Revolutionizing Organizational Communication in Industry 4.0: Unlocking Opportunities and Overcoming Challenges in Bangladesh
DOI:
https://doi.org/10.15575/jcspi.v2i1.693Keywords:
Industry 4.0, Opportunities and Challenges, Organizational CommunicationAbstract
This paper examines the impact of Industry 4.0 on organizational communication, exploring the opportunities and challenges presented by this revolutionary paradigm shift. The study employs a qualitative research methodology, drawing on academic literature, case studies, and in-depth interviews with national and international organizations. By evaluating the importance of effective communication in the Internet of Things (IoT) era, the paper assesses the opportunities and identifies the challenges of Industry 4.0 in organizational communication. The study delves into the complex relationship between technology and communication, outlining best practices for implementing communication tools and artificial intelligence (AI) in Industry 4.0. Effective communication is crucial for success in Industry 4.0, as it enables individuals to collaborate effectively and share ideas, leading to improved decision-making and problem-solving. However, information overload, miscommunication, and isolation risks must be mitigated to ensure effective communication. Investing in employee training and development, establishing clear communication protocols, and balancing virtual and face-to-face communication can help organizations manage these risks effectively. Mitigating the risks associated with organizational communication in Industry 4.0 is crucial to ensure that organizations can successfully leverage the opportunities presented by this era of digitalization. Recommendations include adopting cybersecurity measures, streamlining communication processes, protecting personal information, ensuring clarity and transparency, regularly updating data security measures, and promoting inclusive communication to overcome social barriers and ensure sustainable organizational communication.
References
Adam, M., Wessel, M., & Benlian, A. (2020). AI-based chatbots in customer service and their effects on user compliance. Electronic Markets, 17, 1–19.
Agrawal, A., Gans, J., & Goldfarb, A. (2018). Prediction machines: The simple economics of artificial intelligence. Harvard Business Review.
Bader, V., & Kaiser, S. (2019). Algorithmic decision-making? The user interface and its role for human involvement in decisions supported by artificial intelligence. Organization, 26(5), 655–672.
Balasubramanian, N., Ye, Y., & Xu, M. (2022). Substituting human decision-making with machine learning: implications for organizational learning. Academy of Management Review, 47(3).
Benbya, H., Davenport, T. H., & Pachidi, S. (2020). Artificial intelligence in organizations: Current state and future opportunities. MIS Quarterly Executive, 19(4), 9–21.
Benbya, H., Nan, N., Tanriverdi, H., & Youngjin, Y. (2020). Complexity and information systems research in the emerging digital world. MIS Quarterly, 44(1), 1–17.
Cockburn, I. M., Henderson, R., & Stern, S. (2018). The impact of artificial intelligence on innovation (Vol. 24449). National Bureau of Economic Research Cambridge, MA, USA.
Daugherty, P., & Wilson, H. J. (2018). Human + machine: Reimagining work in the age of AI. Harvard Business Review Press.
Davenport, T. (2018). The AI Advantage: How to put the artificial intelligence revolution to work. MIT Press.
Erol, B. A., Majumdar, A., Benavidez, P., Rad, P., Choo, K.-K. R., & Jamshidi, M. (2019). Toward artificial emotional intelligence for cooperative social human–machine interaction. IEEE Transactions on Computational Social Systems, 7(1), 234–246.
Flores, E., Xu, X., & Lu, Y. (2020). Human Capital 4.0: a workforce competence typology for Industry 4.0. Journal of Manufacturing Technology Management, 31(4), 687–703.
Giannakos, M. N., Mikalef, P., & Pappas, I. (2021). Systematic literature review of Elearning capabilities to enhance organizational learning. Information Systems Frontiers, 1–17. https://doi.org/10.1007/s10796-020-10097-2
Hsieh, Y. J., Chen, Y.-L., & Wang, Y.-C. (2021). Government and social trust vs. hotel response efficacy: A protection motivation perspective on hotel stay intention during the COVID-19 pandemic. International Journal of Hospitality Management, 97, 102991.
Irandoost, S. F., Sedighi, S., Hoseini, A. S., Ahmadi, A., Safari, H., & Azar, F. E. F. (2022). Activities and challenges of volunteers in confrontation with COVID-19: A qualitative study in Iran. International Journal of Disaster Risk Reduction, 82, 103314.
Jaiswal, A., Arun, C. J., & Varma, A. (2022). Rebooting employees: Upskilling for artificial intelligence in multinational corporations. The International Journal of Human Resource Management, 33(6), 1179–1208.
Jasim, N. A., AlRikabi, H. T. S., & Farhan, M. S. (2021). Internet of Things (IoT) application in the assessment of the learning process. IOP Conference Series: Materials Science and Engineering, 1184(1).
Karthikeyan, A., Garg, A., Vinod, P. K., & Priyakumar, U. D. (2021). Machine learning based clinical decision support system for early COVID-19 mortality prediction. Frontiers in Public Health, 9, 626697.
Liu, W., Liang, Y., Wei, S., & Wu, P. (2021). The organizational collaboration framework of smart logistics ecological chain: a multi-case study in China. Industrial Management & Data Systems, 121(9), 2026–2047.
Murray, A., Rhymer, J., & Simon, D. (2021). Humans and Technology: Forms of Conjoined Agency in Organizations. Academy of Management Review, 46(3).
Nonaka, I., & von Krogh, G. (2009). Perspective—Tacit Knowledge and Knowledge Conversion: Controversy and Advancement in Organizational Knowledge Creation Theory. Organization Science, 20(3), 481–683.
Pachidi, S., & Huysman, M. (2016). Organizational intelligence in the digital age: Analytics and the cycle of choice. In Routledge Companions in Business, Management, and Accounting.
Pettersen, L. (2019). Why artificial intelligence will not outsmart complex knowledge work. Work, Employment and Society, 33(6), 1058–1067.
Phan, P., Wright, M., & Lee, S. H. (2017). Of robots, artificial intelligence, and work. Academy of Management Perspectives, 31(4), 253–255.
Singh, S., Joshi, R., Jain, P., & Abilash, K. (2024). Human AI: Ethics and broader impact for mental healthcare. In Emotional AI and Human-AI Interactions in Social Networking (pp. 191–212). Elsevier.
Waardenburg, L., Sergeeva, A., & Huysman, M. (2020). Filling the void: How occupational authority emerges from curating learning algorithms. Academy of Management Proceedings.
West, D. M. (2018). The future of work: Robots, AI, and automation. Brookings Institution Press.
Downloads
Published
Issue
Section
License
Copyright (c) 2024 Fahim Shahriar, Md. Shahriar Bulbul Tonmoy, Farhana Yeasmin
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.