Designing a Model for Human Resources Architecture with an Intelligent Approach in Tax Administration in Southeastern Provinces of Iran
محورهای موضوعی : Business Strategy
محمدرضا غلامی
1
,
Abdolali Keshtegar
2
,
Vahid Pourshahabi
3
1 - Phd. Student of Management, Zahedan Branch, Islamic Azad University, Zahedan, Iran
2 - Department of Government Management, Faculty Management and Acconunting, University of Sistan and Baluchestan, Zahedan, Iran
3 - Assistant Professor, Department of Management, Zahedan Branch, Islamic Azad University, Zahedan, Iran
کلید واژه: Intelligentization of human resources, Intelligentization, Tax Administration in Southeastern Provinces of Iran (TASEPI) , Human resources intelligent management.,
چکیده مقاله :
Background: This study was conducted with the aim of designing the architectural model of human resources of Tax Administration in Southeastern Provinces of Iran with the intelligent approach.
Methods: This study was of a mixed type and the statistical population in the qualitative part was 20 experts of Tax Administration managers in the southeastern provinces of Iran (TASEPI), namely Sistan and Baluchistan, Kerman, Hormozgan and South Khorasan. 264 people were selected using G*Power. Sampling of the qualitative part was purposeful and the quantitative part was random cluster sampling. The data collection tool was a researcher-made questionnaire containing 77 items that included six dimensions of intelligent human resources architecture and six dimensions of intelligentization. The software used was Smart-PLS and SPSS-16.
Results: The results showed that the dimensions of human resource architecture were effective in the way of intelligentization as follows: intelligent human resource system (0.965), intelligent human resource management (0.960), intelligent organizational learning (0.955), intelligent organizational architecture strategy (0.953). Technology-oriented (0.945) and smart knowledge management (0.451). The dimensions of intelligentization are also from the dimension of intelligentizing human resources (0.974), intelligent participation of employees (0.965), human resource maintenance activities (0.962), forming a talent fund (0.949), advanced functional activities (0.927) and the dimension of creating new roles of human resources (0.895).
Background: This study was conducted with the aim of designing the architectural model of human resources of Tax Administration in Southeastern Provinces of Iran with the intelligent approach.
Methods: This study was of a mixed type and the statistical population in the qualitative part was 20 experts of Tax Administration managers in the southeastern provinces of Iran (TASEPI), namely Sistan and Baluchistan, Kerman, Hormozgan and South Khorasan. 264 people were selected using G*Power. Sampling of the qualitative part was purposeful and the quantitative part was random cluster sampling. The data collection tool was a researcher-made questionnaire containing 77 items that included six dimensions of intelligent human resources architecture and six dimensions of intelligentization. The software used was Smart-PLS and SPSS-16.
Results: The results showed that the dimensions of human resource architecture were effective in the way of intelligentization as follows: intelligent human resource system (0.965), intelligent human resource management (0.960), intelligent organizational learning (0.955), intelligent organizational architecture strategy (0.953). Technology-oriented (0.945) and smart knowledge management (0.451). The dimensions of intelligentization are also from the dimension of intelligentizing human resources (0.974), intelligent participation of employees (0.965), human resource maintenance activities (0.962), forming a talent fund (0.949), advanced functional activities (0.927) and the dimension of creating new roles of human resources (0.895).
1. Coupe, T. (2019). “Automation, job characteristics and job insecurity”, International Journal of Manpower, Vol. 40 No. 7, pp. 1288-1304.
2. Ardakani, M.Sh, Abdollahzadeh, A., and Shokri, Sh. (2019). An analysis of the role of human resource architecture models on the performance of organizations, National Conference of Economy, Development Management and Entrepreneurship with the approach of supporting Iranian goods, Zahedan, Sistan and Baluchistan representative industrial management organization
3. Spencer, A.J., Buhalis, D. and Moital, M. (2012). “A hierarchical model of technology adoption for small owner-managed travel firms: an organisational decision-making and leadership perspective”, Tourism Management, 33 (5): 1195-1208.
4. Henfridsson, O., Mathiassen, L., and Svahn, F. (2014). “Managing technological change in the digital age: the role of architectural frames”, Journal of Information Technology, Vol. 29 No. 1, pp. 27-43.
5. McDonald, K., Fisher, S. and Connelly, C.E. (2017). E-HRM Systems in Support of “Smart” Workforce Management: An Exploratory Case Study of System Success, Emerald Publishing, doi: 10.1108/978-1-78714-315-920161004.
6. Kumar, S. (2019). “Artificial intelligence divulges effective tactics of top management institutes of India”, Benchmarking: An International Journal, 26 (7): 2188-2204.
7. Tohidenjad, T., and Moghadasi, A.R. (2021). A research on the applications of artificial intelligence in the management of information age organizations, the 13th National Conference on Computer Science and Engineering and Information Technology, Babol.
8. Nair, P. (2017). “The rise of the AI recruiter: is HR tech the next to challenge human intuition”, available at: https://www.growthbusiness.uk.
9. Richards, G., Yeoh, W., Chong, A.Y.L., and Popovi_c, A. (2019). “Business intelligence effectiveness and corporate performance management: an empirical analysis”, Journal of Computer Information Systems, 59 (2): 188-196.
