Energy consumption of retrofitting existing public buildings in Malaysia under BIM approach: pilot study

Building information modeling (BIM) platforms to enhance design and construction processes have been rising recently, with BIM-based tools such as Autodesk Revit’s Architecture. The importance of BIM can be mainly seen in reducing energy consumption by at least 30%, leading to a huge cut in carbon dioxide, and saving the environment. BIM helps engineers and contractors to use less material for better benefits for stakeholders, including organizations, governmental offices, and businesses. This study investigates the reliability and validity of a constructed questionnaire to pre-determine the applications relevant to a questionnaire to be used in a large-scale study. The literature has highlighted the connection between BIM and energy-driven retrofits. However, the application of BIM to the retrofitting of existing structures confronts obstacles, which may be attributable to the multidisciplinary character of information sharing, the timeliness of communication, and the large number of technology components required to provide an optimal exchange. A pilot study was conducted, identifying the sample size of 30 random respondents out of 167 samples. SPSS was used for estimating the percentages of the demographic attributes for the respondents, the face validity, internal-consistency validity, the validation of all contracts, and Pearson’s correlation. The results show that engineers constitute 46%, project managers (20%), contractors (17%), and the rest (approximately 17%) are divided among other professionals. The validity of internal consistency ranges from 0.791 to 0.912, which reflects perfect consistency. The internal consistency of each part was recorded at 0.942 (energy), 0.957 (strategies), and 0.979 (framework). The validation for the energy part ranges from 0.610 to 0.912; for strategies (0.451 to 0.884,) and for the framework (0.681 to 0.884). Pearson’s correlation for all 17 questions showed a minimum value of 0.464, while the maximum value was 0.890. The results show that all questionnaire elements were successfully validated with a Cronbach alpha factor mainly higher than 0.6—the threshold accepted by most researchers. Hence, the work on the broader scale of testing and analysis could proceed.

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