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NOTICE: This is the authors’ version of a work that was accepted for publication in the ASCE Journal of Management in Engineering. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published and can be accessed via the following link: http://ascelibrary.org/doi/abs/10.1061/%28ASCE%290742-597X%282009%2925%3A2%2869%29 PLEASE REFER TO THE RESEARCH IN THIS MANUSCRIPT, IF CITED, AS FOLLOWS: Taylor, J., and Bernstein, P. (2009). “Paradigm Trajectories of Building Information Modeling Practice in Project Networks,” ASCE Journal of Management in Engineering, 25(2): 69-76.
Paradigm Trajectories of Building Information Modeling Practice in Project Networks1 John E. Taylor, A.M.ASCE. 2 and Phillip G. Bernstein, F.AIA. 3
ABSTRACT Researchers have examined building information modeling (BIM), or parametric three-dimensional computer-aided design (3D CAD), from a myriad of technological perspectives. Many of these studies focus on examining or enhancing the interoperability of building information modeling technologies across project networks. The interoperability of business practices that must complement technological interoperability has been largely ignored. In this paper we examine building information modeling practice paradigms in project networks. We combine qualitative and quantitative data and analytical approaches to investigate 26 specific cases of firms using building information modeling tools. We identify four distinct practice paradigms and then induce an evolutionary model for building information modeling practice paradigm trajectories in project networks. The findings highlight the importance of understanding and developing interorganizational work practices to reap the benefits of building information modeling. CE Database Subject Headings: Computer-aided design, information systems, innovation, organizations, three-dimensional models
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Final Draft of Manuscript Prior to Publication. Article published in the ASCE Journal of Management in
Engineering and is available at: http://dx.doi.org/10.1061/(ASCE)0742-597X(2009)25:2(69). 2
Assistant Professor, Dept of Civil Engineering and Engineering Mechanics, Columbia University, Room 618, S.W.
Mudd Building, 500 West 120th Street, New York, NY 10027. Phone: (212) 854-1182. Fax (212) 854-6267. Email:
[email protected]. 3
Lecturer, School of Architecture, Yale University, 180 York Street, New Haven, CT 06511. Phone: (203) 432-
2288. Fax: (203) 432-7175. Email:
[email protected].
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INTRODUCTION Building information modeling (BIM) is a new industry term referring to parametric three-dimensional computer-aided design (CAD) technologies and processes in the architecture, engineering, and construction (A/E/C) industry. BIM technologies are unique when compared to earlier advances in CAD technology because when coupled with integration of work practices between architects, engineers, fabricators and contractors they can lead to tremendous improvements in project productivity. With twodimensional line-based CAD, data was typically exchanged between firms in the form of a printed set of plans. The plans themselves then became the visual representation where coordination and conflicts could be elaborated and resolved (Henderson 1999). However, with BIM a network of interdependent architects, engineers, fabricators and construction firms can collaborate to develop a virtual building information model of the planned structure (Taylor 2007). This paper presents the results of a seven month empirical investigation into the evolution of BIM practice paradigms. We identify four distinct practice paradigms and then examine paradigmatic evolution along two dimensions; experience with using BIM tools on projects and the extent of interorganizational sharing of building information models across project networks. A more thorough understanding of how BIM paradigms evolve in project networks will enable architects, engineers, fabricators and contractors to both anticipate and accelerate the capture of benefits associated with BIM tools and processes.
