Mobile Technology-Enabled Decision Support in Operations Management: Enhancing Human-Centered Smart Manufacturing
DOI:
https://doi.org/10.3991/ijoe.v22i07.61579Keywords:
mobile technology-enables decision support, human-centered smart manufacturing, operations management, real-time manufacturing connectivity, sustainable industrial performanceAbstract
Intelligent process design and the integration of new technologies are necessary for smart manufacturing systems to meet high-performance standards, which include resilience, short lead times, high due date reliability, and tailored items for every customer. The planning and control of such smart manufacturing systems necessitate several instances of human decision-making. The increasing adoption of mobile technologies is transforming operations management by enabling real-time connectivity, responsiveness, and human-centered decision-making in manufacturing environments. While prior smart manufacturing models have largely emphasized automation and digital systems, many overlook the critical role of human judgment, experience, and adaptability supported through mobile technology. This study develops an interactive framework that integrates human intelligence with mobile technology–enabled decision support systems to enhance operational flexibility, productivity, and sustainability in manufacturing operations. Grounded in operations management principles, the framework illustrates how mobile platforms facilitate real-time information access, collaborative problem-solving, and adaptive learning across production processes. Empirical findings indicate that mobile technology–supported human decision-making leads to superior operational performance compared to traditional, technology-independent approaches. Results further demonstrate that mobile-enabled automation and connectivity, alongside human and organizational capital, positively contribute to green value creation in industrial firms. However, excessive reliance on automated mobile systems may constrain human creativity and situational judgment, highlighting the importance of balanced integration between human capabilities and mobile technologies. This study contributes to the operations management literature by clarifying how mobile technology–enabled human augmentation supports efficient, ethical, and sustainable manufacturing performance.
References
[1] Zhang, C., Wang, Z., Zhou, G., Chang, F., Ma, D., Jing, Y., Cheng, W., Ding, K. and Zhao, D., 2023. Towards new-generation human-centric smart manufacturing in Industry 5.0: A systematic review. Advanced Engineering Informatics, 57, p.102121.
[2] Wang, B., Zheng, P., Yin, Y., Shih, A. and Wang, L., 2022. Toward human-centric smart manufacturing: A human-cyber-physical systems (HCPS) perspective. Journal of Manufacturing Systems, 63, pp.471-490.
[3] Wang, T., Zheng, P., Li, S. and Wang, L., 2024. Multimodal human–robot interaction for human‐centric smart manufacturing: a survey. Advanced Intelligent Systems, 6(3), p.2300359.
[4] Li, D., Liu, S., Wang, B., Yu, C., Zheng, P. and Li, W., 2025. Trustworthy AI for human-centric smart manufacturing: A survey. Journal of Manufacturing Systems, 78, pp.308-327.
[5] Liu, S., Zhang, J., Yi, S., Gao, R., Mourtzis, D. and Wang, L., 2024. Human-centric systems in smart manufacturing. In Manufacturing from Industry 4.0 to Industry 5.0 (pp. 181-205). Elsevier.
[6] Wang, T., Fan, J. and Zheng, P., 2024. An LLM-based vision and language cobot navigation approach for Human-centric Smart Manufacturing. Journal of Manufacturing Systems, 75, pp.299-305.
[7] Zheng, P. ed., 2023. Human–Robot Collaboration for Futuristic Human-Centric Smart Manufacturing. Journal of Manufacturing Science and Engineering, 145(12), p.120301.
[8] Ma, D., Zhang, C., Zhou, G., Xu, Q., Li, J., Zhao, D. and Leng, J., 2025. A systematic review on vision-based proactive human assembly intention recognition for human-centric smart manufacturing in industry 5.0. IEEE Internet of Things Journal.
[9] Soldatos, J. and Kyriazis, D. eds., 2021. Trusted artificial intelligence in manufacturing: a review of the emerging wave of ethical and human centric AI technologies for smart production.
[10] Yanytska, L., 2025. The rise of human-centric manufacturing in the industry 5.0 era. The International Journal of Advanced Manufacturing Technology, 139(9), pp.5067-5077.
[11] Bechinie, C., Zafari, S., Kroeninger, L., Puthenkalam, J. and Tscheligi, M., 2024. Toward human-centered intelligent assistance system in manufacturing: challenges and potentials for operator 5.0. Procedia Computer Science, 232, pp.1584-1596.
[12] Wang, T., Fan, J. and Zheng, P., 2024. An LLM-based vision and language cobot navigation approach for Human-centric Smart Manufacturing. Journal of Manufacturing Systems, 75, pp.299-305.
[13] Emeka, U.C., Okpala, C.C. and Nwamekwe, C.O., 2025. Human-Centric Design Integration in Industry 5.0: A Framework for Resilient Smart Manufacturing. INTERNATIONAL JOURNAL OF INDUSTRIAL AND PRODUCTION ENGINEERING (IJIPE).
[14] Chen, S.C., Chen, H.M., Chen, H.K. and Li, C.L., 2024. Multi-objective optimization in Industry 5.0: Human-centric AI integration for sustainable and intelligent manufacturing. Processes, 12(12), p.2723.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2026 Halim Mad Lazim, Noor Hidayah Abu, Aizul Nahar Harun, Roshartini Omar, Kasmaruddin Che Hussin, Mohd Saiful Izwaan Saadon
This work is licensed under a Creative Commons Attribution 4.0 International License.
