2021
DOI: 10.11113/ijbes.v8.n2.667
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Relationship between Window and View Factors in the Workplace: A SEM Approach

Abstract: Office occupants’ have always preferred workplaces that have windows that connects them to the outside. Window access to the outside can influence occupants’ satisfaction with the combination of other workplace features. This study aims to identify the window and view factors relationship in the workplace, to confirm the reliability and validity of the measurement and structural model. Adopting a cross-sectional survey design, primary data from five offices in the Kogi State of Nigeria with 267 respondents wer… Show more

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Cited by 4 publications
(3 citation statements)
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“…In addition, the Principal Component Analysis (PCA) was performed on data with good Kaiser-Meyer-Olkin (KMO) values of 0.872 and a substantial Bartlett's Test of Sphericity value of 0.000. Finally, with a reliable Cronbach's alpha measure of 0.934, as presented in Table 3, the data set was suitable and acceptable for Confirmatory Factor Analysis (CFA) [25].…”
Section: Results Of Ordinal-scale Surveymentioning
confidence: 97%
“…In addition, the Principal Component Analysis (PCA) was performed on data with good Kaiser-Meyer-Olkin (KMO) values of 0.872 and a substantial Bartlett's Test of Sphericity value of 0.000. Finally, with a reliable Cronbach's alpha measure of 0.934, as presented in Table 3, the data set was suitable and acceptable for Confirmatory Factor Analysis (CFA) [25].…”
Section: Results Of Ordinal-scale Surveymentioning
confidence: 97%
“…However, as shown in Table 2, a Cronbach's alpha of 0.954 was attained in the collected data for this study, above the 0.7 thresholds appropriate for utilizing a data set for the subsequent statistical procedure. Furthermore, the Principal Component Analysis (PCA) produced a Kaiser-Meyer-Olkin (KMO) value of 0.66, above the required minimum of 0.6 measure (Achoba, Majid, & Obiefuna, 2021a;Aule, Majid, & Jusan, 2022b). Bartlett's Test of Sphericity also produced a significant 0.000 value, confirming the suitability of data for SEM.…”
Section: Discussionmentioning
confidence: 99%
“…In most cases, CFA requires generating path diagrams and covariances before loading the factors, observed or measured variables. The loaded CFA model is then run and examined to remove insignificant components with less than 0.5 standardized regression weights (Achoba et al, 2021a;Achoba, Majid, & Obiefuna, 2021b;Aule et al, 2022a). The first-order CFA is complete when model goodness-of-fit is attained, and the criteria for reliability and validity are met.…”
Section: Discussionmentioning
confidence: 99%