derhan/semantic-scholar-manajemen-proyek huggingface dataset:
Comparing advanced and traditional machine learning algorithms for construction duration prediction: a case study of Addis Ababa’s public sector
Authors: Soreti Merga Liben; Belachew Asteray Asteray Demiss; W. Elsaigh
Year: 2024


 Accurate prediction of construction durations is crucial for effective project management, particularly in rapidly urbanizing areas such as Addis Ababa. However, there exists a notable research gap regarding the comparative analysis of advanced machine learning (ML) algorithms against traditional methods. This study aims to develop and evaluate various advanced ML algorithms to predict construction completion times in Addis Ababa, with the goal of improving resource allocation and enhancing client satisfaction. Data were collected through surveys administered to multiple construction organizations within the city, which served as the foundation for training, validating, and comparing a range of ML models. The research utilized the caret package in R for model development and assessment, incorporating methodologies such as artificial neural networks (NN), Random Forest (RF), Support Vector Machine (SVM), K-Nearest Neighbors (KNN), and Classification and Regression Trees (CART). To evaluate variable importance, multivariate visualizations, including correlation and scatter plot matrices, were employed, while performance metrics such as mean absolute error (MAE), root mean square error (RMSE), and R-squared (R²) were utilized for model comparison. The findings indicated that the RF model achieved an RMSE of 74 days and an R² of 0.97, while the KNN model also demonstrated strong performance with an RMSE of 81 days and an R² of 0.97, marking them as the most accurate models for predicting construction durations. In contrast, the NN model exhibited subpar performance, likely due to constraints related to training data and variable selection. As a result, the RF model was further optimized to improve its predictive accuracy. The study concludes that while the RF model proves to be highly effective for predicting construction durations in Addis Ababa, there is a critical need to expand the dataset and incorporate additional variables to enhance the performance of deep learning and other ML algorithms in this field.
Reducing preventable harm: observations on minimizing bloodstream infections.
Authors: P. Pronovost; Sally Weaver; S. Berenholtz; L. Lubomski; L. Maragakis; Jill Marsteller; J. Pham; Melinda D. Sawyer; D. Thompson; Kristina R. Weeks; M. Rosen
Year: 2017

Purpose The purpose of this paper is to provide a practical framework that health care organizations could use to decrease preventable healthcare-acquired harms. Design/methodology/approach An existing theory of how hospitals succeeded in reducing rates of central line-associated bloodstream infections was refined, drawing from the literature and experiences in facilitating improvement efforts in thousands of hospitals in and outside the USA. Findings The following common interventions were implemented by hospitals able to reduce and sustain low infection rates. Hospital and intensive care unit (ICU) leaders demonstrated and vocalized their commitment to the goal of zero preventable harm. Also, leaders created an enabling infrastructure in the way of a coordinating team to support the improvement work to prevent infections. The team of hospital quality improvement and infection prevention staff provided project management, analytics, improvement science support, and expertise on evidence-based infection prevention practices. A third intervention assembled Comprehensive Unit-based Safety Program teams in ICUs to foster local ownership of the improvement work. The coordinating team also linked unit-based safety teams in and across hospital organizations to form clinical communities to share information and disseminate effective solutions. Practical implications This framework is a feasible approach to drive local efforts to reduce bloodstream infections and other preventable healthcare-acquired harms. Originality/value Implementing this framework could decrease the significant morbidity, mortality, and costs associated with preventable harms.
Balancing Project Schedule, Cost, and Value under Uncertainty: A Reinforcement Learning Approach
Authors: Claudio Szwarcfiter; Y. Herer; A. Shtub
Year: 2023

Industrial projects are plagued by uncertainties, often resulting in both time and cost overruns. This research introduces an innovative approach, employing Reinforcement Learning (RL), to address three distinct project management challenges within a setting of uncertain activity durations. The primary objective is to identify stable baseline schedules. The first challenge encompasses the multimode lean project management problem, wherein the goal is to maximize a project’s value function while adhering to both due date and budget chance constraints. The second challenge involves the chance-constrained critical chain buffer management problem in a multimode context. Here, the aim is to minimize the project delivery date while considering resource constraints and duration-chance constraints. The third challenge revolves around striking a balance between the project value and its net present value (NPV) within a resource-constrained multimode environment. To tackle these three challenges, we devised mathematical programming models, some of which were solved optimally. Additionally, we developed competitive RL-based algorithms and verified their performance against established benchmarks. Our RL algorithms consistently generated schedules that compared favorably with the benchmarks, leading to higher project values and NPVs and shorter schedules while staying within the stakeholders’ risk thresholds. The potential beneficiaries of this research are project managers and decision-makers who can use this approach to generate an efficient frontier of optimal project plans.
A Metric-Based Multi-Agent System for Software Project Management
Authors: Ching-seh Wu; Wei-chun Chang; I. Sethi
Year: 2009

