Digital Platforms for the Built Environment: A Systematic Review Across Sectors and Scales

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

The study advocates for a paradigm shift toward modular, service-oriented, and human-centered platforms underpinned by standardized ontologies, explainable AI, and participatory governance models. The paper makes very innovative and meaningful recommendations as a result of a comprehensive study, and I believe its major value is combing the 6 domains in the same context and as drivers for possible and deep transformation of AEC.

A key statement in reviewing the great potential of digital technologies to transform the sector is “The lack of cross-sectoral comparisons… prevents the development of a shared vision of digital platform contribution towards the sustainable, efficient, responsive, and inclusive trans formation of the built environment”. Is this really a problem, that these technologies are not informing processes and there is no shared vision? Is there a proof for example that AI has made a difference in project management, as mentioned in section 3.1, like risk (LL 280-85) or safety (LL 298-302)? Are they the right ones purely for the AEC sector, possibly more suitable for the Energy sector?

My main criticism is that this exercise seems to be strong academic research in line with drivers like DigiPLACE or GAIA-X, but is the industry in need for a way forward in such a level? I believe all the scientific papers reviewed show limited practical applications and this is the essence, the industry and administration/ clients are still finding their way in these technological domains. The industry dimension is missing from this paper and maybe this is the state of the field. The authors need to reflect on this at the introduction.

Maybe the enhancement of the role of these technologies as socio- organizational facilitators is the primary driver?

This to me is an important dimension to discuss, but otherwise the paper fulfils its aims abundantly and will be of great interest to researchers in all the fields discussed. It is very well written (though many sentences could have been much more focused and curtailed) and it is ready for publication.

These more specific comments should be addressed, but would not change the contribution of the work.

“This deficiency causes the unfavorable creation of resilient, reliable, and agile knowledge bases for informed decision-making, risk reduction, and performance optimization in increasingly complex, dynamic, and uncertain environments.” This is key statement for the paper in LL 81-93 and the problem is not clear, it seems AEC is actually resilient?

The authors mention a limitation of the study in L 251: “relying solely on English articles brings in geographic and cultural bias … reflecting the Global North”. The authors could have included articles in Italian and Spanish in their systematic literature exploration. A systematic suggestion for further research can be included.

Table 4: from my experience in the UK where I am based, legacy data are not stored any more in paper for 20 years now. File formats and versions, yes, this can be a problem.

 

Author Response

General Comment: The study advocates for a paradigm shift toward modular, service-oriented, and human-centered platforms underpinned by standardized ontologies, explainable AI, and participatory governance models. The paper makes very innovative and meaningful recommendations as a result of a comprehensive study, and I believe its major value is combing the 6 domains in the same context and as drivers for possible and deep transformation of AEC.

Response: We thank the reviewer for this encouraging and thoughtful feedback. We are pleased that the integrative nature of the study, bringing together six distinct but interrelated domains, was recognized as a key strength. Our aim was to highlight how systemic transformation in the AEC sector and beyond can be enabled by cross-domain insights, modular platform architectures and inclusive, human-centered governance approaches. The positive reception of our recommendations regarding explainable AI and participatory models reinforces the relevance of the proposed framework and motivates further empirical validation and interdisciplinary dialogue.

 

Comment: A key statement in reviewing the great potential of digital technologies to transform the sector is “The lack of cross-sectoral comparisons… prevents the development of a shared vision of digital platform contribution towards the sustainable, efficient, responsive, and inclusive trans formation of the built environment”. Is this really a problem, that these technologies are not informing processes and there is no shared vision? Is there a proof for example that AI has made a difference in project management, as mentioned in section 3.1, like risk (LL 280-85) or safety (LL 298-302)? Are they the right ones purely for the AEC sector, possibly more suitable for the Energy sector?

Response: Thank you for your constructive observation. We agree that the claim regarding the lack of a shared vision should be substantiated. We have revised the statement to emphasize that the fragmentation of research and implementation practices across sectors creates challenges in establishing shared standards and governance models. This, in turn, limits the broader integration of digital platforms within the built environment.

Additionally, we have strengthened the evidential basis of Section 3.1 by including specific studies where AI has contributed to risk mitigation and safety enhancement in the AEC sector, for example, the use of machine learning for real-time construction site hazard detection, or predictive analytics for optimizing scheduling and cost management. These examples were selected for their relevance to the AEC context, although we acknowledge the cross-applicability to other sectors such as energy.

The revised version of Section 3.1 provides a more balanced, evidence-based perspective and avoids overgeneralizations. It also recognizes the need for further empirical validation and sector-specific adaptation of AI solutions to harness their potential within construction.

 

Revised text – 1. Introduction

The current fragmentation of research across technological domains and sectoral applications limits the ability to develop shared frameworks, data standards and governance models. This constrains not only knowledge transfer but also the practical integration of digital platforms across construction, infrastructure and energy systems [16]. For example, while AI applications in risk management and safety monitoring are emerging within the AEC sector (e.g., real-time hazard detection and predictive maintenance using computer vision and machine learning), their integration into comprehensive, interoperable platform ecosystems remains limited due to sectoral silos [17].

 

Revised text – 3.1. Artificial intelligence in digital platforms

Recent research suggests that AI has the potential to help address these challenges by enabling predictive analytics, real-time decision-making and automation, although widespread implementation remains limited. For instance, AI-based tools have been applied to construction risk management by improving safety protocols, optimizing resource allocation and supporting proactive hazard detection through computer vision and deep learning models [23]. In particular, real-world applications such as real-time safety monitoring systems using AI-powered computer vision have shown promise in detecting unsafe conditions on construction sites, thereby reducing the risk of accidents [24]. Similarly, AI-powered Digital Twins are being explored for real-time monitoring and adaptive planning in large-scale construction projects, aiming to reduce uncertainties and improve responsiveness to dynamic conditions [25].

AI is also being explored for its role in automated design processes, where machine learning techniques are used to optimize structural integrity, material efficiency and cost-effectiveness [22]. In waste management, AI-enabled platforms contribute to circular economy principles by reducing material waste and enhancing sustainability practices [22]. Safety solutions powered by AI offer dynamic risk assessment through real-time monitoring, enabling early detection of potential hazards and improving workplace safety outcomes [23]. Moreover, AI contributes to cybersecurity in construction platforms by enhancing the protection of sensitive project data from cyber threats [25].

