Predicting the innovative behavior of employees of technology companies based on the application of artificial intelligence

Document Type : Original Article

Authors

1 Assistant Professor, Department of Information Technology Engineering, Payame Noor University, Tehran, Iran

2 M.A. in Information Technology Management, Payame Noor University, Tehran, Iran

Abstract

This article was purposed at examining the impact of the use of artificial intelligence on the innovative behavior of employees of technology companies. Research method, descriptive and of the type of correlation with the statistical population including all employees of technology companies in Ilam province with a number of 716 people, Which for the required sample size determination, using Krejcie and Morgan Table (1970), 256 people were selected by the available sampling method. Data collection tools were standard AI questionnaires by Chen et al. (2022, translated by Fergie et al., 1402) and the Jensen questionnaire of employees innovative behavior questionnaire (2000). Descriptive findings showed that the application of artificial intelligence and innovative behavior among employees of technology companies and their components is at a higher than average level. Also, the results of the Pearson correlation coefficient test also showed that at a meaningful level of 05/0, There is a meaningful and direct relationship between the application of artificial intelligence and the innovative behavior of employees of technology companies. Similarly, the results of the structural model of the research showed that in the research model, the hypothetical model of relative intermediation has a favorable effect on the innovative behavior of employees of technology companies with data. Additionally, in the hypothetical model, all the coefficients of the model path were statistically significant, and the use of artificial intelligence has a significant positive and direct impact on the innovative behavior of employees of technology companies to the extent of the effect of 0/823.  Therefore, in explaining the desired performance of employees in innovative behavior, the necessity and examination of the acceptance of artificial intelligence among employees is suggested.

