2014
DOI: 10.11113/jt.v69.3245
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A Hierarchical Latent Variable Model of Leadership Styles using PLS-SEM

Abstract: The aim of this article is to propose second order hierarchical component models to analyze the two leadership styles (transformational leadership and transactional leadership) for technology-based SMEs. We adopted the two-stage approaches in partial least square-structural equation modelling to examine the appropriateness of hierarchical modelling for both leadership styles. The findings indicate that the conceptual properties of transformational leadership and transactional leadership are matched with reflec… Show more

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Cited by 8 publications
(5 citation statements)
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References 21 publications
(22 reference statements)
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“…Technology-based firms have an impact on economic growth, job opportunities and many innovations as explained by Massa and Testa (2008). Despite the importance of technologybased firms towards the economy, limited studies have been found focusing on technology-based firms (Majid, Ismail & Cooper, 2011;Ajagbe, Choi, Aslan & Ismail, 2012;Arshad, Rasli, Mustafar & Norhalim, 2013;Arshad, Goh & Rasli, 2014;Arshad, 2016). Many researches have been studying leadership styles where majority concentrated in SMEs (Yang, 2008;Yildrim & Saygin, 2011;Arham & Muenjohn, 2012).…”
Section: Introductionmentioning
confidence: 99%
“…Technology-based firms have an impact on economic growth, job opportunities and many innovations as explained by Massa and Testa (2008). Despite the importance of technologybased firms towards the economy, limited studies have been found focusing on technology-based firms (Majid, Ismail & Cooper, 2011;Ajagbe, Choi, Aslan & Ismail, 2012;Arshad, Rasli, Mustafar & Norhalim, 2013;Arshad, Goh & Rasli, 2014;Arshad, 2016). Many researches have been studying leadership styles where majority concentrated in SMEs (Yang, 2008;Yildrim & Saygin, 2011;Arham & Muenjohn, 2012).…”
Section: Introductionmentioning
confidence: 99%
“…The PLS-SEM relaxes the tight sample size and normality assumptions of covariance-based SEM (Haenlein& Kaplan, 2004;Wong, 2013). Because research constructs are multidimensional and latent, structural equation modelling (SEM) is the most suitable method, which is why PLS-SEM was used in this work (Arshad, Goh, & Rasli, 2014;Bawuro et al 2019). PLS-SEM evaluation is done in two steps.…”
Section: Methodsmentioning
confidence: 99%
“…The strict suppositions of covariance-based SEM of sample size and normality are lessened by the PLS-SEM (Haenlein& Kaplan, 2004;Wong, 2013). The use of PLS-SEM in this study was motivated by the fact that research constructs are multi-dimensional and latent, making Structural Equation Modelling (SEM) the most appropriate technique (Arshad, Goh, & Rasli, 2014;Bawuro et al 2019). PLS-SEM is evaluated in two stages.…”
Section: Methodsmentioning
confidence: 99%