Characterizing the Effects of Cloud-Based BIM Collaboration Tools on Design Coordination Processes

Abstract

Design coordination is a critical process for avoiding spatial conflicts and ensuring design alignment in large-scale construction projects. While Building Information Modelling (BIM) tools have improved coordination through 3D model integration and clash detection, inefficiencies persist due to fragmented workflows, frequent tool switching, and challenges with issue documentation. Cloud-based BIM collaboration tools offer a promising alternative by enabling real-time model sharing, centralized issue tracking, and enhanced stakeholder communication. However, empirical evidence on their practical implementation and effects on coordination processes remains limited. Unlike prior cloud-BIM reviews that focus on technical capabilities or adoption barriers in isolation, this study provides an empirically grounded framework that links specific tool features to observable workflow changes and their downstream impacts on coordination outcomes. This study investigates the impact of cloud-based BIM collaboration tools on the design coordination process, with a focus on issue identification, resolution, and documentation. A framework was developed using a mixed-methods approach comprising action research, an ethnographic case study, and comparative analysis of three large infrastructure projects to categorize workflow changes resulting from tool adoption. The findings indicate that cloud-based BIM tools streamline coordination by reducing manual transitions, automating documentation, and improving information accessibility during meetings. Nevertheless, their effectiveness is constrained by organizational structures and contract limitations. This study provides a validated process-change framework and practical insights for engineering managers seeking to align digital collaboration tools with project delivery strategies, contributing to both theory and practice in BIM-based coordination and digital transformation in the AEC industry.

1. Introduction

Design coordination is a critical preconstruction process that ensures a project’s functional, aesthetic, and economic requirements are met while avoiding spatial conflicts among building systems [1,2]. The complexity of this process increases with the number of systems involved, and errors can significantly impact construction costs, with some design errors exceeding USD 26,000 [3]. Effective design coordination management is crucial to delivering cost-effective, high-quality projects [4].

Traditionally, design coordination relies on visual inspection and manual comparison of 2D drawings [1]. This process can be inefficient and often leads to undetected conflicts that require costly resolution during construction [5]. Design coordination meetings conducted to address these issues can cost between USD 8000 and USD 23,000 per session [6].

Subsequently, Building Information Modeling (BIM) tools have been adopted to increase efficiency by enabling 3D model integration for automated clash detection [7]. BIM-based coordination has enhanced scheduling, cost control, and productivity while reducing rework and change orders [8,9]. Despite these advantages, BIM-based design coordination presents challenges. Many practitioners revert to 2D drawings due to difficulties in BIM interaction, leaving 3D data underutilized [10,11]. Frequent transitions between design representations cause inefficiencies and data loss [1,12]. Additionally, BIM tools often fail to document the complexity, priority, and severity of issues, leading to discrepancies in resolution [13,14]. Given the thousands of conflicts that can emerge during coordination [13], addressing these challenges is essential.

Current design collaboration tools for BIM-based coordination span several categories, each suited to different aspects of the coordination workflow. Desktop-based model coordination tools such as Autodesk Navisworks and Solibri Model Checker support clash detection and model review but typically operate as standalone applications that require manual data transfer between stakeholders [7]. Common data environment (CDE) platforms, including Autodesk BIM Collaborate, Trimble Connect, and Bentley ProjectWise, aim to centralize model storage and version management across project teams [15,16]. More recently, open-source, interoperable platforms such as Speckle have emerged to address limitations in data exchange through object-level collaboration and API-driven workflows [17]. Despite this diversity, existing tools differ substantially in how they support the three core coordination activities: issue identification (clash detection and filtering), issue resolution (model navigation and real-time discussion), and issue documentation (recording outcomes and tracking progress). These differences create fragmented workflows in which practitioners must frequently transition between tools, representations, and communication channels—a persistent source of inefficiency that the present study seeks to address [6].

Cloud-based BIM collaboration tools offer a promising alternative to these fragmented workflows by enabling real-time integration and exchange of 3D models while maintaining centralized project data [15,18,19,20]. These tools streamline workflows, enhance communication, and reduce reliance on paper-based processes, ultimately lowering rework costs [21]. Several vendors, such as Autodesk, Trimble, and Speckle, now offer cloud-enabled common data environments for BIM coordination. In parallel, recent studies have introduced graph-based solutions that address inter-domain consistency [17], clash dependency resolution [22], and asynchronous version control [23,24], highlighting the growing innovation in this field. However, many of these tools face implementation barriers stemming from organizational structures, team dynamics, and contractual limitations [16,25,26].

Understanding the impact of cloud-based BIM collaboration tools on design coordination is essential to ensure their effective integration into practice. While prior studies have examined cloud-BIM capabilities from a technical standpoint [15,16,27] or surveyed adoption barriers at an organizational level [25,26], few have empirically documented how tool adoption changes coordination workflows in real project settings. This study addresses that gap by providing an empirically grounded, process-change framework that traces the relationship from specific tool features through observable workflow modifications to their impacts on coordination outcomes. Unlike existing cloud-BIM reviews, this framework is derived from firsthand observations of coordination practices across multiple projects and validated through expert interviews, offering both theoretical contributions to the BIM adoption literature and actionable guidance for practitioners. Specifically, this study investigates how cloud-based BIM collaboration tools influence the design coordination process, with a focus on issue identification, resolution, and documentation. It addresses the following research questions:

• What changes in the design coordination process result from adopting cloud-based BIM collaboration tools?
• How can these changes be categorized and linked to the impact of cloud-based BIM collaboration tools?

A mixed-methods approach was employed to address these questions, including action research, an ethnographic case study, and a case study analysis of three large-scale construction projects. The action research developed a workflow for integrating cloud-based BIM tools into an ongoing project. The ethnographic study documented pre- and post-adoption changes, while the case study analysis developed and validated a framework categorizing these changes through expert interviews. This framework provides industry professionals with practical insights into implementing cloud-based BIM tools while contributing to the change management literature, particularly regarding digital collaboration adoption.

2. Literature Review

2.1. BIM-Based Design Coordination Process and Challenges

Design coordination enables project stakeholders to detect and resolve conflicts in building systems before they impact construction or operations. This multidisciplinary process involves architectural, structural, mechanical, electrical, and plumbing designs and requires expertise in building systems, codes, and client objectives [28]. Traditionally, coordination relies on visual inspections of 2D drawings to identify conflicts. However, this approach is inefficient and often results in undetected issues that must be addressed on-site, increasing costs and inefficiencies [13,14].

