The construction industry is a knowledge-intensive industry, and knowledge has been identified as a vital resource for improving decision-making and a critical factor for increasing productivity and gaining organisational competitive advantage within the construction industry. Although, building information modelling BIM has been described as a 'shared knowledge resource for information' which forms the basis for 'reliable decisions during the lifecycle of a project', evidence from the literature indicate that current BIM implementation (BI) has not been able to effectively integrated knowledge into BIM. While BIM has significantly improved the quality of information available for use within the industry, capturing and integrating experiential knowledge (EK) into BIM implementation (BI) for improved decision-making in BIM projects is still very challenging. Knowledge management (KM) as a discipline can provide processes and tools/techniques for capturing and integrating EK into BI. Hence, leveraging KM processes and tools, this study develops a conceptual BIM-Knowledge framework for integrating EK into BI for improved decision-making in BIM projects.
The study adopts convergent parallel mixed methods based on a pragmatic paradigm, which combines both qualitative and quantitative methods concurrently in a single study. Pragmatism philosophical stance provides the flexibility required to address the complex nature of the research question, which explores how the integration of EK into BI could improve decision-making in BIM projects. The study starts with the review of extant literature to explore the key concepts in the study, culminating in developing a preliminary framework. The preliminary framework provides the basic constructs that were further explored and investigated using semi-structured interviews and questionnaire surveys. Semi-structured interviews were conducted with thirty highly experienced stakeholders within the UK construction industry to explore their lived experiences about the constructs. Transcripts of the interviews were subjected to content analysis using NVivo 11 to identify prevalent codes from the quotations. In line with the adopted research philosophy, constructs from the literature review were also put together in a questionnaire survey and distributed to industry practitioners via Bristol Online Survey (BOS) to investigate their opinions about the constructs. The questionnaire's responses were subjected to rigorous statistical and factor analyses using Statistical Package for the Social Sciences (SPSS-21).
Findings from the analysis of both semi-structured interviews and questionnaires were triangulated for corroboration. The triangulation results led to the development of a conceptual BIM-Knowledge (BIM-K) framework for integrating EK into BI for improved decision-making in BIM projects. The proposed conceptual BIM-K framework consists of three main components: the BIM-K Core, which forms the framework's nucleus; the SKI, which consists an inventory of the skills and knowledge important to key decision-makers in BI; and the Output, which is the improved decision-making in BIM projects.
The BIM-K Core component consists of three layers of concentric circles: (i) the integration layer where EK from best practice, past mistakes and creative ideas from different project phases are integrated into BI, (ii) the KM process layer, where the five KM processes and their appropriate tools and techniques help facilitate the effective integration process, and (iii) the layer of impacting factors, where four categories of factors that could impact on the effectiveness of the integration process are domiciled. The conceptual BIM-K framework was partially validated with industry experts virtually to test its suitability for practical implementation. The framework will benefit all key decision-makers in BIM projects, especially the client, designers, the engineer, contractors and suchlike, by improving the quality of decisions regarding BI tasks and activities right from the pre-design phase of the project.