derhan/semantic-scholar-manajemen-proyek huggingface dataset:
What Project Strategy Really Is: The Fundamental Building Block in Strategic Project Management
Authors: P. Patanakul; A. Shenhar
Year: 2012

Strategic project management is gradually becoming a popular and growing trend within the discipline of project management. The general idea is that project management teams must learn how to deal with the business aspects of their projects, as well as better support their company's business strategy and sustainability, rather than just focus on meeting traditional time, budget, and performance goals. Although this approach has been gaining popularity, strategic project management has not yet become an explicit and widely used approach in the practice of project implementation. One of the concepts mentioned as an important element is project strategy; however, no universal framework or even a clear definition of what project strategy is has so far emerged. The goal of this article is to fill in this gap and provide a useful definition and a framework for the further study and implementation of the project strategy concept. Specifically, to achieve this goal, we first look at the origins of strategy in military and business research to discuss the question of what, exactly, project strategy is; we follow this discussion with an explicit definition of a project strategy. We then outline a framework for building a dedicated project strategy document for an individual project, and show how this framework can guide the project planning and execution processes. Using a case study approach, which included an action research phase, we demonstrate how project teams can adopt the strategy concept in a natural way that would lead their project to better business results.
Blockchain Integration in Critical Systems Enhancing Transparency, Efficiency, and Real-Time Data Security in Agile Project Management, Decentralized Finance (DeFi), and Cold Chain Management
Authors: Odunayo Akindotei; Igba Emmanuel; Babatunde Olusola Awotiwon; Adah Otakwu
Year: 2024

Blockchain technology has garnered significant attention for its potential to revolutionize critical systems by enhancing transparency, efficiency, and data security. This review examines the integration of blockchain in three essential domains: Agile Project Management, Decentralized Finance (DeFi), and Cold Chain Management. By leveraging decentralized ledgers and smart contracts, blockchain provides a robust framework for real-time tracking, data integrity, and automated compliance, addressing long-standing challenges across these sectors. In Agile Project Management, blockchain fosters seamless collaboration and transparent decision-making, minimizing bottlenecks and improving accountability. In DeFi, blockchain strengthens security for digital transactions and identity verification while offering financial autonomy and mitigating fraud risks. Within Cold Chain Management, blockchain ensures traceability, reduces data tampering risks, and enhances visibility throughout supply chain processes, safeguarding temperature-sensitive goods. This paper evaluates existing blockchain-based applications and frameworks, identifies current limitations, and discusses future opportunities for optimizing critical systems through blockchain. The findings highlight blockchain's transformative role in driving operational efficiency, security, and data transparency across diverse applications, providing a roadmap for industries to harness its full potential in critical environments.
Digitalization of Present Work Process; Investigating the Role of Leadership, Change Management and Top Management Support in the Success of Enterprise Resource Planning Projects
Authors: Dong Wang; Abdul Samad Kakar; Muhammad Kamran Khan; Muhammad Iftikhar Ali; Wong Chee Hoo; Chee How Liau; Muhammad Anwar Khan
Year: 2024

Background: Organizations across the world implement enterprise resource planning (ERP) projects to transform their daily routine work process digitally. However, research on factors that lead to successful ERP projects is limited, especially empirical research studies. Therefore, the current study focused on investigating the influence of transformational leadership (TFL) on ERP project success. This research examined the mediating role of change management in the relationship between TFL and the success of projects of ERP. Additionally, it investigated the moderating role of top management support (TMS) over the relationship between TFL and the success of ERP projects. Method: The study gathered data from 408 IT professionals involved in different ERP projects in the various sectors of Pakistan using a purposive sampling technique. The SPSS and SmartPLS software were used for data analysis. Results: The findings of the study disclosed that TFL is positively related to ERP project success and change management and that change management is subsequently related to ERP project success. The findings also revealed the mediating role of change management over the relationship between TFL and the successful completion of ERP projects, while top management support moderates the nexus of TFL and the success of ERP projects. Conclusions: This research adds to the literature by highlighting the importance of TFL in ERP project success. In addition, it highlights the role of change management and TMS in achieving successful outcomes. Our findings provide valuable insights for practitioners and researchers to improve successful project management in the IT industry.
Application of Digital Technologies Tools for Social and Sustainable Construction in a Developing Economy
Authors: Ayodeji Emmanuel Oke; John Aliu; Paramjit Singh Jamir Singh; Solomon A. Onajite; A. Kineber; M. Samsurijan
Year: 2023