While many of these applications also have relevance in other domains such as energy and manufacturing, their implementation within the AEC sector is being tested in research and pilot projects. For instance, AI-supported mobility prediction and optimization solutions are being adapted to improve construction site logistics and workforce scheduling [26].

Overall, these technological advancements suggest that AI has the potential to enhance efficiency, safety and sustainability in construction, but further empirical validation and sector-specific adaptation are needed to fully realize these benefits.

 

Comment: My main criticism is that this exercise seems to be strong academic research in line with drivers like DigiPLACE or GAIA-X, but is the industry in need for a way forward in such a level? I believe all the scientific papers reviewed show limited practical applications and this is the essence, the industry and administration/ clients are still finding their way in these technological domains. The industry dimension is missing from this paper and maybe this is the state of the field. The authors need to reflect on this at the introduction.

Response: We thank the reviewer for highlighting this essential point. We agree that the adoption of advanced digital platforms across the construction industry and public administration is still limited and that most scientific contributions reviewed focus on conceptual frameworks or early-stage applications. We have revised the Introduction to reflect this reality. In particular, we now emphasize that the paper does not assume full industry readiness but rather seeks to expose the existing fragmentation and systemic barriers that inhibit broader implementation. Our intention is to position the study as a foundational step, one that not only synthesizes existing academic research but also highlights the urgent need for industry-aligned and scalable digital solutions.

 

Revised text – 1. Introduction

While these research initiatives reflect a vision aligned with emerging European digital frameworks such as DigiPLACE and GAIA-X, the practical application of such platforms in the construction industry and public administration remains limited [13]. Digital maturity across the sector is uneven and many proposed solutions are still at the conceptual or prototype stage. As a result, there is a disconnect between the systemic integration envisaged in academic discourse and the current technological readiness and adoption capacity of most industry actors, particularly SMEs and local administrations [14].

 

Comment: Maybe the enhancement of the role of these technologies as socio- organizational facilitators is the primary driver?

Response: We thank the reviewer for this valuable observation. We agree that the socio-organizational role of digital platforms, particularly their ability to act as facilitators of collaboration and stakeholder coordination, may indeed represent their transformative potential. While our original framing highlighted the multidimensional nature of platforms, we have revised the manuscript to position these systems as socio-organizational infrastructures, not technical tools. This perspective is now further emphasized in the Introduction section, aligning with the reviewer’s insight and strengthening the conceptual clarity of the paper.

 

Revised text – 1. Introduction

Beyond their technical capacity, digital platforms are conceived as socio-organizational facilitators, enabling more effective communication, stakeholder alignment and cross-institutional collaboration. Their role as orchestrators of procedural and institutional transformation may represent their value in the AEC sector, where fragmented actors and siloed decision-making often impede innovation and systems integration.

 

Comment: “This deficiency causes the unfavorable creation of resilient, reliable, and agile knowledge bases for informed decision-making, risk reduction, and performance optimization in increasingly complex, dynamic, and uncertain environments.” This is key statement for the paper in LL 81-93 and the problem is not clear, it seems AEC is actually resilient?

Response: We thank the reviewer for highlighting the ambiguity in this key sentence. The original phrasing may have suggested that resilient and agile knowledge bases are already being created, which was not our intention. We have now revised the sentence to clarify that the lack of coordinated data and information systems hinders the development of such knowledge infrastructures.

 

Revised text – 1. Introduction

This deficiency hinders the development of resilient and agile knowledge bases that are essential for informed decision-making and performance optimization in complex and uncertain environments.

In this context, digital platforms, defined here as modular, interoperable systems that integrate data and workflows across stakeholders, emerge as potential drivers of transformative change within the AEC sector with the potential to offer inclusive, interoperable, and modular environments for the coordination of data, information, knowledge bases and processes across technologies, stakeholders, project phases, and scales [10].

 

Comment: The authors mention a limitation of the study in L 251: “relying solely on English articles brings in geographic and cultural bias … reflecting the Global North”. The authors could have included articles in Italian and Spanish in their systematic literature exploration. A systematic suggestion for further research can be included.

Response: We thank the reviewer for this thoughtful and constructive comment. We agree that relying on English-language sources introduces a geographic and cultural bias, favoring the Global North. While this decision was based on ensuring peer-reviewed quality and consistency across major databases, we recognize its limitations. In response, we have now expanded the “Methodology” section to include a recommendation that future reviews incorporate literature in other used languages, such as Italian and Spanish, to improve the inclusiveness and geographic representativeness of digital platform research in the built environment.

 

Revised text – 2. Methodology

While this study offers a comprehensive synthesis of peer-reviewed academic literature, one notable limitation is its reliance on English-language sources. This introduces a potential geographic and cultural bias, as most indexed literature originates from institutions and researchers in the Global North. However, the challenges and patterns that emerge, such as data fragmentation, platform immaturity, interoperability issues and institutional inertia, are often systemic and not exclusive to the Global North. As such, they may offer valuable reference points for identifying analogous barriers and guiding digital platform development in Global South contexts, provided that they are adapted through context-sensitive implementation strategies.

Future research could address this by including academic and grey literature published in other languages, such as Italian, Spanish, French, or Chinese, to better represent Southern European, Latin American, and Asian perspectives on digital platform development in the built environment. This constraint underlines the need for follow-up research into digital platform development and deployment in the Global South, where there might be differences in socio-institutional conditions, technological adoption pathways, and governance concerns. While these constraints follow from the scope of the study and methodological rigor, they open up possibilities for such subsequent studies as empirical case-study research, stakeholder workshop sessions, and policy conversations that might corroborate, contextualize, and augment the evidence of the current study to make them generalizable across various global contexts. Accordingly, while the review's findings may not generalize to all geographical regions, especially those underrepresented in English-language academic discourse, they provide a framework upon which tailored studies can be developed. Future research should aim to include primary case studies and literature from underrepresented regions to validate and adapt the proposed conceptual models and cross-domain insights in diverse local conditions.

 

Comment: Table 4: from my experience in the UK where I am based, legacy data are not stored any more in paper for 20 years now. File formats and versions, yes, this can be a problem.

