Using the Dirichlet model to predict how fashion brands compete and grow on eBay

Abstract

Abstract E‐fashion brand competition has historically been studied from an attitudinal lens, through surveys and theory‐based approaches. These studies generally examine consumer attitudes, satisfaction and loyalty; highlighting that trust, satisfaction and reputation are key e‐commerce success elements. However, the empirical consumer behaviour literature rebuts the use of attitudes to explain brand performance, criticising their subjectivity and the overall ineffectiveness of loyalty as a brand growth tool. The article presents Gerald Goodhardt and colleagues' Dirichlet model as an alternative approach to understanding e‐fashion buyer behaviour. The Dirichlet model is a robust, stochastic model that has reliably predicted well‐established law‐like patterns of buyer behaviour and brand competition. We apply Dirichlet modelling to a new, non‐fast moving consumer goods category to extend consumer behaviour research in the online environment. The study uses consumer panel data from the United Kingdom, across two consecutive years. We conclude that the Dirichlet model has an excellent fit within the eBay fashion brand market. The study also identifies that the well‐known double jeopardy pattern exists within this market, demonstrating that e‐fashion brands grow through acquisition rather than retention of customers. This provides a different viewpoint than most e‐fashion brand growth literature. In addition to this, we examine the predictive capability of the Dirichlet model. We use a holdout sample to show that the model can predict future brand performance metrics, which is an exciting new development in consumer behaviour research.

Cite this work

No public copy is stored for this record, so only the metadata is cited.

Stored only when both papers are in the corpus — 6 citations exist upstream.

Papers that cite the same references — the relational fallback while embeddings are still backfilling.