{"title":"Strategic determinants of big data analytics in the AEC sector: a multi-perspective framework","authors":"Sushil S. Chaurasia, Surabhi Verma","doi":"10.5130/ajceb.v20i4.6649","DOIUrl":null,"url":null,"abstract":"With constant flow of large data sets generated by different organisations, big data analytics promises to be a revolutionary game changer for Architecture, Engineering and Construction (AEC) industry. Despite the potential of Big Data, there has been little research conducted thus far to understand the Big Data phenomenon, specifically in the AEC industry. The objective of this research therefore is to understand the contributing factors for adopting big data in AEC firms. The investigation combined the perceived strategic value of BDA with the TOE framework (technology, organization, and environment), to develop and test a holistic model on big data adoption. A set of hypotheses derived from the extant literature was tested on data from structured surveys of about 365 firms, categorised as construction service firms (engineering and architecture) and construction firms (firms engaged in managing construction projects). The results indicated that the inhibitors and facilitators of BDA adoption are different in the construction services (architecture and engineering) and construction firms. For effective adoption of BDA solutions, the findings will guide the business managers to have realistic expectations of BDA integration challenges in AEC sector.","PeriodicalId":51729,"journal":{"name":"Construction Economics and Building","volume":null,"pages":null},"PeriodicalIF":1.8000,"publicationDate":"2020-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"12","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Construction Economics and Building","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5130/ajceb.v20i4.6649","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"MANAGEMENT","Score":null,"Total":0}
引用次数: 12
Abstract
With constant flow of large data sets generated by different organisations, big data analytics promises to be a revolutionary game changer for Architecture, Engineering and Construction (AEC) industry. Despite the potential of Big Data, there has been little research conducted thus far to understand the Big Data phenomenon, specifically in the AEC industry. The objective of this research therefore is to understand the contributing factors for adopting big data in AEC firms. The investigation combined the perceived strategic value of BDA with the TOE framework (technology, organization, and environment), to develop and test a holistic model on big data adoption. A set of hypotheses derived from the extant literature was tested on data from structured surveys of about 365 firms, categorised as construction service firms (engineering and architecture) and construction firms (firms engaged in managing construction projects). The results indicated that the inhibitors and facilitators of BDA adoption are different in the construction services (architecture and engineering) and construction firms. For effective adoption of BDA solutions, the findings will guide the business managers to have realistic expectations of BDA integration challenges in AEC sector.
期刊介绍:
Construction Economics and Building (formerly known as the Australasian Journal of Construction Economics and Building [AJCEB]) is a peer reviewed, open access publication for original research into all aspects of the economics and management of building and construction, quantity surveying and property management as well as construction and property education. It is free for authors, readers and libraries.