Sustainable Planning Research Articles

Research into the Influence Mechanisms of Visual-Comfort and Landscape Indicators of Urban Green Spaces

Urban green spaces play a crucial role in providing social services and enhancing residents’ mental health. It is essential for sustainable urban planning to explore the relationship between urban green spaces and human perceptions, particularly their visual comfort. However, most current research has analyzed green spaces using two-dimensional indicators (remote sensing), which often overlook human visual perceptions. This study combined two-dimensional and three-dimensional methods to evaluate urban green spaces. Additionally, the study employed machine learning to quantify residents’ visual comfort in green-space environments and explored the relationship between green spaces and human visual perceptions. The results indicated that Kitakyushu exhibited a moderate FCV and an extremely low Green View Index (GVI). Yahatanishi-ku was characterized as having the highest visual comfort. Tobata-ku demonstrated the lowest visual comfort. Natural, GVI, openness, enclosure, vegetation diversity, landscape diversity, and NDBI were positively correlated with visual comfort. FCV and ENVI were negatively correlated with visual comfort. Vegetation diversity had the most impact on improving visual comfort. By integrating remote sensing and street-view data, this study introduces a methodology to ensure a more holistic assessment of green spaces. Urban planners could use it to better identify areas with insufficient green space or areas that require improvement in terms of green-space quality. Meanwhile, it could be helpful in providing valuable input for formulating more effective green-space policies and improving overall urban environmental quality. The study provides a scientific foundation for urban planners to improve the planning and construction of healthy and sustainable cities.

Forgotten Ecological Corridors: A GIS Analysis of the Ditches and Hedges in the Roman Centuriation Northeast of Padua

Studying historical rural landscapes beyond their archaeological and cultural significance, as has typically been addressed in previous research, is important in the context of current environmental challenges. Some historical rural landscapes, such as Roman land divisions, have persisted for more than 2000 years and may still contribute to sustainability goals. To assess this topic, the hydraulic and vegetation network of the centuriation northeast of Padua were studied, emphasising their multiple benefits. Their length, distribution, and evolution over time (2008–2022) were vectorised and measured using available digital terrain models and orthophotographs in a geographic information system (GIS). The results revealed a significant decline in the length of water ditches and hedgerows across almost all examined areas, despite their preservation being highlighted in regional and local spatial planning documents. These findings indicate the need for a better understanding of the local dynamics driving such trends and highlight the importance of adopting a more tailored approach to their planning. This study discusses the GIS metrics utilised and, in this way, contributes to landscape monitoring and restoration actions. Finally, a multifunctional approach to the sustainable planning of this area is proposed here—one that integrates the cultural archaeological heritage in question with environmental preservation and contemporary climate adaptation and mitigation strategies.

Estimation Stand Volume, Basal Area and Quadratic Mean Diameter Using Landsat 8 OLI and Sentinel‐2 Satellite Image With Different Machine Learning Techniques

ABSTRACTThe data required for sustainable forest planning is provided by traditional forest inventories, which are labor, time, and cost‐intensive. Providing this data quickly, reliably, and accurately is crucial for planners and researchers. The objective of this study was to predict stand basal area (BA), stand volume (V), and quadratic mean diameter (dq) by leveraging vegetation indices (VIs) and reflectance (R) derived from Landsat 8 OLI and Sentinel 2 satellite images, along with topographic (T) data obtained from ALOS‐PALSAR satellite imagery. Forest inventory data for a total of 250 sample plots were used for modeling in the study. Stand parameters were estimated using support vector machines (SVM), multiple linear regression (MLR), decision tree (DT), and random forest (RF) algorithms. In modeling V, BA, and dq, both individual and combinations of R, VIs, and T values obtained from satellite imagery were used as independent variables. Using the generated datasets, each of the stand parameters was modeled separately with MLR, SVM, RF, and DT algorithms, and the success of the models was compared to determine the modeling technique and dataset with the highest success for the relevant parameter. The results showed that for each stand parameter, the highest model success was achieved in the combined dataset, which was created by combining all datasets. However, in terms of modeling techniques, the highest success for each stand parameter was achieved with different modeling techniques. The highest success for V is obtained in the model using the SVM method (R2 = 0.78; RMSE = 0.28 m3/ha), the RF method yielded the highest model performance for BA (R2 = 0.70; RMSE = 2.53 m2/ha), and finally, the highest success for dq was obtained in the DT method (R2 = 0.74; RMSE = 0.02 cm). In general, the datasets obtained from Sentinel 2 images showed higher model success than the datasets obtained from Landsat 8 OLI images.

