Open Access
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
Published online 07 February 2023
  1. J.C. Spohrer, H. Demirkan, Introduction to the Smart Service Systems: Analytics, Cognition, and Innovation Minitrack, in Proceedings of the 48th Hawaii International Conference on System Sciences. pp. 1442–1442. IEEE, HI, USA (2015) [Google Scholar]
  2. T. Mo, W. Li, W. Chu, Z. Wu, CABS3: Context-Awareness Based Smart Service System, in Proceedings of the 2010 International Conference on Computational Intelligence and Software Engineering, pp. 1–4. IEEE, Chengdu City, China (2010) [Google Scholar]
  3. T. Le Dinh, T.T. Pham Thi, C. Pham-Nguyen, L.N.H. Nam, A knowledge-based model for context-aware smart service systems, Journal of Information and Telecommunication, 1–22, (2021) [Google Scholar]
  4. S. Goedertier, R. Haesen, J. Vanthienen, EM-BrA2CE v0.1: A Vocabulary and Execution Model for Declarative Business Process Modeling, SSRN Journal, (2007) [Google Scholar]
  5. I. Graham, Business rules management and service oriented architecture: a pattern language, John Wiley, Chichester, England, Hoboken, NJ (2006) [Google Scholar]
  6. H. Herbst, Business Rule-Oriented Conceptual Modeling, Physica-Verlag HD, Heidelberg (1997) [Google Scholar]
  7. R.G. Ross, Principles of the Business Rule Approach, Addison-Wesley Professional (2003) [Google Scholar]
  8. OMG, Business Rules Group - Company contributions, (2022) [Google Scholar]
  9. T. Le Dinh, T.T.P. Thi, Information-Driven Framework for Collaborative Business Service Modelling, International Journal of Service Science, Management, Engineering, and Technology 3, 1–18 (2012) [CrossRef] [Google Scholar]
  10. S.L. Vargo, R.F. Lusch, Service-dominant logic, International Journal of Research in Marketing 34, 46–67 (2017) [CrossRef] [Google Scholar]
  11. C. Perera, A. Zaslavsky, P. Christen, D. Georgakopoulos, Context Aware Computing for The Internet of Things: A Survey, IEEE Commun. Surv. Tutorials 16, 414-454, (2014) [CrossRef] [Google Scholar]
  12. P. Loucopoulos, W.M.N.W. Kadir, BROOD: Business Rules-driven Object-Oriented Design, Journal of Database Management 19, 41–73, (2008) [CrossRef] [Google Scholar]
  13. G.J. Nalepa, K. Kluza, UML representation for rule-based application models with xtt2-based business rules, Int. J. Soft. Eng. Knowl. Eng. 22, 485–524, (2012). [CrossRef] [Google Scholar]
  14. F. Rosenberg, S. Dustdar, Business rules integration in BPEL - a service-oriented approach, in Proceedings of the Seventh IEEE International Conference on E-Commerce Technology (CEC’05), pp. 476–479 (2005) [Google Scholar]
  15. OMG, About the Decision Model and Notation Specification Version 1.4 beta, (2022) [Google Scholar]
  16. Oracle, Fusion Middleware Designing Business Rules with Oracle Business Process Management, (2022) [Google Scholar]
  17. G.F. Nalepa, Modeling with Rules Using Semantic Knowledge Engineering. Springer International Publishing, Cham (2018) [Google Scholar]
  18. OMG, Semantics of Business Vocabulary and Business Rules, v1.4, (2022) [Google Scholar]
  19. P. Jiménez, R. Corchuelo, On the design of an advanced business rule engine. Software: Practice and Experience, (2022) [Google Scholar]
  20. M. Bonais, K. Nguyen, E. Pardede, W. Rahayu, Automated generation of structural design models from SBVR specification, AO 11, 51–87, (2016). [Google Scholar]
  21. H. Takatsuka, S. Saiki, S. Matsumoto, M. Nakamura, Design and Implementation of Rule-Based Framework for Context-Aware Services with Web Services, in Proceedings of the 16th International Conference on Information Integration and Web-based Applications & Services. pp. 233–242. ACM, Hanoi Viet Nam (2014) [Google Scholar]
