Wilson Marin

The management of cultural heritage is crucial for optimizing natural, archaeological and cultural resources for tourism development. This study focuses on evaluating Uchuraccay (a village in Peru) residents’ perceptions of this relationship. A survey of 520 respondents examined tangible and intangible heritage aspects, alongside tourism’s environmental, social and economic dimensions. Findings reveal challenges: 38.65% feel that tangible heritage lacks appreciation due to limited public awareness, insufficient conservation funding and limited promotion. Additionally, 40.96% believe that intangible heritage suffers from inadequate management and preservation policies. These insights underscore the necessity for cultural heritage assessments to enhance economic growth through targeted tourism strategies.

In an increasingly dynamic and competitive global economy, where rapid technological advancements continually reshape market structures, digital transformation has emerged as a critical driver of business resilience and sustainable growth. This study examines how the adoption of digital technologies contributes to enhancing operational efficiency, organizational adaptability, and long-term competitiveness. Using a mixed-methods approach, quantitative and qualitative data were collected from 70 medium-sized service-sector companies in Peru. The findings reveal that organizations implementing digitalization processes experienced notable improvements in productivity (63%) and responsiveness to changing environments (58%). However, persistent challenges remain, particularly in relation to the technological gap, change management, and digital skills training. The study concludes that digital transformation should not be understood merely as technological modernization, but rather as a comprehensive strategic process aimed at achieving the Sustainable Development Goals (SDGs), promoting decent work, and fostering more resilient economies in developing countries.

Nowadays, implementing data analytics is necessary to improve the collection, evaluation, analysis, and organization of data that allow the discovery of patterns, correlations, and trends that improve knowledge management, development of strategies, and decision-making in the organization. Therefore, this study aims to provide an accurate and detailed assessment of the current state of data analytics in the retail sector, identifying specific areas of improvement to strengthen knowledge management in organizations. The research is applied with a quantitative approach and non-experimental design at a descriptive and propositional level. The survey technique was used, and as a data collection instrument, a questionnaire addressed to 351 employees of companies in the retail sector concerning the variable data analysis with the dimensions of data extraction, predictive analysis, and machine learning and the variable management of the knowledge with the dimensions knowledge creation and knowledge storage. The results show that 52.99% of collaborators indicate that the level of data extraction is terrible, 57.83% indicate that the level of predictive analysis is wrong, and 54.99% express that the level of machine learning is average, which contributes to the implementation of innovative resources and solutions that promote the inclusion of a high-tech approach to address information management problems and contribution to the development of knowledge in an institution.