Mr. Harshal Kadam, Mr. Mayur Prajapati, Mr. Amit Yadav, Prof. Sonali Karthik
ConQuote Connect is a smart digital platform designed to solve common problems in the construction industry, such as unclear project details, payment delays, miscommunication and the difficulty of finding trustworthy contractors. It creates a single, streamlined space where builders can post their construction projects and contractors can submit structured and easy to compare quotations. A key part of the system is the use of Building Information Modeling (BIM), which allows builders to upload 3D models of their projects. These models help both parties clearly understand the scope of work and visually track progress through milestones, such as marking when the foundation, floors, or roofing are completed. To make payments more secure, transparent, and fair, ConQuote Connect uses blockchain-powered smart contracts. These contracts safely hold project funds and only release payments when a builder confirms that a milestone has been completed through the BIM model. The platform also includes AI tools that assist in comparing contractor quotes and helping builders make faster, more informed and data backed decisions. When a contractor successfully completes a project, they receive a digital certificate in the form of an NFT, which becomes part of their verifiable reputation and track record on the platform. Both builders and contractors have their own personalized dashboards to manage tasks, communicate updates, track progress and approve or verify completed work. By combining BIM, blockchain and AI in one easy to use system, ConQuote Connect offers a modern, transparent and trustworthy way to manage construction projects reducing disputes, saving time and improving industry collaboration.
Background: Despite the growing adoption of hybrid contract models in construction, energy, and agricultural procurement, there remains a significant gap in understanding how lump-sum and unit-price contracts differentially allocate risk across sectors and country contexts. This study addresses this gap by examining risk mitigation strategies through document analysis and thematic synthesis. Objective: The aim of this study was to identify key risk allocation strategies, contractual mechanisms, and the effectiveness of hybrid models in managing uncertainty across developed and developing country contexts. Methods: A qualitative approach based on thematic analysis and cross-case comparison was applied, drawing on 48 peer-reviewed sources published between 2015 and 2025, alongside relevant sector documents and procurement reports. Results: The analysis identified that hybrid contracts reduced cost overrun variability by incorporating performance-based incentives aligned with Expected Utility Theory and Principal-Agent Theory, while developing economies such as Indonesia and Bangladesh exhibited distinct risk profiles requiring adaptive contract mechanisms. However, significant gaps remain, particularly regarding the empirical validation of blockchain-enabled contract enforcement and AI-driven risk prediction, as well as the underrepresentation of developing economy contexts in existing research. Conclusion: The findings carry both scientific and practical implications. Theoretically, this study advances an integrative multi-theory framework combining Expected Utility Theory, Game Theory, and Principal-Agent Theory to analyse contract risk across diverse contexts. Practically, the results provide evidence-based guidance for procurement professionals and policymakers in selecting and designing contract structures that balance cost certainty with adaptive flexibility.
The construction industry faces several difficulties in warehouse management along with construction industry&s;s supply chain that is characterized by complex, multi-tiered interactions involving material suppliers, transporters, contractors, and on-site project managers. Traditional management systems suffer from delayed information exchange, lack of transparency, and vulnerability to fraud or errors, often leading to cost overruns and schedule delays. The purpose of the current paper is to suggest an Artificial Intelligence of Things (AIoT) and blockchain-based supply chain management model to be used in the construction industry. AIoT involves the use of IoT devices or RFID tags, GPS trackers, and environmental sensors along with AI algorithmic methods to conduct predictive analytics, anomaly detection, and automated decision-making in the edge or the cloud. Blockchain technology offers the benefit of immutable and transparent records that cannot be altered and is tamper resistant, which facilitates trust among the distributed stakeholders and automates the workflows of the contract through the use of smart contracts. The architecture that is proposed has three layers: 1 AIoT real-time data acquisition sensing and analytics, 2 Secure data storage blockchain ledger and smart contract execution, and 3 A stakeholder application dashboard. In order to test our framework, we conducted a simulation of a scenario with prefabricated steel parts as supply. We determined the effectiveness of the system in tracking items, recording events as swiftly as possible, the security of the process and the efficiency of the whole process. The findings were also staggering: the accuracy of the tracking increased by 92 percent, the reporting is 58 percent quicker, and the prevention of fraud is much more robust than the traditional ERP systems. Such results demonstrate that the convergence of the AIoT and blockchain technologies can contribute to the solution of current issues in the supply chain in construction, which will result in the improved and more data-driven project management. Second, we will experiment with this approach through real life projects and how it could be used with Building Information Modelling (BIM) platforms.
