Data

Identifying Key Selection Criteria for Smart Building Technologies in The United Arab Emirates Prisons

Queensland University of Technology
Aldhaheri, Mohammed
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ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rfr_id=info%3Asid%2FANDS&rft_id=info:doi10.25912/RDF_1660707109466&rft.title=Identifying Key Selection Criteria for Smart Building Technologies in The United Arab Emirates Prisons&rft.identifier=10.25912/RDF_1660707109466&rft.publisher=Queensland University of Technology&rft.description=Initially, semi-structured interviews were conducted involving 14 experts from prison and construction sectors for their opinions on smart building technologies that were currently being used in UAE prisons and the potential criteria for their selection (unpublished data). After conducting a thematic analysis of the interviewees’ responses and literature review, 15 smart building technologies and 14 criteria on how to select these technologies were listed in the questionnaire. The questionnaire contains three sections. The first section included questions on the respondents’ personal and socio-economic information such as age, gender, employment status, education level, type of organization, and the number of years with the organization. The next section was designed to rank the smart building technologies being used in prison facilities in UAE based on the Likert scale ranging from 1 to 5 (where 1 represented not important at all, and 5 represented extremely important) regarding their importance. The last section explored the opinion of respondents on the relative importance of different criteria for the selection of smart building technologies in the UAE prisons based. Responses to questions in each section were measured on a Likert scale ranging from 1–5 (where 1 represented not important at all, and 5 represented extremely important) &rft.creator=Aldhaheri, Mohammed &rft.date=2022&rft.edition=1&rft.relation=https://eprints.qut.edu.au/234429/&rft.coverage=56.439500,26.076500 51.472300,26.076500 51.472300,22.631514 56.439500,22.631514 56.439500,26.076500&rft_rights=© Mohammed Abdulla Mohammed Mesfer Aldhaheri, 2022.&rft_rights=Creative Commons Attribution 3.0 http://creativecommons.org/licenses/by/4.0/&rft_subject=Principal component analysis&rft_subject=Building&rft_subject=BUILT ENVIRONMENT AND DESIGN&rft_subject=Prisons&rft_subject=UAE&rft_subject=Green building&rft_subject=Selection criteria&rft_subject=Smart building technology&rft_subject=Civil engineering&rft_subject=ENGINEERING&rft_subject=Other built environment and design&rft_subject=HVAC&rft.type=dataset&rft.language=English Access the data

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Creative Commons Attribution 3.0
http://creativecommons.org/licenses/by/4.0/

© Mohammed Abdulla Mohammed Mesfer Aldhaheri, 2022.

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Contact Information

Postal Address:
Mr Mohammed Aldhaheri

m.aldhaheri@hdr.qut.edu.au

Full description

Initially, semi-structured interviews were conducted involving 14 experts from prison and construction sectors for their opinions on smart building technologies that were currently being used in UAE prisons and the potential criteria for their selection (unpublished data). After conducting a thematic analysis of the interviewees’ responses and literature review, 15 smart building technologies and 14 criteria on how to select these technologies were listed in the questionnaire.

The questionnaire contains three sections. The first section included questions on the respondents’ personal and socio-economic information such as age, gender, employment status, education level, type of organization, and the number of years with the organization. The next section was designed to rank the smart building technologies being used in prison facilities in UAE based on the Likert scale ranging from 1 to 5 (where 1 represented not important at all, and 5 represented extremely important) regarding their importance. The last section explored the opinion of respondents on the relative importance of different criteria for the selection of smart building technologies in the UAE prisons based.

Responses to questions in each section were measured on a Likert scale ranging from 1–5 (where 1 represented not important at all, and 5 represented extremely important)

Data time period: 20 09 2021 to 06 11 2021

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56.439500,26.076500 51.472300,26.076500 51.472300,22.631514 56.439500,22.631514 56.439500,26.076500

53.9559,24.354007

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