Academic Journal
Unlocking determinants of smart construction: an integrated model of UTAUT2, TTF, and perceived risk for IoT acceptance in AEC industry.
| Title: | Unlocking determinants of smart construction: an integrated model of UTAUT2, TTF, and perceived risk for IoT acceptance in AEC industry. |
|---|---|
| Authors: | Wang, Kaiyang, Guo, Fangyu, Zhang, Cheng, Hao, Jianli, Wang, Zhitao |
| Source: | Engineering Construction & Architectural Management (09699988); 2025, Vol. 32 Issue 8, p5394-5428, 35p |
| Subject Terms: | Internet of things, Construction industry, Construction project management, Innovation adoption, Technology Acceptance Model, Risk perception |
| Geographic Terms: | China |
| Abstract: | Purpose: The Internet of Things (IoT) offers substantial potential for improving efficiency and effectiveness in various applications, notably within the domain of smart construction. Despite its growing adoption within the Architecture, Engineering, and Construction (AEC) industry, its utilization remains limited. Despite efforts made by policymakers, the shift from traditional construction practices to smart construction poses significant challenges. Consequently, this study aims to explore, compare, and prioritize the determinants that impact the acceptance of the IoT among construction practitioners. Design/methodology/approach: Based on the integrated model of Unified Theory of Acceptance and Use of Technology (UTAUT2), Task-Technology Fit (TTF), and perceived risk. A cross-sectional survey was administered to 309 construction practitioners in China, and the collected data were analyzed using structural equation modeling (SEM) to test the proposed hypotheses. Findings: The findings indicate that TTF, performance expectancy, effort expectancy, hedonic motivation, facilitating conditions, and perceived risk exert significant influence on construction practitioners' intention to adopt IoT. Conversely, social influence and habit exhibit no significant impact. Notably, the results unveil the moderating influence of gender on key relationships – specifically, performance expectancy, hedonic motivation, and habit – in relation to the behavioral intention to adopt IoT among construction practitioners. In general, the model explains 71% of the variance in the behavioral intention to adopt IoT, indicating that the independent constructs influenced 71% of practitioners' intentions to use IoT. Practical implications: These findings provide both theoretical support and empirical evidence, offering valuable insights for stakeholders aiming to gain a deeper understanding of the critical factors influencing practitioners' intention to adopt IoT. This knowledge equips them to formulate programs and strategies for promoting effective IoT implementation within the AEC field. Originality/value: This study contributes to the existing literature by affirming antecedents and uncovering moderators in IoT adoption. It enhances the existing theoretical frameworks by integrating UTAUT2, TTF, and perceived risk, thereby making a substantial contribution to the advancement of technology adoption research in the AEC sector. [ABSTRACT FROM AUTHOR] |
| Copyright of Engineering Construction & Architectural Management (09699988) is the property of Emerald Publishing Limited 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: | Complementary Index |
| FullText | Links: – Type: other Text: Availability: 0 CustomLinks: – Url: https://www.emerald.com/insight/content/doi/10.1108/ECAM-05-2023-0482 Name: Emerald Insight (All Content) (s7799221) Category: fullText Text: View full text at Emerald MouseOverText: View full text at Emerald |
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| Items | – Name: Title Label: Title Group: Ti Data: Unlocking determinants of smart construction: an integrated model of UTAUT2, TTF, and perceived risk for IoT acceptance in AEC industry. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Wang%2C+Kaiyang%22">Wang, Kaiyang</searchLink><br /><searchLink fieldCode="AR" term="%22Guo%2C+Fangyu%22">Guo, Fangyu</searchLink><br /><searchLink fieldCode="AR" term="%22Zhang%2C+Cheng%22">Zhang, Cheng</searchLink><br /><searchLink fieldCode="AR" term="%22Hao%2C+Jianli%22">Hao, Jianli</searchLink><br /><searchLink fieldCode="AR" term="%22Wang%2C+Zhitao%22">Wang, Zhitao</searchLink> – Name: TitleSource Label: Source Group: Src Data: Engineering Construction & Architectural Management (09699988); 2025, Vol. 32 Issue 8, p5394-5428, 35p – Name: Subject Label: Subject Terms Group: Su Data: <searchLink fieldCode="DE" term="%22Internet+of+things%22">Internet of