Search Results (118)

Background: Sustainable supply chain development is a global priority driven by resource depletion, socio-economic challenges, and environmental concerns. Existing biofuel supply chain studies, however, often focus on isolated upstream or downstream processes and inadequately address multi-stakeholder engagement. Achieving sustainability requires coordinated participation of stakeholders across multiple decision levels, from individuals to society. This study proposes a collaborative framework to support sustainable biofuel development. Methodology: The framework comprises three steps: (i) current-state analysis through stakeholder identification, power–interest mapping, and engagement assessment; (ii) definition of a desired future state; and (iii) development of transition strategies integrating bottom-up and top-down approaches. The framework is applied to a biofuel case study in Ethiopia. Results: Twenty-four stakeholders were identified across nano, micro, meso, and macro levels. Power–interest and engagement analyses revealed key decision-makers and categorized stakeholders as aligned, passive, or militant. The results show that transitioning stakeholders toward active collaboration requires integrated strategies, including capability development, policy alignment, knowledge sharing, and technological advancement. These interventions support coordinated decision-making, improved resource management, and sustainability outcomes such as job creation, energy security, and greenhouse gas reduction. Conclusion: The proposed multi-level interaction framework effectively aligns stakeholders by integrating bottom-up and top-down strategies. It provides a systematic approach to guiding collaborative transitions toward sustainable development. Full article

Background: Artificial intelligence (AI) is transforming medical practice, enhancing diagnostic accuracy, personalisation, and clinical efficiency. However, this transition raises complex ethical challenges related to transparency, accountability, fairness, and human oversight. This study examines how the literature conceptualises and distributes ethical responsibility in AI-assisted healthcare. Methods: This semi-systematic, theory-informed thematic review was conducted in accordance with the PRISMA 2020 guidelines. Publications from 2020 to 2025 were retrieved from PubMed, ScienceDirect, IEEE Xplore databases, and MDPI journals. A semi-quantitative keyword-based scoring model was applied to titles and abstracts to determine their relevance. High-relevance studies (n = 187) were analysed using an eight-category ethical framework: transparency and explainability, regulatory challenges, accountability, justice and equity, patient autonomy, beneficence–non-maleficence, data privacy, and the impact on the medical profession. Results: The analysis revealed a fragmented ethical landscape in which technological innovation frequently outperforms regulatory harmonisation and shared accountability structures. Transparency and explainability were the dominant concerns (34.8%). Significant gaps in organisational responsibility, equitable data practices, patient autonomy, and professional redefinition were reported. A multilevel ethical responsibility model was developed, integrating micro (clinical), meso (institutional), and macro (regulatory) dimensions, articulated through both ex ante and ex post perspectives. Conclusions: AI requires governance frameworks that integrate ethical principles, regulatory alignment, and epistemic justice in medicine. This review proposes a multidimensional model that bridges normative ethics and operational governance. Future research should explore empirical, longitudinal, and interdisciplinary approaches to assess the real impact of AI on clinical practice, equity, and trust. Full article

Historic waterfront streets are not only an important component of urban public spaces but also highlight the distinctive features and historical contexts of the city. High-quality streetscape visual perception plays a crucial role in advancing the cultural, social, environmental, and economic sustainability of the urban street space. This study was initiated to construct a multi-dimension and multi-scale comprehensive evaluation framework to assess the visual quality of waterfront streets, taking “Water City” Liaocheng as a typical case. Technical methods of semantic segmentation, sDNA (Spatial Design Network Analysis), GIS (Geographic Information System), and statistical analysis were utilized. Following the extraction and classification of street space elements, a multi-dimensional evaluation index system of natural coordination, artificial comfort, and historical culture for the visual assessment was established. Space syntax was performed on waterfront streets by sDNA to quantify macro-level scale spatial structure and meso-level scale pedestrian accessibility. The results of micro-scale visual perception, meso-scale behavioral walkability, and macro-scale spatial structure, were integrated to construct a multi-scale diagnostic framework for eight classifications. This framework provides a scientific basis to put forwards the refined and sustainable optimization strategies for historic waterfront streets. Full article

Predicting information diffusion in social networks is a fundamental problem in many applications, and one of the primary challenges is to predict the future popularity of information in social networks. However, most existing models fail to simultaneously capture the accurate micro-level user node features, meso-level linear spread features, and predict the macro-level popularity during the information propagation process, which may result in unsatisfactory prediction performance. To address this issue, we propose a new cascade prediction framework CasNS: Node-level and Sequence-level Features for Cascade Prediction. CasNS utilizes node-level features by employing a self-attention mechanism to capture the hidden features of the target node with respect to other nodes. Additionally, it leverages multiple one-dimensional convolutional layers with the dynamic routing algorithm to obtain sequence-level features across different dimensions. Through experiments on a large number of real-world datasets, our model demonstrates superior performance compared with other state-of-the-art methods, thereby validating the feasibility of our approach. Full article

