Search Results (91)

The construction sector significantly contributes to global environmental degradation through intensive resource extraction, high energy consumption, and substantial waste generation. Addressing this unsustainable trajectory requires integrated approaches that simultaneously improve operational efficiency and material circularity. Lean Construction (LC) and Circular Economy (CE) offer complementary frameworks for enhancing process performance and reducing environmental impacts. However, their combined implementation remains underdeveloped and fragmented. This study conducts a systematic literature review (SLR) of 18 peer-reviewed articles published between 2010 and 2025, selected using PRISMA 2020 guidelines and sourced from Scopus and Web of Science databases. A mixed-method approach combines bibliometric mapping and qualitative content analysis to investigate how LC and CE are jointly operationalized in construction contexts. The findings reveal that LC improves cost, time, and workflow reliability, while CE enables reuse, modularity, and lifecycle extension. Integration is further supported by digital tools—such as Building Information Modelling (BIM), Design for Manufacture and Assembly (DfMA), and digital twins—which enhance traceability and flow optimization. Nonetheless, persistent barriers—including supply chain fragmentation, lack of standards, and regulatory gaps—continue to constrain widespread adoption. This review identifies six strategic enablers for LC-CE integration: crossdisciplinary competencies, collaborative governance, interoperable digital systems, standardized indicators, incentive-based regulation, and pilot demonstrator projects. By consolidating fragmented evidence, the study provides a structured research agenda and practical insights to guide the transition toward more circular, efficient, and sustainable construction practices. Full article

Artificial intelligence (AI)-powered mental health chatbots have evolved quickly as scalable means for psychological support, bringing novel solutions through natural language processing (NLP), mobile accessibility, and generative AI. This systematic literature review (SLR), following PRISMA 2020 guidelines, collates evidence from 25 published, peer-reviewed studies between 2020 and 2025 and reviews therapeutic techniques, cultural adaptation, technical design, system assessment, and ethics. Studies were extracted from seven academic databases, screened against specific inclusion criteria, and thematically analyzed. Cognitive behavioral therapy (CBT) was the most common therapeutic model, featured in 15 systems, frequently being used jointly with journaling, mindfulness, and behavioral activation, followed by emotion-based approaches, which were featured in seven systems. Innovative techniques like GPT-based emotional processing, multimodal interaction (e.g., AR/VR), and LSTM-SVM classification models (greater than 94% accuracy) showed increased conversation flexibility but missed long-term clinical validation. Cultural adaptability was varied, and effective localization was seen in systems like XiaoE, okBot, and Luda Lee, while Western-oriented systems had restricted contextual adaptability. Accessibility and inclusivity are still major challenges, especially within low-resource settings, since digital literacy, support for multiple languages, and infrastructure deficits are still challenges. Ethical aspects—data privacy, explainability, and crisis plans—were under-evidenced for most deployments. This review is different from previous ones since it focuses on cultural adaptability, ethics, and hybrid public health incorporation and proposes a comprehensive approach for deploying AI mental health chatbots safely, effectively, and inclusively. Central to this review, symmetry is emphasized as a fundamental idea incorporated into frameworks for cultural adaptation, decision-making processes, and therapeutic structures. In particular, symmetry ensures equal cultural responsiveness, balanced user–chatbot interactions, and ethically aligned AI systems, all of which enhance the efficacy and dependability of mental health services. Recognizing these benefits, the review further underscores the necessity for more rigorous academic research into the development, deployment, and evaluation of mental health chatbots and apps, particularly to address cultural sensitivity, ethical accountability, and long-term clinical outcomes. Full article

