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A Bayesian Dual Clustering Approach for Selecting Data and Parameter Granularities

Mingyung Kim et al.

Marketing Science2026https://doi.org/10.1287/mksc.2024.1018article
FT50UTD24AJG 4*ABDC A*
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0.50

Abstract

We propose a Bayesian dual clustering method that infers both data and parameter granularities.

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https://doi.org/https://doi.org/10.1287/mksc.2024.1018

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@article{mingyung2026,
  title        = {{A Bayesian Dual Clustering Approach for Selecting Data and Parameter Granularities}},
  author       = {Mingyung Kim et al.},
  journal      = {Marketing Science},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1287/mksc.2024.1018},
}

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A Bayesian Dual Clustering Approach for Selecting Data and Parameter Granularities

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Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

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