban green infrastructure data on BIM

Digitisation is gaining importance with 3D workflow for architecture-specific annotation of built heritage. The objective is to use the Building Information Modeling (BIM) methodology in order to carry out a study of alternatives of impact on environmental sustainability associated with the potential allergenicity with green infrastructure on a new housing, located in Mérida (SW Spain). It is intended to simulate the meteorology (direction and speed of the wind) in the study city with the compass rose for 18 years (2003-2020) to assess the meteorological pattern associated with the wind on the studied housing. 3 green infrastructure garden alternatives (considering 5 ornamental species of cypress trees) were designed to evaluate the potential impact of allergenicity on the housing. AIROT index was applied to project the results on the frontage of the housing. This index was developed in the field of large areas of urban environments. The calculation was carried out in the most exact way possible in specific sections of the frontage of the housing and automatically with tools associated with the BIM environment (such as Autodesk Revit, Dynamo, Enscape, Wrplot and Bim One) to the discipline of Architecture (such as Autodesk Autocad and Autodesk Flow Design). The obtained results were applied to evaluate 3 scenario designs, trying to minimize the potential exposure to urban green infrastructure (focus on cypress trees) in this current project, and offering a health reference guide in future projects, from the design phase considering appropriate measures and proposing recommendations.

Study on the Drivers of Inclusive Green Growth in China Based on the Digital Economy Represented by the Internet of Things (IoT)

With the vigorous development of digital economy based on digital technologies such as Internet of things (IoT), big data, and artificial intelligence, new vitality has been injected into China's economic model. Inclusive green growth (IGG) supports the transformation of society towards a better quality of life and well-being, as well as environmental protection. Therefore, it is crucial to identify the main drivers of IGG. However, IGG is subject to a variety of interpretations and lacks definitional clarity. To brigade this gap, this study primarily evaluates the performance of IGG and explores the key drivers on IGG in China. Specifically, the data envelopment analysis (DEA) model is employed to calculate IGG for 281 cities in China during 2005-2020. Subsequently, we take advantage of a nest of machine learning (ML) algorithm to demonstrate the vital drivers of urban IGG, which avoids the defects of endogenous linear hypothesis of traditional econometric methods. The results indicate that digitization represented by the IoT and other digital technology is the core drivers of the urban IGG in the overall sample, accounting for about 50% among all of drivers. This finding provides new evidence supporting the "high-quality development" strategy in China, as well as shedding light on grasping the principal fulcrum to achieve the transformation towards IGG in developing economies similar to China.

Sanitation, water, energy use, and traffic volume affect environmental quality: Go-for-green developmental policies

Carbon emissions are primarily the result of human activity in urban areas. Inadequate sanitary facilities, contaminated drinking water, nonrenewable energy, and high traffic congestion have all impacted the natural ecosystem. Using data from 1975 to 2019, the study assessed the impact of the aforementioned variables on Pakistan's carbon emissions in light of this crucial fact. The ARDL cointegration method was used to estimate the short- and long-run parameter estimates. Urban sanitation challenges and energy consumption increase carbon emissions, which affects the natural environment by raising a country's carbon intensity. Economic expansion confirmed the inverted U-shaped relationship between carbon emissions and economic growth to verify the Environmental Kuznets Curve (EKC) hypothesis in the long run. In contrast, the monotonically rising function of carbon emissions provides evidence of the nation's economic development in the short run. Access to clean drinking water improves population health and encourages the purchase of eco-friendly products. The government must improve sanitation services and use renewable energy sources to enhance air quality.