Response: We thank the reviewer for this valuable insight. We acknowledge that in countries like the UK, the digitization of legacy data has been well advanced for two decades and paper-based archives are not an issue in current workflows. However, the reference to paper-based legacy data in Table 4 reflects the persistence of such challenges in less mature regions or in older administrative and infrastructure systems where full digitization has not yet been achieved. To clarify this point, we have revised the entry in Table 4 to contextualize the variability across regions.

Reviewer 2 Report

Comments and Suggestions for Authors

The authors present a systematic cross-sectoral review of digital platforms in the built environment across six domains, examining their functional roles, technologies, limitations, and emerging trends. The paper provides a cross-domain perspective, analytical framework, categorization of structural barriers, and research agenda for platform development. Upon review, several aspects warrant further discussion:

1. The assessment of technological maturity requires further development. The manuscript identifies emerging technologies such as "large language models (LLMs), immersive digital spaces (AR, VR, XR), and federated learning" (lines 1067-1068), noting that these technologies have "significant gaps in terms of their maturity, scalability, and interoperability" (lines 1069-1070). A more detailed evaluation of technology readiness levels across applications would enhance the paper's practical relevance. The discussion of "Metaverse as a virtual model of platform urbanism" (lines 367-368) would also benefit from additional examination of implementation feasibility.
2. The paper notes a methodological limitation regarding geographical bias (lines 251-254), stating that "relying solely on English articles brings in geographic and cultural bias with the selected literature reflecting mainly the Global North contexts, practices, and agendas." This limitation requires reconciliation with the recommendation (lines 1073-1075) for developing "context-sensitive, frugal, and inclusive platform models" for the Global South. Including case studies from diverse geographical contexts or clarifying the scope of generalizability would address this issue.
3. The cross-scalar integration mechanisms need additional elaboration. While the conceptual framework (lines 175-180) includes "lifecycle phase or scale" as an analytical dimension, the paper would benefit from addressing the technical and organizational challenges of integrating data across building, urban, and regional scales. The recommendation for "multi-scale, multi-domain, and standardized ontologies" (lines 983-984) requires more specific implementation guidance regarding data granularity and hierarchical relationships.
4. The paper presents a tension between data integration imperatives and privacy/security concerns. The sections on data quality, availability and interoperability (lines 922-930) and the integration strategies (lines 982-989) need to address more directly the "privacy and data security issues" mentioned elsewhere (lines 936-941). The proposed use of "distributed ledger technologies" (lines 1002-1003) warrants examination of trade-offs between openness and protection.
5. The cost-benefit analysis for platform implementation needs additional quantitative evidence. While "implementation costs" are identified as a limitation (lines 966-969), the paper would benefit from more substantive evidence supporting the conclusions about "substantial operational savings and prolonged asset lifespans" (lines 510-512). The proposed solutions (lines 981-1004) should address economic feasibility across different organizational contexts.
6. The conceptual boundaries between digital platforms and related technologies require clarification. The definition of digital platforms (lines 163-170) and earlier descriptions (lines 81-93) create some ambiguity in discussions of digital twin applications (lines 417-419). Similarly, the relationship between Digital Twins (lines 376-378) and digital twin-based platforms (lines 451-456) needs more precise delineation of functionalities and implementations.
7. The case study analysis would benefit from additional quantitative assessment. The overview of cost management applications (lines 480-487) and case examples (lines 490-504, 516-523) need more quantitative evidence to support the claimed benefits (lines 570-573). Additionally, the absence of platforms focused on "the construction stage" (lines 586-587) requires reconciliation with the assertion that "the sector is entering an even more extensive and complex phase of digital transformation" (lines 43-44).

Author Response

General Comment: The authors present a systematic cross-sectoral review of digital platforms in the built environment across six domains, examining their functional roles, technologies, limitations, and emerging trends. The paper provides a cross-domain perspective, analytical framework, categorization of structural barriers, and research agenda for platform development. Upon review, several aspects warrant further discussion:

Response: We thank the reviewer for acknowledging the value and scope of our systematic cross-sectoral review. We appreciate the recognition of the paper’s contributions, including the comparative framework, the categorization of limitations and the proposed research agenda. In response to the reviewer’s insightful observations and the specific comments provided, we have thoroughly revised the manuscript to offer additional clarifications and critical elaborations.

 

Comment: 1. The assessment of technological maturity requires further development. The manuscript identifies emerging technologies such as "large language models (LLMs), immersive digital spaces (AR, VR, XR), and federated learning" (lines 1067-1068), noting that these technologies have "significant gaps in terms of their maturity, scalability, and interoperability" (lines 1069-1070). A more detailed evaluation of technology readiness levels across applications would enhance the paper's practical relevance. The discussion of "Metaverse as a virtual model of platform urbanism" (lines 367-368) would also benefit from additional examination of implementation feasibility.

Response: We thank the reviewer for this insightful and constructive comment. We agree that a more explicit evaluation of the technological maturity of the emerging tools discussed would enhance the manuscript’s relevance and clarity. In response, we have revised the Discussion (Cross-domain synthesis) section by introducing the TRL framework to categorize the maturity of key technologies, including BIM, digital twins, LLMs, federated learning, immersive environments and the Metaverse.

Specifically:

• We classified mature technologies (e.g., BIM, traditional dashboards) as operating at TRL 8–9;
• We assessed emerging technologies like LLMs, federated learning and the Metaverse at TRL 2–5, highlighting current barriers to scalability and operational integration;
• We provided concrete examples of implementation feasibility for the Metaverse, referencing pilot applications in select global cities and the current limitations impeding widespread deployment.

 

Revised text – 4. Discussion (Cross-domain synthesis)

To provide a more concrete evaluation of technological maturity, the framework of Technology Readiness Levels (TRLs) is introduced. This helps assess the developmental stage and implementation feasibility of emerging technologies. Mature technologies such as BIM, IoT systems and traditional dashboard interfaces operate at TRL 8–9, indicating full deployment in commercial and operational contexts. In contrast, innovations like large language models (LLMs), federated learning, and immersive environments (AR, VR, XR) remain at TRL 3–5, as they have been validated within niche applications related to the built environment. Similarly, the Metaverse, discussed as a virtual model of platform urbanism, remains conceptual (TRL 2–4), hindered by technological, legal and organizational readiness gaps.

