Exogenous variables as predictors of neighborhood store

Abstract

Neighborhood stores are an engine of the country's economy. However, they are exposed to situations such as the arrival of discount stores, the use of digital channels, changes in consumer habits, and poor physical structures. Therefore, studying exogenous variables to forecast their effect on sales is relevant. The objective of this study is to model econometrically to forecast the effect of exogenous variables on the sales of neighborhood stores. The research uses a quantitative, descriptive, correlational field method with two phases; the first is applying a measurement instrument to a cluster sample of 66 stores. From the data collected in the second phase, econometric models were tested to establish the effect of the exogenous variables on the sales of neighborhood stores. Based on the values found in the proposed model, it can be inferred that the most influential variable is the unemployment rate, followed by the employment rate and inflation. It is concluded that it is essential for neighborhood stores to reflect on the effects of environmental variables on their commercial activity to be financially sustainable and prepared in times of economic crisis. The study suggests that shopkeepers should be aware of exogenous variables to optimize their sales and avoid being immersed in unstable financial situations.