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Background. The relevance of the topic is determined by the importance of ensuring the efficiency of verification and certification work and, in this regard, the need to optimize both the structure of verification departments and the planning of verification work. The purpose of the work is to develop a set of models for the construction аnd functioning of a departmental system of verification bodies, which takes into account the main structural and functional parameters of the system of verification bodies. Materials and methods. The article considers a set of models for the construction and operation of a departmental system of verification bodies, which consists of a number of models: the work distribution model allows one to describe the distribution of verification works in the established stationary mode of operation of the serviced objects and verification bodies; the network planning model allows one to describe the distribution of works in time, and the duration of work on servicing applications; the transport model allows one to describe the planning of methods and routes for delivering batches of measuring instruments to verificationdepartments, or the routes of movement of mobile verification laboratories; the system functioning model allows one to describe the processes of performing verification works in a territorially distributed departmental system of verification bodies with various options for constructing the system, distributing and organizing works; the model of expenses and incomes allows one to describe the processes of resource expenditure with various options for constructing verification bodies and organizing works. Results and conclusions. The use of a set of models will allow one to perform a formalized description of the composition and operation of a territorially distributed departmental system of verification bodies, to determine a set of basic system parameters and quality indicators, as well as the relationships between these sets. The considered set of models can be used in the formation and evaluation of options for constructing verification departments and organizing verification works.

Theory of change has become a common tool in project design because it helps teams agree on hypothesized causal pathways to a desired goal and examine their underlying assumptions. Yet, a consensus has not emerged on the specific steps and components of a theory of change. What constitutes a theory of change? Using 22 theory of change publications, we did a structured analysis of the components of a theory of change. Where there was substantial agreement among the publications on a specific component of a theory of change, we included it in the first iteration of our approach. We then ordered the components in a logical sequence, developed guidance for each component, tested them with project teams, and revised them in an iterative process. We tested and refined our guidance over 3 years with 73 teams from 18 countries. Here, we share our learning and recommendations for those interested in developing a robust theory of change for a conservation project. The authors conducted a structured analysis of 22 publications on theory of change, identifying common components to form the basis of their approach. Over 3 years, they tested and refined this approach with 73 project teams from 18 countries, offering guidance and recommendations for creating effective theories of change. [ABSTRACT FROM AUTHOR]

The article discusses a project in Italy that addressed the issue of hexavalent chromium (Cr(VI)) in groundwater in the province of Piacenza. Due to new regulations, an iterative process was developed to assess the problem, identify treatment technologies, define project priorities, and implement solutions within budget and time constraints. The project included site identification, technology choices, intervention planning, and process improvements, resulting in improved water quality and reduced Cr(VI) levels ahead of regulatory deadlines. The project showcased efficient planning and technology selection for successful implementation. [Extracted from the article]

Traditional teaching methods in construction management education often face challenges in providing students with practical, real-world experiences crucial for skill development. To address these limitations, this study explores the potential of integrating building information modeling (BIM) and virtual reality (VR) as educational tools for construction management students. Our aim is to assess the effectiveness of a 4D-BIM-based VR simulation in enhancing student's learning experiences and performance in construction project management. This research employs a mixed-method approach, combining quantitative data and qualitative insights from a comparative experiment involving undergraduate students. Quantitative data were collected through objective error detection measures in construction sequences and processes, while qualitative insights were gathered from participant feedback. The findings highlight that students using VR-based simulations detected more errors in construction sequences and processes than in traditional 2D drawings, showcasing the utility of BIM and VR-enabled approaches in teaching construction management. This study contributes to the ongoing discourse on integrating advanced technologies into educational practices, particularly in construction management, where practical hands-on experiences are crucial for skill development and real-world application. [ABSTRACT FROM AUTHOR]

Artificial intelligence (AI) has helped enhance the management of software development projects through automation, improving efficiency and enabling project professionals to focus on strategic aspects. Despite its advantages, applying AI in software development project management still faces several challenges. Thus, this study investigates key obstacles to applying artificial intelligence in project management, specifically in the project planning phase. This research systematically reviews the existing literature. The review comprises scientific articles published from 2019 to 2024 and, from the inspected records, 17 papers were analyzed in full-text form. In this review, 10 key barriers were reported and categorized based on the Technology–Organization–Environment (TOE) framework. This review showed that eleven articles reported technological challenges, twelve articles identified organizational challenges, and six articles reported environmental challenges. In addition, this review found that there was relatively little interest in the literature on environmental challenges, compared to organizational and technological barriers. [ABSTRACT FROM AUTHOR]