 

Revised text – 4. Discussion (Cross-domain synthesis)

Furthermore, incorporating TRL perspectives clarifies the maturity gaps between technologies. Digital twins and BIM-GIS platforms, for example, are at TRL 6–8, yet their broader deployment is hindered by issues of semantic interoperability, legacy data integration and platform silos. In contrast, technologies such as federated learning, which offer privacy-preserving, distributed AI training, remain at proof-of-concept stages in the built environment and face challenges related to data governance, computational infrastructure and legal compliance. These differences in maturity demand tailored R&D strategies that account for both readiness and application domain.

The Metaverse provides another instructive case. While promising for virtual participatory governance and immersive urban simulation, its current applications are limited. Pilot projects in cities like Seoul and Singapore are still in exploratory phases, with widespread implementation constrained by interoperability issues, accessibility of hardware, digital literacy and policy uncertainty. As such, the Metaverse in its current form is best positioned at an experimental TRL, reinforcing the need for incremental adoption supported by cross-sectoral testbeds and collaborative development frameworks.

 

Comment: 2. The paper notes a methodological limitation regarding geographical bias (lines 251-254), stating that "relying solely on English articles brings in geographic and cultural bias with the selected literature reflecting mainly the Global North contexts, practices, and agendas." This limitation requires reconciliation with the recommendation (lines 1073-1075) for developing "context-sensitive, frugal, and inclusive platform models" for the Global South. Including case studies from diverse geographical contexts or clarifying the scope of generalizability would address this issue.

Response: We thank the reviewer for highlighting this important point. In response, we have clarified in the Methodology section that, although the literature analyzed reflects Global North experiences, the challenges and patterns identified, such as data fragmentation and governance barriers, are often systemic and thus relevant for broader application. We now note that these insights can guide the development of context-sensitive and frugal digital platforms in the Global South, provided they are adapted to local infrastructural and institutional contexts.

Additionally, we have strengthened the Conclusion by calling for further empirical research and case studies in Global South settings to operationalize and validate the applicability of these findings.

 

Revised text – 2. Methodology

While this study offers a comprehensive synthesis of peer-reviewed academic literature, one notable limitation is its reliance on English-language sources. This introduces a potential geographic and cultural bias, as most indexed literature originates from institutions and researchers in the Global North. However, the challenges and patterns that emerge, such as data fragmentation, platform immaturity, interoperability issues and institutional inertia, are often systemic and not exclusive to the Global North. As such, they may offer valuable reference points for identifying analogous barriers and guiding digital platform development in Global South contexts, provided that they are adapted through context-sensitive implementation strategies.

Future research could address this by including academic and grey literature published in other languages, such as Italian, Spanish, French, or Chinese, to better represent Southern European, Latin American, and Asian perspectives on digital platform development in the built environment. This constraint underlines the need for follow-up research into digital platform development and deployment in the Global South, where there might be differences in socio-institutional conditions, technological adoption pathways, and governance concerns. While these constraints follow from the scope of the study and methodological rigor, they open up possibilities for such subsequent studies as empirical case-study research, stakeholder workshop sessions, and policy conversations that might corroborate, contextualize, and augment the evidence of the current study to make them generalizable across various global contexts. Accordingly, while the review's findings may not generalize to all geographical regions, especially those underrepresented in English-language academic discourse, they provide a framework upon which tailored studies can be developed. Future research should aim to include primary case studies and literature from underrepresented regions to validate and adapt the proposed conceptual models and cross-domain insights in diverse local conditions.

 

Revised text – 5. Conclusions

A gap in the literature is the Global South, wherein the majority of research does not consider the unique socio-economic, institutional, and infrastructural contexts. While this paper focuses on literature from the Global North, many of the structural challenges identified, such as platform fragmentation, low interoperability and governance barriers, are systemic and occur in underrepresented contexts as well. Emphasis is placed in this paper on the need for developing context-sensitive, frugal, and inclusive platform models, co-designed with the local stakeholders, ensuring that digital transformation processes promote equity, inclusion, and resilience, and do not increase digital divides. Future research should address this gap by integrating literature and empirical evidence from underrepresented regions and by validating proposed models through case studies that reflect diverse geographical, cultural and institutional settings.

 

Comment: 3. The cross-scalar integration mechanisms need additional elaboration. While the conceptual framework (lines 175-180) includes "lifecycle phase or scale" as an analytical dimension, the paper would benefit from addressing the technical and organizational challenges of integrating data across building, urban, and regional scales. The recommendation for "multi-scale, multi-domain, and standardized ontologies" (lines 983-984) requires more specific implementation guidance regarding data granularity and hierarchical relationships.

Response: We thank the reviewer for this important observation. In response, we have revised the Cross-domain synthesis section to further elaborate the technical and organizational mechanisms enabling cross-scalar integration. Specifically, we have expanded on how hierarchical and semantic ontologies can be implemented to bridge different spatial and functional scales, from the object/component level (BIM) to urban/regional models (GIS, digital twins). We now discuss the importance of aligning metadata schemas, handling bidirectional data flows and ensuring consistency in spatial and temporal resolutions. Furthermore, we provide practical examples of how these ontologies can support top-down policy translation and bottom-up data aggregation through service-oriented architectures and modular platform design.

 

Revised text – 4. Discussion (Cross-domain synthesis)

Additionally, a major integration challenge involves data interoperability and semantic coherence across spatial scales (building, neighborhood, urban, regional) and lifecycle stages (design, construction, operation, end-of-life). Digital platforms often operate with scale-specific data granularity, e.g., BIM models at the object/component level versus GIS datasets at the territorial level, which complicates integration. Therefore, the implementation of hierarchical ontologies that define entity relationships across spatial and functional levels is critical. For example, nested relationships (e.g., 'door' within 'room' within 'building' within 'urban block') must be modeled using aligned metadata schemas and linked data techniques. These ontologies should also support bidirectional data flows, allowing both top-down (e.g., policy-to-asset) and bottom-up (e.g., sensor-to-system) integration.

 

Revised text – 4. Discussion (Cross-domain synthesis)

Integrating data across scales further requires designing ontological frameworks capable of bridging granular object-level BIM datasets with abstract GIS and statistical models, often deployed at urban or regional scales. This involves explicit mapping of semantic terms and units (e.g., energy use per square meter in BIM to district-level consumption in GIS) as well as ensuring consistency in spatial reference systems and temporal resolution.

