Issue |
ITM Web Conf.
Volume 51, 2023
International Conference on Exploring Service Science (IESS 2.3)
|
|
---|---|---|
Article Number | 04005 | |
Number of page(s) | 14 | |
Section | Service Innovation and Inclusion | |
DOI | https://doi.org/10.1051/itmconf/20235104005 | |
Published online | 07 February 2023 |
Towards a Rule Modeling Framework for Context-aware Smart Service Systems
1 School of Business, Université du Québec à Trois-Rivières, Canada
2 Faculty of Information Technology, University of Science, Ho Chi Minh city, Vietnam
3 Vietnam National University, Ho Chi Minh city, Vietnam
4 Faculty of Business, Technological University Dublin, Ireland
* Corresponding author: thi.my.hang.vu@uqtr.ca or vtmhang@fit.hcmus.edu.vn
Since business rules aim at enforcing regulations in an organization, they are critical in governing business activities from a managerial standpoint. On the other hand, another type of rules has emerged in context-aware service systems: context rules. Context rules are employed for context reasoning to recommend and operate the right services in an appropriate manner. In this sense, context rules ensure the smartness of services in smart service systems. For decades, researchers and practitioners have addressed rule modelling and rule management in information systems and business services. However, in relation to context-aware services in smart service systems, there is a lack of exploring the rule aspect, especially considering how business rules and context rules are involved in such a system. The purpose of this paper is to propose a rule modelling framework (called RuCBS framework) for expressing rules in context-aware smart service systems over the three aspects of service science (Management, Science, and Engineering). The framework presents concepts, a meta-model that connects these concepts, and rule patterns. The framework is validated with a case study on banking services. Future research directions on rules in context-aware smart service systems are also discussed.
© The Authors, published by EDP Sciences, 2023
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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