Integration of 5D Building Information Modelling (BIM) into large rail projects has the potential to significantly enhance cost management and control. Nevertheless, 5D-BIM implementation has encountered difficulties stemming from technical, functional, and governance-related factors. This paper builds a conceptual framework to support financial decision-making, enhances project management, and promotes efficient project delivery. The framework encompasses a set of interrelated elements that include project governance, BIM policies and standards, digital platforms, BIM LOD, cost estimation classification, and continuous improvement. The proposed framework acknowledges the significance of project governance in guiding and organizing the implementation of 5D-BIM. Additionally, BIM policies and standards ensure the adherence to quality standards for the produced BIM models. Digital platforms serve as the basis for multiple users to generate, access, share, and exchange project information. BIM LOD promotes collaboration and coordination among all project stakeholders. Cost estimation classification aligns the estimation process with the development of project scope and financial decision-making. Continuous improvement plays a vital role in optimizing processes, enhancing efficiency, and achieving higher-quality outcomes. Moreover, it fosters stakeholder satisfaction, improves project performance, and nurtures a conducive environment for innovation and learning. The study analyses the framework utilization in the Victorian rail projects and identifies key implementation challenges. This can be summed up as follows: The main technical hurdles were the lack of current horizontal infrastructure standards for data exchange and the lack of compatibility with current cost management standards. Increased project complexity and the absence of clear project governance strategies and processes posed organizational challenges. A further validation of the framework in real-world rail projects was recommended to achieve the implementation goals.

Olympic Games have a huge impact on the cities where they are held, both during the actual celebration of the event and before and after it. This study presents a new approach based on spatial analysis, GIS, and data coming from Location Based Social Networks to model the spatiotemporal dimension of impacts associated with the Rio 2016 Olympic Games. Geolocalized data from Twitter are used to analyze the activity pattern of users from two different viewpoints. The first monitors the activity of Twitter users during the event -the arrival of visitors, where they came from, and the use resident and tourist made of different areas of the city. The second assesses the spatiotemporal use of the city by Twitter users before the event, compared to the use during and after the event. The results not only reveal which spaces were the most used while the Games were being held but also changes in the urban dynamics after the Games. Both approaches can be used to assess the impacts of mega-events and to improve the management and allocation of urban resources such as transport and public services infrastructure.

This article aims at presenting the results that were found in the design and implementation of a new management model of Critical Success Factors for improving the effects of research projects. The model was based on the theory of structural equations derived from factor analyses and multiple linear regression models. For achieving the purpose, the authors developed an empirical evidence analysis founded on a literature review in the knowledge area of project management. Afterwards, the process of identification of the CSFs was carried out for a group of research projects launched in Colombia as a result of the application and measurement of an instrument. They were the basis for the development of a structural relationship modeling. Also, this contributed to determine the CSFs that explain the generation of effects of research projects, and the project management execution process from which it can be carried out based on said measurement indicators.

Models come in different forms: visual, arithmetic, mental, physical. The most common type of model is arguably the mental model, which people use to view and interpret the world. A model can be described as a representation of a problem or a situation – a simplified representation. The process of building or developing a model is called modeling. A model once developed by the modeller, can be ‘owned’ by a manager or decision maker. The ideal is to make the model an extension of the user’s ability to think about and analyse problems or situations. When used properly – taking into consideration its limitations – an economic model for a project can provide insight for decision makers, when making the crucial decision to approve a project. An economic model for a liquefied natural gas (LNG) project is shown as an example.

Madrid Nuevo Norte (Madrid New North) is an urban redevelopment program applied in the city of Madrid in Spain. In relevance with this, the aim of this paper is twofold: firstly, the project examines if Nuevo Norte project is aligned with the principles of sustainability. Secondly, the paper investigates the impact of Nuevo Norte on the application of city marketing strategies in Madrid. For that purposes, questionnaires were distributed through Internet in 122 urban developers and planners located in the Spanish capital. The results indicated that overall, Nuevo Norte contributes in the sustainable development of Madrid; however, concerns were identified regarding the budget and the timeline of the project. In addition, NNMP provides significant opportunities to local authorities to implement sustainable city marketing strategies, aiming to improve the competitiveness and the quality of life in the city of Madrid. To this end, it seems that city marketing, through the construction of Mega projects, should sift to sustainability, ensuring a better life for local residents and communities in general. The research is expected to assist local authorities in Spain to harness the potential of mega projects, such as Nuevo Norte, in designing city marketing strategies and to promote Madrid in an international context as a city that gives emphasis in urban sustainability.

Site environments and instrumental characteristics of carbon dioxide (CO₂) measurements operated by local governments in the Kanto Plain, the center of which is Tokyo were summarized for this study. The observation sites were classified into environments of three types: urban, suburban, and woodland. Based on a few decades of accumulated hourly data, the diurnal and seasonal variations of CO₂ concentrations were analyzed as a composite of anomalies from annual means recorded for each site. In urban areas, the highest concentrations appear before midnight in winter. The second peak corresponds to the morning rush hour and strengthening of the inversion layer. Suburban areas can be characterized as having the highest concentration before dawn and the lowest concentration during the daytime in summer in association with the activation of respiration and photosynthesis of vegetation. In these areas, concentration peaks also appear during the morning rush hour. Woodland areas show background features, with the highest concentration in early spring: higher than the global background by about 5 ppmv.