BIM-based coordination follows a three-step cycle: (1) issue identification, where conflicts between building systems are detected and filtered for false positives; (2) issue resolution, which involves discussions among contractors, architects, engineers, and sub-trades; and (3) issue documentation, which records the discussion and final resolution [6].

While these steps are well established, challenges persist that disrupt coordination and reduce efficiency [29,30]. These challenges include practitioners resorting to using 2D paper-based drawings for data exchange and underutilizing the 3D models. Transitioning between design representations remains time-consuming and error-prone, often leading to information loss during issue documentation [30].

Several recent studies have explored advanced coordination techniques to address these inefficiencies. For example, Wang et al. [17] introduced a graph-based framework for inter-domain consistency maintenance. Esser et al. [23,24] proposed version control systems for BIM coordination that mimic Git-based workflows, enabling asynchronous collaboration and improved traceability. Hu et al. [22] developed a clash dependency network to optimize the sequence in which design issues are resolved. These studies highlight the growing interest in intelligent coordination systems but note that implementation challenges persist in real-world settings. Addressing these challenges requires not only technological solutions but also structured approaches to managing the process changes that accompany tool adoption, as discussed in Section 2.3.

2.2. Cloud-Based BIM Collaboration Tools

Cloud-based computing enables on-demand access to shared computing resources, allowing stakeholders to collaborate in real time across the design and construction phases [31,32]. Cloud-based BIM tools facilitate model integration, data exchange, and real-time collaboration among project participants. These platforms provide centralized repositories for storing, updating, and interacting with 3D models across disciplines [33].

Several frameworks have been proposed for cloud-based BIM implementation [34,35]. Singh et al. [20] highlighted their advantages in communication, data sharing, and real-time issue tracking, enabling coordination meeting insights to be stored for future reference. Additionally, these tools support collaborative markups and tagging of shared models [36]. However, research on cloud-based BIM collaboration remains limited, particularly regarding its practical application in design coordination [27]. Existing studies lack ethnographic insights into whether these tools deliver tangible benefits or how their integration impacts coordination processes [27].

Recent studies have further evaluated CDE platforms such as Autodesk BIM Collaborate, Trimble Connect, and Speckle, which provide integrated design management and issue-tracking capabilities [15,16]. While commercial platforms offer advanced features, their effectiveness is often limited by contractual frameworks and uneven adoption of tools among stakeholders [25,26]. The interaction between organizational structures, team roles, and tool capabilities remains underexplored in BIM literature.

A related area of growing research interest is the application of text mining and natural language processing (NLP) to construction issue documentation. Cloud-based BIM tools generate structured textual data through their issue trackers, including defect descriptions, resolution comments, and status logs. Recent studies have demonstrated that such textual records can be systematically analyzed using advanced classification techniques. For instance, Wang [37] developed graph neural network models to classify fire-door defect descriptions in inspection records, achieving high accuracy in automated defect categorization. In a complementary study, Wang [38] proposed a transformer-based text analysis framework for monitoring building defects, demonstrating that models such as RoBERTa can effectively classify unstructured inspection narratives into actionable defect categories. While these studies focus on defect inspection rather than design coordination, they illustrate the broader potential for automated text analysis of issue documentation generated by cloud-based BIM collaboration platforms, a direction directly relevant to the documentation improvements observed in the present study.

Additionally, cloud-enabled BIM integration is emerging as a topic of interest for managing spatially distributed assets, although its role in design coordination workflows is still evolving [17]. These developments underscore the need for context-sensitive, empirical studies that examine tool adoption within real project environments. This study addresses this gap by implementing a cloud-based BIM collaboration tool in a real-world case study to evaluate its effects on design coordination.

2.3. Change Management and Technology Adoption in BIM Implementation

The adoption of new digital tools in construction projects is not merely a technical undertaking; it requires deliberate change management to ensure that stakeholders adapt their practices, workflows, and expectations accordingly. Several frameworks have been applied to understand technology adoption in the Architecture, Engineering, and Construction (AEC) industry. The Technology Acceptance Model (TAM) posits that perceived usefulness and perceived ease of use are primary determinants of tool adoption [39]. Extensions of TAM, such as the Unified Theory of Acceptance and Use of Technology (UTAUT), further incorporate social influence and facilitating conditions as predictors of adoption behavior [40]. In the BIM context, these models have been used to explain why some organizations adopt BIM more readily than others and how individual user perceptions shape implementation outcomes [41].

Beyond individual acceptance, organizational change management models provide a complementary lens for understanding BIM tool integration. The ADKAR model, which describes change readiness through five stages (Awareness, Desire, Knowledge, Ability, and Reinforcement), has been applied in construction contexts to assess project teams’ readiness to transition from established coordination practices to new digital workflows [42]. Matthews et al. [25] demonstrated that BIM implementation outcomes are strongly influenced by organizational culture, leadership commitment, and the alignment between contractual structures and digital tools.

Methodologically, action research has been recognized as a suitable approach for studying technology adoption in construction because it bridges the gap between academic inquiry and industry practice [43,44]. By embedding the researcher within the project team, action research enables iterative development and evaluation of new workflows while capturing the contextual factors that influence adoption outcomes [45]. Similarly, ethnographic methods have been employed to study coordination practices in construction settings, offering rich, contextual descriptions of how practitioners interact with tools and artifacts during design coordination [1,6]. The combination of action research and ethnographic methods, as employed in the present study, provides both the interventionist capability to test new tool integrations and the observational depth to document resulting behavioral changes.

Despite the availability of these theoretical and methodological frameworks, their application to cloud-based BIM collaboration tools remains limited. Most existing studies examine BIM adoption at the organizational level rather than tracing specific process-level changes within coordination workflows. This study contributes to the literature by applying action research and ethnographic methods through a change-management lens to systematically document and categorize process changes resulting from the adoption of cloud-based BIM tools.

