Managing the Influence of Stakeholders on the Scope of Major Construction Projects to Prevent Scope Creep in the BIM Era

The present PhD thesis is centred on investigating the challenge of scope creep within construction projects, denoting the phenomenon of an uncontrolled enlargement of project scope without essential adaptations. Stakeholders are identified as a major source of uncertainty and requests for changes in scope, which can result in risky events. Therefore, an overarching framework is needed to effectively resolve the problem of scope creep caused by stakeholder influence. The adoption of Building Information Modelling (BIM) is suggested as an effective methodology for the streamlined management of information in construction projects, thus enabling project managers to develop an appropriate solution for the identified problem. To develop this framework, a meta-analysis approach and case study strategy is employed to analyse and synthesise secondary data collected from the PMBOK GUIDE’S (PMI, 2017) project management processes, BIM-related standards, and six case study projects. The objective is to identify essential processes and activities, their sequence and interdependencies, problematic issues, and best practices. The outcome of the research is the creation of a Process Framework designed to address the problem of scope creep triggered by stakeholder influence. The elements and concepts of this framework are verified by undertaking semi-structured interviews with five practitioners from the construction and infrastructure industry. The Process Framework functions as a unifying mechanism that combines project management and BIM processes, thereby ensuring coordination and integration towards the overarching objective of managing stakeholder influence on project scope and mitigating scope creep. Additionally, this research contributes to the understanding of the relationship between BIM documents and project management processes. The study explores how BIM fits within project management processes and identifies the benefits of BIM for the resolution of issues in construction projects, including end product visualization, clash detection, and efficient information sharing. This study provides an extensive and meticulous analysis of scope creep within construction projects and presents a pragmatic framework for dealing with this issue

The Trilogy of Science: Filling the Knowledge Management Gap with Knowledge Science and Theory

The international knowledge management field has different ways of investigating, developing, believing, and studying knowledge management. Knowledge management (KM) is distinguished deductively by know-how, and its intangible nature establishes different approaches to KM concepts, practices, and developments. Exploratory research and theoretical principles have formed functional intelligences from 1896 to 2013, leading to a knowledge management knowledge science (KMKS) concept that derived a grounded theory of knowledge activity (KAT). This study addressed the impact of knowledge production problems on KM practice. The purpose of this qualitative meta-analysis study was to fit KM practice within the framework of knowledge science (KS) study. Themed questions and research variables focused on field mechanisms, operative functions, principle theory, and relationships of KMKS. The action research used by American practitioners has not established a formal structure for KS. The meta-data-analysis examined 385 transdisciplinary peer-reviewed articles using social science, service science, and systems science databases, with a selection of interdisciplinary studies that had a practice-research-theory framework. Key attributes utilizing Boolean limiters, words, phrases and publication dates, along with triangulation, language analysis and coding through analytic software identified commonalities of the data under study. Findings reflect that KM has not become a theoretically saturated field. KS as the forensic science of KM creates a paradigm shift, causes social change that averts rapid shifts in management direction and uncertainty, and connects KM philosophy and science of knowledge. These findings have social change implications by informing the work of managers and academics to generate a methodical applied science

Digital libraries: The challenge of integrating instagram with a taxonomy for content management

Interoperability and social implication are two current challenges in the digital library (DL) context. To resolve the problem of interoperability, our work aims to find a relationship between the main metadata schemas. In particular, we want to formalize knowledge through the creation of a metadata taxonomy built with the analysis and the integration of existing schemas associated with DLs. We developed a method to integrate and combine Instagram metadata and hashtags. The final result is a taxonomy, which provides innovative metadata with respect to the classification of resources, as images of Instagram and the user-generated content, that play a primary role in the context of modern DLs. The possibility of Instagram to localize the photos inserted by users allows us to interpret the most relevant and interesting informative content for a specific user type and in a specific location and to improve access, visibility and searching of library content

