Ainoo, F N Y (2025) Leveraging big data in AEC decision-making: A governance framework. PhD thesis, Capella University, USA.
Abstract
This study explored deficiencies in data governance frameworks within the architecture, engineering, and construction (AEC) sector, focusing on their alignment with the operational and technological requirements for managing big data. Semi-structured interviews were conducted with AEC professionals using a qualitative generic inquiry approach to examine the challenges of data integration, quality assurance, security, and alignment with task requirements. The thematic analysis of the interview data identified persistent issues, including fragmented data integration, inconsistent data quality, inadequate security measures, and a lack of task-specific governance tools. This study applied Task-Technology Fit (TTF) theory to evaluate the alignment between existing governance frameworks and the dynamic demands of AEC projects. The findings demonstrated that misalignments in governance practices impede decision-making processes, reduce operational efficiency, and increase project risks. This study extended the application of TTF theory by emphasizing its relevance in designing governance frameworks that better support big data management in the sector. This study contributes to the academic discourse by underscoring the critical role of tailored governance frameworks and proposing practical improvements for industry stakeholders. Recommendations include standardizing data formats, enhancing quality assurance practices, strengthening security protocols, and developing task-specific tools. The study also identified opportunities for future research, such as exploring the integration of emerging technologies, such as blockchain and artificial intelligence, expanding the geographic scope, and adopting mixed-methods approaches to validate findings. By addressing key deficiencies in data governance, this study provides actionable insights for improving project outcomes and operational efficiency within the AEC sector, while establishing a foundation for future investigations into innovative governance strategies.
| Item Type: | Thesis (Doctoral) |
|---|---|
| Thesis advisor: | Grant, G |
| Uncontrolled Keywords: | artificial intelligence; blockchain; data management; governance; integration; interview; quality assurance; security; thematic analysis |
| Index terms: | investigation, emerging technology, artificial intelligence, blockchain, governance, efficiency, project outcome, decision-making process, data management, thematic analysis, strengthening, integration, decision-making, misalignment, interview, quality assurance, strategy, big data |
| Subjects: | innovation and technology management, project completion, engineering problems, quality assurance, structural engineering, artificial intelligence, computing systems, business, data collection methods, information systems, decision analysis, organizational analysis, data management, methods and analysis, performance management, management |
| Topics: | Governance, Business Strategy, Research Practice, Organizational Design, Digital Applications, Risk Management, Engineering Principles, Project Management, Quality Management |
| Descriptive scope: | 4 PCEA |
N.B. Descriptive scope is a count of how many of the five facets of empirical research are indicated by the words used in title, abstract and keywords. It is not intended as a judgement on the research; merely a count of the kind of word we would expect to indicate Phenomenon, Concepts, Theoretical framing, Empirical techniques, Analytical techniques. If all five are present, then a code of “5 PCTEA” will indicate this. If you feel the coding for this record is questionable, we welcome discussion around the terms we matched or the way we categorized them. The facet you would expect may not be coded, or a facet may be coded inappropriately. This can also bear on a larger question, of which facets should be treated as defining in construction management research. Please get in touch, and we will look at it. More details here