This study aims to evaluate the diverse application areas of digital technologies (DTs) within the Nigerian construction industry, with the intention of gaining insights into their potential benefits, challenges, and opportunities for enhancing efficiency, productivity, and overall performance. This will help us to understand how innovative technologies can improve the various stages of construction projects. To achieve the objectives of this study, a convenience sampling approach was employed to distribute closed-ended questionnaires among construction professionals located in Lagos State. Several statistical tools were used to analyze the obtained data, including percentages, frequencies, mean item scores, and exploratory factor analyses were performed to gain a comprehensive understanding of the dataset. The major findings from the study indicated that architectural design, cost planning, building system analysis, structural analysis, and contract documentation are areas in which DT is mostly applied in the construction industry. Further analysis using factor analysis revealed four clusters of application areas as the pre-contract stage, construction stage, post-contract stage, and modeling stage. The findings of this study offer valuable insights into the effective utilization of DT in the construction industry, thereby contributing to informed decision-making and improved project management practices. The insights gained from this research can inform industry professionals, policymakers, and stakeholders in making informed decisions to drive positive changes and innovation within the sector.
IS Project Management: Size, Complexity, Practices and the Project Management Office
Authors: Nancy L. Martin; J. Pearson; Kimberly A. Furumo
Year: 2005

The current research is an exploratory investigation into current IS project management practices related to projects of varying size and complexity across diverse industries Survey data on a broad range of project management issues was collected from 129 IS project managers. The relationships between project size and complexity with 13 project management practices and 3 project performance measures were analyzed. In addition, the influence of a PMO on the use of standardized project management practices and project performance was empirically tested. Our findings suggest that IS project size influences budget and project quality, while project complexity influences the use of specific project management practices. The PMO is empirically linked to project budget.
Infrastructures of digital humanities
Authors: C. Sula; Kalani Craig; Michelle Dalmau; Alexandra Humphreys; E. Hyvönen; Humphrey Keah; J. Kiplang’at; Thea Lindquist; N. Weber
Year: 2020

This panel will convene participants from a range of roles and institutions to build on previous work in infrastructures of digital humanities: the organizational and structural aspects of the field responsible for collaboration, partnership, training and support, access, preservation, sustainability, and more. Information professionals play a key role in these infrastructures, from technical expertise to project management to training and support for methods and tools. Panelists from faculty, centers and institutes, and academic and digital libraries will address issues of capacity building, disciplinarity, and labor across various settings.
Change management: A framework for measuring and implementing organisational change
Authors: Christa Y. Leung; Jason E. Barclay; Catherine T. Botz; Nicole K. Hanf; Jan C. Jasperson; Keri N. Kirby; Christopher J. Mull; Archana S. Shinde; Matthew M. Vogl
Year: 2021

In 2018, Mayo Clinic completed the largest transformational project in its 150-year history. Mayo Clinic was prepared to take on the implementation of new software systems (Epic Systems Corp) as an integrated electronic health record (EHR) and revenue cycle management (RCM) system across all sites of the enterprise. Three foundational teams were launched for this project: leadership, project management and change management. In a project such as this, a common pitfall is to focus completely on the system and lose sight of the end users. For Mayo Clinic, the people side of change was at the forefront of the project. A robust change management team was budgeted, staffed and engaged with an experienced outside consulting partner. A goal for the change management team centred on the best way to measure the change management impact and the degree to which it was making a positive contribution in driving successful adoption of the new EHR and RCM system. With literature lacking in this area, the team moved forward with courage and quickly learned that the easy part was the development of a survey with questions mapped to the six components of the change management strategy and the phases of the awareness, desire, knowledge, ability, reinforcement (ADKAR) Model (Prosci Inc). The hard part was building the infrastructure to visually display millions of rows of data that needed to be positioned, filtered and analysed for all affected locations. The authors share the methods to measure change and explain the importance of developing a comprehensive and robust means of gathering and displaying large volumes of change management data at the project onset. This paper prepares the reader to confidently develop an organisational framework to measure and report the effectiveness of a change management strategy.
Software process anti-pattern detection in project data
Authors: P. Pícha; Přemek Brada
Year: 2019

