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...
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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 |