The construction industry is undergoing a significant transformation with the adoption of decentralized models, which leverage distributed decision-making, collaborative networks, and advanced technologies such as blockchain, digital twins, and artificial intelligence (AI). These innovations promise enhanced transparency, efficiency, and stakeholder engagement in high- rise building projects. However, decentralization introduces unique risks—spanning technical, social, economic, legal, and environmental domains—that challenge traditional risk management frameworks. This research systematically identifies and categorizes these risks, emphasizing their implications for decentralized high-rise construction. Key technical risks include design clashes and quality inconsistencies due to fragmented workflows, while social risks encompass labor disputes and community opposition. Economic risks arise from budget fragmentation and supply chain volatility, legal risks stem from contractual ambiguities and regulatory non- compliance, and environmental risks involve waste mismanagement and increased carbon footprints. To address these challenges, the study proposes a comprehensive risk management framework integrating emerging technologies. For instance, Building Information Modeling (BIM) and digital twins enable real-time clash detection and quality assurance, blockchain ensures transparent and automated contract execution, and AI-driven analytics predict safety hazards and cost overruns. The framework is validated through a case study of Skyline Towers in Dubai, where decentralized strategies reduced design errors by 45% and payment delays by 80%. The research employs a mixed-methods approach, combining a systematic literature review with empirical analysis of real-world projects. Findings highlight the critical role of stakeholder alignment, hybrid governance models, and sustainable practices in mitigating risks. The study concludes with actionable recommendations for policymakers and industry practitioners, advocating for standardized digital protocols, adaptive risk governance, and proactive environmental controls. By bridging the gap between technological innovation and risk management, this research contributes a forward-looking framework to enhance resilience and efficiency in decentralized high-rise construction, ensuring sustainable urban development in an increasingly complex industry landscape.
The ethical and social implications of smart contracts (SC) in the construction industry are examined, with a particular focus on their interaction with the Joint Contracts Tribunal (JCT) suite of standard forms. Using a qualitative, narrative literature review, this article compares blockchain-enabled automation with established contractual mechanisms, concentrating on payment processes, governance and the role of professional judgement. Although the findings suggest that SC can enhance transparency and payment integrity, especially in a building information modelling enabled environment, they also introduce rigidity, reduce the scope for discretionary decision making and raise concerns regarding fairness, inclusivity and legal certainty. A hybrid model is proposed in which SC complement, rather than replace, JCT mechanisms, preserving relational trust and interpretative flexibility while delivering auditable efficiency where automation adds genuine value. The review draws on peer-reviewed academic literature, industry reports and material relevant to contemporary UK construction practice. Academic databases (Scopus, ScienceDirect, Taylor & Francis Online and the ICE Virtual library) were searched using targeted keywords. Sources were selected based on relevance, academic rigour and recency, with priority given to publications from the past decade.
This study investigates the rapid centralization of the Ethereum builder market under the Proposer-Builder Separation (PBS) architecture. We argue that existing research, by focusing predominantly on influential order flows, lacks a comprehensive evaluation of order flow behavioral patterns and economic purposes. To address this gap, we analyze Ethereum transactions from September 2023 to August 2025 to characterize Exclusive Order Flows (EOFs) and non-atomic Maximal Extractable Value (MEV) -- the missing components corresponding to these behavioral and economic dimensions, respectively. We introduce a novel exclusivity metric based on Kullback-Leibler divergence and employ supervised learning to identify 75 EOFs and 322 non-atomic MEV flows, which account for 71\% and 23\% of trading-related builder revenue. A longitudinal analysis of builder strategies across these dimensions delineates the market's evolution into four distinct eras, revealing that while EOFs were instrumental in establishing early dominance, incumbents have since decoupled market share from immediate EOF dependency by leveraging entrenched network effects. Ultimately, we conclude that builder centralization is an emergent property of the PBS framework itself, as the architecture systematically violates the fundamental prerequisites of a competitive market.
