The relationship between unstructured information and marketing knowledge: an experiment in the US wine market
Paola Scorrano,
Monica Fait and
Amedeo Maizza
International Journal of Management Practice, 2015, vol. 8, issue 3, 232-246
Abstract:
The aim of this paper is to assess, with a view to marketing strategies, the potential of a marketing intelligence software application designed to extract information from non-structured web sources (typically websites and social media). The paper also proposes a conceptual model that SMEs can use to transform simple qualitative and quantitative data into knowledge that is useful for supporting the decision-making process in the context of international marketing. The presentation of the proposed interpretative model is followed by the application to the wine market in the USA. Comparison of the themes typical of online discourse in the worlds of supply and demand highlights a certain communicative misalignment that SMEs can resolve by adopting suitable communicative strategies.
Keywords: marketing intelligence; information extraction; wine markets; consumer behaviour; text mining; websites; social networks; unstructured information; marketing knowledge; USA; United States; wine industry; marketing strategies; social media; SMEs; small and medium-sized enterprises; communication; decision making; international marketing. (search for similar items in EconPapers)
Date: 2015
References: Add references at CitEc
Citations: View citations in EconPapers (1)
Downloads: (external link)
http://www.inderscience.com/link.php?id=72772 (text/html)
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:ids:ijmpra:v:8:y:2015:i:3:p:232-246
Access Statistics for this article
More articles in International Journal of Management Practice from Inderscience Enterprises Ltd
Bibliographic data for series maintained by Sarah Parker ().