Multidimensional Framework Research Articles

Booming solar energy drives land value enhancement: Evidence from 648 photovoltaic projects in China

Land use of photovoltaic (PV) facilities has always been a pressing research field, as the transition to renewable energy requires balancing between land productivity and energy generation. A comprehensive assessment of PV land use benefits is crucial for informed deployment decisions. Here, we propose a multidimensional land use analysis framework, focusing on power generation, production, ecology, and their co-benefits, aiming to assess the impact of PV applications on land use and to quantify the ensuing changes in land value. The results show that PV deployment significantly increases land values. Specifically, the power generation value of PV land in China ranges from 1.90×105 to 5.09×105CNY/hm2; the production value brought by agricultural development ranges from 6.28×104 to 1.53×105CNY/hm2, and the value of ecosystem services provided by the land ranges from 2.43×104 to 8.95×104CNY/hm2. From a power station type perspective, the development potential for agricultural PV systems in optimizing layout and flexible use is infinite. This system can create tremendous increments in land value. Building desert-based PV plants provides the highest appreciation multiple for arid areas’ land resources while bringing sustainable economic and ecological prosperity. This study contributes to a better understanding of the current impact of PV deployment on land resources, and helps policymakers and stakeholders find intrinsic linkages between energy and the economy, ecology, and the environment, thus guiding and steering a more sustainable development of renewable energy planning and land use optimization in China.

Multidimensional woodchips-like Mn-metal-organic framework for asymmetric supercapacitor devices

Multidimensional manganese-metal organic frameworks (Mn-MOF) are synthesized using 1,2,4,5-Benzene tetracarboxylic acid (BTTC) at various temperatures (100–160°C). The Fourier-transform infrared spectroscopy (FT-IR) and X-ray diffraction (XRD) techniques successfully confirm the formation of Mn-MOF. Among the various temperatures, the Mn-MOF synthesized at 140°C (Mn-MOF@BTTC-140) is remarkable because it has excellent crystallinity and a unique morphology, i.e., woodchips-like structure. The synthesized Mn-MOF@BTTC materials are used in supercapacitor applications. In comparison to all materials, Mn-MOF@BTTC-140 revealed the maximum specific capacitance (Cs) of 627 F g-1 @ 1 A g-1, and it displayed 91% capacitance retention even after the 6000 cycles at a current density of 10 A g-1. Furthermore, the supercapacitor device (SD) constructed using carbon nanofibers (CNF) as the negative electrode and Mn-MOF@BTTC-140 as the positive electrode delivered an energy density of 25 W h kg-1 at a power density of 532 W kg-1. Ultimately, LED lighting demonstrates that our fabricated materials suit practical applications.

Impact of Health Education Programme on Adherence to Treatment in Knee Osteoarthritis: An Interventional Study on Egyptian Patients.

To measure the level of adherence of patients with primary knee osteoarthritis (KOA) to an interventional therapeutic and rehabilitation programme and investigate factors that hinder patients' adherence. A total of 154 participants with primary knee osteoarthritis (KOA) were divided into intervention and control groups. The intervention protocol included patient education on the nature and treatment of KOA, therapeutic exercise, a weight loss programme for overweight patients, and a physical therapy programme. Participants were followed for 3months. The Visual Analog Scale for Pain (VAS-p), the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC), and knee Kellgren-Lawrence OA grading were measured before and after the intervention. Additionally, the Morisky adherence questionnaire and the WHO Multidimensional Framework for factors affecting adherence were assessed. One fifty four participants with KOA were randomly allocated into intervention and control groups. A low level of adherence was detected in both groups (68.8% in the intervention group vs. 84.4% in the control group). Patients who followed the interventional programme were more adherent. Adherence to therapy was associated with a reduction in the Visual Analog Scale for Pain (VAS-p) (p=0.016) and improved function as measured by WOMAC (p=0.018). Factors primarily associated with patient non-adherence included unemployment (67.8%), low income (59.3%), no previous response to therapy (58.5%), less frequent follow-up visits (55.1%), lack of insurance (66.9%), difficult access to services (59.3%), and high cost of services (55.1%). Adherence to treatment in OA patients is a significant concern and a common problem, appearing to be associated more with socioeconomic factors than with pain and function.

