Main factors affecting the development of food microenterprises: an artificial neural networks analysis

Abstract

The development of micro-enterprises in the restaurant and mobile food service sector is a key component for local economic growth and job creation in the Quevedo canton, Los Ríos province, Ecuador. This research aimed to identify and prioritize the main elements of the micro, meso, and macro environment that influence the business development of food service micro-enterprises. A quantitative, descriptive, and non-experimental approach was applied, using a structured questionnaire administered to a representative sample of 166 micro-enterprises. This was complemented by analysis using Artificial Neural Networks. The results show that business development responds to a multifactorial dynamic, highlighting factors such as negotiating power with suppliers, organizational structure, access to credit policies, administrative and financial management, customer service training, and political uncertainty. Furthermore, the study reveals that, although variables such as digital marketing and the use of artificial intelligence have less relative importance in the model, their low incidence is associated with limitations in their adoption and strategic use. Finally, the research demonstrates the usefulness of Neural Networks as a methodological tool for prioritizing factors in business studies of micro-enterprises in the food sector in local environments.