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.