Background: In Canada, 30 percent of the older adult population is foreign-born. Immigrant older adults are more likely to experience significant social isolation due to a variety of factors. However, limited research exists on the influence of specific factors. The objective of this study is to understand the economic factors that contribute to social isolation among older immigrants in the Greater Toronto Area (GTA), Canada. Methods: A qualitative interpretive description method was used. Following research ethics boards’ approval, semi-structured individual interviews were conducted with a total of 47 Arabic, Mandarin, and Punjabi-speaking older immigrants in the GTA. The interviews were conducted in their preferred language, audio-recorded, and translated (when needed) into English and transcribed. Thematic analysis of the data was informed by an ecosystemic framework. Results: Six themes were identified: (1) barriers to finding employment; (2) living a “hand-to-mouth life” due to limited income/pension; (3) housing costs that eliminate choices and options; (4) costs (and availability) of transportation as a barrier to getting around; (5) lack of “essential” healthcare coverage; and (6) costs of community programs that prevent “getting out of the house.” These economic factors at micro, meso, and macro levels of society intersected to create desperate situations that contributed to social isolation among older immigrants in the GTA. Conclusions/Implications: Addressing these economic factors is critical to immigrant older adults’ aging in place. Service providers must advocate for accessible physical and financial resources and services including affordable housing and transportation, old age security, and comprehensive healthcare coverage for older immigrants. Future research should focus on economic challenges faced by older adults across other immigrant communities in the GTA as well as in other cities, provinces, and territories. Full article

Specialized terminals in coastal ports play an increasingly important role in maritime transport. To enhance the resilience of specialized terminals, it is vital to increase their ability to maintain a certain level of function under various emergencies. This effort is fundamental to ensuring the handling efficiency of coastal ports and the stability of the shipping network. In this paper, from the perspective of the coastal port transportation system, we developed a resilience evaluation framework considering micro-level, meso-level, and macro-level influencing factors on specialized terminals. To evaluate the comprehensive resilience of the specialized terminal, we quantitatively calculated each evaluation indicator and proposed an improved Ranking Based on Optimal Points (RBOP) method. The application results were obtained from a study on specialized container terminals at eight hub ports in coastal China. The improved RBOP method takes into account both the current status and future development trends of specialized terminals. As a result, compared with TOPSIS, VIKOR, Multi-MOORA, and WASPAS, the ranking results of the improved RBOP and the latest method (i.e., WASPAS) are the closest, which only differ in the seventh and eighth ranking, while the outcomes of the improved RBOP align more closely with expert expectations. The proposed method enables the resilience evaluation of specialized terminals from a holistic perspective of the coastal port transportation system. This helps port managers identify bottlenecks in the resilience of specialized terminals and can enhance the efficiency and stability of port operations. Full article

Business Economics lacks coherent theoretical foundations despite its prominence in business education. This paper critiques conventional equilibrium-based curricula that begin with ceteris paribus assumptions, proposing instead a systems-based evolutionary framework integrating macro–meso–micro perspectives. Through conceptual analysis, we demonstrate how traditional approaches fail to capture dynamic business realities. Our evolutionary framework incorporates seven pillars: variation–selection–retention dynamics, multi-level integration, dynamic capabilities, institutional networks, complexity theory, organizational form evolution, and behavioral insights. The paper provides curriculum guidelines (12-week structure) that maintain economic literacy while teaching students to reason through feedback loops, uncertainty, and systemic change. This repositioning represents the need for a paradigm shift from static optimization toward understanding businesses as adaptive systems, better preparing students for navigating continuous change in complex environments. Full article