There is a significant amount of guidance on Project Management (PM) including software development methodologies, best practices and anti-patterns (APs). There is, however, a lack of automated way of applying this knowledge by analyzing readily available data from tools aiding in software PM, such as Application Lifecycle Management (ALM) tools. We propose a method of detecting process and PM anti-patterns in project data which can be used to warn software development teams about a potential threat to the project, or to conduct more general studies on the impact of AP occurrence on project success and product quality. We previously published a concept for the data mining and analysis toolset distinct from other research approaches and related work. Based on this toolset, we devised a formalized basis for our detection method in the form of standardized AP description template and a model for pattern operationalization over project data extracted from ALM tools. The main contribution of this paper is the general method for AP operationalization taking the description template as a starting point, discussed together with its potential limitations. We performed an initial validation of the method on data from student projects, using an AP we encountered in practice called "Collective Procrastination" which we also describe in this paper together with its detailed formal operationalization.
Detecting similarities in antipattern ontologies using semantic social networks: implications for software project management
Authors: Dimitrios Settas; Sulayman K. Sowe; I. Stamelos
Year: 2009

Abstract Ontology has been recently proposed as an appropriate formalism to model software project management antipatterns, in order to encode antipatterns in a computer understandable form and introduce antipatterns to the Semantic Web. However, given two antipattern ontologies, the same entity can be described using different terminology. Therefore, the detection of similar antipattern ontologies is a difficult task. In this paper, we introduce a three-layered antipattern semantic social network, which involves the social network, the antipattern ontology network and the concept network. Social Network Analysis (SNA) techniques can be used to assist software project managers in finding similar antipattern ontologies. For this purpose, SNA measures are extracted from one layer of the semantic social network to another and this knowledge is used to infer new links between antipattern ontologies. The level of uncertainty associated with each new link is represented using Bayesian Networks (BNs). Furthermore, BNs address the issue of quantifying the uncertainty of the data collected regarding antipattern ontologies for the purposes of the conducted analysis. Finally, BNs are used to augment SNA by taking into account meta-information in their calculations. Hence, other knowledge not included in the social network can be used in order to search the social network for further inference. The benefits of using an antipattern semantic social network are illustrated using an example community of software project management antipattern ontologies.
Software cost estimation for global software development a systematic map and review study
Authors: Manal El Bajta; A. Idri; J. Fernández-Alemán; J. Nicolás; J. Álvarez
Year: 2015

Software cost estimation plays a central role in the success of software project management in the context of global software development (GSD). The importance of mastering software cost estimation may appear to be obvious. However, as regards the issue of customer satisfaction, end-users are often unsatisfied with software project management results. In this paper, a systematic mapping study (SMS) is carried out with the aim of summarising software cost estimation in the context of GSD research by answering nine mapping questions. A total, of 16 articles were selected and classified according to nine criteria: publication source, publication year, research type, research approach, contribution type, software cost estimation techniques, software cost estimation activity, cost drivers and cost estimation performances for GSD projects. The results show that the interest in estimating software cost for GSD projects has increased in recent years and reveal that conferences are the most frequently targeted publications. Most software cost estimation for GSD research has focused on theory. The dominant contribution type of software cost estimation for GSD research is that of models, while the predominant activity was identified as being software development cost. Identifying empirical solutions to address software cost estimation for GSD is a promising direction for researchers.
Knowledge Transfer within Enterprises from the Perspective of Innovation Quality Management: A Decision Analysis Based on the Stackelberg Game
Authors: Shumei Wang; Ming Sun; Yaoqun Xu
Year: 2024

It is of great significance to study the effectiveness of knowledge transfer between the new and the veteran employees within enterprises for promoting sustainable innovation from the perspective of innovation quality management. However, few studies have examined the impact of innovation quality on the effectiveness of knowledge transfer between the new and veteran employees. In addition, knowledge of how reward and punishment incentives affect the effectiveness of knowledge transfer in innovation quality management remains insufficient. Since the amount of knowledge transfer is an important aspect of the effectiveness of knowledge transfer, this paper constructs a Stackelberg game model with an innovation-quality-oriented threshold of the knowledge transfer amount and investigates the amount of knowledge transfer between new and veteran employees in the collaborative innovation of research and development (R&D) projects within enterprises. A case study was used to reveal that the innovation-quality-oriented threshold for the knowledge transfer amount can effectively promote the amount of knowledge transfer between the new and the veteran employees in collaborative innovation. Moreover, reward is more effective than punishment in promoting the amount of knowledge transfer to exceed the innovation-quality-oriented threshold. This study enriches the theories of knowledge transfer games under quality management. By virtue of end-to-end project management strategies, modern multimedia technologies, and reward incentives this study can be used to conduct quality control during project execution, to promote knowledge retention in R&D projects, the innovation quality of projects, and the achievement of the Sustainable Development Goals (SDGs). The research methodology employed in this paper was limited to a case study, and the data utilized are not empirical data.
Enhancing software development practices with AI insights in high-tech companies
Authors: Daniel Ajiga; Patrick Azuka Okeleke; Samuel Olaoluwa Folorunsho; Chinedu Ezeigweneme
Year: 2024

