Detecting Informal Organization Through Data Mining Techniques
- URL: http://arxiv.org/abs/2009.02895v1
- Date: Mon, 7 Sep 2020 05:42:37 GMT
- Title: Detecting Informal Organization Through Data Mining Techniques
- Authors: Maryam Abdirad, Jamal Shahrabi
- Abstract summary: This study classifies indices of human resources influencing the creation of informal organizations.
Applied data mining techniques in this study are factor analysis, clustering by K-means, classification by decision trees, and finally association rule mining by GRI algorithm.
- Score: 0.0
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: One of the main topics in human resources management is the subject of
informal organizations in the organization such that recognizing and managing
such informal organizations play an important role in the organizations. Some
managers are trying to recognize the relations between informal organizations
and being a member of them by which they could assist the formal organization
development. Methods of recognizing informal organizations are complicated and
occasionally even impossible. This study aims to provide a method for
recognizing such organizations using data mining techniques. This study
classifies indices of human resources influencing the creation of informal
organizations, including individual, social, and work characteristics of an
organizations employees. Then, a questionnaire was designed and distributed
among employees. A database was created from obtained data. Applied data mining
techniques in this study are factor analysis, clustering by K-means,
classification by decision trees, and finally association rule mining by GRI
algorithm. At the end, a model is presented that is applicable for recognizing
the similar characteristics between people for optimal recognition of informal
organizations and usage of this information.
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