Since the early 1990s, scholars of digital construction technology have developed increasingly sophisticated theoretical models for integrating design, engineering, and project management into a unified digital framework. These advancements have largely outpaced the practical implementation of digital tools, particularly in U.S. residential construction. One of the earliest and most significant contributions to this field came from G. A. van Nederveen and F. P. Tolman. In their article “Modelling Multiple Views on Buildings,” they introduce a conceptual framework that later became fundamental to building information modeling (BIM).¹ Nederveen and Tolman argue that construction professionals engage with a project from different disciplinary perspectives. Yet these perspectives must be digitally unified to ensure consistency throughout a building’s lifecycle. Despite the potential of their theoretical model, the technology required to fully realize it remains underdeveloped.

The divergence between digital construction theory and its practical implementation can be traced through several key historiographical trends. Charles Eastman, one of the earliest scholars to investigate digital building representations, outlined the first systematic approach to object-based design in the 1970s. His seminal work, “An Outline of the Building Description System,” published as a research report at the Georgia Institute of Technology, anticipated many of the principles that later defined BIM.² His influence carried into later decades, culminating in the BIM Handbook, co-authored with Paul Teicholz, Rafael Sacks, and Kathleen Liston, which became a foundational text for understanding the evolution and implementation of BIM in construction industries.³

Scholars have debated the nature and function of BIM since its early development, particularly regarding whether it should be classified primarily as a technological tool or a conceptual framework. Andrzej Szymon Borkowski has examined the epistemological challenges of defining BIM, arguing that its ambiguous status as both a software-driven approach and a theoretical paradigm has complicated its adoption (Borkowski 2023, 646). Some scholars emphasize BIM’s role as a collaborative process that integrates multidisciplinary data into a shared digital environment, while others argue that its most critical function lies in its capacity to enhance predictive modeling and improve the accuracy of project execution.⁴

As BIM evolved from a theoretical concept into a digital construction tool, scholars recognized its potential for improving efficiency and reducing errors in large-scale infrastructure and commercial projects. However, its application in residential construction has remained limited, as Kim Hua Tan, Guojun Ji, Chee Peng Lim, and Ming-Lang Tseng have shown in their analysis of big data and decision-making in digital environments. They argue that industries that successfully integrate digital technologies do so by developing structured knowledge systems that transform raw data into actionable insights.⁵ In contrast, residential construction firms frequently generate vast amounts of data without corresponding strategies for systematically collecting, analyzing, and applying that information.

The lack of long-term data management in residential construction has resulted in what scholars term “dark data”, or information that is collected but not actively utilized for decision-making. Mattia Pedota has demonstrated that industries lacking a structured approach to data retention and knowledge sharing struggle to develop the flexibility needed for technological adaptation. Without a comprehensive strategy for managing digital information, residential construction firms remain unable to leverage BIM and other digital construction technologies to their full potential.⁶

The absence of a standardized definition of BIM further complicates its implementation. Dana K. Smith and Michael Tardif, in their book Building Information Modeling: A Strategic Implementation Guide, stress that a major barrier to BIM adoption is the inconsistency in how different firms interpret and utilize it.⁷ Some companies regard BIM as a software platform for 3D modeling, while others view it as a methodological approach to project management and lifecycle analysis. This lack of standardization has led to fragmented implementation strategies, reinforcing skepticism among construction professionals about BIM’s practical benefits.

Compounding these challenges, the emergence of new digital construction technologies has introduced both opportunities and obstacles. Andrew McCoy and Armin Yeganeh, in their research on emerging construction technologies, highlight the potential of modular construction, geospatial tracking, artificial intelligence-driven project management, and robotics to increase efficiency, reduce costs, and improve project outcomes.⁸ However, they also emphasize that these technologies remain difficult to integrate into existing workflows, particularly in an industry where interoperability between software platforms is limited.

The historiography of digital construction technology reveals that the persistent gap between digital construction theory and practical adoption in residential construction results from three key factors. The first is the underdevelopment of digital construction hardware and software, which has yet to achieve the functionality envisioned by early theorists such as van Nederveen, Tolman, and Eastman. The second is the industry’s treatment of construction data as ephemeral, preventing the accumulation of historical knowledge that could drive innovation. The third is the lack of a standardized definition of BIM, leading to inconsistent implementation and limited adoption. Until these foundational issues are addressed, the theoretical promise of digital construction will continue to exceed its practical application.

The historiography of digital construction technology demonstrates that while scholars have made significant advancements in theory, modeling, and data-driven decision-making, the U.S. residential construction industry has been slow to adopt these innovations. Scholars such as van Nederveen, Tolman, Eastman, Borkowski, and Tan have developed theoretical models and frameworks that emphasize the importance of digital integration in construction management. However, the practical challenges of data retention, interoperability, and industry-wide standardization have limited digital adoption in the residential sector.

As Everett Rogers’ diffusion of innovation theory suggests, successful technological adoption requires the reduction of uncertainty through structured information management.⁹ If residential construction firms fail to establish long-term data strategies and knowledge-sharing mechanisms, digital construction tools will remain an underutilized resource. The future of digital construction technology in residential buildings depends on the industry’s ability to treat data as an asset rather than a byproduct. Until firms recognize that historical project data can inform and optimize future construction efforts, the divide between digital construction theory and its practical implementation will persist.

Notes

1. G. A. van Nederveen and F. P. Tolman, “Modelling Multiple Views on Buildings,” Automation in Construction 1, no. 3 (December 1, 1992): 215–24, https://doi.org/10.1016/0926-5805(92)90014-B. ↩︎
2. Charles Eastman, “An Outline of the Building Description System. Research Report No. 50,” Research Report, Physical Planning (Pittsburgh, PA: Carnegie-Mellon University, September 1974), 3-4 https://eric.ed.gov/?id=ED113833. ↩︎
3. Eastman et al., eds., BIM Handbook, 1-12. ↩︎
4. Bilal Succar, “Building Information Modelling Framework: A Research and Delivery Foundation for Industry Stakeholders,” Automation in Construction 18, no. 3 (May 1, 2009): 357-375. ↩︎
5. Kim Hua Tan et al., “Using Big Data to Make Better Decisions in the Digital Economy,” International Journal of Production Research 55, no. 17 (September 2, 2017): 4998–5000, https://doi.org/10.1080/00207543.2017.1331051. ↩︎
6. Mattia Pedota, “Big Data and Dynamic Capabilities in the Digital Revolution: The Hidden Role of Source Variety,” Research Policy 52, no. 7 (September 1, 2023): 104812, https://doi.org/10.1016/j.respol.2023.104812. ↩︎
7. Dana K. Smith and Michael Tardif, Building Information Modeling: A Strategic Implementation Guide for Architects, Engineers, Constructors, and Real Estate Asset Managers (Hoboken: John Wiley & Sons, 2012), 34-35. ↩︎
8. Andrew McCoy and Armin Yeganeh, “An Overview of Emerging Construction Technologies,” Research Report, NAIOP Research Foundation Reports (Herndon, VA: National Association of Industrial and Office Parks, March 2021), https://www.naiop.org/globalassets/research-and-publications/report/an-overview-of-emerging-construction-technologies/researchreportnaiop-emerging-construction-technologies.pdf. ↩︎
9. Everett M. Rogers, Diffusion of Innovations (New York: Simon and Schuster, 1962), 13. ↩︎