Volume 4,Issue 1
Training and Adoption of AI Technology for Sustainable Career in Vulnerable Employment Groups: A Mixed-Method Netcoincidental Analysis
This mixed-methods study investigates the acceptance of artificial intelligence (AI) among vulnerable employment groups (freelancers, gig workers, low‑skilled workers) and the role of training in shaping their attitudes and behaviors. Based on an extended Technology Acceptance Model (TAM), we surveyed 39 individuals from vulnerable employment backgrounds and conducted in‑depth interviews with 6 participants. Quantitative data were analyzed using descriptive statistics, independent t‑tests, and reticular coincidence analysis (RAC) to visualize significant associations among TAM dimensions, training experience, and demographic variables. Qualitative data provided contextual insights into participants' perceptions. Results show generally positive attitudes, with perceived usefulness (M = 5.41) and intention to use (M = 5.49) rated highest, while actual use lagged (M = 4.93). Training experience was associated with higher perceived ease of use (p < 0.05) and behavioral intention. RAC networks revealed that positive attitudes cluster together, forming a profile of younger, experienced, trained individuals; negative attitudes were rare and linked to older age and lack of training. Interview narratives confirmed that training reduces anxiety, builds practical skills, and enhances career prospects. These findings underscore the importance of targeted AI training programs for vulnerable groups to promote digital inclusion and employability, contributing to SDG 8 (Decent Work and Economic Growth) and SDG 10 (Reduced Inequalities).
[1] George AS, George ASH, 2023, A Review of ChatGPT AI’s Impact on Several Business Sectors. Partners Universal International Innovation Journal, 1(1): 9–23.
[2] Bekker S, Larsen TP, Leschke J, 2025, 9: Unemployment Protection in Changing Labour Markets. Edward Elgar Publishing, 131-152.
[3] Davis FD, 1989, Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology. MIS Quarterly, 13(3): 319–340.
[4] Venkatesh V, Morris MG, Davis GB, et al., 2003, User Acceptance of Information Technology: Toward a Unified View. MIS Quarterly, 27(3): 425.
[5] Dahri NA, Yahaya N, Al-Rahmi WM, et al., 2024, Extended TAM Based Acceptance of AI-Powered ChatGPT for Supporting Metacognitive Self-Regulated Learning in Education: A Mixed-Methods Study. Heliyon, 10(8): e29317
[6] Escobar M, Martinez-Uribe L, 2020, Network Coincidence Analysis: The netCoin R Package. Journal of Statistical Software, 93: 1–32.
[7] Zhang C, Schießl J, Plößl L, et al., 2023, Acceptance of Artificial Intelligence Among Pre-Service Teachers: A Multigroup Analysis. International Journal of Educational Technology in Higher Education, 20(1): 49.
[8] Fuchs K, 2023, Exploring the Opportunities and Challenges of NLP Models in Higher Education: Is Chat GPT a Blessing or a Curse? Frontiers in Education, 8.
[9] Kanwal A, Hassan SK, Iqbal I, 2023, An Investigation into How University-Level Teachers Perceive Chat-GPT Impact upon Student Learning. Gomal University Journal of Research, 39(3): 250–265.
[10] Yu H, 2023, Reflection on Whether Chat GPT Should Be Banned by Academia from the Perspective of Education and Teaching. Frontiers in Psychology, 14.
[11] Ali JKM, Shamsan MAA, Hezam TA, et al., 2023, Impact of ChatGPT on Learning Motivation: Teachers and Students’ Voices. Journal of English Studies in Arabia Felix, 2(1): 41–49.
[12] Yilmaz H, Maxutov S, Baitekov A, et al., 2023, Student Attitudes Towards Chat GPT: A Technology Acceptance Model Survey. International Educational Review, 1(1): 57–83.
[13] García Alonso EM, León Mejía AC, Sánchez Cabrero R, et al., 2024, Training and Technology Acceptance of ChatGPT in University Students of Social Sciences: A Netcoincidental Analysis. Behavioral Sciences, 14(7): 612.
[14] Schoonenboom J, Johnson RB, 2017, How to Construct a Mixed Methods Research Design. KZfSS Kölner Zeitschrift Für Soziologie Und Sozialpsychologie, 69(S2): 107–131.
[15] Raman R, Mandal S, Das P, et al., 2024, Exploring University Students’ Adoption of ChatGPT Using the Diffusion of Innovation Theory and Sentiment Analysis with Gender Dimension. Human Behavior and Emerging Technologies, 2024(1): 3085910.