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ZENODO
Article . 2025
License: CC BY
Data sources: ZENODO
ZENODO
Article . 2025
License: CC BY
Data sources: Datacite
ZENODO
Article . 2025
License: CC BY
Data sources: Datacite
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Mentoring and Entrepreneurship in Higher Education: A Study from the Plithogenic Statistics

Authors: Wilmer Ortega Chávez; Janett Karina Vásquez Pérez; Beker Maraza Vilcanqui; Nazario Aguirre Baique; Carlos Manuel Sacarías Mercado; Ciro Angel Lazo Salcedo; Reyna Olano del Castillo;

Mentoring and Entrepreneurship in Higher Education: A Study from the Plithogenic Statistics

Abstract

Entrepreneurship management in university students is a key factor for economic and social development, especially in intercultural contexts such as the Peruvian Amazon. However, the absence of effective training strategies limits the strengthening of these competencies. This study aims to evaluate the impact of a mentoring program on strengthening entrepreneurship management in students at the National Intercultural University of the Amazon in Peru. The research concludes that the implementation of mentoring programs can represent a key strategy to promote student entrepreneurship in regions with development needs, providing relevant evidence for educational practice and future interventions in higher education. Plithogenic statistics is an extension of traditional statistics that allows the analysis of data sets with multiple levels of uncertainty, contradiction, and neutrality, integrating variables that do not necessarily belong entirely to a sample or population. Its importance lies in the fact that it provides mathematical tools to study complex real-world phenomena—such as social, medical, or organizational dynamics—where the data are not entirely clear or defined, thus improving the accuracy of analysis and decision-making. It is for all these advantages that we use the Plithogenic Statistics as a tool for the study to be conducted. Mentoring and entrepreneurship in higher education encompass several dimensions that interact dynamically with each other, and there are also components of uncertainty within this phenomenon.

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    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    0
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Average
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Average
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green