Success by efficient resource planning in a project based environment

Resource planning is a key determinant of the success of community-based projects, yet there is limited consolidated evidence on how its core practices influence project performance. This systematic literature review examines the relationship between resource planning and community-based project performance, focusing on three central constructs: resource identification, resource distribution, and scheduling and budgeting. Drawing on peer-reviewed studies from African contexts, the review examines how effective identification of human, financial, material, and informational resources ensures alignment with community needs. Resource distribution is analyzed in terms of equitable and efficient allocation across project activities, which enhances implementation effectiveness and community satisfaction. Scheduling and budgeting practices are examined for their role in ensuring timely project execution, cost control, and long-term sustainability. Project performance is conceptualized as a multi-dimensional construct encompassing efficiency (time and cost), effectiveness (achievement of project objectives), and sustainability (enduring project impact). The review further highlights the moderating role of community participation, local partnerships, and transparency in planning, which strengthen the relationship between resource planning and project outcomes. Theoretical perspectives from the Resource-Based View, Contingency Theory, and Stakeholder Theory are integrated to explain the mechanisms through which resource planning influences performance. The findings indicate that community-based projects with structured resource planning processes, supported by active stakeholder engagement, demonstrate higher levels of efficiency, effectiveness, and sustainability. A conceptual framework linking resource planning constructs to multi-dimensional project performance under the influence of moderating factors is proposed, providing a foundation for future empirical research and practical decision-making. This review contributes to knowledge on resource management in community-based projects and offers practical guidance for project managers, policymakers, and development practitioners. Keywords: Resource Planning, Community-Based, Project Performance, Africa

Deriving from a critique of the theory of management that has influenced the practice of project management, this article explores an alternative paradigm in the form of systems thinking. The known multi-disciplinary usefulness of systems thinking is proposed as a means of reconsidering project planning, implementation and control, leading to potential implications for the education of project managers. The appropriate selection of systems approaches for use in the planning and control of complex projects in any development sector, including construction, is considered. Although the specific details of any specific ‘process-based’ systems approaches are not presented, the conceptual rationale for such approaches to project planning and control is presented. This is done within a framework of critical consideration of those factors that are argued to contribute to failure to meet key project outcomes, especially in complex projects. Contemporary literature (extensively referred to in this article) increasingly suggests that there are limits to the established ‘rational-oriented’ approaches to project management. The current body of practice knowledge requires the addition of complementary, ‘process-based’ approaches for a new generation of strategic project managers. Specific recommendations for educational development in this regard are made. This article explores the influence of contemporary organisational theory on project management and hence the need to add critically necessary soft skills capacity to the current body of knowledge.

This publication presents a novel approach to predicting the amount of electricity generated by wind power plants. The research focuses on data-driven models such as XGBoost, Liquid Time-constant Networks, and covers both the analysis of properties of individual forecasting models as well as aspects of their integration into a hybrid model. By analyzing real-world weather scenarios, the approach aims to identify the highest accuracy forecasting model for the short-term 24-h forecast of wind farm power output. A more accurate forecast allows for more efficient resource planning and better distribution of resources on the electricity grids, thus ensuring a greener approach to energy production. The study shows that the proposed Hybrid (XGBoost + LTC) model predicts wind power generation with an nMAE of 0.0856, representing an improvement over standalone XGBoost and LTC models, and outperforming classical approaches such as LSTM and statistical models like ARIMAX in terms of forecasting accuracy.