3. Research Methods

This study employed a mixed-methods approach [46], integrating action research, an ethnographic case study, and a case study analysis of three large-scale construction projects. Expert interviews with project participants further validated the findings. The research was designed as a sequential, three-phase investigation in which the output of each phase served as input to the next, ensuring methodological coherence and the progressive refinement of the findings. This sequential design was chosen because the research questions required both interventionist capability (to test whether a cloud-based BIM tool could be integrated into an active project) and observational depth (to document the resulting process changes in situ). Neither action research nor ethnographic methods alone could satisfy both requirements; their combination provided complementary strengths, as discussed in the methodological literature reviewed in Section 2.3. The overall methodology is depicted in Figure 1.

In the first phase, action research was conducted to integrate a cloud-based BIM collaboration tool into the design coordination process for an airport expansion project, thereby streamlining the workflow. This phase addressed the practical question of how to deploy the tool within an active coordination workflow and produced the revised workflow documented in Section 4.1. The second phase involved an ethnographic case study to document pre- and post-adoption changes, with case examples illustrating key differences in BIM-based coordination. This phase shifted the methodological focus from intervention to observation, capturing the behavioral and procedural changes that emerged after the tool was embedded in daily practice (Section 4.2). In the third phase, a framework categorizing process changes was developed through a case study analysis of the airport expansion, a transit operations and maintenance facility, and a hospital redevelopment project.

Table 1. Overview of the three case study projects.

	Airport Expansion	Transit Facility	Hospital Construction
Project Description	Construction of a new parkade, a new central utility building, electrical infrastructure upgrades, sustainable energy systems, and a rainwater capture system	Construction of an operations and maintenance facility to support the inspection, service, maintenance, storage, and deployment of up to 96 light rail vehicles	Construction of a six-story and 75-bed Mental Health and Substance Use Wellness Centre with multi-level 450-stall underground parkade.
Project Location	Vancouver, Canada	Bellevue, USA	Vancouver, Canada
Project Budget	USD 460 million	USD 218 million	USD 210 million
Project Size	200,000 sq. ft.	165,000 sq. ft.	223,889 sq. ft.
Delivery Model	Construction Manager	Design-Build	Design-Build

provides an overview of the three projects. By extending the analysis to two additional projects with different delivery models, team structures, and Revizto (version 4.8.47798) usage patterns, this phase tested whether the changes observed in Phase 1 and Phase 2 were project-specific or generalizable across contexts. This framework was then applied to assess the impact of cloud-based BIM adoption on the design coordination process.

The airport expansion project, where the principal researcher was embedded as a BIM coordinator, served as the primary case study and provided the richest contextual data. Coordination meetings on this project were held weekly, with approximately 10 regular attendees representing six disciplines: mechanical, electrical, plumbing, fire protection, architectural, and general contracting. The project involved a high degree of model complexity, with four federated sub-models corresponding to distinct building phases (see

Table 2. Overview of Revizto usage in the three case study projects.

	Airport Expansion	Transit Facility	Hospital Construction
Scope of Revizto usage	Design coordination between stakeholders from different firms (contractor, architect, and engineering consultants)	Design coordination between stakeholders from the same firm (architect, and engineering consultants)	Design coordination between stakeholders from different firms (contractor, architect, engineering consultants, and operators)
Data Transferred	3D models from Navisworks 2D sheets from Revit Clashes from Navisworks	3D models from Revit Clashes from Navisworks	3D models from Revit 2D sheets from Revit Clashes from Navisworks
Model Organization	Four models divided by components: Building model Parkade building model Site and ancillary building model Existing building model	Three models divided by components – Main Building #1 model Main Building #2 model Site and ancillary building model	3 models differentiated by user: Consultant model—for design coordination and model task delegation. Contractor model—for construction coordination and site issue progress tracking Owner/operator model—for project review and internal collaboration
Update cycle and publisher	All the four models were updated on a weekly basis	All the 3 models were updated daily on an avg.	The consultant’s model was updated on an avg. every 2 days, the contractor’s model updated for construction milestones, and owner/operator’s model updated for milestone reviews
Issue Creation	Markups in 3D only in addition to issue creation through Navisworks Clash Sync	Markups in 3D only in addition to issue creation through Navisworks Clash Sync	Markups in 2D and 3D as well as issue creation through Navisworks Clash Sync

). Prior to the adoption of Revizto, the coordination workflow relied on Navisworks for clash detection and on manual Excel spreadsheets for issue tracking. The transit facility and hospital projects, which employed three federated models each, served as validation cases and contributed data through expert interviews and reviews of project documentation rather than direct observation of meetings. Across all three projects, coordination maturity prior to cloud-based BIM adoption followed a similar pattern: Navisworks-based clash detection supplemented by manual tracking tools, with limited integration between the model environment and the issue documentation process.

3.1. Action Research: Tool Integration

Action research addresses real-world challenges while contributing to knowledge through collaboration between academia and industry [43]. This iterative methodology comprises five phases: diagnosing, action planning, action taking, evaluating, and specifying learning [44,45]. This study applied action research to an airport expansion project, as shown in Figure 2. The principal researcher, acting as a BIM coordinator, collaborated with the general contractor to implement Revizto [47] as a cloud-based BIM collaboration tool. The research focused on improving issue identification, resolution, and documentation in the BIM-based design coordination process. Data were collected through informal discussions and direct observations involving project managers, site superintendents, BIM managers, and coordinators. The first action research cycle aimed to optimize issue identification and resolution:

• Diagnosing: Existing workflows were examined, highlighting inefficiencies consistent with previous research [29,30].
• Action Planning: BIM coordination inefficiencies were identified, and strategies for integrating the cloud-based tool were formulated.
• Action Taking: The cloud-based BIM tool was introduced and tested in the project’s design coordination meetings.
• Evaluating: Feedback from project participants was collected through observation and informal discussion.
• Specifying Learning: Refinements were made based on participant experiences; the final workflow is presented in the findings.

The second cycle focused on issue documentation. Following the same five-step process, the team standardized the recording of meeting outcomes, comments, and resolution data in Revizto’s issue tracker. Dashboard and reporting features were evaluated for tracking coordination progress.

3.2. Ethnographic Case Study: Documenting Changes

An ethnographic case study was conducted during the airport expansion project to document the changes resulting from the adoption of a cloud-based BIM tool. The principal researcher, embedded as a BIM coordinator, observed BIM-based design coordination processes before and after Revizto integration. Detailed notes were taken during design coordination meetings to identify specific workflow differences. The ethnographic approach was selected because it allows the researcher to capture not only the procedural changes in coordination workflows but also the contextual factors, such as participant interactions, informal communication patterns, and emergent workarounds, that shape how tools are used in practice [1,6]. Data collection spanned the entire tool integration period and included direct observation of coordination meetings, informal discussions with project participants, and review of project documentation, such as issue tracker logs and meeting reports. The observations were structured around the three coordination stages (issue identification, resolution, and documentation) to enable systematic comparison of pre- and post-adoption practices.

