Document Type : Research Paper

Authors

1 Assistant professor، Artificial application development Group، Research center for ICT، Tehran، Iran Corresponding Author: e.safari@itrc.ac.ir

2 Researcher، Artificial application development Group، Research center for ICT، Tehran، Iran

Abstract

One of the most important issues in the development of artificial intelligence is the adoption of the use of artificial intelligence by the private and public sectors. In other words, in order for artificial intelligence to be used in a country or industry, it is necessary to identify and evaluate the important factors of adoption. The purpose of this study is to identify and rank the factors affecting admission in the public and private sectors in Iran. For this purpose, first, a set of models and factors affecting the adoption of technology were extracted from the literature and opinions of experts and were classified into three categories: technological, organizational and environmental factors Then, the most important factors in each category were determined through a collection questionnaire, and using nonparametric Friedman test for each category with the most important and least important criteria. In order to weight and prioritize the factors, the quantitative approach and BWM technique have been used. The statistical population of the study included 37 experts in artificial intelligence in the public sector and 45 experts in the private sector. According to the obtained results, in the public sector, 3 important factors of admission are the support of senior managers, the existence of the required infrastructure for artificial intelligence and the existence of specialized and capable forces in the field of artificial intelligence. Efficiency and productivity with the use of artificial intelligence, cost savings with the use of artificial intelligence and ease of use and learning has been easy.

