Downloads

Ge, Y., Chen, P., & Marimuthu, A. (2026). The Dual Cognitive and Emotional Pathways Linking AI Awareness and Knowledge Sharing Intention: Evidence from Private Higher Education Institutions in China. Economics & Management Information, 5(2), 0014. https://doi.org/10.62836/emi.v5i2.0014

The Dual Cognitive and Emotional Pathways Linking AI Awareness and Knowledge Sharing Intention: Evidence from Private Higher Education Institutions in China

Purpose: This study seeks to explore how artificial intelligence awareness (AIA) affects the knowledge sharing intention (KSI) of faculty in Chinese private universities via dual cognitive and emotional pathways, while also assessing the moderating role of organisational change adaptability (OCAD) in this relationship, thereby clarifying the dynamics of knowledge behaviour transformation within educational institutions amid technological empowerment. Design/methodology/approach: This research utilises a quantitative methodology, gathering data from faculty members of private universities in China using online surveys. A dual-path mechanism model is developed, grounded in the TPB and JD-R frameworks, to examine the influence of AIA on KSI, incorporating OCA as a moderating component. A hierarchical model analysis technique (Model 1–Model 5) is employed, integrating PLS-SEM and OLS regression to validate hypotheses and investigate mediating and moderating effects, therefore systematically elucidating the underlying mechanisms. Findings: The results demonstrate that Artificial Intelligence Awareness (AIA) has a significant and beneficial effect on Attitude Towards Knowledge Sharing (ATKS) and Knowledge Sharing Intention (KSI), while also indirectly enhancing KSI by mitigating Emotional Exhaustion (EE). Organisational Change Adaptability (OCA) significantly moderates the association between AIA and ATKS, but does not significantly affect the relationship between AIA and EE. This indicates that educators’ understanding of AI influences their desire to share knowledge via cognitive and emotional channels, while their adaptation to organisational change significantly contributes to this dynamic. Originality/value: This paper develops a theoretical model that synthesises cognition, attitude, emotion, and organisational regulation at the nexus of AI awareness and information sharing. This study elucidates the impact of AI awareness on knowledge-sharing intentions via cognitive and emotional channels, delineates the moderating effect of organisational change adaptability, and expands the theoretical framework of educational technology adoption and knowledge management. This study offers novel insights into the psychological dynamics of knowledge workers towards rising technology.

artificial intelligence awareness knowledge sharing intention organizational change adaptability TPB JD-R

