Marketing decision support using artificial intelligence and knowledge modeling : application to tourist destination management

Stalidis, George/ Karapistolis, Dimitrios/ Vafeiadis, Athanasios/ Καραπιστόλης, Δημήτριος/ Βαφειάδης, Αθανάσιος/ Σταλίδης, Γιώργος


Institution and School/Department of submitter: ΤΕΙ Θεσσαλονίκης
Keywords: Συστήματα που βασίζονται στη γνώση (Πληροφορική);Knowledge-based systems (Computer science);Τουρισμός--Οικονομικές απόψεις;Tourism--Economic aspects;Διαχείριση brand;Brand management;Τουριστικός προορισμός;Tourist destination
Issue Date: 12-Feb-2014
Publisher: Elsevier
Citation: Conference on Strategic Innovative Marketing, Madrid, 2014
Stalidis,Karapistolis,Vafeiadis, G. (2015). International Conference on Strategic Innovative Marketing. Πρακτικά συνεδρίου από 3ο Marketing Decision Support Using Artificial Intelligence and Knowledge Modeling: Application to Tourist Destination Management που διεξήχθη σε Madrid. Φορέας διεξαγωγής -. -: Elsevier.
Journal: Procedia - Social and Behavioral Sciences, vol. 175, 2015
Abstract: Knowledge-based information systems are advanced tools in the hands of the marketer, enabling him to take evidence-based decisions in complex situations. In this paper, advanced data analysis, neural networks and knowledge representation technologies are brought together towards an intelligent information system for tourist destination marketing. In previous work, knowledge engineering methods were proposed for the extraction and modeling from market survey data of factors, associations, clusters and hidden patterns that explain a market phenomenon or customer behavior. The feasibility of managing these findings in a Knowledge-Base, as reusable, sharable and machine understandable knowledge was shown using preliminary results from primary surveys on the tourism of Thessaloniki. In the current work, we present the continuation of these developments, including: (a) the final results of the survey on the tourism of Thessaloniki, (b) a refined Knowledge Base filled with real and validated content derived from the analysis of the full-scale survey data, (c) the extension of the methods with an artificial neural network classifier and (d) the deployment of an inference engine and a query mechanism in order to exercise the knowledge content for decision support. Pilot trials showed that the intelligent system was able to assist users who are not experts in analysis to solve typical destination marketing problems
Description: Δημοσιεύσεις μελών--ΣΔΟ--Τμήμα Εμπορίας και Διαφήμισης, 2014
URI: http://195.251.240.227/jspui/handle/123456789/4613
Other Identifiers: http://www.sciencedirect.com/science/article/pii/S1877042815012409
10.1016/j.sbspro.2015.01.1180
Item type: other
Submission Date: 2018-02-27T18:19:36Z
Item language: el
Item access scheme: free
Institution and School/Department of submitter: ΤΕΙ Θεσσαλονίκης
Appears in Collections:Δημοσιεύσεις σε Περιοδικά

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