Keywords

حسینی شعار، منصوره، اسفندیاری مقدم، علیرضا، زارعی، عاطفه، حسن‌زاده، محمد. (1396). بررسی عوامل مؤثر بر پذیرش فناوری وب 2، 0 در دولت الکترونیک از دیدگاه شهروندان و ارائه الگو: مورد دفاتر پیشخوان دولت در استان همدان. تعامل انسان و اطلاعات، شماره 3، 61-71. doi: 20. 1001. 1. 24237418. 1396. 4. 3. 1. 6.
حقیقی نسب، منیژه، تقوی، زهرا. (1399). پذیرش فناوری اطلاعات سبز با استفاده از چارچوب فناوری- سازمان- محیط در صنعت بانکداری. مطالعات مدیریت کسب‌وکار هوشمند، 9(34)، 63-94. doi: 10. 22054/IMS. 2020. 46042. 1596
 حیدریه، سید عبدالله، سید حسینی، سید محمد، شهابی، علی. (1392). شبیه‌سازی مدل پذیرش فناوری در ایران با رویکرد پویایی سیستم (مطالعه موردی بانکداری ایران)، فصلنامه مدیریت توسعه فناوری، 1(1)، 67 -98. doi: 10. 22104/jtdm. 2013. 4
طاهرخانی، لیلا. (1398). بررسی عوامل کلیدی مؤثر بر پذیرش سیستم‌های برنامه‌ریزی منابع سازمان ابری در شرکت‌های کوچک و متوسط-مطالعه موردی شرکت بنیان گستر اروند (سهامی خاص). رویکردهای پژوهشی نوین در مدیریت و حسابداری، 11(3)، 213-232. ‌ https://majournal. ir/index. php/ma/article/view/157
عبدالوند، ندا، طارانی، دریا. (1393). عوامل پذیرش سیستم‌های برنامه‌ریزی منابع سازمانی ابری در شرکت‌های کوچک و متوسط ایران، فصلنامه انجمن علوم مدیریت ایران، 9(34), 81-104. http://journal. iams. ir/article_186_42. html?lang=fa.
قربانی زاده، وجه الله، حسن نانگیر، سیدطه، رودساز، حبیب. (1392). فراتحلیل عوامل مؤثر بر پذیرش فناوری اطلاعات در ایران، پژوهش‌های مدیریت در ایران، 17(2)، 177-196. doi: 20. 1001. 1. 2322200. 1392. 17. 2. 8. 4
محترمی، ا.، و خدادادحسینی، س.، و الهی، ش. (1392). بررسی عوامل مؤثر بر پذیرش فناوری‌های اطلاعاتی در سازمان‌ها. مدیریت توسعه فناوری، 1(3 )، 97-122. doi: 10. 22104/JTDM. 2014. 59.
محمدی، ع. ، و امیری، ی. (1392). شناسایی و تبیین عوامل موثر بر پذیرش نوآوری فناوری اطلاعات در سازمان های دولتی با رویکرد مدل یابی معادلات ساختاری. مدیریت فناوری اطلاعات، 5(4)، 195-218.  doi: 10. 22059/jitm. 2013. 36060
ملاحسینی، علی، فروزانفر، محمدحسین. (1397). توسعه و بومی‌سازی مدل پذیرش فناوری (TAM) در شرکت‌های کوچک و متوسط. فصلنامه توسعه تکنولوژی صنعتی، 16(34)، 39-48. http://jtd. iranjournals. ir/article_33399. html.
موحدی، مسعود، احمدوند، علی‌محمد، علی یاری، نامجویان، فلورانس. (2015). نقش عوامل فردی، سازمانی و مدیریتی مؤثر بر پذیرش فناوری اطلاعات در سازمان‌های دولتی ایران. پژوهش‌های مدیریت منابع انسانی، 7(3)، 1-28.
یعقوبی، نورمحمد؛ شکوهی، جواد؛ جعفری، حمیدرضا. (1393). شناسایی و رتبه‌بندی عوامل کلیدی مؤثر بر به‌کارگیری رایانش ابری در سلامت الکترونیک، پردازش و مدیریت اطلاعات، 30(2)، 549-572. http://jipm. irandoc. ac. ir/article-۱-۲۶۳۹-fa. html.
References
Alsheibani, S., Cheung, Y., & Messom, C. (2018). Artificial Intelligence Adoption: AI-readiness at Firm-Level. In PACIS (p. 37). ‌
Alsheibani, S. A., Cheung, D., & Messom, D. (2019). Factors inhibiting the adoption of artificial intelligence at organizational-level: A preliminary investigation. https://researchmgt. monash. edu/ws/portalfiles/portal/287736273/287674072_oa. pdf.
Chatterjee, S., 2020. AI strategy of India: policy framework, adoption challenges and actions for government. Transforming Government: People, Process and Policy, 14(5), pp. 757-775. https://doi. org/ 10. 1108/TG-05-2019-0031. ‌
Concepcion, R. S., Bedruz, R. A. R., Culaba, A. B., Dadios, E. P., Pascua, A. R. (2019). The technology adoption and governance of artificial intelligence in the Philippines. In 2019 IEEE 11th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management (HNICEM) (pp. 1-10). IEEE. doi:10. 1109/HNICEM48295. 2019. 9072725.
Dasgupta, A., Wendler, S. (2019). AI Adoption Strategies. University of oxford. https://www. ctga. ox. ac. uk/files/aiadoptionstrategies- march2019pdf.
Flasiński, M. (2016). Introduction to artificial intelligence. Switzerland: Springer International Publishing. https://link. springer. com/book/ 10. 1007/978-3-319-40022-8.
Gummadidala, P. R., Karippur, N. K., Koilakuntla, M. (2020). Analysis of Factors Influencing the Adoption of Artificial Intelligence for Crime Management. In International Working Conference on Transfer and Diffusion of IT (pp. 3-9). Springer, Cham. https://link. springer. com/ chapter/10. 1007/978-3-030-64849-7_1.
Makridakis, S. (2017). The forthcoming artificial intelligence (AI) revolution: Its impact on society and firms. Futures, 90, 46–60. https://doi. org/10. 1016/j. futures. 2017. 03. 006.
Mutawa, M., & Rashid, H. (2020, August). Comprehensive Review on the Challenges that Impact Artificial Intelligence Applications in the Public Sector. In Proceedings of the International Conference on Industrial Engineering and Operations Management. Detroit, Michigan, USA. http://www. ieomsociety. org/detroit2020/ papers/451. pdf.
Noordt, C., & Misuraca, G. (2020). Exploratory insights on artificial intelligence for government in Europe. Social Science Computer Review, 0894439320980449. ‌ https://doi. org/10. 1177/0894439320980 449.