Software Project Management (SPM) is one of the primary factors to software success or failure. Software projects often fail because the mangers do not know true project status. Software project planning can be one of the most critical activities in the SPM process. Without a realistic and objective software project plan, the software development process cannot be managed in an effective way. This paper presents a metric-based multi-agent system, Software Project Planning Associate (SPPA), to assist managers in understanding and visualizing SPM process defined in a software project plan. SPPA consists of Intelligent Agents developed in the Java programming language and JESS (Java Expert System Shell) to assist a software project manager in objectively initializing a software project plan, refining/improving a plan, organizing, staffing, scheduling, measuring, visualizing, controlling, tracking, predicting, and data collecting. The resources, tasks, schedules, and milestones of the software project are described in a generic metric-based software project plan. As software development process evolves, metrics are unobtrusively gathered and compliance to the plan is reported by intelligent agents. Software process effectiveness predictions are made and recommendations are dynamically reported by multi intelligent agents suggesting the software development that should be executed to best comply with the software project plan.
Use of the Benefits Management Methodology in an Insurance Company: Case Study
Authors: Vera Silva; J. Fernandes
Year: 2020

The benefits management methodology is a complementary analysis technique to traditional project management practices. It dynamically evaluates the benefits associated with the implementation of an information system (IS), including all phases from planning to monitoring, both during and after the implementation. This article presents a case study of the application of the Cranfield School of Management's benefits management technique as it is applied to an insurance company. It identifies and quantifies the underlying benefits of IS implementation, organizational and structural changes, and alignment with the organization's strategy. The data was collected through analysis of secondary documents and interviews with insurance company employees. The main contribution of this article is to demonstrate the versatility of the Cranfield School of Management's technique during the study of IS projects. It provides a graphical visualization of the dependencies between all elements of the network.
Management of industrial service projects developed by Brazilian companies and their relationship with critical success factors
Authors: I. C. Machado; Izabella Rampasso; O. Quelhas; W. Leal Filho; Vinicius Minatogawa; Matheus Franco; R. Anholon
Year: 2022

Purpose – This study aims to analyze the project management of industrial services developed by Brazilian companies and their relationship with Critical Success Factors. Theoretical framework – Through a content analysis, Critical Success Factors were aligned to industrial service management and PMBOK project management guidelines.Design/methodology/approach – To develop the study, a survey on industrial service project management was carried out on industrial service professionals. Survey data were analyzed through frequency distribution and ranked using the TOPSIS technique. Findings – The results showed that the companies mentioned use PMBOK guidelines, however, they can be improved. Comparatively, the project schedule management is highlighted; the five CSFs that are considered more relevant are related to the scope, schedule, costs, integration, communications and resource management. Research, Practical & Social implications – The results provide insights for organizational practices and guide management improvements, showing the main opportunities for improvement in the companies analyzed. Originality/value – The literature fails to provide an analysis of Brazilian industrial service companies. In this sense, this study provides a valuable contribution to the field.Keywords: Industrial Services Management; Critical Success Factors; Project Management; Brazil.
Five Highs, Four Lows, and Three Optimizations: A Study on the Integrated Online and Offline Autonomous Learning Model
Authors: Huangzhi Lin; Tian Liu
Year: 2023

: Given the "Five High" characteristics of online-offline integrated teaching, including high uncertainty in teaching mode, high complexity of teaching environment, high utilization of information technology, high requirements for students' self-discipline, and high expectations for teachers' teaching abilities, and given the "Four Low" challenges of low classroom attraction, low utilization rate of online course resources, low student participation and interest in learning, and low communication and interaction between teachers and students, we propose a project management approach to explore self-learning teaching methods. This approach aims to optimize three aspects: transforming teachers' classroom roles, efficiently implementing flipped classrooms, and reasonably assigning online and offline tasks. Ultimately, our goal is to achieve a deep integration of online and offline teaching and to cultivate students' ability for independent learning.
The Effectiveness of Implementing Agile Project Management: A Systematic Literature Review
Authors: Aisha Sonetya Rahmah Aisha Sonetya Rahmah; Nauval Rafa Pratama Nauval Rafa Pratama; Shafina Aulia Kuswadi Shafina Aulia Kuswadi; Mohammad Ichsan Mohammad Ichsan
Year: 2024