Malintha Fernando, Nimasha Dilukshi Hulathdoowage, B. A. K. S. Perera
Construction projects are complex and demand advanced digital technologies to enhance automation, transparency, and efficiency. As a result, tools like enterprise resource planning (ERP), smart contracts, and electronic tendering (e-tendering) are being adopted. However, these technologies often operate separately rather than as a unified system. Although there are a few cases where ERP is integrated with smart contracts, integration with e-tendering remains largely absent. Therefore, this study creates a unified framework combining these three technologies to improve automation, transparency, and efficiency in the construction industry. Thus, a scoping review was conducted, selecting 50 publications from 2014 to 2024 for in-depth analysis. A content analysis was performed to identify the limitations of ERP systems, and key functions and features of ERP systems, e-tendering, and smart contracts. The proposed unified framework focuses on how these technologies can function synergistically to improve different areas in construction projects. The study identified 12 areas that can be streamlined. After the scoping review, five expert interviews were conducted to validate the framework. Experts critically commented on the applicability, benefits, limitations and strategies, in line with the framework. The study highlights that, by centralizing key functions into a single integrated system, the unified framework streamlines operations, enhances transparency, and enables real-time, evidence-based decision-making across complex construction environments. Furthermore, the study highlights that by addressing the inefficiencies of fragmented data management and nonintegrated systems, the proposed framework offers a comprehensive solution to persistent industry challenges like cost overruns, delays, and lack of transparency. The study further critically analyzes how the limitations identified concerning ERP systems are addressed through the unified system. Based on the findings and the unified framework, future research areas are proposed.
Die Arbeit untersucht den Einsatz von Smart Contracts in Infrastrukturprojekten zur Reduzierung von Kollaborationsproblemen. Auf Basis einer Netzwerkanalyse von VOB-Urteilen werden Problemcluster identifiziert, mittels Prinzipal-Agent-Theorie formalisiert und mit Smart-Contract-Funktionalitäten verknüpft. Ein prototypischer Prozess wird als Smart Contract umgesetzt und evaluiert. Ergebnisse zeigen Verbesserungen in Transparenz, Dokumentation und Vertrauen, trotz technischer Herausforderungen.
The Decentralized Autonomous Organizations (DAOs) are shaping the future of the governance by moving away toward the power of the communities making calls without a central body. Nevertheless, it is becoming harder to assess the quality of the proposals as those are increasing and the number of demands is increasing as well. Manual reviews need more man power, lack consistency and are prone to bias because each one can produce varying levels of clarity, possibility, and fit within organizational objectives. In this paper, we introduce the proposal evaluation system based on AI, which uses transformer-based Natural Language Processing (NLP) models and Explainable AI (XAI) to automate and interpret the assessments of DAO proposals. The system scores in three dimensions, including impact, feasibility, and goal alignment in a clear and continuous way, with the justifications in human-readable formats. Our solution promotes both the fairness and scalability of decision-making in DAOs by decreasing voter fatigue and achieving a more straightforward workflow in governing the activities. Trained and validated on real-world DAO proposal datasets, the model delivers high performance regarding accuracy, explainability, and user trust. The contribution of this project is to guide the community to the intelligent systems of governance in Web3 through how to increase the transparency and trust in them using automated decision-support tools leaving the decentralized nature of DAOs intact.
Henry Gunawan, Chandra Lukita, Tri Angreni, Muhammad Syarif Hartawan · 7 authors
The persistent financing gap in sustainable infrastructure remains a major barrier to achieving the United Nations Sustainable Development Goals (SDGs), as traditional financing models often suffer from limited transparency, high entry barriers, and restricted investor access. This study explores the integration of Blockchain technology and tokenization as innovative mechanisms to address these challenges by enhancing transparency, inclusivity, and investment accessibility. Utilizing a mixed-methods approach, data were collected through interviews with financial experts, Blockchain developers, and project managers, alongside surveys involving 100 respondents from the finance and infrastructure sectors across multiple regions. The analysis combined thematic coding using NVivo and statistical assessment of Likert scale responses to evaluate transparency, trust, accessibility, and perceived security risks. Results show that Blockchain significantly improves transparency (mean score 4.2) and trust (4.0), while tokenization facilitates fractional ownership and broadens access to infrastructure investment (4.1). Although moderate concerns about security remain (score 3.3), the strong interest in tokenized investment, especially among developers and investors, reflects a growing readiness for adoption. The novelty of this research lies in its comprehensive examination of the combined application of Blockchain and tokenization for sustainable infrastructure financing a synergy that is rarely addressed in existing literature. By proposing a decentralized, secure, and inclusive financing model, this study offers valuable insights for policymakers, practitioners, and fintech stakeholders seeking to close the infrastructure financing gap and promote long-term sustainability.