Assessment of Home-based Monitoring in Adults with Chronic Lung Disease. An Official American Thoracic Society Research Statement.

Background: There is increasing interest in the use of home-based monitoring in people with chronic lung diseases to improve access to care, support patient self-management, and facilitate the collection of information for clinical care and research. However, integration of home-based monitoring into clinical and research settings requires careful consideration of test performance and other attributes. There is no published guidance from professional respiratory societies to advance the science of home-based monitoring for chronic lung disease. Methods: An international multidisciplinary panel of 32 clinicians, researchers, patients, and caregivers developed a multidimensional framework for the evaluation of home-based monitoring in chronic lung disease developed through consensus using a modified Delphi survey. We also present an example of how the framework could be used to evaluate home-based monitoring using spirometry and pulse oximetry in adults with asthma, bronchiectasis/cystic fibrosis (CF), chronic obstructive pulmonary disease (COPD), and interstitial lung disease (ILD). Results: The PANACEA framework includes seven domains (test Performance, disease mANAgement, Cost, patient Experience, clinician Experience, researcher Experience, and Access) to assess the degree to which home-based monitoring assessments meet the conditions for clinical and research use in chronic lung disease. Knowledge gaps and recommendations for future research of home spirometry and pulse oximetry in asthma, bronchiectasis/CF, COPD, and ILD were identified. Conclusion: The development of the PANACEA framework allows standardized evaluation of home-based monitoring in chronic lung diseases to support clinical application and future research.

A Critical Review of Holistic Infection Control Practices in Healthcare Systems

The safety of patients and the general public has never been seriously doubted regarding infection control, especially in health facilities where nosocomial infections are still rampant. This critical review discusses comprehensive essential infection control concerns, including an evidence-based and multidimensional framework. Thus, presented in the literature and method sections, the outcomes focus on recent issues, ideas, and applications. It offers ideas about the effectiveness of adopting approaches to whole-person care to minimize the prevalence of infection and international compliance with quality healthcare. The result shows the importance of building stronger networks of effective systems against new emerging diseases.

SOCIAL MEDIA INFLUENCERS AND INFLUENCER MARKETING: A SYSTEMATIC LITERATURE REVIEW

The rise of Social Media Influencers (SMIs) has positioned Influencer Marketing (IM) as a pivotal strategy for businesses. Despite growing interest, research remains fragmented. This paper consolidates existing literature, analyzing 61 studies from the SCOPUS database to provide a comprehensive overview of IM dynamics. We explore how SMIs influence consumer intentions and behaviors, culminating in a multidimensional framework that identifies key variables, mediators, and moderators affecting consumer outcomes. This framework highlights various themes and research gaps, paving the way for future inquiries into emerging areas within influencer marketing. Ultimately, this study enriches the understanding of IM and offers valuable insights for academics and practitioners navigating this dynamic field.

Correlation analysis of failure risk factors in automated container port logistics systems from a resilience perspective

