A Preliminary Study on the Career Competency of AI-integrated workplaces in Nanjing Tourism Industry: A Moderating Effect of Organizational Culture
DOI:
https://doi.org/10.62051/ijgem.v6n3.24Keywords:
A Preliminary Study, AI-integrated workplaces, Career Competency, Organizational Culture, Nanjing Tourism IndustryAbstract
As Artificial Intelligence (AI) continues to merge with the tourism industry, AI-integrated workplaces place higher demands on employee occupational competence. However, existing research has paid insufficient attention to how AI factors affect occupational competence and the moderating role of organizational culture in this process. Taking the tourism industry in Nanjing as a background, this study initially explores the impact of factors such as AI training on occupational competence and analyses the moderating effect of organizational culture. Preliminary analysis of the questionnaire data reveals that factors such as AI training significantly enhance occupational competence; organizational culture has a significant moderating affect that. After preliminary testing, the reliability validity and correlation values have met the criteria. There is a positive correlation between the variables. The study enriches the theoretical framework of occupational competence in the smart tourism industry, and future research can be extended to more industries and regions, and explore the dynamic influence mechanism.
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[1] Nanjing Daily, 2024.03.07. Accelerating Transformation and Upgrading, Integrating into Thousands of Industries, and Landing on ‘Just-In-Time Scenarios’- Standing at the Wind Gap, Nanjing Seizes the High Ground of Artificial Intelligence (AI) Development. https://www.nanjing.gov.cn/zt/njtdjjyxsxzthz/ywjj/202403/t20240307_4181792.html
[2] Chen, W., & Wang, H. (2021). The impact of smart technologies on tourism: A systematic review. Tourism Management Perspectives, 40, 100879. https://doi.org/10.1016/j.tmp.2021.100879
[3] Zhao, L., & Sun, Y. (2021). Smart tourism: A review of AI applications and ethical considerations. Sustainability, 13(2), 847. https://doi.org/10.3390/su13020847
[4] Li, X., & Yang, Y. (2022). Challenges and prospects of AI-driven smart tourism in China. Journal of Hospitality and Tourism Technology, 13(3), 455-472. https://doi.org/10.1108/JHTT-01-2022-0015
[5] Xu, F., & Gursoy, D. (2020). Artificial intelligence and robotics in tourism and hospitality: Current applications and future trends. Tourism Economics, 26(4), 729-746. https://doi.org/10.1177/1354816619877582
[6] Zhang, L., & Zhang, J. (2020). Development and application of artificial intelligence in smart tourism. Journal of Tourism Studies, 35(4), 56-67.
[7] DeFillippi, R. J., & Arthur, M. B. (1994). The Boundaryless Career: A Competency-Based Perspective. Journal of Organizational Behavior, 15(4), 307-324.
[8] Bandura, A. (1986). Social foundations of thought and action: A social cognitive theory. Prentice-Hall.
[9] Lengrand, P. (1965). An Introduction to Lifelong Education. UNESCO.
[10] McClelland, D. C. (1973). Testing for competence rather than for intelligence. American Psychologist, 28(1), 1-14.
[11] Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340. https://doi.org/10.2307/249008
[12] Arthur, M. B., & Rousseau, D. M. (1996). The boundaryless career: A new employment principle for a new organizational era. Oxford University Press.
[13] Tomlinson, M., Baird, M., Berg, P., & Cooper, R. (2020). Flexible careers across the life course: Advancing theory, research and practice. Human Relations, 73(2), 139–157. https://doi.org/10.1177/0018726719878105
[14] Lent, R. W., Brown, S. D., & Hackett, G. (1994). Toward a unifying social cognitive theory of career and academic interest, choice, and performance. Journal of Vocational Behavior, 45(1), 79–122. https://doi.org/10.1006/jvbe.1994.1027
[15] Zhou, L., Mou, J., Cui, Y., & Wu, Y. (2021). Smart tourism research: A social science perspective. Annals of Tourism Research, 87, 103141. https://doi.org/10.1016/j.annals.2021.1031
[16] Candy, P. C. (1991). Self-direction for lifelong learning: A comprehensive guide to theory and practice. Jossey-Bass.
[17] Illeris, K. (2017). How we learn: Learning and non-learning in school and beyond (2nd ed.). Routledge. https://doi.org/10.4324/9781315147277
[18] Jain, S., Aggarwal, A., & Sharma, V. (2020). Artificial intelligence in tourism: A review of applications and future research directions. Tourism Review, 75(1), 1–17. https://doi.org/10.1108/TR-06-2019-0220
[19] Kyndt, E., & Baert, H. (2015). Learning conditions for non-formal and informal workplace learning. Journal of Workplace Learning, 27(4), 250–275. https://doi.org/10.1108/JWL-05-2014-0045
[20] Kaban, R. H., Anzelina, D., Sinaga, R., & Silaban, P. J. (2021). Pengaruh Model Pembelajaran PAKEM terhadap Hasil Belajar Siswa di Sekolah Dasar. Jurnal Basicedu, 5(1), 102-109.
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