The rapid advancement of artificial intelligence (AI) has brought transformative changes to project management, necessitating a departure from traditional methodologies previously employed in IT project implementations. This paper explores the evolution of project management from conventional IT approaches to the dynamic demands of AI-driven projects. While foundational principles of project management—such as planning, risk management, and stakeholder communication—remain relevant, AI projects introduce unique challenges and require significant adaptations to existing frameworks. The study begins by delineating the characteristics and core principles of traditional IT project management. Traditional methods are characterized by their structured phases, fixed requirements, and a focus on sequential task execution. These principles have been foundational in achieving success in conventional IT projects through detailed planning, rigorous documentation, and predefined quality assurance measures. In contrast, AI projects are distinguished by their reliance on data, iterative development, and high levels of uncertainty. Unique characteristics of AI projects include the need for continuous experimentation, data-driven decision-making, and adaptability to evolving project requirements. The paper identifies key challenges in managing AI projects, such as dealing with data quality issues, ensuring model interpretability, and addressing ethical considerations. To effectively manage AI projects, project managers must adopt new strategies, including Agile and iterative methodologies that support flexibility and continuous feedback. The study emphasizes the importance of cross-functional teams, as AI projects require diverse expertise from data scientists, engineers, and domain specialists. Additionally, handling the inherent uncertainty in AI projects involves fostering a culture of innovation and adaptability. Key differences between traditional IT and AI project management are analyzed, highlighting variations in planning and scoping, risk management, stakeholder communication, and quality assurance. Traditional IT management relies on detailed upfront planning and predictable risk management, whereas AI projects necessitate adaptive planning, dynamic risk assessment, and ongoing model validation. The paper also addresses the transition to AI project management, discussing necessary skill adaptations for project managers, organizational changes to support AI initiatives, and the role of specialized tools and technologies. A hypothetical case study illustrates how traditional IT project management experience can be applied to an AI project, providing insights into practical adaptations and lessons learned. LllLooking forward, the paper explores emerging trends in project management influenced by AI advancements and emphasizes the need for continuous learning and adaptation. The evolving role of project managers in the AI era is examined, underscoring the importance of embracing new methodologies and technologies to stay relevant. While core project management principles remain integral, the shift to AI-driven projects requires substantial modifications to traditional practices. Project managers must evolve their approaches to navigate the complexities of AI projects effectively, ensuring continued success in an increasingly technology-driven landscape.

Private Sector-led Urban Development Projects. Management, Partnerships and Effects in the Netherlands and the UK

In this paper, an overview is given of the project data instances available in the literature to carry out academic research in the field of integrated project management and control. This research field aims at integrating static planning methods and risk analyses with dynamic project control methodologies using the state-of-the-art knowledge from literature and the best practices from the professional project management discipline. Various subtopics of this challenging discipline have been investigated from different angles, each time using project data available in literature, obtained from project data generators or based on a sample of empirical case studies. This paper gives an overall overview of the wide variety of project data that are available and are used in various research publications. It will be shown how the combination of artificial data and empirical data leads to improved knowledge on and deeper insights into the structure and characteristics of projects useful for academic research and professional use. While the artificial data can be best used to test novel ideas under a strict design in a controlled academic environment, empirical data can serve as the necessary validation step to translate the academic research results into practical ideas, aiming at narrowing the bridge between the theoretical knowledge and practical relevance. A summary of the available project data discussed in this paper can be downloaded from http://www.projectmanagement.ugent.be/research/data VIDEO about paper: https://youtu.be/9VESaMeh3nI

The article is a continuation of regular research on project management based on efficient transportation. The purpose of the work is to improve the efficiency of management decision-making in the implementation of projects in transport logistics through the use of automated planning and analysis systems. The object of study is the process of forming organizational support for project management in transport logistics using automated planning and analysis systems for project efficiency. The subject of the study is the practical tools for organizational support of project management in transport logistics using automated systems for planning and analyzing project performance. Methods. In the course of the study, a systematic approach was implemented, general scientific methods were used, including logical analysis, synthesis, induction, deduction, analogy, and modeling. The theoretical and methodological basis of the study is the fundamental provisions of project management, management efficiency theory, scientific works of domestic and foreign scientists on project management at the micro, meso, and macro levels. Given the purpose of the work, several tasks were set and solved, in particular, the applied imperatives of resource and budget planning were outlined on the example of a logistics center based on the Odesa seaport and the project implementation was monitored in Microsoft Project. In terms of resource and budget planning, the expediency of using the method and indicators of the volume utilized is proved. The actual progress of the project against the planned indicators is analyzed. A new project was created using the Microsoft Project software and data entry method. In terms of monitoring, conclusions were drawn on the course of events in the project implementation and the status of implementation by individual types of work was clearly shown. All this made it possible to achieve concrete results. In terms of resource and budget planning, it was determined to what extent there is a deviation from the planned project implementation timeframe. In terms of monitoring, the need to optimize staffing, budget, and time parameters was identified. The essence of this optimization boils down to the decision to attract additional labor resources with the corresponding cost of work per hour. This made it possible to get rid of the conflict and obtain positive dynamics in the project implementation, as evidenced by the date of its completion, which remained unchanged after the resources were equalized. The need to continue the study and focus on project risk management is outlined.