This paper aims to explore the correlations among failure risk factors of automated container port logistics systems from a resilience perspective. Based on the Wuli-Shili-Renli (WSR) theory and a multi-dimensional resilience framework, five key categories of risk factors affecting system resilience are identified: port infrastructure, port logistics operation organization, port personnel, port operational environment, and port emergency response and management. Through expert interviews, system component analysis, and a review of related literature across these five dimensions, 36 specific risk factors were identified to establish an initial set of system failure risk factors. Subsequently, a dual-factor screening method combining grey relational analysis and rank correlation was applied to simplify the initial set, constructing a system failure risk factor index system from a resilience perspective. Finally, a comprehensive model combining the Fuzzy Decision-Making Trial and Evaluation Laboratory (FDEMATEL) method and the Total Adversarial Interpretation Structure Model (TAISM) was proposed. This model identifies and quantifies the complex correlations among system failure risk factors from a resilience perspective, revealing their relative importance and their impact on system resilience. The results indicate that system resilience is primarily influenced by internal factors such as the smoothness of collection and distribution operations, infrastructure service capacity, and the stability of technical support systems. External factors, such as the prevention capability for major emergency threats and the improvement of government supervision and coordination feedback mechanisms, also significantly impact system resilience. The complex interactions among key factors have a profound effect on system resilience, underscoring the need to enhance coordination and management measures to strengthen overall system resilience. This study provides a theoretical foundation for developing targeted strategies to enhance the resilience of automated container port logistics systems.

Mergers and Attributions: An Examination of M&A Terminations in 1996–2022

AbstractFirms often make attributions regarding their actions in managing relationships with shareholders and investors. While research utilizing attribution theory has found that firms tend to attribute negative outcomes to external factors and positive outcomes to internal ones, this behaviour can have both positive and negative consequences. Addressing these contrasting results, our paper adopts a multidimensional framework of attribution to study how firms offer explanations for their actions. Leveraging insights from attribution theory and expectancy violation theory, we investigate whether investors respond diversely to firms' heterogeneous attributions for terminating acquisitions. Our findings indicate that an initial positive market reaction to an acquisition announcement is negatively correlated with the market reaction to the acquisition's termination. This negative relationship diminishes when the acquirer attributes the termination to external, uncontrollable and unstable factors. This paper contributes to the acquisition literature by highlighting multiple categories of attributions for firms to strategically manage market reactions.

Stakeholder treatment disparity and employee whistleblowing: A multi‐stakeholder, multidimensional framework of social comparison

AbstractResearch SummaryWe integrate social comparison theory into stakeholder research to develop a multi‐stakeholder, multidimensional framework to investigate how firms' relative treatment of employees affects employee whistleblowing. We theorize that a higher compensation disparity between the CEO and employees and treatment disparity between external stakeholders and employees will decrease employees' loyalty, leading to more external whistleblowing. The effects will be amplified with increased external labor market mobility. We use a multi‐method approach to test these predictions. In Study 1, we rely on archival data to test the influence of treatment disparities on whistleblowing. In Study 2, with two experiments, we demonstrate causality and examine employee loyalty as the explanatory mediating mechanism. Our study contributes to stakeholder theory by highlighting the critical implications of stakeholder treatment disparities.Managerial SummaryThis study examines the relationship between firms' treatment toward employees and employee whistleblowing to an outside entity. External whistleblowing may generate unintended short‐term negative consequences for firms. Firms need to be aware of the potential reputational damage of external whistleblowing and make strategic decisions that could prevent such behavior. Based on data from US publicly listed firms from 1992 to 2013 as well as two experiments, we find that employees will make comparisons among different references groups (i.e., CEOs and other stakeholders). Unfavorable comparison will decrease employee loyalty toward the firms, leading to more whistleblowing. This effect is even stronger if employees have more opportunities in the external labor market. The results suggest that firms need to be careful about creating huge disparities in stakeholder treatment.

Mapping the Landscape of Inclusion: A Multidimensional Conceptual Framework for Inclusive Education in Pakistan

Using qualitative conceptual analysis in this paper, the author wants to develop a conceptual understanding of the provision of education in Pakistan. Using literature from various disciplines, paradigms of inclusive education in Pakistan and in developing countries are compared to develop a theory that would encompass the ideas developed up until now. The resulting conceptual framework consists of seven interconnected concepts: Support, programmes, legislation/policy, school climate, teacher education, curriculum implementation, community involvement, finance, and organizational culture. This framework can be beneficial in the huge Pakistani process of attempting to conceptualize and systematically understand the complexities of implementing inclusive education. It can assist policymakers, practitioners, and researchers in changing and evolving research for the improvement of inclusive education in Pakistan. Last, the paper concludes and considers how the topic and ideas the paper presents could be taken forward to strengthen the practice of integration and participation of children with disabilities in each of the educational systems in Pakistan. More specifically, there is a need for findings regarding the international concept of inclusive education, the continued expansion and elaboration of its theoretical paradigms and models, including education policies and outcomes, and teacher training in relation to inclusion, curriculum development, and community participation regarding exclusion in Pakistan.