Artificial intelligence (AI) has helped enhance the management of software development projects through automation, improving efficiency and enabling project professionals to focus on strategic aspects. Despite its advantages, applying AI in software development project management still faces several challenges. Thus, this study investigates key obstacles to applying artificial intelligence in project management, specifically in the project planning phase. This research systematically reviews the existing literature. The review comprises scientific articles published from 2019 to 2024 and, from the inspected records, 17 papers were analyzed in full-text form. In this review, 10 key barriers were reported and categorized based on the Technology–Organization–Environment (TOE) framework. This review showed that eleven articles reported technological challenges, twelve articles identified organizational challenges, and six articles reported environmental challenges. In addition, this review found that there was relatively little interest in the literature on environmental challenges, compared to organizational and technological barriers.

Indonesia is the global coral reef restoration leader by number of projects, yet these remain diverse and disparate. This study reviews the status of Indonesian coral reef restoration within a framework of international common best practice (CBP) that incorporates internationally-recognised Standards for Ecological Restoration (SER). This framework is used to formulate recommendations for a formal network of reef restoration practitioners with the purview to develop and implement a national restoration roadmap. Forty-five projects were surveyed to determine how projects have been planned and implemented. This was compared with recommendations from CBP. There is particular scope to increase quantitative data collection, reinforce community involvement, improve ecological data collection, and standardise monitoring protocols. While 84% of projects reported quantifiable goals, 64% did not quantify goals during planning and 61% did not incorporate climate-smart design features. Quantitative reef monitoring surveys were absent in 22% of projects. The majority of projects did not quantify important ecological metrics like coral community composition/diversity (96%), coral health/bleaching (89%), benthic community (62%), and coral survival (62%). Indonesia has the capacity, regulations, and networks to position itself as a reef restoration driver in the Coral Triangle region; this will require increased coordination, alignment, and quantification of restoration. A structured, collaborative, and iterative national network of various stakeholders would facilitate the development of a national restoration roadmap based on adaptive management strategies. This would aid in standardising project planning, monitoring, and reporting. Efforts should include an increased focus on climate change adaptation goals. [ABSTRACT FROM AUTHOR]

As with many industries, the early life science R&D drug discovery sector is facing growing pressure and higher demands on products in terms of cost, quality, and time‐to‐market. Additionally, the complexity of involved targets and systems, requirements for rapid, safe, and developable candidates are increasing. The drug discovery market, often regarded as rather conservative, relies more and more on advanced technologies. It is therefore a significant task for suppliers to create good solutions that meet customer requirements. The life science industry has a long tradition of using projects as the preferred method to manage these complex systems developments, such as the production of target proteins, screening of compounds, and follow‐up of hit compounds. When applying the project approach, the level of uncertainty is usually high, and the risk of those uncertainties must be managed starting in the early planning phase. Thus, this paper focuses on the issue of how to manage risks in the early project planning phase. We first review state‐of‐the‐art practices in risk management for complex systems project management and identify an important framework, Novelty‐Technology‐Cost‐Pace (NTCP), and apply it to successful risk management for early life science projects. Through an in‐depth case study in the life science industry, we demonstrate a systemic integration of the NTPC framework into project planning. [ABSTRACT FROM AUTHOR]

Additive manufacturing with concrete – guidance for planning and implementation of projects This guideline, created by the DAfStb Working Group "Digital Concrete Construction through Additive Manufacturing," serves as a comprehensive resource to support the planning and implementation of additive manufacturing projects in concrete construction. It is intended for architects, planners, applicants, material manufacturers, construction companies, and other parties involved in construction. After a brief introduction to the classification, terminology, and methods of additive manufacturing, legal aspects and approval procedures are highlighted to ensure seamless integration of this technology into construction practice. The guide addresses the integration of additive manufacturing methods with concrete into construction law, explains the approval process, and offers assistance for coordinating responsibilities in projects. It addresses technical rules for the design and construction of structures, particularly for walls produced by additive manufacturing, and covers constructive aspects of reinforcement. An important component is concrete and component testing, including methods for sample preparation and testing procedures for fresh and hardened concrete, making the guide a useful tool for professionals in the field of digital concrete construction. [ABSTRACT FROM AUTHOR]

