| Autor: |
Linda Cusumano, Ricardo Saraiva, Rasmus Rempling, Robert Jockwer, Nilla Olsson, Mats Granath |
| Rok vydání: |
2022 |
| Zdroj: |
IABSE Symposium, Prague 2022: Challenges for Existing and Oncoming Structures. |
| ISSN: |
2221-3783 |
| Popis: |
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. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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