References

  1. Slimi Z, Villarejo Carballido B. Navigating the Ethical Challenges of Artificial Intelligence in Higher Education: An Analysis of Seven Global AI Ethics Policies. TEM Journal 2023; 590–602. https://doi.org/10.18421/TEM122-02.
  2. Levin RC. Online Learning & the Transformation of Global Higher Education. Daedalus 2024; 153(2): 262–274. https://doi.org/10.1162/daed_a_02079.
  3. Marimuthu A, Arokiasamy L. The Study on Knowledge Management Process, and Knowledge Management Enablers towards Sustainability of Private University: A Literature Review. International Journal of Early Childhood Special Education 2022; 14(3).
  4. Israilidis J, Siachou E, Kelly S. Why Organizations Fail to Share Knowledge: An Empirical Investigation and Opportunities for Improvement. Information Technology & People 2021; 34(5): 1513–1539. https://doi.org/10.1108/ITP-02-2019-0058.
  5. Lima LADO, Fonseca JFVD, Oliveira VBD; et al. The use of Artificial Intelligence (AI) in the School Environment: Implications for the Teaching and Learning Process. In Navigating Through the Knowledge of Education, 1st ed.; Seven Editora: São José dos Pinhais, Brazil, 2024. https://sevenpublicacoes.com.br/index.php/editora/article/view/3900.
  6. Sadykova G, Kayumova A. Educators’ Perception of Artificial Intelligence as Instructional Tool. TEM Journal 2024; 3194–3204. https://doi.org/10.18421/TEM134-54.
  7. Cahyaningtyas VE, Nuvriasari A. Study of Innovative Behavior in Terms of Leadership Roles, Organizational Culture and Knowledge Sharing. East Asian Journal of Multidisciplinary Research 2024; 3(2): 949–960. https://doi.org/10.55927/eajmr.v3i2.7865.
  8. Rahman S, Hossain M, Islam MZ; et al. Linkage between Culture, Leadership, and Knowledge Sharing in MNCs. Journal of Global Information Management 2022; 30(1): 1–21. https://doi.org/10.4018/JGIM.301200.
  9. Vallery Imanuel P, Sugiharti T. Hubungan Antara Kepemimpinan Diri, Berbagi Pengetahuan, Dan Perilaku Kerja Inovatif di Lembaga Pendidikan Tinggi. Jurnal Pendidikan Dan Kewarganegara Indonesia 2025; 2(1): 61–68. https://doi.org/10.61132/jupenkei.v2i1.154.
  10. Zhao S, Dong Y, Luo J. Profiles of Teacher Professional Identity among Student Teachers and Its Association with Mental Health. Frontiers in Public Health 2022; 10: 735811. https://doi.org/10.3389/fpubh.735811.
  11. Hammad T. Exploring the Intersection of AI and Emotional Intelligence: Navigating the Promise and Peril. (Unpublished manuscript).
  12. Li C, Zhang Y, Niu X; et al. Does Artificial Intelligence Promote or Inhibit on-the-Job Learning? Human Reactions to AI at work. Systems 2023; 11(3): 114. https://doi.org/10.3390/systems11030114.
  13. Li W, Zhang X, Li J; et al. An Explanatory Study of Factors Influencing Engagement in AI Education at the K-12 Level: An Extension of the Classic TAM Model. Scientific Reports 2024; 14(1): 13922. https://doi.org/10.1038/s41598-024-64363-3.
  14. Xu G, Xue M, Zhao J. The Association between Artificial Intelligence Awareness and Employee Depression: The Mediating Role of Emotional Exhaustion and the Moderating Role of Perceived Organizational Support. International Journal of Environmental Research and Public Health 2023; 20(6): 5147. https://doi.org/10.3390/ijerph20065147.
  15. Hızarcı AK, Tarier A, Özgen Ö; et al. Understanding the Role of Artificial Intelligence in the Context of SMEs. Uluslararası Anadolu Sosyal Bilimler Dergisi 2024; 8(4): 970–995. https://doi.org/10.47525/ulasbid.1572700.
  16. Riyadi S, Helmita A, Anggoro Y. The Effect of Change Management on Organizational Adaptability in the Age of Technology. Maneggio 2024; 1(5): 85–97. https://doi.org/10.62872/7dn4vx41.
  17. Nikitina I, Ishchenko T. The Impact of AI on Teachers: Support or Replacement? Scientific Journal of Polonia University 2024; 65(4): 93–99. https://doi.org/10.23856/6511.
  18. Ajzen I. The Theory of Planned Behavior. Organizational Behavior and Human Decision Processes 1991; 50(2): 179–211. https://doi.org/10.1016/0749-5978(91)90020-T.
  19. Moreno V, Cavazotte F, Dutra JP. Antecedentes Psicossociais e Organizacionais do Compartilhamento de Conhecimento no Ambiente de Trabalho. Revista de Administração Contemporânea 2020; 24(4), 283–299. https://doi.org/10.1590/1982-7849rac2020190239.
  20. Pham Thi TD, Duong NT. A Study on Knowledge Sharing Behavior among IT Engineers: An Extended Theory of Planned Behavior. Human Behavior and Emerging Technologies 2022; 2022: 1–14. https://doi.org/10.1155/2022/2376811.
  21. Bakker AB, Demerouti E. The Job Demands-Resources Model: State of the Art. Journal of Managerial Psychology 2007; 22(3): 309–328. https://doi.org/10.1108/02683940710733115.
  22. Brougham D, Haar J. Smart Technology, Artificial Intelligence, Robotics, and Algorithms (STARA): Employees’ Perceptions of Our Future Workplace. Journal of Management & Organization 2018; 24(2): 239–257. https://doi.org/10.1017/jmo.2016.55.
