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Published on: September 11, 2021
Evaluation of psychometric properties of perceived value applied to universities
Marelby Amado-Mateus1, Yonni Angel Cuero-Acosta1, Alfredo Guzman-Rincón2
1Business School, Universidad del Rosario, Bogotá, Colombia.
Abstract:
Over the past 20 years, the construct of perceived value has been the subject of much research, most of it applied to the service sector. The intangible nature of this sector requires an in-depth analysis of customer perceptions of what they give and what they receive. In this research, perceived value is applied in the context of higher education, where perceived quality faces several challenges and has a tangible component that is related to their experience when receiving the educational service, and an intangible component that is related to the image and reputation of the university. One of these challenges is the increasingly competitive environment of universities, so it is important to understand what factors influence students' perception of value. For this purpose, several scales of perceived value were reviewed and one was selected and its psychometric properties were evaluated. For this evaluation, cultural adaptation techniques, exploratory factor analysis and confirmatory factor analysis were used. The statistical results showed the validity and reliability of the scale applied to universities in the Colombian context.
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Decision Making: P-value Method
First, a specific claim about the population parameter is proposed. The claim is based on the research question and is stated in a simple form. Further, an opposing statement to the claim is also stated. These statements can act as null and alternative hypotheses: a null hypothesis would be a neutral statement while the alternative hypothesis can...
P-value
P-value stands for the probability value. P-value is the probability that, if the null hypothesis is true, the results from another randomly selected sample will be as extreme or more extreme as the results obtained from the given sample.
A large P-value calculated from the data indicates to not reject the null hypothesis. But a higher P-value does not mean that the null hypothesis is true. The smaller the P-value, the more...

