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DATA MINING BASED MODEL AGGREGATION AgEcon
Szucs, Imre.
Applying modelling techniques for getting acquainted with customer behaviour, predicting the customers’ next step is neccessary to keep in competition, by decreasing the capital requirement (Basel II - IRB) or making the portfolio more profitable. According to the easily implementable modelling techniques, data mining solutions widespread in practice. Using these models with no conditions can lead into inconsistent future on portfolio change. Consequence of this situation, contradictory predictions and conclusions come into existence. Recognizing and conscious handling of inconsistent predictions is an important task for experts working on different scene of the knowledge based economy and society. By realizing and solving the problem of inconsistency in...
Tipo: Journal Article Palavras-chave: Model aggregation; Consistent future; Data mining; CRM; Basel II; Research and Development/Tech Change/Emerging Technologies.
Ano: 2007 URL: http://purl.umn.edu/58928
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Customer relationship management in the agricultural machinery market Ciência Rural
Nunes,Amanda Letícia Pit; Abi-Saab,Otavio Jorge Grigoli; Ralisch,Ricardo.
ABSTRACT: Customer Relationship Management can be regarded as a business approach. The objective was to know the customers, meet their expectations, and thus build customer loyalty. Although, the agricultural sector makes significant economic contributions to the Brazilian market and induces sharp competition among its companies, a huge opportunity still presents itself for the diffusion and implementation of CRM in the agricultural machinery sector. This study aimed to highlight the importance of customer management, by introducing the customer relationship management (CRM) concept. This is possible in the event of reselling agricultural machines, with the intention of retaining the customers and raising the profitability of these companies. It is...
Tipo: Info:eu-repo/semantics/article Palavras-chave: Concessionaire; Customer loyalty; CRM; Marketing.
Ano: 2017 URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0103-84782017000700355
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