EconPapers    
Economics at your fingertips  
 

Contextual Fuzzy-Based Decision Support System Through Opinion Analysis: A Case Study at University of the Salerno

Carmen De Maio (), Aurelio Tommasetti (), Orlando Troisi (), Massimiliano Vesci (), Giuseppe Fenza () and Vincenzo Loia ()
Additional contact information
Carmen De Maio: Deparment of Computer Science, University of Salerno, Fisciano (SA), Italy
Aurelio Tommasetti: Department of Management and Information Technology, University of Salerno, Fisciano (SA), Italy
Orlando Troisi: Department of Management and Information Technology, University of Salerno, Fisciano (SA), Italy
Massimiliano Vesci: Department of Management and Information Technology, University of Salerno, Fisciano (SA), Italy
Giuseppe Fenza: Department of Management and Information Technology, University of Salerno, Fisciano (SA), Italy
Vincenzo Loia: Department of Management and Information Technology, University of Salerno, Fisciano (SA), Italy

International Journal of Information Technology & Decision Making (IJITDM), 2016, vol. 15, issue 05, 923-948

Abstract: According to the literature about customer satisfaction and loyalty, it is possible to define knowledge-based system to support management decision-making in the organizations. Nevertheless, the problem as to how much the context impacts on correlation has not been investigated in the literature. This paper focuses on developing of Decision Support System (DSS) taking into account correlations among statistical factors, i.e., expert knowledge, and customers’ opinions depending on several contextual features, e.g., culture, location, in order to build context-sensitive simulation environment. The proposed work defines a general system design workflow to tailor knowledge-based DSS by using a fuzzy model to quantify correlations among variables in a given context. We explore ontologies to represent correlations among statistical factors, e.g., Calculative Commitment, Quality of Service. We apply fuzzy data analysis techniques to train fuzzy classifier on the customer’s opinions collected by survey. Finally, synergistic usage of Description Logic and Fuzzy Theory allows the implementation of a simulation environment that supports the management team to tune business strategies. The framework has been instantiated for a case study to support public administration at the University of the Salerno.

Keywords: Fuzzy logic; DSS; description logic; ontology; loyalty; commitment (search for similar items in EconPapers)
Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://www.worldscientific.com/doi/abs/10.1142/S0219622016500231
Access to full text is restricted to subscribers

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:wsi:ijitdm:v:15:y:2016:i:05:n:s0219622016500231

Ordering information: This journal article can be ordered from

DOI: 10.1142/S0219622016500231

Access Statistics for this article

International Journal of Information Technology & Decision Making (IJITDM) is currently edited by Yong Shi

More articles in International Journal of Information Technology & Decision Making (IJITDM) from World Scientific Publishing Co. Pte. Ltd.
Bibliographic data for series maintained by Tai Tone Lim ().

 
Page updated 2025-03-20
Handle: RePEc:wsi:ijitdm:v:15:y:2016:i:05:n:s0219622016500231