Unified waste metrics: A gamified tool in next-generation strategic planning

A gamification approach for tackling waste management planning and urban development provide a more engaging and interactive experience with high pedagogical potential. Existing serious games involving waste management are complex in their data ingestion, use, and presentation, limiting individuals' opportunities to gain knowledge and decision-making skills transferrable to the real world. Simulations, by comparison, provide either an oversimplified and unrealistic user interface or explore in depth individual rather than aggregate key performance indicators for waste management, limiting potential knowledge retention. There is a clear opportunity in creating an informative, easy-to-use simulation-based game to help stakeholders build understanding of waste management policies, performance, and causal relationships. This gamified tool provides clear feedback through quick-visibility performance indicators (i.e., waste accumulation index, waste compositional analysis, prevention activities etc.) and offers the opportunity, through multi-criteria decision making, of simulating real-life scenarios and previewing the possible outcomes of certain in-game actions. The research question is how the process of gamification might serve as powerful tool for educating decision makers. The results are considered as a reference point to any policy maker intending to assess environmental performance, proposed activities to reach Circular Economy targets, and European Green Deal and UN Sustainable Development Goals.

Sustainability in Numbers by Data Analytics

For a successful delivery of the United Nations Sustainable Development Goals (UNSDGs) and to track the progress of UNSDGs as well as identify the gaps and the areas requiring more attention, periodic analyses on the "research on sustainability" by various countries and their contribution to the topic are inevitable. This paper tracks the trends in sustainability research including the geographical distribution on sustainability research, their level of multi-disciplinarity and the cross-border collaboration, their distribution of funding with respect to the UNSDGs, and the lifecycle analyses. Cumulative publications and patents on sustainability could be fitted to an exponential function, thereby highlighting the importance of the research on sustainability in the recent past. Besides, this analytics quantifies cross-border collaborations and knowledge integration to solve critical issues as well as traditional and emerging sources to undertake sustainability research. As an important aspect of resource sustainability and circular economy, trends in publication and funding on lifecycle assessment have also been investigated. The analytics present here identify that major sustainability research volume is from the social sciences as well as business and economics sectors, whereas contributions from the engineering disciplines to develop technologies for sustainability practices are relatively lower. Similarly, funding distribution is also not evenly distributed under various SDGs; the larger share of funding has been on energy security and climate change research. Thus, this study identifies many gaps to be filled for the UNSDGs to be successful.

Optimization of water quality monitoring programs by data mining

Water quality monitoring programs are essential planning and management tools, but they face many challenges in the developing world. The scarcity of financial and human resources and the unavailability of infrastructure often make it impossible to meet the legal requirements of water monitoring. Many approaches to optimizing water quality monitoring programs have already been proposed. However, few investigations have developed and tested data mining for this purpose. This article has developed data-based models to reduce the number of water quality parameters of monitoring programs using data mining. The objective was to extract patterns from the database, expressed by association rules, which together with field parameters, measured with automatic probes, can estimate laboratory variables. This approach was applied in 35 monitoring stations along 27 river basins throughout Brazil. The data are from fifty years of monitoring (1971-2021), constituting 6328 observations of 60 water quality parameters investigated in different environmental contexts, water quality, and the structuring of monitoring programs. With the applied approach it was possible to estimate 56% of the laboratory parameters in the monitoring stations investigated. The influence of environmental characteristics on the optimization capacity of monitoring programs was evident. The methodology used was not influenced by different water quality levels and anthropogenic impacts. However, the number of parameters was the most influential element in optimization. Monitoring programs with 20 or more water quality variables have the highest potential (≥44%) of optimization by this methodology. Results demonstrate that this approach is a promising alternative that can reduce the frequency of analyses measured in the laboratory and increase the spatial and temporal coverage of water quality monitoring networks.

Analysis of energy management schemes for renewable-energy-based smart homes against the backdrop of COVID-19

This article reviews energy management schemes for smart homes integrated with renewable energy resources in the context of the COVID-19 pandemic. The incorporation of distributed renewable energy system has initiated an acute transition from the traditional centralized energy management system to independent demand responsive energy systems. Renewable energy-based Smart Home Energy Management Systems (SHEMSs) play a vital role in the residential sector with the increased and dynamic electricity demand during the COVID-19 pandemic to enhance the efficacy, sustainability, economical benefits, and energy conservation for a distribution system. In this regard, the reviews of various energy management schemes for smart homes appliances and associated challenges has been presented. Different energy scheduling controller techniques have also been analyzed and compared in the COVID-19 framework by reviewing several cases from the literature. The utilization and benefits of renewable-based SHEMS have also been discussed. In addition, both micro and macro-level socio-economic implications of COVID-19 on SHEMSs are discussed. A conclusion has been drawn given the strengths and limitations of different energy scheduling controllers and optimization techniques in the context of the COVID-19 pandemic. It is observed that renewable-energy-based SHEMS with improved multi-objective meta-heuristic optimization algorithms employing artificial intelligence are better suited to deal with the dynamic residential energy demand in the pandemic. It is hoped that this review, as a fundamental platform, will facilitate the researchers aiming to investigate the performance of energy management and demand response schemes for further improvement, especially during the pandemic.