Integrating BIM and GIS for design collaboration in railway projects

Collaboration is essential to achieve project targets and minimising rework in any project including railway projects. The railway project is considered as a megaproject that requires effective collaboration in order to achieve efficiency and effectiveness. To ensure that the railway continues to provide safe, reliable, cost-effective services, and remains environmentally friendly while driving economic growth, engaging new technologies and new types of work models are required. Among these technologies, Building Information Modelling (BIM) and Geographic Information Systems (GIS) are recent technologies that support collaboration. However, using these technologies to achieve effective collaboration is challenging, especially in railway projects as they are amongst the most complicated projects and often numerous parties are involved in making important decisions. Currently, there is a lack of evidence-based guidelines or processes for effective collaboration in railway projects throughout their design stage. Therefore, this thesis has focused on developing a process model to improve collaboration in the design stage of railway projects using BIM and GIS. This research adopted a mixed-methods approach to examine and identify the issues that hinder collaboration in railway projects to assist in developing theBIM and GIS-enabled collaboration process model. An online questionnaire was designed and distributed to professionals to assess the state-of-the-art in BIM and GIS followed by two rounds of in-depth interviews with experts. The first round aimed to identify collaboration issues and consisted of 15 in-depth, face to face and videoconference/telephone interviews; while the second round consisted of 10 in-depth interviews to identify the process model components of the collaborative process using IDEF technique.The questionnaire data were analysed using descriptive statistics and statistical tests (for example, Regression analysis, Wilcoxon Signed Ranks and Kruskal-Wallis Test). The results showed a lack of training in BIM and GIS and identified collaboration as a significant factor for railway projects, but there were many challenges to achieve effective collaboration. These challenges have been further investigated during the first round of interviews using content and thematic analysis. The results revealed that the most common challenges were getting the right information at the right time for the right purposes followed by resistance to change. Furthermore, the findings indicated that developing a process model, based on a clear plan of work demonstrating the collaboration process, is a potential solution to tackle these challenges. Thus, a Collaborative Plan of Work (CPW) has been developed through combining the RIBA (Royal Institute of British Architects) Plan of Work and the GRIP (Governance for Railway Investment Projects) stages. This CPW will be the basis to develop a process model for BIM and GIS-enabled collaboration. The results from the second round of the interviews identified the process model components which are: key players’ roles and responsibilities, tasks (BIM and GIS Uses), BIM and GIS-based deliverables, and critical decision points for collaborative process design. Moreover, this process model was formulated utilising Integrated DEFinition (IDEF) structured diagramming techniques (IDEF0 and IDEF3).In conclusion, the process model of the collaboration process and the integrated implementation of BIM and GIS sets out role and responsibilities, deliverables, and key decision points. Finally, the research outcomes have been validated through a focus group and interviews with professionals in the biggest Railway company where the proposed process model was operationalised using a commercial Common Data Environment platform (viewpoint 4project). From their discussion, feedback and recommendations the IDEF processes model have been refined. It is concluded that such a process is crucial for effective collaboration in railway projects as it enables the management of the design process in terms of technologies used, activities, deliverables, and decision points. Therefore, the research findings support the notion that BIM and GIS can help to achieve effective collaboration by delivering the right information at the right time for the right purposes. As a result, they help to achieve the projects’ objectives efficiently in terms of time, cost and effort.</div

FAIR Metadata Standards for Low Carbon Energy Research—A Review of Practices and How to Advance

The principles of Findability, Accessibility, Interoperability, and Reusability (FAIR) have been put forward to guide optimal sharing of data. The potential for industrial and social innovation is vast. Domain-specific metadata standards are crucial in this context, but are widely missing in the energy sector. This report provides a collaborative response from the low carbon energy research community for addressing the necessity of advancing FAIR metadata standards. We review and test existing metadata practices in the domain based on a series of community workshops. We reflect the perspectives of energy data stakeholders. The outcome is reported in terms of challenges and elicits recommendations for advancing FAIR metadata standards in the energy domain across a broad spectrum of stakeholders

A framework for outsourcing facilities management services in Nigeria's public hospitals

Literature has established FM as a global business model that continues to explore how organisation can grow faster through expansion into new markets, find new ways of fostering innovation through collaborative outsourcing that will achieve right balance between the decision to outsource, risks and legal requirements embedded in the service level agreement (SLA) between client organisations and their FM outsourcing vendors. The study aims to develop and test a framework for outsourcing facilities management services using data from Nigeria’s public hospitals. The specific objectives are among others; to determine a set of key factors that influence the decision to outsource facilities management services in public hospitals; to conduct an empirical survey of facilities management services outsourced in public hospitals; to access the satisfaction of users of outsourced FM services and model the satisfaction of users on quality of outsourced facilities management services using SEM; and assess the probability and severity of risks associated with outsourcing of facilities management services in public hospitals. Data for this study were collected using a cross sectional 2-strand questionnaire survey and case study. During the first strand of questionnaire survey, a total of 85 responses were received from the six states comprising the study area while 11 of them were discarded due to missing data resulting in 74 usable responses. This gave an overall response rate of 45.4%. A total of 246 survey responses were received during the second strand of questionnaire survey. Of these, 38 were not fully completed and therefore discarded leaving 208 as usable responses. This resulted in an overall response rate of 25.1%. The case study component involved semi-structured interview section with 4 participants representing 4 cases (3 hospitals and 1 FM organisation). Findings revealed that 25 of the 31 factors were significant in explaining the decision to outsource FM service in Nigeria’s public hospitals; while 15 of them grouped into 5 broad categories were recommended for framework construction based on their factor loadings during analysis. Also, 6 facilities management services including plant management and repairs; general cleaning services; waste disposal and environmental management; landscape maintenance; security; and catering/restroom management are completely outsourced in all the 74 hospitals. Findings additionally revealed that service quality in relation to catering, plant maintenance, waste management, security, landscape maintenance, and cleaning services received very high satisfaction ratings from respondents. Findings also established 24 out of the 35 risk factors as critical, 4 factors as somehow critical, and 5 factors as not critical. Besides, 9 risk factors were selected based on their factor loadings from PCA to develop the outsourcing framework. Drawing on theoretical analysis and input from the questionnaire survey and case study, an outsourcing framework comprising 4 components was developed to assist public hospitals administrators achieve sustainable best practice resource management. It is recommended among others that further research be conducted to develop standardised criteria for vendor selection processes

