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dc.contributor.authorReyes Veras, Paola
dc.contributor.authorRenukappa, Suresh
dc.contributor.authorSuresh, Subashini
dc.contributor.authorAlgahtani, Khaled
dc.contributor.editorDawood, Nashwanen
dc.contributor.editorRahimian, Farzaden
dc.contributor.editorSheikhkhoshkar, Moslemen
dc.date.accessioned2021-12-15T09:28:37Z
dc.date.available2021-12-15T09:28:37Z
dc.date.issued2022-01-01
dc.identifier.citationReyes-Veras, P., Renukappa, S., Suresh, S. and Alghatani, K. (2022) Strategies for implementing big data concept in the construction industry of the Dominican Republic. in Industry 4.0 Applications for Full Lifecycle Integration of Buildings: Proceedings of the 21st International Conference on Construction Applications of Virtual Reality, Nashwan Dawood, Farzad Rahimian & Moslem Sheikhkhoshkar (eds.), pp.210-219. Middlesbrough: Teeside University Press.en
dc.identifier.isbn9780992716134
dc.identifier.urihttp://hdl.handle.net/2436/624487
dc.descriptionThis is an accepted manuscript of an article published in the Proceedings of the 21st International Conference on Construction Applications of Virtual Reality, 8th-10th December 2021, Teeside University, Middlesborough. The accepted version of the publication may differ from the final published version.en
dc.description.abstractThe Big Data (BD) boom has increased exponentially in recent years, reaching even the most traditional industries. In construction, this technology has come to be considered as the possible solution to the challenges that the industry has been facing in recent years, with some authors even naming this technology as the future of the construction industry. However, despite this reception, studies that explain in detail the factors that favour the adoption of Big Data are scarce and non-existent in some cases. Understanding these influencing factors is a key element in ensuring future technology adoption across the industry. Such is the case of the strategies which make up an action plan for companies that seek to adopt Big Data in the future. Therefore, the objective of this study is to identify the strategies that would allow the adoption of Big Data in the construction industry of the Dominican Republic. To identify these strategies, qualitative research was carried out due to the scarcity of sources that address the subject. In the data collection process, a total of 21 interviews were conducted representing companies with undoubted presence in the construction market of the Dominican Republic. As a result of the data analysis, four main strategies were identified which include the promotion of standardization and popularization of the BD concept and its benefits, investment in training and development of staff skills, support for the development of current technologies as well as the inclusion of technology in the education curriculum of present and future professionals. These strategies identified in the study will help companies that plan to implement Big Data in the future to carry out an action plan and identify the steps to follow to achieve a successful adoption of the technology. Also, this study contributes to the body of knowledge of research professionals who focus on the elements for Big Data adoption as well as possible future professionals in the area.en
dc.formatapplication/pdfen
dc.language.isoenen
dc.publisherTeeside Universityen
dc.relation.urlhttps://convr2021.com/en
dc.sourceIndustry 4.0 Applications for Full Lifecycle Integration of Buildings: Proceedings of the 21st International Conference on Construction Applications of Virtual Realityen
dc.subjectbig dataen
dc.subjectconstructionen
dc.subjectDominican Republicen
dc.subjectstrategiesen
dc.subjecttechnologyen
dc.titleStrategies for implementing big data concept in the construction industry of the Dominican Republicen
dc.typeConference contributionen
dc.date.updated2021-12-11T14:07:13Z
dc.conference.namehe 21st International Conference on Construction Applications of Virtual Reality (CONVR2021)
dc.conference.locationTeeside University, Middlesbrough, UK
pubs.finish-date2021-12-10
pubs.start-date2021-12-08
dc.date.accepted2021-12-01
rioxxterms.funderUniversity of Wolverhamptonen
rioxxterms.identifier.projectUOW15122021SRen
rioxxterms.versionAMen
rioxxterms.licenseref.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/en
rioxxterms.licenseref.startdate2022-01-01en
refterms.dateFCD2021-12-15T09:28:09Z
refterms.versionFCDAM
refterms.dateFOA2022-01-01T00:00:00Z


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