Towards sustainable urban energy solutions: A multi-dimensional assessment framework for fifth-generation district heating and cooling systems

Decarbonising heating and cooling often focuses on electrification, with heat pumps and decentralised generation playing key roles. This transition poses economic and environmental challenges, particularly in the production, operation, and disposal of these systems. However, greenhouse gas emissions from heating and cooling equipment are often overlooked. This study evaluates whether fifth-generation district heating and cooling (5GDHC) systems offer a better alternative to traditional heat pumps and chillers for electrifying heating and cooling in buildings. We introduce a framework to compare the performance of 5GDHC systems with traditional alternatives, focusing on engineering, economic, and environmental aspects. The framework uses linear programming, cradle-to-grave life cycle assessment, and a global sensitivity analysis to support decision-making under uncertainty. It is applied to five case studies: Brisbane, Melbourne, New York City, Paris, and Singapore, under three scenarios: current trends, and slow and rapid electrification aiming for net zero by 2050 and 2040. Results show that 5GDHC systems can reduce annualised costs, which include capital and operational costs, by up to 26% and GHG emissions by up to 21%, with self-sufficiency rates up to 98%. This framework aids planners and policymakers in making informed decisions for sustainable urban energy solutions, emphasising the importance of an early, holistic assessment.

Complexity Evaluation for Urban Intersection Scenarios in Autonomous Driving Tests: Method and Validation

As autonomous driving technology scales up, complex urban intersections pose significant safety challenges. Current testing methods struggle to simulate these complex scenarios at a manageable cost, making simulation testing essential. For effective evaluation, establishing comprehensive and objective complexity metrics is crucial. However, existing complexity evaluation methods often depend on the performance of the primary vehicle and are based on local interaction relationships, which lack a global perspective and objectivity and have yet to be validated by autonomous driving systems. To address this issue, this paper proposes a multidimensional complexity assessment framework that introduces system-level indicators such as vehicle count, interaction density, disorder, and risk. This framework quantifies the complex interactions at intersections from a global perspective, independent of primary vehicle performance. Experimental results demonstrate that the complexity evaluation results are highly consistent with the performance of a high-level autonomous driving system (Apollo). The framework has been successfully applied to test scenario generation on the Apollo platform, achieving twice the scenario generation efficiency of traditional methods, thus showcasing substantial engineering value.

Instruments for assessing social health in the context of cognitive decline and dementia: a systematic review.

The concept of social health has recently received increasing attention in dementia research. Various notions of what social health is and how it can be measured are circulating. They may pose challenges for comparing results and interpreting them for the development of interventions. This systematic review aims to classify existing instruments that measure various domains of social health. To achieve this, we applied a new multidimensional framework consisting of six key domains of social health. A systematic review was conducted following the PRISMA 2020 guidelines. PubMed/MEDLINE, PsychINFO, and CINAHL were searched for studies published between January 2000 and July 2023. A total of 227 studies (longitudinal, case-control, and cross-sectional cohort studies) with 102 single instruments were included. The search terms were as follows: (1) dementia (i.e., Alzheimer's, cognitive impairment); (2) social health markers (i.e., decision-making, social participation, loneliness); and (3) instruments (i.e., tools, measures). The instruments are mainly self-reported, and the number of items ranges from 3 to 126. Despite the wide array of instruments available, most focus on individual domains of social health. We recommend the development of more conceptually robust instruments that can comprehensively evaluate psychosocial interventions and adequately capture all domains of social health.

