Key factors influencing the decision to adopt industrialised building systems technology in the Malaysian construction industry: an inter-project perspective

Zakaria, Sharifah Akmam Syed; Gajendran, Thayaparan; Skitmore, Martin; Brewer, Graham

doi:10.1080/17452007.2017.1298512

Cited by 19 publications

(10 citation statements)

References 45 publications

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“…Although scholars mentioned above have studied the influencing factors of PC technology adoption and their interrelationships, the psychological and behavioral factors reflecting practitioners’ adoption behavior have been ignored (Akmam et al. , 2018a; Akmam et al. , 2018b).…”

Section: Introductionmentioning

confidence: 99%

Proposing a multifaceted model for adopting prefabricated construction technology in the construction industry

Yuan

et al. 2021

ECAM

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Purpose Although prefabricated construction (PC) technology has attracted considerable attention worldwide because of its significant role in the global fight against COVID-19, market-driven adoption is still limited. The mechanisms for PC technology adoption have yet to be defined, which inhibits its diffusion in the construction market. This study aims to reveal the intrinsic motivation and action mechanism for PC technology adoption. Design/methodology/approach Drawing on the technology acceptance model (TAM), the study integrates characteristics from the diffusion of innovation theory to propose a multifaceted model for explaining practitioners’ PC technology adoption behavior from technology, organization and environment contexts. The proposed theoretical model was empirically examined via a survey of 234 professionals in mainland China using the partial least squares-structural equation modeling technique. Findings The outcomes indicated that relative advantage, corporate social responsibility and market demand are significantly positively related to practitioners’ perceived usefulness from PC technology. Regulatory support and trading partner support have noticeable positive effects on practitioners’ perceived ease of use from PC technology. Perceived ease of use is found to positively influence perceived usefulness, and both of them have a positive influence on the attitude toward adopting PC technology. Attitude is further confirmed as an important predictor of adoption intention, which would lead to actual PC technology adoption behavior. Originality/value To the best of the authors’ knowledge, this paper is the first attempt to explore industry perceptions toward PC technology adoption, providing valuable guidance for the effective diffusion of PC technology and laying a reliable foundation for research on other construction innovation adoption in post-COVID-19.

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Section: Introductionmentioning

confidence: 99%

Proposing a multifaceted model for adopting prefabricated construction technology in the construction industry

Yuan

et al. 2021

ECAM

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“…A defect list is a special document that allows to calculate and take into account in advance the costs that must be spent on repairs in order to restore the original appearance and characteristics of material values [11,12]. The defect list is made after a visual inspection (technical inspection) of the structural elements of apartment buildings, it must reflect all types of work that must be performed to restore the building's operability.…”

Section: Resultsmentioning

confidence: 99%

Improving programs for capital repairs of apartment buildings and their role in the sustainability of the region

et al. 2021

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The current state of the housing stock of the Russian Federation necessitates overhaul of the common property of apartment buildings. The basis of the state program (concept) for overhaul of apartment buildings is formed by regional programs and short-term plans for overhaul of the common property of apartment buildings. Therefore, the purpose of this article was to study the implementation of the regional program for the overhaul of apartment buildings and develop directions for its improvement. The subject of the research is the regional program for the overhaul of the common property of apartment buildings in the Volgograd region, which is a document that guarantees the overhaul within the time frame established in it. The analysis of the implementation of the program according to the data of the Fund For Overhaul of the Volgograd region is presented. The problems of the implementation of the regional program are identified and directions for their elimination are outlined, which will allow achieving the target indicators of the regional overhaul program.

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“…This is together with power supply, professional bodies support and project documentation with one source each. Influencing Factors Source 3D detailing [13], [15], [20], [28] Clash Detection [13], [20], [28] Collaboration/communication [15] , [19], [22], [24], [25], [27], [28] Comparability [14], [17], [18], [23], [30] Complexity [14], [17], [18] Cost of adopting AI [14], [15], [16], [18], [19], [20], [21], [22], [23], [24], [25], [26], [28], [29], [31] Costing and estimating [13], [28] Define project roles and responsibilities [13], [28] Documentation [13], [28] Facilities Management [13], [28] Fragmented industry [15] Goal Setting [13],…”

Section: Factors Influencing the Adoption Of Ai In The Construction I...mentioning

confidence: 99%

A Systematic Literature Review of Influencing Factors and Strategies of Artificial Intelligence Adoption in the Construction Industry

Tjebane

Musonda

Okoro

2022

IOP Conf. Ser.: Mater. Sci. Eng.

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The construction industry has seen an increase in Artificial Intelligence(AI) in recent years, a paradigm shift in many industries. It puts under pressure for technological advancement. Therefore, AI is under great attention in the construction industry as a new strategic paver. This paper adopts a systematic literature review (SLR) approach and followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines to observe and understand the influencing factors and strategies for AI adoption. The SLR for AI-related research carried out between 2010 and 2020. Data was collected from ASCE Journals, Emerald Insight, Elsevier ScienceDirect, Engineering Village, Google Scholar, ICE virtual library, IOPscience, IEEE Xplore, ScienceDirect, Scopus, SpringerLink and Taylor & Francis. The paper identifies and classifies the new developments in AI research, making its implementation and adoption a reality in the construction industry. This review has the potential for construction industry stakeholders, especially those in developing countries, to utilise the accumulated evidence from selected systematic reviews to enable the usage of AI for infrastructure development

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Key factors influencing the decision to adopt industrialised building systems technology in the Malaysian construction industry: an inter-project perspective

Cited by 19 publications

References 45 publications

Proposing a multifaceted model for adopting prefabricated construction technology in the construction industry

Proposing a multifaceted model for adopting prefabricated construction technology in the construction industry

Improving programs for capital repairs of apartment buildings and their role in the sustainability of the region

A Systematic Literature Review of Influencing Factors and Strategies of Artificial Intelligence Adoption in the Construction Industry

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