The digital transformation of China’s manufacturing industry has exacerbated employee stress, particularly in medium-sized enterprises. Existing stress measurement tools often focus on isolated stress factors, neglecting the complex interplay of personal, work-related, and technological influences. This study develops and validates a multidimensional instrument that integrates cognitive stress appraisal, emotional regulation, behavioral coping strategies, workload perception, AI-enabled ease of use (AI-EoU), and stress management. Survey data from 50 employees in medium-sized manufacturing firms were analyzed using Exploratory Factor Analysis(EFA), Cronbach’s ?, and Pearson correlations. The results demonstrate strong construct validity (KMO > 0.8) and high reliability (Cronbach’s ?> 0.88). This research extended the Transactional Model of Stress and Coping(TMSC) by positioning AI-EoU as a secondary appraisal resource highlighting its role in influencing stress adaptation in digitalized workplaces. The developed instrument offers firms a robust tool for evaluating and enhancing stress management predictors in technology-driven environments.
Acarturk, C., & Mucen, B. (2022). Performance in the workplace: A critical evaluation of cognitive enhancement. NanoEthics, 16(1), 107-114. https://doi.org/10.1007/s11569-021-00407-6.
Cao, D., Tao, H., Wang, Y., Tarhini, A., & Xia, S. (2020). Acceptance of automation manufacturing technology in China: an examination of perceived norm and organizational efficacy. Production planning & control, 31(8), 660-672. https://doi.org/10.1080/09537287.2019.1669091
China Labour Watch. (2023). Working conditions in Chinese high-tech manufacturing. https://www.chinalaborwatch.org
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS quarterly, 319-340. https://doi.org/10.2307/249008
Fliege, H., Rose, M., Arck, P., Walter, O. B., Kocalevent, R. D., Weber, C., & Klapp, B. F. (2005). The Perceived Stress Questionnaire (PSQ) reconsidered: Validation and reference values from different clinical and healthy adult samples. Psychosomatic Medicine, 67(1). https://doi.org/10.1097/01.psy.0000151491.80178.78
Gladden, M., Fortuna, P., & Modli?ski, A. (2022). The empowerment of artificial intelligence in post-digital organizations: exploring human interactions with supervisory AI. Human Technology, 18(2), 98-121. https://doi.org/10.14254/1795-6889.2022.18-2.2
Gouveia, V. V., Moura, H. M. D., Oliveira, I. C. V. D., Ribeiro, M. G. C., Rezende, A. T., & Brito, T. R. D. S. (2018). Emotional Regulation Questionnaire (ERQ): evidence of construct validity and internal consistency. Psico-USF, 23(3), 461-471. https://doi.org/10.1590/1413-82712018230306
Guo, R., Kelana, B. W. Y., Safar, A. E., Mahmod, A., & Cheng, L. (2025). Reframing Stress Management in Digitized Workplaces: The Mediating Role of AI-Enabled Ease of Use. International Journal of Academic Research in Business and Social Sciences, 15(6), 1177–1193.
Haggart, B. (2019). The age of surveillance capitalism: The fight for a human future at the new frontier of power, S. Zuboff (2018). journal of digital media & policy, 10(2), 229-243. https://doi.org/10.1386/jdmp.10.2.229_5
Hainmueller, J., Mummolo, J., & Xu, Y. (2019). How much should we trust estimates from multiplicative interaction models? Simple tools to improve empirical practice. Political Analysis, 27(2), 163-192. https://doi.org/10.1017/pan.2018.46.
Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2010). Multivariate data analysis. Vectors. Retrieved from http://doi.org/10.1016/j.ijp harm.2011.02.019
Hou, Y. and Fan, L. (2024). Working with ai: the effect of job stress on hotel employees’ work engagement. Behavioral Sciences, 14(11), 1076. https://doi.org/10.3390/bs14111076
Kashive, N., Powale, L., & Kashive, K. (2020). Understanding user perception toward artificial intelligence (AI) enabled e-learning. The International Journal of Information and Learning Technology, 38(1), 1-19. https://doi.org/10.1108/ijilt-05-2020-0090.
Kengue Mayamou, P., & Michel, S. (2020). Mobile Money: décryptage d’une succes story africaine. Management & Datascience, 4(5).
Kopp, T. (2024). Facets of trust and distrust in collaborative robots at the workplace: Towards a multidimensional and relational conceptualisation. International Journal of Social Robotics, 16(6), 1445-1462.
Lee, M. K. (2018). Understanding perception of algorithmic decisions: Fairness, trust, and emotion in response to algorithmic management. Big Data & Society, 5(1). https://doi.org/10.1177/2053951718756684
Mohamed, A., Isahak, M., Isa, M., & Nordin, R. (2022). The effectiveness of workplace health promotion program in reducing work-related depression, anxiety and stress among manufacturing workers in Malaysia: mixed-model intervention. International Archives of Occupational and Environmental Health, 95(5), 1113-1127. https://doi.org/10.1007/s00420-022-01836-w.