10. Saxena, R. and Kumar, Y. (2020). "Influence of Artificial Intelligence on Work, People and the Firm: A Multi-Industry Perspective", Kumar, P., Agrawal, A. and Budhwar, P. (Ed.) Human & Technological Resource Management (HTRM): New Insights into Revolution 4.0, Emerald Publishing Limited, Bingley, pp. 111-132.
11. Bogićević, M. B. (2020). A conceptual framework for designing the architecture of human resource management. Ekonomski horizonti, 22(2), 119-136.
12. Deluji, N. (2015). The effect of administrative automation on the level of intelligent organization and organizational health (South West Tehran Electric Company), master's thesis, Northern Strategy Institute of Higher Education, Faculty of Management.
13. Rezaei, S., Mirabidini, S.J., Abtahi, A. (2018). Factors affecting the implementation of business intelligence in Iran's banking industry. Intelligent Business Management Studies, 6(23), 81-33.
14. Rouhani, A., Amin Kazemi, B., and Arasteh, M.R. (2021). Investigating the impact of artificial intelligence on the future direction of human resource management, the third national conference of new studies in entrepreneurship and business management, Semnan.
15. Seyed Javadin, S.R., Shahbaz Moradi, S., Hasangholipour, T., Mirsepasi, N. (2014). Conceptual framework of human resource architecture with a strategic approach (research in National Iranian Oil Company), Business Management Quarterly, 6 (1): 89-106.
16. Nourafza, N., Izadi, S., and Javadzadeh Amini, S. (2019). Investigating the relationship between artificial intelligence and improving the effectiveness of human resource management, the 6th national conference on applied research in computer engineering and information technology, Tehran.
17. Yazdanpanah, A.A., and Afsarian, A.R. (2014). Paradigms effective in using artificial intelligence systems in human resource management functions, Tehran, International Conference on Business Development and Excellence.
18. Agarwal, A. (2022). "AI adoption by human resource management: a study of its antecedents and impact on HR system effectiveness", Foresight, Vol. ahead-of-print No. ahead-of-print.
19. Bersin, J. (2018), “Talent trends technology disruptions for 2018”, available at: https://www.isaconnection.org/assets/documents.
20. Boon, C.; Hartog, D.N.D.; Lepak, D.P. (2019). A Systematic Review of Human Resource Management Systems and Their Measurement. Journal of Management, 45 (6): 2498–2537.
21. Lee, H.W., Pak, J., Kim, S., Li, L.Z. (2019). Effects of Human Resource Management Systems on Employee Proactivity and Group Innovation. Journal of Management, 45 (2): 819-846.
22. Chowdhury S., Prasanta, D., Sian, J.E., Sudeshna, B., Oscar, R.E., Amelie, A., Linh, T. (2022). Unlocking the value of artificial intelligence in human resource management through AI capability framework, Human Resource Management Review,100899, ISSN 1053-4822, https://doi.org/10.1016/j.hrmr.2022.100899.
23. Das, D. (2022). "Understanding the choice of human resource and the artificial intelligence: “strategic behavior” and the existence of industry equilibrium", Journal of Economic Studies, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/JES-06-2021-0305.
24. Anand, G., Ward, P.T. and Tatikonda, M.V. (2010). “Role of explicit and tacit knowledge in Six Sigma projects: an empirical examination of differential project success”, Journal of Operations Management, Vol. 28 No. 4, pp. 303-315.
25. Arslan, A., Ruman, A., Naughton, S. and Tarba, S.Y. (2021). “Human dynamics of automation and digitalisation of economies: discussion on the challenges and opportunities”, in Park, S.H., Gonzalez-Perez, M.A. and Floriani, D.E. (Eds), The Palgrave Handbook of Corporate Sustainability in the Digital Era, Palgrave Macmillan (Springer Nature), pp. 613-629.
26. Bawden, D. and Robinson, L. (2009). “The dark side of information: overload, anxiety and other paradoxes and pathologies”, Journal of Information Science, Vol. 35 No. 2, pp. 180-191.
27. Vrontis, D., Christofi, M., Pereira, V., Tarba, S., Makrides, A., and Trichina, E. (2021). “Artificial intelligence, robotics, advanced technologies and human resource management: a systematic review”, International Journal of Human Resource Management, Early view. doi: 10.1080/09585192.2020.1871398.
28. Istudor, N., Ursacescu, M., Sendroiu, C., & Radu, I. (2016). Theoretical framework of organizational intelligence: a managerial approach to promote renewable energy in rural economies. Energies, 9(8), 639.
29. Charlier, R. and Kloppenburg, S. (2017). “Artificial intelligence in HR: a No-brainer”, available at: www.pwc.nl.
30. De Angelis, C.T. (2013). A knowledge management and organizational intelligence model for public administration. International Journal of Public Administration, 36(11), 807-819.
31. Fenech, R., Baguant, P., & Ivanov, D. (2019). The changing role of human resource management in an era of digital transformation. International Journal of Entrepreneurship, 22 (2): 166-175.
32. Ghorbani, A., Danaei, A., Zargar, S. M., & Hematian, H. (2019). Designing of smart tourism organization (STO) for tourism management: A case study of tourism organizations of South Khorasan province, Iran. Heliyon, 5(6), e01850.
