SPSS Amos
Nils Holmberg
210401
Dataset
We illustrate the SEM using a subset of data from the International Sponsorship Study (ISS 2016), which broadly captures consumer attitudes towards international sponsorship deals. Specifically, we test the predictive relationships between four latent factors.
Theoretical model
We test whether animosity towards Germany and ethnocentrism more generally, predict consumer attitudes (ATT) towards German automotive brand SMART. We also investigate whether higher levels of ATT significantly improve perceptions of fit for a hypothetical sponsorship between SMART and the England international soccer team.
Theoretical model
Hypotheses
Stated in the form of three directional hypotheses, the following predicted relationships are tested:
- H1a: Higher animosity towards Germany leads to a lower attitude towards SMART.
- H1b: Higher ethnocentrism leads to a lower attitude towards SMART car brand.
- H1c: A higher attitude towards SMART leads to a more favourable perception of its fit with the England soccer team as its primary sponsor.
SPSS Amos hands-on
SPSS Amos is a powerful structural equation modeling (SEM) software helping support your research and theories by extending standard multivariate analysis methods, including regression, factor analysis, correlation and analysis of variance.