 

Revised text – 4. Discussion (Cross-domain synthesis)

This orchestrator function is relevant in cross-scalar scenarios, where platforms must manage data at different levels of abstraction and spatial granularity. For instance, integrating IoT sensor data from individual building systems into regional digital twin environments requires real-time data normalization and alignment through middleware components that operate under a unified ontology layer. Such middleware must also include privacy-preserving computation protocols or federated learning models when sensitive data is involved, enabling analytics without centralized data exposure.

 

Comment: 4. The paper presents a tension between data integration imperatives and privacy/security concerns. The sections on data quality, availability and interoperability (lines 922-930) and the integration strategies (lines 982-989) need to address more directly the "privacy and data security issues" mentioned elsewhere (lines 936-941). The proposed use of "distributed ledger technologies" (lines 1002-1003) warrants examination of trade-offs between openness and protection.

Response: We thank the reviewer for this important and constructive observation. In response, we have revised the “Cross-domain synthesis” section to articulate the tension between data integration and privacy/security. Specifically, we have added a dedicated discussion that emphasizes how the integration of data across sectors and scales, while critical to unlocking the full potential of digital platforms, must be balanced with concerns related to privacy and cybersecurity risks.

We have also expanded the paragraph discussing distributed ledger technologies to address the trade-offs involved, including scalability limitations and potential conflicts with data protection regulations such as the GDPR. This revised section now provides a more nuanced analysis of the openness–protection dilemma and highlights the need for architectural solutions that ensure controlled transparency and compliance.

Additionally, we now refer to privacy-preserving approaches, such as federated learning and decentralized identity management, within the context of middleware components for cross-scalar platform integration.

 

Revised text – 4. Discussion (Cross-domain synthesis)

However, this drive toward integration must be balanced with privacy and cybersecurity concerns, especially when integrating sensitive user data or operational parameters across platforms. Ensuring that data sharing does not compromise confidentiality, while enabling transparency and reuse, is a critical technical and ethical challenge.

 

Revised text – 4. Discussion (Cross-domain synthesis)

These offer tamper-proof audit trails and decentralized access control, which can help mitigate risks of unauthorized data manipulation or breaches. Nevertheless, they introduce trade-offs in terms of scalability, latency and compliance with data protection regulations such as GDPR. Therefore, careful architectural design is required to optimize between openness, control and legal conformity.

 

Revised text – 4. Discussion (Cross-domain synthesis)

This orchestrator function is relevant in cross-scalar scenarios, where platforms must manage data at different levels of abstraction and spatial granularity. For instance, integrating IoT sensor data from individual building systems into regional digital twin environments requires real-time data normalization and alignment through middleware components that operate under a unified ontology layer. Such middleware must also include privacy-preserving computation protocols or federated learning models when sensitive data is involved, enabling analytics without centralized data exposure.

 

Comment: 5. The cost-benefit analysis for platform implementation needs additional quantitative evidence. While "implementation costs" are identified as a limitation (lines 966-969), the paper would benefit from more substantive evidence supporting the conclusions about "substantial operational savings and prolonged asset lifespans" (lines 510-512). The proposed solutions (lines 981-1004) should address economic feasibility across different organizational contexts.

Response: We thank the Reviewer for this insightful comment, which helps improve the practical relevance of our study. In response, we have revised the “Cross-domain synthesis” section by integrating quantitative examples and empirical evidence to substantiate the discussion on cost-benefit analysis and economic feasibility. Specifically, we included references to EU-funded research and international pilot projects that quantify deployment costs (e.g., €100,000–€500,000 for smart building platforms), operational savings (up to 20% in energy expenditures) and ROI periods (typically 3–5 years in infrastructure management contexts). We also emphasized that economic feasibility varies depending on the size and organizational maturity of the implementing institution. Furthermore, we discussed the financial constraints faced by smaller public authorities, highlighting the importance of scalable and frugal solutions. These additions aim to clarify the potential economic benefits of digital platform adoption while also acknowledging their contextual limitations.

 

Revised text – 4. Discussion (Cross-domain synthesis)

These constraints, particularly implementation costs, have been estimated in recent studies. For instance, EU-funded research on energy platforms indicates that initial deployment costs for interoperable smart systems in public buildings can range between €100,000 and €500,000 depending on scale, while operational savings of up to 20% on annual energy bills have been documented [164]. Similarly, lifecycle cost evaluations of BIM-integrated asset management platforms show potential return on investment (ROI) within 3–5 years when applied at city-scale infrastructure networks [165].

 

Revised text – 4. Discussion (Cross-domain synthesis)

This would also help the development of platforms whose focus is centered on cost management, not yet investigated in research. Pilot implementations of lifecycle cost management platforms in hospital infrastructure projects in Italy and the Netherlands have shown improved budget forecasting accuracy by over 25% compared to conventional methods, reducing overall project overruns [176]. However, adoption in smaller municipalities remains limited due to upfront capital and staff training costs, showing that economic feasibility is context-dependent.

 

Comment: 6. The conceptual boundaries between digital platforms and related technologies require clarification. The definition of digital platforms (lines 163-170) and earlier descriptions (lines 81-93) create some ambiguity in discussions of digital twin applications (lines 417-419). Similarly, the relationship between Digital Twins (lines 376-378) and digital twin-based platforms (lines 451-456) needs more precise delineation of functionalities and implementations.

Response: We thank the reviewer for this important observation regarding the need to clarify the conceptual distinction between digital platforms and the enabling technologies they often incorporate, particularly Digital Twins. In the revised manuscript, we have improved the definitions and descriptions to address this ambiguity.

1. We revised the definition of digital platforms to emphasize their role as socio-technical infrastructures that orchestrate data and users and that integrate, without being synonymous with, technologies such as Digital Twins, BIM and AI. We distinguish platforms as environments that coordinate and scale these technologies into service ecosystems.
2. We included a clarifying sentence noting that, while digital platforms incorporate advanced technologies (e.g., DTs, BIM, IoT), they operate at a different functional layer by enabling interoperability and service deployment across systems and actors.
3. We revised the text to define Digital Twins as enabling technologies that provide synchronized digital representations of assets, whereas digital twin-based platforms are systems that incorporate DTs as part of broader coordination architectures. We specify that these platforms use DTs to provide real-time data integration, multi-stakeholder collaboration and service orchestration.
4. We further clarified that platforms leveraging DTs serve to operationalize real-time simulation and decision-making capabilities within a broader data governance and interoperability framework.