This work shows the preliminary description of the origin of a sedimentary - exhalative outcrop of Jurassic Lower Pliensbachian. The location of this deposit was achieved by applying an examination based in the identification of sedimentary transgressions of heterochronies ages and the identification of a Rift – type mega –structure. According with the methodology, it was carried out a study of the discordant relationships between two types of sediments: continental and marine. According the characterization, it was noted the existence of light rare earths, in values that show positive anomalies in comparison with the distribution of elements in upper continental crust according to the Clarke [1], reflecting so a felsic affinity of the mineral deposit. Also, positive anomalies of platinum and Pd, were determined with marginal contents of Au and Ag; and finally the base metals Zn, Pb and Cu were detected in low contents, which could be due to the presence of altered shale. According to the sedimentary lithology found, which was of siliciclastic type; to the exhalative roots observed during the fieldwork; the presence of quartz minerals such as biotite and muscovite; the presence of minerals of hydrothermal remobilization like chalcopyrite with some base metals, altered shale, as well as sulfur deficiency; this mineral reservoir could be defined as a SEDEX – type.

The role stakeholders play is fundamental to the realisation of sustainable development. Con-sequentially, there is need for the major stakeholders to be fully aware of their respective roles. Thus, this paper focused on assessing the Stakeholders roles in sustainable housing projects in Lagos State, Nigeria. Structured questionnaire survey was used to collect data from 259 stake-holders involved in sustainable housing projects in Lagos State, Nigeria. A total of 203 responses were obtained, representing 78% response rate. Primary data regarding the extent of stakeholders awareness of their roles in sustainable housing were collected. The data collected were analysed using mean ranking analysis and analysis of variance (ANOVA). The data collected were used to determine the extent of awareness of the stakeholders’ role in sustainable housing pro-jects in Lagos State, Nigeria. The results showed that all the stakeholders were aware of their respective roles in the delivery of sustainable housing projects and were highly conscious of them. Although their extent of awareness was at varying levels, there was no statistically significant difference of opinions amongst the different categories of stakeholders in the delivery of sustainable housing projects. The study concluded that Government and Project Managers have key roles to play as major stakeholders in the delivery of sustainable housing projects. The knowledge of the awareness of stakeholders’ roles in the delivery of sustainable housing project provides invaluable information to stakeholders regarding the important roles to focus attention on in achieving sustainable housing projects. The study provides a veritable basis for assessment of sustainable housing project in Lagos State, Nigeria.

This paper presents a study conducted to identify, assess, rank, and compare the most influencing factors causing schedule delay during construction phase of petrochemical projects in Saudi Arabia. The methodology followed in this research to achieve the main aims is a combination of comprehensive review of the literature and interviewing number of local experts, which have resulted in identifying of 23 factors. Through a web-based questionnaire survey, the identified factors were ranked. Total of 90 completed responses were gathered from 106 received responses. The completed responses gathered from 38 contractors and 52 owners. Of 90 participants, there are 32 project managers, 22 project engineers, 7 construction supervisors and the other 31 having different positions in projects departments The study has found that the most influencing factors causing schedule delay during construction in petrochemical projects in Saudi Arabia are “Poor site management and supervision by contractors”; “Conflict between main contractor and subcontractor”; “poor planning and scheduling of projects by contractor”; “Delay of material or equipment delivery”; and followed by “Delay in Handing Over Construction Site to Contractor”. This paper is original in the sense that the areas of knowledge and practice covered in the identified factors were distributed and not available in one source. The factors are derived from personal interviews with selected project managers, project engineers, construction supervisors and the others from different positions in project department and from the relevant literature.

The 2022-2023 Chilean summer showed increased temperatures and similar burned area, compared to the 2016-2017 season, where more than 500,000 hectares were compromised, mainly in the rural areas. After a brief review, it is revealed that the effects of forest fires on soil and hydrological properties are barely debated in Chile. Here, we showed a climatological analysis where temperature records in the 2016-2017 season were unusual, as well as another unexpected increase in the summer of 2022-2023, resulting in high-severity fires known as ‘mega-fires’ or “storm-fires”. Mega-fires affect forest plantations and native forests mainly from 33º S (Maule Region) to 39º S (Los Ríos Region) and they are expected to become frequent due to climate change, moving from the north to the south. We present an overview of the influence of wildfires on soil components in the most affected areas (inland, Coastal, and Andes ranges), their hydrological impacts, and potential erosion risk due to high winter precipitation. We propose several management practices that could help to prevent or mitigate these events, including pre-and post-fire interventions, such as afforestation and seeding, selective logging, mulching, erosion barriers, soil preparation, and dam monitoring. We argue that any effective plan in fire-prone and affected areas should include a combination of actions taken at the hillslope scale at integral ecosystem management, whose effectiveness should be monitored and verified regionally at the watershed scale.

Rural women constitute one of the most marginalized and vulnerable groups in the world. Despite playing a critical role in sustainable development and food security, they face systemic inequalities and structural constraints that limit their access to resources, services and opportunities. The purpose of this research is to identify advances and setbacks in the formulation of 17 SDG indicators for rural women. Systematic Review Registered in PROSPERO: CRD42023420583. Sixteen articles were included. Three indicators were identified: entrepreneurship, empowerment and gender equality. Due to its relevance in rural areas where women have an active role in family income through cooperatives, associations and companies to improve quality of life and that of their community, however, aspects of discrimination are still evident in gender and inequality in participation in economic spheres and decision making.

The construction sector has begun to embrace the digital revolution, intending to improve efficiency. How, on the other hand, should the industry adopt digital tools? And how should the connection between humans and technology function? This study aims to shed light on how the construction sector may bridge the gap between AI deployments’s potential and realized advantages. This article presents research based on a comprehensive review of the literature, case studies of Speller Metcalfe, a design-build and refurbishment project in Malvern, England, Jacobsen Construction, a project digitizing the planning process in Salt Lake City, Utah, USA, and Menkes Development Inc., real-time visibility to construction site insights and data-driven decision-making in Toronto, Canada. The experiences gained via this study show that it is feasible to acquire expertise while adopting sophisticated technologies, such as artificial intelligence, by installing fundamental digital tools (AI). However, when it comes to AI, the level of trust between humans and machines will be the deciding element in its success. This article is a pioneering effort in examining the deployment of AI and how people and technology should interact. This study is limited to three case studies and three digital technologies. To further the study, it is suggested to debate the adaptation of AI on the user's premises, gather more empirical data, and examine case studies from different sectors.