In the shift toward sustainable and resource-efficient manufacturing, Artificial Intelligence (AI) is playing a transformative role in overcoming the limitations of traditional production scheduling methods. This study, based on a Systematic Literature Review (SLR), explores how AI techniques enhance Advanced Planning and Scheduling (APS) systems, particularly under finite-capacity constraints. Traditional scheduling models often overlook real-time resource limitations, leading to inefficiencies in complex and dynamic production environments. AI, with its capabilities in data fusion, pattern recognition, and adaptive learning, enables the development of intelligent, flexible scheduling solutions. The integration of metaheuristic algorithms—especially Ant Colony Optimization (ACO) and hybrid models like GA-ACO—further improves optimization performance by offering high-quality, near-optimal solutions without requiring extensive structural modeling. These AI-powered APS systems enhance scheduling accuracy, reduce lead times, improve resource utilization, and enable the proactive identification of production bottlenecks. Especially relevant in high-variability sectors like fashion, these approaches support Industry 5.0 goals by enabling agile, sustainable, and human-centered manufacturing systems. The findings have been highlighted in a structured framework for AI-based APS systems supported by metaheuristics that compares the Industry 4.0 and Industry 5.0 perspectives. The study offers valuable implications for both academia and industry: academics can gain a synthesized understanding of emerging trends, while practitioners are provided with actionable insights for deploying intelligent planning systems that align with sustainability goals and operational efficiency in modern supply chains. Full article

The integration of lithium-ion (Li-ion) battery energy storage systems (LiBESSs) with photovoltaic (PV) generation offers a promising solution for powering auxiliary services (ASs) in high-voltage power stations. This study conducts a systematic literature review (SLR) to evaluate the feasibility, benefits, and challenges of this integration. The proposed SLR complies with the PRISMA 2020 statement, and it is also registered on the international PROSPERO platform (ID 1073599). The selected methodology includes the following key steps: definition of the research questions; search strategy development; selection criteria of the studies; quality assessment; data extraction and synthesis; and discussion of the results. Through a comprehensive analysis of scientific publications from 2013 to 2024, trends, advancements, and research gaps are identified. The methodology follows a structured review framework, including data collection, selection criteria, and evaluation of technical feasibility. From 803 identified studies, 107 were eligible in accordance with the assessed inclusion criteria. Then, a custom study impact factor (SIF) framework selected 5 out of 107 studies as the most representative and assertive ones on the topics of this SLR. The findings indicate that Li-ion BESSs combined with PV systems enhance reliability, reduce reliance on conventional sources, and improve grid resilience, particularly in remote or constrained environments. The group of reviewed studies discuss optimization models and multi-objective strategies for system sizing and operation, along with practical case studies validating their effectiveness. Despite these advantages, challenges related to cost, regulatory frameworks, and performance variability remain. The study concludes that further experimental validations, pilot-scale implementations, and assessment of long-term economic impacts are necessary to accelerate the adoption of BESS-PV systems in high-voltage power substations. This study was funded by the R&D program of the Brazilian National Electric Energy Agency (ANEEL) via project number PD-07351-0001/2022. Full article

Gender equity is one of the most complex contemporary challenges, encompassing political, economic, labor, and cultural dimensions. This study aims to analyze the impact of public policies, labor practices, and social movements in promoting gender equity across various socio-political contexts. To answer the central question of how these elements influence a reduction in gender inequalities, a Systematic Literature Review (SLR) was conducted, complemented by a Bibliometric Analysis, following PRISMA protocol guidelines. The bibliographic search, carried out in the Scopus database, covered the period from 2015 to 2025 and identified 26 relevant studies that met the predefined inclusion criteria. The results reveal that, despite progress in formulating policies aimed at combating gender-based violence and promoting equality, the implementation of these measures is hindered by a lack of inter-institutional coordination and the persistence of deeply rooted cultural norms. Likewise, structural inequalities in the labor sphere are evident, such as the gender wage gap and barriers to professional advancement. On the other hand, social movements have emerged as key actors—including governmental institutions, civil society organizations, and healthcare providers—in highlighting and transforming these disparities by driving changes in political agendas and increasing women’s representation in decision-making positions. In summary, this study underscores the need to adopt intersectional and comprehensive approaches to achieve effective and sustainable gender equity, while comparing the influence of policies across different global regions. Full article