Very few decision markers now dispute the challenges associated with climate change (CC). The world over, CC awareness has risen to undisputed levels and this will continue to be so in the few decades to come. However, challenges still remain in terms of understanding and a need to integrate CC within the context of developmental tools like project planning (PP), disaster risk management (DRM) and environmental evaluation (EE) when dealing with brownfields development. The situation is aggravated by the fact that very few (if at all) professionals involved in decision making and development planning have formal tertiary education and training incorporating the four areas under discussion. Among the decision makers are: the chief executive officers, politicians, town planners, engineers, financiers, economists, project managers and consultants. Times have changed and the business of today requires that decision makers at all levels have adequate knowledge and awareness on the reality of CC and how this must be mainstreamed into decision making tools like PP, DRM and EE. This paper presents theoretical perspectives and conceptualises a framework in which CC could be mainstreamed into PP, DRM and EE – a four-in-one framework when dealing with brownfield issues. The work is a valid information source for the group of practitioners indentified and other interested stakeholders. The paper establishes and concludes that CC issues in brownfield development, particularly mitigation, adaptation and technology can be better addressed through the proposed four-in-one framework. Such a framework is made possible by existing synergies in PP, DRM and EE cycles. This is an aspect that could assist, especially developing countries to move fast towards green, low-carbon economies and be part of the global greening evolution.

A major challenge in Information Systems and Information Technology is to improve the ability to conceptualize, design, develop and deliver information systems that meet customer requirements. Project management is often adopted to create solutions that work and meet customer needs. The principles of project management as defined by the Project Management Institute, can improve project success rates. Researchers in the project management need to help practitioners understanding the impact of different principles on the success of IS development. This study undertakes a survey of project management experts on the state of practice and research to examine the need for improving project management, and suggest areas that can be improved. Research may be the most effective means of defining opportunities for enhancing project success rates by tapping the wealth of literature and complementing it with the expertise of project management practitioners. INTRODUCTION Software development applications require frequent changes and updates in order to support enterprise systems. These frequent changes to IS/IT comprise a large volume of software development efforts. These efforts, undertaken as projects, are generally complex and take place in a dynamic environment where business conditions and technologies change frequently during the life of the project (Chen, et. al., 2004). The factors of project success include user involvement and project size, management and planning (Schmidt, et al., 2001). A fully operational project management system in enterprise offers the best opportunity for project success through the implementation of methods and tools for planning, organizing, and managing team-based activities to accomplish specific directives (Jurison, 1999). Project management is widely adopted in Corporate America embraces project management to implement system changes (Muriithi & Crawford, 2003; Park & Pena-Mora, 2003; Yilmaz & Phillips, 2007), which are even considered as too significant to outsource (Fish & Seydel, 2006) or having high risk of leading to undesirable consequences (Wei & Peach, 2006). However, many projects fail, even when performed using project management techniques. Such project failure reduces the capability of technology components. The 2004 Chaos report by the Standish Group found that only 28% of IT projects were successful, down from 34% in earlier report; The proportion of IT projects canceled before completion increased to 18% (from 15%), and a further 51% of IT projects were considered challenged as they are seriously late, over budget and missing expected features (The Standish Group, 2004; The Standish Group, 2007). Possible causes for these findings are the size and expense of large projects, a return to traditional development practices on large projects (Boddy, 1993), the absence of user involvement (Turner & Cochrane, 1993; Akbulut & Motwani, 2005), and lack of executive support (Munns & Bjeirmi, 1996). Thus, scope management is regarded as a key area of successful project management in practice (Hayes, 2004). Although some project failures are because of technical reasons, most are directly related to the failure of stakeholders to embrace the principles of good project management (Jurison, 1999). As part of the project management process, project teams must understand the standards to which their projects are being held in order to ensure that project performance is emphasized appropriately (Crawford, 2005). The Field Guide to Project Management (Cleland, 2004) suggests that project management should be an easy sell to organizations because it enhances business performance and increases revenue. An organization can manage project effectively by identifying its goals in applying project management principles (Aladwani, 2002). For most organizations, these goals are to apply a proven practice, optimize resources, serve customer needs and save time and money (Turner & Cochrane, 1993). …