3.3. Case Study Analysis: Framework Development

A case study analysis was performed across the airport expansion, transit facility, and hospital projects to develop and refine the framework. Table 2 provides an overview of how Revizto was used across the three projects. While the airport expansion project provided the most detailed meeting-level data due to the researcher’s embedded role, the transit facility and hospital projects offered complementary perspectives across different delivery models, team configurations, and Revizto usage patterns, strengthening the transferability of the findings. The framework draws on the Activity Theory lens to categorize observed changes by activities, functionalities, artifacts, and impacts at each stage of the coordination process. Insights from each project were synthesized to develop a robust categorization of changes resulting from the adoption of cloud-based BIM. The framework was refined through assessments in the transit facility and hospital projects, with the finalized version detailed in the findings section.

3.4. Expert Interviews: Framework Validation

The framework categorizing BIM-based design coordination changes from cloud-based BIM adoption was validated through nine expert interviews. Participants included BIM coordinators, BIM managers, project coordinators, and project managers from the transit facility and hospital projects. While BIM coordinators and managers had direct experience with Revizto, other participants regularly attended design coordination meetings.

The interviews examined factors influencing Revizto’s implementation, including organizational dynamics and contractual structures affecting issue identification, resolution, and documentation. Insights gathered highlighted workflow modifications, benefits, and challenges associated with cloud-based BIM adoption. Expert feedback validated the observed process changes and confirmed the study’s categorization framework.

4. Findings

4.1. Workflow for Integrating Cloud-Based BIM Collaboration Tool

During the action research cycle, the BIM-based design coordination process transitioned from using Autodesk Navisworks as the primary discussion tool to Revizto as the central platform for managing model information and coordination meetings. The following sections outline how Revizto facilitated different stages of the workflow.

4.1.1. Issue Identification

During the issue identification process, designers’ models were first collated in Navisworks and then exported to Revizto. Alongside the models, 2D drawings were also uploaded to ensure consistency in issue tracking. Weekly model updates were synchronized to the central model in Revizto. However, since Revizto did not support automated clash detection at the time, Navisworks’ clash detective was used to identify clashing building systems. After filtering out false positives, clashes were synchronized with Revizto, tagged to the responsible designers, and prioritized by severity. The internal team added comments in the Revizto issue tracker to enhance clarity, and ensure issues were well documented before coordination meetings. Additionally, constructability challenges not detected by Navisworks were manually created as new issues in Revizto. These issues were then reviewed during design coordination meetings. Figure 3 illustrates the issue identification workflow developed during the study, with Revizto-induced changes highlighted in green.

4.1.2. Issue Resolution

The general contractor and design consultants attended coordination meetings to resolve identified issues. The prioritization of issues within Revizto determined the order of the discussion. Revizto’s viewpoints allowed meeting attendees to quickly locate design issues in the model, while its map view enabled stakeholders to focus on specific project quadrants for localized issue resolution. Revizto’s object filters facilitated recoloring and hiding elements, improving understanding of how a given design issue affected surrounding systems. Discussions and decisions were recorded as comments directly within the issue tracker. Figure 4 contrasts the issue resolution process in the Revizto-based workflow with the traditional Navisworks-based approach.

4.1.3. Issue Documentation

Previously, when Navisworks was the primary discussion tool, issue documentation was a manual and time-intensive process. The BIM coordinator had to compile model screenshots, meeting notes, and drawing markups before distributing them to stakeholders. With Revizto, meeting discussions and comments were recorded directly in its issue tracker, automating documentation. This system enabled real-time tracking, automatically generating reports and dashboards that streamlined issue monitoring. Figure 5 compares the traditional and Revizto-enhanced workflows with the updated steps highlighted in green. Following the implementation of this revised workflow, the general contractor adopted the cloud-based tool for design coordination across other projects, demonstrating its practical benefits and scalability.

4.2. Outlining the Changes from Tool Adoption

An ethnographic case study of the airport expansion project revealed key changes in design coordination due to adopting a cloud-based BIM collaboration tool. The following sections describe the modifications in issue identification, resolution, and documentation.

4.2.1. Issue Identification

Before adopting the cloud-based tool, the BIM coordinator manually collated models in Navisworks, conducted automated clash detection, filtered false positives, and prioritized issues for discussion. These issues were recorded in Excel or Word documents with columns outlining the status, priority, screenshot, description, and responsible party. After adopting Revizto, the overall tasks remained the same, but the issue-tracking process improved significantly. Clashes detected in Navisworks were synchronized with Revizto, where screenshots were automatically generated, and additional comments were added based on internal discussions (Figure 6). Issues were tagged with location and discipline information (mechanical, plumbing, fire protection, electrical), streamlining issue tracking and eliminating the need for manual Excel trackers.

4.2.2. Issue Resolution

Previously, design coordination meetings relied on manually updated Excel trackers, meeting notes, and 2D drawings, while the BIM coordinator navigated models in Navisworks to provide visual references. Participants needed to cross-reference these various sources to understand issues and record solutions. The adoption of Revizto simplified this process. The issue tracker stored all relevant information, including priority, location, screenshots, and comment logs, ensuring meeting participants could quickly retrieve necessary data. Revizto’s map and viewpoint functionalities enabled easy navigation, helping participants understand how design issues affected surrounding systems. Discussions were logged directly within the issue tracker, eliminating the need to switch between multiple tools and improving issue resolution efficiency.

4.2.3. Issue Documentation

In the traditional workflow, the BIM coordinator manually documented meeting discussions, updated the Excel tracker, and added screenshots before distributing them to stakeholders. This process was time-consuming and prone to errors. With Revizto, meeting comments were recorded directly in its issue tracker, which automatically generated reports summarizing issues, priorities, and meeting discussions. The cloud-based tool’s live-tracking feature replaced static Excel trackers, providing real-time updates as models changed in Navisworks. This streamlined workflow significantly reduced manual effort while enhancing documentation accuracy and coordination efficiency.

