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.

Financial indicators are the most used variables in measuring the business performance of companies, signaling about the financial position, comprehensive income, and other significant reporting aspects. In a competitive environment, the performance measurement model allows performing comparative analysis in the same industry and between industries. This paper aims to design a composite financial index to determine the financial performance of listed companies, further used in predicting business performance through neural networks. Principal components analysis was used to build a composite financial index, employing four traditional accounting indicators and four value-based indicators for the period 2011–2018. Five experiments were conducted to predict business performance through the composite financial index. The results showed that observations from two years, of the first three experiments, indicate a better predictive behavior than the same experiments using observations from one year. Therefore, we concluded that observations from more than one year are necessary to predict the value of the financial performance index. Findings led us to the conclusion that recurrent neural networks model predicted better financial performance composite index when taken into consideration more real data for the financial performance index (2012–2018) instead of just for one year (2018).

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.

ESG reporting and disclosure enable financial performance by attracting revenues and optimizing managerial decisions. Within this landscape falls the present study that aimed to examine the quality of ESG reporting connected to the financial performance of listed companies. Stratified analysis revealed four groups of companies according to the average value of ROA and ROE indicators, as well as four classes according to the average ESG disclosure score. The analysis of GRI topics and materiality disclosure scores showed an average disclosure level on ESG components, located between a satisfactory and a good level of disclosure. Also, companies were found to be more inclined to disclose data on the sustainability strategy but provided poor and vague information on the business model. The results of comparative clustering analysis based on FinESG reporting and disclosure scores showed that 31.57% of companies maintained their position in the final ranking. Content analysis of sustainability reports by Leximancer, v.5.0 software highlighted that the most salient topic was “employees”, and it revealed correlations between the themes “employees” and “emissions”. The practical implications of the study were found in the promotion of an integrated reporting that best meets the needs of both stakeholders and those of environmental protection and the development of society.

Board gender diversity literature has demonstrated the positive influence of female leaders’ traits, such as openness to negotiation and collaboration, greater flexibility in approaching professional tasks, and improved quality of life, on the business development strategy and consequently on the performance of the companies. This study aims to investigate gender diversity’s link to business performance through bibliometric network analysis, highlighting the scientific literature dynamics through a scientific mapping of the existing knowledge. The temporal evolution of the gender diversity and business performance nexus in the scientific publications selected from Web of Science was examined for 1996–2021, investigating more than 2000 documents and focusing on author, keyword, paper, journal, and topic analysis. The statistical processing of publications was performed in R using Bibliometrix and Biblioshiny software, revealing the most influential and prolific authors and also the most representative journals. Results of the panoramic synopsis analysis revealed outstanding research trends, topics related to women and business performance including women directors, firm performance, issues of board diversity including size, structure, board gender diversity, and independence of members, and issues connected to leadership and gender with items such as gender equality, diversity management, women on boards, and culture.

Purpose: The 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/approach: Using 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.Findings: Results 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/implications: The 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 implications: ESEG Dindx can be an instrument for managers that can optimize the link between the FP of companies and its sustainable development.Social implications: ESEG 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/value: This study adds value to the existing literature by the proposed research framework, design of ESEG Dindx and the way correlations between variables were investigated.