New Challenges of Decision Support Systems

Dear Colleagues,

Decision Support Systems (DSSs) are adopted in several research and industry fields to support decision-making processes with high-quality decisions. In the past decades, the widespread adoption of data-driven technologies introduced elements of novelty in the study and development of DSSs, enabling such systems to face the complexity and dynamic nature of information. Artificial intelligence techniques enabled decision-making solutions capable of supporting end users in dynamic and information-dense areas such as healthcare, industry, finance, environment, and knowledge management. Moreover, as the world is experiencing the huge advancement in integration of eXtended Reality (XR) and Metaverse into our lives, the significance of the data-driven AI and inferences accuracy and reliability is remarkably observable.

Today, DSSs must be able to provide solid recommendations and suggestions by integrating expert knowledge, data-driven inferences, uncertain and incomplete information usually transmitted in massive streams of data in real time without data pre-processing and cleaning. Moreover, theoretical and technological AI-based advances can smoothly integrate the decision-making processes in the digital experience, supporting the generation of tailored and intelligent recommendations.

This Special Issue aims to attract high-value articles and literature reviews exploring the research issues, challenges, solutions, and applications pertaining to DSSs in the modern era.

Topics relevant for this Special Issue include (but are not limited to):

• Integration of data-driven and ontology-based solutions in DSSs
• AI techniques and Smart Autonomous Agents for decision-making
• Explainable AI (xAI) DSSs
• Robust methodologies for DSSs’ development
• AI-powered metaverse, opportunities & challenges
• Challenges of DSSs and data-driven approaches in real time XR environments
• Applications of DSSs in different research areas (healthcare, personalized medicine, Ambient Assisted Living and Ambient Assisted Working, learning environments, finance, manufacturing and industry, circular economy, environmental management, knowledge management).

Examples of articles describing Decision Support Systems in different fields [1–11].

References

1. Spoladore, D.; Pessot, E. An Ontology-Based Decision Support System to Foster Innovation and Competitiveness Opportunities of Health Tourism Destinations. In Digital and Strategic Innovation for Alpine Health Tourism. SpringerBriefs in Applied Sciences and Technology; Spoladore, D., Pessot, E., Sacco, M., Eds.; Springer: Cham, Switzerland, 2023. https://doi.org/10.1007/978-3-031-15457-7_4.
2. Mahroo, A.; Spoladore, D.; Ferrandi, P.; Lovato, I. A Digital Application for Strategic Development of Health Tourism Destinations. In Digital and Strategic Innovation for Alpine Health Tourism; Spoladore, D., Pessot, E., Sacco, M., Eds.; SpringerBriefs in Applied Sciences and Technology; Springer: Cham, Switzerland, 2023. https://doi.org/10.1007/978-3-031-15457-7_5.
3. Spoladore, D.; Mahroo, A.; Trombetta, A.; Sacco, M. DOMUS: A domestic ontology managed ubiquitous system. J. Ambient. Intell. Hum. Comput. 2022, 13, 3037–3052. https://doi.org/10.1007/s12652-021-03138-4.
4. Spoladore, D.; Colombo, V.; Arlati, S.; Mahroo, A.; Trombetta, A.; Sacco, M. An Ontology-Based Framework for a Telehealthcare System to Foster Healthy Nutrition and Active Lifestyle in Older Adults. Electronics 2021, 10, 2129. https://doi.org/10.3390/electronics10172129.
5. Spoladore, D.; Sacco, M. Semantic and Dweller-Based Decision Support System for the Reconfiguration of Domestic Environments: RecAAL. Electronics 2018, 7, 179. https://doi.org/10.3390/electronics7090179.
6. Zhai, Z.; Martínez, J.F.; Beltran, V.; Martínez, N.L. Decision support systems for agriculture 4.0: Survey and challenges. Comput. Electron. Agric. 2020, 170, 105256.
7. Juan, Y.K.; Chi, H.Y.; Chen, H.H. Virtual reality-based decision support model for interior design and decoration of an office building. Eng. Constr. Archit. Manag. 2021, 28, 229–245.
8. Deveci, M.; Mishra, A.R.; Gokasar, I.; Rani, P.; Pamucar, D.; Özcan, E. A decision support system for assessing and prioritizing sustainable urban transportation in metaverse. IEEE Trans. Fuzzy Syst. 2022, 31, 475–484.
9. Gonzales, R.M.D.; Hargreaves, C.A. How can we use artificial intelligence for stock recommendation and risk management? A proposed decision support system. Int. J. Inf. Manag. Data Insights 2022, 2, 100130.
10. Naqvi, S.M.R.; Ghufran, M.; Meraghni, S.; Varnier, C.; Nicod, J.M.; Zerhouni, N. Human knowledge centered maintenance decision support in digital twin environment. J. Manuf. Syst. 2022, 65, 528–537.
11. Cantini, A.; Peron, M.; De Carlo, F.; Sgarbossa, F. A decision support system for configuring spare parts supply chains considering different manufacturing technologies. Int. J. Prod. Res. 2022, 1–21.

Dr. Daniele Spoladore
Dr. Atieh Mahroo
Guest Editors

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