The Effects of Authentic Leadership on Strategic Internal Communication and Employee-Organization Relationships

Abstract

This study examines how strategic leadership influences excellent internal public relations by establishing the linkage between authentic leadership, symmetrical and transparent communication, and employee–organization relationships. The results showed that authentic leadership as an antecedent factor plays a critical role in nurturing an organization's symmetrical and transparent communication system, which in turn, cultivates quality employee–organization relationships. An organization's symmetrical communication worldview greatly fosters its day-to-day transparent communication practice. Transparent communication, characterized by information substantiality, accountability, and employee participation, largely contributes to employee trust, control mutuality, commitment, and satisfaction. The impact of symmetrical communication on employees' relational outcomes is fully mediated via transparent communication. Significant theoretical and practical implications of the findings are discussed.

Notes

¹Small business companies with less than 250 employees were excluded from the population in this study because small companies have different organization dynamics from medium and large corporations. Leadership and public relations practice are believed to be more salient in big and mature corporations.

²The sampling firm is a global provider of sampling solutions for survey research with headquarters in the United States and was the first commercial research sampling company.

³Companies that participants worked for covered a variety of industries including education, retail, healthcare, finance, information technology, food, industrial and manufacturing, transportation and logistics, and so forth.

⁴Walumbuwa et al. (2008) first operationalized authentic leadership in the Authentic Leadership Questionnaire (ALQ). Although research has demonstrated encouraging evidence of the reliability and validity of ALQ (Gardner et al., 2011; Walumbuwa et al., 2008), one major concern is that the full ALQ is commercially copyrighted. Hence, this study adopted an equivalent measure, the ALI.

⁵The alpha values reported are Cronbach's (1957) reliability coefficients for each construct in this study.

⁶Although there exist a few measures of symmetrical communication (e.g., J. E. Grunig, 1992; L. A. Grunig, et al., 2002) in the public relations literature, the study adopted Dozier et al.'s (1995) measure because it was developed particularly to measure the symmetrical qualities of internal communication from the employee's perspective.

⁷According to Kline (2005), structural equation modeling (SEM) is a technique that can be applied to both non-experimental and experimental data to verify a priori models comprised of latent variables or a mix of latent and observable variables. Thus, in the present study, structural SEM was used as the primary statistical method to test the hypothesized model.

⁸According to Kline (2005), a single-fit index reflects only a particular aspect of model fit and a favorable value of that index does not, by itself, indicate good fit. There is no single magic index that provides a gold standard for all models. The chi-square is the most commonly reported measure of model-data fit. However, it is strongly dependent on the sample size. Thus, this study used a combination of fit indexes. According Hu and Bentler (1999), a cutoff value close to .95 for CFI (i.e., comparative fit index), TLI (i.e., Tucker-Lewis index); a cutoff value close to .08 for SRMR (i.e., standardized root mean square residual); and a cutoff value close to .06 for RMSEA (i.e., root mean square error of approximation) indicates good fit between the hypothesized model and the observed data. Additionally, according to Hu and Bentler's joint cutoff criteria, a SEM model with CFI, TLI ≥ .95 and SRMR < .10 or RMSEA ≤ .06 and SRMR ≤ .10 can suggest that the fit between the data and the proposed model is reasonable.

⁹As the demographic variables demonstrated small effects on variables in the hypothesized model, for model brevity, they were not included in the SEM model testing.

¹⁰According to Kline (2005), bootstrapping is a procedure in which one takes repeated, smaller random samples of an existing sample to develop empirical estimates of standard errors of any parameter. Bootstrapping is a common procedure used to address multivariate non-normality issues.