  23. Bock GW, Zmud RW, Kim YG; et al. Behavioral Intention Formation in Knowledge Sharing: Examining the Roles of Extrinsic Motivators, Social-Psychological Forces, and Organizational Climate. MIS Quarterly 2005; 29(1): 87–111. https://doi.org/10.2307/25148669.
  24. Hassan M, Aksel I, Nawaz MS; et al. Knowledge Sharing Behavior of Business Teachers of Pakistani Universities: An Empirical Testing of Theory of Planned Behavior. European Scientific Journal 2016; 12(13): 29. https://doi.org/10.19044/esj.2016.v12n13p29.
  25. Maslach C, Jackson SE. The Measurement of Experienced Burnout. Journal of Organizational Behavior 1981; 2(2): 99–113. https://doi.org/10.1002/job.4030020205.
  26. Adams C, Pente P, Lemermeyer G; et al. Artificial Intelligence and Teachers’ New Ethical Obligations. The International Review of Information Ethics 2022; 31(1). https://doi.org/10.29173/irie483.
  27. Wahyuni P. Predicting Knowledge Sharing Intention Based on Theory of Reasoned Action Framework: An Empirical Study on Higher Education Institution. 2013. (Unpublished master’s thesis).
  28. Oreg S. Resistance to Change: Developing an Individual Differences Measure. Journal of Applied Psychology 2003; 88(4): 680–693. https://doi.org/10.1037/0021-9010.88.4.680.
  29. Pahkin K, Nielsen K, Väänänen A; et al. Importance of Change Appraisal for Employee Well-Being during Organizational Restructuring: Findings from the Finnish Paper Industry’s Extensive Transition. Industrial Health 2014; 52(5): 445–455. https://doi.org/10.2486/indhealth.2014-0044.
  30. Kumi E, Osei HV, Asumah S; et al. The Impact of Technology Readiness and Adapting Behaviours in the Workplace: A Mediating Effect of Career Adaptability. Future Business Journal 2024; 10(1): 63. https://doi.org/10.1186/s43093-024-00355-z.
  31. Canossa-Montes de Oca H, Peraza-Villarreal N. Gestión del Talento Humano en la era de la Inteligencia Artificial: Retos y Oportunidades en el Entorno Laboral. 593 Digital Publisher CEIT 2024; 9(1): 302–319. https://doi.org/10.33386/593dp.2024.1.2170.
  32. Chen SS, Chuang YW, Chen PY. Behavioral Intention Formation in Knowledge Sharing: Examining the Roles of KMS Quality, KMS Self-Efficacy, and Organizational Climate. Knowledge-Based Systems 2012; 31: 106–118. https://doi.org/10.1016/j.knosys.2012.02.001.
  33. Khine TH. Effect of Teachers’ Attitudes on Behavioral Intentions toward the New Curriculum Implementation: Mediating Role of Perceived Behavioral Control. International Journal of Educational Management and Development Studies 2022; 3(4): 154–172. https://doi.org/10.53378/352952.
  34. Tamayo MR, Tróccoli BT. Exaustão Emocional: Relações com a Percepção de Suporte Organizacional e com as Estratégias de Coping no Trabalho. Estudos de Psicologia 2002; 7(1): 37–46. https://doi.org/10.1590/S1413-294X2002000100005.
  35. Ain NU, Azeem MU, Haq IU; et al. When Does Knowledge Hiding Hinder Employees’ Job Performance? The Roles of Emotional Exhaustion and Emotional Intelligence. Knowledge Management Research & Practice 2024; 22(2): 210–222. https://doi.org/10.1080/14778238.2023.2297972.
  36. Van Dam K. Employee Adaptability to Change at Work: A Multidimensional, Resource-Based Framework. In The Psychology of Organizational Change; Oreg S, Michel ART, Eds.; Cambridge University Press: Cambridge, UK, 2013; pp. 123–142. https://doi.org/10.1017/CBO9781139096690.007.
  37. Kodden B. The Ability to Adapt. In The Art of Sustainable Performance; Kodden B, Ed.; Springer: Berlin, Germany, 2020; pp. 25–30. https://doi.org/10.1007/978-3-030-46463-9_4.
  38. Jussupow E, Spohrer K, Heinzl A. Identity Threats as a Reason for Resistance to Artificial Intelligence: Survey Study with Medical Students and Professionals. JMIR Formative Research 2022; 6(3): e28750. https://doi.org/10.2196/28750.
  39. Zheng J, Zhang T. Association between AI Awareness and Emotional Exhaustion: The Serial Mediation of Job Insecurity and Work Interference with Family. Behavioral Sciences 2025; 15(4): 401. https://doi.org/10.3390/bs15040401.
  40. Ng W. Can We Teach Digital Natives Digital Literacy? Computers & Education 2018; 123: 106–117. https://doi.org/10.1016/j.compedu.2018.04.002.
  41. Watkins MB, Ren R, Umphress EE; et al. Compassion Organizing: Employees’ Satisfaction with Corporate Philanthropic Disaster Response and Reduced Job Strain. Journal of Occupational and Organizational Psychology 2015; 88(2): 436–458. https://doi.org/10.1111/joop.12088.
  42. Hair JF, Hult GTM, Ringle CM; et al. A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM), 2nd ed.; SAGE: Sauzende Oaks, CA, USA, 2017.
  43. Hamal O, El Faddouli NE, Harouni MHA; et al. Artificial Intelligent in Education. Sustainability 2022; 14(5): 2862. https://doi.org/10.3390/su14052862.
  44. Wang P, Xie H. Application and Exploration of Artificial Intelligence in Teaching and Learning in Private Colleges and Universities. World Journal of Education and Humanities 2024; 6(3): 26. https://doi.org/10.22158/wjeh.v6n3p26.

Supporting Agencies

  1. Funding: This research received no external funding.