Predictive models applied to the eco-efficiency indicators of a banking institution, Peru
DOI:
https://doi.org/10.21142/SS-0602-2025-e133Keywords:
Eco-efficiency, per capita consumption, linear regression, water, energy, recoverable solid wasteAbstract
Institutional savings for public entities was a mandatory provision established by Peru’s Ministry of the Environment (MINAM) in 2009, and in subsequent years the emphasis was oriented toward eco-efficiency. In this context, as a state-owned bank, Agrobanco set a baseline and adopted this environmental management tool in 2022. The aim of this study was to build prediction models for eco-efficiency indicators using Agrobanco’s records from 2022 to 2024. A linear regression analysis was conducted to investigate the relationship between the number of employees and indicators for energy and water savings, as well as the generating of recoverable solid waste, as published in the institution’s quarterly reports on its official website. According to the p-value, the significant models for the study were CIDCA (2.07E-04), CCE (3.11E-06) and CIDCE (1.80E-09), relative to their critical values. The study found that per capita water consumption and electricity consumption demonstrate a positive effect with respect to the number of employees, reflecting the effectiveness of the management instrument for these resources. It should be noted that the established models for the generation of recoverable waste do not indicate a significant relationship to the number of employees when predicting their behavior. To summarize, the data from the eco-efficiency indicators for water and energy savings from 2022 to 2024 facilitate the building of effective predictive models for evaluating the management tool.
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Copyright (c) 2025 Leslye Millones-Cumpa, July Zegarra-Choque

This work is licensed under a Creative Commons Attribution 4.0 International License.







