Elsevier, Procedia Social and Behavioral Sciences, (148), p. 110-118, 2014
DOI: 10.1016/j.sbspro.2014.07.024
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Marketing for tourist destinations, either as strategic planning or as short-term marketing-mix specification, has a lot to gain from computerized information tools. In this paper, we present knowledge engineering methods for the extraction and modeling of findings from market surveys and data analytics in the form of reusable and sharable knowledge. In contrast to information-based systems which are able to store and provide high quality information but their user relies on his own interpretation and decision abilities, we focus on a knowledge-based approach where data analysis and reasoning are consolidated and the system is thus able to provide solutions to common marketing problems. Data analysis methods suitable for discovering factors, associations, clusters and in general hidden patterns that explain a market phenomenon or customer behavior, are applied on multiple surveys related to tourist destination marketing. In addition, a computerized knowledge management process, utilizing ontologies and a rule-based inference engine, is developed to capitalize the extracted knowledge and offer it to support marketing planning problems. Preliminary results are presented on capturing the image of Thessaloniki as tourist destination and suggesting important factors for improving its promotion to individual visitor groups.