Large scale projects increasingly operate in complicated settings whilst drawing on an array of complex data-points, which require precise analysis for accurate control and interventions to mitigate possible project failure. Coupled with a growing tendency to rely on new information systems and processes in change projects, 90% of megaprojects globally fail to achieve their planned objectives. Renewed interest in the concept of Artificial Intelligence (AI) against a backdrop of disruptive technological innovations, seeks to enhance project managers cognitive capacity through the project lifecycle and enhance project excellence. However, despite growing interest there remains limited empirical insights on project managers ability to leverage AI for cognitive load enhancement in complex settings. As such this research adopts an exploratory sequential linear mixed methods approach to address unresolved empirical issues on transient adaptations of AI in complex projects, and the impact on cognitive load enhancement. Initial thematic findings from semi-structured interviews with domain experts, suggest that in order to leverage AI technologies and processes for sustainable cognitive load enhancement with complex data over time, project managers require improved knowledge and access to relevant technologies that mediate data processes in complex projects, but equally reflect application across different project phases. These initial findings support further hypothesis testing through a larger quantitative study incorporating structural equation modelling to examine the relationship between artificial intelligence and project managers cognitive load with project data in complex contexts.

Introduction. Setting the stage. Project management centres on avoinding problems. The invisible project manager. Project management is an emerging profession. Getting the words in the right order. Introduction to project management. What is project management? What is project planning? How do you project plan? Nine steps to a successful project. The scope of the project and its objectives. Defining the project. Changes to the project. Establishing key dates. Evaluation of potential risks. The cost/time/quality triangle. The spectrum of projects. The need for planning. Project planning. The bar chart versus network analysis. Network analysis - a primer. Activity-on-arrow plans. The precedence convention. Choosing the tasks. Drawing up the plan. A fly on the wall. Resource management. Resource definition. Resource allocation. Resource aggregation. Resource aggravation. Resource levelling. Resource smoothing. Resource hierarchies. Resource calendars. Money management. Progress monitoring and control. Concepts. Cost monitoring. Reporting. Computers and other boxes with many buttons. PERT - a potted history. Hardware and software. Types of software. Some words of advice. Advanced critical-path topics. Work breakdown structure and organizational breakdown structure. Merging plans, boiler plating, or task processing. Hammocks. Calendars. Constraint dates. Negative floats. Subprojects. Claims. The people issues. The role of the project manager. The classification of people. Decision making. Motivation. Choosing project-planning software. Hardware. Software criteria. Major software suppliers. Risk management. Qualitative risk. Quantitative risk. Case study: The british library. Contingency and insurance. Terminology Definitions. Alternative definitions. Further reading. Index.

Maximizing reader insights into project management and handling complexity-driven risks, this book explores propagation effects, non-linear consequences, loops, and the emergence of positive properties that may occur over the course of a project. This book presents an introduction to project management and analysis of traditional project management approaches and their limits regarding complexity. It also includes overviews of recent research works about project complexity modelling and management as well as project complexity-driven issues. Moreover, the authors propose their own new approaches, new methodologies and new tools which may be used by project managers and/or researchers and/or students in the management of their projects. These new elements include project complexity definitions and frameworks, multi-criteria approaches for project complexity measurement, advanced methodologies for project management (propagation studies to anticipate potential behaviour of the project, and clustering approaches to improve coordination between project actors) and industrial case studies (automotive industry, civil engineering, railroad industry, performing arts,…) and exercises (with their solutions) which will allow readers to improve and strengthen their knowledge and skills in the management of complex and (thus) risky projects.