ERP implementation methodologies and frameworks: a literature review

Enterprise Resource Planning (ERP) implementation is a complex and vibrant process, one that involves a combination of technological and organizational interactions. Often an ERP implementation project is the single largest IT project that an organization has ever launched and requires a mutual fit of system and organization. Also the concept of an ERP implementation supporting business processes across many different departments is not a generic, rigid and uniform concept and depends on variety of factors. As a result, the issues addressing the ERP implementation process have been one of the major concerns in industry. Therefore ERP implementation receives attention from practitioners and scholars and both, business as well as academic literature is abundant and not always very conclusive or coherent. However, research on ERP systems so far has been mainly focused on diffusion, use and impact issues. Less attention has been given to the methods used during the configuration and the implementation of ERP systems, even though they are commonly used in practice, they still remain largely unexplored and undocumented in Information Systems research. So, the academic relevance of this research is the contribution to the existing body of scientific knowledge. An annotated brief literature review is done in order to evaluate the current state of the existing academic literature. The purpose is to present a systematic overview of relevant ERP implementation methodologies and frameworks as a desire for achieving a better taxonomy of ERP implementation methodologies. This paper is useful to researchers who are interested in ERP implementation methodologies and frameworks. Results will serve as an input for a classification of the existing ERP implementation methodologies and frameworks. Also, this paper aims also at the professional ERP community involved in the process of ERP implementation by promoting a better understanding of ERP implementation methodologies and frameworks, its variety and history

A Theory-Driven Design Framework for Social Recommender Systems

Social recommender systems utilize data regarding users’ social relationships in filtering relevant information to users. To date, results show that incorporating social relationship data – beyond consumption profile similarity – is beneficial only in a very limited set of cases. The main conjecture of this study is that the inconclusive results are, at least to some extent, due to an under-specification of the nature of the social relations. To date, there exist no clear guidelines for using behavioral theory to guide systems design. Our primary objective is to propose a methodology for theory-driven design. We enhance Walls et al.’s (1992) IS Design Theory by introducing the notion of “applied behavioral theory,” as a means of better linking theory and system design. Our second objective is to apply our theory-driven design methodology to social recommender systems, with the aim of improving prediction accuracy. A behavioral study found that some social relationships (e.g., competence, benevolence) are most likely to affect a recipient’s advice-taking decision. We designed, developed, and tested a recommender system based on these principles, and found that the same types of relationships yield the best recommendation accuracy. This striking correspondence highlights the importance of behavioral theory in guiding system design. We discuss implications for design science and for research on recommender systems

Generative retrieval-augmented ontologic graph and multi-agent strategies for interpretive large language model-based materials design

Transformer neural networks show promising capabilities, in particular for uses in materials analysis, design and manufacturing, including their capacity to work effectively with both human language, symbols, code, and numerical data. Here we explore the use of large language models (LLMs) as a tool that can support engineering analysis of materials, applied to retrieving key information about subject areas, developing research hypotheses, discovery of mechanistic relationships across disparate areas of knowledge, and writing and executing simulation codes for active knowledge generation based on physical ground truths. When used as sets of AI agents with specific features, capabilities, and instructions, LLMs can provide powerful problem solution strategies for applications in analysis and design problems. Our experiments focus on using a fine-tuned model, MechGPT, developed based on training data in the mechanics of materials domain. We first affirm how finetuning endows LLMs with reasonable understanding of domain knowledge. However, when queried outside the context of learned matter, LLMs can have difficulty to recall correct information. We show how this can be addressed using retrieval-augmented Ontological Knowledge Graph strategies that discern how the model understands what concepts are important and how they are related. Illustrated for a use case of relating distinct areas of knowledge - here, music and proteins - such strategies can also provide an interpretable graph structure with rich information at the node, edge and subgraph level. We discuss nonlinear sampling strategies and agent-based modeling applied to complex question answering, code generation and execution in the context of automated force field development from actively learned Density Functional Theory (DFT) modeling, and data analysis