Search Results (61)

Sustainable development initiatives are essential for enhancing the social economy and environmental preservation in marginalised rural areas of Tanzania. This study examines the impact of an IoT micro-factory on sustainable development, addressing issues such as inadequate production techniques, agribusiness monopolisation practices, the shortage of small-scale factories, and the failure to leverage global market comparative advantages. It explores the mediating role of architectural innovation and the moderating role of industrial symbiosis. The study surveyed 196 participants, including 100 orange farmers, 96 industrial engineers in the beverage sector, and conducted interviews with 3 industrial managers and 3 industrial consultants. SmartPLS 4 was used to evaluate the relationships between constructs. The results indicate that both IoT micro-factories and global production networks (GPNs) have a direct influence on sustainable social-economic development. Architectural innovation mediates these relationships, while industrial symbiotic moderates the interaction between IoT micro-factories and architectural innovation. The findings emphasise the importance of IoT micro-factories for sustainable development, with industrial symbiotic relationships addressing gaps in knowledge, skills, and equitable trade. The industrial stakeholders should prioritise IoT micro-factories as small-scale factories to promote sustainable development in rural communities of developing countries. Full article

Food waste poses a significant global challenge with profound economic, environmental, and social implications. Within the European Union, socioeconomic conditions, food affordability, and sustainability initiatives create a complex framework for understanding and mitigating food waste. This study examines how economic and sustainability factors shape food waste patterns across EU member states, employing advanced statistical techniques to uncover underlying dynamics. The analysis focuses on five key variables: the Harmonized Index of Consumer Prices for food, food waste, food retail sales, the Sustainable Development Goals Index, and GDP per capita. Factorial analysis and a general linear model were used to investigate linear relationships, and multilayer Perceptron (MLP) neural networks were employed to model the non-linear relationships driving food waste. At the same time, hierarchical cluster analysis identified four distinct country groups, each characterized by unique combinations of these variables. The results reveal that higher GDP per capita and stronger sustainability performance are associated with lower food waste, whereas higher food prices and increased retail activity present more nuanced influences. The findings underscore the importance of customized policies that address the EU’s diverse socioeconomic and sustainability contexts, offering a pathway toward more sustainable food systems and reduced waste. Full article

Future energy security and consumption trends for energy products have stimulated the consumption of products such as bioethanol, biodiesel, or biogas, generated from non-petroleum sources. Therefore, the production of these products aims to increase its viability progressively. The supply chain (SC) approach enables the evaluation of the structures used to produce these types of bioenergy. Consequently, the identification of tools to represent the production stages of the SC and their articulation with the objective functions, as well as the strategies and solution software implemented in the design of SC for bioenergy products are presented throughout this bibliographic analysis. Based on systematic and narrative literature analysis, current trends and future research issues are performed. The bibliographic analysis has evidenced that the production of bioenergy is a research topic that has evolved in the last decades. Strategic decisions such as factory capacity and the location of production facilities are the most frequently used decision variables in the design of bioenergy SC. Similarly, it was found that the bioenergy SC designs have focused on the implementation of several feedstocks simultaneously. Finally, due to these evaluation and design trends, the bioenergy SC designs that include environmental and social objectives aimed at sustainability are a future relevant research issue. Full article

Optimizing multi-factory remanufacturing systems with social welfare considerations presents critical challenges in task allocation and process coordination. This study addresses this gap by proposing a hybrid disassembly line balancing and multi-factory remanufacturing process optimization problem, considering workers with government benefits. A mixed-integer programming model is formulated to maximize profit, and its correctness is verified using the CPLEX solver. Furthermore, a discrete zebra optimization algorithm is proposed to solve the model, integrating a survival-of-the-fittest strategy to improve its optimization capabilities. The effectiveness and convergence of the algorithm are demonstrated through experiments on disassembly cases, with comparisons made to six peer algorithms and CPLEX. The experimental results highlight the importance of this research in improving resource utilization efficiency, reducing environmental impacts, and promoting sustainable development. Full article

Achieving the transformation from “growth at the expense of the environment” to “growth through environmental protection” is an essential path for developing countries to promote sustainable economic and social development. This paper utilizes the staggered difference-in-differences model to empirically test the impact of the “Green Factory” policy under China’s green manufacturing system on corporate sustainable development performance in a large sample of Chinese A-share listed companies from 2010 to 2023. The findings show that the level of corporate sustainable development performance significantly improves after being certified as a “Green Factory”. After a series of robustness tests such as the parallel trend test, placebo test, and heterogeneous treatment effects test, the promoting effect remains significant. This association is stronger among non-state-owned enterprises, enterprises in high-polluting industries, as well as enterprises with higher environmental information transparency. The mechanism tests reveal that participating in the “Green Factory” project enhance corporate sustainable development performance by attracting more green investors and promoting corporate green innovation. Overall, this paper provides micro-level empirical evidence for the driving factors of corporate sustainable development and offers policy evaluation and practical insights for the implementation of green manufacturing system and voluntary environmental regulation policies. Full article

