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Online shopping has been experiencing continuous growth over the past few decades, a trend that was further accelerated by the COVID-19 pandemic. There is no expectation that this trend will slow down in the near future. The goal of this paper is to investigate specific factors, which could affect purchasing decisions on the Internet. We created two models, tested and compared them applying logistic regression on the sample of 1318 adults. Model 1 was designed to test the importance of other customers’ reviews by purchasing decisions. Model 2 tested the financial/non-financial benefits of online shopping. In model 1, we identified these statistically significant predictors related to social characteristics 1. Gender, 2. Study at university, 3. Identification with statement, 4. Purchase on electronic marketplaces, and with functionality: 5. The most trust-inspiring e-shop function, 6. Comparison of similar products from different sellers before purchasing. These factors explain, according to Nagelkerke R, 0.196 variability. In the second model for the social characteristics were: 1. Type of settlement, and for functionality: 2. Preferred payment option, and they explain 0.0341 variability of the dependent variable.
CERNY et al. (Mon,) studied this question.