We are interested in the hierarchy of the main Romanian companies in the manufacturing industry by considering eight financial and seven non-financial indicators. Thirty three listed companies, that are non-financial institutions, were selected for the study and in order to control the reliability of the data we used the Bucharest Stock Exchange database, official data published by the Romanian Ministry of Public Finance, and the annual reports released by the companies on their websites, collecting information for the years 2011–2015. Because the human thinking is subjective and ambiguous we prefer linguistic variables, converted afterwards in triangular fuzzy numbers, to represent the importance of indicators. Our method involves the calculation of the weights of individual or categories of indicators based on Fuzzy Analytic Hierarchy Process. Then, the level of performance for each company, separately for financial, non-financial and all indicators is obtained by TOPSIS method. We deduce an objective hierarchy of the companies on a rigorous basis, which is however dependent from the choice of indicators and the conversion scale of linguistic variables into triangular fuzzy numbers. Also, following the obtained results we concluded that the overall performance of companies for the analyzed period is significantly influenced by non-financial indicators.

New challenges and perspectives to improve non-financial reporting and the disclosure of environmental, social, and governance indicators have been launched towards the development horizon of Romanian public interest entities, implementing the provisions of Directive 2014/95/EU in the local regulatory framework. In this context, our approach focused on the content analysis of the non-financial information reported by listed companies, for the period 2017–2019, and the measure of the average disclosure degree on environmental, social, economic, and governance (ESEG) indicators. To measure the average degree of disclosure, a composite index was constructed through the main component analysis for categorical data that allowed the classification of sampled companies by sustainable performance. The results showed a slight increase in the ESEG disclosure index at the level of the sampled companies, from 47 units in 2017 to 52 units in 2019, several companies “went ahead” and others “recovered over the period”. Cross-sectional analysis revealed differences in the average non-financial disclosure index, and also in the disclosure index of ESEG indicators. The non-parametric correlation analysis highlighted the existence of a statistically significant positive correlation of medium intensity between the disclosure index of non-financial information and the publication of the non-financial statement or report.

PurposeThe purpose of this work is twofold. First, looks to identify the main homogenous groups of companies after environmental, social, economic and governance (ESEG) disclosures, non-financial statement and earnings per share (EPS), and second investigates the connection between variables.Design/methodology/approachUsing financial and non-financial information from annual reports of private listed companies, the authors performed two-step cluster analysis (TSCA) in the first stage of the research, followed by parametric, nonparametric correlation analysis, as well as regression analysis based on panel data, in the second stage.FindingsResults of TSCA revealed a cluster of companies with good financial and non-financial outcomes and a cluster of companies with poor performance. The performance dynamics showed a slight improvement during the period for few companies and composition analysis of clusters by industries through Kruskal–Wallis test highlighted differences between clusters, only for 2017. The main findings confirm a direct, although weak in intensity but statistically significant correlation between ESEG disclosure index, its sustainability component and financial performance (FP), valid for the entire period. Also, the results showed a direct link of low intensity to average, but statistically significant between the non-financial statement and EPS, valid only for 2017 and 2018.Research limitations/implicationsThe results indicate mixed findings which invites further in-depth research. Limits of the study can be found in selected indicators and the short period of time analyzed. However, the practical implications are worth considering from the perspective of finding new managerial tools that can better shape the relationship between ESEG disclosures and FP.Practical implicationsESEG Dindx can be an instrument for managers that can optimize the link between the FP of companies and its sustainable development.Social implicationsESEG Dindx measures the disclosure degree of ESEG information by the companies listed on Bucharest Stock Exchange (BSE). The main findings of the work confirm a direct, although weak in intensity but statistically significant correlation between ESEG disclosure index, its sustainability component and FP, valid for the entire period.Originality/valueThis study adds value to the existing literature by the proposed research framework, design of ESEG Dindx and the way correlations between variables were investigated.

This study examined the influence of the executive board of directors’ gender diversity on the financial performance of listed companies on the Bucharest Stock Exchange, for the period 2011 to 2019. The analysis of the composition and different characteristics of the board and the executive directors proved to be effective tools for corporate governance in countries with an emerging capital market. Therefore, a disclosure index on directors’ characteristics was used to moderate the interaction between gender diversity and financial performance, based on the theoretical framework provided by upper echelon theory. The study contributes to the enrichment of the literature both by using the composite indicator built by applying the multiway PCA method on panel data to express financial performance and by designing the ten EGLS panel models involving five financial indicators and two proxies for gender diversity. The results showed that there is a positive impact of the proportion of women on the executive board of directors on financial performance, measured through the composite index, ROA, ROE, and SOL. A statistically significant impact of gender diversity on financial performance was found only for SOL, in the case of the Blau index. Also, using the random-effects model to perform the panel data analysis, the results showed that a higher executive board size can be associated with better financial performance measured through the composite index, ROA, ROE, and EPS. Practical implications are significant for the board of executives’ composition, the complexity of the relationship with the board, and reshaping governance practices.

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