Analyzing the Societal Impact of Academic Research Using Fuzzy Inference Models

Improving universities’ social impact is a significant problem in the higher education sector, which can be solved by appropriately shaping public policies, strategies of individual scientific organizations, and academic practices. Effectively conducting social impact analyses can support improving organizations’ functioning mechanisms and individual academics’ impact practices. These analyses can use data analysis methods and systems that are helpful for better understanding the positive or negative effects of decisions regarding selecting organizational impact strategies. The study of social impact and interactions between scientific organizations and their stakeholders is multifaceted and complex. Therefore, it requires the use of interdisciplinary approaches and sophisticated knowledge-based models. It is worth paying attention to fuzzy logic, which is useful in building such models and developing research on their application to support knowledge management necessary for conducting comprehensive analyses of the social impact of various scientific organizations. This is justified by the need to learn about the mechanisms of functioning systems of relations between scientific organizations and their stakeholders, as well as the types of influence occurring and knowledge exchange during the implemented interaction processes. The pace of changes in the scientific community environment forces an increase in openness for introducing analysis models adequate for the dynamic progress in developing new computational technologies. The main goal of this paper is to create a fuzzy inference model that helps support knowledge management for ongoing analysis and assessment of the social impact of research. The presented theoretical considerations, relating to the construction of the proposed model, are supplemented with a proposal for its implementation, which may later facilitate extensive verification studies based on empirical data. The obtained preliminary research results allow for the formulation of fundamental limitations, the overcoming of which creates a reasonable basis for further development of research on subsequent models of the analysis of social impact.

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Publication Details

Journal
European Conference on Knowledge Management
Published
2025-08-29
DOI
https://doi.org/10.34190/eckm.26.1.3923
Primary Topic
Online Learning and Analytics
Type
article
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article

Analyzing the Societal Impact of Academic Research Using Fuzzy Inference Models

Tadeusz A. Grzeszczyk
European Conference on Knowledge Management
Online Learning and Analytics
article

Analyzing the Societal Impact of Academic Research Using Fuzzy Inference Models

Tadeusz A. Grzeszczyk
article en

Abstract

Improving universities’ social impact is a significant problem in the higher education sector, which can be solved by appropriately shaping public policies, strategies of individual scientific organizations, and academic practices. Effectively conducting social impact analyses can support improving organizations’ functioning mechanisms and individual academics’ impact practices. These analyses can use data analysis methods and systems that are helpful for better understanding the positive or negative effects of decisions regarding selecting organizational impact strategies. The study of social impact and interactions between scientific organizations and their stakeholders is multifaceted and complex. Therefore, it requires the use of interdisciplinary approaches and sophisticated knowledge-based models. It is worth paying attention to fuzzy logic, which is useful in building such models and developing research on their application to support knowledge management necessary for conducting comprehensive analyses of the social impact of various scientific organizations. This is justified by the need to learn about the mechanisms of functioning systems of relations between scientific organizations and their stakeholders, as well as the types of influence occurring and knowledge exchange during the implemented interaction processes. The pace of changes in the scientific community environment forces an increase in openness for introducing analysis models adequate for the dynamic progress in developing new computational technologies. The main goal of this paper is to create a fuzzy inference model that helps support knowledge management for ongoing analysis and assessment of the social impact of research. The presented theoretical considerations, relating to the construction of the proposed model, are supplemented with a proposal for its implementation, which may later facilitate extensive verification studies based on empirical data. The obtained preliminary research results allow for the formulation of fundamental limitations, the overcoming of which creates a reasonable basis for further development of research on subsequent models of the analysis of social impact.

European Conference on Knowledge ManagementVol. 26(1)
Warsaw University of Technology (PL)
Openalex Percentile: Top 74%
Online Learning and Analytics
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