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The NBD-Dirichlet model for Italian sparkling wines: understanding competitive relationships among brands

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  • Francesca Bassi

    (University of Padova)

Abstract

The NBD-Dirichlet model is applied to describe the Italian market of sparkling wines by means of repeated purchases recorded by a sample of families over two years. Sparkling wine is a convenience good with a moderate level of involvement, high frequency of purchase and low perceived differentiation. The Italian market of sparkling wine is characterized by a large number of brands proposing similar products offered in supermarkets. This very large assortment represents a very particular situation, both in terms of sales strategies and consumer purchasing behavior. This specific type of market can be well represented by the NBD-Dirichlet model to obtain analyses that explain the competitive dynamics among brands and their relative performance. Results of model estimation identified at least three groups of brands with different positioning in the market. Managerial implications of these results are linked to the possibility for each single brand to compare actual performance with that estimated by the model and with competitors belonging to the same segment.

Suggested Citation

  • Francesca Bassi, 2025. "The NBD-Dirichlet model for Italian sparkling wines: understanding competitive relationships among brands," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 34(4), pages 707-726, September.
    • Handle: RePEc:spr:stmapp:v:34:y:2025:i:4:d:10.1007_s10260-025-00778-0
    DOI: 10.1007/s10260-025-00778-0
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    References listed on IDEAS

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    1. Leeflang, P.S.H. & Wittink, Dick R., 2000. "Building models for marketing decisions: past, present and future," Research Report 00F20, University of Groningen, Research Institute SOM (Systems, Organisations and Management).
    2. Jarvis, Wade & Mueller, Simone & Chiong, Kathleen, 2010. "A latent analysis of images and words in wine choice," Australasian marketing journal, Elsevier, vol. 18(3), pages 138-144.
    3. repec:dgr:rugsom:00f20 is not listed on IDEAS
    4. Bassi, Francesca & Pennoni, Fulvia & Rossetto, Luca, 2021. "Market Segmentation and Dynamic Analysis of Sparkling Wine Purchases in Italy," Journal of Wine Economics, Cambridge University Press, vol. 16(3), pages 283-304, August.
    5. Rossetto, Luca & Gastaldello, Giulia, 2018. "The Loyalty Structure of Sparkling Wine Brands in Italy," Journal of Wine Economics, Cambridge University Press, vol. 13(4), pages 409-418, November.
    6. Desmond Lam & Richard Mizerski, 2009. "An investigation into gambling purchases using the NBD and NBD–Dirichlet models," Marketing Letters, Springer, vol. 20(3), pages 263-276, September.
    7. Francesca Bassi & Fulvia Pennoni & Luca Rossetto, 2020. "The Italian market of sparkling wines: Latent variable models for brand positioning, customer loyalty, and transitions across brands' preferences," Agribusiness, John Wiley & Sons, Ltd., vol. 36(4), pages 542-567, October.
    8. Franses,Philip Hans & Paap,Richard, 2010. "Quantitative Models in Marketing Research," Cambridge Books, Cambridge University Press, number 9780521143653, November.
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