Smart Value Chains: Integrating Big Data and Sustainability in Industry 4.0
Keywords:
Industry 4.0, Big Data, sustainability, operational efficiency, circular economy, data governance, transparency, Artificial Intelligence
Abstract
Industry 4.0 has transformed production processes through the integration of advanced digital technologies such as Big Data, Artificial Intelligence (AI), and the Internet of Things (IoT), improving operational efficiency and promoting sustainability in value chains. This study explores how the adoption of Big Data and other emerging technologies facilitates the shift towards more sustainable and circular business models. Using a quantitative approach, three key dimensions are examined: real-time data integration, operational efficiency and circularity, and algorithmic governance and transparency. The results show that the integration of Big Data significantly contributes to waste reduction, energy consumption optimization, and improved transparency in operational processes. Furthermore, data governance emerges as a critical factor to ensure ethical and equitable use of information. This paper offers recommendations to enhance the implementation of sustainable technologies and promote greater interdepartmental collaboration within organizations.Downloads
Download data is not yet available.
References
Bai, C., Zhang, X., & Zhou, H. (2020). The impact of big data analytics on supply chain sustainability: A literature review and future directions. Journal of Cleaner Production, 275, 124110. https://doi.org/10.1016/j.jclepro.2020.124110
Chen, J., Xu, L., & Shi, X. (2021). Cyber-physical systems and big data: An integrated approach for manufacturing system design. Computers in Industry, 129, 103426. https://doi.org/10.1016/j.compind.2021.103426
Floridi, L., Taddeo, M., & Turilli, M. (2018). The ethics of big data: The machine learning paradigm. Ethics and Information Technology, 20(4), 293-305. https://doi.org/10.1007/s10676-018-9462-4
Kamble, S. S., Gunasekaran, A., & Dhone, N. C. (2020). Industry 4.0 and lean manufacturing practices for sustainable organizational performance in Indian manufacturing companies. International Journal of Production Economics, 231, 107862. https://doi.org/10.1016/j.ijpe.2020.107862
Lu, Y., & Xu, X. (2020). Smart manufacturing and big data: A perspective on the future of the manufacturing industry. Advanced Engineering Informatics, 45, 101143. https://doi.org/10.1016/j.aei.2020.101143
Mikalef, P., Krogstie, J., Pappas, I. O., & Giannakos, M. (2020). Investigating the effects of big data analytics capabilities on firm performance: The mediating role of dynamic capabilities. Information & Management, 57(2), 103169. https://doi.org/10.1016/j.im.2019.103169
Porter, M. E., & Heppelmann, J. E. (2014). How smart, connected products are transforming competition. Harvard Business Review, 92(11), 64-88.
Schwab, K. (2016). The Fourth Industrial Revolution. World Economic Forum.
Wamba-Taguimdje, S. L., Fosso Wamba, S., Kala Kamdjoug, J. R., & Tchatchouang Wanko, C. E. (2020). Influence of artificial intelligence (AI) on firm performance: The business value of AI-based transformation projects. Business Process Management Journal, 26(7), 1893–1924. https://doi.org/10.1108/BPMJ-10-2019-0411
Chen, J., Xu, L., & Shi, X. (2021). Cyber-physical systems and big data: An integrated approach for manufacturing system design. Computers in Industry, 129, 103426. https://doi.org/10.1016/j.compind.2021.103426
Floridi, L., Taddeo, M., & Turilli, M. (2018). The ethics of big data: The machine learning paradigm. Ethics and Information Technology, 20(4), 293-305. https://doi.org/10.1007/s10676-018-9462-4
Kamble, S. S., Gunasekaran, A., & Dhone, N. C. (2020). Industry 4.0 and lean manufacturing practices for sustainable organizational performance in Indian manufacturing companies. International Journal of Production Economics, 231, 107862. https://doi.org/10.1016/j.ijpe.2020.107862
Lu, Y., & Xu, X. (2020). Smart manufacturing and big data: A perspective on the future of the manufacturing industry. Advanced Engineering Informatics, 45, 101143. https://doi.org/10.1016/j.aei.2020.101143
Mikalef, P., Krogstie, J., Pappas, I. O., & Giannakos, M. (2020). Investigating the effects of big data analytics capabilities on firm performance: The mediating role of dynamic capabilities. Information & Management, 57(2), 103169. https://doi.org/10.1016/j.im.2019.103169
Porter, M. E., & Heppelmann, J. E. (2014). How smart, connected products are transforming competition. Harvard Business Review, 92(11), 64-88.
Schwab, K. (2016). The Fourth Industrial Revolution. World Economic Forum.
Wamba-Taguimdje, S. L., Fosso Wamba, S., Kala Kamdjoug, J. R., & Tchatchouang Wanko, C. E. (2020). Influence of artificial intelligence (AI) on firm performance: The business value of AI-based transformation projects. Business Process Management Journal, 26(7), 1893–1924. https://doi.org/10.1108/BPMJ-10-2019-0411
Published
2025-01-21
How to Cite
Solorzano Movilla, J. (2025). Smart Value Chains: Integrating Big Data and Sustainability in Industry 4.0. IJMSOR: International Journal of Management Science & Operation Research, 10(1), 73-85. Retrieved from https://ijmsoridi.com/index.php/ijmsor/article/view/136
Section
PAPERS
Published papers are the exclusive responsibility of their authors and do not necessary reflect the opinions of the editorial committee.
IJMSOR respects the moral rights of its authors, whom must cede the editorial committee the patrimonial rights of the published material. In turn, the authors inform that the current work is unpublished and has not been previously published.
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported License.