The documentation of cultural heritage, particularly built heritage, represents a critical component in ensuring its preservation, sustainable management, and effective transmission to future generations. As the field increasingly undergoes a digital transformation, there is a growing need for structured, standardised approaches that can guide professionals and stakeholders through the complexities of documentation practices. Despite the availability of numerous standards and charters, a clear synthesis of consolidated methodologies and recent technological shifts remains limited. This study addresses this gap by conducting a Systematic Literature Review (SLR) to assess current documentation practices. The research is part of a larger initiative funded by the FSE REACT-EU programme under the Italian PON Ricerca e Innovazione 2014–2020, specifically aiming to support public and private stakeholders in developing practical documentation strategies. Using the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) framework, over 266 publications were analysed to reconstruct the state of the art. The findings confirm widely adopted practices among research groups while also highlighting emerging trends driven by technological advancements in geomatics. These insights will contribute to the formulation of practical guidelines to support operators in the field and reinforce the integration of innovative tools in Cultural Heritage documentation workflows. Full article

Digital transformation is the process of using digital technologies for creating or modifying existing business processes and customer experience, leveraging cutting-edge technology to meet changing market needs. Disruptions like the COVID-19 pandemic, regional wars, and climate-driven natural disasters create consequential scenarios, e.g., global supply chain disruption creating further demand–supply mismatch for healthcare enterprises. According to KPMG’s 2021 Healthcare CEO Future Pulse, 97% of healthcare leaders reported that COVID-19 significantly accelerated the digital transformation agenda. Successful digital transformation initiatives, for example, digital twins for supply chains, augmented reality, the IoT, and cybersecurity technology initiatives implemented significantly enhanced resiliency in supply chain and manufacturing operations. However, according to another study conducted by Mckinsey & Company, 70% of digital transformation efforts for healthcare enterprises fail to meet their goals. Healthcare enterprises face unique challenges, such as complex regulatory environments, cultural resistance, workforce IT skills, and the need for data interoperability, which make digital transformation a challenging project. Therefore, this study explored potential barriers, enablers, disruption scenarios, and digital transformation use cases for healthcare enterprises. A structured literature review (SLR), followed by thematic content analysis, was conducted to inform the research objectives. A sample of sixty (n = 60) peer-reviewed journal articles were analyzed using research screening criteria and keywords aligned with research objectives. The key themes for digital transformation use cases identified in this study included information processing capability, workforce enablement, operational efficiency, and supply chain resilience. Collaborative leadership as a change agent, collaboration between information technology (IT) and operational technology (OT), and effective change management were identified as the key enablers for digital transformation of healthcare enterprises. This study will inform digital transformation leaders, researchers, and healthcare enterprises in the development of enterprise-level proactive strategies, business use cases, and roadmaps for digital transformation. Full article

This paper offers a systematic literature review of age-related disparities in the adoption of digital payment systems, a phenomenon that is becoming increasingly relevant as financial transactions become predominantly digital. Using the SPAR-4-SLR protocol, 66 scholarly contributions published between 2014 and 2024 are examined and categorised into four thematic clusters: demographic determinants, behavioural drivers, structural barriers linked to the grey digital divide, and emerging insights from neurofinance. The review highlights a multifactorial set of barriers that limit older adults’ engagement with digital payments, including usability challenges, cognitive and physical limitations, digital skill gaps, and perceived security risks. These obstacles are further amplified by structural inequalities such as socio-economic status, geographic location, and infrastructural constraints. While digital payments are often presented as tools of inclusion, the findings underscore the risk of exclusion for ageing populations without tailored design and policy interventions. The review also identifies areas for further research, particularly at the intersection of ageing, cognitive function, and human–technology interaction, proposing a research agenda that supports more inclusive and age-responsive financial innovation. Full article

As cyberattacks continue to rise alongside the rapid expansion of digital systems, effective threat detection remains a critical yet challenging task. While several machine learning approaches have been proposed, the use of graph neural networks (GNNs) for cyberattack detection has not yet been systematically explored in depth. This paper presents a systematic literature review (SLR) that analyzes 28 recent academic studies published between 2020 and 2025, retrieved from major databases including IEEE, ACM, Scopus, and Springer. The review focuses on evaluating how GNN models are applied in detecting various types of attacks, particularly those targeting IoT environments, web services, phishing, and network traffic. Studies were classified based on the type of dataset, GNN model architecture, and attack domain. Additionally, key limitations and future research directions were extracted and analyzed. The findings provide a structured comparison of current methodologies and highlight gaps that warrant further exploration. This review contributes a focused perspective on the potential of GNNs in cybersecurity and offers insights to guide future developments in the field. Full article