Mountainous traditional villages represent unique socio-ecological systems that have evolved through centuries of adaptation to complex topographies and multi-hazard environments. Understanding their terrain–resilience coupling mechanisms is essential for risk-sensitive planning and heritage preservation in mountainous regions. This study integrates multi-source remote sensing data and GIS spatial analysis to investigate 57 national-level traditional villages in the southern Qinba Mountains, China. Using kernel density estimation (KDE), nearest neighbor index (NNI), and Geodetector modeling, we identify the spatial distribution characteristics and topographic driving forces that shape settlement patterns across macro-meso-micro scales. Results reveal that 83% of the villages are clustered in low-mountain and hilly zones (550–1200 m elevation), preferring slopes below 15° and south-facing aspects. Elevation exerts the strongest influence (q = 0.46), followed by slope (q = 0.32) and aspect (q = 0.29), forming a multi-level adaptation framework of “macro-elevation differentiation, meso-slope constraint, and micro-aspect optimization.” Morphological Spatial Pattern Analysis (MSPA) further indicates that traditional villages achieve ecological balance and disaster avoidance through adaptive spatial strategies such as terrace-based flood prevention, convex-bank stabilization, and platform-based hazard avoidance. These strategies are not merely topographic preferences but natural adaptation mechanisms formed by long-term responses to multi-hazard environments—dynamic adaptation processes that reduce disaster exposure and optimize resource use efficiency through active adjustment of site selection and spatial transformation (the disaster density in the 100m core zone buffer is 0.077 events/km², significantly lower than 0.290 events/km² in peripheral areas). These findings demonstrate that remote sensing techniques can effectively reveal the terrain–resilience coupling of traditional villages, providing quantitative evidence for integrating spatial resilience into cultural landscape conservation, ecological security assessment, and rural revitalization planning. The proposed multi-scale analytical framework offers a transferable approach for evaluating settlement adaptability and resilience in other mountainous cultural heritage regions worldwide. Full article

Within the circular economy, repair is increasingly recognised as a crucial yet underexplored strategy that extends product lifespans and reduces waste. Service design offers approaches to support this transition by addressing technical, social, and systemic dimensions. This review aimed to synthesise how service design contributes to repair practices and identify research gaps. Following PRISMA 2020 guidelines, we systematically searched Scopus and Web of Science, applied inclusion criteria focusing on service design and repair within the circular economy, and conducted multi-step screening and snowballing. From 132 initial records, 73 studies were included (journal articles, conference papers, book chapters). Thematic synthesis identified three areas: micro-level interactions between producers, products, and users (e.g., motivations, trust, communication); meso-level tools, frameworks, and platforms enhancing accessibility and efficiency; and macro-level societal transformation through regulations, standards, and communities. Results highlight service design’s potential to foster systemic change by integrating environmental, social, and economic aspects, while also revealing notable research gaps related to the limited engagement of repairers, policymakers, and cross-level collaboration. Compared to previous studies, this review contributes a novel integrated framework linking micro-, meso-, and macro-level dimensions of repair within the circular economy, offering both conceptual insights and actionable directions for practitioners and policymakers. The study is limited by language constraints and the lack of a formal bias evaluation. All reviewed materials are publicly accessible on OSF. This research was conducted without external financial support. Full article

The rapid proliferation of e-commerce has reshaped the spatial logic and facility typologies of urban logistics. While the literature on logistics facility location selection is extensive, there is limited understanding of how the relative importance of location criteria varies across facility types shaped by e-commerce. This study addresses this gap by analyzing the location criteria of logistics facilities of different sizes using a multi-criteria decision-making (MCDM) approach. Twenty-five criteria, identified through a literature review and feedback from seven experts in the Istanbul e-commerce logistics sector, were analyzed using the Fuzzy Simple Additive Weighting (SAW) method. The relative weights of criteria were calculated for three facility scales, macro-, meso-, and micro-scales, to reveal how location priorities vary across scales. Proximity to main arteries ranks first across all scales (macro: 0.317, meso: 0.431, micro: 0.409). Land rental values are highly prioritized at both the macro- and meso-scale, while population density ranks prominently at the macro- and micro-scale. At the meso-scale, shopping mall proximity gains notable weight, whereas intermediate arteries stand out as a key factor at the micro scale. These findings advance the understanding of scale-sensitive dynamics in urban logistics and provide a framework for more adaptable and sustainable logistics planning. Full article

Background: Systems thinking (ST) is an approach to problem-solving that views systems through a holistic perspective, focusing on the interconnections and relationships between various elements. In healthcare, the World Health Organization’s 2009 report marked a paradigm shift toward ST, prompting the development and use of ST tools to address complex challenges. Despite this, limited attention has been given to ST’s application in healthcare human resource management (HRM). This paper aims to provide a scoping review of ST application in healthcare HRM to explore its value in workforce management. Methods: Following Arksey and O’Malley’s framework, a scoping review was conducted to map how ST has been applied in healthcare HRM. Peer-reviewed articles published between 1999 and December 2024 were identified through Scopus and PubMed, using search terms such as systems thinking, human resources, and workforce. Data were extracted using a structured tool, and findings were analyzed through the lens of the system level of application. Results: The review identified 19 studies from 15 countries, with the majority using qualitative or mixed methods approaches across diverse settings. Core applications were applied at the macro, meso, and micro system levels to address workforce challenges, map feedback loops, identify leverage points, and strengthen stakeholder collaboration. ST was commonly applied at regional and national levels and supported improved workforce planning, policy development, and service coordination. Most studies employed soft systems modeling. Conclusions: This review highlights ST’s potential to enhance HRM by recognizing interdependencies across workforce functions. Findings suggest that ST enables more integrated strategies, promotes collaboration, and supports systemic decision-making. The adoption of ST in healthcare HRM may address persistent workforce challenges, though implementation remains limited by reductionist perspectives and unfamiliarity with ST tools. Full article

