Knowledge management and data mining for marketing

By Michael J. Shaw, C. Subramaniam, G. Tan, M. Welge. Decision Support Systems, 2001

624 citations recorded by the source corpus.

Subfields: Computational Theory and Mathematics, Information Systems, Marketing

View Paper: https://www.semanticscholar.org/paper/7fbb68352cce21d6653c77629adfb7f1eb565ee6

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In Computational Theory and Mathematics

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In Marketing

Citations in the corpus

Forecasting and operational research: a review (2008, background): “Snyder et al (2002) and Shenstone and Hyndman (2005) have pointed out the inconsistency between Croston’s model (that assumes”
Application of data mining techniques in customer relationship management: A literature review and classification (2009, methodology): “Examples of visualization model are 3D graphs, ‘‘Hygraphs” and ‘‘SeeNet” (Shaw et al., 2001).”
Identification of influencers - Measuring influence in customer networks (2008, background): “These techniques are typically based on information about individual characteristics of customers, where decision tree learners or logistic regressions are used to estimate the probability of a person to respond to a campaign, to buy a product, or to switch to another provider [54] [38] [12] [37].”
Customer relationship management research (1992‐2002): An academic literature review and classification (2005, background): “A deeper understanding of data mining and knowledge management in CRM is necessary in today's highly customer-centred business environment ( Shaw et al. , 2001”
Exploring the role of customer relationship management (CRM) systems in customer knowledge creation (2014, methodology): “Analytical systems such as data warehouses, data mining and OLAP are capable of creating deep knowledge about customers’ behaviors, purchasing trends, and preferences [6, 64].”
Data mining techniques and applications — A decade review (2017, methodology): “Shaw applied data mining in marketing to support marketing [22].”
Integrating AHP and data mining for product recommendation based on customer lifetime value (2005, neutral): “Data mining techniques [9] are a widely used information technology for extracting marketing knowledge and further supporting marketing decisions [4,5,33].”
Modeling wine preferences by data mining from physicochemical properties (2009, background): “Another interesting application is target marketing [24].”
Knowledge management technologies and applications - literature review from 1995 to 2002 (2003, background): “…objective for applying DM to extract knowledge from a database for certain management issues, such as customer service support, corporate failure prediction, marketing, and grid services (Abidi, 2001; Cannataro et al., 2002; Ha et al., 2002; Hui & Jha, 2000; Lin & McClean, 2001; Shaw et al., 2001).”
Artificial intelligence in supply chain management: A systematic literature review (2021, methodology): “Gligor et al. (2018) propose an ANN-based solution for forecasting the electricity production of a photovoltaic power plant, and Sheremetov et al. (2013) focus on different models, such as a feedforward neural network model and a Gamma classifier for forecasting in the time series context of…”