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<div> The online environment has its own specifics, which shape the specific behavior of all market subjects, both customers and companies that trade electronically. The aim of the paper is to create, quantify and verify a conceptual comprehensive model of relationships between determinants that influence consumers when shopping online. The impetus for the conducted research was the discovery of the non-existence of a comprehensive model of online shopping behavior that reflects the specifics of the online environment. The main research method is the method of online questioning in the form of a questionnaire survey among a selected group of Czech respondents (n = 926) shopping online with the aim of evaluating the determinants of online shopping behavior. The results of the questionnaire survey are subsequently used to build a comprehensive model of online shopping behavior, which was statistically compiled and verified using the PLS-SEM method, which, based on statistical data, estimates the size and quality of the links between the measured (manifest) and assumed unmeasured (latent) variables. The results show that the selected factors (31 factors) explain up to 82.53% of the variability of the total variance. The results of the correlation analysis of the factors confirmed that the defined factors are not mutually dependent and that in the comprehensive model the factors are not only identified but also statistically significant. The results also confirmed that the correlation of e.g. psychological factors are stronger than dependence on other investigated factors in the comprehensive model of online shopping behavior. The research clearly showed that the key factors for customers when shopping online are Security and risk elimination (SE), together with the Online distribution and logistics (OD) and Online payments (OP). Impulsive online shopping was identified by customers as the least important factor. The validated model provides a comprehensive explanation of the current phenomenon of online shopping that integrates and extends previous studies identifying behavioral models of online shopping behavior. </div>