A neural network extension for solving the Pareto/Negative Binomial Distribution Model

Shao-Ming Xie

This research proposes a new estimation scheme to solve the estimation burden of the Pareto/NBD model and to release its power in out-of-sample prediction and then builds a neural network-based model (NNA-based model) for parameter estimation of the Pareto/NBD model, by designing a loss function to include the likelihood of the Pareto/NBD model and the mean absolute error.

Introduction

In customer relationship management (CRM), market practitioners and academic researchers are concerned about how a company maintains long-term and sustainable customer relationships (Bolton & Tarasi, 2017; Payne & Frow, 2005). A long-run beneficial customer relationship is the result of an effective CRM strategy whereby the firm needs to harness the strategic-, operational-, and analytical-level processes geared toward customer value creation (Iriana & Buttle, 2007; Bolton & Tarasi, 2017), customer satisfaction (Hassan et al., 2015; Mithas et al., 2005), and customer loyalty (Khan et al., 2022). These CRM results are based upon precise customer relationship monitoring. Nevertheless, firms are unable...

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