Abstract
Fashion brand extension is a well-developed strategy which in principle benefits consumers because there will be more variety of products available under the brand umbrella. In a recently published paper (Choi et al., Journal of the Textile Institute, 102(10):890–904, 2011), a statistical analysis for fashion brand extensions is reported. Despite getting some insights, the special features of the data lead to the failure of many traditional statistical tests. In this chapter, we employ artificial neural networks (ANN) to explore the same brand extensions problem in marketing, and illustrate how we can provide scientifically sound evidence to support more parts of the hypotheses which cannot be proven by conventional statistical testing methods. This result reveals that ANN can be a useful tool for conducting analysis for business problems in a scientific manner. Moreover, we discuss the consumer welfare issues related to the findings on brand extensions of fashion brands from different geographical regions and different periods of time.
This research is partially supported by the funding provided by the Hong Kong Polytechnic University.
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Choi, TM., Yu, Y. (2014). An Analysis of Fashion Brand Extensions by Artificial Neural Networks. In: Choi, TM. (eds) Fashion Branding and Consumer Behaviors. International Series on Consumer Science. Springer, New York, NY. https://doi.org/10.1007/978-1-4939-0277-4_5
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DOI: https://doi.org/10.1007/978-1-4939-0277-4_5
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