Artificial Intelligence (AI) is revolutionizing software development practices in high-tech companies, providing transformative insights and tools that enhance productivity, quality, and efficiency. This review explores the integration of AI into software development processes, highlighting its impact on key areas such as code generation, bug detection, project management, and testing. AI-driven tools are enabling developers to automate repetitive tasks, optimize code, and identify potential issues before they become critical, thus reducing development time and improving software reliability. Machine learning algorithms analyze vast amounts of data from past projects to provide predictive analytics, guiding teams in decision-making and resource allocation. Natural language processing (NLP) facilitates more intuitive interactions with development tools, streamlining communication and collaboration among team members. Furthermore, AI enhances continuous integration and continuous deployment (CI/CD) pipelines by automating the testing and deployment stages, ensuring that code changes are seamlessly integrated and deployed with minimal human intervention. By leveraging AI, high-tech companies can adopt more agile methodologies, respond swiftly to market changes, and deliver high-quality software products. The review also discusses the challenges of integrating AI into software development, including the need for substantial initial investment, the complexity of AI models, and the importance of ensuring data privacy and security. Solutions such as fostering a culture of continuous learning, investing in AI-specific training for developers, and establishing robust data governance frameworks are essential for overcoming these barriers. In conclusion, AI-driven insights and tools offer significant advantages for high-tech companies, enabling them to enhance their software development practices, achieve greater efficiency, and maintain a competitive edge in a rapidly evolving technological landscape. Embracing these advancements requires a strategic approach, including investment in AI technologies and training, to fully harness the potential of AI and drive innovation in software development. 
Keywords: AI, Software Development, High-Tech, Practices, Companies.
Military artificial intelligence applied to sustainable development projects: sound environmental scenarios
Authors: Germán Darío Corzo-Ussa; É. L. Álvarez-Aros; Juan Pablo Mariño; Nicolás Amézquita-Gómez
Year: 2023

Artificial intelligence (AI) used in intelligence, surveillance, and reconnaissance (ISR) has a high application interest in project management. This article presents a result of military research on ISR applicable to monitoring and recognition of audio signals for environmental protection and critical infrastructure. Two databases with environmental sounds were built from open access platforms for training, validation, and testing. The identification characteristics for IA are extracted from the preprocessing of the sounds, obtaining the Mel Frequency Cepstral Coefficients (MFCC). As a result, model performance for more realistic soundstages shows higher accuracy compared to training categories in identifying signal frequency and duration settings. It is concluded that the model is applicable to various environmental scenarios as a low-cost alternative technology to be applied in sustainable project management.
CHALLENGES IN CONSTRUCTION INDUSTRY
Authors: Onur Basar; Pinar Basar
Year: 2023

Purpose- The purpose of this study is to research some of the major problems and challenges in the construction industry that need to be addressed and solved by various stakeholders. Factors influencing technology use in building construction project management Inadequate risk management, lack of structure, poor communication, unrealistic expectations/bad forecasting, delayed cash flow and limited skills.
Methodology- The study employs a quantitative study to explore the construction industry for building a competitive advantage.
Findings- The analysis reveals that the construction industry faces various challenges that can impact project delivery, productivity, and overall performance. there are some common problems in the construction industry. Construction projects often encounter cost overruns due to factors such as inaccurate initial estimates, changes in project scope, unforeseen site conditions, and fluctuations in material and labor costs. Budgetary constraints can lead to financial strain and project delays. Delays in construction projects can occur due to factors like poor project planning and management, inclement weather, labor shortages, regulatory approvals, and issues with subcontractors or suppliers. These delays can result in increased costs, contractual disputes, and dissatisfaction among project stakeholders. Construction sites are inherently hazardous environments, and ensuring worker safety is a critical concern. Failure to comply with safety regulations, inadequate training, lack of safety protocols, and inadequate risk assessments can lead to accidents, injuries, and even fatalities. Effective communication and collaboration among project teams, including architects, engineers, contractors, and subcontractors, are essential for successful project delivery. Inadequate communication, misinterpretation of project requirements, and lack of coordination can lead to errors, rework, and delays. Maintaining high-quality construction standards is crucial, but the industry often faces challenges in ensuring consistent quality control.
Conclusion - based upon the analysis findings it may be concluded that the difficulties can turn to competitive advantage with better strategic planning, risk management, and management of resources. The construction industry has a very important role in many countries for Economic Development, Innovation, Technological Change, and Growth.

Keywords: construction industry, competitiveness, opportunities,
JEL Codes: M11, M10, O10