Online reporting by banks: a structural modelling approach

Abstract

PurposeA structural equation model is proposed to explain internet reporting by banks. The model relates three constructs of financial institutions (size, financial performance, and internet visibility) to their final influence on internet information disclosure (e‐transparency).Design/methodology/approachThis paper's proposed model analyses a sample of Spanish financial institutions using publicly available data. The model is tested using partial least squares.FindingsA positive and statistically significant relationship has been found between size, financial performance, internet visibility, and e‐transparency, with direct and indirect effects. The study shows that size accounts for most of the variance. Size has a positive effect on e‐transparency, financial performance, and internet visibility. However, the direct effect of financial performance and internet visibility on e‐transparency is small.Research limitations/implicationsThe researchers have analysed only one year of data from one country and one sector. The direction of cause and effect assumed in the model is a logical one, but statistical methods cannot prove causality, only association. Even though any bank can disclose its financial information online for a very low cost, building a robust, interactive web site requires major resources. This gives larger banks a value added advantage.Originality/valueThe paper examines the relationship between size, financial performance, internet visibility and e‐transparency using a structural model. Although structural models are commonly used in many scientific disciplines, they have not yet been applied in disclosure research.

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RSC y empresas tecnológicas: Un estudio sobre las motivaciones de implantación e integración en empresas españolas

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“…Although Cronbach's alpha for three categories (accessibility, timeliness and company information) is below the often-suggested acceptable level of 0.7 (e.g. SerranoCinca, Fuertes-Callén & Gutiérrez-Nieto, 2007;Nunnaly, 1978;Kelton & Yang, 2008), it can still be viewed as acceptable given the alpha of 0.51 as reported by Gul and Leung (2004) and 0.64 reported by Botosan (1997). Gul and Leung (2004) did however admit that the low alpha reported in their results suggested that random measurement error could reduce the power of the empirical tests in their study.…”