Xu, J (2021) A human-organization-technology fit model to harness the power of building information modeling in construction project organizations. PhD thesis, University of Hong Kong, Hong Kong.
Abstract
The construction industry has long been criticized for being slow in embracing innovation and digitalization. A widely referred example is Building Information Modeling (BIM), which is expected as a game-changing innovation to effect construction’s digital transformation, but its actual adoption remains sluggish. It is further observed that different construction organizations have different experiences in harnessing BIM’s power. A proper human-organization-technology (HOT) configuration is a promising direction to explain the problem. Whilst scholars and practitioners are endeavored to add new technical edges to BIM, the HOT fit and how it affects BIM adoption have been paid scant attention. This research aims to develop a HOT fit model and contextualize it in construction project organizations (CPOs) to harness the power of BIM. It has five specific objectives: (1) identify theoretical explanations and gaps of technology adoption in organizations; (2) summarize the problems of HOT relationship; (3) develop a conceptual HOT fit model, contextualize it into BIM adoption in CPO, and operationalize it; (4) investigate how human, organization, and technology characteristics influence the HOT fit; and (5) advise CPOs on how to achieve HOT fit. It employs a mixed-method combined with literature review, content analysis, social network analysis, comparative case study, and statistical analysis. This research quantifies the HOT fit index and its three sub-dimensions, namely the Human-Technology fit, Human-Organization fit, and Organization-Technology fit, by conducting SNA of 14 BIM projects and 6 Non-BIM projects in Hong Kong. It is found that project size is a primary factor influencing the HOT fit. On top of project size, organization hierarchy steepness and BIM’s level of development (LOD) further explain the HOT fit. Flatter organization structure, larger project size, or higher LOD BIM can break the prior subtle HOT fit. It is against our orthodox that the steeper hierarchy can enable a higher HOT fit. The BIM application scenarios, especially the most widely applied ones such as 3D visualization, clash analysis, and 4D simulation, are not found to be very closely correlated with the HOT fit and its three sub-dimensions. Professional type and rank are not found to have statistically significant impacts on the HOT fit. Nevertheless, closer investigations indicated that the impact of professional type is scenario-sensitive; higher professional rank tends to have lower HOT fit. The research can help CPOs to evaluate their HOT fit before and during BIM adoption. It can help diagnose how their organizational structure and BIM adoption strategies can be adjusted to achieve a higher HOT fit to harness the designated potential of BIM. Nevertheless, the research is not to provide a prescribed, “one-size-fit-for-all” solution to BIM adoption. It is better to treat it as an analytic framework that can be used repetitively along the way. Due to the limited data source, it is hard to delineate the effects of more characteristics that may impact the HOT fit. Future research can be directed to expand the characteristics, integrate subjective and objective fit, and conduct longitudinal analysis to enhance the explanatory power of the HOT fit model.
| Item Type: | Thesis (Doctoral) |
|---|---|
| Uncontrolled Keywords: | building information modeling; innovation; visualization; professional; Hong Kong; content analysis; network analysis; organizational structure; social network analysis; statistical analysis; case study; simulation; project organization |
| Index terms: | transformation, statistical analysis, network analysis, building information modelling, construction organization, Hong Kong, case study, dimension, construction industry, explanatory power, technology adoption, investigation, 4D simulation, literature review, content analysis, strategy, social network analysis, project organization, digitalization, organizational structure, longitudinal analysis, 3D visualization, visualization, level of development, construction project, configuration, practitioner |
| Subjects: | data collection methods, business, data analysis and analytics, data science, health monitoring assessment and metrics, management, design practice, industry analysis, systems engineering, information systems, sociology, practitioner, organization, innovation and technology management, digital technology, visualization, organizational theory, Geography, production management, theoretical framing, research methods |
| Topics: | Geographical Context, Project Management, Engineering Principles, Health and Safety, Design Practice, Digital Applications, Organizational Design, Research Practice, Business Strategy, Roles and Professions |
| Descriptive scope: | 5 PCTEA |
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