The role of involvement with public transport in the relationship between service quality, satisfaction and behavioral intentions.

• The relationship among SQ, SA, INV and BI is analyzed using 8 models and 5 samples. • Results suggest that INV is a complete mediator between SA and BI or loyalty. • Results also suggest that SA is a complete mediator between SQ and INV towards PT. • INV is the factor with the highest effect on BI, followed by SQ and SA. • The following sociodemographic characteristics produce heterogeneity in the factors. • City, household location, gender, age, travel frequency, education and income level. Several studies have made manifest that involvement with public transport play a key role in the intentions of its use. However, conflicting models exist in the literature about involvement's role in the relationship between service quality, satisfaction and behavioral intentions or loyalty. Previous studies suggest all possible roles: antecedent, mediator, moderator and direct effects. A structural equation modeling approach is applied here to further understand the role of involvement with public transport, comparing eight alternative models and using data from a single survey carried out in five European cities (Madrid, Rome, Berlin, Lisbon and London). Later, the study uses a multiple indicators and multiple causes structural equation modeling approach (SEM-MIMIC) to analyze the effect of heterogeneity present in the data over the four constructs considered (service quality, satisfaction, involvement and behavioral intentions). This comprehensive methodological approach provides a number of noteworthy findings, including the empirical verification that satisfaction is a full mediator between service quality and involvement, and involvement is a full mediator between satisfaction and behavioral intentions. The results further suggest that involvement is the factor that contributes most to behavioral intentions or loyalty, followed by service quality perceptions and satisfaction. Lastly, this study demonstrates the relevance of controlling for heterogeneity in users' perceptions, so as to obtain more robust relations among factors and identify significant differences among market segments, which could prove useful for public transport operators or policy makers. [ABSTRACT FROM AUTHOR]