Abstract The construction industry is among the few industries that contribute to the growth and development of the economy; its size gives a representative potential in contributing to economic development. However, the nature of the construction industry in Egypt is plagued by disputes, which often arise from contractual issues, communication breakdowns, and project management challenges during various stages of the project. Furthermore, construction contracts are always viewed as complex and dense paperwork that makes it difficult to extract necessary information, inhibiting smooth operation. This can be solved by implementing smart contracts. A smart contract can include blockchain technology that executes agreed-upon terms automatically and autonomously. This data-driven mechanism automatically issues payments at the end of each clause, reducing the potential for disputes. The aim of this research is to Investigate the potential of smart contracts in reducing disputes in the construction projects. This study will be performed by adopting a qualitative approach through collecting and analysing data from various literature sources, as books, journals, and existing research, to construct a comprehensive understanding from a holistic point of view focusing on relevant keywords as smart contracts and disputes during various stages in construction projects to identify the relationship between them and present it in a relationship matrix. Second, analysis of case studies to investigate the effectiveness of smart contracts and validate the identified relationship and view its potential in construction projects.
The Engineering, Procurement, and Construction (EPC) industry faces significant financial management challenges due to the complexity of project financing, milestone-based payments, and multi-stakeholder collaboration. Traditional on-premise ERP financial systems are often inefficient, leading to delays in financial reporting, security vulnerabilities, and regulatory compliance difficulties. This study explores the development of cloud-based financial solutions tailored to the EPC industry, examining the benefits, challenges, and applicability of existing models such as Software as a Service (SaaS), Platform as a Service (PaaS), and Blockchain-based decentralized finance (DeFi). A Hybrid Cloud-Based Financial Framework is proposed, integrating SaaS for accounting, PaaS for customization, and Blockchain for secure transactions. Experimental validation demonstrates that cloud adoption reduces financial processing time by 87.5%, enhances cash flow visibility, improves security, and increases regulatory compliance efficiency by 40%. This paper highlights the importance of AI-driven predictive analytics, automated compliance, and hybrid cloud models in modern EPC finance and proposes strategies for overcoming integration challenges, cybersecurity risks, and workforce adoption barriers. Future research should focus on scaling hybrid cloud solutions globally and integrating AI-powered risk assessment tools.
Contract management in construction law plays a critical role in mitigating risks, ensuring performance enforcement, and facilitating dispute resolution.The increasing complexity of construction projects, coupled with evolving regulatory frameworks, necessitates robust contract management strategies to address financial, operational, and legal risks.Poorly managed contracts often lead to cost overruns, project delays, and disputes, making it essential for stakeholders to adopt proactive measures in drafting, executing, and enforcing contractual obligations.This study examines key aspects of contract management in construction law, focusing on risk allocation, dispute resolution mechanisms, and performance enforcement strategies.Risk mitigation strategies, including well-defined contract terms, contingency planning, and insurance provisions, are explored to illustrate how parties can safeguard their interests.The research also highlights the effectiveness of alternative dispute resolution (ADR) methods, such as mediation, arbitration, and adjudication, in reducing litigation costs and project disruptions.Furthermore, contract enforcement mechanisms, including penalty clauses, performance bonds, and liquidated damages, are analyzed for their role in ensuring compliance and timely project completion.The study also evaluates the impact of digital transformation on contract management, particularly the use of smart contracts and blockchain technology to enhance transparency, efficiency, and dispute prevention.Through case studies and legal precedents, this research provides practical insights into how construction professionals, legal practitioners, and policymakers can optimize contract management practices.A comprehensive approach to risk management, dispute resolution, and performance enforcement is essential to maintaining legal compliance, ensuring financial stability, and improving project delivery in the dynamic construction sector.
