Enhancing Corporate Performance Through Transformational Leadership in AI-driven ERP Systems
Yang Zhang 1,
Fei Huang 2 * More Detail
1 Ph.D candidate, School of Management, Seoul School of Integrated Sciences and Technologies, Seoul, Republic of Korea
2 Assistant Professor, School of Management, Seoul School of Integrated Sciences and Technologies, Seoul, Republic of Korea
* Corresponding Author
Journal of Information Systems Engineering and Management, 2024 - Volume 9 Issue 2, Article No: 24844
https://doi.org/10.55267/iadt.07.14797
Published Online: 26 Apr 2024
Views: 169 | Downloads: 240
APA 6th edition
In-text citation: (Zhang & Huang, 2024)
Reference: Zhang, Y., & Huang, F. (2024). Enhancing Corporate Performance Through Transformational Leadership in AI-driven ERP Systems.
Journal of Information Systems Engineering and Management, 9(2), 24844.
https://doi.org/10.55267/iadt.07.14797
Vancouver
In-text citation: (1), (2), (3), etc.
Reference: Zhang Y, Huang F. Enhancing Corporate Performance Through Transformational Leadership in AI-driven ERP Systems. J INFORM SYSTEMS ENG. 2024;9(2):24844.
https://doi.org/10.55267/iadt.07.14797
AMA 10th edition
In-text citation: (1), (2), (3), etc.
Reference: Zhang Y, Huang F. Enhancing Corporate Performance Through Transformational Leadership in AI-driven ERP Systems.
J INFORM SYSTEMS ENG. 2024;9(2), 24844.
https://doi.org/10.55267/iadt.07.14797
Chicago
In-text citation: (Zhang and Huang, 2024)
Reference: Zhang, Yang, and Fei Huang. "Enhancing Corporate Performance Through Transformational Leadership in AI-driven ERP Systems".
Journal of Information Systems Engineering and Management 2024 9 no. 2 (2024): 24844.
https://doi.org/10.55267/iadt.07.14797
Harvard
In-text citation: (Zhang and Huang, 2024)
Reference: Zhang, Y., and Huang, F. (2024). Enhancing Corporate Performance Through Transformational Leadership in AI-driven ERP Systems.
Journal of Information Systems Engineering and Management, 9(2), 24844.
https://doi.org/10.55267/iadt.07.14797
MLA
In-text citation: (Zhang and Huang, 2024)
Reference: Zhang, Yang et al. "Enhancing Corporate Performance Through Transformational Leadership in AI-driven ERP Systems".
Journal of Information Systems Engineering and Management, vol. 9, no. 2, 2024, 24844.
https://doi.org/10.55267/iadt.07.14797
Organisational traits, technological adoption, and transformative leadership in Chinese enterprises are examined in this study using a dataset 2010–2022. The main goal is to understand how transformative leadership affects business performance and how AI-driven ERP systems, organisational scale, and technology adoption culture modulate this relationship. The paper provides a solid framework for understanding these complex linkages using a big dataset using R and SPSS statistical analysis. Revolutionary leadership consistently boosts business. Organisational size mediates and revolutionary leadership may work better in larger organisations. Technology adoption culture highlights an organization's readiness to accept new technology, regulating the relationship. The study also found that AI-driven ERP systems diminish the correlation, suggesting that higher-tech organisations benefit from transformational leadership. This information can help CEOs adjust their technology and company characteristics strategies. Leadership theories benefit from theoretical implications that highlight contextual aspects that affect leadership dynamics. Understanding how organisational culture affects AI-driven revolutionary leadership may also help. Integrating AI and ethical transformative leadership affects sustainability and trust. Finally, the innovative leadership of AI-driven ERP systems in numerous areas and sizes explains it.
- Abuhantash, A. (2023). The impact of human resource information systems on organizational performance: A systematic literature review. European Journal of Business and Management Research, 8(3), 239-245.
- Aldoseri, A., Al-Khalifa, K. N., & Hamouda, A. M. (2023). Re-thinking data strategy and integration for artificial intelligence: concepts, opportunities, and challenges. Applied Sciences, 13(12), 7082.
- Al-Husseini, S., El Beltagi, I., & Moizer, J. (2021). Transformational leadership and innovation: The mediating role of knowledge sharing amongst higher education faculty. International Journal of Leadership in Education, 24(5), 670-693.
- Al-Surmi, A., Bashiri, M., & Koliousis, I. (2022). AI based decision making: combining strategies to improve operational performance. International Journal of Production Research, 60(14), 4464-4486.
- Ångström, R. C., Björn, M., Dahlander, L., Mähring, M., & Wallin, M. W. (2023). Getting AI Implementation Right: Insights from a Global Survey. California Management Review, 66(1), 5-22.
- Auh, S., Menguc, B., Sainam, P., & Jung, Y. S. (2022). The missing link between analytics readiness and service firm performance. Service Industries Journal, 42(3-4), 148-177.
- Baiyere, A., Salmela, H., & Tapanainen, T. (2020). Digital transformation and the new logics of business process management. European Journal of Information Systems, 29(3), 238-259.
