تعداد نشریات | 30 |
تعداد شمارهها | 467 |
تعداد مقالات | 4,522 |
تعداد مشاهده مقاله | 7,145,260 |
تعداد دریافت فایل اصل مقاله | 5,334,960 |
هوش مصنوعی درمقابل روشهای هدایت انسانی در ارزیابی استخدام منابع انسانی: فراترکیب مزایا و معایب | ||
مدیریت منابع انسانی پایدار | ||
دوره 6، شماره 11، مهر 1403، صفحه 214-191 اصل مقاله (958.2 K) | ||
نوع مقاله: مقاله پژوهشی | ||
شناسه دیجیتال (DOI): 10.22080/shrm.2024.5100 | ||
نویسندگان | ||
محمد اعتمادی1؛ احسان چیت ساز* 1؛ سحر کوشکی2؛ سیدمحمدعلی جعفری3 | ||
1گروه توسعه کارآفرینی، دانشکده کارآفرینی، دانشگاه تهران، تهران، ایران | ||
2کارشناسی ارشد مدیریت کارآفرینی سازمانی، دانشکده کارآفرینی،دانشگاه تهران،تهران،ایران | ||
3دانشکده کارآفرینی دانشگاه تهران | ||
تاریخ دریافت: 22 مهر 1403، تاریخ پذیرش: 22 مهر 1403 | ||
چکیده | ||
انتخاب بهترینها برای استخدام منابع انسانی در سازمانها همواره یک چالش اساسی بوده است. امروزه با افزایش دانش ما از پیچیدگیهای عملکرد انسانها، ارزیابی آنها دشوارتر از گذشته شده است. در این میان با پیشرفت و فراگیرشدن هوش مصنوعی، ارزیابی مبتنی بر هوش مصنوعی افزایش روزافزون دارد؛ اما مانند هر فرآیند نوظهوری، مزایا و معایب آن واضح نیست. تحقیقات مختلف، با نگاههای مختلف این موضوع را دنبال کردهاند؛ اما هدف این پژوهش فراترکیبی بر مزایا و معایب استفاده از هوش مصنوعی درمقایسهبا دیگر روشهای هدایت انسانی در ارزیابی برای استخدام منابع انسانی در سازمانها است. با روش فراترکیب به تحلیل نظاممند یافتههای پژوهشی پیشین پرداخته شد. پرکاربردترین روشهای ارزیابی بهترتیب قضاوت مدیریت، استخدام سنتی، فناوریهای آنلاین، تصویر کارفرما و اطلاعات جمعیتشناختی شناسایی شد. مهمترین معایب این روشها بهترتیب، عدم طراحی درست، نابرابری و تبعیض و مزایای آن کاهش حجم کار، فرصتهای شغلی و جذب بهترینها شناسایی شد. درمقابل، بکارگیری هوش مصنوعی در ارزیابی منابع انسانی دارای چالشهای عدم پذیرش، تصمیمگیری فناوری محور و امنیت اطلاعات و مزایای بهبود تصمیمگیری، بهبود در فرایند استخدام و کاهش زمان و هزینه است. | ||
کلیدواژهها | ||
هوش مصنوعی؛ استخدام الکترونیکی؛ ارزیابی منابع انسانی؛ تصویر کارفرما؛ روش استخدام منابع انسانی | ||
عنوان مقاله [English] | ||
Artificial Intelligence (AI) vs. Human-Led Approaches in Human Resource Recruitment Assessment: A Meta-Synthesis of Advantages and Disadvantages | ||
نویسندگان [English] | ||
Mohammad Etemadi1؛ Ehsan Chitsaz1؛ Sahar Koushki2؛ Seyed Mohammadali Jafari3 | ||
1Department of Entrepreneurship Development, Faculty of Entrepreneurship, University of Tehran, Tehran, Iran | ||
2Master of Entrepreneurship Management, Entrepreneurship ,Faculty, Tehran University , Tehran, Iran | ||
3Faculty of Entrepreneurship, Farshi Moghadam Street | ||
چکیده [English] | ||
Selecting the best candidates for human resource recruitment in organizations has always been a fundamental challenge. Today, with our increased understanding of the complexities of human performance, evaluating individuals has become more difficult than before. Meanwhile, with the advancement and widespread adoption of artificial intelligence, AI-based evaluations are on the rise; however, like any emerging process, its advantages and disadvantages are not clear. Various studies have pursued this subject from different perspectives, but the aim of this research is a meta-synthesis of the advantages and disadvantages of using artificial intelligence compared to other human-led methods in the evaluation for recruiting human resources in organizations. Using the meta-synthesis method, previous research findings were systematically analyzed. The most commonly used evaluation methods were identified, in order, as managerial judgment, traditional recruitment, online technologies, employer branding, and demographic information. The most significant disadvantages of these methods, respectively, were improper design, inequality and discrimination, while their advantages were identified as reducing workload, providing job opportunities, and attracting the best candidates. In contrast, employing artificial intelligence in human resource evaluation presents challenges such as lack of acceptance, technology-driven decision-making, and information security, but offers advantages like improved decision-making, enhancements in the recruitment process, and reductions in time and cost. | ||