Sustainability and resilience interface at typical urban green and blue infrastructures: costs, benefits, and impacts assessment

The rapid urbanization witnessed in recent years has led to the deterioration of urban ecosystems, resulting in various environmental and socioeconomic challenges. In response to these concerns, the implementation of Green and Blue Infrastructures (GBI) has gained prominence as a sustainable urban planning approach. GBI is a planned network system of natural and semi-natural spaces, along with other environmental elements, managed and designed to provide a wide range of ecosystem services and improve ecological conditions, thereby contributing to citizens' wellbeing and quality of life. This study presents a comprehensive assessment of the costs, benefits (ecosystem services), and impacts (ecosystem dis-services) associated with the incorporation of GBI in urban environments using the technique of emergy accounting. To achieve this, the research paper introduces a novel integrated valuation framework. This framework encompasses key components such as constructing/maintenance costs, ecosystem services, needed costs to human health and biodiversity damage, as well as ecosystem dis-services. Furthermore, the study conducts a comparative analysis of the costs, benefits, and impacts associated with different urban GBIs via ternary phase diagram, shedding light on their varying contributions to the urban ecosystem. The findings reveal that green roofs offer more ecosystem benefits as compared to other GBIs, but this study also highlights that green roof entail higher initial construction costs and produce a greater number of dis-services. Conversely, street trees have lower initial costs and impacts yet generate higher benefits. Furthermore, green walls, despite having a lower input emergy value and fewer benefits, result in higher impacts compared to other green-blue ecosystems. These findings provide valuable insights for urban planners, policymakers, and stakeholders, enabling them to make informed decisions in developing sustainable cities for the wellbeing of present and future generations.

Designing sustainable diet plans by solving triobjective integer programs

AbstractWe present an algorithm for triobjective nonlinear integer programs that combines the $$\varepsilon $$ ε -constrained method with available oracles for biobjective integer programs. We prove that our method is able to detect the nondominated set within a finite number of iterations. Specific strategies to avoid the detection of weakly nondominated points are devised. The method is then used to determine the nondominated solutions of triobjective 0–1 models, built to design nutritionally adequate and healthy diet plans, minimizing their environmental impact. The diet plans refer to menus for school cafeterias and we consider the carbon, water and nitrogen footprints as conflicting objectives to be minimized. Energy and nutrient contents are constrained in suitable ranges suggested by the dietary recommendation of health authorities. Results obtained on two models and on real world data are reported and discussed.

An integrated approach for analysing land surface temperature, heatwave and air pollution for sustainable planning in Delhi and its environs, India

An integrated approach for analysing land surface temperature, heatwave and air pollution for sustainable planning in Delhi and its environs, India

Participatory mapping of ecosystem services of coastal wetlands in Taiwan

AbstractThere is a lack of knowledge and understanding about what ecosystem services are and how to utilize them in a sustainable way. Ecosystem services are thus often underrecognized by the decision makers in charge of creating wetland management plans. Due to this, ecosystem services, which have been used by communities for a long time, are often left out of wetland's wise‐use plans. Inclusion of local communities and promotion of local knowledge are vital aspects of creating sustainable, equitable and resilient wetland management plans that are truly ‘wise’. In this research, we utilize participatory mapping methods to engage communities and create a database of the ecosystem services being used in Chigu Salt Pan Wetland and Chigu Lagoon, located along the coast of Southwestern Taiwan. We look at who are using the ecosystem services, to what degree they are being used and where exactly in the wetland system they are being extracted/utilized. This will pave the way for future researchers to better understand the value of Chigu Salt Pan Wetland and the ecosystem services they provide and promote the use of participatory methods in other locations.