Although South Africa is well known for its incredible biodiversity, targeted efforts are still re-quired to accelerate the discovery and description of the still-unknown species in this floristically mega-diverse country. In addition, new species discovery is a new opportunity for the devel-opment of ethnobotanical knowledge. In the present study, we collected data on current knowledge of plant richness in the country and expert taxonomists’ opinions and used statistical modelling technique to predict what might still be missing in South Africa’s flora. According to experts’ opinions and our modelling, we might be missing 1400-1575 plant species in the country. We predicted that we might take 40-45 years to identify and describe these species and that be-tween 64 and 315 taxonomists will be required. The pool of taxonomists who took part in this study have spent a total of R 680 670 000 (US $40 039 411) to describe 419 species. This implies that, in theory, R 1 624 510.74 (US $95 559) was spent, on average, to describe 1 species. At this rate, R 2 558 604 415.00 (US $150 506 142) would be required to describe the 1575 (modelling) or R 2 274 315 036.00 (US $133 783 237) for the 1400 remaining species (expert opinion) in the current context where both full- and part-time taxonomists are committed to biodiversity assessment in the country. It is important to highlight that this estimate does not correspond to what is required specifically for only species description but does integrate all connected activities, e.g., running cost, bursary, salaries, grants, etc. Furthermore, we must bear in mind that these estimates do not account for the possibility of taxonomic revision which, on its own, needs to be funded, nor do they account for molecular laboratory requirement. However, if we consider that 15% of the predicted funds are spent solely on taxonomic activities, this means that we would need ~R243 673 (US$ 14 334) on 1 species. Overall, our study provides an important figure that can inform policy development including funding and recruitment strategies of taxonomists to fuel efforts towards a comprehensive assessment of the unique South Africa’s biodiversity. The implication of new species discovery is that it opens windows for traditional knowledge development.

One of the most serious concerns about mega event-related changes to small cities is how to effectively utilize newly developed public attractions after the Olympic Games. Making connections with existing local amenities and forming attraction networks can be effective strategies for continuing a city’s revitalization. However, despite the expected benefits, attraction network research shows that these benefits often fail to materialize. With the case of Gangneung, a 2018 winter Olympic hosting city, this study investigated visitation patterns to nineteen selected attractions using network analysis. The results indicate that the most influential nodes are located on the northern coast, the eastern coast, and in the south downtown area, those nodes being the central locations where the strongest of connections are made. New attractions such as the Olympic Park and Walwha Linear Park were rather isolated. While seasonal and periodic variations, visitors’ residences, and destination choice attitudes had a significant effect on visitation patterns, the attraction networks, modes of transportation, proximity to region, and type similarity were not significant factors in the forming of visitation patterns. The results make a methodological contribution to tourist behavior and network research. In addition, beyond individual attraction development, the results provide practical implications in regard to networking and cooperation between multiple attractions using temporal and spatial strategies such as management/investment prioritizing, travel route development, and program scheduling.

The research paper comprehensively and consistently addresses all relevant theoretical areas related to the topic and includes an extensive empirical analysis of the absorption of EU funds and their impact on the sustainable development of Croatia, Slovenia, Hungary, and Poland. The analysis aims to investigate the efficiency of the absorption of funds from the EU, the impact of these funds on regional development of countries, as well as the reasons for such impacts. The "Regional Development Model Based on EU Funds" was tested with the aim of applying the model to the Republic of Croatia, countries in the region, and other European countries to achieve a higher level of absorption of financial resources from the available EU funds. Data for the empirical analysis were collected using a highly structured survey questionnaire on a sample of 244 respondents involved in the preparation and implementation of EU-funded projects. The contribution of economic science in theoretical terms arises from the development of scientific knowledge and ideas about the importance of increasing the number of development projects that will increase the absorption of funds from the European Union, thereby increasing economic activities in Croatia and the region. The expected contribution of economic science in the applied sense is based on the formulation of the "Regional Development Model Based on EU Funds," which is based on the application of knowledge, good practices, and stakeholder experiences, considering relevant indicators from available sources. The greatest contribution is demonstrated through testing the "Regional Development Model Based on EU Funds," which is applicable to the Republic of Croatia, countries in the region, and other European countries over a longer period. Finally, research of the impact of EU funds on the regional development of recipient countries is considerably less represented and very modest, only in the "upswing" of systematic scientific research. The research aims to fill the gaps in research and encourage thinking of key stakeholders responsible for regional development, who should eventually realize the importance of defining a regional policy aimed at EU funds as a key to regional development and reducing regional disparities within countries.

Student project management is becoming increasingly important in various settings such as technical clubs, planning clubs, and research laboratories. However, effective methodologies for managing student-led projects have not yet been established. This study aims to address key issues related to cost and motivation in student-led projects and propose effective improvement plans. The significance of this study lies in its potential to identify challenges faced in current student project management practices and offer solutions to mitigate risks. By sharing our findings, we aim to encourage further research on this topic and promote the adoption of effective methodologies for managing student-led projects.