کلیدواژهها [English] | ||
Artificial intelligence, electronic recruitment, human resources assessment, employer image, human resources recruitment method | ||
مراجع | ||
Abdollahi Alibeik, Hamed & Etemadi, Mohammad. (2024) Exploring Epistemological Perspectives on AI Integration in Entrepreneurial Data-Driven Decision-Making: Rationalist, Empirical, and Constructivist Approaches. The 19th National Conference on Economics, Management and Accounting. https://civilica.com/doc/2023582 Afzal, M. N. I., Shohan, A. H. N., Siddiqui, S., & Tasnim, N. (2023). Application of AI on human resource management: A review. Journal of Human Resource Management. https://doi.org/10.46287/fhev4889 akbari emami, S., Jamipour, M., & Fathi, S. (2023). Designing a framework for using artificial intelligence in human resource management: An exploratory approach. Journal of Sustainable Human Resource Management, 5(9), 284-263. doi: 10.22080/shrm.2023.4416 [In Persian] Alzyoud, A. A. Y., Omar, K. M., & Arbab, A. (2024). Navigating the future: The role of artificial intelligence in shaping recruitment practices. https://doi.org/10.1109/icetsis61505.2024.10459627 Asif, A. (2024). Integrating AI in recruitment: A review of perceptions, acceptance, adoption and ethical considerations of AI usage. Frontiers in Business, Economics and Management. https://doi.org/10.54097/c759fx45 Chalco-Chávez, C. L., Fernandez-Hurtado, G., & Cordova-Buiza, F. (2023). Factors influencing the human talent recruitment process in private companies: A systematic review. https://doi.org/10.34190/ecmlg.19.1.1796 Chitsaz, Ehsan & Tajpour, Mehdi & Hosseini, Elahe & Khorram, Hengameh & Zorrieh, Saloomeh. (2019). The Effect of Human and Social Capital on Entrepreneurial Activities: A Case Study of Iran and Implications. Entrepreneurship and Sustainability Issues. 6. 1393-1403. 10.9770/jesi.2019.6.3(24). Correa, R. M., & Frate, F. (2021). Digital Transformation at the Recruitment and Selection Process: A Study of Semantic Analysis. Journal on Innovation and Sustainability RISUS, 12(2), 67-74. Eger, L., Mičík, M., & Řehoř, P. (2018). Employer branding on social media and recruitment websites: Symbolic traits of an ideal employer. E+ M. Ekonomie a Management, 21(1), 224-237. Etemadi, M., Chitsaz, E., & Ghodratizahed, F. (2024). The Paradox of Rewards: Reconsidering Employee Satisfaction and Ideation Performance; Journal of Sustainable Human Resource Management, 6(10), -. doi: 10.22080/shrm.2024.4599 [in Persian] Etemadi, M., Chitsaz, E., Abolghasemi Dehaqani, M., & Ghodratizadeh, F. (2024). The Interplay of Monetary Rewards, Expectations, and Ideation Quality: An Empirical Analysis. Journal of Entrepreneurship Development, 16(4), 116-142. doi: 10.22059/jed.2023.360337.654210 [in Persian] Forat yazdi, E., Chitsaz, E., & Etemadi, M. (2024). Demystifying Artificial Intelligence (AI) in Human Resource Management (HRM): A Bibliometric Analysis of Explainable Artificial Intelligence (XAI) (2013-2023). Sciences and Techniques of Information Management. doi: 10.22091/stim.2024.10488.2075 [in Persian] FraiJ, J., & László, V. (2021). Literature review: Artificial intelligence impact on the recruitment process. International Journal of Engineering and Management Sciences. https://doi.org/10.21791/IJEMS.2021.1.10 Horodyski, P. (2023). Applicants' perception of artificial intelligence in the recruitment