BACKGROUND Researchers contend that building information modeling technologies are being adopted more slowly in the A/E/C industry than its predecessor 2D CAD (Whyte et al. 2002; Whyte et al. 1999). Harty (2005) identified how the implementation of 3D CAD in a large infrastructure project had spillover effects which impacted multiple firms. He termed innovations like 3D CAD that impact multiple firms as "unbounded" innovations (2005, p. 512). Elsewhere researchers classify innovations that impact multiple specialist
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organizations as "systemic" innovations (Taylor and Levitt, 2004, p. 84). Research has shown how systemic innovations are more difficult to implement and diffuse more slowly than localized innovations (Taylor 2007, Taylor and Levitt 2007). In addition to research on adoption and implementation of 3D CAD, a number of researchers explore the development of objects and tools to support cooperative model-based design and construction (Kartam 1999; Roy and Kodkani 1999; Szykman et al. 2001; Halfawy and Froese 2005). Some of these researchers seek to address general issues of CAD object interoperability (Szykman et al. 2001) while others explore web-based forms of object exchange (Roy and Kodkani 1999) or idiosyncratic object extensions to capture the A/E/C design process (Halfawy and Froese 2005). A recent report by the National Institute of Standards and Technology in the United States (Gallaher et al. 2004) estimates the cost of inadequate interoperability in the A/E/C industry to be $15.8 billion. As a result, the body of literature on interoperability of model-based design software will likely continue to grow and evolve to address this global issue. Researchers focused on improving interoperability of model-based CAD tools are joined by a growing body of researchers seeking to use these tools to integrate processes not feasible with 2D CAD. Researchers explore the use of BIM tools to integrate and improve the scheduling of construction activities (Songer et al. 2001; Heesom and Mahdjoubi 2004), the estimation of costs (StaubFrench et al. 2003), the constructability of buildings (Fischer 1993), the identification of time-space conflicts in production (Akinci et al. 2002), and the visualization of the construction process (McKinney and Fischer 1998). The realization of the increased functionality and productivity associated with BIM tools requires firms to successfully adopt and implement the associated technologies. However, it has been shown that design and construction firms are adopting BIM tools slowly when compared to earlier adoption of 2D CAD (Whyte et al. 2002; Whyte et al. 1999). Users of these tools operate in interdependent project networks (Chinowsky and Taylor 2007). Research has show that BIM tools impact interdependent work processes in project networks (Harty 2005; Taylor 2007). To capture the full benefit of BIM tools, firms in project networks must coordinate and develop interoperable business practices. However, firms may
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have different interpretations –or paradigms– toward the practice of using BIM tools. Technological paradigms have been show to exist and vary among firms in a population (Dosi 1982). Differences in paradigmatic practice across organizations in a project network increase difficulties in developing interorganizational practices to support efficient use of BIM tools. This may explain difficulties identified in the adoption of BIM tools when compared to earlier 2D CAD adoption rates. In this paper we investigate and identify firm-level BIM practice paradigms in project networks. We examine how those paradigms evolve with increasing use of BIM tools on projects. Finally, we examine how interorganizational sharing of BIM models evolves firm-level paradigms in project networks evolve.
RESEARCH METHODOLOGY We employed a mixed research methodology which included qualitative and quantitative approaches to gather and analyze data regarding BIM practice paradigms. We asked informants to describe their use of BIM tools on recent projects to ascertain general patterns of use across cases included in the study. From this data we developed a grounded understanding of firm-level paradigms of BIM practice. Because we were interested specifically in how these paradigms evolved over time and how they impacted the project network we also collected data from each firm interviewed about the number of projects they had completed using BIM tools and the extent to which current projects shared building information models across the project network. Researchers propose that qualitative researchers include multiple data collection methods to increase construct validity (Eisenhardt 1989). We utilized interviews, direct observation, and primary documentation to collect data on BIM practice paradigms. Researchers recommend examining multiple cases to manage the internal validity of the constructs identified (Eisenhardt 1991). We examined 26 distinct cases of organizations that had used BIM tools on at least one project. Since we specifically
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selected firms that had completed at least one project using BIM tools, the organizations in the study were selected for their ability to provide analytic generalization (Yin 1989). Of the firms investigated in this project, 13 were construction firms, 10 were architecture firms, and 3 were engineering firms. We did not select firms that were using a specific BIM tool, but did require that the tool be a parametric, object-based 3D CAD tool. A number of tools meeting this requirement have been introduced into the A/E/C marketplace in the past decade. We were less interested in the specific tool and more interested in identifying consistent paradigmatic trends across different BIM tools. We included only firms that had completed at least one project using BIM tools. Of the firms included in our study, 13 had completed between one and five BIM projects, 9 had completed between six and twenty-five projects, and 4 had completed more than twenty-six projects. The ranges were determined after several interviews when it became apparent that interviewees could not pinpoint the exact number of projects their organization had completed. Those same firms had little problem determining whether their firm had completed between one and five projects, between six and twenty-five projects, or more than twenty-six projects. The contacts for the first several firms included in the study originated from contacts provided by Autodesk, Inc. and the Stanford University Center for Integrated Facility Engineering. However, following these initial contacts we utilized a snowball sampling technique. As we interviewed the first several firms, we asked for contact names at other firms that they knew were actively using BIM tools. Because we allowed the sampling to progress over the course of the study, the firms originated from multiple locations and had varying scales of operation. Of the firms included in the study, 16 were based in the United States, 8 were based in Europe, 1 was based in Australia, and 1 was based in Asia. Regarding the scope of their business activity, 15 had international operations, 7 had national operations, and 4 had only local operations. A summary of the descriptive statistics for the 26 cases examined in this manuscript are contained in Table 1.
