Factors Affecting the Adoption of Internet of Things Technologies in Smart Business Based on the TAM

Document Type : Research Paper

Authors

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, Karaj Branch, Islamic Azad University, Alborz, Iran

4 Associate Professor, Department of Industrial and Mechanical Engineering, Qazvin Branch, Islamic Azad University, Qazvin, Iran

Abstract

Objective: Given that the Internet of Things has been widely studied and considered and is increasing, so it is necessary to examine the factors affecting the application and acceptance of this technology as much as possible. Accordingly, the purpose of this study is to explain the relationships between the dimensions and indicators of the IoT adoption model in smart business.
Method: From the point of view of purpose, this research is a descriptive research, from the philosophical point of view, it is based on the compositional approach, and in fact, it will use the chemo-facial approach. According to the combined approach of the research, first, criteria and sub-criteria were extracted based on interviews and a paradigm model was presented using the grounded theory method. Then, in the quantitative part, the validation of the presented paradigm model was performed based on the data collected based on a questionnaire. To evaluate the qualitative validity of the research, face validity and qualitative validity of the content and to evaluate the quantitative reliability, Cronbach's alpha method was used. In order to analyze the data and achieve the main goals, SPSS and Smart PLS soft wares were used.
Findings: The results of 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 regulations. The final acceptance model with a GOF index of 0.491 indicates the high overall quality of the model and applicability in the study population. All the variables identified in the model, including infrastructure, management, technology, education and finally cultural and social, in the acceptance of electronic services, have an important and significant role and the relationship between endogenous and exogenous variables of the model has been significant. Priorities for the effects of the technology acceptance model variables were government rules and regulations (0.552), financial dimension (0.504) and socio-cultural dimension (0.419), respectively.
Conclusion: According to the research results, creating the necessary environment to facilitate the entry and launch of new technologies in the country is essential.           

Keywords


Al-Fuqaha A., M. Guizani, M. Mohammadi, M. Aledhari, M. Ayyash. (2015). Internet of Things: A Survey on Enabling Technologies, Protocols and Applications, DOI: 10.1109/COMST.2015.2444095, IEEE Communications Surveys & Tutorials
Anas A. Al-Bakri Marios I. Katsioloudes. (2015). The factors affecting e-commerce adoption by Jordanian SMEs", Management Research Review, 38(7), 726-749
Atzori Luigi, Antonio Iera, Giacomo Morabito. (2010). The Internet of Things: A Survey,” Computer Networks, 54, 2787-2805.
Choshin. Mahdi y Ghaffari. Ali.(2017).An investigation of the impact of effective factors on the success ofe-commerce in small- and medium-sized companies, Computers in Human Behavior, 66, 67–74
Conti,M., Dehghantanha, A., Franke, K.,Watson, S. (2018). Internet of Things security and forensics: Challenges and Opportunities. Future Generation Computer Systems, 78(3): 544–546.
Danila.raudah,Abdullah.akilah.(2014). User satisfacation on  e-govermant services: an integarated model, procedia-scocial and behavior sciences 164(2014), 575-582
Gao, L., Bai, X. (2014). A unified perspective on the factors influencing consumer acceptance of Internet of Things technology. Asia Pac. J. Market. Logist. 26 (2), 211–231.
Fleisch, E., Weinberger, M., & Wortmann, F. (2015). Business models and the internet of things. In Interoperability and Open-Source Solutions for the Internet of Things(pp. 6–10). Springer.
Henseler, J., Dijkstra, T.K., Sarstedt, M., Ringle, C.M., Diamantopoulos, A., Straub, D.W., ... Calantone, R.J., 2014. Common beliefs and reality about PLS: comments on Rönkkö and Evermann (2013). Organ. Res. Methods 17 (2), 182–209.
Karahanna, E., Straub, D.W., Chervany, N.L., 1999. Information technology adoption across time: a cross-sectional comparison of pre-adoption and post-adoption beliefs. MIS Q. 183-213.
Karahoca Adem, Dilek Karahoca, Merve Aksöz, (2017) "Examining intention to adopt to internet of things in healthcare technology products", Kybernetes, https://doi.org/10.1108/K-02-2017-0045
Lee, J., Rao, H., (2015), " Perceived risks, counter-beliefs, and intentions to use anti-/counter-terrorism websites: An exploratory study of government-citizens online interactions in a turbulent environment", Decision Support Systems, (43), 1431-1449.
Luthra, S., Garg, D., Mangla, S.K., Berwal, Y. (2018). Analyzing challenges to Internet of Things (IoT) adoption and diffusion: An Indian context. Procedia Computer Science, 125: 733-739.
Pundir Y., N. Sharma, Y. Singh. (2010). Internet of Things (IoT): Challenges and Future Directions, International Journal of Advanced Research in Computer and Communication Engineering. 5(3), 1-20.
Sfar, A.R., Natalizio, E., Challal, Y., Chtourou, Z. (2018). A Roadmap for Security Challenges in Internet of Things. Digital Communications and Networks, 4(2): 2118-137. 31.
Sha, K., Wei, W., Yang, T.A., Wang, Z., Shi, W. (2018). On Security Challenges and Open Issues in Internet of Things. Future Generation Computer Systems, 83: 326-337.
Tan,M., Teo, T.S. (2000). Factors influencing the adoption of internet banking. J. AIS 1. 1(5), 1-10.
Vermesan, O. and Friess, P., (2013). Internet of Things: Converging Technologies for Smart Environments and Integrated Ecosystem. Aalborg, Denmark: River Publishers
N. S. Vipin, M. Abdul Nizar, (2015). Efficient On-line SPAM Filtering for Encrypted Message,”IEEE International Conference on Signal Processing, Informatics, Communication andEnergy System, IEEE, pp. 1-5.
Kardaras, D. K., Karakostas, B., Barbounaki, S. G., & Kaperonis, S. (2019). A Framework for Analyzing the Impact of Data Analytics and the Internet of Things on Digital Marketing. In Techno-Social Systems for Modern Economical and Governmental Infrastructures(pp. 211–240). IGI Global.
Kim, S., &Kim, S. (2016). A multi-criteria approach toward discovering killer IoT application in Korea. Technological Forecasting and Social Change, 102, 143–155.
Mohammadzadeh,A. K., Ghafoori, S., Mohammadian, A., Mohammadkazemi, R., Mahbanooei, B., & Ghasemi, R. (2018). A Fuzzy Analytic Network Process (FANP) approach for prioritizing internet of things challenges in Iran. Technology in Society, 53, 124–134.