The purpose of this research study is to examine and explain whether there is a positive or negative linear relationship between sustainability reporting, inadequate management of economic, social, and governance (ESG) factors, and corporate performance and sustainable growth. The financial and market performances of companies are both analyzed in this study. Sustainable growth at the company level is introduced as a dimension that depends on sustainability reporting and the management of ESG factors. In order to achieve the main objective of the paper, the methodology here focuses on the construction of multifactorial linear regressions, in which the dependent variables are measurements of financial and market performance and assess corporate sustainable growth. The independent variables of these regressions are the sustainability metrics and the control variables included in the models. Most of the existing literature focuses on the causality between sustainability performance and financial performance. While most impact studies on financial performance are restricted to sustainability performance, this study refers to the degree of risk associated with the inadequate management of economic, social, and governance factors. This work examines the effects of ESG risk management, not only on performance, but also on corporate sustainable growth. It is one of the few studies that addresses the problem of the involvement of companies in controversial events and the way in which such events impact the sustainability and sustainable growth of the company.

Abstract:The aim of this paper is to highlight the influence of economic and qualitative factors on steel production globally, as well in the EU, US, and China, using a dataset corresponding to the period 2000-2015. The research methods used are the study of specialist literature, problematisation, modelling, and simulation using Statistical Package for the Social Sciences (SPSS) software. The main conclusion of this paper is that, on long term, the steel production is largely influenced by the rate of real economic growth and by car production, even if in the short term the correlation is not obvious. Likewise, qualitative factors affect the steel industry in the context of current regulations on reducing carbon emissions and ensuring sustainable development. An additional aim of the present study is to define entropy in the sustainable development of steel production, as well as illustrate some of its properties and the quality management modelling of the research process in steel production.

The intangible resources management (IRM) is a key area within organizations, not only in terms of theory, but also in practice. However, reality shows that organizations face unexpected challenges in developing and implementing strategies and processes of intangible resources management. This article seeks to contribute to the improvement of IRM at the organization level by building a model that describes the process followed by organizations seeking to implement an intangible resources management system. Our study emphasizes the need of three phases: the identification of critical intangible resources for creating value; the measurement of these resources through a set of indicators and, finally, the monitoring of the resources and intangible activities. However, the management, monitoring and reporting on intangible resources is very idiosyncratic and unique for each organization; there is not a universal recipe, each organization should develop its own process.

In this article, we propose a test of the dynamics of stock market indexes typical of the US and EU capital markets in order to determine which of the two fundamental hypotheses, efficient market hypothesis (EMH) or fractal market hypothesis (FMH), best describes market behavior. The article’s major goal is to show how to appropriately model return distributions for financial market indexes, specifically which geometric Brownian motion (GBM) and geometric fractional Brownian motion (GFBM) dynamic equations best define the evolution of the S&P 500 and Stoxx Europe 600 stock indexes. Daily stock index data were acquired from the Thomson Reuters Eikon database during a ten-year period, from January 2011 to December 2020. The main contribution of this work is determining whether these markets are efficient (as defined by the EMH), in which case the appropriate stock indexes dynamic equation is the GBM, or fractal (as described by the FMH), in which case the appropriate stock indexes dynamic equation is the GFBM. In this paper, we consider two methods for calculating the Hurst exponent: the rescaled range method (RS) and the periodogram method (PE). To determine which of the dynamics (GBM, GFBM) is more appropriate, we employed the mean absolute percentage error (MAPE) method. The simulation results demonstrate that the GFBM is better suited for forecasting stock market indexes than the GBM when the analyzed markets display fractality. However, while these findings cannot be generalized, they are verisimilar.

This study argues that the context in which an organization adopts the principles of corporate sustainability and is guided by a culture of sustainability will determine the development of the components of corporate intangible resources. However, in trying to evaluate the impact of adopting the principles of corporate sustainability on the development of the intangible resources held by a company, we encountered a major problem, namely that there is no consistent and internationally accepted methodology for assessing such resources, despite theorists’ and practitioners’ efforts to develop intangible measurement techniques. The main research objective of this article is to propose the creation of a simplified model for the assessment of intangible resources, which depends only on publicly available information for each of the components of the model. This model can therefore contribute to the practical implementation of intangible resource management by offering an autonomous and objective instrument that uses only publicly available information, thus facilitating comparisons between organizations.