Valentina Villa, Luca Gioberti, Marco Domaneschi, F. Necati Çatbaş
The civil engineering sector operates within a complex ecosystem of stakeholders, requiring efficient management and maintenance of structural and infrastructural assets. In this context, there is an increasing need for robust tools to track critical events (e.g., alerts, unusual behaviors) and support decision-making processes related to maintenance and interventions. At the same time, ensuring secure and prompt payments is essential for timely and effective responses. This paper investigated the potential of smart contracts, integrated with blockchain technology, to automate and optimize asset management and maintenance processes. The proposed framework examines how these technologies can enhance operational efficiency, security, and event traceability, providing a structured approach for both routine operations and emergency interventions. Although smart contracts have been widely applied in the construction phase of infrastructure projects, their use in long-term asset management remains largely unexplored. As a conceptual study, this work does not present a quantitative analysis but instead lays the groundwork for future research and real-world applications of blockchain-based smart contracts in infrastructure management and safety procedures.
Viraaji Mothukuri, Reza M. Parizi, James L. Massa, Abbas Yazdinejad
Rampant scams plague decentralized finance (DeFi) projects, creating a DeFi credibility problem that limits the impact of DeFi advances in the availability and variety of financial services. This paper presents a novel solution to the DeFi credibility problem by developing an AI multi-model that generates TrustScore ratings for DeFi projects and clear explanations of the scores. We generate DeFi-project TrustScore by aggregating multiple factors that provide DeFi investors with a holistic view of DeFi project trustworthiness. To rate a DeFi project with a TrustS core, we combine the output of four AI pipelines that analyze smart contract code vulnerabilities, suspicious transactions, anomalous price changes to smart contracts, and social media scam sentiment. Applying four factors exponentially improves the trust-score accuracy over the single-factor approaches done historically. Two of the factors, anomalous price change, and social media sentiment, have not been used before to detect DeFi fraud. Furthermore, we enhanced the most critical factor, smart-contract code vulnerability detection, with the latest Large Language Models (LLMs). Our overall system is a multi-model composed of a TrustS core Explainer LLM that aggregates individual pipeline results, a fine-tuned GPT model to audit smart contract code, the Prophet forecasting tool, FinBERT tailored for financial Natural Language Processing (NLP), and XGBoost for classification. The proposed approach identifies a significant proportion of known fraudulent DeFi projects and generates an accurate and explained TrustScore. Thus, we address the DeFi credibility problem so that investors can make reliable decisions about DeFi projects.
Purpose This study aims to identify and analyse critical success factors (CSFs) for the successful implementation of distributed ledger technology (DLT) in the Nigerian construction industry. Design/methodology/approach This study adopts a quantitative approach that uses snowball sampling techniques to identify professionals participating in the study. A structured questionnaire was used to collect data virtually, using Google Forms, resulting in 217 valid responses. The collected data were subjected to rigorous statistical analysis (descriptive and inferential) to identify and prioritise the CSFs and evaluate the participants’ awareness and knowledge of DLT. Findings This study revealed 24 key CSFs that are pivotal in ensuring the effective implementation and adoption of DLT in the Nigerian construction industry. Furthermore, the research highlights a moderate level of awareness, but significantly low knowledge of DLT among industry professionals. Practical implications The findings of this study will benefit professionals, practitioners and policymakers in the Nigerian construction industry by providing insights into the potential of DLT to improve construction operations. Originality/value This study contributes to the literature by identifying the CSFs for implementing DLT in the construction industry and shedding light on the current level of awareness and knowledge within the Nigerian context. The findings offer valuable insights for policymakers, industry practitioners and researchers, providing a solid foundation for informed decision-making and developing effective strategies to enhance DLT adoption in the construction sector.
John Aliu, Ayodeji Emmanuel Oke, Lydia Uyi Ehiosun
Purpose This study aims to evaluate the drivers influencing the integration of distributed ledger technologies (DLTs) in the Nigerian construction industry to provide a comprehensive analysis of the factors that shape the adoption and utilization of this transformative technology within the sector. Design/methodology/approach This objective was achieved through a quantitative research approach, utilizing a structured questionnaire to systematically gather data from various stakeholders in the Nigerian construction sector. Data obtained were analyzed using descriptive statistics, alongside inferential statistical techniques like the Kruskal-Wallis H-test, the Shapiro-Wilk test and exploratory factor analysis. Findings The most highly ranked drivers for DLT within the construction industry are security and fraud resistance, traceability and transparency, government support, compliance and reporting and trust building. Further analysis unveiled five distinct factors of application areas, namely: technological and operational drivers, economic and financial drivers, regulatory and government drivers, collaborative and stakeholder drivers and environmental and sustainability drivers. Practical implications The practical implications emphasize the need for construction industry stakeholders to focus on security, transparency and trust-building when considering DLT adoption. This study also offers valuable insights for investors and technology providers seeking opportunities in the Nigerian construction sector. Originality/value This study sheds light on the factors most critical for DLT adoption in the Nigerian construction sector. Unlike previous research, this study pinpoints security and fraud resistance, along with traceability and transparency, as the most influential drivers. This highlights the Nigerian construction industry’s particular vulnerability to fraud and its emphasis on clear audit trails.
