Decision Tree-Based Classification Model for Identification of Effective Leadership Indicators

This study was aimed at identifying effective leadership abilities as appreciated by soldiers in the Lithuanian armed forces. Leader behavior was measured using an adapted version of the Leader Behavior Description Questionnaire (LBDQ), which was originally developed by Andrew W. Halpin from Ohio St...

Full description

Bibliographic Details
Main Authors: Svajone Bekesiene, Sarka Hoskova-Mayerova
Format: Article
Language:English
Published: ITB Journal Publisher 2018-08-01
Series:Journal of Mathematical and Fundamental Sciences
Subjects:
Online Access:http://journals.itb.ac.id/index.php/jmfs/article/view/4080
id doaj-c8b3e261966e463e89ec1e74b3b2438d
record_format Article
spelling doaj-c8b3e261966e463e89ec1e74b3b2438d2020-11-24T22:05:47ZengITB Journal PublisherJournal of Mathematical and Fundamental Sciences2337-57602338-55102018-08-0150212114110.5614/j.math.fund.sci.2018.2.2Decision Tree-Based Classification Model for Identification of Effective Leadership IndicatorsSvajone Bekesiene0Sarka Hoskova-Mayerova1General Jonas Zemaitis Military Academy of Lithuania, Šilo Str. 5A, LT-10322 Vilnius, LithuaniaUniversity of Defence, FMT, Kounicova 65, 66210, Czech RepublicThis study was aimed at identifying effective leadership abilities as appreciated by soldiers in the Lithuanian armed forces. Leader behavior was measured using an adapted version of the Leader Behavior Description Questionnaire (LBDQ), which was originally developed by Andrew W. Halpin from Ohio State University. Data were collected from soldiers holding different ranks and doing professional military service in all units of the Lithuanian armed forces and were analyzed using the IBM SPSS version 20 software application. For our data analysis, the Chi-square Automatic Interaction Detector (CHAID) decision tree growing method was used with three class dependent variables. The CHAID algorithm helped in specifying the best splits for each of twelve potential predictors and then select the predictors whose splits presented the most serious differences in the sub-populations of the sample. In the Chi-squared significance test, the lowest p-value was achieved. The model structures obtained after analysis are presented.http://journals.itb.ac.id/index.php/jmfs/article/view/4080CHAID growing methoddecision tree modelleadershipleadership styleleader behavior
collection DOAJ
language English
format Article
sources DOAJ
author Svajone Bekesiene
Sarka Hoskova-Mayerova
spellingShingle Svajone Bekesiene
Sarka Hoskova-Mayerova
Decision Tree-Based Classification Model for Identification of Effective Leadership Indicators
Journal of Mathematical and Fundamental Sciences
CHAID growing method
decision tree model
leadership
leadership style
leader behavior
author_facet Svajone Bekesiene
Sarka Hoskova-Mayerova
author_sort Svajone Bekesiene
title Decision Tree-Based Classification Model for Identification of Effective Leadership Indicators
title_short Decision Tree-Based Classification Model for Identification of Effective Leadership Indicators
title_full Decision Tree-Based Classification Model for Identification of Effective Leadership Indicators
title_fullStr Decision Tree-Based Classification Model for Identification of Effective Leadership Indicators
title_full_unstemmed Decision Tree-Based Classification Model for Identification of Effective Leadership Indicators
title_sort decision tree-based classification model for identification of effective leadership indicators
publisher ITB Journal Publisher
series Journal of Mathematical and Fundamental Sciences
issn 2337-5760
2338-5510
publishDate 2018-08-01
description This study was aimed at identifying effective leadership abilities as appreciated by soldiers in the Lithuanian armed forces. Leader behavior was measured using an adapted version of the Leader Behavior Description Questionnaire (LBDQ), which was originally developed by Andrew W. Halpin from Ohio State University. Data were collected from soldiers holding different ranks and doing professional military service in all units of the Lithuanian armed forces and were analyzed using the IBM SPSS version 20 software application. For our data analysis, the Chi-square Automatic Interaction Detector (CHAID) decision tree growing method was used with three class dependent variables. The CHAID algorithm helped in specifying the best splits for each of twelve potential predictors and then select the predictors whose splits presented the most serious differences in the sub-populations of the sample. In the Chi-squared significance test, the lowest p-value was achieved. The model structures obtained after analysis are presented.
topic CHAID growing method
decision tree model
leadership
leadership style
leader behavior
url http://journals.itb.ac.id/index.php/jmfs/article/view/4080
work_keys_str_mv AT svajonebekesiene decisiontreebasedclassificationmodelforidentificationofeffectiveleadershipindicators
AT sarkahoskovamayerova decisiontreebasedclassificationmodelforidentificationofeffectiveleadershipindicators
_version_ 1725824698789396480