 

Revised text – 1. Introduction

While digital platforms often incorporate technologies like Digital Twins and AI, they differ in that platforms provide the infrastructural backbone and governance architecture through which these technologies interoperate, scale and deliver user-facing services.

While these research initiatives reflect a vision aligned with emerging European digital frameworks such as DigiPLACE and GAIA-X, the practical application of such platforms in the construction industry and public administration remains limited [13]. Digital maturity across the sector is uneven and many proposed solutions are still at the conceptual or prototype stage. As a result, there is a disconnect between the systemic integration envisaged in academic discourse and the current technological readiness and adoption capacity of most industry actors, particularly SMEs and local administrations [14].

 

Revised text – 2. Methodology

Digital platforms are socio-technical ecosystems that orchestrate data, technologies, actors and services to enable multi-scalar, cross-sectoral collaboration and decision-making. While they may integrate enabling technologies such as Digital Twins, BIM, and IoT, platforms are distinguished by their role in hosting, coordinating and scaling these technologies into cohesive service environments, rather than functioning as standalone tools.

 

Revised text – 3.2. Digital Twin integration through digital platforms

DTs serve as enabling technologies that synchronize digital replicas with real-time physical data, enhancing monitoring and simulation capabilities. When embedded within digital platforms, DTs contribute to broader system orchestration by feeding real-time data into platform services for planning, decision support and lifecycle optimization.

 

Revised text – 3.2.4. Energy efficiency

Digital Twin-based platforms integrate DTs with other technologies such as BIM and IoT to create interoperable environments for real-time monitoring and urban system management. In this context, the platform acts as the coordination layer, enabling multi-user access, data governance, and cross-system interaction based on DT inputs.

 

Comment: 7. The case study analysis would benefit from additional quantitative assessment. The overview of cost management applications (lines 480-487) and case examples (lines 490-504, 516-523) need more quantitative evidence to support the claimed benefits (lines 570-573). Additionally, the absence of platforms focused on "the construction stage" (lines 586-587) requires reconciliation with the assertion that "the sector is entering an even more extensive and complex phase of digital transformation" (lines 43-44).

Response: We thank the reviewer for this constructive observation. In response, we revised the Discussion section to better substantiate the benefits of cost management platforms with available quantitative data and references. Specifically, we expanded the description of case examples to include indicative figures, such as cost overrun reductions and maintenance efficiency gains, drawn from relevant pilot studies and industry reports.

Furthermore, we clarified the seeming contradiction regarding the absence of platforms during the construction stage by noting that this phase remains underserved despite the ongoing digital transformation of the sector. A new sentence was added in the Introduction which now acknowledges that the construction phase, due to its complexity and fragmentation, continues to face critical platform adoption gaps, especially in real-time data integration and process coordination.

 

Revised text – 1. Introduction

The Architecture, Engineering, and Construction (AEC) sector is undergoing a digital transformation, driven by the convergence of cross-cutting technologies such as Building Information Modeling (BIM), Artificial Intelligence (AI), the Internet of Things (IoT), Digital Twins (DT), blockchain and cloud-based collaborative platforms [1]. Over the past two decades, BIM has laid the groundwork for this transition by enabling integrated data environments that enhance coordination across design, construction and facility operations [2]. Today, the sector is entering a more complex and integrated phase, in which these technologies not only support real-time monitoring, predictive analysis and lifecycle asset management, but also challenge traditional organizational and governance models [3]. However, critical gaps persist, particularly during the construction stage, where integrated platforms for real-time coordination and data exchange remain limited and process fragmentation continues to hinder seamless digitalization.

 

Revised text – 3.3.1. Data integration across domains

For instance, in a pilot deployment within a mid-sized municipality, the implementation of a BIM-integrated cost management platform led to a 25% reduction in project cost overruns and shortened procurement timelines by 30% [68].

Reviewer 3 Report

Comments and Suggestions for Authors

Abstract
•    You mention a systematic review of 125 peer-reviewed studies but do not describe how the studies were selected (e.g., databases, inclusion criteria, PRISMA approach, etc.).
•    Consider including a brief mention of how the six domains were defined or clustered—was this emergent from the literature or predefined?
•    What makes this review unique compared to existing ones in digital construction or smart cities literature? Is it the cross-sectoral comparison? The global south focus?
•    Phrases like “data fragmentation, poor interoperability, process incoherence...” are heavy and abstract. Consider simplifying or giving a more concrete example.

Introduction.

The opening could be more concise. Consider merging lines 38–42 into a sharper, more impactful paragraph:
The Architecture, Engineering, and Construction (AEC) sector is undergoing a profound digital transformation. Over the past two decades, Building Information Modeling (BIM) has laid the groundwork by enabling integrated data environments that enhance coordination across design, construction, and facility operations.

Clarify What You Mean by “Digital Platforms” Early On
The definition of digital platforms appears later (lines 81–87). Readers unfamiliar with this domain may benefit from a brief working definition earlier, such as:
“Digital platforms—defined here as modular, interoperable systems that integrate data, technologies, and workflows across stakeholders—have recently gained attention as potential enablers of transformation in AEC.”

Do any of the reviewed studies explicitly compare how platforms operate across more than one sector or lifecycle stage?
Is the review positioned only for AEC researchers, or also urban planners, data scientists, and policy designers? The framing of terms like “platform” and “socio-technical” could be tailored accordingly.

Methodology
You mention following PRISMA, but do not explain how it was applied (search terms, inclusion/exclusion criteria, screening stages). Even if these are in the Supplementary Materials, a brief summary is essential.

In line 144, you mention that a formal protocol wasn’t prepared. To mitigate this, you could strengthen the rationale for why a systematic review was still warranted despite this omission.

Why 2015–2025? Is this based on technological emergence or a literature saturation point?