Contract management, which directly impacts the success of architecture, engineering, and construction (AEC) projects, has been affected by the application of Industry 4.0 (I4.0) technologies. This study extensively reviewed the I4.0 application in contract management using a hybrid approach of bibliometrics and a systematic literature review to capture this trend. Scopus and Web of Science were selected as the papers’ databases, and 203 papers were filtered from a total of 2,524 papers from 2011 until the end of 2022. The bibliometric analysis explored and analyzed large volumes of data in six areas: publication year, journal, country, author, methodology, and keyword. The systematic literature review discovered eight key topics regarding I4.0 application and implication areas in the contract management of the AEC industry, including tender/bid phase, cost estimation, BIM contractual requirements, smart contracts, analyzing and monitoring contracts, claim and dispute management, information management and traceability, intellectual property rights; and regarding each topic, relevant I4.0 technologies were identified. Finally, benefits, challenges, and gaps of the literature were identified based on systematic analysis results. This paper contributes to the body of knowledge by identifying and synthesizing the current status of the research subject, and providing the researchers with the study’s theoretical and practical contributions.
Hossein Naderi, Mohammad Hossein Heydari, Alireza Shojaei
The architecture, engineering, and construction (AEC) industry is widely known for being fragmented. In this situation, blockchain technology has been introduced as a promising solution to bring trust and transparency to the industry. As blockchain technology continues to evolve, it has embraced new capabilities and features, including Fungible-Tokens (FTs) and Non-Fungible Tokens (NFTs), which have recently drawn significant attention in various industries. Tokenization can be seen as a next-generation solution to address challenges in the AEC. However, the application of tokenization for the AEC industry has remained undeveloped. To address this gap, this study provides an overview of tokenization, followed by an investigation of its applications in the AEC industry using a literature review method. By illustrating a clear outlook of the potential advantages and challenges, the study helps to set realistic expectations over the potential improvement that tokenization can bring. This can also serve as a fundamental source for further investigation by researchers and practitioners.
Several construction projects globally suffer due to time and cost overruns. These could be due to reasons attributable to the contracting parties or unforeseen external circumstances. Disputes often arise between the parties regarding which side caused the delay and the compensation terms for the delay. Thus, this study is motivated to explore a digital contractual solution for contract administrators and project managers using blockchain technology-enabled smart contracts. In this regard, the research attempts to develop smart contract clauses that (1) carefully allocate liability and delay accountability at various construction stages; (2) automatically compute the delay compensations and notify the responsible party; and (3) determine the resultant extensions of time and cost, with cost variations. The goal is to develop computable legal contracts for industry and academia focusing on the extension of time, delay compensation, and variation, which can be applied to all projects worldwide, regardless of the complexity or scale.
Infrastructure, which encompasses highways, rails, ports, terminals, energy, and telecommunication systems, is critical to sustaining productivity expansion, living standards, and stability. These projects widely rely on different skills and sources of capital. There is also widespread consensus that infrastructure complexities are often difficult to predict. Managing and controlling all these inputs for balancing different project sides play critical roles in this context. These processes can, however, be automated, and their duration and costs are reduced with emerging technologies, specifically blockchain technology and digital twins for infrastructure projects. Using decentralization in the construction industry can be advantageous for applications that make subjective and transparent decisions on complex and large infrastructure projects. There are currently no systems that can process large amounts of data efficiently while simultaneously taking into account user information to facilitate the development of such technologies. This research focuses on identifying data-driven techniques for automating data extraction from decentralized autonomous organizations (DAO), using volunteers (voters) for assistance.