process. Computers in Human Behavior Reports, 100303. Hu, Y., Lyu, Z., & Sun, W. (2023). Review of research on influencing factors of personnel recruitment. Lecture Notes in Education Psychology and Public Media. https://doi.org/10.54254/2753-7048/18/20231272 Jayasekara, C., Senarathne, I., Wickramasinghe, A., Jayathilaka, N., Thelijjagoda, S., De Silva, H., Giguruwa, N., & Abeysinghe, N. (2023). Artificial intelligence agent to identify the correct human resources. https://doi.org/10.1109/icac60630.2023.10417197 Johanna Mosquera, I., & Mehta, M. (2024). Enhancing human resources management through AI-driven talent acquisition and employee engagement. https://doi.org/10.58532/v3binc3p9ch1 Kamble, P. R., & Kulkarni, U. (2022). An Innovative Approach of Personality Recognition for E-Recruitment. International Conference on Awareness Science and Technology. https://doi.org/10.1109/ICAST55766.2022.10039605 Kambur, E., & Akar, C. (2021). Human resource developments with the touch of artificial intelligence: a scale development study. Int. J. Manpow. Kot, S., Hussain, H. I., Bilan, S., Haseeb, M., & Mihardjo, L. W. (2021). The role of artificial intelligence recruitment and quality to explain the phenomenon of employer reputation. Journal of Business Economics and Management, 22(4), 867-883. Kshetri, N. (2021). Evolving uses of artificial intelligence in human resource management in emerging economies in the global South: some preliminary evidence. Management Research Review, 44(7), 970-990. Mosavi jad, S. M., Ahmadizad, A., hossaeni, S. M., & mohammadi, H. (2022). An analysis of the role of human capital competencies in sustainable strategic management. Journal of Sustainable Human Resource Management, 4(7), 232-215. Mujtaba, D. F., & Mahapatra, N. R. (2024). Fairness in AI-driven recruitment: Challenges, metrics, methods, and future directions. https://doi.org/10.48550/arxiv.2405.19699 Mohammadi Eliasi Ghanbar, Chitsaz Ehsan, & Gerami Abbas. (2010). Identifying intra-organizational factors affecting the performance of start-up companies. Nawaz, N. (2020). Artificial intelligence applications for face recognition in recruitment process. Journal of management Information and Decision Sciences, 23(S1), 507-517. Norman, E., & Pahlawati, E. (2024). Peran artificial intelligence dalam rekrutmen dan seleksi: Meningkatkan efisiensi dan akurasi dalam MSDM. Sci-tech Journal. https://doi.org/10.56709/stj.v3i1.320 Oncioiu, I., Anton, E., Ifrim, A. M., & Mândricel, D. A. (2022). The influence of social networks on the digital recruitment of human resources: An empirical study in the tourism sector. Sustainability, 14(6), 3693. Ore, O., & Sposato, M. (2022). Opportunities and risks of artificial intelligence in recruitment and selection. International Journal of Organizational Analysis, 30(6), 1771-1782. Pan, J., Ye, N., Yu, H., Hong, T., Al-Rubaye, S., Mumtaz, S., ... & Chih-Lin, I. (2022). AI-driven blind signature classification for IoT connectivity: A deep learning approach. IEEE Transactions on Wireless Communications, 21(8), 6033-6047. Prasad, P. (2024). AI-powered talent acquisition: Enhancing recruitment processes in the digital age. Indian Scientific Journal of Research in Engineering and Management. https://doi.org/10.55041/ijsrem35619 Perifanis, N. A., & Kitsios, F. (2023). Investigating the influence of artificial intelligence on business value in the digital era of strategy: A literature review. Information, 14(2), 85. Rad, M. B., Valmohammadi, C., & Shayan, A. (2020). An empirical investigation of the factors affecting the use of social networks in human resources recruitment. International Journal of Public Administration. https://doi.org/10.1080/01900692.2019.1636396 Rani, C., & Kajla, T. (2023). Artificial