ABSTRACT
Cross-cultural consumer behavior is of market interest due to globalization of marketplaces, migration, multicultural marketplaces, and diffusion in the EU of many languages. The objective of this study is to check whether the local language used in a marketing communication could affect the consumers’ preferences for food products. The theoretical foundation is the consumer motivational approach that goes deeper into motivations interfering with the consumers’ preference order. The multivariate conjoint analysis is used to evaluate the preferences for attributes described in different languages. A number of students from the University of Udine (located in the northeastern part of Italy) have been submitted to interviews to examine their preferences for a simulated sandwich package reporting information in different languages, distributed by vendor machine. The results suggest that the consumer’s reaction to local language depends on sociodemographic profile, cultural background, language knowledge, and family education, and the local language could actually be used as a market tool for market segmentation. These results are of interest to many EU countries with bilingual communities such as Spain, Belgium, the UK, Switzerland, and most of the Italian regions where local languages are still alive.
Notes
1. The contributes of marketing, sociology, psychology disciplines have created an interdisciplinary framework for the consumer behavior to explain the influence of immaterial factors as personality, perception of cultural and hedonic values and beliefs. For the purpose of marketing strategies, these factors have originated a sociodemographic approach, which includes language, ethnicity, age, status, size of family, income, education, social relation, and employment. To read more, see http://www.ehow.com/about_5162253_definition-consumer-behavior.html#ixzz2o21HWFNA.
2. The dependent variable is a rating on an ordinal scale of measurement that translates preferences, whereas the independent variables are often nominal or sometimes interval scale variables.
3. Green and Srinivasan suggest a minimum of 100 interviews enough to have reliable results.