Long-Term Evolution of Ecologically Fragile Waterside Rural Areas and Strategies for Local Spatial Planning: An Empirical Study in Baiyangdian, China

Under the dynamics of urbanization and counterurbanization, rural areas in China face both challenges and opportunities with the government’s new-town policy. A comprehensive analysis is essential for developing effective strategies. Characterized by traditional water settlements and high ecological sensitivity, Anxin County, which encompasses 50% of Baiyangdian Lake, was selected as a case study. Anxin County was incorporated into the National New Area in 2017, and it served as an experimental site for green ecological development. This study aims to provide insights into the sustainable spatial planning of Anxin County’s settlements by examining their long-term evolution and locational differences, modeling the driving mechanisms, and proposing differentiated spatial planning strategies based on predictive outcomes. Our research findings indicate the folllowing: (1) Anxin County’s settlements have expanded significantly in the past, with a notable surge between 1975 and 1996. Initially, semi-waterside settlements experienced the fastest growth before the 1970s, followed by land settlements. (2) Natural and socio-economic factors are modeled as independent variables to explain the evolution of settlement areas. The results indicate a decreasing impact of natural factors and an increasing influence of socio-economic factors over time. Furthermore, the evolution of settlements in water areas is relatively straightforward and random, whereas land settlements are influenced by a complex array of factors. (3) Utilizing the model to predict settlement growth, the study identifies settlements requiring relocation, and it proposes the most suitable relocation targets for them. A total of 23 villages, including Bei Tianzhuang and Cai Putai, are identified for relocation, while villages such as Ma Village, Bian Village, and Liu Lizhuang have strong capacities for accepting in-migrants. The study also offers recommendations for enhancing waterfront landscapes, flexible land use, road network systems, and internal construction.

Research on the Practical Path of Green Finance in the Low-carbon Transformation of Smart Cities: A Case Study of the Transformation and Development of European Smart Cities

This study aims to explore the practical path of green finance in promoting low-carbon transformation of smart cities by taking the transformation of smart cities in Europe as a case study. The successful experience of smart city transformation in Europe is deeply studied through case analysis, and the application of green finance and its impact mechanism on urban transformation are discussed. The study found that green finance plays an important role in the transformation of smart cities in Europe, which promotes the transformation of cities to lowcarbon and smart direction through the practice path of policy formulation, technological innovation and sustainable development planning. This study provides a reference for the low-carbon transformation of smart cities in other regions, and has certain theoretical and practical significance for promoting sustainable urban development.

Machine learning-aided hybrid technique for dynamics of rail transit stations classification: a case study

Accurate classification of rail transit stations is crucial for successful Transit-Oriented Development (TOD) and sustainable urban growth. This paper introduces a novel classification model integrating traditional methodologies with advanced machine learning algorithms. By employing mathematical models, clustering methods, and neural network techniques, the model enhances the precision of station classification, allowing for a refined evaluation of station attributes. A comprehensive case study on the Chengdu rail transit network validates the model’s efficacy, highlighting its value in optimizing TOD strategies and guiding decision-making processes for urban planners and policymakers. The study employs several regression models trained on existing data to generate accurate ridership forecasts, and data clustering using mathematical algorithms reveals distinct categories of stations. Evaluation metrics confirm the rationality and accuracy of the results. Additionally, a neural network achieving high accuracy on labeled data enhances the model’s predictive capabilities for unlabeled instances. The research demonstrates high accuracy, with the Mean Squared Error (MSE) for regression models (Multiple Linear Regression (MLR), Deep-Learning Neural Network (DNN), and K-Nearest Neighbor (KNN)) remaining below 0.012, while the neural networks used for station classification achieve 100% accuracy across seven time intervals and 98.15% accuracy for the eighth, ensuring reliable ridership forecasts and classification outcomes. Accuracy in rail transit station classification is critical, as it not only strengthens the model’s predictive capabilities but also ensures more reliable data-driven decisions for transit planning and development, allowing for more precise ridership forecasts and evidence-based strategies for optimizing TOD. This classification model provides stakeholders with valuable insights into the dynamics and features of rail transit stations, supporting sustainable urban development planning.

Assessing the Impact of Vertical Greenery Systems on the Thermal Performance of Walls in Mediterranean Climates

This study investigates the impact of vertical greenery systems (VGSs) applied to several typical wall configurations on indoor thermal conditions in a building module situated in the Mediterranean climate of Catania, Italy. By means of dynamic simulations in TRNSYS vers.18, the research compares the thermal behavior of walls made of either hollow clay blocks (Poroton) or lava stone blocks against a lightweight wall setup already in place at the University of Catania. The primary focus is on evaluating the VGSs’ capability of reducing peak inner surface temperatures and moderating heat flux fluctuations entering the building. The findings indicate that adding an outer vertical greenery layer to heavyweight walls can decrease the peak inner surface temperature by up to 1.0 °C compared to the same bare wall. However, the greenery’s positive impact is less pronounced than in the case of the lightweight wall. This research underscores the potential of green facades in enhancing the indoor thermal environment in buildings in regions with climates like the Mediterranean one, providing valuable insights for sustainable building design and urban planning.