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Table 1. Descriptive Statistics of Cases Investigated
Case 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26
Discipline Contractor Contractor Contractor Contractor Contractor Contractor Contractor Contractor Contractor Contractor Contractor Contractor Contractor Engineer Engineer Engineer Architect Architect Architect Architect Architect Architect Architect Architect Architect Architect
Base of Operations United States Europe United States Asia United States United States Europe Europe Europe Europe United States United States United States United States Europe United States United States United States United States Europe United States United States United States Europe United States Australia
Scale of Operations International International National International International National International National International International Local Local Local National National Local National National International International International International International International International International
# BIM Projects Completed 6-25 6-25 1-5 1-5 >26 6-25 >26 6-25 6-25 >26 1-5 1-5 1-5 6-25 6-25 1-5 1-5 1-5 6-25 1-5 1-5 >26 1-5 1-5 1-5 6-25
Extent of BIM Electronic File Sharing Into Supply Chain Across Project Network Across Project Network Within Firm Into Supply Chain Across Project Network Into Supply Chain Across Project Network Into Supply Chain Into Supply Chain Into Supply Chain Across Project Network Across Project Network Into Supply Chain Into Supply Chain Across Project Network Within Firm Across Project Network Within Firm Within Firm Across Project Network Into Supply Chain Across Project Network Across Project Network Across Project Network Into Supply Chain
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Interviews were approximately two hours in duration and ranged from one to four hours in length. We collected and analyzed over 50 hours of interview data during the course of the project. In addition to interview discussions, direct observations were made within two of the interviewed firms to observe the process of BIM tool usage. Much more in-depth observations were able to be made with these two firms. We were invited to attend company meetings and project discussions, to visit project sites both under construction and recently completed, and to generally observe the interaction between participants on the projects. We took extensive notes during this process and took digital photographs for use in our data analysis. Interview discussions and observations were recorded in a numbered set of field research notebooks. Interview discussions were also recorded using a digital voice recorder. We requested hard copies of materials discussed during interview discussions and observations. Data collected included contract documents, process flow diagrams, construction schedules, building information models, bills of materials, project decision schedules, animations of building information models, and any other information that might lend insight into the utilization of BIM tools. This primary documentation was attached to our field notebooks and often elucidated concepts that were not entirely clear when reviewing the notes from an interview or observation. Overall, we were able to manage the reliability of our findings by keeping an indexed, organized database of our field notebooks, audio interview files, photographs, and documentation collected. Initially we analyzed the qualitative data to discern consistent patterns that emerged within specific firm-level paradigms. The qualitative data was analyzed using the line-by-line microanalysis technique to identify quotes relevant to BIM practice (Strauss and Corbin 1990). Four distinct paradigms emerged from the quotes and these were further refined using the constant comparative method (Glaser and Strauss 1967) and axial coding (Strauss and Corbin 1990). Next we analyzed quantitative data collected from the cases to ascertain whether an evolution along the paradigmatic trajectory correlated with increased utilization of BIM on projects. Finally, we tested for a correlation as to whether evolving along the BIM practice paradigm trajectory impacted interorganizational sharing of BIM electronic files.
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BUILDING INFORMATION MODELING PRACTICE PARADIGMS The primary research question explored in this project was to identify BIM practice paradigms. In the process of aggregating data from the interviews and observations a pattern of clear and distinct paradigms emerged. We categorized each firm as fitting into one of four emergent paradigmatic categories of BIM practice; visualization, coordination, analysis, or supply chain integration. In the following sections we describe each of these BIM practice paradigms and include representative quotes from the data.
Visualization Paradigm Only two firms in the study still maintained a BIM practice paradigm of visualization after completing at least one BIM project. However, each of the firms in the study at one time in their past did view BIM tools chiefly as a way to improve how the model for a project was visualized and communicated to the various project stakeholders. From a number of interviews, discussions and presentations the authors have been involved in outside the scope of this project; it appears that firms which have not yet implemented BIM perceive the primary role of the tools as enhancing visualization. One European contractor who held a visualization paradigm described BIM practice in his organization during our interview as follows: “the 2-D CAD model is deceptive to clients, it doesn’t represent reality … with the 3-D model we can get closer to visualizing reality … we can now specify finishes in such a way that the owner gets what they are asking for”
An architect from the United States who also adopted a visualization paradigm of BIM practice described the impact of visualization on project decision making as follows: “clients don’t get 2-D, you need 3-D, even 4-D, one owner made a decision to spend hundreds of millions of dollars on a project based on a 90 second animation of the 3-D model”
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The visualization paradigm for BIM practice was described by other firms interviewed as being their initial approach to using BIM on projects. Based on this qualitative data we position the visualization paradigm as the first stage in BIM practice paradigm evolutionary trajectory.
