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Decision-making is a fundamental cognitive process that involves evaluating alternatives and selecting among them. This process can range from simple choices, such as deciding what to wear, to complex decisions, like choosing a major in college or a career path. The complexity of the decision often dictates the approach we use, which can be broadly categorized into two types: automatic and controlled decision-making.
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Revolutionizing construction: A cutting-edge decision-making model for artificial intelligence implementation in

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Summary

Artificial intelligence (AI) adoption in construction is significantly driven by technology, advancement, and knowledge. These factors contribute to improved project completion, sustainability, and safety in the building industry.

Keywords:
Artificial intelligenceBenefits assessmentConstruction digitalizationDigital transformationHealth and safetyProject completionSustainable construction

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Area of Science:

  • Construction Management
  • Artificial Intelligence Applications
  • Technology Adoption

Background:

  • The construction industry faces challenges in adopting new technologies.
  • Artificial Intelligence (AI) offers potential solutions for efficiency and safety.
  • Understanding AI adoption drivers is crucial for successful implementation.

Purpose of the Study:

  • To identify key drivers influencing AI adoption in the construction sector.
  • To evaluate the impact of these drivers on AI implementation.
  • To provide insights for stakeholders on leveraging AI effectively.

Main Methods:

  • Comprehensive literature review to identify AI adoption factors.
  • Survey of construction industry stakeholders for data collection.
  • Exploratory Factor Analysis and Partial Least Squares Structural Equation Modeling (PLS-SEM).

Main Results:

  • Technology, advancement, and knowledge emerged as primary AI adoption drivers.
  • These factors directly explain approximately 15% of the observed effects of AI adoption.
  • AI deployment shows potential for enhancing construction health and safety and project timelines.

Conclusions:

  • Technology, advancement, and knowledge are significant drivers for AI adoption in construction.
  • AI integration can lead to substantial improvements in project outcomes and safety.
  • Tailored strategies are recommended for policymakers and stakeholders to maximize AI benefits.