Call for Papers: Transactions on Engineering Management, Special Section on “Operational Innovation in Interdisciplinary Research”

Guest Editors

Prof. Meng Li
University of Houston, USA
mli@bauer.uh.edu

Dr. Xiaoyan Xu
University of Southampton, UK
Xiaoyan.Xu@soton.ac.uk

Prof. Xiaohang Yue
University of Wisconsin-Milwaukee, USA
xyue@uwm.edu

Schedule

Submission deadline: 15 June 2025

Scope and Objectives

Over the past years, operations management (OM) has faced numerous challenges, including demand uncertainty, disruption risks, financial problems, and shifting consumer behaviors, all exacerbated by unforeseen crises like pandemics, earthquakes, and extreme climate events (Rodriguez-Espindola 2022, Xu et al. 2023). In response, companies are seeking operational innovation to enhance supply chain resilience, maintain their competitiveness, and realize sustainable development. Operational innovation refers to the development and application of new methods, processes, or technologies aimed at improving operational efficiency, effectiveness, and flexibility, creating solutions to match needs (Kavadias and Ulrich 2020).

By embracing operational innovation, companies can unlock new value, streamline processes, and enhance their capabilities to better navigate potential crises, thus paving the way for sustainable growth. Disruptive technologies such as artificial intelligence (AI), blockchain, and predictive analytics are key tools for operational innovation, enabling companies to reduce demand uncertainty (Li 2023), automate procurement and sourcing processes (Cui et al. 2022), and lessen the risk of information asymmetry (Choi et al. 2022, Xu et al. 2022). Designing contracts innovatively can also help eliminate operational inefficiencies by improving profit allocation flexibility (Lu et al. 2019), guarding against disruption risks (Li et al. 2020), and increasing customer satisfaction (Li et al. 2023).

Key Themes

• Innovative Manufacturing Processes
  • Additive manufacturing (3D printing)
  • Smart manufacturing and industry 4.0
  • AI automation and robotics
  • Sustainable and green manufacturing
  • Advanced materials and nanotechnology
  • Supply chain integration and collaborative innovation
• Innovative Procurement Processes
  • Digital procurement solutions
  • Strategic supplier relationships
  • Procurement as a service (PaaS)
  • Sustainable procurement
  • Data-driven decision making in procurement
  • Collaborative and open innovation procurement
• Operational Innovation in Supply Chain Finance
  • Use of blockchain technology
  • Dynamic discounting
  • Collaborative financing models
  • Innovative payment solutions
  • Sustainability-linked financing
  • Predictive risk management
• Innovative Marketing Operations and Customer Experience
  • Omnichannel marketing in the new normal
  • Advanced analytics and AI
  • Automation and real-time marketing
  • Augmented and virtual reality experiences
  • Social media and influencer marketing
• Sustainability through Operational Innovation
  • Circular economy practices
  • Technology adoption for carbon neutrality in supply chain
  • Sustainable transportation and logistics
  • Employee engagement and corporate social responsibility (CSR)
  • Collaboration with non-governmental organizations (NGOs) and non-profit organizations (NPOs)

Notes for Prospective Authors: Submission Process

Please prepare the manuscript according to IEEE-TEM’s guidelines and submit it to the journal’s Manuscript Central site at https://ieee.atyponrex.com/journal/tem-ieee. Clearly state that the submission is for the Special Section on “Operational Innovation in Interdisciplinary Research”.

References

• Choi, T. M., Kumar, S., Yue, X., & Chan, H. L. (2022). Disruptive technologies and operations management in the Industry 4.0 era and beyond. Production and Operations Management, 31(1), 9-31.
• Cui, R., Li, M., & Zhang, S. (2022). AI and procurement. Manufacturing & Service Operations Management, 24(2), 691-706.
• Hou, P., Liu, Z., Xie, L., & Zhang, S. (2023). To Transfer or Not? Analysis of the Original Equipment Manufacturer’s Strategic Outsourcing Strategy in the Presence of the Supplier’s Innovation Effort. IEEE Transactions on Engineering Management, 71, 7341-7352.
• Kavadias, S., & Ulrich, K. T. (2020). Innovation and new product development: Reflections and insights from the research published in the first 20 years of manufacturing & service operations management. Manufacturing & Service Operations Management, 22(1), 84-92.
• Li, G., Liu, M., Bian, Y., & Sethi, S. P. (2020). Guarding against disruption risk by contracting under information asymmetry. Decision Sciences, 51(6), 1521-1559.
• Li, M. (2023). Demand uncertainty reduction among competing retailers. Production and Operations Management, 32(6), 1994-2001.
• Li, M., & Li, T. (2022). AI automation and retailer regret in supply chains. Production and Operations Management, 31(1), 83-97.
• Li, R., Yang, L., & Yue, X. (2023). Multiperiod channel coordination in franchise networks: The necessity of internal inventory trading and franchiser involvement. Production and Operations Management, 32(11), 3452-3468.
• Lu, M., Sethi, S., Xie, Y., & Yan, H. (2019). Profit allocation, decision sequence and compliance aspects of coordinating contracts: A retrospect. Production and Operations Management, 28(5), 1222-1237.
• Rodriguez-Espindola, O. (2022). Multiperiod model for disaster management in simultaneous disasters. IEEE Transactions on Engineering Management, 71, 4971-4984.
• Xu, X., Choi, T. M., Chung, S. H., & Shen, B. (2022). Government subsidies and policies for mask production under COVID-19: is it wise to control less? IEEE Transactions on Engineering Management, 71, 3172-3188.
• Xu, X., Sethi, S. P., Chung, S. H., & Choi, T. M. (2023). Reforming global supply chain management under pandemics: The GREAT‐3Rs framework. Production and Operations Management, 32(2), 524-546.
• Xu, X., Siqin, T., Chung, S. H., & Choi, T. M. (2023). Seeking survivals under COVID‐19: The WhatsApp platform’s shopping service operations. Decision Sciences, 54(4), 375-393.

Guest Editor Bios

Meng Li

Meng Li is a Professor, the founding director of Bauer Human-Centered AI Institute, SCM PhD coordinator, and endowed C.T. Bauer Chair of AI at C.T. Bauer College of Business, University of Houston. His recent research interests focus on human-centered AI. His research has appeared in journals such as Management Science, Manufacturing & Service Operations Management, Operations Research, Production and Operations Management, Journal of Operations Management, Strategic Management Journal, and Nature Sustainability. He is a Department Editor for Journal of Operations Management and Decision Sciences Journal, and a Senior Editor for Production and Operations Management. His work has been funded by companies such as Shell and HPE.

Xiaoyan Xu

Xiaoyan Xu is a Lecturer in Southampton Business School at University of Southampton. Her research interests focus on marketing and operations interfaces, sustainable supply chain management, and supply chain digitalization. She has published research papers in leading journals such as IEEE Transactions on Engineering Management, Production and Operations Management, Decision Sciences, IISE Transactions, International Journal of Production Economics, International Journal of Production Research, and Transportation Research Part E.

Xiaohang Yue

Xiaohang Yue is a Professor in Supply Chain, Operations Management & Business Statistics at University of Wisconsin-Milwaukee. His research interests include supply chain management, operations management, management information systems, and marketing management. He is a Senior Editor of IEEE Transactions on Engineering Management and Production and Operations Management. His research has been published in journals such as Operations Research, Production and Operations Management, Naval Research Logistics, IISE Transactions, and IEEE Transactions.