Coordination Paradigm After evolving beyond a paradigm of visualization, firms interviewed described using BIM to improve the coordination of work within the firm and across the project network. Nearly half of the firms included in this research project adopted a BIM paradigm of coordination. None of these firms had completed more than five BIM projects. Therefore, very quickly after adopting BIM tools, firms adopt a coordination paradigm. However, because so many of the firms included in the study were still at this level of paradigmatic evolution, the findings suggest that firms have difficulty moving beyond issues of coordination to reap the full benefits of BIM. Of the 11 firms that were at this paradigmatic stage of BIM practice, 9 had worked out the sharing of electronic BIM files with other firms on projects. Only 2 of the firms did not share files outside of their firm. It is not surprising that firms viewing BIM as a way to improve coordination would seek ways to improve technological interoperability to exchange electronic files. One architect from the United States described how BIM supports coordination in the following quote: “today we design the structure, then the ducts, then the plumbing, then the lighting systems … this all occurs in stratifications of space, with BIM we pre-coordinate the penetrations and do things like nestle the lighting systems between ducts” Similar comments were made by an engineering design firm based in the United States. That engineer described how the key benefit of BIM was to check for conflicts in the model. He described using BIM to “identify coordination issues like ‘where are the slab edges?’ and ‘where is the elevator opening?’” The aforementioned examples describe a coordination paradigm that seeks to improve coordination across a project network. One firm interviewed primarily viewed their utilization of BIM as a way to improve coordination of design files –and hence productivity– within their firm. This outlier
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case involved a firm that only shared electronic files within their firm (not with project partners). The firm that refused to share their BIM files viewed their increased productivity with improved internal BIM model coordination as a source of firm competitive advantage. They did not want to share electronic files with their customer and partner firms or even let those firms know they were using BIM. In this way they could charge similar rates for the same work that was taking them substantially less time to complete. The architect from this U.S. firm described the firm-level focus of BIM practice as follows: “we did a very similar project with BIM to one we did in 2-D CAD and our total internal costs were 33% lower, but our charges to the owner were the same … we would like to maintain that profit margin but when competitors start to lower their price then we'll have to lower ours”
The remaining firms included in the study did not express the same firm-level accrual of interests. In contrast, they viewed BIM as a way to impact coordination for the entire project, including all the stakeholders on the project. An architect from the United States described how a more project-centric view of coordination can impact the overall project in the following quote: “if you can get a good group of guys on the project willing to take on the challenge of BIM you can do it in less time with less people … we’re saving a month or more by getting the fabricator involved earlier in the process”
Analysis Paradigm All of the firms in the study that adopted an analysis paradigm of BIM utilization shared electronic files with other firms on projects (in three of four cases) or with fabricators and suppliers in the supply chain (in the remaining one out of four cases). This suggests that some sharing of electronic files would be necessary for BIM to be an effective tool for analysis. The four firms that adopted a BIM practice paradigm of analysis had all completed between six and twenty-five projects. This suggests again that some experience with BIM is required in order to evolve to this stage of paradigmatic evolution. A representative quote from a firm adopting a BIM paradigm of analysis is as follows: “we were able to test the energy utilization of the building and iterate the building shape, insulation, windows, lighting options and the planning of space to optimize overall building cost and energy utilization concerns”
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Firms with an analysis BIM paradigm described a variety of analytical possibilities using BIM models. For example, firms described using models to analyze the impact of design changes on cost, to analyze access and egress patterns in situations of fire, to analyze lighting scenarios and optimize utilization of natural light, to analyze thermal loads using dynamic thermal modeling (DTM), and to analyze the flow of wind and ventilation using computational flow dynamics (CFD).
Supply Chain Integration Paradigm The most evolved BIM paradigm identified in this research project was the supply chain integration BIM practice paradigm. Only one of the nine firms that evolved to this paradigm had completed five BIM projects or less. Four of the firms had completed between six and twenty-five projects and the remaining four had completed over twenty six projects. The fact that one firm adopted a supply chain integration paradigm within its first five BIM projects suggests that a firm does not need to evolve through the successive stages of BIM evolution consecutively. However, upon closer examination of this company, we realized that this startup construction firm was actually an integrated provider of materials and construction and made supply chain integration a fundamental component of its business model from their very first project. If we examine the remaining eight firms that adopted a supply chain integration BIM paradigm, we observe overall that they completed a relatively large number of BIM projects. Of all the cases included in this research investigation only four firms had completed over twenty-six BIM projects and three of those four had evolved to a paradigm of supply chain integration. The outlier case of the integrated material manufacturing and construction firm notwithstanding, it appears to take a significant amount of actual BIM experience to evolve to this paradigm. Not surprisingly, we can also observe that all of the nine firms which adopted a supply chain integration paradigm were sharing files with other firms in the supply chain. A European contractor described the supply chain integration BIM practice paradigm as follows:
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“we proved that CAD/CAM is possible in the construction industry with products that are difficult to define … we automated the window specification process by integrating manufacturer knowledge of 100 to 150 parameters and moved it to the point where the architect specifies the window”
Firms that evolved to a supply chain integration practice paradigm for BIM described how the same BIM model created to design the building could be used by manufacturing firms to actually configure to order or manufacture the materials that go into the building. A number of firms spoke of BIM models “feeding machines” which is to say that the model itself would be used to drive computer numerically controlled (CNC) manufacturing machinery. Firms at this level of paradigmatic evolution described that the real savings from supply chain integration was not from the sharing of electronic files in the supply chain, but from redesigning the process in response to a more integrated modeling approach.