  22. M. Wieland, F., Steimle, B., Mitschang, D. Lucke, P. Einberger, D. Schel, M. Luckert, T. Bauernhansl, Rule-based integration of smart services using the manufacturing service business, in Proceedings of the 2017 IEEE SmartWorld, Ubiquitous Intelligence & Computing, Advanced & Trusted Computed, Scalable Computing & Communications, Cloud & Big Data Computing, Internet of People and Smart City Innovation (SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI), pp. 1–8 (2017) [Google Scholar]
  23. L. Daniele, P. Dockhorn Costa, L. Ferreira Pires, Towards a Rule-Based Approach for Context-Aware Applications, in: Pras, A. and van Sinderen, M. (eds.) Dependable and Adaptable Networks and Services. pp. 33–43. Springer Berlin Heidelberg, Berlin, Heidelberg (2007) [Google Scholar]
  24. P.D. Costa, J.P.A. Almeida, L.F. Pires, M. van Sinderen, Evaluation of a Rule-Based Approach for Context-Aware Services, in Proceedings of the IEEE GLOBECOM 2008-2008 IEEE Global Telecommunications Conference, pp. 1–5 (2008) [Google Scholar]
  25. I.H. Sarker, A.S.M. Kayes, ABC-RuleMiner: User behavioral rule-based machine learning method for context-aware intelligent services, Journal of Network and Computer Applications 168, 102762 (2020). [Google Scholar]
  26. F. Burgstaller, B. Neumayr, C.G. Schuetz, M. Schrefl, Modification Operations for Context-Aware Business Rule Management, in Proceedings of the 2017 IEEE 21st International Enterprise Distributed Object Computing Conference (EDOC), pp. 194–203(2017) [Google Scholar]
  27. J. Han, Y.-K. Jeong, I. Lee, A Rule-Based Ontology Reasoning System for Context-Aware Building Energy Management, in Proceedings of the 2015 IEEE International Conference on Computer and Information Technology; Ubiquitous Computing and Communications; Dependable, Autonomic and Secure Computing; Pervasive Intelligence and Computing. pp. 2134–2142. IEEE, LIVERPOOL, United Kingdom (2015) [Google Scholar]
  28. A.R. Hevner, S.T. March, J. Park, S. Ram, Design Science in Information Systems Research, MIS Quarterly 28, 75–105, (2004). [CrossRef] [Google Scholar]
  29. K. Peffers, T. Tuunanen, M.A. Rothenberger, S. Chatterjee, A Design Science Research Methodology for Information Systems Research, Journal of Management Information Systems 24, 45–77, (2007) [CrossRef] [Google Scholar]
  30. UML: About the Unified Modeling Language Specification Version 2.5.1, [Google Scholar]
  31. T. Le Dinh, T.T.P. Thi, N.A.K. Dam, W. Menvielle, A Service Science Perspective on Resilience of Service Organisations, in Proceedings of the ITM Web Conf. 38, 02002. (2021) [Google Scholar]
  32. T. Le Dinh, T.T.P. Thi, Collaborative Business Service Modelling in Knowledge-Intensive Enterprises, International Journal of Innovation in the Digital Economy 7, 1–22, (2016) [CrossRef] [Google Scholar]
  33. T. Le Dinh, T.M.H. Vu, N.A.K. Dam, J. Ralyte, Smart service modeling, technical report (2022) [Google Scholar]
  34. S.L. Vargo, P.P Maglio, M.A. Akaka, On value and value co-creation: A service systems and service logic perspective, European Management Journal 26, 145–152, (2008) [CrossRef] [Google Scholar]
  35. T. Le Dinh, G. Fillion, Acquiring Domain Knowledge of Information Systems: The Information System Upon Information Systems Approach, Academy of Information & Management Sciences Journal 10, 57–77 (2007) [Google Scholar]
  36. R. Coetzee, Towards Designing an Artefact Evaluation Strategy for Human Factors Engineering: A Lean Implementation Model Case Study, South African Journal of Industrial Engineering 30, 289–303, (2019). [CrossRef] [Google Scholar]
  37. J. Venable, J. Pries-Heje, R. Baskerville, FEDS: a Framework for Evaluation in Design Science Research, European Journal of Information Systems 25, 77–89, (2016). [CrossRef] [Google Scholar]
  38. J. Venable, J. Pries-Heje, R. Baskerville, A Comprehensive Framework for Evaluation in Design Science Research, in: Peffers, K., Rothenberger, M., and Kuechler, B. (eds.) Design Science Research in Information Systems, Advances in Theory and Practice, pp. 423–438. Springer Berlin Heidelberg, Berlin, Heidelberg (2012) [Google Scholar]

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