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Unsupervised KDD to creatively support managers' decision making with fuzzy association rules : a distribution channel application
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Orriols-Puig, Albert, Martínez-López, Francisco J., Casillas, Jorge and Lee, Nick (2013) Unsupervised KDD to creatively support managers' decision making with fuzzy association rules : a distribution channel application. Industrial Marketing Management, 42 (4). pp. 532-543. doi:10.1016/j.indmarman.2013.03.005 ISSN 0019-8501.
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Official URL: http://dx.doi.org/10.1016/j.indmarman.2013.03.005
Abstract
To be competitive in contemporary turbulent environments, firms must be capable of processing huge amounts of information, and effectively convert it into actionable knowledge. This is particularly the case in the marketing context, where problems are also usually highly complex, unstructured and ill-defined. In recent years, the development of marketing management support systems has paralleled this evolution in informational problems faced by managers, leading to a growth in the study (and use) of artificial intelligence and soft computing methodologies. Here, we present and implement a novel intelligent system that incorporates fuzzy logic and genetic algorithms to operate in an unsupervised manner. This approach allows the discovery of interesting association rules, which can be linguistically interpreted, in large scale databases (KDD or Knowledge Discovery in Databases.) We then demonstrate its application to a distribution channel problem. It is shown how the proposed system is able to return a number of novel and potentially-interesting associations among variables. Thus, it is argued that our method has significant potential to improve the analysis of marketing and business databases in practice, especially in non-programmed decisional scenarios, as well as to assist scholarly researchers in their exploratory analysis.
| Item Type: | Journal Article | ||||||
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| Divisions: | Faculty of Social Sciences > Warwick Business School > Marketing Group Faculty of Social Sciences > Warwick Business School |
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| Journal or Publication Title: | Industrial Marketing Management | ||||||
| Publisher: | Elsevier Inc. | ||||||
| ISSN: | 0019-8501 | ||||||
| Official Date: | May 2013 | ||||||
| Dates: |
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| Volume: | 42 | ||||||
| Number: | 4 | ||||||
| Page Range: | pp. 532-543 | ||||||
| DOI: | 10.1016/j.indmarman.2013.03.005 | ||||||
| Status: | Peer Reviewed | ||||||
| Publication Status: | Published | ||||||
| Access rights to Published version: | Restricted or Subscription Access |
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