Industry 4.0 Wireless Networks and Cyber-Physical Smart Manufacturing Systems as Accelerators of Value-Added Growth in Slovak Exports

Industry 4.0 integrates smart and connected production systems that are pivotal in predicting and supporting production in real-time, leading to sustainable organizational performance. In manufacturing, it may increase productivity, sustainability, and energy efficiency, while optimizing competitiveness. The main purpose of this paper is to determine the impact of Industry 4.0 on the Slovak economy through a secondary data analysis in the automotive industry, which is the leading sector in the country. The paper aims to provide a comprehensive analysis of the various opportunities that are available in the value-added growth of car exports in Slovakia. It also explores the case study of PSA Group Slovakia, which highlights the importance of the Industry 4.0 concept in boosting the country’s export growth. The paper proposes a series of recommendations and steps to improve Slovakia’s innovation environment.

Digital economy and urban low-carbon sustainable development: the role of innovation factor mobility in China

To address climate change, one of the toughest contemporary environmental issues, growing importance is attached to the role of the digital economy in combating environmental degradation. Using panel data from 237 Chinese cities during the period 2011-2018, this paper attempts to provide a more systematic view of the relationship between the digital economy and urban low-carbon sustainable development to make up for the existing empirical inconclusiveness. Based on the fixed-effect model, results show that boosting the digital economy can effectively promote urban low-carbon sustainable development, and the conclusion remains robust across a series of robustness checks. Furthermore, innovation factor mobility is the critical transmission channel through which the digital economy affects urban low-carbon sustainable development. Spatiotemporal heterogeneity analysis reveals that the promoting effect of the digital economy on urban low-carbon sustainable development decreases from the northeast to the southeast of China, whereas the impact of innovation factor mobility on urban low-carbon sustainable development decreases from the southeast to the northeast with the Pearl River Delta as the core. Panel threshold regression analysis shows that the impact of the digital economy on urban low-carbon sustainable development is getting stronger with the increase of economic development level charactered with nighttime lights.

Edge AI and Blockchain for Smart Sustainable Cities: Promise and Potential

Modern cities worldwide are undergoing radical changes to foster a clean, sustainable and secure environment, install smart infrastructures, deliver intelligent services to residents, and facilitate access for vulnerable groups. The adoption of new technologies is at the heart of implementing many initiatives to address critical concerns in urban mobility, healthcare, water management, clean energy production and consumption, energy saving, housing, safety, and accessibility. Given the advancements in sensing and communication technologies over the past few decades, exploring the adoption of recent and innovative technologies is critical to addressing these concerns and making cities more innovative, sustainable, and safer. This article provides a broad understanding of the current urban challenges faced by smart cities. It highlights two new technological advances, edge artificial intelligence (edge AI) and Blockchain, and analyzes their transformative potential to make our cities smarter. In addition, it explores the multiple uses of edge AI and Blockchain technologies in the fields of smart mobility and smart energy and reviews relevant research efforts in these two critical areas of modern smart cities. It highlights the various algorithms to handle vehicle detection, counting, speed identification to address the problem of traffic congestion and the different use-cases of Blockchain in terms of trustworthy communications and trading between vehicles and smart energy trading. This review paper is expected to serve as a guideline for future research on adopting edge AI and Blockchain in other smart city domains.

