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Evaluation of Factors Affecting the Adoption of Smart Buildings Using the Technology Acceptance Model

Journal: International Journal of Advanced Networking and Applications (Vol.7, No. 06)

Publication Date:

Authors : ; ;

Page : 2936-2943

Keywords : Information technology; Perceived ease of use; Perceived usefulness; smart building; TAM; technology acceptance;

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Abstract

Objective: This study aimed to find a solution to the acceptance of smart buildings in Iran using the technology acceptance model (TAM). The main research question is the significance of this model relationships, as well as the anticipated adoption of smart buildings in Iran using variables included in the model. Methods: This descriptive study, is based on survey data collection methods and the way of analyzing data is correlational and casual study. Measurement tool was designed based on the standardized questionnaire presented by Davis. The reliability coefficient was 0.88. Statistical population is unlimited and included citizens of Iran in 1395. The sample consisted of 388 individuals. Given the infinity of society and Cochran formula, 384 individual is sufficient for this research. This study is a random sampling one that was done in the period of 30 days. Findings and conclusions: The results revealed that all relationships in the model are significant. And among the variables of the model, perceived usefulness, the attitude toward using, and features of smart buildings had the most intense relationship in acceptance this technology. Using regression equations, each of the dependent variables in the model, is predictable by the independent variables. Innovation of research: The intensity of relationship between variables in technology acceptance model and impact of each variable in explaining the criterion factor was analyzed. Research limitations: Many people tend not to complete the questionnaire and some ones answer questions unrealistic. Despite all the explanations to justify the respondents, still there are possible directions in responses. Practical consequences: Using regression equations obtained in this study, we can predict the criterion variables in the model of technology adoption.

Last modified: 2016-07-15 16:04:31