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Identifying Key Selection Criteria for Smart Building Technologies in the United Arab Emirates Prisons
The selection of an appropriate smart building technology has been a challenge for stakeholders, because no specific selection criteria are currently available. This study aimed to identify the potential selection criteria for the selection of smart building technologies for prison buildings in the United Arab Emirates. A questionnaire survey was conducted to evaluate the relative importance of smart building technologies and the specific selection criteria. 238 experts from the public and the private sector with rich experience in the construction and prison industry participated in the survey. The data obtained were analyzed for descriptive statistics and the Mann-Whitney U test was conducted to compare the responses of the government and private sector respondents. Cronbach’s coefficient was estimated using reliability analysis. Finally, exploratory factor analysis was performed by Principal Axis Factoring (PAF) to extract the contributing factors and was further improved by varimax rotation using SPSS. To evaluate the appropriateness of the factor extraction, the Kaiser-Mayer-Olkin (KMO) measure of sampling accuracy and Barlett’s test of sphericity were conducted. The results demonstrated that most participants thought that the safety and security, anti-hacking capability, high working efficiency, and durability of the new smart building technology were very important. 14 listed selection criteria were extracted into three factors by factor analysis explaining 50.585% total variation. Regarding smart building technologies, fire protection was mostly voted by the participants followed by video surveillance and heat, ventilation, and air-conditioning system (HVAC). This study is a novel research study identifying the key selection criteria for the selection of important smart building technologies and would be helpful for a broad audience.
Identifying Key Selection Criteria for Smart Building Technologies in the United Arab Emirates Prisons
The selection of an appropriate smart building technology has been a challenge for stakeholders, because no specific selection criteria are currently available. This study aimed to identify the potential selection criteria for the selection of smart building technologies for prison buildings in the United Arab Emirates. A questionnaire survey was conducted to evaluate the relative importance of smart building technologies and the specific selection criteria. 238 experts from the public and the private sector with rich experience in the construction and prison industry participated in the survey. The data obtained were analyzed for descriptive statistics and the Mann-Whitney U test was conducted to compare the responses of the government and private sector respondents. Cronbach’s coefficient was estimated using reliability analysis. Finally, exploratory factor analysis was performed by Principal Axis Factoring (PAF) to extract the contributing factors and was further improved by varimax rotation using SPSS. To evaluate the appropriateness of the factor extraction, the Kaiser-Mayer-Olkin (KMO) measure of sampling accuracy and Barlett’s test of sphericity were conducted. The results demonstrated that most participants thought that the safety and security, anti-hacking capability, high working efficiency, and durability of the new smart building technology were very important. 14 listed selection criteria were extracted into three factors by factor analysis explaining 50.585% total variation. Regarding smart building technologies, fire protection was mostly voted by the participants followed by video surveillance and heat, ventilation, and air-conditioning system (HVAC). This study is a novel research study identifying the key selection criteria for the selection of important smart building technologies and would be helpful for a broad audience.
Identifying Key Selection Criteria for Smart Building Technologies in the United Arab Emirates Prisons
Mohammed Abdulla Mohammed Mesfer Aldhaheri (Autor:in) / Bo Xia (Autor:in) / Madhav Nepal (Autor:in)
2022
Aufsatz (Zeitschrift)
Elektronische Ressource
Unbekannt
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