The manuscript is too long, need to reduce the page

Author Response

Comment: Abstract

•    You mention a systematic review of 125 peer-reviewed studies but do not describe how the studies were selected (e.g., databases, inclusion criteria, PRISMA approach, etc.).
•    Consider including a brief mention of how the six domains were defined or clustered—was this emergent from the literature or predefined?
•    What makes this review unique compared to existing ones in digital construction or smart cities literature? Is it the cross-sectoral comparison? The global south focus?
•    Phrases like “data fragmentation, poor interoperability, process incoherence...” are heavy and abstract. Consider simplifying or giving a more concrete example.

Response: We thank the reviewer for this constructive and insightful comment regarding the clarity and precision of the abstract. In response, we have revised the abstract to address the following aspects:

1. We have now included a concise mention of the PRISMA 2020 methodology adopted for study identification and screening, the use of the Scopus database, and the inclusion criteria (e.g., peer-reviewed journal articles published in English between 2015 and early 2025).
2. A sentence has been added to clarify that the six thematic domains (AI in construction, digital twins, lifecycle cost management, BIM-GIS for underground utilities, energy systems, and public administration) were identified based on a combination of preliminary literature analysis and their recognized relevance in policy and academic discourse on digitalization in the built environment.
3. We have highlighted the originality of this review in its cross-sectoral and cross-scalar synthesis of digital platforms in the built environment, contrasting it with scoped reviews. We also clarify that while the dataset is based on literature from the Global North, the study emphasizes future directions and methodological approaches relevant to the Global South.
4. We have rephrased abstract terms such as “data fragmentation, poor interoperability, and process incoherence” using more accessible expressions (e.g., incompatible data formats, disconnected systems, and uncoordinated workflows) to enhance readability and clarity for a broader audience.

 

Revised text – Abstract

The digital transformation of the architecture, engineering, and construction (AEC) sector is accelerating the adoption of digital platforms as critical enablers of data integration, stakeholder collaboration and process optimization. This paper presents a systematic review of 125 peer-reviewed journal articles (2015–2025), selected through a PRISMA-guided search using the Scopus database, with inclusion criteria focused on English-language academic literature on platform-enabled digitalization in the built environment. Studies were grouped into six thematic domains, i.e. artificial intelligence in construction, digital twin integration, lifecycle cost management, BIM-GIS for underground utilities, energy systems and public administration, based on a combination of literature precedent and domain relevance. Unlike existing reviews focused on single technologies or sectors, this work offers a cross-sectoral synthesis, highlighting shared challenges and opportunities across disciplines and lifecycle stages. It identifies the functional roles, enabling technologies and systemic barriers affecting digital platform adoption, such as fragmented data sources, limited interoperability between systems and siloed organizational processes. These barriers hinder the development of integrated and adaptive digital ecosystems capable of supporting real-time decision-making, participatory planning and sustainable infrastructure management. The study advocates for modular, human-centered platforms underpinned by standardized ontologies, explainable AI and participatory governance models. It also highlights the importance of emerging technologies, including large language models and federated learning, as well as context-specific platform strategies, especially for applications in the Global South. By offering an integrated, cross-domain perspective, the review contributes a foundational framework for advancing equitable and scalable digital platform development in the built environment.

Comment: The opening could be more concise. Consider merging lines 38–42 into a sharper, more impactful paragraph:

The Architecture, Engineering, and Construction (AEC) sector is undergoing a profound digital transformation. Over the past two decades, Building Information Modeling (BIM) has laid the groundwork by enabling integrated data environments that enhance coordination across design, construction, and facility operations.

Response: We appreciate the reviewer’s thoughtful suggestion. In response, we revised the opening paragraph of the Introduction to improve conciseness and strengthen its impact. Specifically, we merged lines 38–42 into a unified paragraph that highlights the AEC sector's digital transformation, the foundational role of BIM, and the growing complexity introduced by emerging technologies such as AI, IoT, Digital Twins, and cloud-based platforms. This revision eliminates redundancy and aligns the introductory tone with the overarching goals of the paper.

 

Revised text – 1. Introduction

The Architecture, Engineering, and Construction (AEC) sector is undergoing a digital transformation, driven by the convergence of cross-cutting technologies such as Building Information Modeling (BIM), Artificial Intelligence (AI), the Internet of Things (IoT), Digital Twins (DT), blockchain and cloud-based collaborative platforms[1]. Over the past two decades, BIM has laid the groundwork for this transition by enabling integrated data environments that enhance coordination across design, construction and facility operations[2]. Today, the sector is entering a more complex and integrated phase, in which these technologies not only support real-time monitoring, predictive analysis and lifecycle asset management, but also challenge traditional organizational and governance models[3]. However, critical gaps persist, particularly during the construction stage, where integrated platforms for real-time coordination and data exchange remain limited and process fragmentation continues to hinder seamless digitalization.

 

Comment: Clarify What You Mean by “Digital Platforms” Early On

The definition of digital platforms appears later (lines 81–87). Readers unfamiliar with this domain may benefit from a brief working definition earlier, such as:

“Digital platforms—defined here as modular, interoperable systems that integrate data, technologies, and workflows across stakeholders—have recently gained attention as potential enablers of transformation in AEC.”

Response: We thank the reviewer for this helpful and constructive suggestion. In response, we have added a concise working definition of “digital platforms” at their first mention in the Introduction to improve clarity for readers less familiar with the concept.

 

Revised text – 1. Introduction

In this context, digital platforms, defined here as modular, interoperable systems that integrate data, technologies, and workflows across stakeholders, emerge as potential drivers of transformative change within the AEC sector with the potential to offer inclusive, interoperable, and modular environments for the coordination of data, information, knowledge bases and processes across technologies, stakeholders, project phases, and scales[10].

 

Comment: Do any of the reviewed studies explicitly compare how platforms operate across more than one sector or lifecycle stage?

Is the review positioned only for AEC researchers, or also urban planners, data scientists, and policy designers? The framing of terms like “platform” and “socio-technical” could be tailored accordingly.

Response: Thank you for your comment. We have revised the Introduction to clarify that only a few studies compare platform use across sectors or lifecycle stages, highlighting the need for a systemic synthesis. The review now addresses a broader audience, including AEC researchers, urban planners, data scientists and policy designers, and reframes digital platforms as socio-technical ecosystems that support both technological functions and institutional coordination.

