Research Article
Open access
Published on 26 December 2024
Download pdf
Liu,Y.;Zhang,Y. (2024). AI-Mediated Leadership and New Employee Onboarding: Applying Expectation Violation Theory to Understand Acceptance of AI Avatars. Journal of Applied Economics and Policy Studies,15,1-5.
Export citation

AI-Mediated Leadership and New Employee Onboarding: Applying Expectation Violation Theory to Understand Acceptance of AI Avatars

Yichen Liu *,1, Yaqi Zhang 2
  • 1 School of Journalism and Communication, Nanjing Normal University, Nanjing, 210023, China
  • 2 Soochow University

* Author to whom correspondence should be addressed.

https://doi.org/10.54254/2977-5701/2024.19658

Abstract

This paper explores the role of AI avatars as an emerging form of interaction in organizational management, especially the research gap in the acceptance and interaction patterns of AI avatars in the context of new employee organization socialization. Through a structured questionnaire and quantitative analysis with a Likert scale, we discuss the impact of the Expectation Violation Theory (EVT) and the Technology Acceptance Model (TAM) on the socialization of new employees.

Keywords

AI avatars, socialization, Expectation Violation Theory (EVT), Technology Acceptance Model (TAM)

[1]. Bevan, J. L., Ang, P.-C., & Fearns, J. B. (2014). Being unfriended on Facebook: An application of Expectancy Violation Theory. Computers in Human Behavior, 33, 171–178. https://doi.org/10.1016/j.chb.2014.01.029

[2]. Bryman, A. (2016). Social research methods. Oxford university press.

[3]. Burgoon, J. K. (1978). A communication model of personal space violations: Explication and an initial test. Human Communication Research, 4(2), 129-142.

[4]. Chu, A. Z.-C.& Chu, R. J.-C. (2011). The intranet's role in newcomer socialization in the hotel industry in Taiwan – technology acceptance model analysis. The International Journal of Human Resource Management, 22(05), 1163-1179. https://doi.org/10.1080/09585192.2011.556795

[5]. Cohen, J. (2013). Statistical power analysis for the behavioral sciences. routledge.

[6]. Creswell, J. W., & Creswell, J. D. (2017). Research design: Qualitative, quantitative, and mixed methods approaches. Sage publications.

[7]. Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319-340.

[8]. Denzin, N. K., & Lincoln, Y. S. (Eds.). (2011). The Sage handbook of qualitative research. sage.

[9]. Dillman, D. A., Smyth, J. D., & Christian, L. M. (2014). Internet, phone, mail, and mixed-mode surveys: The tailored design method. John Wiley & Sons

[10]. Fan, F., Fu, L., & Jiang, Q. (2023). Virtual idols vs online influencers vs traditional celebrities: How young consumers respond to their endorsement advertising. Young Consumers. https://doi.org/10.1108/YC-08-2023-1811

[11]. Fishbein, M., & Ajzen, I. (2011). Predicting and changing behavior: The reasoned action approach. Psychology press.

[12]. Fowler Jr, F. J. (2013). Survey research methods. Sage publications.

[13]. Gursoy, D., Chi, O. H., Lu, L., & Nunkoo, R. (2019). Consumers acceptance of artificially intelligent (AI) device use in service delivery. International Journal of Information Management, 49, 157-169.

[14]. Gong, W., Jung, J., & Lim, J. S. (2022). Exploring parasocial relationships with AI-powered virtual influencers: An expectancy violation perspective. Frontiers in Psychology, 13, 993935.

[15]. Hutson, J., Ratican, J., & Biri, C. (2023). Essence as Algorithm: Public Perceptions of AI-Powered Avatars of Real People. DS Journal of Artificial Intelligence and Robotics, 1(2), 1-14. https://doi.org/10.59232/AIR-V1I2P101

[16]. Lee, S. K., Kramer, M. W., & Guo, Y. (2019). Social media affordances in entry-level employees’ socialization: Employee agency in the management of their professional impressions and vulnerability during early stages of socialization. New Technology, Work and Employment, 34(3), 244-259. https://doi.org/10.1111/ntwe.12147

[17]. Levin, K. A. (2006). Study design III: Cross-sectional studies. Evidence-based dentistry, 7(1), 24-25.

[18]. Lichtenthaler, U. (2020). Extremes of acceptance: Employee attitudes toward artificial intelligence. Journal of Business Strategy, 41(5), 39-45. DOI: 10.1108/JBS-12-2018-0204

[19]. Likert, R. (1932). A technique for the measurement of attitudes. Archives of psychology.

[20]. Lohr, S. L. (2021). Sampling: design and analysis. Chapman and Hall/CRC.

[21]. Na, S., Heo, S., Han, S., Shin, Y., & Roh, Y. (2022). Acceptance Model of Artificial Intelligence (AI)-Based Technologies in Construction Firms: Applying the Technology Acceptance Model (TAM) in Combination with the Technology–Organisation–Environment (TOE) Framework. Buildings, 12(2)

[22]. Petrat, D., Yenice, I., Bier, L., & Subtil, I. (2022). Acceptance of artificial intelligence as organizational leadership: A survey. TATuP - Zeitschrift für Technikfolgenabschätzung in Theorie und Praxis / Journal for Technology Assessment in Theory and Practice, 31(2), 64-69. https://doi.org/10.14512/tatup.31.2.64

[23]. Peña, J., et al. (2023). Virtual leaders: Can customizing authoritarian and democratic business leader avatars influence altruistic behavior and leadership empowerment perceptions? Computers in Human Behavior, 141, 107616.

[24]. Peifer, Y., et al. (2022). Artificial Intelligence and its Impact on Leaders and Leadership. Procedia Computer Science, 200, 1024–1030.

[25]. Sharma, M., & Vemuri, K. (2022). Accepting Human-like Avatars in Social and Professional Roles. ACM Transactions on Human-Robot Interaction, 11(3), Article 28. https://doi.org/10.1145/3526026

[26]. Smith, A. M., & Green, M. (2018). Artificial Intelligence and the Role of Leadership. Journal of Leadership Studies, 12(3), 85-87. DOI:10.1002/jls.21605

[27]. Song, Q., Wang, Y., Chen, Y., Benitez, J., & Hu, J. (2019). Impact of the usage of social media in the workplace on team and employee performance. Information & Management, 56(103160). https://doi.org/10.1016/j.im.2019.04.003

[28]. Venkatesh, V., Thong, J. Y., & Xu, X. (2012). Consumer acceptance and use of information technology: extending the unified theory of acceptance and use of technology. MIS quarterly, 157-178.

[29]. Warfield, D. (2015). Expectancy violations theory. In C. R. Berger & M. E. Roloff (Eds.), The International Encyclopedia of Interpersonal Communication (pp. 1-9). John Wiley & Sons.

Cite this article

Liu,Y.;Zhang,Y. (2024). AI-Mediated Leadership and New Employee Onboarding: Applying Expectation Violation Theory to Understand Acceptance of AI Avatars. Journal of Applied Economics and Policy Studies,15,1-5.

Data availability

The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.

Disclaimer/Publisher's Note

The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of EWA Publishing and/or the editor(s). EWA Publishing and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

About volume

Journal:Journal of Applied Economics and Policy Studies

Volume number: Vol.15
ISSN:2977-5701(Print) / 2977-571X(Online)

© 2024 by the author(s). Licensee EWA Publishing, Oxford, UK. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license. Authors who publish this series agree to the following terms:
1. Authors retain copyright and grant the series right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this series.
2. Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the series's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this series.
3. Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See Open access policy for details).