Explaining the Relationships between the Dimensions and Characteristics of the Internet of Things Technology Acceptance Model in Smart Business

Subject Areas : business management

AmirAbbas Farahmand ¹ , Reza Radfar ² , Alireza Pourabrahimi ³ , Mani Sharifi ⁴

1 - Department of Technology Management, UAE Branch, Islamic Azad University, Dubai, United Arab Emirates
2 - Department of Industrial Management, Science and Research Branch, Islamic Azad University, Tehran, Iran
3 - Department of Industrial Management, Karaj Branch, Islamic Azad University, Alborz, Iran
4 - Department of Industrial and Mechanical Engineering, Qazvin Branch, Islamic Azad University, Qazvin, Iran.

Received: 2020-09-15 Accepted : 2020-10-20 Published : 2020-12-21

Keywords: Internet of Things, technology acceptance, Technology Innovation,

Abstract :

The purpose of this study is to explain the relationships between the dimensions and indicators of the IoT technology adoption model in smart business. This research is a descriptive research based on the purpose and based on a combined approach. According to the combined approach of the research, first, criteria and sub-criteria were extracted based on interviews and using grounded theory method. Then, in the quantitative part, the validation of the presented paradigm model was performed based on the collected data based on a questionnaire. To evaluate the qualitative validity, face validity and qualitative content validity and to evaluate the quantitative reliability, Cronbach's alpha method was used. In order to analyze the data, SPSS software and structural equation modeling method and smart.PLS software are used. The results of pivotal coding showed that 63 primary codes were identified in six categories: social dimension, cultural dimension, human dimension, technological dimension, financial dimension, management dimension and government laws and regulations. Also, the value of the numerical GOF index was equal to 0.491, which indicates the high overall quality of the model. All variables identified in the model were significant and the relationships between endogenous and exogenous variables of the model were also significant.