Management Theory and Studies for Rural Business and Infrastructure Development, Volume 28

Decision trees for hierarchical classification of the antecedents of an employee’s affective commitment

Žaneta Kavaliauskienė

Abstract

Managers of agricultural companies could benefit from hierarchical classification of the antecedents of affectively committed manpower (revealing the motives of an employee’s commitment) because they could initiate the interventions when the problem exists. They can adopt, for example, the appropriate leadership behavior in order to improve the level of affective commitment and, in turn, the levels of job satisfaction and job performance. Scientific problem statement – unexplored hierarchical dependence of the antecedents of an employee’s affective commitment. The objective of the research – applying of Decision trees to identify hierarchical dependence (according to the strongly affectively committed groups of respondents). The scientific research techniques: to verify the research there were used general methods of scientific research, such as scientific literature analysis, synthesis and generalization. Empirical research was grounded on quantitative data processing methods. There were used multidimensional statistical method, such as exploratory and confirmatory analysis (Decision trees module, Chaid method); applied descriptive statistics. Research data processing was done with the help of SPSS 18. In this theoretically based article outlined concentrated interactions among antecedents of an employee’s affective commitment explain job-related behaviors of individuals, thus may be also applied in human resource management practice of agricultural companies while searching for the most optimal managerial strategy stimulating affective commitment of employees to their employing organization.

JEL codes: M 100, M 120.

Keyword(s): affective commitment, organizational commitment, Decision trees.


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Management Theory and Studies for Rural Business and Infrastructure Development eISSN 2345-0355

This journal is published under the terms of the Creative Commons Attribution-Noncommercial 3.0 Unported License. Responsible editor: Dr Audrius Gargasas.