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Speaker: Peeter VERLEGH Date and Location – Thursday November 24th 2022 from 13:30 to 17:0<\/strong>0 —————————————–<\/p>\n Nutrition claims are a common way to highlight the healthiness of a food by focusing on either the addition of positive nutrients in the food product or the removal of negative nutrients from it. Previous research has, however, not focused on comparing these two different types of nutrition claims. Through a meta-analysis of 174 effect sizes and three experimental studies, we investigate how consumers respond to addition-focused versus removal-focused nutrition claims. The results show that consumers have more positive attitudes and purchase intentions towards products with addition claims (vs. removal claims) and provide evidence that this difference is a result of a higher perceived value of the product with added positive nutrients. These results provide important insights to food marketers as well as public policy makers.<\/p>\n ——————————————<\/p>\n Speaker: Ghasem ZAEFARIAN<\/strong><\/p>\n \u00a0 <\/strong>Leeds Business School<\/i><\/p>\n Date and Location – Thursday November 24th 2022 from 13:30 to 17:0<\/strong>0 —————————————–<\/p>\n Endogeneity issues in empirical research have received increasing academic attention. Tackling endogeneity problems effectively and using the appropriate estimation techniques are important quality benchmarks in the publication process of many academic journals.In this workshop, I will outline the problem of endogeneity bias, provide an overview of potential sources, i.e. omission of variables, errors in variables and simultaneous causality. I will also discuss ways to deal with endogeneity, including techniques based on instrumental variables as well as instrument-free approaches.
\n<\/strong>Vrije Universiteit Amsterdam<\/i><\/p>\n
\nin Paris campus (P305) and on Zoom<\/strong><\/p>\nABSTRACT<\/h2>\n
\nin Paris campus (P305) and on Zoom<\/strong><\/p>\nABSTRACT<\/h2>\n
\nThis methodological workshop aims to provide researchers with an initial overview of the causes of and some existing remedies for endogeneity bias, which should be considered in designing research projects as well as when analysing data to obtain insights into cause and effect relationships<\/p>\n