View in EDS

Safety professionals' acceptance of artificial intelligence in the construction industry: an extended technology acceptance model.

Saved in:
Bibliographic Details
Title: Safety professionals' acceptance of artificial intelligence in the construction industry: an extended technology acceptance model.
Authors: Chellappa, Vigneshkumar1 (AUTHOR) vkumar.chellappa@polyu.edu.hk
Source: Safety Science. Jul2026, Vol. 199, pN.PAG-N.PAG. 1p.
Subjects: Artificial intelligence, Construction industry safety, Risk perception, Trust, Technology Acceptance Model, Privacy, Social influence
Geographic Terms: India
Abstract: • Trust, perceived risk, and social influence are significant predictors of safety professionals' intention to adopt AI for construction safety. • Higher levels of technology anxiety negatively affect perceptions of AI's usefulness and ease of use, hindering adoption. • The non-significance of privacy concerns suggests that professionals may prioritize operational safety over data privacy. Artificial Intelligence (AI) offers promising solutions to enhance safety performance in the construction industry, including detecting unsafe conditions, predicting safety risks, and identifying unsafe worker behavior. Despite these benefits, AI adoption remains limited in developing regions like India due to barriers including low digital literacy, risk aversion, and strong social influences. Additionally, growing concerns about data privacy and security complicate technology acceptance, making it crucial to understand these factors to prevent user resistance and underutilization of safety-enhancing technologies. This study examines the key factors influencing AI acceptance among safety professionals in India, focusing on trust, perceived risk, social influence, privacy concerns, and technology anxiety, and using an extended Technology Acceptance Model. The acceptance of AI was analyzed using Structural Equation Modeling. The results indicate that trust, perceived risk, and social influence significantly influence behavioral intention to adopt AI, whereas technology anxiety negatively affects perceived usefulness and ease of use. Notably, the unexpected lack of significance of privacy concerns suggests a potential "safety-privacy tradeoff," where professionals prioritize operational safety over data privacy. These findings underscore the importance of building trust, managing risk perceptions, and addressing technology anxiety to foster AI adoption and improve safety in the Indian construction sector. [ABSTRACT FROM AUTHOR]
Copyright of Safety Science is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
FullText Text:
  Availability: 0
Header DbId: egs
DbLabel: Engineering Source
An: 192618715
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: Safety professionals' acceptance of artificial intelligence in the construction industry: an extended technology acceptance model.
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Chellappa%2C+Vigneshkumar%22">Chellappa, Vigneshkumar</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> vkumar.chellappa@polyu.edu.hk</i>
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="JN" term="%22Safety+Science%22">Safety Science</searchLink>. Jul2026, Vol. 199, pN.PAG-N.PAG. 1p.
– Name: Subject
  Label: Subjects
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Artificial+intelligence%22">Artificial intelligence</searchLink><br /><searchLink fieldCode="DE" term="%22Construction+industry+safety%22">Construction industry safety</searchLink><br /><searchLink fieldCode="DE" term="%22Risk+perception%22">Risk perception</searchLink><br /><searchLink fieldCode="DE" term="%22Trust%22">Trust</searchLink><br /><searchLink fieldCode="DE" term="%22Technology+Acceptance+Model%22">Technology Acceptance Model</searchLink><br /><searchLink fieldCode="DE" term="%22Privacy%22">Privacy</searchLink><br /><searchLink fieldCode="DE" term="%22Social+influence%22">Social influence</searchLink>
– Name: SubjectGeographic
  Label: Geographic Terms
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22India%22">India</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: • Trust, perceived risk, and social influence are significant predictors of safety professionals' intention to adopt AI for construction safety. • Higher levels of technology anxiety negatively affect perceptions of AI's usefulness and ease of use, hindering adoption. • The non-significance of privacy concerns suggests that professionals may prioritize operational safety over data privacy. Artificial Intelligence (AI) offers promising solutions to enhance safety performance in the construction industry, including detecting unsafe conditions, predicting safety risks, and identifying unsafe worker behavior. Despite these benefits, AI adoption remains limited in developing regions like India due to barriers including low digital literacy, risk aversion, and strong social influences. Additionally, growing concerns about data privacy and security complicate technology acceptance, making it crucial to understand these factors to prevent user resistance and underutilization of safety-enhancing technologies. This study examines the key factors influencing AI acceptance among safety professionals in India, focusing on trust, perceived risk, social influence, privacy concerns, and technology anxiety, and using an extended Technology Acceptance Model. The acceptance of AI was analyzed using Structural Equation Modeling. The results indicate that trust, perceived risk, and social influence significantly influence behavioral intention to adopt AI, whereas technology anxiety negatively affects perceived usefulness and ease of use. Notably, the unexpected lack of significance of privacy concerns suggests a potential "safety-privacy tradeoff," where professionals prioritize operational safety over data privacy. These findings underscore the importance of building trust, managing risk perceptions, and addressing technology anxiety to foster AI adoption and improve safety in the Indian construction sector. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of Safety Science is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=egs&AN=192618715
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1016/j.ssci.2026.107194
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 1
        StartPage: N.PAG
    Subjects:
      – SubjectFull: Artificial intelligence
        Type: general
      – SubjectFull: Construction industry safety
        Type: general
      – SubjectFull: Risk perception
        Type: general
      – SubjectFull: Trust
        Type: general
      – SubjectFull: Technology Acceptance Model
        Type: general
      – SubjectFull: Privacy
        Type: general
      – SubjectFull: Social influence
        Type: general
      – SubjectFull: India
        Type: general
    Titles:
      – TitleFull: Safety professionals' acceptance of artificial intelligence in the construction industry: an extended technology acceptance model.
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Chellappa, Vigneshkumar
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 01
              M: 07
              Text: Jul2026
              Type: published
              Y: 2026
          Identifiers:
            – Type: issn-print
              Value: 09257535
          Numbering:
            – Type: volume
              Value: 199
          Titles:
            – TitleFull: Safety Science
              Type: main
ResultId 1