Social cybernetics, as an interdisciplinary field, has gained increasing interest in the last decade due to the influence of information technologies in society through connectivity, Internet of things, process automation, artificial intelligence among others. This research focuses on exploring the relationship between social cybernetics (communication and control mechanisms) based on information technologies and local development, using structural equation modeling as an analytical tool. The design was non-probabilistic, with a sample of 482 people. The independent variables under study were Use of ICT for communication between local authorities and the population (CAP), Use of ICT for collaboration between public and private institutions (CPPC), Use of ICT for shared decision making (SDM), Use of ICT for local development planning (LDP) and Use of ICT for knowledge management (KM); and the dependent variable was Local Development (LD). It was determined that there is a relationship between all of them except with CAP. The direction and magnitude of the other ratios were: + 0.1390; - 0.3661; + 0.4472 and + 0.8432 respectively. The coefficient of determination (R2) was 93.69% facilitating the prediction of future results. The model has an adequate fit.

The business context has been affected by the action of Covid 19, and companies must react to this new reality. The research analyzes people, processes and technology and their effect on the development of the respective business strategy in small companies in Huancayo, Peru. The study design was non-probabilistic, cross-sectional, qualitative-quantitative and explanatory in a sample of 99 business units. The analytical technique used was structural equation modeling based on PLS. The results indicate that there is a positive relationship between the processes and technology used and the implementation of actions to achieve their objectives. No significant relationship was found with people, given that in the face of the health emergency, economic paralysis, closure of markets and sectors, the companies had to make decisions and postpone concern for human resources. The coefficient of determination (R2) was 79.3%, which shows that the model presented allows predicting future results.