Conduct Research And Find Two Studies Related To The Variables

Regression analysis is a useful method for understanding connections between different factors in a business. For e-commerce businesses, it can help predict success and determine the effectiveness of systems. Independent variables, such as frequency of online shopping, can be used to explain changes in a dependent variable. Studies have found positive correlations between different factors, such as CP and e-commerce adoption in SMEs, and promotional activities and sales. Overall, this type of analysis can provide valuable insights for businesses looking to improve their operations. The approach used in the study involved analyzing correlation and variable importance, ultimately finding that the reputation of a product in the online market improves over time. Additionally, studying cross-sectional data on bilateral trade through cross-border e-commerce can also reveal important information for businesses.

I am unable to directly provide specific recent research articles or their results due to limitations in my current browsing capabilities. However, I can guide you through the process of finding such studies.

To find studies related to the variables used in e-commerce, such as correlation and regression, you can visit academic databases like Google Scholar, PubMed, or ResearchGate. By searching for terms like "e-commerce variables correlation regression study," you should be able to find academic research articles that meet your criteria.

When analyzing the results of such studies, the r-value (correlation coefficient) is a measure of the strength and direction of the linear relationship between two variables. A value close to 1 indicates a strong positive correlation, while a value close to -1 indicates a strong negative correlation. A value near 0 suggests no linear relationship.

Please conduct a search on the suggested academic databases or specify any additional criteria, and I can assist you further.

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