Rural environment has experienced changes as a result of Covid-19, which encourage the introduction of sustainability in education. However, the representation of rurality in school geography and in the 2030 Agenda are factors that continue to present rurality as a concept opposed to urban spaces. The objective was to investigate the perception that the student has about the rural environment from an instrument and his drawings to understand if the explanation of it allows to introduce elements related to sustainability in educational projects. The quantitative research approach allows analyzing the psychometric properties of an instrument to measure the perception of the rural environment of a sample of 300 fifteen-year-old students from Brazil, Colombia and Spain. Those school knowledges that idealize rurality warn of the pedagogical difficulties to promote the teaching of rurality from sustainability criteria and condition the formation of students from a citizenship committed to social problems. This study is important because it diagnoses the elements that intervene in the teaching of rurality from school geography and provides some suggestions to include sustainability in educational projects.

Sustainable development is inconceivable without healthy real estate market. A housing project can be regarded as sustainable only when all the dimensions of sustainability (environmental, economic, and social) are dealt with. There has been an increased interest in using sustainability indicators for evaluating the impacts of the new development projects. Past and recent experiences have shown that sustainability indicators can be useful tools for measuring the outcomes of new construction, when used appropriately and adequately. The aim of this article is to propose an integrated, hierarchically structured system of sustainability indicators to be used for assessment of the new housing development projects in the Baltic States. This aim is achieved through accomplishing three objectives. First, based on a review of literature related to assessing building project performance and sustainable development in construction, the paper proposes a hierarchically structured system of sustainability indicators. Second, based on a survey of experts from the Baltic States, significances of criteria are estimated by the Analytic Hierarchy Process (AHP) method. Finally, paper proposes recommendations to government authorities and real estate developers as to how to enhance the performance of new residential projects according to the principles of sustainability.

Context: Despite the effort put into developing standards for structuring construction cost, and the strong interest into the field. Most construction companies still perform the process of data gathering and processing manually. That provokes inconsistencies, different criteria when classifying, misclassifications, and the process becomes very time-consuming, particularly on big projects. Additionally, the lack of standardization makes very difficult the cost estimation and comparison tasks. Objective: To create a method to extract and organize construction cost and quantity data into a consistent format and structure, to enable rapid and reliable digital comparison of the content. Method: The approach consists of a two-step method: Firstly, the system implements data mining to review the input document and determine how it is structured based on the position, format, sequence, and content of descriptive and quantitative data. Secondly, the extracted data is processed and classified with a combination of data science and experts’ knowledge to fit a common format. Results: A big variety of information coming from real historical projects has been successfully extracted and processed into a common format with 97.5% of accuracy, using a subset of 5770 assets located on 18 different files, building a solid base for analysis and comparison. Conclusion: A robust and accurate method was developed for extracting hierarchical project cost data to a common machine-readable format to enable rapid and reliable comparison and benchmarking.

Space syntax can be potentially applied for the evaluation of quality of user flows particularly in solving problems of sustainable projects in spaces intended for users to move around. This study aims to analyze the concepts of pedestrian flows (open and closed) by space syntax based bibli-ographical approach on a global scale, demonstrating the capability of improvements in Sus-tainable Development Goals (SDGs) as applied to the architecture of sustainable flows. Scopus theoretical reference bases were used, which are directly related to the theme of space syntax in open and closed spaces. Frequency analyzes were carried out, applying the content analysis, to identify words with a degree of similarity, related to “space syntax: flow in urban environ-ments” and “space syntax in closed built systems”, in relations to the SDGs. The results show that pedestrian flows identified in the literature aid to understand the global production on space syntax in open and closed spaces, directed to user flows in the built environment, where many environments of flows in the built space analyzed become unsustainable because they do not present full flow efficiency. In our study on space syntax, the following central terms were identified: pedestrian movements (open urban systems) and space (closed built systems), which allows a better understanding of the flows, highlighting the importance of the urbanist architect on the functionality of user flows in sustainable architectural projects on a global scale. The most frequent categories for open environments were the terms space and form and for closed envi-ronments were space and flow.

The move to lean construction is a lengthy process that may call into question established ways of construction management delivery. The objective of this article is to help businesses take the first step on this route by introducing a few lean manufacturing techniques and practices that may be used on projects over the next few weeks. Although the construction industry has come a long way since its start, the essential technology to change it has not yet found a home. The digital switch has now entered the construction industry to boost production. Artificial intelligence (AI) is a discipline of computer science described as the potential of machines to mimic intelligent human behavior by modelling traditionally complicated problems using human-inspired techniques. Due to its complexity, AI distinguishes itself from lower degrees of digitalization. The complexity of artificial intelligence involves the formation of new circumstances for human collaboration and trust. This dissertation investigates the application of artificial intelligence and the suitable interaction between humans and AI-based technologies. This study attempts to shed light on how the construction industry may close the gap between the potential and actual benefits of artificial intelligence deployment. Comparing the prospective benefits of AI implementation to the present benefits and challenges of AI deployment in the construction industry revealed the disparity.

The comfort of human life depends on the quality, size, and reliability of the infrastructure projects. In the infrastructure systems, rapid growth is found, where the economic and sustainable impact has become a topic of significant concern for policies and government officials. To achieve con-straints of sustainable development, all the policies and actions over the infrastructure project's life cycle must be assessed. Decision-makers have adopted approaches for economic, social, and en-vironmental initiatives through Life Cycle Assessment (LCA) and Life Cycle Cost Analyses (LCCA) of infrastructure projects. The purpose of this review is to highlight the impact of per-forming LCA and LCCA in infrastructure projects. To achieve this goal, a systematic literature review methodology is adopted in which renowned databases, i.e., Web of Science, Science Direct, Emerald and Scopus were selected to extract the relevant literature. Using the PRISMA approach, 1251 publications were identified which were then filtered and 55 documents were included in the final review. In the extracted publications most, researchers were biased toward LCA and LCA individually, whereas few focused on integrated LCA and LCCA. The researchers assessed the costs and impact associated with the infrastructure project while there were less focused on the environmental cost. Besides this, techniques of economic, social, and environmental growth of infrastructure projects have been emphasized during the design phase because of substantial relations between infrastructure design and operation management. Moreover, a conceptual framework has been developed that will assist the decision-makers to consider the effects of LCA and LCCA on various aspects of the infrastructure project and how it impacts sustainability. In the last, a case study was performed to assess the developed framework with the incorporation of environmental impact cost.

