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- Cusumano, Linda, 1981, et al.
(författare)
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Intelligent building contract tendering - potential and exploration
- 2022
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Ingår i: IABSE Symposium Prague, 2022: Challenges for Existing and Oncoming Structures - Report. - Zurich, Switzerland : International Association for Bridge and Structural Engineering (IABSE). ; , s. 1902-1909
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Konferensbidrag (refereegranskat)abstract
- Project tendering is the construction business “Tightrope-walking.” It is a time-limited balance act where technical and business specialists find the best technical proposal at the right price. The purpose and aim of this study were to explore artificial intelligence (AI) in the tender work and to identify challenges and possibilities with data-driven decision-making. An AI work support tool was adopted and used to extract and process client requirements. The tool and digital-work procedure were presented and discussed with tender specialists from a large contractor in a workshop. A two-step survey was performed in connection to the workshop, investigating the potential users' insights and attitudes for implementation. The main result and conclusion were that AI and digitalization could support tendering; however, successfully generating business value will require higher levels of digitalization, well-structured databases, and access to historical project data.
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| 2. |
- Cusumano, Linda, 1981, et al.
(författare)
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Natural language processing as work support in project tendering
- 2022
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Ingår i: Current Perspectives and New Directions in Mechanics, Modelling and Design of Structural Systems. - London : CRC Press. - 9781003348443 ; , s. 1583-1588
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Konferensbidrag (refereegranskat)abstract
- When producing a tender, contractors manually analyze client requirements contained within many different text documents. The combination of requirements lead to crucial design decisions and every decision is related to costs and risks. This study explores the possibility of making the client requirement analysis in design-bid contracts automated to reduce the risk of conceptual design mistakes. The research approach chosen includes developing a work support tool based on natural language processing and analyzing its usefulness through a combination of surveys and a workshop for tendering specialist. The results show that applying digitalized working methods and using artificial intelligence in the tender phase can enable data-informed decision making and generate benchmarking and risk management opportunities. The study contributes to insights regarding automation and digitization possibilities in tender projects and how artificial intelligence tools can be designed for supporting data-driven decisions.
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| 3. |
- Saraiva, Ricardo Alencar, 1984, et al.
(författare)
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Data-informed Building Procurement: A contractor exploration on embodied-carbon targets through Buildability and AI
- 2020
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Rapport (övrigt vetenskapligt/konstnärligt)abstract
- The construction industry has been object of criticism due to poor productivity rates, lethargic development, and irresponsible use of natural resources. It has been pointed out that segment peculiarities, such as fragmentated, project-based, and one-of-a-kind, stand as barriers for change, compromising the urgent agenda for sustainable development. Regardless of that, recent climate agreements have input unprecedent pressure on the industry with challenging decarbonization goals. Motivated by that, this thesis explores a Swedish contractor perspective on how embodied carbon targets can be addressed in the building sector through better-informed tender briefings and buildability. For that, the study follows an abductive reasoning and exploratory mixed method approach, where a broad qualitative study informs a quantitative survey. Findings reveal a clear need for better-informed decisions on tender briefings. It exposes that data in early stages is reduced and inaccurate due to undefinitions and undeveloped assessments methods that tackles limited criteria. Additionally, it is argued that information flows are difficulted by outdated practices and the fragmented reality of conventional buildings product development, in which several stakeholders co-create, negotiate, and transfer asset ownership along the way. These actors, as investigations support, usually hold opposing interests driven by short-term economic gains. Consequently, neither environmental nor societal criteria appear to be effectively informed and spoken for during early stages of decision-making, regardless the considerably high share of emissions and relevant social issues that the sector comprise. Further, it is exposed that decarbonization roadmaps proposing investments in greener materials solutions, although longed-for, might escalate building costs considerably, possibly leading to economic and social issues linked to housing prices. Therefore, it is argued the plan may turn unfeasible, especially in face of the broad implementation which is vital to attend set targets. Accordingly, seeking to compensate such economic impacts, the thesis explores opportunities to reduce waste through the promotion of Buildability principles in the earliest stages of concept design, when it can still be addressed. As such, obstacles and inflexibilities created via client requirements and tender procedures are analyzed to propose changes. However, findings show the public procurement act challenges contractors ability to influence on more buildable solutions in public tenders. And Partnering strategies, which are often seen as a remedy for that, has been reducing due to public clients fear of volatile budgets - a viewpoint which contractors oppose since Partnering is a mean for many ends. Consequently, the thesis concludes that contractors are dependent on client’s leading role and can hardly count with better informed briefings and easier to build requirements. Nonetheless, it is suggested that contractors could develop a strategy based on data-informed ‘side-offers’, as a way around the limitations framed by the public procurement dynamics. Accordingly, a roadmap for AI-applications is advocated for contractors to reduce lead-time and resources spent for the elaboration of these side-offers. For that, it recommends the use of cutting-edge technologies to process an integrated multi-criteria design, that is informed by data collected both from the product and the market (client). Ultimately, the thesis supports that through automation, contractors can gain access to the right information at the right time, and thus promote a more valuable and sustainable alternative for public clients to procure.
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