Murphy, L. (1996). Stress Management in Work Settings: A Critical Review of the Health Effects. American Journal of Health Promotion, 11(2), 112-135. https://doi.org/10.4278/0890-1171-11.2.112.
Pillai, R., Sivathanu, B., & Dwivedi, Y. (2020). Shopping intention at AI-powered automated retail stores (AIPARS). Journal of Retailing and Consumer Services, 57, 102207. https://doi.org/10.1016/j.jretconser.2020.102207.
Pouy, S., Taheri_Ezbarami, Z., Rassouli, M., Maroufizadeh, S., Darbandi, B., & Javadi-Pashaki, N. (2025). Translation and Psychometric Evaluation of the Persian Version of the Pediatric Quality of Life Inventory 4.0 (PedsQL 4.0) for Iranian Children With Cancer. Journal of Holistic Nursing And Midwifery, 35(2), 149-157. https://doi.org/10.32598/jhnm.35.2.2852.
Qu, C., & Kim, E. (2025). Investigating AI Adoption, Knowledge Absorptive Capacity, and Open Innovation in Chinese Apparel MSMEs: An Extended TAM-TOE Model with PLS-SEM Analysis. Sustainability, 17(5), 1873. https://doi.org/10.3390/su17051873
Ross, J. (2017). Organizational Support, Workload, and Intent to Stay: Work Environment Perceptions in Perianesthesia Nursing Units. Journal of Perianesthesia Nursing, 32(4). https://doi.org/10.1016/j.jopan.2015.07.001
Shandong Bureau of Statistics. (2022). Shandong electronic information industry annual. http://tjj.shandong.gov.cn/tjnj/nj2022/zk/zk/indexch.htm
Shrestha, N. (2021). Factor Analysis as a Tool for Survey Analysis. American Journal of Applied Mathematics and Statistics, 9(11), 4-11. https://doi.org/10.12691/AJAMS-9-1-2.
Sonnentag, S., & Fritz, C. (2007). The Recovery Experience Questionnaire: development and validation of a measure for assessing recuperation and unwinding from work. Journal of occupational health psychology, 12(3), pp.204-221.
Svensen, E., Neset, G., & Eriksen, H. (2007). Factors associated with a positive attitude towards change among employees during the early phase of a downsizing process. Scandinavian Journal of Psychology, 48(2), 153–159. Retrieved from http://dx.doi.org/10.1111/j.1467- 9450.2007.00577.x
Tarafdar, M., Cooper, C. L., & Stich, J. F. (2019). The technostress trifecta?techno eustress, techno distress and design: Theoretical directions and an agenda for research. Information systems journal, 29(1), 6-42. https://doi.org/10.1111/isj.12169
Tarafdar, M., Pullins, E. B., & Ragu?Nathan, T. S. (2015). Technostress: negative effect on performance and possible mitigations. Information systems journal, 25(2), 103-132.
Tavakol, M., & Dennick, R. (2011). Making sense of Cronbach's alpha. International Journal of Medical Education, 2, 53 - 55. https://doi.org/10.5116/ijme.4dfb.8dfd.
Tortorella, G., Powell, D., Hines, P., Mac Cawley Vergara, A., Tlapa, D., & Vassolo, R. (2025). How does artificial intelligence impact employees’ engagement in lean organisations?. International Journal of Production Research, 63(3), 1011-1027. https://doi.org/10.1080/00207543.2024.2368698.
Xu, Z., Chin, T., & Cao, L. (2020). Crafting Jobs for Sustaining Careers during China’s Manufacturing Digitalization. Sustainability, 12(5), 2041. https://doi.org/10.3390/su12052041.
Yang, S., Liu, K., Gai, J., & He, X. (2022). Transformation to industrial artificial intelligence and workers' mental health: evidence from China. Frontiers in Public Health, 10, 881827. https://doi.org/10.3389/fpubh.2022.881827
Zuckerman, M., & Gagne, M. (2003). The COPE revised: Proposing a 5-factor model of coping strategies. Journal of Research in Personality, 37(3). https://doi.org/10.1016/S0092-6566(02)00563-9
Panchetti, T., Pietrantoni, L., Puzzo, G., Gualtieri, L., & Fraboni, F. (2023). Assessing the relationship between cognitive workload, workstation design, user acceptance and trust in collaborative robots. Applied Sciences, 13(3), 1720. https://doi.org/10.3390/app13031720
Guo, R., Kelana, B. W. Y., Safar, A. E., Mahmod, A., Ji, Z., & Cheng, L. (2025). Pilot Study on the Validity and Reliability of a Multi-Dimensional Stress Management Instrument in Medium-Sized Manufacturing Firms in China. International Journal of Academic Research in Business and Social Sciences, 15(9), 1315–1325.
Copyright: © 2025 The Author(s)
Published by Knowledge Words Publications (www.kwpublications.com)
This article is published under the Creative Commons Attribution (CC BY 4.0) license. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this license may be seen at: http://creativecommons.org/licences/by/4.0/legalcode