Measuring complexity in mega construction projects: fuzzy comprehensive evaluation and grey relational analysis

PurposeMega construction projects (MCPs), characterized by their vast scale, numerous stakeholders and complex management, often face significant uncertainties and challenges. While existing research has explored the complexity of MCPs, it predominantly focuses on qualitative analysis and lacks systematic quantitative measurement methods. Therefore, this study aims to construct a complexity measurement model for MCPs using fuzzy comprehensive evaluation and grey relational analysis.Design/methodology/approachThis study first constructs a complexity measurement framework through a systematic literature review, covering six dimensions of technical complexity, organizational complexity, goal complexity, environmental complexity, cultural complexity and information complexity and comprising 30 influencing factors. Secondly, a fuzzy evaluation matrix for complexity is constructed using a generalized bell-shaped membership function to effectively handle the fuzziness and uncertainty in the assessment. Subsequently, grey relational analysis is used to calculate the relational degree of each complexity factor, identifying their weights in the overall complexity. Finally, the weighted comprehensive evaluation results of project complexity are derived by combining the fuzzy evaluation results with the grey relational degrees.FindingsTo validate the model’s effectiveness, the 2020 Xi’an Silk Road International Conference Center construction project is used as a case study. The results indicate that the overall complexity level of the project is moderate, with goal complexity being the highest, followed by organizational complexity, environmental complexity, technical complexity, cultural complexity and informational complexity. The empirical analysis demonstrates that the model can accurately reflect the variations across different dimensions of MCP complexity and can be effectively applied in real-world projects.Originality/valueThis study systematically integrates research on MCPs complexity, establishing a multidimensional complexity measurement framework that addresses the limitations of previous studies focusing on partial dimensions. Moreover, the proposed quantitative measurement model combines fuzzy comprehensive evaluation and grey relational analysis, enhancing the accuracy and objectivity of complexity measurement while minimizing subjective bias. Lastly, the model has broad applicability and can be used in MCPs across different countries and regions, providing a scientific and effective basis for identifying and managing MCP complexity.

Construction of women's empowerment index for Bangladesh.

This study is dedicated to refining and enhancing the measurement model of women's empowerment in Bangladesh. Women's empowerment, a crucial and multifaceted aspect of societal growth, is often hindered by gender disparities. This is particularly evident in societies like Bangladesh, where women face inequalities in education, economic opportunities, and decision-making power. To address these disparities effectively, it is essential to have a comprehensive understanding of women's empowerment. Therefore, this study aims to refine and enhance the measurement model to capture the multifaceted nature of women's empowerment accurately. To gather data for this study, a structured questionnaire was administered to married women of reproductive age (15-49) in eight Mouza/Mohalla in Dhaka, Bangladesh. This unique approach allowed us to capture a diverse range of perspectives. We used thirty-three indicators across economic, socio-cultural, household, and psychological dimensions to measure women's empowerment. The sample data were then randomly divided for exploratory factor analysis (EFA) and Confirmatory Factor Analysis (CFA) to identify and validate a comprehensive multidimensional framework. Out of 625 respondents, only 36% of women worked, and ~39% married before age 18. Employing thirty-three items in EFA led to identifying eight critical factors (economic independence, control over household financial decisions, household decision-making, reproductive decision-making, freedom of movement, media exposure, positive self-esteem, and negative self-esteem). These factors, which explained 72.661% of the total variance in the data, provide a practical framework for understanding and addressing women's empowerment. Each component was then divided into two sub-dimensions to acquire a better understanding. The CFA indicated a good model fit for each dimension, and convergent and discriminant validity assessments were used to establish reliability and validity, further enhancing the practical implications of our findings. The results of our rigorous exploratory and confirmatory factor analyses not only confirmed the sample structures and internal consistency but also provided significant insights. The findings suggested an adequate fit for all CFA models, indicating the robustness of our measurement model. According to the CFA results, each dimension's variables are satisfactory, and all the dimensions can be combined to create a single index measuring women's empowerment. This comprehensive understanding of women's empowerment, with its specific dimensions and factors, equips policymakers and practitioners with the knowledge to develop a wide range of interventions appropriate to particular facets of empowerment, thereby fostering societal growth and gender equality.