Strategic Financial Planning for Long-Term Sustainability in Madrasah Aliyah

This study investigates strategic financial planning for long-term sustainability in Madrasah Aliyah Siti Mariam Banjarmasin. The objective is to analyze the institution's financial challenges, explore strategies for enhancing financial sustainability, and propose recommendations for effective financial management. The research employs qualitative methods, including interviews and observations, to gather data on financial practices, challenges, and strategies within the institution. The findings reveal significant challenges in allocating financial resources effectively, including dependence on Government funding and limited investment in critical areas such as infrastructure and staff development. However, the study also identifies promising strategies for improving financial sustainability, such as diversifying revenue streams through fundraising events and partnerships, optimizing resource utilization, and implementing prudent financial management practices. Based on these findings, recommendations are proposed to prioritize investments in key areas, enhance revenue diversification efforts, and foster a culture of financial responsibility within the institution. Overall, the study contributes to understanding strategic financial planning in educational institutions and provides practical insights for enhancing long-term sustainability in Madrasah Aliyah Siti Mariam Banjarmasin.

Grassland or Cropland? Land Use Dilemma and Ecological Solutions in Inner Mongolia

ABSTRACTInner Mongolia plays a critical role in both ecological conservation and food provision in China. However, some researchers have argued that focusing on and improving only one side of the equation necessarily threatens the functionality of the opposite side. To address this problem, we compared a “business‐as‐usual” scenario (BAU) with a “sustainable land use planning” scenario (SLU) constructed by simulating spatiotemporal changes in croplands and grasslands in Inner Mongolia from 2020 to 2030. Additionally, we analyzed the changes in ecosystem services and protein supply associated with changes in land use. We found that, in the BAU scenario, grasslands would decrease by 1.85% over the simulation period, while croplands would increase by 9.94%, with ecosystem services decreasing under both land uses. In contrast, land use changes over the same period in the SLU scenario are more significant, with increases of 11.33% and 2.78% in grassland and cropland, respectively, but, in this case, with ecosystem services increasing under both land uses. Moreover, protein supply increased under both scenarios, but SLU scenario can provide 33% more protein than the BAU scenario. The interconversion of cropland and grassland is the main type of land conversion in the study region, while cropland, grassland, and bare land show a triangular cycle of conversion. In addition, the implementation of scenario planning can realize multiple dividend for cultivation, livestock, and ecology in Inner Mongolia.

Implementation of a Nurse-Initiated Antibiotic Time-Out (NATO) in Childhood Cancer Patients in Central America

Abstract Background Children with cancer are at high risk for infection and frequently require antimicrobials. Antimicrobial stewardship (AMS) interventions can mitigate toxicity and development of antibiotic resistance yet the pharmacy and infectious diseases specialists who usually perform AMS are often absent in global settings. We report our experience testing a novel intervention to shift the antibiotic timeout to nurses in six pediatric oncology units in Central America. Methods The Nurse-initiated Antibiotic Timeout (NATO) is a scripted conversation between nurses and physicians to reevaluate antibiotic appropriateness after 48 to 72 hours of empiric use for febrile neutropenia. First, we performed a baseline assessment of AMS capacity using the WHO Practical Toolkit for AMS Programmes checklist. Based on these results, sites tailored a generic implementation plan emphasizing educational and documentation tools and iterative PDSA (Plan-Do, Study-Act) cycles to improve implementation and effectiveness outcomes. Results All sites collected antimicrobial use data for a minimum of two months. Four sites then piloted NATO, producing change ideas, including changes to documentation tools, antimicrobial decision categories, communication processes, and times. From August 2022 – October 2023, NATO was performed in 53.4% of febrile neutropenia episodes in the three sites reporting data. Sites had substantial NATO performance rate variation from month to month. Sites reported changes in antimicrobial therapy in 47% of episodes after a 6-month period (Figure 1). Conclusion The difference in performance rate of NATO underscores the importance of real-time reporting to adjust AMS implementation strategies. The change ideas developed by each site differed, however, core tools emerged, which will support AMS in other global settings. Next steps include comparing antimicrobial use pre- and post-intervention and determining a sustainability and scalability plan. Figure 1. Incidence of change in antibiotic therapy over time.