4.3. Framework for Analyzing Changes

As outlined in the project’s BIM execution plan, the BIM coordinator plays a central role in issue identification, resolution, and documentation. Given this responsibility, their perspective was used to develop a framework analyzing changes resulting from cloud-based BIM adoption. Insights from three case study projects, action research, and an ethnographic study of the airport expansion project informed the framework, as presented in

Table 3. Framework developed to categorize the changes resulting from the adoption of cloud-based BIM collaboration tool.

Design Process	Process View			Impact View
	Activity Lens	Functionality Lens	Artifact Lens	Benefit Lens	Challenge Lens	Severity Lens
Component of the processes	Steps in the process added or removed due to tool adoption	Functionalities of adopted tool enabling the change	Artifacts added or replaced as a result of adopting the tool	Observed benefits due to tool adoption	Observed challenges due to tool adoption	Severity of the changes due to tool adoption

.

This framework evaluates design coordination changes by examining workflow steps, tool functionalities, and artifacts, along with the associated benefits, challenges, and impact severity. The issue identification, resolution, and documentation processes before and after adopting Revizto were systematically compared to capture process shifts. Figure 7 summarizes these relationships, while

Table 4. Changes in the design coordination process from cloud-based BIM tool adoption.

Design Coordination Process Components	Process View			Impact View
	Activity Lens	Functionality Lens	Artifact Lens	Benefits	Challenges	Severity
Issue Identification	The steps involved in preparing the Excel tracker are eliminated with transition to Revizto The need for manually reviewing past issues in the issue tracker is removed	Model collation and clash detection continues to happen in Navisworks Viewpoint creation from Navisworks is now enabled by Revizto issue tracker	The use of Excel to maintain a manual issue tracker is removed because of similar functionality integrated within Revizto	Reduced transitions: For preparing the issue tracker Reduced activities: Resolved issues auto-update based on updated models—no need to manually check progress of all open issues and past discussion stay intact for open issues.	Shared definitions: Setting mutually acceptable priority for issues Learning curve: Onboarding new stakeholders and acclimatizing with the tool’s features	Activity lens—low (majority of the steps involved remain unchanged) Functionality lens—low (in-built issue tracker has similar functionalities to the Excel tracker) Artifact lens—medium (the external Excel tracker is replaced by in-built issue tracker)
Issue Resolution	The transitions required between Excel issue tracker and model are removed The transitions between 2D drawings and 3D model viewing are eliminated Meeting notes are added to the comment log	The common data environment of the cloud-BIM tool collates the meeting notes, model information, and issues for discussion The 2D-3D overlap feature enables viewing the 2D drawings for an area where the issue is located	Cloud-tool is the only tool used during the discussion in comparison to using 2D drawings, 3D models, and Excel tracker	Reduced transitions: For discussing issues during coordination meeting Increased information access: Cloud tool collates the 2D, 3D, and issue information	Meeting protocol: Setting issue discussion process—navigating by issues in each room vs. issues with a given priority Model size: Uploading drawings leading to large file sizes and slower navigation	Activity lens—medium (in-built features reduce the steps involved around discussing an Issue) Functionality lens—high (cloud tool enables functionalities such as 2D-3D model data overlap that was unavailable earlier) Artifact lens—high (need for external Excel issue tracker and 2D drawings eliminated)
Issue Documentation	The steps involved in preparing the Excel tracker are eliminated Manual addition of screenshots for issue not required Manual tracking of progress on issues not required	Issue tracker and cloud dashboard eliminate the need for Excel tracker Cloud-dashboard provides real-time status of design coordination progress	The Excel tracker is replaced with auto generated reports from online Revizto dashboard	Reduced activities: The manual workload of maintaining the Excel issue tracker is removed Increased efficiency: The task of categorizing the issues discussed during the meeting is automated by the cloud tool	Limited customizability: The auto-generated report offered limited formatting and text customization especially for adding legal disclosures	Activity lens—high (steps involved in maintaining external Excel tracker eliminated) Functionality lens—high (the in-built issue tracker can auto-generate reports for distribution) Artifact lens—high (need for external Excel tracker, model file with viewpoints, and screenshots of issues eliminated)

details the observed modifications in overall design coordination.

4.4. Validation of Findings

Expert interviews with nine practitioners confirmed the framework’s categorization of changes resulting from cloud-based BIM adoption. These semi-structured discussions provided insights into workflow modifications, benefits, and challenges.

Table 5. Key interview excerpts supporting the framework findings.

Design Coordination Process Components	Framework Lenses	Framework Findings	Interview Excerpts
Issue Identification	Activity Lens	Reduced steps: The steps involved in preparing the Excel tracker are eliminated Manual addition of screenshots for the issue is not required Manual tracking of progress on issues not required	“It gives you the opportunity to do visual as well as clash reviews, bunch of other things. But what I use it mostly for is visual clash reviews. So, you load all the models and kind of just navigate through them looking for obvious problems.”
	Functionality Lens	Model collation and clash detection continues to happen in Navisworks Viewpoint creation from Navisworks is now enabled by the Revizto issue tracker	“Our issue tracker maintained a log of comments from all previous discussions from the design coordination meeting. We would set agenda items based on priorities of issues during the coordination meetings.”
	Artifact Lens	The use of Excel to maintain a manual issue tracker is removed because of similar functionality integrated within Revizto	“There’s lots of time saving. I also think that it allows our senior engineers that people who are a little less tech savvy to comfortably navigate the model with the fear of wrecking something”
	Impact Lens	Reduced transitions: For preparing the issue tracker Reduced activities: Resolved issues auto-update based on updated models—no need to manually check the progress of all open issues and past discussion stay intact for open issues.	“The BIM team would be the first to praise using it on all our projects. We’re looking at piloting in projects in other cities.”
Issue Resolution	Activity Lens	The transitions required between Excel issue tracker and model are removed The transitions between 2D drawings and 3D model viewing are eliminated Meeting notes are added to the comment log	“The drawings overlap feature was key to getting the superintendents and site team involved in the BIM meetings”
	Functionality Lens	The common data environment of the cloud-BIM tool collates the meeting notes, model information, and issues for discussion The 2D-3D overlap feature enables viewing the 2D drawings for an area where the issue is located	“If you’re in a 3D view, and there’s things blocking what you want to see, you can’t zoom past them, you have to, you have to find another way to look So, and now this software allows them to very simply with a few little mouse clicks, or, or keyboard strokes, walk around a model and really get a clear understanding of, of what’s been modeled and how it works and what, what everything means.”
	Artifact Lens	Cloud-tool is the only tool used during the discussion in comparison to using 2D drawings, 3D models, and Excel tracker	“The map was a good feature to have during the meetings. We would often get lost in the model wasting time figuring out the location of the issue before it”
	Impact Lens	Reduced transitions: For discussing issues during coordination meeting Increased information access: Cloud tool collates the 2D, 3D, and issue information	“So, you can jump from a 2D plan to the 3D view, and you can jump back, and you can make comments here and see them and then and, and it keeps running comment log. So, you can see a comment, they can identify who needs to fix it, the person can fix it, re upload the model, and you can see the old versus the new and what was wrong and how they came to the solution.”
Issue Documentation	Activity Lens	The steps involved in preparing the Excel tracker are eliminated Manual addition of screenshots for issue not required Manual tracking of progress on issues not required	“The biggest time savers were the reports. I would be spending almost whole day after the meeting putting everything together, that the report just did in one click”
	Functionality Lens	Issue tracker and cloud dashboard eliminate the need for Excel tracker Cloud-dashboard provides real-time status of design coordination progress	“The project managers liked having an overview of the BIM meeting but rarely attended the coordination meetings. The dashboard became their gospel, and my PM asked me to schedule its emails for the whole team”
	Artifact Lens	The Excel tracker is replaced with auto generated reports from online Revizto dashboard	“Getting the designers onboard with the reports needed some push. Once they saw the links to the model in the report files, I think that won them over”
	Impact Lens	Reduced activities: The manual workload of maintaining the Excel issue tracker is removed Increased efficiency: The task of categorizing the issues discussed during the meeting is automated by the cloud tool	“I would be lost often with all the notes and screenshots I took during the meeting. Combining them took forever before using the issue reports.”

