Analysis of three-way non-symmetrical association of food concepts in cross-cultural marketing

Rosaria Lombardo (), Eric J. Beh () and Luis Guerrero ()
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Rosaria Lombardo: University of Campania
Eric J. Beh: University of Newcastle
Luis Guerrero: IRTA-Monells

Quality & Quantity: International Journal of Methodology, 2019, vol. 53, issue 5, No 5, 2323-2337

Abstract: Abstract This paper analyses the non-symmetrical association among some key-words in a food context, given the European countries and gender of participants to a survey. The aim is to understand the meaning of the food concepts traditional and innovation associated to selected key-words in cross-cultural marketing. For studying the association among three categorical variables, usually, one can refer to Pearson’s three-way statistic, but in case of non-symmetrical association we prefer to consider Marcotorchino’s three-way predictability index and its related $$C_M$$ C M -statistic. Doing so, we present a generalisation of three-way non-symmetrical correspondence analysis to portray the predictability of food concepts given the knowledge of participants’country and gender.

Keywords: Food concepts; Three-way categorical data; Predictability index; Non-symmetrical three-way correspondence analysis (search for similar items in EconPapers)
Date: 2019
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DOI: 10.1007/s11135-018-0733-6

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