As the effects of the global ecological and environmental crisis continue to escalate, nations around the world are compelled to explore new economic development models aimed at mitigating environmental damage. As an important driving force for economic development, green innovation; digital transformation; and environmental, social, and corporate governance (ESG) have become inevitable choices for pursuing sustainable development in business. Taking Chinese high-tech enterprises as the research object, this study draws on resource-based theory, innovation economics theory, stakeholder theory, and internal organization theory to verify the feasibility of green innovation and digital transformation for enterprises to achieve their goals in high-quality development. Implementing correlation analysis, factorial decomposition, and multiple regression techniques and other methods, hypothesis testing was conducted on the premise of limited questionnaire samples to explore the impact of green innovation and digital transformation on the high-quality development of enterprises and the intermediary effect of ESG management between green innovation, digital transformation, and the high-quality development of enterprises. The results show that green innovation and digital transformation play a crucial role in enhancing the quality of enterprise development; ESG management acts as a partial intermediary in the relationship between green innovation and the high-quality development of enterprises. ESG management serves as a partial intermediary between digital transformation and high-quality development of enterprises. Using the bootstrap method for a robustness test, the conclusion of ESG management mediation is still valid. Based on observation and data, this study provides concrete evidence that ESG management promotes the high-quality development of enterprises and provides practical references for enterprises to form a sustainable development model and government departments to improve ESG management. Full article

The increasing complexity of sustainable development amid financial market regulations has increased the importance of high-quality datasets. However, there is a lack of an integrated approach combining green-finance metrics with the requisite data optimization. This study presents an integrated approach combining green-finance metrics with data optimization. The study uses factorial design methodologies on a sample of 30 firms listed on the Saudi Stock Exchange. Data over five years (2018–2022) were analyzed, focusing on key financial metrics, ESG (environmental, social, and governmental) scores, and sustainability factors. Data analysis used machine-learning models including random forest and XGBoost, Principal Component Analysis (PCA), and regression techniques to evaluate prediction accuracy. The findings revealed that extending the data history from 1–2 to 3–5 years reduced the mean squared error (MSE) by up to 40%, with the XGBoost model achieving an MSE of 0.03 and demonstrating better generalization. In contrast, random forest showed a near-perfect fit with an MSE of 0.00 but risked overfitting. The sampling frequency also affected the accuracy, with weekly and monthly sampling outperforming daily intervals, resulting in an MSE improvement of 15–20%. This study provides a framework for integrating ESG metrics into economic models, aiding policymakers and industry leaders in making informed decisions. The promising results of this study also open avenues for future research and development in sustainable finance and data analysis, offering hope for further progress and innovation. Full article

Our study investigates the relevance and application of key performance indicators (KPIs) and key risk indicators (KRIs) in business management from 1992 to 2023 through a comprehensive bibliometric analysis performed in RStudio using the Bibliometrix platform and in VOSviewer. Utilizing data from the Web of Science database, we identify trends, key themes, and influential research in this domain, observing an annual growth rate of 17.76%. Our analyses include the top 10 most globally cited documents, word clouds based on authors’ keywords and Keywords Plus, clustering by coupling, co-occurrence networks, and factorial analysis. Our findings reveal a significant increase in research interest post-2004, with sustainability and corporate social responsibility emerging as central themes. We confirm positive correlations between KPIs, improved organizational performance, and effective risk management via KRIs. This research underscores the importance of international collaboration and diverse thematic exploration in advancing the field. Full article

Programmable Logic Controllers (PLCs) are indispensable for current and future industrial development, especially in smart factories, smart home technology, automated production lines, and machinery manufacturing. This study presents the trends in PLC software and hardware development through a technology roadmap and offers relevant suggestions to help industries achieve sustainable development, enhance market competitiveness, and provide references for research. Through expert interviews and fuzzy Delphi analysis, this study points out that future PLC development needs to focus on editing interfaces, syntax, Central Processing Units, Memory Units, and Communication Modules. Specific recommendations include visualizing regional/global label settings and connection settings, adding Python, JAVA, LabVIEW, and Scratch syntax, improving instruction execution speed, expanding program and expansion capacities, and adopting dual-channel Ethernet and connections to external networks and wireless networks. Fuzzy hierarchical analysis shows that Communication Modules are the most important component, followed by Central Processing Units and syntax expansion, and, finally, program and expansion capacity enhancements. These suggestions aim to promote product innovation and social environment demand evaluation, enhance product competitiveness, and achieve sustainable development goals. Full article

