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Consumer preferences for beer attributes in Germany: A conjoint and latent class approach

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  • Meyerding, Stephan G.H.
  • Bauchrowitz, Alexander
  • Lehberger, Mira

Abstract

Despite high marketing expenses by large breweries, the traditional German beer market has been declining for many years. The development may be related to reasons such as demographic change or increased health awareness. In a changing market, it is especially important to gain a precise knowledge of these variables. The aim of this study is to identify the attributes of beer that are crucial to the purchasing process and to segment the German market for beer. For this purpose, a conjoint analysis was carried out with a subsequent latent class analysis. As a result of the latent class analysis, three consumer segments were identified. In addition to achieving results from the conjoint analysis, the segments were characterized by sociodemographic status, beer-related questions, and results from a food-related lifestyle approach.

Suggested Citation

  • Meyerding, Stephan G.H. & Bauchrowitz, Alexander & Lehberger, Mira, 2019. "Consumer preferences for beer attributes in Germany: A conjoint and latent class approach," Journal of Retailing and Consumer Services, Elsevier, vol. 47(C), pages 229-240.
    • Handle: RePEc:eee:joreco:v:47:y:2019:i:c:p:229-240
    DOI: 10.1016/j.jretconser.2018.12.001
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    1. Rigoberto A. Lopez & Xenia Matschke, 2012. "Home Bias in US Beer Consumption," Pacific Economic Review, Wiley Blackwell, vol. 17(4), pages 525-534, October.
    2. Maack, Klaus & Haves, Jakob & Schmid, Katrin & Stracke, Stefan, 2011. "Entwicklung und Zukunft der Brauwirtschaft in Deutschland," Study / edition der Hans-Böckler-Stiftung, Hans-Böckler-Stiftung, Düsseldorf, volume 127, number 260.
    3. Liesbeth Colen & Johan Swinnen, 2016. "Economic Growth, Globalisation and Beer Consumption," Journal of Agricultural Economics, Wiley Blackwell, vol. 67(1), pages 186-207, February.
    4. Choi, David Y. & Stack, Martin H., 2005. "The all-American beer: a case of inferior standard (taste) prevailing?," Business Horizons, Elsevier, vol. 48(1), pages 79-86.
    5. Junyi Shen, 2009. "Latent class model or mixed logit model? A comparison by transport mode choice data," Applied Economics, Taylor & Francis Journals, vol. 41(22), pages 2915-2924.
    6. Greene, William H. & Hensher, David A., 2003. "A latent class model for discrete choice analysis: contrasts with mixed logit," Transportation Research Part B: Methodological, Elsevier, vol. 37(8), pages 681-698, September.
    7. Bavorova, Miroslava & Unay-Gailhard, İlkay & Lehberger, Mira, 2016. "Who buys from farmers’ markets and farm shops: The case of Germany," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 40(1), pages 107-114.
    8. Julia Schricker, 2016. "A Boost for the Craft Beer Market," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 69(07), pages 49-52, April.
    9. C M Costanzo & W C Halperin & N D Gale & G D Richardson, 1982. "An Alternative Method for Assessing Goodness-of-Fit for Logit Models," Environment and Planning A, , vol. 14(7), pages 963-971, July.
    10. Gunarathne, Anoma & Hemmerling, Sarah & Krestel, Naemi & Zühlsdorf, Anke & Spiller, Achim, 2017. "Segmenting Foodies in Germany: Actionable Insights for Agro-food Marketers," 2017 International Congress, August 28-September 1, 2017, Parma, Italy 261422, European Association of Agricultural Economists.
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