Public-private partnership (PPP) is a prominent tool for sustainable infrastructure development. However, the positive contributions of PPPs towards attainment of sustainable, climate resilience and zero carbon infrastructure projects are hampered by poor financial risk management. This problem is more prevalent in developing countries like Ghana where private investment inflow has plummeted due to COVID-19 recession and poor project performance. Thus, this study aims at assessing the key financial risk management strategies in ensuring sustainable PPP infrastructure projects in Ghana. The study utilised primary data from PPP practitioners in Ghana solicited through survey questionnaires. Factor analysis, mean scores and fuzzy synthetic analysis are the data analysis techniques for this study. The results revealed sustainable and green funding models, effective cost reduction initiatives, competent team with committed leadership, and emerging technologies and regulations constitute the key strategies to manage financial risks of sustainable PPP infrastructure projects. Although, future studies must expand the scope of data gathering, the findings of the study enrichen the theoretical understanding of financial risks in sustainable investments in PPP infrastructures. Relevant remedies that will aid the development of practical financial risk management guidelines are provided in this study for PPP practitioners.

This comprehensive article explores the intricate responsibilities of executives leading AI projects within the framework of Federal Directives, specifically Executive Order 14110 and Executive Order 14091. The executive role is dissected, covering aspects such as defining leadership in the AI context, historical perspectives, current trends, and challenges in AI project leadership. The article delves into the significance of Federal Directives, particularly Executive Order 14110, which emphasizes safe, secure, and trustworthy AI development, and Executive Order 14091, focusing on racial equity and support for underserved communities. Key provisions of these orders are outlined, including safe AI development, secure AI implementation, trustworthy AI use, and commitments to racial equity. The article also highlights steps that should guide documenting case studies that align with successful AI projects, showcasing compliance with Executive Orders and positive impacts on communities and organizations. The future outlook focuses on anticipating regulatory changes, adapting to evolving ethical standards, and promoting a culture of continuous improvement within AI projects. The conclusion summarizes executive responsibilities, emphasizing the call to action for ethical and inclusive AI leadership, contributing to the positive evolution of AI technologies for societal well-being.

Under the development mode of deep blending of emerging technologies, major projects are important for enhancing China's comprehensive national strength and independent innovation capability. Based on the social benefits of major projects, and considering the influence of reputation factors, an evolutionary game model composed of a general contractor and subcontractor of major projects is established. This paper studies the influence of various factors including the income distribution coefficient of collaborative innovation, and MATLAB simulation software is analyzed the influence of factors on an evolutionary path. The results show that a reasonable income distribution coefficient can promote the game behavior of both parties to the direction of active collaborative innovation; The reduction of innovation cost and the improvement of spillover technology absorption capacity can make innovation subjects tend to choose active collaborative innovation strategies. In addition, reputation loss above a specific threshold can effectively inhibit free-riding behavior and encourage innovation subjects to choose active collaborative innovation strategies. The research results provide reference for promoting major projects' technology innovation.

Many pilot-based initiatives have been developed to promote awareness and use of climate information services among vulnerable smallholder farmers in Africa through million-dollar investments. However, despite their experimental nature, these pilot projects have been successful in raising participating farmers’ awareness and use of climate information services and they can inform transferrable good practices. Through a systematic literature review approach, this review sought to understand ways in which these past pilot projects have contributed to climate risk management in the context of smallholder farming and the factors that led to their success. Results showed that climate information services main contribution to climate risk management has been through facilitating farm level decision making. Factors that led to success of the pilots include: use of downscaled information; building institutional partnerships to add value to climate information; involving farmers through the co-designing and co-developing process; face-to-face way of communication; embedding pre-seasonal workshops in the activities of local institutions for sustainability; using diversity of communication channels to enhance reach among others. These factors can be borrowed as good practices to inform future efforts focused on increasing adoption of climate information services among a wider population beyond pilot project reach.

In the contemporary construction management, poor project performance, cost overrun, and low-quality construction have become a central point of attention for improving project performance including information, interaction and communication management. virtual design and construction and building information modelling play indispensable role in improving the project performance. The aim of this study is to propose a Virtual Information Modeling as a novel information and communication technology method with potential to overcome problems in the construction industry. Using one-sample t test with Kolmogorov-Smirnov approach, we analysed data collected from structured questionnaire survey involving project managers working at architecture, engineering and construction industries in Tehran, Iran. The results suggest that the most important benefits and challenges of using Virtual Information Modeling are related to the area of integration, and implementation of Virtual Information Modeling has the greatest impact on this area of project management knowledge. Thus, integration should be considered a top priority for construction companies implementing Virtual Information Modeling in their projects. Policymakers should understand that careful management of virtual information is essential for improving the performance of projects and enhancing the process efficiency.

Abstract: Interface risks are inherent in every construction project from start to finish. Identifying and managing these risks effectively in every project phase is crucial for actualising project objectives. This paper shows a comprehensive framework showing several relationships between project stakeholders and how the interface risks between them that influence project execution are identified and managed for the overall construction project success. Firstly, literature review on interfaces and interface risks were car-ried out and how organisations managed interface risks were discussed and secondly, the collection of quantitative data was conducted by means of structured online questionnaires. The sample consisted of 205 construction project professionals who were selected randomly. This group included individuals with various roles in the construction industry, The data was analysed using descriptive statistical methods, including factor analysis, reliability assessment, and calculations of frequencies and percentages. Finally, the results showed all the factors, work culture and organisational approaches that influence interface risk management and ways to identify and manage interface risks effectively.