intelligence applications in human resource management. Advances in Logistics, Operations, and Management Science. https://doi.org/10.4018/979-8-3693-0418-1.ch012 Rožman, M., Oreški, D., & Tominc, P. (2022). Integrating artificial intelligence into a talent management model to increase the work engagement and performance of enterprises. Frontiers in Psychology, 13, 1014434. Rozsa, Z., & Machova, V. (2020). Factors affecting job announcement competitiveness on job listing websites. Journal of Cryptology. https://doi.org/10.7441/JOC.2020.04.07 Sadlapur, S. (2017). Information literacy of management students in Mumbai metropolitan area. Tilak Maharashtra Vidyapeeth. Sasi, K. P. (2024). Impact of AI in recruitment and talent acquisition. Human Resource and Leadership Journal. https://doi.org/10.47941/hrlj.2117 Shahi, Tahereh, et al. (2020). Behavioral factors affecting talent management: Meta-synthesis technique. Iranian Journal of Management Studies, 13(1), 117-137. Shirkhodaie, M., Nejat, S., Kameli, A., & Mehdikhani, H. (2019). Investigating the effects of brand image on the potential employee’s intention to apply a job through mediating role of employer brand attractiveness (Case Study: students of Tehran University, college of Farabi). Journal of Sustainable Human Resource Management, 1(1), 127-113. https://doi.org/10.22080/shrm.2019.2359 [In Persian] Shao, Y. (2022). [Retracted] Human‐Computer Interaction Environment Monitoring and Collaborative Translation Mode Exploration Using Artificial Intelligence Technology. Journal of environmental and public health, 2022(1), 4702003. Strang, K. D., & Zhaohao, S. (2022). ERP staff versus AI recruitment with employment real-time big data. Discover Artificial Intelligence. https://doi.org/10.1007/s44163-022-00037-1 Sandelowski, M., Barroso, J., & Voils, C. I. (2007). Using qualitative metasummary to synthesize qualitative and quantitative descriptive findings. Research in nursing & health, 30(1), 99-111. Trivedi, A. P. O. O. R. V. A., & Pillai, L. A. L. I. T. H. A. (2020). HR: digital transformation 2020. Advances and applications in mathematical sciences, 20(2), 261-267. Tsai, P.-H., Kao, Y. L., & Kuo, S. Y. (2023). Exploring the critical factors influencing the outlying island talent recruitment and selection evaluation model: Empirical evidence from Penghu, Taiwan. Evaluation and Program Planning. https://doi.org/10.1016/j.evalprogplan.2023.102320 Tsiskaridze, R., Reinhold, K., & Järvis, M. (2023). Innovating HRM recruitment: A comprehensive review of AI deployment. Marketing i menedzment innovacij. https://doi.org/10.21272/mmi.2023.4-18 Zhang, M., Zhang, N., Yang, J., Feng, D., & Li, J. G. (2024). Application of competency model in enterprise human resource recruitment management. Advances in Transdisciplinary Engineering. https://doi.org/10.3233/atde240421 Yazdani, H., & hakiminia, M. (2024). Identifying the challenges and opportunities of using artificial intelligence in Human resource management with a meta-synthesis approach. Journal of Sustainable Human Resource Management, 6(10), 139-113. https://doi.org/10.22080/shrm.2024.4601 Wang-Cowham, C. (2011). Developing talent with an integrated knowledge-sharing mechanism: An exploratory investigation from the Chinese human resource managers' perspective. Human Resource Development International, 14(4), 391-407. Wilska, E. (2014). Determinants of effective talent management. Journal of positive Management, 5(4), 77-88. Wehner, N., Seufert, A., Hoßfeld, T., & Seufert, M. (2023). Explainable data-driven QoE modelling with XAI. In 2023 15th international conference on quality of multimedia experience (QoMEX) (pp. 7-12). IEEE. | ||
آمار تعداد مشاهده مقاله: 522 تعداد دریافت فایل اصل مقاله: 224 |