things</searchLink><br /><searchLink fieldCode="DE" term="%22Construction+industry%22">Construction industry</searchLink><br /><searchLink fieldCode="DE" term="%22Construction+project+management%22">Construction project management</searchLink><br /><searchLink fieldCode="DE" term="%22Innovation+adoption%22">Innovation adoption</searchLink><br /><searchLink fieldCode="DE" term="%22Technology+Acceptance+Model%22">Technology Acceptance Model</searchLink><br /><searchLink fieldCode="DE" term="%22Risk+perception%22">Risk perception</searchLink> – Name: SubjectGeographic Label: Geographic Terms Group: Su Data: <searchLink fieldCode="DE" term="%22China%22">China</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Purpose: The Internet of Things (IoT) offers substantial potential for improving efficiency and effectiveness in various applications, notably within the domain of smart construction. Despite its growing adoption within the Architecture, Engineering, and Construction (AEC) industry, its utilization remains limited. Despite efforts made by policymakers, the shift from traditional construction practices to smart construction poses significant challenges. Consequently, this study aims to explore, compare, and prioritize the determinants that impact the acceptance of the IoT among construction practitioners. Design/methodology/approach: Based on the integrated model of Unified Theory of Acceptance and Use of Technology (UTAUT2), Task-Technology Fit (TTF), and perceived risk. A cross-sectional survey was administered to 309 construction practitioners in China, and the collected data were analyzed using structural equation modeling (SEM) to test the proposed hypotheses. Findings: The findings indicate that TTF, performance expectancy, effort expectancy, hedonic motivation, facilitating conditions, and perceived risk exert significant influence on construction practitioners' intention to adopt IoT. Conversely, social influence and habit exhibit no significant impact. Notably, the results unveil the moderating influence of gender on key relationships – specifically, performance expectancy, hedonic motivation, and habit – in relation to the behavioral intention to adopt IoT among construction practitioners. In general, the model explains 71% of the variance in the behavioral intention to adopt IoT, indicating that the independent constructs influenced 71% of practitioners' intentions to use IoT. Practical implications: These findings provide both theoretical support and empirical evidence, offering valuable insights for stakeholders aiming to gain a deeper understanding of the critical factors influencing practitioners' intention to adopt IoT. This knowledge equips them to formulate programs and strategies for promoting effective IoT implementation within the AEC field. Originality/value: This study contributes to the existing literature by affirming antecedents and uncovering moderators in IoT adoption. It enhances the existing theoretical frameworks by integrating UTAUT2, TTF, and perceived risk, thereby making a substantial contribution to the advancement of technology adoption research in the AEC sector. [ABSTRACT FROM AUTHOR] – Name: Abstract Label: Group: Ab Data: <i>Copyright of Engineering Construction & Architectural Management (09699988) is the property of Emerald Publishing Limited 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.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1108/ECAM-05-2023-0482 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 35 StartPage: 5394 Subjects: – SubjectFull: China Type: general – SubjectFull: Internet of things Type: general – SubjectFull: Construction industry Type: general – SubjectFull: Construction project management Type: general – SubjectFull: Innovation adoption Type: general – SubjectFull: Technology Acceptance Model Type: general – SubjectFull: Risk perception Type: general Titles: – TitleFull: Unlocking determinants of smart construction: an integrated model of UTAUT2, TTF, and perceived risk for IoT acceptance in AEC industry. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Wang, Kaiyang – PersonEntity: Name: NameFull: Guo, Fangyu – PersonEntity: Name: NameFull: Zhang, Cheng – PersonEntity: Name: NameFull: Hao, Jianli – PersonEntity: Name: NameFull: Wang, Zhitao IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 08 Text: 2025 Type: published Y: 2025 Identifiers: – Type: issn-print Value: 09699988 Numbering: – Type: volume Value: 32 – Type: issue Value: 8 Titles: – TitleFull: Engineering Construction & Architectural Management (09699988) Type: main |
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