Analysis of the characteristics of projects in diverse industries

This scientific article explores the theoretical aspects of team management in the context of different management methodologies and compares the effectiveness of Agile and Waterfall project management methodologies. The study reveals that Agile methodologies are highly effective and provide significant cost savings but are still not widely used in Ukraine. Also, this article compares such methodologies as Scrum, Kanban, Lean, PRINCE2, SIX SIGMA, and Hybrid. The choice of methodology should depend on specific project conditions, such as team size and project complexity. The study presents new insights into the advantages and disadvantages of various approaches to team management. The study finds that teams using the Agile methodology achieve better results on average than teams using the Waterfall methodology. It also shows that using Agile methodologies is more common in small teams than in large ones. As project complexity increases, traditional methods such as Waterfall become more common. Therefore, the article provides a valuable contribution to the field of project management and can be helpful for project managers who are looking for an optimal approach to managing their teams. Purpose of the article. The purpose of this article is to investigate the theoretical aspects of team management in the context of different management methodologies and to compare the effectiveness of these methodologies in Ukraine and other countries. In addition, the paper aims to contribute to the ongoing debate about the benefits of using agile methodologies in project management and to highlight the need for further research in this area. Design/methodology/approach. This article is based on a comprehensive literature review of recent research and publications on team management and project management methodology. Research sources used include scientific journals, conference proceedings, books and online resources. The focus is on comparing and contrasting different approaches to team management across methodologies including Agile, Waterfall and Lean. The study also includes an analysis of empirical data collected during surveys conducted in Ukraine and other countries to determine the most effective team management practices for projects of various sizes and complexities. The research design used in this study is primarily qualitative as the focus is on exploring the theoretical aspects of team management through different management methodologies. However, research also includes a quantitative element, as the analysis of survey data involves the use of statistical methods to identify relationships between variables. Limitations of the study include the sample size of the survey participants and the geographical coverage of the study, which is mainly focused on Ukraine and other European countries. Особистий фінансовий консалтинг: світовий досвід та перспективи розвитку в Україні 141 Findings. The results of this study indicate that Agile methodologies are becoming increasingly popular in software development teams around the world. The study also found that the use of Agile methodologies is more prevalent in smaller teams compared to larger teams. This trend may be due to the fact that smaller teams are more flexible and can adapt more easily to the iterative and collaborative nature of Agile methods. However, the data also suggests that as the complexity of a project increases, the use of Agile methods becomes less prevalent, with more traditional methods such as Waterfall being used instead. In terms of team management, the study found that the use of Agile methodologies can lead to higher levels of team collaboration and communication, which can ultimately lead to more efficient and effective project outcomes. However, it is important to note that effective team management requires more than just the use of a particular methodology, and other factors such as leadership, communication skills, and team dynamics also play a crucial role. Overall, the findings suggest that Agile methodologies can be a powerful tool for software development teams, particularly in smaller teams and less complex projects, but that effective implementation and management are key to achieving success. Originality/value. The originality and value of this study lie in the comprehensive analysis and comparison of different management methodologies in the context of team management. The study presents new insights into the advantages and disadvantages of various approaches to team management and provides practical recommendations for organizations in Ukraine and other countries. Furthermore, the study contributes to the existing body of literature on team management by providing empirical evidence on the effectiveness of different management methodologies. The study also highlights the importance of considering the size and complexity of the project when choosing a management methodology. Overall, the findings of this study can provide valuable guidance for managers and organizations in selecting the most suitable team management methodology for their specific needs and circumstances. Practical implications. The results of this study have practical implications for project managers and team leaders who are responsible for managing teams in different countries with different project sizes and complexities. Research shows that using a specific methodology does not guarantee success in team management and that an individualized approach based on the specific needs of the team and project is more effective. Overall, the practical implications of this study can help project managers improve their team management skills and increase the likelihood of project success.

Recommender system for software project planning one application of revised CBR algorithm