- Bunod, R., Augstburger, E., Brasnu, E., Labbe, A., & Baudouin, C. (2022). Artificial intelligence and glaucoma: A literature review. Journal Francais D'ophtalmologie, 45(2), 216-232.
- Bustinza, O. F., Vendrell-Herrero, F., Perez-Arostegui, M., & Parry, G. (2019). Technological capabilities, resilience capabilities and organizational effectiveness. International Journal of Human Resource Management, 30(8), 1370-1392.
- Cadden, T., Dennehy, D., Mantymaki, M., & Treacy, R. (2022). Understanding the influential and mediating role of cultural enablers of AI integration to supply chain. International Journal of Production Research, 60(14), 4592-4620.
- Chau, K. Y., Tang, Y. M., Liu, X., Ip, Y. K., & Tao, Y. (2021). Investigation of critical success factors for improving supply chain quality management in manufacturing. Enterprise Information Systems, 15(10), 1418-1437.
- Grover, P., Kar, A. K., & Dwivedi, Y. K. (2022). Understanding artificial intelligence adoption in operations management: Insights from the review of academic literature and social media discussions. Annals of Operations Research, 308(1), 177-213.
- Har, L. L., Rashid, U. K., Chuan, L. Te, Sen, S. C., & Xia, L. Y. (2022). Revolution of retail industry: From perspective of retail 1.0 to 4.0. Procedia Computer Science, 200(2019), 1615-1625.
- Jöhnk, J., Weißert, M., & Wyrtki, K. (2021). Ready or Not, AI Comes—An interview study of organizational AI readiness factors. Business and Information Systems Engineering, 63(1), 5-20.
- Kucharska, W., & Rebelo, T. (2022). Transformational leadership for researcher’s innovativeness in the context of tacit knowledge and change adaptability. International Journal of Leadership in Education, 1-22. https://doi.org/10.1080/13603124.2022.2068189
- Libai, B., Bart, Y., Gensler, S., Hofacker, C. F., Kaplan, A., Kötterheinrich, K., & Kroll, E. B. (2020). Brave new world? On AI and the management of customer relationships. Journal of Interactive Marketing, 51, 44-56.
- Madan, R., & Ashok, M. (2023). AI adoption and diffusion in public administration: A systematic literature review and future research agenda. Government Information Quarterly, 40(1), 101774.
- Mao, H., Zhang, T., & Tang, Q. (2021). Research framework for determining how artificial intelligence enables information technology service management for business model resilience. Sustainability (Switzerland), 13(20). https://doi.org/10.3390/su132011496
- Martínez-Peláez, R., Ochoa-Brust, A., Rivera, S., Félix, V. G., Ostos, R., Brito, H., . . . Mena, L. J. (2023). Role of digital transformation for achieving sustainability: Mediated role of stakeholders, key capabilities, and technology. Sustainability, 15(14), 11221.
- Nazir, M. A., & Khan, M. R. (2022). Identification of roles and factors influencing the adoption of ICTs in the SMEs of Pakistan by using an extended Technology Acceptance Model (TAM). Innovation and Development, August, 1-27. https://doi.org/10.1080/2157930X.2022.2116785
- Nuerk, J., & Dařena, F. (2023). Activating supply chain business models’ value potentials through Systems Engineering. Systems Engineering, 26(5), 660-674.
- Raoof, R., Basheer, M. F., Javeria, S., Ghulam Hassan, S., & Jabeen, S. (2021). Enterprise resource planning, entrepreneurial orientation, and the performance of SMEs in a South Asian economy: The mediating role of organizational excellence. Cogent Business and Management, 8(1). https://doi.org/10.1080/23311975.2021.1973236
- Sallam, K., Mohamed, M., & Mohamed, A. W. (2023). Internet of Things (IoT) in supply chain management: Challenges, opportunities, and best practices. Sustainable Machine Intelligence Journal, 2. https://doi.org/10.61185/SMIJ.2023.22103
- Sjödin, D., Parida, V., Palmié, M., & Wincent, J. (2021). How AI capabilities enable business model innovation: Scaling AI through co-evolutionary processes and feedback loops. Journal of Business Research, 134, 574-587.
- Tajasom, A., Hung, D. K. M., Nikbin, D., & Hyun, S. S. (2015). The role of transformational leadership in innovation performance of Malaysian SMEs. Asian Journal of Technology Innovation, 23(2), 172-188.
- Van Nguyen, T., Pham, H. T., Ha, H. M., & Tran, T. T. T. (2022). An integrated model of supply chain quality management, Industry 3.5 and innovation to improve manufacturers’ performance—A case study of Vietnam. International Journal of Logistics Research and Applications, 1-23. https://doi.org/10.1080/13675567.2022.2059457
- Yousra, M., & Khalid, C. (2021). Analysis of the variables of intention of the adoption and acceptance of artificial intelligence and big data tools among leaders of organizations in Morocco: Attempt of a theoretical study. European Scientific Journal, 17(29), 106-127.
- Zulu, S. L., & Khosrowshahi, F. (2021). A taxonomy of digital leadership in the construction industry. Construction Management and Economics, 39(7), 565-578.
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