BUILDING INFORMATION MODELING PRACTICE PARADIGM TRAJECTORIES With the specific BIM practice paradigms identified, we needed further research to test whether or not the paradigms evolve with increasing utilization of BIM on projects. In other words, are the paradigms themselves static or do they dynamically evolve over time? Furthermore, in order to understand how interorganizational practices evolve we also needed to test whether, as firms evolved from one paradigm to the next, the propensity to share BIM electronic files increased (within the firm, across the project network, or into the supply chain). The following two hypotheses describe the foundation for two statistical analyses we will describe in the following sections.
HYPOTHESIS 1. As firm-level BIM practice paradigms evolve from ‘Visualization’ to ‘Coordination’ to ‘Analysis’ to ‘Supply Chain Integration’, the number of BIM projects those firms have executed will increase. HYPOTHESIS 2. As firm-level BIM practice paradigms evolve from ‘Visualization’ to ‘Coordination’ to ‘Analysis’ to ‘Supply Chain Integration’, the extent to which firms share BIM electronic files will increase from ‘Within the Firm’ to ‘Across the Project Network’ to ‘Into the Supply Chain’.
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We use cross-tabular relationship tests to test relationships among the three categorical types of data (BIM practice paradigm, BIM project experience, and extent of BIM file sharing). First we test using a Chi-squared (χ2) distribution whether the data from the two categories of data are independent. This is done by measuring the degree of deviation between observed (O) and expected (E) frequencies according to the following equation. χ2 = Σ [ (O – E)2 / E ]
(1)
Assuming the two categories of data are independent, we next calculate the coefficient of determination to indicate the relative strength of the relationship. We compare the Chi-squared value in (1) with the maximum Chi-squared value (χ2max) to compute the relative strength of the relationship. The maximum Chi-squared value is calculated as follows: χ2max = N (A – 1) where;
(2)
N = total number of cases categorized A = number of rows or columns (whichever is smaller)
The coefficient of determination (D) then becomes the Chi-squared value in (1) divided by the maximum Chi-squared value in (2). D = χ2 / χ2max
(3)
The coefficient of determination identified in (3) will be a value in the range from 0 to 1 which when expressed as a percentage gives the relative strength of the relationship between the two categorical variables in the data set.
Table 2. Cross-tabular Comparison of BIM Practice Paradigm and Number of BIM Projects Executed BIM Practice Paradigm # BIM Projects Executed 1-5 6-25 >26 Column Totals
Visualization 2 0 0 2
Coordination 10 1 0 11
Analysis 0 4 0 4
Supply Chain Integration 1 4 4 9
Row Totals 13 9 4 26
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Cross-tabular Relationship between BIM Practice Paradigm and BIM Project Experience Table 2 includes cross-tabular data for BIM practice paradigm trajectory and BIM project experience. We hypothesized in Hypothesis 1 that there is a positive relationship between these two categorical data sets. In other words, firms evolve from one BIM practice paradigm to the next as they gain experience executing BIM projects. To conduct the Chi-squared test for independence we need to create a table with the observed and expected frequencies for each combination of categorical variable. This is presented in Table 3. The Chi-squared value ffor this cross-tabular comparison calculated using equation (1) is 24.9136. This results in a ρ value of less than 0.001, indicating very strong evidence against the null hypothesis. Therefore, the two categories of data are independent. We then used equation (2) to determine the maximum Chi-squared value which resulted in a value of 52.
