Analysis of disclosure determinants: a local-relation approach

Abstract

Purpose In the literature on determinants of disclosure, scholars generally tend to investigate the existence of relations in “global” terms by considering the whole range of observed values pertaining to both dependent and independent variables involved in the descriptive model. Despite the different methodologies used coherently to this approach, a hypothesis can be only accepted or rejected entirely. This paper aims to contribute to the literature by proposing a data-driven method based on smooth curves, which allow scholars to detect the existence of local relations, significant in a limited interval of the dependent variable. Design/methodology/approach The employment of smooth curves is simplified by conducting a study on goodwill disclosure. The model derived by the adoption of the locally weighted scatterplot smoothing (LOWESS) curves may provide an accurate description about complex relations between the extent of disclosure and its expected determinants, whose shape is not completely captured by traditional statistic techniques. Findings The model based on LOWESS curves provided a comprehensive description about the complexities characterizing the relationship between disclosure and its determinants. The results show that in some cases, the extent of disclosure is influenced by multi-faceted local relations. Practical implications The exemplificative study provides evidences useful for standard setters to improve their comprehension about the inclination of companies in disclosing information on goodwill impairment. Originality/value The adoption of smooth curves is coherent with an inductive research approach, where empirical evidence is generalized and evolves into theoretical explanations. The method proposed is replicable in all the field of studies, when extant studies come to unclear and contradicting results as a consequence of the complex relations investigated.

Evaluating risks-based communities of Mafia companies: a complex networks perspective

“…In so doing, we are in line with literature on corporate disclosure, where the adoption of self-constructed indexes is quite common (see e.g. Castellano et al 2019). Generally, unweighted indexes are preferred in this field of research, since they are easier to calculate and allow to reduce the subjectivity bias (see e.g.…”

Impact of firm performance and corporate governance mechanisms on intellectual capital disclosures in CEO statements

“…The disclosure of intellectual capital (IC) is an important factor that leads a successful firm to achieve its objectives and contributes to knowledge in the economy (Petty and Guthrie, 2000). Specifically, this type of disclosure shares knowledge about a company's human development, innovation and connections (Cabello-Medina et al, 2011;Castellano et al, 2019). A firm illustrates its IC voluntarily, as part of its CEO statement to stakeholders (Striukova et al, 2008).…”

Research on the quality of information disclosure of listed companies in the era of big data

“…When the Lagrange multiplier method is used, the number of disclosures in category L is calculated as shown in Equation (15). After minimizing the variance, the larger the parameter for determining the feature weights, the more indicator features are obtained.…”

“…The study used a content analysis approach based on the Global Reporting Initiative organizational framework to calculate the scores of companies disclosing people-related, social and product-related information. The literature [15] proposes a datadriven approach based on a smoothing curve that detects the presence of local relationships and simplifies the application of the smoothing curve by examining goodwill disclosure information. In other words, it is argued that the model derived using locally weighted scatter plot smoothing (LOWESS) curves can accurately describe the complex relationship between both the degree of disclosure and the expected determinants.…”