Waste classification is a critical step in waste management that is time-consuming and necessitates automation to replace traditional approaches. Recently, machine learning (ML) and deep learning (DL) have gained attention from researchers seeking to automate waste classification by providing alternative computational techniques to address various waste-related challenges. Significant research on waste classification has emerged in recent years, reflecting the growing focus on this domain. This systematic literature review (SLR) explores the role of artificial intelligence (AI), particularly machine learning (ML) and deep learning (DL), in automating waste classification. Using Kitchenham’s and PRISMA guidelines, we analyze over 97 studies, categorizing AI-based techniques into ML-based, DL-based, and hybrid models. We further present an in-depth review of over fifteen publicly available waste classification datasets, highlighting key limitations such as dataset imbalance, real-world variability, and standardization issues. Our analysis reveals that deep learning and hybrid approaches dominate the current research landscape, with CNN-based architecture and transfer learning techniques showing particularly promising results. To guide future advancements, this study also proposes a structured roadmap that organizes challenges and opportunities into short-, mid-, and long-term priorities. The roadmap integrates insights on model accuracy, system efficiency, and sustainability goals to support the practical deployment of AI-powered waste classification systems. This work provides researchers with a comprehensive understanding of the state-of-the-art in ML and DL for waste classification and offers insights into areas that remain unexplored. Full article

High-risk industries like mining must address occupational safety to reduce accidents and fatalities. Training through role-playing, simulations, and Serious Games (SGs) can reduce occupational risks. This study aims to conduct a systematic literature review (SLR) on SG methodologies for the mining sector. This review was based on a methodology inspired by the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. Three research questions were formulated to explore how SGs contribute to immediate feedback, brain stimulation, and training for high-risk scenarios. The review initially identified 1987 studies, which were reduced to 30 relevant publications following a three-phase process: (1) A search string based on three research questions was defined and applied to databases. (2) Publications were filtered by title and abstract. (3) A full-text reading was conducted to select relevant publications. The SLR showed SG development methodologies with structured processes that are adaptable to any case study. Additionally, it was found that Virtual Reality, despite its implementation costs, is the most used technology for safety training, inspection, and operation of heavy machinery. The first conclusion of this SLR indicates the lack of methodologies for the development of SG for training in the mining field, and the relevance of carrying out specific methodological studies in this field. Additionally, the main findings obtained from this SLR are the following: (1) Modeling languages (e.g., GML and UML) and metamodeling are important in SG development. (2) SG is a significant mechanism for cooperative and participative learning strategies. (3) Virtual Reality technology is widely used in safe virtual environments for mining training. (4) There is a need for methodologies that integrate the specification of cognitive functions with the affective part of the users for SGs suitable for learning environments. Finally, this review highlights critical gaps in current research and underscores the need for more integrative approaches to SG development. Full article

The rise of Construction 4.0—driven by digitalisation, automation, and data-intensive technologies—is radically reshaping the construction industry. While its technological innovations are widely acknowledged, their implications for industrial relations remain underexplored. In this study, we conduct a systematic literature review (SLR) of 91 peer-reviewed articles published between 2010 and 2024, aiming to synthesise emerging knowledge on how Construction 4.0 is transforming workforce dynamics, employment models, and labour relations. Using NVivo software and an inductive thematic approach, we identify seven key themes: workforce transformation, the attraction of new generations and women, skill requirements and workforce development, supply chain and logistics optimisation, digital twin technology in project management, the emergence of new business models, and safety and risk assessment. Our findings highlight both opportunities—such as improved collaboration, skill diversification, and enhanced productivity—and challenges, including job displacement, digital ethics, and widening disparities between developed and developing countries. Recent studies from 2023 and 2024 underscore routine-biased changes in workforce structure, evolving project management practices through digital twins, and critical skill shortages within the sector. Furthermore, contemporary policy shifts and increasing labour tensions in some regions reveal deeper socio-economic implications of digital construction. This review contributes to a more holistic understanding of how technological innovation intersects with social systems in the built environment. The insights presented offer valuable guidance for policymakers, educators, and industry leaders seeking to navigate the evolving landscape of Construction 4.0. Full article