Within a lean context, the aim is to eliminate all forms of waste, including environmental waste, to improve productivity and reduce costs. Key to achieving this objective are operational performance and sustainability indicators. Lean companies must prioritize both operational performance and sustainability, remaining cognizant of their current status. With this in mind, the authors sought to ascertain whether lean companies demonstrate enhanced sustainability. Thus, the authors raised the following research question: does a lean company exhibit greater sustainability? However, these indicators have traditionally been measured independently, and few studies have indicated the need for a global indicator that could simultaneously address both. Such a global indicator would enable a clearer assessment and understanding of the trade-offs between operational performance and sustainability. This paper introduces such an integrated indicator, aiming to measure companies’ lean–green compliance by intertwining sustainability issues with overall equipment effectiveness (OEE). The authors have termed this indicator business overall performance and sustainability effectiveness (BOPSE). Its primary goal is to evaluate business effectiveness by considering both operational performance and sustainability compliance. The sustainability strand was drawn from, adapted, and simplified based on the Global Reporting Initiative (GRI). This development was framed in a lean–green environment, emphasizing continuous efforts to identify and reduce all sources of lean waste, alongside the waste prevention perspectives of cleaner production, environmental compliance, and social responsibility, which play crucial roles in shaping the factories of the future. This paper presents the background and development of the BOPSE model. To answer the research question, two research methods were undertaken: a survey and case studies. The model was applied in three distinct case studies, demonstrating its usefulness in discerning varying levels of lean–green compliance through this integrated indicator. Full article

The global energy crisis, which began in 2021 due to the extraordinary economic recovery after the pandemic and intensified after Russia’s invasion of Ukraine in February 2022, has changed the conditions of energy management, paying more attention to energy efficiency. Natural gas prices have reached record levels and, consequently, so have electricity prices in some markets. Oil prices have reached their highest level since 2008. Higher energy prices have contributed to sharply increased inflation. Households are again becoming interested in buying coal as a source of heat. High energy and gas prices have pushed many families into poverty and forced some factories to cut production or even close. They have also slowed economic growth to the point where some countries are heading for a serious recession. Paradoxically, the negative effects of the energy crisis may accelerate the introduction of cleaner, sustainable, renewable energy such as wind and solar energy. The energy crisis is comparable to the oil crisis of the 1970s, when it contributed to significant advances in energy efficiency. The current crisis has highlighted the importance of investments in renewable energy resources and initiated the process of integrating regional markets, developing energy efficiency and promoting renewable energies. The aim of this article is to comprehensively explore the complex relationship between energy awareness, consumption patterns, and energy efficiency, with a focus on both individual consumers and industries, during the global energy crisis. This paper is based on a literature review, overarching policy documents, energy reports, and other secondary documents. The primary research method was the systematic literature review method, based on which the impact of the global energy crisis on energy efficiency was evaluated. This study emphasizes the diverse influences on energy awareness, ranging from economic factors to consumer preferences and environmental consciousness. The findings of the paper underscore the significant responsibility of industries in contributing to energy-saving efforts and the active role of consumers in the energy market. The responsibility of industries in contributing to energy efficiency is highlighted, with a call for a comprehensive approach that integrates energy-saving criteria into product development and corporate social responsibility. Full article

The aim of this research is, on the one hand, to develop a scale that can be used for assessing attitudes towards retirement as a prevention and intervention tool for improving the life of people in retirement, thereby enhancing a sustainable world that offers quality of life, as well as personal, social, and community well-being, and the efficient use of available materials and socio-sanitary resources. On the other hand, the aim of this research is to analyze the psychometric properties of such a scale, i.e., the reliability and validity of a sample of people at an age that is close to retirement age. Hence, the factorial validity was tested using the confirmatory factor analysis (CFA) technique, and the criterion validity was tested by considering general self-efficacy, self-regulation, state of irritation, and certain dimensions of health and personality. The obtained results confirmed the existence of four factors in the scale of attitudes towards retirement as follows: (i) leisure, (ii) economy, (iii) status, and (iv) health. The obtained correlations showed that attitudes towards retirement are positively linked to variables such as self-esteem and self-regulation, whereas significant and negative correlations related to irritation and fatigue were found. Hence, according to the obtained results, the proposed scale is an easy and relevant tool for working on a better and more profitable psychological adaptation to retirement from work. Thus, a society where tools of psychological evaluation, such as the Attitudes toward Retirement Scale (ARS) proposed in this study, are utilized allows for the detection of problems among people facing retirement, which will lead to a more sustainable and evolved society that provides quality of life as well as personal, social, and community well-being. Full article

