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.

In this paper we aimed to build a composite financial index for measuring the financial health of the companies listed in the AERO (Alternative exchange in Romania) market of the Bucharest Stock Exchange. We used a principal component analysis in order to build this composite financial index using the rates of return, liquidity and the management of 25 companies listed in the AERO market for the period 2011–2018. We conceived this composite indicator as a score function that established according to the numerical values that result from its application when a company was financially healthy, when it had a poor financial health and when it was financially stable. In order to test the financial health of the selected SMEs (small and medium enterprises), we used the one sample t-test under the model of the study and the three classifications of Z (Z < 0—companies with poor financial health, 0 ≤ Z ≤ 0.5—companies with good financial health and Z > 0.5—companies with very good financial health). In this study we also aimed to identify the possible correlations between the solvency rate and the financial health index and between solvency rate and the evolution of some economic and financial measures of the companies’ activities. The results of the regression analysis using panel data showed a positive and statistically significant relation between solvency and the three rates (rates of return, of liquidity and of management, respectively) determined using the analysis of the principal components. The former model of the solvency rate identified correctly 94.9% of the SMEs with poor financial health, 40% of the SMEs with stable financial health and 72.2% of the SMEs with good financial health.

In this paper we analyzed the link between companies’ performance, in terms of cash and income, and the labor productivity or management rates, in case of the companies from the energy sector listed on the Bucharest Stock Exchange. We focused on the energy sector because of the impact that its expansion has on the evolution of economies around the world and because of its dynamics in the sense of gradually shifting to the use of energy from renewable sources. We have used panel regression models to analyze the operating cash flow and the profitability rates and the determination of a causal or dependency relationship with labor productivity or management rates. The results of this study show a significant negative correlation between operating cash flows and the average duration of stock rotation, and no correlation between productivity and the operating cash flow. Instead, the average duration of stock turnover does not at all influence the profitability rates, and productivity is always significant for the return on assets, ie forthe return on equitywith a positive coefficient, as expected. The gap between the average duration of payment of suppliers and the average duration of receivables does not significantly influence neither the cash flow nor the rates of return.

This research paper aims to find a causal relationship between the circular economy and sustainable economic development. The implementation of the circular economy in the European Union requires, on the one hand, smart regulation and on the other hand, the long-term involvement of all actors in society at all levels—member states, regions, cities, businesses, citizens—and their ability to develop cooperation networks and suitable collaboration and exchange patterns. Moreover, the circular economy is based on business models for reusing, recycling and recovering materials in the production and consumption of goods. This research establishes correlations between circular economy performance measurement indicators and sustainable economic development using panel analysis. Statistically significant correlations were noted between GDP per capita and three independent variables, mainly due to the high R-squared coefficient. This research’s innovation contribution is related to the selection and combination of circular economy indicators. Finally, the results confirmed that an increase in the recycling rate of municipal waste and a decrease in environmental tax revenues and environmental protection expenditures led to an increase in GDP per capita and sustainable economic development.

The current challenges of a circular economy exert a high pressure on manufacturing companies that generate waste to track and implement policies to reduce them and eliminate the toxicity of residues. Hence, the purpose of this study is to analyze the waste management information disclosure linked to the financial performance of companies and test the moderating effect of internal and external variables. The average waste management information disclosure index shows a poor disclosure score for the analyzed period, however, the waste disclosure index after reaching a minimum threshold in 2019 recorded an encouraging increase at the end of 2021. Applying the fixed effects model, ordinary least squares, and two-stage least squares method, the results revealed a positive and statistically significant relationship between management information disclosure and the return on assets, while for the current ratio the connection has been invalidated. A statistically significant influence of the environmental-sensitive industry status, board size, and productivity on the moderating variables was found for the return on assets, while for current ratio, there was none. As for the alternative metrics of financial performance, the results showed that a higher degree of management information disclosure will increase the return on equity and earnings per share, while in the case of liquidity, the results are not conclusive.

The present paper aims to analyze the impairment of tangible assets with the help of artificial intelligence. Stochastic fuzzy numbers have been introduced with a dual purpose: on one hand to estimate the cash flows generated by tangible assets exploitation and, on the other hand, to ensure the value ranges stratifications that define these cash flows. Estimation of cash flows using stochastic fuzzy numbers was based on cash flows generated by tangible assets in previous periods of operation. Also, based on the Lagrange multipliers, were introduced: the objective function of minimizing the standard deviations from the recorded value of the cash flows generated by the tangible assets, as well as the constraints caused by the impairment of tangible assets identification according to which the cash flows values must be equal to the annual value of the invested capital. Within the determination of the impairment value and stratification of the value ranges determined by the cash flows using stochastic fuzzy numbers, the impairment of assets risk was identified. Information provided by impairment of assets but also the impairment risks, is the basis of the decision-making measures taken to mitigate the impact of accumulated impairment losses on company’s financial performance.

If ever the concept “VUCA” (Volatility, Uncertainty, Complexity, and Ambiguity) seemed appropriate to use, it is now. National and global companies experience the highest level of instability due to the Covid-19 pandemic, which is the classic example of a highly volatile, uncertain, complex, and ambiguous world. In this world, decision-makers have to face more challenges appealing to the VUCA Prime leadership approach: vision against volatility, understanding against uncertainty, clarity against complexity, and agility against ambiguity. Some of the ways through which managers can overcome the VUCA characteristics include: providing a shared vision as a criterion for all decisions to be made, identifying the reason for the decision problems and sharing the idea with the followers, going through the entire decision process, following steps in proper order, and developing quick solutions. In an inventory decision taken in a VUCA context, the above ways are possible if using fuzzy inventory methods dealing with volatility, uncertainty, complexity, and ambiguity. This paper aims to adapt a traditional inventory method, Economic Production Quantity (EPQ), to the challenges of the VUCA world, through the fuzzy logic system (FLS). To achieve the best solution for the decision problem in the shortest time possible, the managers can employ a conversion by using the computing platform MATLAB. There are some advantages of this conversion for these two methods, EPQ and FLS. Firstly, the transformation of EPQ in ELQ (Economic Logic Quantity) allows managers to formulate the decision problem, even if they cannot identify and measure precisely the EPQ parameters. Secondly, using FLS to solve ELQ provides the possibility to simulate more alternatives and generate the solution in the shortest amount of time. Thirdly, it allows the decision-makers to evaluate the impact of the solution provided by each simulation on the company’s performance. Using these methods has the following primary limit: the problem formulation step depends on the managers’ understanding ability and managing a large volume of information. Therefore, there may be a risk of obtaining a relevant solution for a decision problem if the decision-makers do not understand the cause of the problem or do not know how to organize and manage a large volume of information. This limit could be overcome by using AHP (Analytic Hierarchy Process), but this is the topic of further research.

The paper aims to develop a MAMDANI fuzzy controller for detecting the financial sustainability risk of the assets owned by the company. This type of risk indicates when an asset no longer produces economic benefits to the company, or the benefits are small enough to no longer justify the asset maintaining in working order. The proposed fuzzy controller has as input variables the asset operating expenses and the variation of this category of expenses from one analysis period to another. The controller's objective function is to keep operating costs at their initial state and thus reducing the financial sustainability risk. The controller's output variable is represented by the economic benefits variation, considered to be an essential component in the financial sustainability risk analysis. The obtained results were interpreted taking into account the objective function of the controller as well as the evolution of the input variables. Two simulations for fuzzy controllers were made, with the mention that the variation ranges for the input variables were delimited. In practice, fuzzy controllers can be generated according to company policies to keep under control the expense categories that accompany the asset exploitation.