The coefficient of
determination from equation (3) produces a relative strength of the relationship between the variables of 47.91%. Hence, we confirm our Hypothesis 1 finding that as BIM practice paradigms evolve along the trajectory identified in our qualitative data analysis, they must gain increased experience with BIM tool utilization on projects. Table 3. Comparison of Observed (O) and Expected (E) Frequencies for Categorical Data Comparing BIM Practice Paradigm and Number of BIM Projects Executed
BIM Practice Paradigm # BIM Projects Executed
Supply Chain Visualization Coordination Analysis Integration Row Totals O = 0.0769 O = 0.3846 O = 0.0000 O = 0.0385 O = 0.5000 1-5 E = 0.0385 E = 0.2115 E = 0.0769 E = 0.1731 E = 0.5000 O = 0.0000 O = 0.0385 O = 0.1538 O = 0.1538 O = 0.3461 6-25 E = 0.0266 E = 0.1464 E = 0.0533 E = 0.1198 E = 0.3461 O = 0.0000 O = 0.0000 O = 0.0000 O = 0.1538 O = 0.1538 >26 E = 0.0118 E = 0.0651 E = 0.0237 E = 0.0533 E = 0.1538 O = 0.0769 O = 0.4231 O = 0.1538 O = 0.3462 O = 1.0000 Column Totals E = 0.0769 E = 0.4231 E = 0.1538 E = 0.3462 E = 1.0000 2 χ = 24.9136; ρ = 0.0004 (since ρ < 0.001 there is very strong evidence against the null hypothesis) Coefficient of Determination 0.4791 Totals may not add to 1.0000 due to rounding
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Cross-tabular Relationship between BIM Practice Paradigm and BIM File Sharing Table 4 includes cross-tabular data for BIM practice paradigm trajectory and BIM electronic file sharing. In Hypothesis 2 we hypothesized a positive relationship between these two categorical data sets. As firms evolve along the BIM practice paradigm trajectory they will tend to increase the extent to which they share electronic BIM files. To conduct the Chi-squared test for independence we created a table with the observed and expected frequencies for each combination of categorical variable and these are presented in Table 5. The Chi-squared value for this cross-tabular comparison calculated using equation (1) is 34.2432. This results in a ρ value of less than 0.001, indicating very strong evidence against the null hypothesis and, hence, the two categories of data are independent. Since the number of rows and columns and the number of the cases is the same as in the examination of Hypothesis 1, the maximum Chi-squared value remains 52. The coefficient of determination from equation (3) produces a relative strength of the relationship between the variables of 65.85%.
This confirms Hypothesis 2 that as BIM practice
paradigms evolve, firms increase the extent to which they share electronic BIM files. Table 4. Cross-tabular Comparison of BIM Practice Paradigm and Extent of BIM Electronic File Sharing BIM Practice Paradigm Extent of BIM Electronic File Sharing Within Firm Across Project Network Into Supply Chain Column Totals
Visualization 2 0 0 2
Coordination 2 9 0 11
Analysis 0 3 1 4
Supply Chain Integration 0 0 9 9
Row Totals 4 12 10 26
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Table 5. Comparison of Observed (O) and Expected (E) Frequencies for Categorical Data Comparing BIM Practice Paradigm and Extent of BIM Electronic File Sharing
BIM Practice Paradigm Extent of BIM Electronic Supply Chain File Sharing Visualization Coordination Analysis Integration Row Totals O = 0.0769 O = 0.0769 O = 0.0000 O = 0.0000 O = 0.1538 Within Firm E = 0.0118 E = 0.0651 E = 0.0237 E = 0.0533 E = 0.1538 O = 0.0000 O = 0.3462 O = 0.1154 O = 0.0000 O = 0.4615 Across Project Network E = 0.0355 E = 0.1953 E = 0.0710 E = 0.1598 E = 0.4615 O = 0.0000 O = 0.0000 O = 0.0385 O = 0.3462 O = 0.3846 Into Supply Chain E = 0.0296 E = 0.1627 E = 0.0592 E = 0.1331 E = 0.3846 O = 0.0769 O = 0.4231 O = 0.1538 O = 0.3462 O = 1.0000 Column Totals E = 0.0769 E = 0.4231 E = 0.1538 E = 0.3462 E = 1.0000 χ2 = 34.2432; ρ = 0.0000 (since ρ < 0.001 there is very strong evidence against the null hypothesis) Coefficient of Determination = 0.6585 Totals may not add to 1.0000 due to rounding
BIM Practice Paradigm Trajectories In the two preceding sections we analyzed categorical data across the 26 cases included in this research. However, two outlier cases were observed; one firm refused to and had no future plans to share BIM electronic files in order to maintain firm-level competitive advantage and another firm immediately integrated file sharing across the supply chain since their business model was to provide integrated services. Even with the inclusion of these two outlier cases the Chi-squared test resulted in confirmation of Hypothesis 1 and Hypothesis 2. However, to create a general purpose model for BIM practice paradigm trajectory evolution, we will treat these two outlier cases separately. Most of the cases investigated (24 out of 26 cases) follow a sequential trajectory from a paradigm of visualization, to one of coordination, to an analysis paradigm, and finally to a supply chain integration BIM practice paradigm. A firm evolves down this paradigmatic trajectory as it gains experience using BIM tools on projects and as it makes the strategic decision to share electronic BIM files across the project network and into the supply chain (see evolutionary trajectory number 1 in Figure 1 below).
