شناسایی و رتبه‌بندی عوامل مؤثر بر پذیرش هوش مصنوعی در بخش دولتی و خصوصی

https://hrmj. ihu. ac. ir/article_15905. html#ar_info_pnl_cite.

References

Alsheibani, S., Cheung, Y., & Messom, C. (2018). Artificial Intelligence Adoption: AI-readiness at Firm-Level. In PACIS (p. 37). ‌

https://core. ac. uk/download/pdf/301376079. pdf.

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.

Sharma, G. D., Yadav, A., Chopra, R., 2020. Artificial intelligence and effective governance: A review, critique and research agenda. Sustain. Futur. 2, 100004. https://doi. org/10. 1016/j. sftr. 2019. 100004

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.