Radhakrishnan, J., & Chattopadhyay, M. (2020, December). Determinants and Barriers of Artificial Intelligence Adoption–A Literature Review. In International Working Conference on Transfer and Diffusion of IT (pp. 89-99). Springer, Cham. https://link. springer. com/chapter/ 10. 1007/978-3-030- 64849-7_9.
Ransbotham, S., Kiron, D., Gerbert, P., Reeves, M., 2017. Reshaping Business With Artificial Intelligence: Closing the Gap Between Ambition and Action. MIT Sloan Mangement Rev. Bost. Consult. Gr. 59, 1–17. https://sloanreview. mit. edu/projects/reshaping-business-with-artificial-intelligence/.
Rao, A. S., & Verweij, G. (2017). Sizing the prize: What’s the real value of AI for your business and how can you capitalise. PwC Publication, PwC, 1-30. https://www. pwc. com/gx/en/issues/analytics/assets/pwc-ai-analysis-sizing-the-prize-report. pdf.
Russell, P. N. (2010). Artificial Intelligence: A Modern Approach by Stuart. Russell and Peter Norvig contributing writers, Ernest Davis... [et al. ]. https://books. google. com/books/about/Artificial_Intelligence. html?id=BQ87zQEACAAJ.
Rezaei, Jafar. (2015). Best-worst multi-criteria decision-making method. Omega 53: 49-57. doi: https://doi. org/10. 1016/j. omega. 2014. 11. 009.
Stuart, R., & Peter, N. (2016). Artificial intelligence-a modern approach (3rd ed). ‌ Pearson. https://repository. unimal. ac. id/1022/.
 World Economic Forum (2019), A Framework for Developing a National Artificial Intelligence Strategy. https://dig. watch/resource/framework-developing-national-artificial-intelligence-strategy.
Yadav, S. P., Mahato, D. P., Linh, N. T. D. (Eds. ). (2020). Distributed artificial intelligence: A modern approach. CRC Press. https://www. amazon. com/Distributed-Artificial-Intelligence-Approach-Everything/dp/0367466651.
Yarlagadda, R. T. (2018). Internet of Things & Artificial Intelligence in Modern Society. International Journal of Creative Research Thoughts (IJCRT), ISSN, 2320-2882. https://papers. ssrn. com/sol3/papers. cfm? abstract_id=3798869.
References [In Persian]
Abdolvand, N., Tatani, D. (2014). Comprehensive investigation on Cloud-ERP Adoption Factors of SMEs in Iran. Iranian journal of management sciences, 9(34), pp. 81-104. http://journal. iams. ir/article_186_42. html? lang=fa.
Ghorbanizadeh, V., Hasan Nangeer, S., Roodsaz, S. (2021). Meta-analysis of effecting factors on the information technology acceptance in Iran', Management Research in Iran. 17(2), pp. 177-196. doi: 20. 1001. 1. 2322200. 1392. 17. 2. 8. 4
Haghighinasab, M.,Taghavi, Z. (2020). Adoption of Green Information Technology Using Technology- Organization- Environment Framework in the bankingIndustry. Journal of Business Intelligence Management Studies, 9(34), 63-94. doi: 10. 22054/IMS. 2020. 46042. 1596.
Heydariyeh, S. A., Seid Hosseini, S. M., Shahabi, A. (2013). Simulation of Technology Acceptance Model in Iran Banking using System Dynamics Modeling Approach (Case study: Refah Bank). Journal of Technology Development Management, 1(1), pp. 67-98. doi: 10. 22104/jtdm. 2013. 4.
Hoseinishoar, M., Esfandyari Moghadam A., Zarei, A., Hassanzadeh, M. (2017). Factors Affecting the Adoption of Web 2. 0 Technology in E-Government from Citizen's Perspective and Providing a Model: Case of Government Offices in Hamadan. Human Information Interaction, 4 (3), 60-71. doi: 20. 1001. 1. 24237418. 1396. 4. 3. 1. 6.
Mohammadi, A., Amiri, Y. (2013). A Survey on Identification & Explanation of Factors Affecting IT Innovation Adoption in Governmental Organizations Using SEM. Journal of Information Technology Management, 5(4), pp. 195-218. doi: 10. 22059/jitm. 2013. 36060.
Mohtarami, A., Hosseini, S. H., Elahi, S. (2014). Investigation of the factors affecting IT diffusion in organizations. Journal of Technology Development Management, 1(3), pp. 97-122. doi: 10. 22104/jtdm. 2014. 59.
Mollahosseini, A., Foroozanfar, M. H. (2019). Development and localization of technology acceptance model (TAM) in small and medium-sized enterprises (SMEs). Quarterly journal of Industrial Technology Development, 16(34), pp. 39-48. http://jtd. iranjournals. ir/article_33399 . html.
Movahedi, M., ahmadvand, A., Aliyari, S., namjooyan, F. (2015). The Role of Effective Individual, Organizational and Managerial Factors on Adopting Information Technology in Iranian State Organizations. Journal of Research in Human Resources Management, 7(3), pp. 1-28. https://hrmj. ihu. ac. ir/article_15905. html#ar_info_ pnl_cite.
Shukuhy, J., Jafari, H. R., Yaghoubi, N. M. (2015). Identify and rank key factors influencing the adoption of cloud computing for a healthy Electronics. Iranian Journal of Information processing and Management, 30 (2):549-572. http://jipm. irandoc. ac. ir/article-1-2639-fa. html.
Taherkhani, L. (2019). A reviewing of key factors influencing the adoption and use of cloud based nterprise resource planning systems in small and medium enterprises: Case study Bonyan Gostar Arvand Co. Journal of New Research Approaches in Management and Accounting, 3(11), 203-222. https://majournal. ir/index. php/ma/article/view/157.