快速消费品
星团(航天器)
计量经济学
业务
经济
计算机科学
营销
程序设计语言
作者
Andreas Niedermeier,Christian Mergel,Agnes Emberger‐Klein,Klaus Menrad
标识
DOI:10.1016/j.bioeco.2024.100064
摘要
Predictive models are increasingly crucial in navigating heterogeneous markets. This study develops a predictive model approach to forecast consumer cluster membership in the green fast-moving consumer goods sector, focusing on bio-based products like adhesives and plasters. Through two online surveys in Germany, we identified key factors acting as drivers and barriers, demonstrating their effectiveness in distinguishing similar consumer segments across both product categories. Utilizing multinomial logistic regression, we crafted a prediction model that accurately forecasts cluster membership, providing novel insights into consumer behavior towards non-food bio-based products. This facilitates the development of targeted business and marketing strategies, optimizing resource allocation in market research activities. Our findings offer significant contributions to understanding the dynamics influencing consumer choices in the bio-based product market.
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