Traditional teaching methods in construction management education often face challenges in providing students with practical, real-world experiences crucial for skill development. To address these limitations, this study explores the potential of integrating building information modeling (BIM) and virtual reality (VR) as educational tools for construction management students. Our aim is to assess the effectiveness of a 4D-BIM-based VR simulation in enhancing student’s learning experiences and performance in construction project management. This research employs a mixed-method approach, combining quantitative data and qualitative insights from a comparative experiment involving undergraduate students. Quantitative data were collected through objective error detection measures in construction sequences and processes, while qualitative insights were gathered from participant feedback. The findings highlight that students using VR-based simulations detected more errors in construction sequences and processes than in traditional 2D drawings, showcasing the utility of BIM and VR-enabled approaches in teaching construction management. This study contributes to the ongoing discourse on integrating advanced technologies into educational practices, particularly in construction management, where practical hands-on experiences are crucial for skill development and real-world application.

While the project planning-performance relationship received much attention, the effects of project planning on megaproject performance have not been investigated empirically and little is known about the conditional mediating process between them. This study builds a moderated mediation model to examine the indirect effects of project planning on megaproject performance via process integration and information integration under the contingency of project complexity. 214-megaproject data through a questionnaire survey in China was used to test hypotheses with hierarchical multiple regression and moderated mediation model. Results show that process integration and information integration mediate the positive relationship between project planning and megaproject performance and the mediating effect of process integration is weaker under a higher level of project complexity. This study advances the understanding of project planning-performance relationships considering integration and project complexity. It also offers practical guidance for managers on improving megaproject integration and performance through appropriate planning skills.

The aim of this study was to develop a multi-objective mathematical programming model for the trade-off of time, cost, and quality in the project-scheduling problem (PSP) by taking priorities and resource constraints as well as activity preemption into account. First, a small-sized problem instance that was a sub-project of an oil and gas construction project was used for te validation of the proposed model and algorithm. Subsequently, considering the sensitivity, complexity, and importance of oil and gas projects, the proposed model was implemented in a large-sized oil and gas construction project. Considering the NP-hardness of this problem, the NSGA-II metaheuristic algorithm was used to deal with the time, cost, and quality trade-off problem. Finally, a sensitivity analysis was implemented on the three main parameters of time, cost, and quality to investigate the effects of changes on the results. The findings show that the proposed model is more sensitive to cost changes, so an increase in project costs leads to a drastic change in the values of other objective functions. [ABSTRACT FROM AUTHOR]

Copyright of Revista Ingeniería e Investigación is the property of Universidad Nacional de Colombia, Facultad de Ingenieraia and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This study investigates the impact of change orders on the budgets of 43 public construction projects in the Kingdom of Saudi Arabia (KSA). It addresses the research problem of budget fluctuations in construction projects and aims to understand the causes and consequences of change orders. The research employs a comprehensive methodology involving data analysis from these projects to draw meaningful insights. The major findings of the study indicate that approximately 75 % of the change orders could have been avoided with more effective project planning and management. Owners are found to be responsible for around 40 % of the change orders, emphasizing the need for improved collaboration and communication between project teams and owners during the planning phase. Inexperienced contractors contribute to at least 5 % of the change orders, suggesting the importance of evaluating contractor expertise before project awarding. The study also provides two equations for estimating additional funding or surpluses for public projects, taking into account fluctuations in construction material prices. Moreover, it identifies six critical construction materials and trades, such as thermal and moisture protection, site work, concrete work, conveying systems, electrical work, and mechanical work, which have the most significant impact on project budgets. These insights offer valuable guidance for enhancing project planning, mitigating budget overruns, and optimizing cost efficiency in public construction projects.