presents key interview excerpts supporting the framework’s findings.

4.5. Synthesis: Distinguishing Software Functionality, Practitioner Behavior, and Collaborative Mechanisms

The findings presented in Section 4.1, Section 4.2, Section 4.3 and Section 4.4 document the changes resulting from the adoption of cloud-based BIM tools across issue identification, resolution, and documentation. To provide a more nuanced understanding of these changes, this section distinguishes between three interrelated dimensions: (1) software functionality, referring to what the tool technically enables; (2) practitioner behavior, referring to how individuals adapt their coordination practices in response to the tool; and (3) collaborative mechanisms, referring to how the coordination process itself is structured and governed.

Table 6. Observed changes categorized by software functionality, practitioner behavior, and collaborative mechanisms.

Coordination Stage	Software Functionality	Practitioner Behavior	Collaborative Mechanisms
Issue identification	Clash sync from Navisworks to Revizto; automated screenshot generation; built-in issue tracker with tagging by discipline and location; viewpoint creation linked to issues	BIM coordinators shifted from manually compiling Excel trackers to curating issues within the cloud platform; internal teams began adding pre-meeting comments to issues, increasing preparation quality; reduced need to manually review resolved issues against updated models	Issue preparation became a collaborative, comment-driven process rather than a single-coordinator task; discipline-based tagging introduced a shared classification system across project teams; priority-setting required negotiation of mutually acceptable severity definitions
Issue resolution	Centralized model viewer replacing separate Navisworks navigation; map view for spatial filtering by project quadrant; object filters for recoloring/hiding building systems; in-tool comment logging during meetings	Meeting participants relied on the cloud tool as the single source of context rather than cross-referencing Excel, drawings, and models; the BIM coordinator transitioned from model navigator to meeting facilitator; attendees engaged more actively with 3D spatial context during discussions	Coordination meetings shifted from multi-tool navigation to a single-platform discussion workflow; issue discussion order became driven by tool-based prioritization rather than ad hoc agenda-setting; real-time comment capture replaced post-meeting documentation, changing the meeting’s temporal structure
Issue documentation	Automated report generation from issue tracker data; live dashboards replacing static Excel trackers; cloud-based access to historical issue discussions and status updates	BIM coordinators were relieved of manual post-meeting compilation tasks; stakeholders began accessing issue status independently rather than waiting for distributed reports; documentation shifted from a retrospective task to a continuous, real-time activity	Accountability became more transparent as all comments and status changes were logged with timestamps and attributed to individuals; reporting transitioned from coordinator-mediated distribution to self-service access; documentation quality became less dependent on individual coordinator diligence

summarizes the observed changes across these three dimensions for each stage of the coordination process.

As Table 6 illustrates, the three dimensions are interdependent but analytically distinct. Software functionality provides the technical affordances, such as centralized issue tracking, automated reporting, and spatial navigation, but these affordances do not automatically translate into improved coordination. Practitioner behavior mediates the relationship between tool capabilities and coordination outcomes: for example, the shift from manual Excel compilation to curated cloud-based issue preparation reflects a change in how BIM coordinators allocate their effort and attention, not merely a change in which software they use. Similarly, collaborative mechanisms represent the structural and procedural arrangements that govern how teams interact during coordination, such as the transition from ad hoc agenda-setting to priority-driven discussion sequences.

Several key factors were observed to influence the effectiveness of collaborative design when cloud-based BIM tools are adopted. First, stakeholder access and onboarding played a critical role: in the airport expansion project, designers who were not onboarded onto Revizto could not independently navigate issues, creating a dependency on the BIM coordinator and limiting the tool’s collaborative potential. Second, contractual alignment shaped tool utilization, as contracts that did not mandate or support the use of the cloud-based platform left features such as 2D drawing overlays and remote model access underutilized. Third, role adaptation emerged as an important behavioral factor: the BIM coordinator’s role shifted from a data compiler to a meeting facilitator, but this shift required both individual willingness and organizational recognition of the expanded role. Fourth, shared protocols for issue prioritization influenced how effectively teams could use the tool’s built-in prioritization features, because without agreed-upon severity definitions, priority tags created confusion rather than clarity. These influencing factors cut across the software, behavioral, and mechanism dimensions, confirming that effective cloud-based BIM adoption requires concurrent attention to technical deployment, individual adaptation, and process governance.

While this study employed qualitative methods that do not yield formal time-based measurements, the ethnographic observations and workflow analysis enable a systematic comparison of process-level indicators before and after the adoption of a cloud-based BIM tool.

