1. This is a mess... How the hell can I validate the consumer behaviors’ scales of my SEM model? Maria Pujol-Jover 1, Irene Esteban-Millat 1 1 Marketing Research Area, Economic and Business Studies, Open University of Catalonia (UOC) OBJECTIVE: The aim of this study is to present an inclusive protocol to validate the consumer behaviors’ scales of A SEM model. Contact: mpujoljo@uoc.edu iestebanm@uoc.edu BACKGROUND: Before empirically contrasting a SEM model it is compulsory to validate not only each measurement scale by itself but also with the rest of instruments included in the model. However, the consumer behavior literature does not present an exhaustive and complete guide about process validation of scales. Authors propose countless criteria and levels to achieve this validity. There is a lack of consensus and certain ambiguities that need to be analyzed. As a consequence researchers have serious troubles to follow a simple process of scales validity. RESULTS: We expect to demonstrate the psychometric properties of each construct (unidimensionality; reliability; convergent, discriminant and nomological validity;…) of our model through EFA and CFA. This would help a better understanding of our proposed protocol of scales validation. CONCLUSIONS: As the consumer behaviour literature needs a simple but rigorous guide to validate measurement scales we propose a complete and inclusive protocol to cover this gap in a methodological paper. CONTRIBUTION: we integrate all different positions of researchers in a unique procedure. Moreover, we give an empirical application to illustrate the different steps to follow in the scales validation process. That is, we validate the different measurement instruments of a proposed model. METHODS: Since the present paper has a methodological denotation is by itself an outcome. However, as we carry out a case study (obtained from an online survey to UOC students with a sample of 2574) to exemplify and clarify our proposed procedure it is necessary a particular methodology. Statistic technique Psychometric properties Exploratory factor analysis (EFA) Individual EFAs of measurement scales Principal component factor analysis Reliability Confirmatory factor analysis (CFA) Global CFA of measurement model Structural equations Convergent and discriminant validity Global CFA of structural model Nomological validity Interactivity Flow Focus attention Control Time distortion Challenges Positive affects Learning Content material Lecturer attitude Skills Personalization H10 H12 H7 H13 H5 H11 H8 H3 H1 H2 H4 H6 H14 H16 H15 H17 H9  Theoretical proposed model  Empirical analysis EFACFA Factorial analysis aplication suitability Correlations > 0,3 KMO > 0,5 Barlett sphericity test confirms significant correlations Selection of the estimation method Measurement model fit GFI, AGFI, NFI, TLI, CFI, IFI > 0,9 RMSEA <0,08 Scales dimensionality Eigenvalue > 1 Explained variance > 0,5 Factor loads > 0,5 Convergent validity Significative loads > 0,5 Items unidimensionality Explained variance analysis > 0,5 Reliability Item-total correlation > 0,3 Cronbach alpha > 0,7 Reliability Composite reliability> 0,7 Discriminant validity Confidence intervals (correlation pairs of variables) do not contain the unit