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An improved task decomposition method based on domain heuristic planning for make-to-order engineering project management
Authors: Xiangci Meng
Year: 2023

In order to achieve autonomous schedule management of the make-to-order engineering project, a structural augmented intelligent task decomposition method (saITDM) that combines case-based reasoning (CBR) with the intelligent planning method and domain managerial needs is presented. It is well known that the more customized a product is, the more complex and unique the production process will be. Regarding to make-to-order engineering industry, such as shipbuilding, each project is particularly ordered to a specific working condition, but there are many fundamental processes taken in several engineering stages, like cutting, blasting, painting and so forth. It means that schedule managerial knowledge would be reused in new projects. Since task decomposition results are normally represented in natural language, unified representation is quite necessary for computer-aided processing. Peer studies have proven that CBR is advantageous to address this issue. However, existing methods that adopts either the single domain CBR or the hierarchical CBR need experts to pay extra effort to consecutively adjust the computer-aid result during the planning process. For reduction of these extra work, saITDM combines CBR with Local search for Planning Graphs (LPG) to auto-generate task composition schemes in alignment with the make-to-order managerial needs. Further, in order to shorten case retrieval and assemble processes, two new processing ways are designed. The first is the notion of project family decomposition factor path (PFDFP) which helps to reuse the heuristic knowledge of schedule managerial needs through clustering similar projects, while the other is a branch algorithm named Longest Compound Breakdown Branch (LCBB) algorithm which helps to reduce the volume of cases on the basis of knowledge discovery. Through a real case study, it is verified that the proposed method is effective and superior to the peer study in efficiency.
Construction practice knowledge for complementing classroom teaching during site visits
Authors: J. Olayiwola; A. Yusuf; A. Akanmu; H. Murzi; Xinghua Gao; K. Afsari
Year: 2023

PurposeAs video-based interventions are continuously utilized as alternatives to physical site visits, directing students' attention to specific learning contents within videos could increase their comprehension and stimulate their interest. Students' knowledge of construction practice can be reinforced, misconceptions and improper inferences can be reduced by calling out significant learning concepts. However, few studies have formalized practice concepts that could be beneficial in preparing students for the workplace. This paper presents an investigation of construction practice concepts, based on site visits that would be beneficial in complimenting classroom teaching to prepare students for the realities of practice.Design/methodology/approachA mixed methods research approach was employed combining qualitative and quantitative data collection and analysis. An online questionnaire, semi-structured interviews and a focus group were conducted with industry practitioners and instructors to identify the topics and practice concepts significant for supporting classroom teaching with site visits.FindingsThe findings suggest that the most relevant topics typically supported with site visits are preconstruction management, excavation and foundation work, construction equipment, construction means and methods, project management, road construction, sustainability, building systems, structures, construction technology, building construction, capstone, site logistics and safety. Practice concepts were identified for each of these topics.Research limitations/implicationsThe study will guide researchers in the design of video-based pedagogical tools to be used as an effective complement of or alternative to site visit experiences. The findings will support instructors on how to structure their teaching practices to prepare students for some of the complexities of the workplace.Originality/valueThis study adds value to the existing literature by providing insights into industry perception of practice concepts for complementing classroom teaching.
An improved way for evaluating competences: A different approach to project management learning
Authors: Enrique Crespo; A. González‐Marcos; F. Alba‐Elías; M. C. Limas; Joaquín B. Ordieres Meré
Year: 2011

This paper presents a formal initiative for monitoring the competence acquisition by a team of students with different backgrounds facing the experience of being working by projects and in a project. These students are inexperienced in the project management field and they play this game on a time-shared manner along with other activities. The goal of this experience is to make some improvements in determining the competence levels acquired by means of how the work is being done. The use of this information, which is out of the scope of this particular work, could make possible to bring additional information to the students involved in terms of their individual competencies and the identification of new opportunities of personal improvement.
Competency-based selection and assignment for project manager in Iranian railways projects by genetic multigenic programming
Authors: Mehdi VakilZadeh; M. Shayanfar; M. Zabihi‑Samani; M. Ravanshadnia
Year: 2023