Harvest and trade of wild edible russula griseocarnosa in North Vietnam

This study examines the harvest and trade of wild edible Russula griseocarnosa in north Vietnam. Russula griseocarnosa is an edible forest mushroom, but there is no reliable information on harvesting practices and trade in this species in Vietnam. This study aims to provide ethnomycological and marketing knowledge for this mushroom. Semi-structured interviews were conducted with mushroom collectors and traders over 2 years; harvest yields were obtained from local officials; and policy settings were sought from forest managers. About 85% of mushroom collectors were women of the Dao, Lo Ursula, Muong, Nung, Mong, San Chi, San Diu, and Tay ethnicities. The collecting season was bimodal, with the wet season beginning (May) and ending (September). The traders were Hoa, Kinh, Nung and Tay, and 57% were women. Fresh mushrooms sold for 9.1-10.5 US$/kg on dry days and 7.0-7.9 US$/kg on wet days. The best grade of dried product fetched 70.4-83.3 US$/kg. A number of interim policies have been established to encourage local people to protect forests and to help create a sustainable edible wild mushroom market. Our study provides the first detailed account of the role of edible wild mushrooms in northeast Vietnam, and this will inform the co-development of rural livelihood and sustainable forest management plans.

Predictive soil mapping using random forest models: Applications in pH and soil organic matter assessment

Digital Soil Mapping (DSM) presents a highly scalable and efficient alternative to traditional soil analysis, which is typically limited by its labor-intensive processes, time constraints and low spatial resolution. By utilizing advanced computational techniques such as machine learning and remote sensing, DSM overcomes these limitations and improves the accuracy, efficiency and scalability of soil property assessments. This study, conducted across Tamil Nadu, India, applied DSM and Random Forest (RF) models to predict 2 key soil properties: pH and Soil Organic Matter (SOM). We employed Conditioned Latin Hypercube Sampling (cLHS) for optimized sampling point selection and utilized the Boruta algorithm to identify the most relevant covariates for accurate modeling. The RF models were fine-tuned using a comprehensive grid search, with the optimal configuration spanning from 500 to 2000 trees (ntree) and mtry from 1 to 11. The best-performing model was found with 2000 trees and mtry set to 1 yielding superior prediction for SOM and pH with Root Mean Square Error (RMSE) values of 0.71 and 0.60 respectively, showcasing a high level of predictive accuracy. Our findings emphasize the critical role that remote sensing indices play in predicting SOM, while pH was influenced by both terrain features and remote sensing data. In comparison to previous studies, this research offers novel improvements in both sampling optimization and model configuration, leading to enhanced predictive performance. These results hold significant potential for sustainable land-use planning, agricultural productivity and environmental management.

Toward holistic neighbourhood sustainability assessment: integrating fuzzy Delphi method for sustainable indicator selection for Aizawl city

ABSTRACT Neighbourhood Sustainability Assessment (NSA) is vital in navigating the complex dynamics of social, environmental, and economic factors in localised settings, especially amidst the challenges of urbanisation, resource scarcity, and climate change. NSA tools have emerged as pivotal instruments in integrating sustainability into urban development, recognising neighbourhood as fundamental units for systemic sustainability approaches. However, existing NSA methodologies tend to favour environmental aspects, prompting a call for more balanced approaches encompassing social and economic dimensions. The study underscores the need for NSA tools to evolve towards context-sensitive methodologies for broader applicability across diverse urban landscapes. Through a literature review, the study highlights the importance of integrating community perspectives, sustainability indicators, and context-specific approaches in NSA, advocating for holistic strategies to drive sustainable urban development agendas. This study presents a methodological framework for selecting neighbourhood sustainability indicators in Aizawl, the capital city of Mizoram which is located in N-E India, by incorporating community perspectives and expert judgments. The methodology involves several steps: review of existing NSA frameworks to select comprehensive indicators, perception and public participation surveys to identify local indicators, engagement of experts through the Fuzzy-Delphi Method, and application of the Analytic Hierarchy Process (AHP) for indicator prioritisation. Through these steps, 47 essential indicators were selected, covering social, economic, environmental and governance aspects. The study emphasises the importance of combining bottom-up community input with top-down-expert knowledge for comprehensive and reliable sustainability assessments. Challenges such as energy and water resource deficiencies are highlighted, underscoring the need for balanced approaches to neighbourhood sustainability planning.