There is no significant predictive model that can be used to predict the impact of requirements planning on the success of the residential construction project in literature. The main aim of this research is to find out the impact of requirements planning on the success of the public residential projects in Pakistan. We conducted semi-structured interviews with 29 policy makers in the first part of the study. We also send the questionnaire to 70 construction companies by employing non-probability convenience sampling in the second quantitative part of the study. We received 178 responses. Thematic analysis of the interviews of the policy makers revealed that they define success in terms of project management and product and consider six practices critical for requirements planning. These practices are 1. Advance planning of tracking and reporting of requrements. 2. Configuration Management. 3. Establishment of requirements prioritization process. 4. Use of metrics for performance measurement of requirements. 5. Capturing traceability structure. 6. Clear definition of the roles and responsibilities of the stakeholders who will participate in the requirements management process. We conducted principal component, correlation and regression analyses to analyze the survey responses. The research findings clearly showed that requirements planning positively impacts the success of the project. For the policy makers, requirements planning impacts product success more and for the construction practitioners, it has more impact on the project management success. There is a communication gap between the policy makers and the practitioners. Issues between federal and the provincial governments about land acquisition, political vested interests, project management training issues and the long design phase are the main impediments in the requirements planning. Traditional project management (upfront planning) practices are preferred over agile or lean (incremental planning). [ABSTRACT FROM AUTHOR]

Copyright of Revista Venezolana de Gerencia (RVG) is the property of Revista de Filosofia-Universidad del Zulia and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The techniques employed to manage an industrial project are based on tools that aim to achieve the objectives set by an organization. Most of these techniques consider the development of operative and predictive models. The difficulty in developing project planning models relies on estimating large sets of parameters and the need to include model sections of poorly identifiable, that increase costs and time. This work develops a hybrid forecasting model for all the phases that make up die-casting projects through a series of parameters and sub-models that contemplate the particularities of each case, thereby achieving greater precision in the forecast. The model identifies the cost and time factors that affect project planning, specifically in the die-casting industry, and intends to predict their future behaviour when certain initially given conditions are modified. To estimate the parameters of the hybrid model, several factors in the processes were considered that interact in this industry, such as primary matter costs and activities associated to the process. The considered processes that have a substantial economic impact on the implementation of the project were selected. The criteria for this selection considered identifying the relevant parts of the design and manufacturing in the diecasting industry. Process factors such as the Cost of aluminium and its related activities, whose processes will be grouped into cost and time entities to build a set of metrics that allow better control over them. Finally, the proposed model is based on analytical, parametric, and analog methods that achieve accuracy greater than 85 % in predicting the time and Cost of the process. [ABSTRACT FROM AUTHOR]

Planners face many obstacles during the planning phase of any new project, especially project scheduling due to the numerous details and complexity of each uniquely designed project; previous experience in similar projects and traditional scheduling methods are not sufficient. The 4D-BIM schedule is the best solution, as it can be integrated with other modern technologies such as UAS, which improves project scheduling by allowing the project team to access project plans, details, and time-related information to simulate construction sequences. Despite the benefits of using 4D-BIM, planners prefer traditional planning and scheduling methods because of the barriers to using modern technologies. This research proposes a structural equation model focusing on estimating the weights of BIM barriers in offshore construction projects, including: the investigation of barriers keeping the construction industry standing at 3D-BIM; the relationships between them; and the evaluation of the probability and impact of each, using fuzzy theory. To validate the proposed model, a case study of an offshore project was conducted. The most important latent variables were awareness, risk, demand, and management, while the most prominent observed variables were the uncertainty of the return on investment and the lack of experienced users. This research guides project managers on actions that can be taken for each key variable to enhance and develop the use of 4D-BIM in project scheduling. [ABSTRACT FROM AUTHOR]

The Chinese government is actively pursuing a low-carbon development model with a clear target of reducing carbon dioxide (CO2) emissions by 2030. This study presents a project-based perspective on CO2 emissions from the industrial sector in the city. The article quantifies and analyzes the project planning by including the entire gross industrial production value, industrial structure, energy intensity, energy structure, and CO2 emission coefficient of the industrial sector's CO2 emissions decomposition model. Monte Carlo simulation and scenario analysis were coupled to evaluate how the city's industrial sector could achieve its peak carbon targets by industry. The expected range of CO2 emissions from the city's industrial sector in 2025, 2030, and 2035, based on the project plan and policies in place, is projected to be between 65.64 and 69.26 Mt, 72.13–78.48 Mt, and 69.32–76.62 Mt. However, the simulations show that there are still considerable uncertainties in reaching the peak carbon target in 2030, necessitating greater government efforts. To achieve the 2030 goal for the city's industrial sector, the paper recommends that the government increase the baseline criteria for industrial structure, energy intensity, and energy structure. This study provides scientific project planning guidance for Chinese cities to successfully achieve the 2030 goal.