Keywords

References

Ahmadi, H, Nouri, A & Ganjeh, A. (2016). Modeling the impact of work culture on innovative behavior and organizational performance of elementary school teachers in Ardabil using structural equation modeling. 4th Scientific-Research Conference on Educational Sciences and
Psychology of Social and Cultural Harms in Iran [In Persian]
Alizadeh, H, Nazarpourkashani, H, Jalali Filshoor, M & Pourjabari Khamneh, A. H. (2023). Predicting consumer behavior based on artificial intelligence marketing. National Conference on Management Research and Humanities in Iran [In Persian]
Bakrizadeh, H, Panahi, M & Jamalvandi, B. (2023). The role of digital literacy in technology acceptance among Payame Noor University librarians. Journal of Technology and Knowledge in Education, 3(2), 27–38 [In Persian]
Battistelli, Adalgisa; Odoardi, C; Vandenberghe, C; Di Napoli, G & Piccione, L. (2019). Information sharing and innovative work behavior: The role of work-based learning, challenging tasks, and organizational commitment. Human Resource Development Quarterly, 30(3), 361–381.
Bauwens, R. (2022). The Impact of Employee Usage of Generative AI on Innovative Work Behavior and the Mediating Role of Self-Efficacy.
Biranvand, A, Zarei, S & Golshani, M. (2020). Impact of organizational climate and knowledge sharing on innovative behavior of employees in knowledge-based companies. Interaction of Human and Information, 7(4), 15–29 [In Persian]
Brynjolfsson, E. Rock, D & Syverson, C. (2021). The productivity J-Curve: How intangibles complement general purpose technologies. American Economic Journal: Macroeconomics, 13(1), 333–372.
Chaubey, A. Sahoo, C. K & Khatri, N. (2019). Relationship of transformational leadership with employee creativity and organizational innovation: A study of mediating and moderating influences. Journal of Strategy and Management, 12(1), 61-82.
Dovali, M & Nohegar, S. (2024). The impact of artificial intelligence on employee performance and work engagement: Moderating role of change leadership. Journal of Organizational Development of Police, 21(1), 46–59 [In Persian]
Ebrahimpour, H, Taghavi, J, Zahed Babolan, A & Moeini Kia, M. (2015). Examining the relationship between learning climate and innovative behavior of elementary school teachers. 1st Scientific-Research Conference on Educational Sciences and Psychology of Social and Cultural Harms in Iran [In Persian]
Ghazalsaflo, H. R. (2023). Challenges and opportunities of using artificial intelligence in human resource management. Journal of Technology in Entrepreneurship and Strategic Management, 2(2), 21–27 [In Persian]
Ghosh, B. Daugherty, P. Wilson, J & Burden, A. (2019). Taking a systems approach to adopting AI. Harvard Business Review, 5(9), 2 .Glikson, E & Woolley, A. W. (2020). Human trust in artificial intelligence: Review of empirical research. The Academy of Management Annals, 14(2), 627–660.
Glikson, E & Woolley, A. W. (2020). Human trust in artificial intelligence:
Hu, Q. Lu, Y. Pan, Z. Gong, Y & Yang, Z. (2021). Can AI artifacts influence human cognition? The effects of artificial autonomy in intelligent personal assistants.
Ivancevich, K and Matteson. (2016). Organizational Behavior & Management. McGraw-Hill Education, 11 edition.
Jadidi Mohammadabadi, A. (2022). Effectiveness of social networks on aggression and creative thinking of female high school students in Yazd. Journal of Technology and Knowledge in Education, 3(2), 17–24 [In Persian]
Kandeepan, V. (2016). Employee Bootlegging behavior of non academic staff members in theuniversity system of sri lanka: a case study in university of jaffna. International Journal of Information Research and Review, 3(1), 1710-1716.
Khan, A. N. Jabeen, F. Mehmood, K., Soomro, M. A & Bresciani, S. (2023). Paving the way for technological innovation through adoption of artificial intelligence in conservative industries. Journal of Business Research, 165, 114019.
Kim, Namhyun & Shim, Changsup. (2018b). Social capital, knowledge sharing and innovation of small-and medium-sized enterprises in a tourism cluster. International Journal of Contemporary hospitality.
Li, X. Cheng, M & Xu, J. (2022). Leaders' innovation expectation and nurses' innovation behaviour in conjunction with artificial intelligence: The chain mediation of job control and creative self‐efficacy. Journal of Nursing Management, 30(8), 3806-3816.
Makarius, E. E. Mukherjee, D. Fox, J. D & Fox, A. K. (2020). Rising with the machines: A sociotechnical framework for bringing artificial intelligence into the organization. Journal of Business Research, 120, 262–273.
Matlabi Nejad, A, Fazeli, F & Elham Navaei. (2022). Systematic review of promises and challenges of artificial intelligence for teachers. Journal of Technology and Knowledge in Education, 3(1), 23–44 [In Persian]
Mousavi, S F & Kolak, A. (2022). The effect of employees’ creative self-efficacy on innovative behavior with mediating role of organizational entrepreneurship (Education in Mehr County). Journal of Smart Marketing Management, 30(3), 156–163 [In Persian]
Raisch, S & Krakowski, S. (2020). Artificial intelligence and management: The automation–augmentation paradox. Academy of Management Review, 46(2), 192–210.
Review of empirical research. The Academy of Management Annals, 14(2), 627–660.
Rodriguez, A & Rodriguez, Y. (2015). Metaphors for today’s leadership: VUCA world, millennial and “Cloud Leaders”. Journal of Management Development, 34(7), 854-866.
Saptowinarno, B. Maharani, A & Wihadanto, A. (2024). Factors affecting innovative work behavior in Tech-Company: A review findings using artificial intelligence. Journal of Economics and Business Letters, 4(4), 1-9.
Theurer, Christian P; Tumasjan, Andranik & Welpe, Isabell M. (2018). Contextual work design and employee innovative work behavior: When does autonomy matter? PloS one, 13(10), e0204089.
Verma, S & Singh, V. (2022). Impact of artificial intelligence-enabled job characteristics and perceived substitution crisis on innovative work behavior of employees from high-tech firms. Computers in Human Behavior, 131, 107215.
Vlacic, B. Corbo, L. Silva, S. C. E & Dabic, M. (2021). The evolving role of artificial intelligence in marketing: A review and research agenda. Journal of Business Research, 128, 187–203.
Wilson, J & Daugherty, P. (2018). Collaborative intelligence: Humans and AI are joining forces. Harvard Business Review, 96(4), 114–124.
Wirtz, J. Patterson, G. P. Kunz, H. W. Gruber, T. Lu, V. N. Paluch, S & Martins, A. (2018). Brave new world: Service robots in the frontline. Journal of Service Management, 29(5), 907–931.
Yang, H & Lee, H. (2019). Understanding user behavior of virtual personal assistant devices. Information Systems and e-Business Management, 17(1), 65–87.
Yazdani, M & Rahimian, A. (2024). Effect of AI readiness on job satisfaction with mediating role of AI innovation and perceived threats in Khalaj Gold Stamping Industry. Journal of Accounting and Management Perspectives, 7(88), 107–118 [In Persian]
Yin, M. Jiang, S & Niu, X. (2024). Can AI really help? The double-edged sword effect of AI assistant on employees’ innovation behavior. Computers in Human Behavior, 150, 107987.Brynjolfsson, E. Rock, D & Syverson, C. (2021). The productivity J-Curve: How intangibles complement general purpose technologies. American Economic Journal: Macroeconomics, 13(1), 333–372.

Files

History

  • Receive Date: 27 November 2024
  • Revise Date: 19 January 2025
  • Accept Date: 27 February 2025
  • First Publish Date: 30 May 2025
  • Publish Date: 22 June 2025

Share

How to cite

Statistics