The study presents the design and validation of a Physical Education for Sustainable Development (PESD) instrument. This consists of a 25-item quantitative instrument that assesses the teaching interventions of physical education teachers. A total of 358 physical education teachers completed the questionnaire. The instrument uses an 8-point Likert scale. For the validation of the instrument, content validation, factorial validation, reliability through Cronbach’s alpha, and stability through test–retest were considered. The results show that the PESD is a two-factor instrument with very high reliability (0.95). In addition, positive results were found for the temporal stability of the scale. The principal component factor analysis results show that the scale consists of two factors: (1) environmental, health, and economic sustainability; and (2) social sustainability, gender, and inclusion. This questionnaire is the first valid and reliable tool to measure the ability of physical education teachers to promote attitudes that favour sustainable actions. Full article

Advances towards smart ecosystems showcase Internet of Things (IoT) as a transversal strategy to improve energy efficiency in buildings, enhance their comfort and environmental conditions, and increase knowledge about building behavior, its relationships with users and the interconnections among themselves and the environmental and ecological context. EU estimates that 75% of the building stock is inefficient and more than 40 years old. Although many buildings have some type of system for regulating the indoor temperature, only a small subset provides integrated heating, ventilation, and air conditioning (HVAC) systems. Within that subset, only a small percentage includes smart sensors, and only a slight portion of that percentage integrates those sensors into IoT ecosystems. This work pursues two objectives. The first is to understand the built environment as a set of interconnected systems constituting a complex framework in which IoT ecosystems are key enabling technologies for improving energy efficiency and indoor air quality (IAQ) by filling the gap between theoretical simulations and real measurements. The second is to understand IoT ecosystems as cost-effective solutions for acquiring data through connected sensors, analyzing information in real time, and building knowledge to make data-driven decisions. The dataset is publicly available for third-party use to assist the scientific community in its research studies. This paper details the functional scheme of the IoT ecosystem following a three-level methodology for (1) identifying buildings (with regard to their use patterns, thermal variation, geographical orientation, etc.) to analyze their performance; (2) selecting representative spaces (according to their location, orientation, use, size, occupancy, etc.) to monitor their behavior; and (3) deploying and configuring an infrastructure with +200 geolocated wireless sensors in +100 representative spaces, collecting a dataset of +10,000 measurements every hour. The results obtained through real installations with IoT as a learning factory include several learned lessons about building complexity, energy consumption, costs, savings, IAQ and health improvement. A proof of concept of building performance prediction based on neural networks (applied to CO₂ and temperature) is proposed. This first learning shows that IAQ measurements meet recommended levels around 90% of the time and that an IoT-managed HVAC system can achieve energy-consumption savings of between 10 and 15%. In summary, in a real context involving economic restrictions, complexity, high energy costs, social vulnerability, and climate change, IoT-based strategies, as proposed in this work, offer a modular and interoperable approach, moving towards smart communities (buildings, cities, regions, etc.) by improving energy efficiency and environmental quality (indoor and outdoor) at low cost, with quick implementation, and low impact on users. Great challenges remain for growth and interconnection in IoT use, especially challenges posed by climate change and sustainability. Full article

This study develops a factorial Bayesian least-squares support vector machine-based energy–water–environment nexus system optimization (i.e., FBL–EWEO) model. FBL–EWEO can provide dependable predictions for electricity demand, quantify the interactions among different factors, and present optimal system planning strategies. The application to Fujian Province is driven by three global climate models (i.e., GCMs) under two SSPs, as well as two levels of economic and social factors’ growth rates. Results revealed in the planning horizon: (1) Fujian would encounter rainy and warming trends (e.g., [2.17645, 4.51247] mm/year of precipitation and [0.0072, 0.0073] °C/year of mean temperature); (2) economic, social, and climatic factors contribute 62.30%, 35.50%, and 1.47% to electricity demand variations; (3) electricity demand would grow with time (increase by [64.21, 74.79]%); (4) the ratio of new energy power would rise to [70.84, 73.53]%; (5) authorities should focus on photovoltaic and wind power plants construction (their proportions increase from [0.81, 1.83]% to [9.14, 9.56]%, [1.33, 4.16]% to [11.44, 15.58]%, respectively); and (6) air pollutants/CO₂ emissions would averagely decline [51.97, 53.90]%, and water consumption would decrease [41.77%, 42.25]%. Findings provide technical support to sustainable development. Full article