This research focuses on the moderating effect of culture on the relationships between KMS and other variables affecting KMS in the service industry. The effects of a number of variables on KMS were examined via analysis and hypothesis testing. These variables included culture; people; process; strategy; and technology. The results show that culture and people have a substantial impact on KMS's performance, emphasizing the need of cultivating a supportive company culture and empowering employees. Furthermore, strategy and technology were shown to be critical in allowing effective knowledge management practices in the service industry. The research also investigates the moderating impacts of culture on these linkages, demonstrating that culture modulates the impact of process, technology, and strategy on KMS. However, it was shown that the interplay between culture and people did not substantially alter the link between people and KMS. These results provide useful insights for firms looking to improve their knowledge management methods, underlining the need to take culture into account and aligning it with strategic goals and technology solutions. While the study adds to our understanding of knowledge management in the service industry, further research is needed to investigate other elements and situations. Overall, this research has practical significance for firms looking to enhance their knowledge management activities and overall organizational performance.

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.