Investigating the Factors Affecting the Readiness Level of IoT Technology Acceptance (Case Study: Financial Activists, Stock Exchange, and Financial Institutions)

Subject Areas : Software Engineering and Information Systems

Amir Abbas Farahmand ¹ , Reza Radfar ² , Alireza Poorebrahimi ³ , Mani Sharifi ⁴

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

Received: 2021-01-07 Accepted : 2021-12-28 Published : 2021-05-01

Keywords: Technology Acceptance, IoT, Ecommerce,

Abstract :

IoT, a state-of-the-art technology, faces many challenges in its growth and development. One of the main concerns is the potential threats posed by the spread of such technology in the world. The widespread adoption and spread of such a technology can threaten us much more seriously than the Internet currently available. The challenges we face in adopting such technology will include both the social and the technical aspects. Technical limitations include security considerations, privacy, as well as the resource, energy, and capacity issues for such a large amount of data and processing. Besides, socially, cultural infrastructure must first be provided for the diffusion of such technologies among the community. This study aimed to investigate the factors affecting the readiness level of the acceptance of IoT technologies. The relationships are examined as six main categories identified, namely the social aspect, the cultural aspect, the human aspect, the technological aspect, the financial aspect, the management aspect, government laws, and regulations. The opinions of senior ICT executives nationwide were collected. The statistical population of this study consists of experts and users of the financial sector, stock exchange, and financial institutions. Since the statistical population is infinite, 384 randomly available individuals are selected. SMART.PLS was used to validate the model and test the relationships between variables. The results indicate the impact of the identified categories on IoT adoption readiness.