Constructing General Human Agency Indicators (GHAIs) and a General Personal Agency Scale (GPAS)

AbstractDespite its importance for the social sciences, human agency remains an ambiguous and underoperationalized construct. After engaging prior research to articulate clear criteria for defining agency and synthesize a multidimensional conceptual framework for human agency, this study develops and validates preliminary General Human Agency Indicators (GHAIs) to measure subconstructs within that framework. Utilizing the Midlife in the United States (MIDUS) dataset, we aggregated a list of 30 survey items previously used in agency research and conducted an iterative process of exploratory factor analysis (EFA) and item elimination to reduce that list to a set of 9–13 items with a strong, consistent factorial structure. Using confirmatory factor analysis (CFA), we identified two bifactor models that demonstrated good fit: a nine-item General Personal Agency scale (GPAS) and a nine-item GHAIs tool combining six items from the GPAS with three measuring agency achievement. Initial evidence for the construct validity of the tools was produced through tests of internal consistency and correlational analysis, indicating that the proposed GPAS and GHAIs effectively measure personal agency, intrinsic agency, instrumental agency, and agency achievement.

STEM-11. MULTIDIMENSIONAL PROFILING OF TUMOR CELL HETEROGENEITY REVEALS CELL-LINEAGE SPECIFIC FUNCTIONS IN SUPRATENTORIAL EPENDYMOMAS

Abstract Supratentorial ependymomas (ST-EPN) are aggressive pediatric brain tumors that are categorized into distinct molecular subgroups. However, the developmental origins, tumor microenvironment, and phenotypic characteristics of tumor subpopulations across these subgroups are still poorly understood. In this study, we explored the human developmental signatures, global spatial organization, and the morphological and migratory tumor cell state behaviors in ST-EPN tumors at unprecedented resolution. We profiled 42 ST-EPN patients encompassing ZFTA-RELA (n = 20), ZFTA-Clusters 1 to 4 (n=20), and ST-YAP1 (n=4) subgroups by single-cell RNA sequencing (scRNA-seq), spatial transcriptomics, and live-cell imaging. We identified recurrent tumor cell states across tumors, that cover both generic cell processes (including cycling and mesenchymal/hypoxia) and human embryonic and fetal brain developmental signatures. ST-EPN subgroups displayed distinct developmental signatures, mapping to two separate temporally restricted progenitors-neuroepithelial-like and embryonic-like cells. Additionally, tumors showed diverging patterns of neuronal or ependymal differentiation, with ZFTA-Cluster 3 tumors as especially distinct from other subgroups in both developmental origin and differentiation. Furthermore, by utilizing 10X Xenium and novel algorithms we discovered that mesenchymal/hypoxia is critical for driving global tissue architecture to become more organized. Notably, recurrent tumors exhibited higher proportion of mesenchymal/hypoxia cells and greater structure than primary tumors. Lastly, by superimposing molecular and functional assays in both in vivo and in vitro models, we found that cell states exhibit distinct morphological and migratory behaviors, with neuronal-like cells being the most invasive. Neuronal-like cells especially exhibited distinct behavioral patterns reminiscent of neuronal migration during development. Moreover, we demonstrated the crucial role of neuronal microenvironment in promoting plasticity of cells toward this neuronal lineage. Taken together, we present a multidimensional framework for investigating cellular states within ST-EPN tumors, offering novel insights into their developmental origins, patterns of spatial organization, and cellular behavioral characteristics.

Sleep quality, daytime sleepiness, and risk of falling: results from an exploratory cross-sectional study.

