Measuring the Image of Private University as a Generic Product: Validation of a Scale

The compulsory nature of online training in university education, brought about by COVID-19, has opened the door to the emergence of several potential competitors in the university space. Thus, measuring a university's image may have even greater importance for the management and differentiation of universities in the new post-COVID-19 horizon. This study aims to test whether a standardized scale of brand image measurement is valid for measuring the image of the 'private university';product. A non-probabilistic convenience sample was chosen, collecting information from 728 citizens from the same territory (Andalusia). The procedure to validate the scale involves dividing the sample (728) into two sub-sets: one to establish the scale, and the other to validate the results. The methodology applied is Confirmatory Factor Analysis using EQS 6.3 software. The scale was validated, and the main results show that people favor the quality of private universities, their commitment to society, and the perfect option that they are. Additionally, results show the idea that private universities present characteristics absent from public ones as non-significant, and do not agree that private universities provide a high value concerning the price that has to be paid.

COVID-19's First Wave: Examination of Impact on Food Purchasing Behaviour in the Eurozone.

COVID-19 has had a negative impact on the living conditions of people in all countries worldwide. With a devastating economic crisis where many families are finding it difficult to pay bills and make ends meet, increases in prices of food basket staples can be very worrying. This study examines the relationship between the incidence of the pandemic during the first wave in 16 Eurozone countries with the variation experienced in food prices. We analysed the harmonised index of consumer food prices (included in HICP) and the classification of the degree of pandemic impact by country, the latter established with the index of deaths provided by the Johns Hopkins Center. The procedure used compared actual food prices during the first wave (March to June 2020) with those foreseeable in the absence of the pandemic. Time series analysis was used, dividing the research period into two phases. In both phases, the Holt-Winters model was applied for estimation and subsequent prediction. After a contrast using Kendall's tau correlation index, it was concluded that in the countries with the highest death rates during the first wave, there was a higher increase in food prices than in the least affected countries of the Eurozone.