Objectives: This study aimed to analyze the awareness of local residents regarding healthcare projects and to suggest some ideas for the revision of local ones. Methods: To delve into the opinions of local residents, the author of this study created a questionnaire composed of eight questions on the general characteristics of the respondents, eight questions on satisfaction with health centers, 16 questions on the awareness of healthcare projects, and 22 questions on local healthcare. The survey was conducted for 409 residents who visited public centers in Gimcheon from 15 March to 14 April 2021. Results: Data analysis revealed the following: The proportion of local residents who use health centers was 39.1%, and those users visit health centers, on average, 3.92 times a year. Among healthcare projects, the project known by the highest proportion of people was vaccinations (84.5%), which was also the project that was most used (38.1%). Among healthcare projects needed in the with-COVID-19 age, respondents awarded the highest score to vaccinations (4.15 points on a five-point Likert scale) and the second highest score to infectious disease management (4.12). Conclusions: For healthcare projects, central and local governments should focus on activating vaccinations, solving the problem of medical accessibility through untact remote treatment and establishing national infectious disease-specializing hospitals and local infectious disease management based on such national hospitals.

This research is aimed at evaluating two different scenarios, firstly, appraising the impacts of employing the concepts of Total Quality Management (TQM) to the construction projects in Saudi Arabia. The results of the study were obtained through utilization of a descriptive analytical approach, where 300 questionnaires were distributed to engineering firms and companies with a response rate of 200 questionnaires, hence achieving the study sample for this research. The data gathered was analyzed by applying the Statistical Package for Social Science (SPSS) program and calculating the Relative importance index (RII) and the mean values. From the research conducted, the outcomes showed that the management’s ability to commit using TQM while applying BIM obtained a relative importance of (0.717), while the relative importance for the management’s ability to commit using TQM without the application of BIM is (0.552). The results showed that construction projects in Saudi Arabia still sustain setbacks from applying TQM concepts and suffer from the lack of administrative, scientific and technical applications. In a second scenario, a hybridized support vector regression (SVR) Harris-hawks optimization (HHO) (i.e., SVR-HHO) were used to predict the TQM. The performance accuracy of the models was checked through three different evaluation metrics namely; mean square error (MSE), correlation co-efficient (CC) and Nash-Sutcliffe efficiency (NSE). the hybridized emerging SVR-HHO outperformed the other two data driven approaches in both the training and testing stages based on the employed evaluation metrics. Overall, the obtained results showed that both the machine learning and metaheuristic approaches were capable of predicting TQM.

The paradigm that assumes the autonomous management of universities involves them in the redefinition of their policies and processes and the training of their staff, designing new formulas that allow them to adapt to a changing environment. In this context, research and sustainable universities can link with society to solve its problems and influence a responsible and sustainable development. Through a Delphi panel, importance to acquire and improve project management (PM) competences by teaching and research staff (TRS) into innovating education and research projects is measured, from the standard of individual competences (ICB4) of the International Project Management Association (IPMA). Also, internal data sources from the flexible structures of two Spanish universities (the University of Cadiz (UCA) and the Technical University of Madrid (UPM)), are investigated, in order to analyze how they are organized. Thanks to the study of cases, an increasing tendency to work by projects is observed, empowering teams, managing properly stakeholders and facilitating their functions towards society. Likewise, after two rounds of experts’ consultation, consensus is reached with an acceptable and stable level of responses, resulting in confirmation that there is alignment between IPMA competences and TRS’ needs for sustained success in education and research, contributing to universities’ development, improvement and sustainability.

As an important support for power system with high penetration of renewable energy, energy storage system (ESS) has changed the traditional model of simultaneous implementation of electricity production and consumption, and its installed capacity under the source-grid-load scenario is rising year by year, but it faces the problems of insufficient utilization and benefits. This study analyzes the functional combination of ESS under the source-grid-load scenarios, and proposes a comprehensive benefit evaluation method of energy storage projects based on fuzzy decision-making trial and evaluation laboratory (DEMATEL) and super efficiency data envelopment analysis (DEA) model, which considers the perspective of economic and social environment. Firstly, the functional requirements of energy storage on the source-grid-load scenarios are explored respectively, and the characteristics of various functions are analyzed to form functional combination schemes. Secondly, index modeling is carried out from three aspects: the whole life cycle cost, functional combination benefit and social environmental benefit, and the comprehensive benefit evaluation index system of energy storage project is proposed, which includes both economic and social environment. Then, the intuitionistic trapezoidal fuzzy number is combined with DEMATEL to form an effective analysis method for the input-output relationship of the indexes, and the comprehensive evaluation is realized based on the super efficiency DEA model. Finally, the effectiveness of the proposed evaluation method and the rationality of the functional combination are verified under source-grid-load scenarios respectively.

The rapidly evolving field of artificial intelligence (AI) continues to witness the introduction of innovative open-source pre-trained models, fostering advancements in various applications. One such model is Llama 2, an open-source pre-trained model released by Meta, which has garnered significant attention among early adopters. In addition to exploring the foundational elements of the Llama v2 model, this paper investigates how these early adopters leverage the capabilities of Llama 2 in their AI projects. Through a qualitative study, we delve into the perspectives, experiences, and strategies employed by early adopters to leverage Llama 2's capabilities. For the purpose of data analysis, the capabilities inherent in the Llama 2 model were employed to conduct keyword extraction from the context of the early adopters' case studies. The findings shed light on the model's strengths, weaknesses, and areas of improvement, offering valuable insights for the AI community and Meta to enhance future model iterations. Additionally, we discuss the implications of Llama 2's adoption on the broader open-source AI landscape, addressing challenges and opportunities for developers and researchers in the pursuit of cutting-edge AI solutions. The present study constitutes an early exploration of the Llama 2 pre-trained model, holding promise as a foundational basis for forthcoming research investigations.

