Call for Papers
Special Issue of the Service Science Journal on:
Service Engineering: Data-Driven Service Design and Optimization
Special Issue Editors
Submissions open: February 1, 2025
Overview
Modern data analytics and data mining techniques have unlocked new opportunities for optimizing service operations and enhancing customer experiences. These advancements span a broad range of organizational activities, including marketing, operations, finance, human resources, product development, and information systems. For instance, data-driven financial models can guide critical decision-making in lending, investing, and credit rating.
This special issue of Service Science aims to highlight recent progress in research on management analytics and data-driven decision-making in the service industry. Over the past decade, the service sector has increasingly gathered vast amounts of data from customer interactions, sales transactions, social media activity, and other sources. We invite contributions that leverage these datasets to design and optimize services and their delivery, including the development of algorithms for uncovering patterns, trends, and actionable insights that can enhance managerial decision-making.
Topics of Interest
We are particularly interested in submissions that address, but are not limited to, the following themes:
- Service Design: How can data improve resource utilization and welfare in modern business models, such as sharing economies and platform operations?
- Service Optimization: Using data to set optimal service capacity, reduce wait times, and improve resource allocation across service touchpoints.
- Enhanced Customer Experience: Leveraging analytics to better understand customer needs, enabling personalized services and tailored recommendations.
- Information Technology in Service: How can data-driven approaches automate and manage business processes, such as identifying automation opportunities or enhancing the application of digital twins?
- Adoption of Advanced Information Technology in Services: Exploring the implementation of AI, machine learning, and other advanced technologies in domains like healthcare diagnostics and high-frequency trading. What challenges hinder adoption, and how can they be overcome?
- Real-Time Data Utilization: How does access to real-time data enable businesses to make informed operational, tactical, and strategic decisions?
- AI and Machine Learning Applications: How can emerging technologies, such as Large Language Models (LLMs), transform service management and productivity?
- Improved Risk Management: Using historical data to identify and mitigate risks in financial activities, such as lending, investment, and credit evaluation.
Scope
The special issue seeks original research papers that explore various aspects of data-driven service design and optimization. We welcome submissions employing analytical, empirical, experimental, or qualitative methods. The issue emphasizes the interdisciplinary nature of service science, focusing on the intersection of data management and analytics in service industries. Submissions from researchers, practitioners, and policymakers in academia, industry, and government agencies are encouraged.
Authors unsure about the alignment of their research with the special issue are invited to submit a brief project description (no more than one page) to the editors for preliminary feedback. This step is optional and does not substitute the peer review process for full submissions.
Submission Process and Timeline
All submissions must be made via the Service Science online submission system: https://mc.manuscriptcentral.com/serv. Submissions will undergo the journal's standard peer-review process. Criteria for acceptance include originality, scientific rigor, and contribution to the field. For detailed submission guidelines, visit the journal's homepage: Service Science Submission Guidelines.
Key Dates:
- Submission Deadline: October 1, 2025
- First-Round Feedback: January 15, 2026
- Revised Submissions Deadline: August 1, 2026
- Final Decisions (subject to minor revisions): November 1, 2026
We look forward to receiving your submissions and to advancing the discourse on service engineering, data-driven service design, and optimization.
For updates and further details: https://pubsonline.informs.org/page/serv/calls-for-papers#/