Table 7. Process-level indicators before and after cloud-based BIM tool adoption.

Indicator	Before Adoption	After Adoption	Change	Source
Issue Identification
Tools required	3 (Navisworks, Excel/Word tracker, 2D drawings)	2 (Navisworks, Revizto)	−1 tool	Figure 3 and Figure 6; Section 4.2.1
Manual steps eliminated	n/a	Excel tracker compilation; manual screenshot capture; manual progress review	3 manual steps removed	Table 4, Activity lens; Section 4.2.1
Artifacts replaced	External Excel/Word issue tracker	Revizto built-in issue tracker	1 external artifact eliminated	Table 4, Artifact lens
Issue resolution
Tools used during meetings	3 (Excel tracker, Navisworks, 2D drawings)	1 (Revizto)	−2 tools	Figure 4; Section 4.2.2
Inter-tool transitions	Multiple (Excel, Navisworks, 2D drawings)	None (single platform)	All eliminated	Table 4, Activity lens; Section 4.2.2
Meeting note capture	Manual (post-meeting)	In-tool (real time)	Post hoc to real-time	Section 4.2.2; Table 5
Issue documentation
Post-meeting manual artifacts	3 (Excel tracker, screenshots, meeting notes)	0 (auto-generated reports)	−3 manual artifacts	Figure 5; Section 4.2.3
Issue status tracking	Static (manual Excel)	Dynamic (live dashboard)	Static to real-time	Table 4, Functionality lens; Section 4.2.3

summarizes these indicators across the three coordination stages, capturing the number of tools and artifacts involved, the number of manual steps eliminated, and the number of tool transitions required. These indicators are derived from the workflow diagrams (Figure 3, Figure 4 and Figure 5) and the ethnographic observations documented in Section 4.1 and Section 4.2.

These process-level indicators demonstrate that cloud-based BIM tool adoption produced measurable reductions in workflow complexity: the number of tools required for issue resolution decreased from three to one, all inter-tool transitions during coordination meetings were eliminated, and three manually prepared post-meeting artifacts were replaced by automated reporting. It should be noted that this study’s qualitative research design, employing action research and ethnographic observation, was selected to capture the richness of workflow changes and behavioural adaptations that quantitative metrics alone cannot convey. Formal time-based measurements (e.g., meeting preparation duration, meeting length, post-meeting documentation time) were not collected, as the primary objective was to develop and validate a process-change framework rather than to conduct a controlled before-and-after efficiency study. Future research employing time-motion analysis or structured logging within cloud-based BIM platforms could complement the present findings by quantifying the time savings associated with these process-level reductions.

5. Discussion

The adoption of cloud-based BIM collaboration tools streamlined the design coordination process by reducing manual steps and improving efficiency. As shown in the synthesis of findings (Section 4.5), these improvements operate across three interconnected dimensions: the technical functionality of the platform, the behavioral adaptations of individual practitioners, and the restructuring of collaborative mechanisms that govern coordination meetings. While the tool provides the infrastructure for change, its impact is mediated by how practitioners adapt their practices and how project teams restructure their coordination protocols. The following subsections discuss two critical areas that require further alignment to maximize the benefits of cloud-based BIM adoption.

5.1. Need for Integrating Clash Detection Process in the Cloud-Based BIM Tool

The projects in this study used a version of Revizto that lacked clash detection and grouping prior to the 1 October 2021, software update. As a result, Autodesk Navisworks was required to collate consultant models, detect clashes, and remove false positives, adding complexity to the workflow. With the introduction of clash automation in Revizto’s latest versions and the availability of native clash detection features in platforms such as Autodesk BIM Collaborate, it is now possible to consolidate these activities within a single platform.

Consolidating clash detection, grouping, and issue tracking into a single environment reduces tool switching and error propagation while improving transparency. However, this shift also requires that teams revisit role assignments and redefine coordination responsibilities to avoid duplication of effort. Emerging solutions, including Speckle and Trimble Connect, also offer modular, object-based collaboration features that could enhance future implementations [16,17].

Beyond platform consolidation, the automated documentation capabilities observed in this study point to a further opportunity: applying text mining and NLP techniques to the structured issue data generated by cloud-based BIM tools. The issue trackers used in this study accumulated detailed textual records of defect descriptions, resolution discussions, and status changes across coordination meetings. Recent advances in construction informatics have demonstrated that similar textual data can be automatically classified and analyzed. For example, graph neural network and transformer-based approaches have been successfully applied to categorize building defect descriptions from inspection records [37,38]. Applying such techniques to the issue documentation generated by cloud-based BIM platforms could enable automated categorization of coordination issues by type, severity, or discipline, further reducing the manual effort involved in post-meeting analysis. This represents a promising direction for future research that builds directly on the documentation workflow improvements identified in the present study.

5.2. Need for Aligning the Project’s Organizational Setup and Processes

The contract for the airport expansion project assigned overall design coordination responsibility to the general contractor but did not include provisions for tools outside the BIM execution plan. Since Revizto was not explicitly mentioned, its implementation faced several challenges:

• Model access: Only the general contractor had access to the Revizto model, which required designers to rely on them for coordination meeting data, leading to communication inefficiencies.
• Model data: The lack of direct designer access limited real-time collaboration, forcing reliance on intermediate updates.
• 2D drawing access: Revizto’s ability to overlay 3D models with 2D drawings was underutilized since contract terms restricted drawing submissions to major design milestones.

Additionally, since designers were not onboarded onto Revizto, coordination meetings relied on screensharing, creating further limitations:

• Issue location: Participants often struggled to locate discussion topics within the model, a challenge that could have been mitigated with Revizto’s remote viewing functionality.
• BIM coordinator dependency: The BIM coordinator became the sole source for answering queries about dimensions, system types, and ownership, leading to inefficiencies.
• Issue resolution: Without direct Revizto access, designers needed gridline-referenced screenshots in their reports, which added unnecessary steps.
• Prioritization protocols: The absence of a standardized process for prioritizing and resolving issues led to misaligned urgency levels and delays.

These challenges highlight that tool effectiveness is shaped not only by software features but by the contractual, organizational, and cultural context in which they are used [25,26]. Cloud-based BIM platforms provide the infrastructure for improved collaboration, but their potential cannot be fully realized without clear protocols for access, responsibilities, and information flow. Based on these observations, the following subsection presents practical recommendations for project teams seeking to adopt cloud-based BIM collaboration tools.