The paper combines two new original concepts about eco-energetic systems. The first one is related to the M.E.N. (Mega-Eco-Nega-Watt) paradigm, which is based on three different but complementary ecological economic spaces: MEGAWATT, as needed energy, ECOWATT, as ecological energy, and NEGAWATT, as preserved energy, even the renewable energies and technologies, in the context of electrical energy production. The second concept presented in this paper is the eco-energetic efficiency, introduced in order to facilitate a correlation between the energetic efficiency of the system and a necessary, new defined ecological coefficient. The proposed formula for eco-energetic efficiency enables an interesting form of reporting to the different situations in which the input energy, output energy, lost energy and externalities, involved in an energetic process interact to produce energy in a specific energetic system, in connection with the circular economy model. Finally, is presented an original diagram of the energetic chains to produce electricity in a resilience regim, with high eco-energetic efficiency from originating in different primary energetic sources as external (gravitation & solar sources), fuels (classical & radioactive), internal sources and others. Even what kind of energetic sources are used to obtain electricity, as coals, gas, wood, hydropower, nuclear power, wind power, biomass, solar systems, and others, the entire process should be sustainable in what is the transdisciplinary integration of the different representative spheres as energy, socio-economy, ecology (environment), with the main core, sustainable education, inclueding the law and administrative aspects, as necessary fields of the knowledge based society/economy.

The purpose of this study is to analyze the causes of cost variation in natural disaster prevention projects (NDPP) in Gyeongsangbuk-do and to develop effective cost and risk management strategies. The study collected data by conducting an online survey of 244 stakeholders. Binary logistic regression was used to analyze the impact of various variables on cost deviation, in-cluding project management risk (PMR), project costing and execution risk (PCER), project exe-cution strategy risk (PESR), construction project risk (CPR), project cost and schedule risk (PCSR), project management challenges (PMC), and construction project subcontractor and safety man-agement (CPSSM). The results showed that PMR (OR=3.744, 95% C.I. [1.657, 8.457]), PCER (OR=5.068, 95% C.I. [2.236, 11.484]), PESR (OR=3.447, 95% C.I. [1. 853, 6.413]), CPR (OR=2.292, 95% C.I. [1.020, 5.151]), PCSR (OR=4.817, 95% C.I. [2.250, 10.317]), PMC (OR=2.954, 95% C.I. [1.452, 6. 013]), and CPSSM (OR=2.419, 95% C.I. [1.297, 4.515]) had statistically significant effects on cost deviation. In particular, PMR, PCER, and PESR were identified as the main causes, and the effects of additional factors such as CPSSM were also important. The developed predictive model plays an important role in helping stakeholders of NDPP to manage risks in advance and take appro-priate preventive measures to ensure the success of the project. This study empirically supports the theoretical hypotheses of previous studies and provides a clear understanding of the causes of cost deviation in NDPP, which provides important insights for strategic decision-making and provides a new perspective on risk management.

In the context of developing machine learning models, until and unless we have the required data engineering and machine learning development competencies as well as the time to train and test different machine learning models and tune their hyperparameters, it is worth trying out the automatic machine learning features provided by several cloud-based and cloud-agnostic platforms. This paper explores the possibility of generating automatic machine learning models with low-code experience. We have developed criteria to compare different machine learning platforms for generating automatic machine learning models and presenting their results. Thereafter, lessons learned by developing automatic machine learning models from a sample dataset across four different machine learning platforms were elucidated. We have also interviewed machine learning experts to conceptualize their domain-specific problems that automatic machine learning platforms could address. Results showed that automatic machine learning platforms could provide a fast track for organizations seeking digitalization of their businesses. Automatic machine learning platforms help produce results, especially for time-constrained projects where resources are lacking. The contribution of this paper is in the form of a lab experiment in which we demonstrate how low-code platforms could provide a viable option to many business cases and henceforth provide a lane that is faster than the usual hiring and training of already scarce data scientists and to analytics projects that suffer from overruns.

The purpose of this article is to disclose the architectural proportions and nature of the Korean national treasure in Seokguram Grotto, Gyeongju. The authors compare its features with those of other ancient hypogeal or ashlar constructions and intend to rediscover its relevant hidden configuration and latent structural properties to show its uniqueness. The methods employed in the research belong initially to architectural design and composition to advance at a later stage, into the nuances of stone masonry, lighting effects or cohesive construction. In this discussion and thorough analysis, different philosophical and scientific subtleties come afloat. The results demonstrate a significant potential capable to be applied in part to recent architectural developments like Tadao Ando’s Buddha Hill in Hokkaido (2017) and the authors’ own project for a Buddhist monument.