Artificial intelligence solutions enabling sustainable agriculture: A bibliometric analysis

There is a dearth of literature that provides a bibliometric analysis concerning the role of Artificial Intelligence (AI) in sustainable agriculture therefore this study attempts to fill this research gap and provides evidence from the studies conducted between 2000–2021 in this field of research. The study is a systematic bibliographic analysis of the 465 previous articles and reviews done between 2000–2021 in relation to the utilization of AI in sustainable methods of agriculture. The results of the study have been visualized and presented using the VOSviewer and Biblioshiny visualizer software. The results obtained post analysis indicate that, the amount of academic works published in the field of AI’s role in enabling sustainable agriculture increased significantly from 2018. Therefore, there is conclusive evidence that the growth trajectory shows a significant climb upwards. Geographically analysed, the country collaboration network highlights that most number of studies in the realm of this study originate from China, USA, India, Iran, France. The co-author network analysis results represent that there are multi-disciplinary collaborations and interactions between prominent authors from United States of America, China, United Kingdom and Germany. The final framework provided from this bibliometric study will help future researchers identify the key areas of interest in research of AI and sustainable agriculture and narrow down on the countries where prominent academic work is published to explore co-authorship opportunities.

Energy Oriented Concepts and Other SMART WORLD Trends as Game Changers of Co-Production—Reality or Future?

The aim of the study is to identify, map and assess the maturity and impact level of the specific energy-oriented economy and other SMART management concepts and social, technological, finance (economical), environmental, and communication (S.T.F.E.C.) trends which arose from the dynamic development and spread of the Industry 4.0 revolution on processes of effective competitiveness and the creation of modern enterprises. The article presents data and information obtained thanks to an in-depth review of the literature (extensive desk research), as well as that obtained as part of the conducted CAWI pilot study. The authors aim to search for answers to three specific research questions, concluding that recently, special attention is paid to such issues as co-creation and co-production, energy-oriented and circular economy, eco-energy, and sustainability. The findings of this study clearly show that in the SMART WORLD era, there is a growing interest in cooperation, co-creation, co-production issues, and usage of modern technologies and SMART management concepts typical of the Industry 4.0 era. The main reason for this is that enterprises strive to optimize and maximize their efficiency in the processes of competitiveness creation. Researched data allows us to conclude that openness to social, environmental, and technological trends and issues, with an approach based on sustainable and eco-energy-oriented development, play an increasingly important role. However, the level of their importance, implementation level, and maturity differ depending on the type of organization or industry. For example, service and trade companies more often than production companies use and rate the usefulness of social trends higher (reality = mainstream orientation for S&T companies and a future orientation for production companies), while production companies apply a more balanced approach, showing greater commitment to economic technological, environmental and financial trends (reality = mainstream orientation for production companies and a future orientation for trade and services companies). Given that the study shows and describes preliminary research results (pilot studies), the authors plan to undertake further efforts in the in-depth scientific exploration of the issues concerned, including, which is particularly important, conducting full-scale research.

Determinants of the Digitalization of Accounting in an Emerging Market: The Roles of Organizational Support and Job Relevance

Digitalization has considerable potential to help achieve the sustainability of the planetary and human systems, including organizations. As digitalization is one of the most promising factors for transformation, there is no doubt that ICT and big data can help promote sustainability. Linking digitalization with a sustainable workplace, the purpose of this investigation is to identify the determinants of the adoption of digitalization of accounting procedures by accounting professionals in Saudi Arabia, an economy rapidly moving towards digital transformation. A holistic model based on the technology acceptance model (TAM), elaboration likelihood model (ELM), and social exchange theory (SET) is proposed and tested. The extension in TAM is proposed by integrating job relevance and organizational support as moderators. A survey method was used to collect data from 365 accounting professionals working in Saudi Arabia. Structural equation modeling and PROCESS macro were used as data analysis techniques. The findings reveal that perceived ease of use has both direct and indirect effects through perceived usefulness on intentions to use e-accounting. Both job relevance and organizational support act as moderators for perceived usefulness and intentions to use e-accounting when treated separately. However, job relevance becomes an insignificant moderator in the presence of organizational support. This finding highlights the importance of organizational support for the successful implementation of e-accounting in an organization.