Assessment of surface irrigation potential and crop water demand in Daramalo Wereda, southern Ethiopia

AbstractAssessing available water and land resources as well as their potential for surface irrigation use is vital for sustainable agricultural development and planning. Agricultural irrigation also plays a crucial role in ensuring food security and reducing poverty in Ethiopia. However, it is dominated by rain‐fed agriculture, with rainfall distribution and intensity vary spatially and temporally. Enhancing agricultural water management and irrigation has the potential to increase agricultural productivity. The objective of the study was to evaluate surface water potential and the irrigation water demand of Zage River sub‐watershed, which were estimated using hydrological model of Soil and Water Assessment Tool (SWAT) and CROPWAT8.0 software, respectively. Slope, soil type, drainage densities, land use/cover, and river proximity were the factors utilized to determine irrigation land suitability. A weighted overlay was completed, with 17.32% of irrigable lands found to be highly suitable, 41.29% moderately suitable, 37.61% marginally suitable, and 3.78% not suitable. The SWAT model result gave very good model performance indicator values of NE = 0.773 and R2 = 0.872 for calibration and NE = 0.771 & R2 = 0.945 for validation. The SWAT model result showed a total of 33.248 million m3 of surface runoff generated annually. Compared with irrigation water demand of 21.068 million m3, this suggests the watershed has high surface water potential for surface irrigation for selected crop types of the watershed. The findings of this research are relevant to improving local water management policies and practices and enable stakeholders to make decisions that enhance agricultural productivity and sustainable agricultural practices and help ensure the food security of local farmers.

SEAs for seas: Strategic environmental assessment for more strategic and environmentally-oriented marine spatial planning processes

The foreseen, and already ongoing, substantial increase in offshore renewable energy and corresponding infrastructures urges policymakers and scholars to carefully consider corresponding long-term environmental effects on the marine environment. Strategic Environmental Assessment (SEA) is becoming a standard tool for Marine Spatial Planning (MSP) processes for enabling planners to develop more sustainable marine spatial plans. To explore how SEA can contribute to a more strategic and environmentally-oriented MSP practice, four SEA processes from four North Sea countries are examined, building on available SEA documents and semi-structured interviews. The results show that SEAs for MSP can take an exploratory or appraisal-oriented approach. Adopting an exploratory approach can open up comparatively more opportunities for SEA to contribute to MSP than an adopting an appraisal-oriented approach, but it requires an early initiation of the SEA within the larger planning process. Still, it does not imply that there is one single best method. Rather, the institutional context establishes the conditions for SEA processes to contribute to MSP practice. Particularly, the political pressures and prior sectoral policymaking for offshore renewable energy restrict what can be included in the scope of an SEA. Also, the limited knowledge on the larger dynamics of the marine environment complicate the assessment of transboundary and cumulative effects. Therefore, as future research continues working towards a robust scientific knowledge base on the marine environment, it is crucial that scholars and policymakers collaborate on a structural basis to bridge the gap between science and policy implementation.

A strategic evaluation of BIM-driven information management in the context of ISO 19650-2 standard

PurposeThis paper presents an in-depth evaluation of BIM-driven information management in the context of ISO 19650-2. The study aimed to understand and evaluate the existing mechanisms and the recommended activities and tasks of collaborative information management, particularly as the Turkish AEC organizations are currently implementing ISO 19650-2.Design/methodology/approachThe study employed a qualitative research design based on information management stages of ISO 19650-2. Semi-structured interviews were conducted with purposefully selected professionals. The framework analyses were made with MAXQDA through conceptual coding to identify current drivers, challenges and incentives for BIM-driven information management. The frequencies of common themes, required tasks and semantic relationships were reported systematically and interpreted to provide a conceptual implementation map, practical insights and actionable recommendations.FindingsThe study results encompass strategies for establishing new tasks and implementation procedures to uphold business value by aligning information management standards with evolving project requirements, providing detailed and responsive EIRs, early use of CDEs, compliant production methods, clarity of roles and responsibilities, increased organizational capacity and capabilities, sustained planning and production quality and leveraging lessons learned.Originality/valueThe study provides evidence-based arguments and strategic insights for BIM-driven information management, focusing on the current implementation compatibilities with ISO 19650-2. Findings and discussions highlight the necessity of industry-wide transformations, reengineered activities/tasks and compliant information flows, which are crucial for adopting ISO 19650-2 and the formulation of national annex documents.