Organizational resilience and long-term success have become essential capabilities in turbulent and uncertain environments. This study redefines these concepts by applying a natural language analysis to a corpus of 1597 peer-reviewed publications retrieved from Web of Science and Scopus. The methodology adopts a three-level framework: first, a thematic clustering of literature into strategic domains; second, a semantic comparison of classical and emerging terms; and third, the mapping of artificial intelligence (AI) opportunities. The results identify five overarching domains: Health and Wellbeing; Organizations, HR and Leadership; Strategy, Innovation, and Culture; Education, Knowledge and Communities; and Society, Environment and Development. These domains illustrate how resilience and success are addressed at micro, meso, and macro levels. Semantically, the discourse expands from traditional notions such as robustness, risk management, and performance towards more human-centered, systemic, and digitally enabled perspectives. The study further highlights how AI functions both as a methodological tool and as a strategic enabler, with applications ranging from predictive health analytics and leadership support systems to foresight tools and sustainability monitoring. The findings contribute to organizational resilience theory and offer practitioners actionable pathways to strengthen resilience and competitiveness in the face of volatility, uncertainty, complexity, and ambiguity. Full article

This article develops a conceptual framework of Sustainable Human Resource Management (Sustainable HRM) by integrating three critical dimensions: Green HRM practices, ethical and responsible leadership, and digital resilience in HR systems. Positioned within the United Nations Sustainable Development Goals (SDGs), the study addresses the lack of theoretical integration across the fragmented literature. The framework highlights employee well-being as the central mediating construct linking HRM practices to sustainability outcomes, connecting micro-level engagement, meso-level HR systems and leadership ethics, and macro-level policy and ESG alignment. This explicitly demonstrates the multi-level (micro–meso–macro) nature of the framework. The proposed model advances theory by extending HRM beyond organizational boundaries, offering Sustainable HRM as a boundary-spanning and original perspective that links people management to global sustainability agendas. Using a five-stage conceptual development process including literature synthesis, construct definition, integrative framework building, formulation of conceptual propositions, and the design of a future research agenda—this study explicitly acknowledges its conceptual nature to set appropriate reader expectations and ensures methodological transparency in framework development. The study further contributes (1) to theory by clarifying how Green HRM, ethical leadership, and digital resilience interact through employee well-being to advance sustainability; (2) to practice by providing HR leaders with pathways to embed sustainability into core processes; and (3) to policy by informing regulators on HRM’s role in achieving SDGs. Ultimately, the framework positions HRM as a strategic enabler of sustainable development. Full article

The circular economy (CE) is increasingly central to international business, promoting resource efficiency and mitigating environmental impacts. However, existing literature often examines isolated elements—such as supply chains, innovation, or business models—resulting in a fragmented understanding of circularity within this domain. To address this gap, the present study conducts a systematic literature review of 128 PRISMA-screened articles, employing thematic analysis to identify six prevailing themes. Despite growing interest, the absence of a cohesive framework has led to disjointed inquiries that overlook the systemic complexities of embedding CE in international business. Anchored in the Attention-Based View and synthesized through the Multi-Level Perspective framework, this review reveals critical research gaps. At the micro level, limited attention is given to entrepreneurship, retailer engagement, and the integration of artificial intelligence. At the meso level, studies insufficiently address cross-sector collaboration and localized strategic alliances. At the macro level, consumer-driven circularity remains underexplored. This study proposes an integrative framework to bridge these levels, advancing both theoretical understanding and practical application. By aligning diverse insights, it delineates strategic pathways for institutionalizing CE principles in international business, thereby supporting sustainable development and environmental stewardship. Full article

This integrative review examines the persistent analytical divide in economics by advancing the macro–meso–micro framework as a comprehensive approach for understanding complex socioeconomic ecosystems and sustainability transitions. Drawing on empirical evidence from European energy systems, particularly Greece and the Region of Eastern Macedonia and Thrace, we demonstrate that conventional economic analysis has systematically overlooked the crucial meso-level where evolutionary processes are most visible and transformative. This conceptual “myopia” has led to fragmented policy interventions that work at cross-purposes across different analytical levels. By reconceptualizing economic systems as evolving rule populations operating simultaneously at three distinct but interconnected levels, this view offers diagnostic potential for effective adaptation to sustainability transitions. The framework’s greatest contribution lies in its theoretical thoroughness and, most importantly, in its practical capacity to generate more coherent interventions that harness evolutionary dynamics. Full article