 

Revised text – 1. Introduction

The existing body of literature lacks a systemic and cross-sectoral synthesis of how digital platforms can act as orchestrators of digital transformation. Only a limited number of studies compare platform use across sectors or life cycle stages, most instead concentrate on isolated domains, technologies, or phases. This reinforces the need for a broader review that examines digital platforms as socio-technical ecosystems: not only technological tools, but enablers of organizational data governance and collaborative workflows[15].

 

Revised text – 1. Introduction

This paper bridges this research gap by providing a systematic and cross-sectoral literature review of digital platforms in the built environment and associated domains. In doing so, it addresses a diverse audience that includes not only AEC researchers, but also urban planners and public policy designers engaged in the digitalization of cities and services. By adopting a multi-domain and multi-scalar perspective, the paper contributes to the existing body of knowledge by investigating how digital platforms might develop from technical tools into interoperable governance infrastructures, bringing together technical and institutional aspects across lifecycle stages and spatial scales.

 

Comment: You mention following PRISMA, but do not explain how it was applied (search terms, inclusion/exclusion criteria, screening stages). Even if these are in the Supplementary Materials, a brief summary is essential.

Response: We thank the reviewer for this insightful comment. In response, we have clarified in the revised Introduction section that while some of the reviewed studies touch upon applications of digital platforms across different lifecycle stages or domains, very few compare platform operations across sectors or phases. This observation highlights a gap in the existing literature and reinforces the novelty and contribution of our cross-sectoral and multi-scalar synthesis.

Additionally, we have revised the framing of the paper to reflect its interdisciplinary relevance. We now state that the review is intended for a broad audience, including urban planners and public policy professionals, in addition to AEC researchers. We have also refined our use of key terms such as “platform” and “socio-technical” to make them more accessible and meaningful to this wider readership.

 

Comment: In line 144, you mention that a formal protocol wasn’t prepared. To mitigate this, you could strengthen the rationale for why a systematic review was still warranted despite this omission.

Response: We thank the reviewer for this insightful observation. In response, we have revised the Methodology section to articulate the rationale for undertaking a systematic review despite not having a pre-registered protocol. Specifically, we now emphasize that the fragmented and cross-sectoral nature of the literature on digital platforms in the built environment necessitated a structured and transparent review approach. Although no formal protocol was registered, the review was conducted in line with PRISMA 2020 guidelines, and we adopted a methodological framework to ensure the reliability and thematic consistency of our findings. These measures ensure that the absence of a pre-registered protocol does not compromise the rigor or value of the study.

 

Revised text – 2. Methodology

Although no formal protocol was registered in a prospective database such as PROSPERO, the decision to adopt a systematic review approach was justified by the need to synthesize fragmented and dispersed literature on digital platforms in the built environment. Given the increasing academic and policy interest in platform-based digital transformation and the absence of existing cross-sectoral reviews, this approach was deemed to ensure transparency, and thematic coherence.

 

Comment: Why 2015–2025? Is this based on technological emergence or a literature saturation point?

Response: Thank you for this pertinent observation. In the revised manuscript, we have clarified the rationale behind selecting the 2015–2025 timeframe. Specifically, the year 2015 was identified as a turning point in the scholarly and institutional discourse surrounding digital platforms in the built environment. It coincides with the launch of key digital transformation initiatives at the European level (e.g., DigiPLACE, early GAIA-X developments), and the rise in platform-enabled solutions across the construction and public administration sectors. This period captures the rapid evolution and mainstreaming of enabling technologies such as BIM and AI within platform ecosystems. The end date of early 2025 ensures the inclusion of the most recent literature at the time of manuscript preparation.

 

Revised text – 2. Methodology

The search for articles was restricted to English-language journal publications between 2015 and early 2025. This date range was chosen to reflect the recent surge in platform-centric research and technological integration across the AEC and urban governance sectors. Specifically, 2015 marks an inflection point, corresponding with increased scholarly attention and the launch of major digitalization initiatives such as the European Commission’s DigiPLACE and the early conceptualization of cross-sector data spaces. The timeframe thus captures a decade in which platform strategies became central to digital transformation efforts.

Round 2

Reviewer 2 Report

Comments and Suggestions for Authors

All the issues have been reasonably and comprehensively explained by the author, and supplementary explanations or modifications have been made at the corresponding positions in the text. There are no more problems.

Author Response

General Comment: All the issues have been reasonably and comprehensively explained by the author, and supplementary explanations or modifications have been made at the corresponding positions in the text. There are no more problems.

We thank the reviewer for their positive assessment and appreciation of our revisions. We are pleased that the modifications and clarifications provided have addressed all concerns.

Reviewer 3 Report

Comments and Suggestions for Authors

Please state the contribution of the research in the conclusion more clearly, to the knowledge and practice

Author Response

Comment: Please state the contribution of the research in the conclusion more clearly, to the knowledge and practice

Response: We thank the reviewer for this valuable suggestion. In response, we have revised the conclusion section to articulate the dual contribution of our work to both academic knowledge and practical application. We now emphasize how this study:

• advances the conceptualization of digital platforms as socio-technical ecosystems and proposes a structured analytical framework to support future research; and
• offers actionable insights and strategic directions for policymakers and practitioners to address systemic barriers and guide the implementation of inclusive and user-centered digital platforms across sectors.

 

Revised text – 5. Conclusions

In terms of academic knowledge, this study contributes a novel cross-sectoral and cross-scalar synthesis of digital platforms in the built environment, introducing a multi-dimensional analytical framework that integrates technical, organizational, and governance perspectives. It expands the conceptualization of platforms beyond technological tools, framing them as socio-technical ecosystems capable of orchestrating data, processes, and stakeholder interactions across domains and lifecycle phases. This provides a foundation for future theoretical development, empirical research, and comparative evaluation of platform maturity and integration.

In terms of practical contribution, the findings serve as a reference for public administrations, platform developers, infrastructure managers, and policy-makers by identifying shared structural barriers (e.g., fragmented data, limited interoperability, siloed processes) and outlining targeted strategies for overcoming them. These include scalable architectures, inclusive governance models, and interoperable data frameworks, which can guide the design, implementation, and regulation of next-generation digital platforms. Furthermore, the review offers actionable insights to support the deployment of digital platforms that are human-centered, lifecycle-aware, and context-adaptable—particularly in urban development, infrastructure maintenance, and energy management.