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Managing Group Decision Making criteria values using Fuzzy Ontologies
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Consensus-Based Decision Support Model and Fusion Architecture for Dynamic Decision Making
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In: Electrical and Computer Engineering Publications (2022)
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Consistency-driven methodology to manage incomplete linguistic preference relation: A perspective based on personalized individual semantics
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Consistency improvement with a feedback recommendation in personalized linguistic group decision making
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Consistency Improvement With a Feedback Recommendation in Personalized Linguistic Group Decision Making
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The risk assessment of construction project investment based on prospect theory with linguistic preference orderings
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Revisiting Fuzzy and Linguistic Decision-Making: Scenarios and Challenges for Wiser Decisions in a Better Way
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Personalized individual semantics-based approach for large scale failure mode and effect analysis with incomplete preference information
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Consensus and opinion evolution-based failure mode and effect analysis approach for reliability management in social network and uncertainty contexts
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Using Multi-granular Fuzzy Linguistic Modelling Methods to Represent Social Networks Related Information in an Organized Way
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A comparison between Fuzzy Linguistic RFM Model and traditional RFM model applied to Campaign Management. Case study of retail business.
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Trust Based Fuzzy Linguistic Recommender Systems as Reinforcement for Personalized Education in the Field of Oral Surgery and Implantology
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Dealing with incomplete information in linguistic group decision making by means of Interval Type‐2 Fuzzy Sets
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In: ISSN: 0884-8173 ; EISSN: 1098-111X ; International Journal of Intelligent Systems ; https://www.hal.inserm.fr/inserm-03026626 ; International Journal of Intelligent Systems, Wiley, 2019, 34 (6), pp.1261-1280. ⟨10.1002/int.22095⟩ (2019)
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Dealing with Incomplete Information in Linguistic Group Decision Making by Means of Interval Type-2 Fuzzy Sets
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A risk-aware fuzzy linguistic knowledge-based recommender system for hedge funds
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Expanding Grey Relational Analysis With the Comparable Degree for Dual Probabilistic Multiplicative Linguistic Term Sets and Its Application on the Cloud Enterprise
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A Fuzzy Linguistic RFM Model Applied to Campaign Management
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Abstract:
In the literature there are some proposals for integrated schemes for campaign management based on segmentation from the results of the RFM model. RFM is a technique used to analyze customer behavior by means of three variables: Recency, Frequency and Monetary value. It is s very much in use in the business world due to its simplicity of use, implementation and interpretability of its results. However, RFM applications to campaign management present known limitations like the lack of precision because the scores of these variables are expressed by an ordinal scale. In this paper, we propose to link customer segmentation methods with campaign activities in a more effective way incorporating the 2–tuple model both to the RFM calculation process and to its subsequent exploitation by means of segmentation algorithms, specifically, k-means. This yields a greater interpretability of these results and also allows computing these values without loss of information. Therefore, marketers can effectively develop more effective marketing strategy.
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Keyword:
2-tuple model; campaign management; IJIMAI; relational strategy; RFM
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URL: https://reunir.unir.net/handle/123456789/12438
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Using clustering methods to deal with high number of alternatives on Group Decision Making
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An overview on managing additive consistency of reciprocal preference relations for consistency-driven decision making and Fusion: Taxonomy and future directions
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