There is growing recognition of the importance of managing sleep disorders in the elderly, particularly given their complexity within a multidimensional framework. The aim of the present study is to investigate whether sleep quality and daytime sleepiness are associated with the risk of falls in older adults. This study included patients aged 75years or older who were consecutively evaluated at the Geriatric Service, University Hospital of Monserrato, Cagliari, Italy. Participants underwent geriatric assessment, including sleep analysis using the Pittsburgh Sleep Quality Index (PSQI), and the Epworth Sleepiness Scale (ESS), as well as an assessment of risk of falls with Performance Oriented Mobility Assessment (POMA). The study included 206 subjects, of whom 70.4% were women, with a median age of 83years. A total of 141 participants (68.4%) had poor sleep quality, and 43 (20.9%) had excessive daytime sleepiness (EDS). Among people at high risk of falls, 85 participants had bad sleep quality, and 24 a satisfying one (χ2: 8.23, p = 0.0029); additionally, 77 participants did not exhibit daytime sleepiness, while 32 did (χ2: 9.03, p = 0.0027). To further explore these results, we designed logistic regressions, considering dichotomized PSQI and dichotomized ESS as independent variables, and dichotomized POMA as the dependent variable, and finally adjusted them for confounders. The adjusted model for PSQI yielded OR: 2.04 (95%CI 1.02-4.10), and the adjusted model for ESS yielded OR: 2.56 (95%CI 1.17-5.91). Our study demonstrated that an increased estimated risk of falling is associated with poor sleep quality and EDS in older adults, independently of the confounders.

Linking theory and practice to advance sustainable healthcare: the development of maturity model version 1.0.

Climate change and increased awareness of planetary health have made reducing ecological footprints a priority for healthcare organizations. However, improving healthcare's environmental impact remains difficult. Numerous researchers argue these difficulties are caused by healthcare's environmental impact being multidimensional, influenced throughout the healthcare chain, and often has downstream consequences that are hard to identify or to measure. Even though existing research describes many successful approaches to reduce healthcare's environmental impact, a robust multidimensional framework to assess this impact is lacking. This research aims at developing a maturity model for sustainable healthcare that could be used for self-assessment by healthcare professionals to identify improvement actions and for sharing best practices in environmental sustainability. A design-oriented approach for maturity model development was combined with an expert panel and six case studies to develop, refine and expand the maturity model for environmentally sustainable healthcare. A maturity model was developed containing four domains: 'Governance', 'Organization Structures', 'Processes', and 'Outcomes and Control'. Applying the model in real-world environments demonstrated the model's understandability, ease of use, usefulness, practicality and ability to identify improvement actions for environmental sustainability in healthcare organizations. This study found that healthcare practitioners could apply the maturity model developed and tested in this study in several hours without training to help them gain valuable insights into the environment footprint of the healthcare setting they worked in. Systematically implementing the model developed in this study could help address the urgent need to mitigate the substantial environmental impact of healthcare. These implementations can help evaluate and improve the maturity model.

Design Thinking Approach to Create Impact Assessment Tool: Cities2030 Case Study

This paper presents the development and testing of an impact assessment tool for the Cities2030 project aimed at transforming city-region food systems to align with the European Union’s Food2030 policy and the European Green Deal. This study highlights the importance of sustainable urban food systems, focusing on food security, environmental sustainability, and public health. Using a design thinking approach, this research emphasizes co-creation, stakeholder engagement, and iterative refinement, developing a flexible, multi-dimensional framework adaptable to diverse city-region contexts. Through collaboration with 65 stakeholders, this tool was tailored to meet the socio-economic and environmental needs of different regions. Case studies from Cities2030 partner cities demonstrate its effectiveness in fostering cross-sectoral collaboration, enhancing community participation, and driving food system innovations. Key findings reveal measurable impacts across social, environmental, and economic dimensions, while addressing challenges like regional disparities in data collection and the need for improved long-term tracking of sustainability metrics. This study concludes by underscoring the role of adaptive, inclusive strategies in assessing urban food systems’ sustainability and resilience and suggests that the tool’s framework could be applied to other urban sustainability areas, such as energy and water management.