5.3. Practical Recommendations for Cloud-Based BIM Tool Adoption

Drawing on the challenges identified in Section 5.2 and the process changes documented in the findings, this section offers five practical recommendations for project teams and engineering managers implementing cloud-based BIM collaboration tools. These recommendations are grounded in the empirical observations from the three case study projects and are intended to bridge the gap between tool deployment and effective coordination practice.

Recommendation 1: Include explicit provisions for cloud-based collaboration tools in project contracts and BIM execution plans. A recurring barrier in the airport expansion project was that Revizto was not specified in the BIM execution plan, which meant its adoption lacked contractual backing. Project teams should ensure that contracts explicitly name the collaboration platform to be used, define which stakeholders are required to access it, and specify the frequency and format of model uploads. Contract language should also address data ownership, access rights upon project completion, and interoperability requirements with other project tools. This aligns with the broader finding that contractual alignment is a precondition for realizing the full potential of cloud-based BIM platforms [25,26].

Recommendation 2: Mandate stakeholder onboarding and provide structured training before the first coordination meeting. The study found that designers who were not onboarded onto Revizto could not independently navigate issues, creating a dependency on the BIM coordinator and limiting collaborative engagement during meetings. Project teams should establish a mandatory onboarding process that includes hands-on training with the cloud-based tool, familiarization with issue tracker workflows (creating, commenting on, and resolving issues), and guidance on using spatial navigation features such as viewpoints and map views. Onboarding should be scheduled at least two weeks before the first coordination meeting to allow stakeholders time to become comfortable with the platform.

Recommendation 3: Establish shared issue prioritization protocols before tool deployment. The absence of agreed-upon severity definitions and prioritization rules was identified as a source of confusion across all three projects. Before initiating cloud-based coordination, project teams should collaboratively define a prioritization schema, specifying categories such as critical, major, and minor, along with clear criteria for each level (e.g., based on safety impact, cost implications, or schedule criticality). These definitions should be documented in the BIM execution plan and configured within the tool’s issue tracker to ensure consistent application across disciplines. Regular calibration sessions during the first month of adoption can help refine these definitions as teams gain experience with the platform.

Recommendation 4: Grant all coordination meeting participants direct access to the cloud-based platform. In the airport expansion project, only the general contractor had access to the Revizto model, forcing designers to rely on screen-sharing and intermediate information during meetings. This arrangement negated several of the tool’s core benefits, including independent model navigation, asynchronous issue review, and remote viewing. Project teams should ensure that all regular coordination meeting participants, including design consultants, sub-trade coordinators, and owner representatives, have individual licensed access to the platform. Where licensing costs are a concern, teams should negotiate multi-user or project-based licensing arrangements as part of the contract scope.

Recommendation 5: Define coordination meeting protocols that leverage the cloud-based tool’s capabilities. The transition from a multi-tool to a single-platform coordination workflow requires corresponding changes in how meetings are structured and facilitated. Project teams should develop meeting protocols that specify how issues are navigated (e.g., by priority ranking within the issue tracker rather than ad hoc agenda-setting), how comments are recorded during the meeting (in-tool rather than in separate notes), and how post-meeting actions are assigned and tracked (through the platform’s status and assignment features). Documenting these protocols in a short coordination guide and reviewing them at the start of the first few meetings can accelerate the transition and reduce the learning curve identified in the findings.

These five recommendations address the organizational, contractual, and procedural dimensions that the findings identified as key mediators of cloud-based BIM tool effectiveness. While the specific tool features will continue to evolve as platforms mature, these governance and process-level practices are broadly applicable across cloud-based BIM collaboration tools and project delivery models. As digital platforms evolve to offer more real-time and distributed coordination capabilities, such as graph-based version control [23,24], organizational alignment and governance models must evolve accordingly.

6. Limitations

This study focuses solely on the design coordination process and a single cloud-based BIM collaboration tool. Future research should investigate the adoption of other BIM and GIS tools, compare different cloud-based BIM solutions, and assess their long-term impact. Another limitation is the variability in the complexity of design issues before and after tool implementation. Although the process remained consistent, differences in issue complexity could influence outcomes. Future studies should account for this factor better to evaluate the tool’s impact on design coordination. Additionally, while this study documents process-level indicators such as the number of tools, manual steps, and artifacts involved in coordination (Table 7), it does not include formal time-based measurements of efficiency gains. The qualitative research design was selected to capture the depth and context of workflow changes, which are difficult to quantify in controlled settings, given the variability of real-world construction projects. Future research could employ time-motion studies, structured task logging, or platform analytics to quantify the time savings associated with the process reductions identified in this study.

7. Conclusions

This study investigated the impact of cloud-based BIM collaboration tools on the design coordination process, focusing on issue identification, resolution, and documentation. Using a mixed-methods approach, including action research, an ethnographic case study, and a case study analysis of three large-scale construction projects, the research developed and validated a framework for categorizing changes resulting from the adoption of a cloud-based BIM collaboration tool.

The findings indicate that integrating Revizto into design coordination workflows improved issue tracking, enhanced collaboration, and streamlined documentation. Transitioning from manual issue tracking to real-time digital workflows reduced inefficiencies and improved decision-making during coordination meetings. The developed framework captures these process improvements by mapping changes across activity steps, tool functionalities, and coordination artifacts.

However, several challenges were also identified. These include contractual limitations, restricted model access for key stakeholders, and the absence of standardized protocols for issue prioritization. These barriers limited the cloud-based tool’s full potential and revealed a need for aligning organizational structures and contracts with digital workflows.

Beyond operational efficiency, the study highlights how cloud-based tools facilitate transparent communication, shared accountability, and faster decision-making. These factors are essential for multidisciplinary collaboration in complex projects. These impacts are relevant during design coordination and throughout the project lifecycle, as consistent documentation and real-time updates support downstream decision-making in construction and operations.

This research contributes to the body of knowledge by providing empirical evidence of the influence of cloud-based BIM tools on coordination efficiency and offering a structured approach to assessing their implementation. For practitioners and engineering managers, the findings provide actionable insights into digital adoption strategies that align with evolving coordination demands. For researchers, the study reinforces the importance of examining tool adoption within organizational and contractual contexts to inform future digital transformation efforts in the AEC industry.