Failure to meet the deadlines for the implementation of investment and construction projects is a problem in all countries of the world, and leads to unstable activity of construction companies. The article studies the most important destabilizing factors affecting the main indicator of sustainable activity of construction companies-the duration of the implementation of an investment and construction projects. To determine and assess the impact of destabilizing factors on the duration of implementation of selected investment and construction projects, a survey was conducted, in which a number of customers, consultants and contractors involved in construction projects took part. Questionnaires developed on the basis of a cluster sample were sent to respondents, 48 responses were received in response to the assessment of destabilizing factors. To analyze the received and grouped information, structural equation modeling using the Smart-PLS program was used. As a result of modeling, a number of results were obtained, the most important of which are the identification of the main reasons that lead to an average (20% - 50%) increase in the duration of projects in the construction sector. The most significant were: the lack of an appropriate procurement program for materials; inefficient scheduling by contractors and instability of construction production; poor-quality processing of incoming information and untimely deci-sion-making due to changes in projects during their implementation. Destabilizing factors con-tribute to an increase in the duration of construction sector projects, which leads to time overruns, cost overruns, and an increase in the negative impact on the overall use of resources. As a result of the study, a set of recommendations was formed, the most important of which is the use of possible compensatory measures that can allow construction companies to eliminate the risks of disrupting construction deadlines for sustainable activities. These compensatory measures include: - recommendations to customers of the construction project; - recommendations to contractors; - recommendations to the consultant. Moreover, the control of destabilizing factors that can cause delays, the improvement of contracts and the precise and clearer definition of all elements of the project can help to reduce the duration of construction, and will allow companies to maintain sustainable activities in the construction industry.

Design changes seem inevitable in engineering, procurement and construction EPC projects. Such changes create a need for a proactive approach to adjusting project scope, cost and time (the triple constraints) for efficiency and effectiveness in overall delivery. This study investigates the causes and implications of design changes in order to improve design change management practices. Data for the study was obtained through online interviews with New Zealand industry practitioners. Thematic analysis was used to collate the results into meaningful data. The study found that design changes were predominantly caused by clients' inadequate strategic planning, insufficient attention to design, EPC contractors' inadequate design ability, and on-site variations. There were three categories of such design changes: direct impact on the project, the reciprocal and complementary effect on stakeholders, and the far-reaching impact on the community. The study concludes by suggesting improvements, such as strengthening the integration of project teams to enhance design quality, strategic alignment of stakeholders at the planning stage, early contractor involvement (ECI) between the planning and design phases, and improving collaboration between design and construction teams. Further, a combination of high technical skills (e.g. design ability) and soft skills (can-do attitude, interpersonal skills, problem-solving skills, documentation skills, etc.) are needed to effect the desired improvement in design change management.

Accurate and stable cost forecasting of substation projects is of great significance to ensure the economic construction and sustainable operation of power engineering projects. In this paper, a forecasting model based on the improved least squares support vector machine (ILSSVM) optimized by wolf pack algorithm(WPA) is proposed to improve the accuracy and stability of the cost forecasting of substation projects. Firstly, the optimal features are selected through the data inconsistency rate (DIR), which helps reduce redundant input vectors. Secondly, the wolf pack algorithm is used to optimize the parameters of the improved least square support vector machine. Lastly, the cost forecasting method of WPA-DIR-ILSSVM is established. In this paper, 88 substation projects in different regions from 2015 to 2017 are chosen to conduct the training tests to verify the validity of the model. The results indicate that the new hybrid WPA-DIR-ILSSVM model presents better accuracy, robustness and generality in cost forecasting of substation projects.

The purpose of this article is to disclose the strenuous efforts of Laszlo Hudec in China and Antonin Raymond in Japan and India to create a modern architectural stance by heralding an incipient space syntax. In the turn of the 19th Century, for dynastic, politic and economic reasons, Eastern Asia had very little modern Architecture. It is a surprising fact that, out of happenstance, two European architects Antonin Raymond and Laszlo Hudec, had to intervene to remedy this situation, to the point of becoming 20th Century icons in Japan and China. Their fruitful careers spanned over thirty years and included locations, like Tamil Nadu or the Philippines. The Oriental territories were not an easy ground for the bold architectural achievements that they produced. Despite of faraway strangeness and uncountable personal losses, in revolutions and wars, which eventually forced them both to leave for the United States of America and never to return, they were successful in the manner of establishing a broad avenue for Modern Asian Architecture which is still recognisable today thanks to their systematic approach. However, theirs is an endangered heritage and the intention of this article is to be a just remembrance of in which way such actions could be performed, how they predated by many years a syntactic approach to architectural composition and why their legacy should be preserved.

Given the context of global climate change, a worldwide increase in land surface temperature (LST) is anticipated, leading to the exacerbation and broadening of its impacts. This could jeopardize the environmental conditions in countries with a predominantly hot and harsh climate, such as Bahrain, one of the Cooperation Countries (GCC) nations. Conversely, Bahrain is currently experiencing significant population growth, leading to a surge in demand for land to accommodate the construction of additional residential developments. This circumstance allows investigation of the potential impact of land use and land cover alterations on the variation in Land Surface Temperature (LST). In order to accomplish this objective, a residential development project was executed within the timeframe spanning from 2013 to 2023. Four sets of Landsat 8 OLI/TIRS remote sensing datasets were selected, with each set corresponding to one of the four climate seasons. Each set consisted of two images: one capturing the study area before the commencement of the development process and the other depicting the study area after the completion of the development. The study area was analyzed by extracting the land surface temperature (LST), normalized difference vegetation index (NDVI), and normalized difference built-up index (NDBI) on various dates. Subsequently, correlation and regression analysis were employed to examine the interrelationships among these three variables. The findings demonstrated a notable rise in the mean land surface temperature throughout the spring and autumn seasons following the conclusion of land development activities. The findings indicate a positive and robust association between LST and NDBI across all seasons. Moreover, this relationship strengthened following the completion of development activities in the area. Conversely, there was a negative correlation between LST and NDVI prior to the region's development, which transformed into a positive relationship post-development. These results provide empirical support for the notion that small-scale residential developments contribute to a notable increase in LST, primarily driven by the expansion of impervious surfaces in built-up areas. The findings can potentially contribute to the formulation of localized adaptation strategies for small-scale residential development projects.