The transformative function of data-driven leadership in higher education institutions (HEIs) is becoming crucial for advancing sustainable development. By integrating data-driven decision-making with Sustainable Development Goals (SDGs), particularly SDG4 (quality education) and SDG10 (reduced inequalities), EIs can improve the efficacy, inclusivity, and employability of their graduates. To examine this influence, this study implements a systematic literature review (SLR) that adheres to the PRISMA standards and integrates empirical and theoretical insights regarding data-driven leadership in HEI governance, teaching, and learning strategies. The results indicate that combining data analytics into decision-making processes improves institutional efficacy, aligns curricula with the market demands, strengthens student outcomes, and cultivates an inclusive and sustainable academic environment. Moreover, this study introduces a conceptual model connecting sustainable development and data-driven decision-making, offering a structured framework for HEIs to navigate digital transformation responsibly. In addition, this model also emphasizes the importance of balancing technology, ethics, and human-centric leadership in developing educational institutions that are prepared for the future. Ultimately, these insights provide practical advice for academic leaders and policymakers aligning HEI strategies with global sustainability objectives. By advocating for innovative, inclusive, and data-driven leadership, HEIs can promote long-term societal transformation and higher education excellence. Full article

Electric mobility has been widely discussed as a viable solution for decarbonizing the transport sector and promoting urban sustainability. However, the integration of electric mobility into urban planning still requires further in-depth research. This article aims to identify the key attributes linking electric mobility with urban planning through a Systematic Literature Review (SLR) and to provide an overview of the Brazilian context regarding policies and guidelines for electromobility. The findings indicate that the primary attributes connecting electric mobility to urban planning include the alignment of existing plans and guidelines, sectoral integration, transport infrastructure, multi-sectoral engagement, environmental sustainability, urbanism, user profiles, technologies, and governance. In Brazil, despite the existence of national guidelines, there is still a gap in updating public policies to fully integrate electromobility into urban planning. The study concludes that a stronger integration between electric mobility and urban planning policies is necessary, along with more robust incentives for the electrification of public transport. By identifying these attributes, this study provides a structured framework for policymakers and urban planners to enhance regulatory mechanisms, infrastructure planning, and governance strategies, contributing to more sustainable, resilient, and efficient urban mobility systems. Full article

Buildings account for a significant share of global energy consumption and carbon emissions, making deep renovations essential for climate mitigation. Renovation passports (RPs) are an emerging concept still in the early stages of development, designed to provide structured step-by-step renovation roadmaps that prevent lock-in effects and optimise energy performance over time. However, their large-scale adoption in the European Union (EU) remains limited due to technical, financial, behavioural, and policy challenges. This study conducts a Systematic Literature Review (SLR) to identify key strategies for the successful development and large-scale implementation of RPs in EU. A total of 217 research articles from Scopus and ScienceDirect, along with 99 EU policy documents and 16 Building Performance Institute Europe (BPIE) reports, were analysed to assess the technical, financial, behavioural, and policy dimensions of RP adoption. Our findings highlight the role of digital tools like Building Information Modelling (BIM), digital building logbooks (DBLs), and one-stop shops (OSSs) in improving RP usability and accessibility. Financial barriers, such as high upfront costs and fragmented funding, require harmonised incentives, green loans, and energy performance contracting. Behavioural factors, including homeowner awareness, trust in renovation services, and decision-making complexity, also influence RP adoption. This study underscores the need for stronger policy integration between RPs and energy performance certificates (EPCs), improved financial instruments, and enhanced stakeholder engagement. By addressing these gaps, this research provides actionable recommendations for policymakers and stakeholders to accelerate the adoption of RPs and contribute to the EU’s Renovation Wave strategy and broader climate neutrality objectives. Full article