**3. Materials and Methods**

A quantitative approach was used, as numerical data were collected and subjected to statistical analysis to verify the correlation of two variables, as well as the generalization and objectification of sample results. The design was non-experimental since there was no manipulation of the variables; rather, they will be examined and compared as they occur in the natural environment. The design is transverse, as data was collected only for the year 2021 (Hernández Sampieri 2010).

This research focuses on a case study of the rural community of La Florida, located in the Atavillos Bajo District, Huaral Province, Lima Department, Peru. The community is considered the base tourist center of the "Rúpac-Marca Kullpi" archaeological complex, also called "El Machu Picchu Limeño", which was designated as national cultural heritage through National Directorial Resolution 283/INC on 25 June 1999. This archaeological site dates to 1200 CE and belongs to the pre-Inca culture of Los Atavillos (Congreso de la República 2017a). During the research process, direct contact was made with residents of La Florida to obtain information and to learn about the residents' perspective on the relationship between sustainable tourism and local development in their area. The statistical population was delimited by a selection criterion for those over the age of majority. All individuals over 18 years of age who live in this population center were considered, yielding a total of 843 persons of undifferentiated sex. Using a simple random probability sampling under the finite population formula, given a confidence level of 95% and a margin of error of 5%, a sample number (n) of 265 inhabitants was selected. These individuals participated in a structured survey with closed questions based on the Likert scale, addressing relevant social, economic, and environmental dimensions

To certify the quality of the survey's content, it was subjected to an expert judgment process. Three specialists, in community development, sustainable tourism, and methodology, respectively, evaluated the consistency, clarity, and concordance of the questions. Regarding the statistical reliability of the survey questionnaire, Cronbach's Alpha test (α) was applied. This test establishes a coefficient that theoretically varies from 0 to 1, distributed as follows: values from 0 to 0.2 are considered to indicate very low reliability, 0.2 to 0.4 low reliability, 0.4 to 0.6 moderate reliability, 0.6 to 0.8 good reliability, and 0.8 to 1 high reliability. If α is close to 0, then the quantized responses are not reliable at all, and if close to 1 the responses are very reliable. As a general rule, if α ≥ 0.8, the answers are considered reliable (Leontitsis and Pagge 2007). After all the surveys had been administered, the results were processed using the statistical software SPSS version 27. To obtain test results, the following procedure was used: first select the "Analyze" option, then the "Scale" option, and third "Reliability Analysis." Then, select the items to evaluate, and finally choose the option "Alpha Model." Following these steps, an α value of 0.8 was obtained, thus indicating high reliability according to the Alpha scale.

To carry out relevant documentary analysis, an extensive search was undertaken for scientific articles indexed in prestigious databases such as Scopus and Web of Science with the keywords: sustainable tourism, sustainable tourism and local development, benefits of local development, tourism and renewable energy. This search extended to official national and supranational organizations: World Tourism Organization (UNWTO), MINEM, Instituto Nacional de Estadística e Informática (INEI), and Peruvian Institute of Economy (INEI). Figures from accommodation associations, travel agencies and the like (AHORA), and the Ministry of Foreign Trade and Tourism (MINCETUR) have also been used to obtain tourism data and identify new trends in the national and international tourism market.

The analysis of renewable energy potential was specifically linked to the use of solar and wind energy, involving the use of photovoltaic panels and wind turbines, respectively. For this purpose, computer simulations were used to determine solar radiation intensity through SOLARGIS, a simulator belonging to the World Bank, and EnAir, a simulator that

generates energy demand and/or generation calculations (in kWh) for a given geographic location. On this basis, we performed calculations to estimate projected energy demand and contributions by the aforementioned systems, all with a high degree of precision (98.5%). Various studies have considered the use of geographic information tools to evaluate tourism resources and renewable energy potential (Valjarevi´c et al. 2018; Rahayuningsih et al. 2016).
