Izvorni znanstveni članak
https://doi.org/10.1080/1331677X.2020.1844581
Modelling OCB and CWB by combined Fuzzy Signature model
Dalia Susnienė
Ojaras Purvinis
Daiva Zostautiene
orcid.org/0000-0002-0101-6739
Laszlo T. Koczy
Sažetak
Globalization and its challenges for organizations led to the
understanding that employees can be a critical factor contributing
to the organization’s performance. Therefore, various studies
sought to understand employee’s behaviour that in itself encompasses various forms of engagement. One of the constructs
defining engagement is citizenship behaviour (OCB) and counterproductive work behaviour (CWB). Based on previous researches,
the study aims to contribute to the knowledge on the correlation
between OCB and CWB considered as a behavioural engagement,
from one side, and interplay of these constructs with the related
constructs such as a trait engagement, perception of organization,
state engagement, from another side. Since the empirical studies
typically tend to concentrate on one or several factors separately,
it is difficult to get a better understanding of relationship of all
forms of engagement in corpore. To address this gap, we create a
complex model of investigation developed to describe the linkage
of the factors - OCB, CWB and related constructs under one
umbrella and, by employing a combined statistical and Fuzzy
Signature (FSig) model, we investigated the link with behavioural
engagement. The present study covered one region of the northern part of Lithuania. It is based on 144 completed questionnaires
from 35 companies. Findings support the assumption of the relationships of behavioural engagement (i.e. OCB and CWB) and the
remaining multifaceted factors, and make a step forward by offering a new model for investigation the multifaceted phenomenon
of employee engagement.
Ključne riječi
Organization citizenship behavior (OCB); Counterproductive work behaviour (CWB); Employee engagement; Fuzzy Signature model (FSig)
Hrčak ID:
301240
URI
Datum izdavanja:
31.12.2021.
Posjeta: 161 *