Using Logistic Regression to Predict Business Model Success in Microenterprises - Cueva Bermeo, André Alberto; Feijoo Jaramillo, Irene Maria; Sarmiento Chugcho, Carlos Bolívar; Mite Albán, María Teresa (Revista Universidad de Guayaquil, 2025)
This study evaluated how gender and marketing activities influence the success of business models in Machala, Ecuador, an especially challenging context for microbusinesses and artisans during the COVID-19 pandemic. Data from 213 companies selected through non-probabilistic sampling were used. The dependent variable was the success of the business model, evaluated binary, while the independent variables were gender and marketing activities. A logistic regression analysis was used using SPSS. The results showed that both gender and marketing activities are significant predictors of business model success. Businesses led by men are 4.92 times more likely to be successful, and implementing marketing activities increases this probability significantly. Gender diversity and the implementation of marketing strategies are critical factors for business success. Promoting these elements can optimize the performance of business models in similar contexts.
Keywords: Entrepreneurship; gender; marketing; business success; logistic regression