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However, two other outlier cases suggest that this trajectory is not the only possible paradigmatic evolution.
Increasing BIM Experience on Projects
Figure 1. Paradigm Trajectories of Building Information Modeling Practice
Supply Chain Integration
Coordination
25
(within firm)
20 Analysis
15 Coordination
2
(across project network)
10
1
3
5 Visualization Within Firm
Across Project Network
Into Supply Chain
Extent of BIM File Sharing
A firm that elects not to share files with other firms on projects or in the supply chain diverges from evolutionary trajectory 1 from Figure 1.
This firm maintains a BIM practice paradigm of
coordination and remains focused on improving productivity internal to the firm. In doing so, the firm limits its ability to evolve to the later paradigmatic stages of analysis and supply chain integration. This evolutionary path is illustrated as trajectory 2 in Figure 1. Conversely, a new firm entering the market with a business model that requires integration of BIM electronic files either across the project or into the supply chain can skip earlier evolutionary stages. The firm in our study immediately adopted a BIM practice paradigm of supply chain integration (see evolutionary trajectory number 3 in Figure 1 below).
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This seems particularly likely to occur as new firms emerge in the area of structural steel fabrication according to several firms interviewed. promising for the A/E/C industry.
The existence of this third evolutionary trajectory is very
Firms that achieved the supply chain integration BIM practice
paradigm described tremendous improvements in overall project productivity and efficiency.
The
possibility that firms might achieve these improvements within the first few projects is of great benefit to an industry that has been described as having poor productivity performance.
CONCLUSION This paper identifies four paradigms for building information modeling practice in A/E/C project networks. It demonstrates that with increasing project experience, firm-level BIM practice paradigms evolve along a trajectory from visualization, to coordination, to analysis, and finally to supply chain integration. It further establishes that as firms evolve along a BIM practice paradigm trajectory, they are increasingly disposed to share electronic BIM files across the project network and into the supply chain for building materials. Interorganizational practices, therefore, evolve as BIM practice paradigms evolve. In over 92% of the cases identified in this research, firms followed the aforementioned BIM practice paradigm trajectory. However, in one case, a firm’s paradigm evolution was forestalled due to that firm’s unwillingness to share electronic files across the project network or into the supply chain. Although they had completed a large number of BIM projects, they failed to evolve beyond the coordination paradigm. Hence, a firm-level focus on the advantages of BIM can result in firms failing to benefit fully from BIM tools. In a second outlier case, a firm effectively bypassed the first three paradigms in a typical BIM practice paradigm trajectory. That firm was formed with a business model to provide integrated material manufacturing and construction services. They were thus able to proceed immediately to a paradigm of supply chain integration upon the formation of the business. Although the forestalled trajectory and the accelerated trajectory together only represented two of twenty-six cases
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investigated, they do provide two alternative paradigmatic trajectories. In total, three trajectories for BIM practice evolution are introduced in this paper. Previous research on BIM or parametric 3D CAD has focused largely on issues of technological interoperability. A report by the National Institute of Standards and Technology in the United States described inadequate interoperability of technology in the design and construction industry in the United States alone as a $15.8 billion problem annually (Gallaher et al. 2004). Therefore research focused on improving BIM technological interoperability will certainly continue to increase. The research presented in this paper, however, contributes to a growing area of research to understand how organizational and interorganizational practices evolve when technological changes like BIM span organizational boundaries in project networks. Addressing technological interoperability is not sufficient to unleash the benefits of integrated technologies. When technological change spans interorganizational boundaries in project networks, interorganizational business practices must also evolve and adapt to these changes. Future research should examine how differences in BIM practice paradigms impact project performance. The existence of some firms who view BIM as a way to enhance visualization, others that see BIM as playing an important coordination role, still others viewing BIM principally as an analytical tool, and finally others who view BIM chiefly as a means to integrate product information into the supply chain is likely to limit the benefits of using BIM for all firms in the project network. Research should identify ways to improve coordination given the existence of this array of paradigms that can co-exist on a project. A promising avenue for future research would be to examine whether firms choosing partners in interdependent project activities based on their stage of practice paradigmatic evolution impacts firmlevel and project-level performance.