As a part of human resource management, active companies in Iran's railway industry must determine the qualifications for appropriate project managers in railway construction. This research aims to consider the importance of Iran's railway construction projects due to the lack of staff with expertise and their high economic impact and budget. A decision-making model is presented. The project manager's qualifications are determined through questionnaires answered by experts in the field. The numerical model is created to determine the qualifications for project management in the railway industry. Therefore, Competency-Based Selection by Genetic Programming Multigenic Regression (CSPR) is proposed for project-oriented human resource management. Decision-making is done in three phases: Hierarchical analysis process for evaluating and determining the qualifications based on the questionnaires. The model is trained and validated by creating optimal coefficients and genes to determine the contribution of each of these qualifications in determining each candidate's final qualifications based on experts' questionnaires. Finally, the model's accuracy with optimal coefficients will be tested based on the questionnaires not used in the model training phase. The CSPR model provides a qualitative method and numerical optimization to evaluate and grade the project manager in Iran's railway construction projects based on the metaheuristic method.
Critical Analysis on the Theoretical Discussion Concerning the Concept of Sustainability and Project Management
Authors: Aliyu Sule M.; Jemimah Nathaniel
Year: 2023

This study discusses reviews literature the most notable works in the field of program management and SDGs. Then it presents and critically analyses the theoretical discussion concerning the concept of sustainability and Project Management. It explores the history of sustainability and its goals as well as its importance and relevance to the environment. Also, there is in-depth literature on sustainable Project Management and the area that the concept can be incorporated. All literature reviewed in this chapter is geared towards achieving the aim of the research. The final subchapter then presents the theoretical model constructed by the author, which lays the foundation of the present research.
Analysis of the importance of business process management depending on the organization structure and culture
Authors: W. Chmielarz; Marek Zborowski; Aneta Biernikowicz
Year: 2013

The present survey mainly aims at analysing determinants of possibilities of improving processes in an organization. The early fragments of the study are devoted to a theoretical analysis of determinants of the process management and its connection with the project management. Then the assumptions of the survey on the impact of the organizational structure and culture on possibilities of applying business process management were presented. The verification of theoretical deliberations and survey assumptions is included in the last part of the article presenting the initial results of the obtained survey and the resulting conclusions.
Incentive contract design and selection for inhibiting unethical collusion in construction projects
Authors: Lei Cui
Year: 2023

Purpose The construction industry has long been criticized for unethical conduct. The owner usually manages the contractor's opportunistic behaviors by employing a professional supervisor, but there is a risk of covert collusion between the supervisor and contractor. Based on the principal–agent theory and collusion theory, this paper aims to investigate optimal collusion-proof incentive contracts.Design/methodology/approachThis paper presents a game-theoretic framework comprising an owner, supervisor and contractor, who interact and pursue maximized self-profits. Built upon the fixed-price incentive contract, cost-reimbursement contract, and revenue-sharing contract, different collusion-proof incentive contracts are investigated. A real project case is used to validate the developed model and derived results.FindingsThis paper shows that the presence of unethical collusion undermines the owner's interests. Especially, the possibility of agent collusion may induce the owner to abandon extracting quality information from the supervisor. Furthermore, information asymmetry significantly affects the construction contract selection, and the application conditions for different incentive contracts are provided.Research limitations/implicationsThis study still has some limitations that deserve further exploration. First, this study explores contractor–supervisor collusion but ignores the possibility of the supervisor abusing authority to extort the contractor. Second, to focus on collusion, this paper ignores the supervision costs. What's the optimal supervision effort that the owner should induce the supervisor to exert? Finally, this paper assumes that the colluders involved always keep their promises. However, what if the colluders may break their promises?Practical implicationsSeveral collusion-proof incentive contracts are explored in a project management setting. The proposed incentive contracts can provide the project owner with effective and practical tools to inhibit covert collusion in construction management and thus safeguard construction project quality.Originality/valueThis study expands the organization collusion theory to the field of construction management and investigates the optimal collusion-proof incentive contracts. In addition, this study is the first to investigate the effects of information asymmetry on contract selection.