ACKNOWLEDGMENTS This research was supported by Autodesk, Inc. and the Stanford University Gerald J. Lieberman Fellowship. In additional to acknowledging financial support, the author also wishes to thank Ray Levitt
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and Bob Tatum for their input and support, as well as the many companies who offered their time to participate in this research investigation.
REFERENCES Akinci, B., Fischer, M., Levitt, R., and Carlson, B. (2002). “Formalization and automation of time-space conflict analysis.” Journal of Computing in Civil Engineering, 6(2) 124–135. Chinowsky, P., and Taylor, J. (2007). “Project networks: Learning, leadership and development.” In M. Sexton (Ed.), Revaluing construction: 54–65. Rotterdam, Netherlands: International Council for Research and Innovation in Building Construction. Dosi, G. (1982). “Technological paradigms and technological trajectories: A suggested interpretation of the determinants and directions of technical change.” Research Policy, 11(3): 147–162. Eisenhardt, K. (1989). “Building theories from case study research.” Academy of Management Review, 14(4): 532–550. Eisenhardt, K. (1991). “Better stories and better constructs: the case for rigor and comparative logic.” Academy of Management Review, 16(3): 620–627. Fischer, M. (1993). “Automating constructibility reasoning with a geometrical and topological project model.” Computing Systems in Engineering, 4(2-3): 179–192. Gallaher, M., O'Connor, A., Dettbarn, J., and Gilday, L. (2004). Cost Analysis of Inadequate Interoperability in the U.S. Capital Facilities Industry. Gaithersburg, MD: U.S. Department of Commerce Technology Administration, National Institute of Standards and Technology. Glaser, B., and Strauss, A. (1967). The Discovery of Grounded Theory: Strategies for Qualitative Research. New York: Aldine. Halfaway, M., and Froese, T. (2005). “Building Integrated Architecture/Engineering/Construction Systems Using Smart Objects: Methodology and Implementation.” Journal of Computing in Civil Engineering, 19(2): 172–181.
21
Harty, C. (2005). “Innovation in construction: a sociology of technology approach.” Building Research and Information, 33(6): 512–522. Heesom, D., and Mahdjoubi, L. (2004). “Trends of 4D CAD applications for construction planning.” Construction Management and Economics, 22(2): 171–182. Henderson, K. (1999). On Line and On Paper: Visual Representations, Visual Culture and Computer Graphics in Design Engineering. Cambridge, MA: MIT Press. McKinney, K., and Fischer, M. (1998). “Generating, evaluating and visualizing construction schedules with 4D-CAD tools.” Automation in Construction, 7(6) 433–447. Roy, U., and Kodkani, S. (1999). “Product modeling within the framework of the World Wide Web.” IIE Transactions on Design and Manufacturing, 31(7): 667–677. Songer, A., Diekmann, J., Rasheed, K., and Hays, B. (2001). “Construction scheduling using 3-D CAD walk-thru.” Construction Innovation, 1(3) 191–207. Staub-French, S., Fischer, M., Kunz, J., and Paulson, B. (2003). “An ontology for relating features with activities to calculate costs.” Journal of Computing in Civil Engineering, 17(4) 243–254. Strauss, A., and Corbin, J. (1990). Basics of Qualitative Research: Grounded Theory Procedures and Techniques. Sage, Newbury Park, CA. Szykman, S., Fenves, S., Keirouz, W., and Shooter, S. (2001). “A foundation for interoperability in nextgeneration product development systems.” Computer-Aided Design, 33(7): 545–559. Taylor, J. (2007). “The antecedents of successful 3D CAD implementation in design and construction networks.” Journal of Construction Engineering and Management, in press. Taylor, J., and Levitt, R. (2004). “Understanding and managing systemic innovation in project-based industries.” In D. Slevin, D. Cleland, & J. Pinto (Eds.), Innovations: Project Management Research 2004: 83–99. Newton Square, PA: Project Management Institute. Taylor, J., and Levitt, R. (2007). “Innovation alignment and project network dynamics: An integrative model for change.” Project Management Journal, in press.
22
Whyte, J., Bouchlaghem, N., and Thorpe, A. (2002). “IT implementation in the construction organization.” Engineering, Construction and Architectural Management, 9(5-6): 371–377. Whyte, J., Bouchlaghem, N., Thorpe, A., and McCaffer, R. (1999). “A survey of CAD and virtual reality within the house building industry.” Engineering, Construction, and Architectural Management, 6(4): 371–379. Yin, R. (1989). Case study research, design and methods. Newbury Park, CA: Sage Publications.
