Modified assessment methodology ESG competitiveness of enterprises to a new generation of investors

The article substantiates the expediency of modifying the methodology for assessing business competitiveness in the context of accelerated global ESG integration. The authors propose a system of criteria for assessing the competitiveness of enterprises, taking into account the requirements of the EU Taxonomy, Regulation (EU) 2020/852, the CSRD, and stakeholder requests for information support for assessing ESG risks and ESG competitiveness of enterprises. This system of criteria is based on a cognitive approach. Thanks to the use of modeling and information tools, it is based on a lateral understanding of the clarity of the distinction between the criteria and sub-criteria for assessing the ESG competitiveness indicator and its components. The introduction of a system of criteria for assessing the competitiveness of enterprises will ensure obtaining realistic results and making informed decisions to strengthen the competitive advantages of enterprises for a new generation of “conscious investors”. The author’s own methodology for integral assessment of ESG competitiveness of metallurgical enterprises is proposed. This methodology is based on the synthesis of integral and reference approaches to assessing the homeostasis of competitiveness. It is adapted to the information support of the Management Report prepared in accordance with the GRI (Global Reporting Initiative) and SASB (Sustainability Accounting Standards Board) standards. Its peculiarity is the assessment based on the extended homeostatic plateau of the dynamic system for determining the thresholds of the optimality of the ESG competitiveness indicator of enterprises. This should become the basis for ESG rating and the fundamental basis for determining strategic imperatives for managing the competitiveness of enterprises in the context of global ESG integration.


Introduction
The aggravation of the triple planetary crisis due to the shortage of natural resources, environmental pollution and climate change requires a transition to a low-carbon economy.Society's expectations are growing and require preserving the planet's sustainability for future generations.In this context, the integration of sustainability and sustainable development (ESG integration) is recognized as one of the strategic priorities of steel companies.When the question of their competitiveness arises, it is about ESG competitiveness.
Traditionally, the competitiveness of enterprises is assessed through a comparative analysis of integrated competitiveness indicators.It is also possible through a comparative analysis of rating indicators or rating positions.In the context of ESG integration, there is a need to revise 1254 (2023) 012126 IOP Publishing doi:10.1088/1755-1315/1254/1/012126 2 approaches to assessing the competitiveness of enterprises, that is, to modify the methodology for its assessment [1, p. 66].

Literature review
Usually, the competitiveness of enterprises was assessed by financial and economic indicators [2][3][4][5][6].However, this is not enough in the context of ESG integration.Investors are increasingly considering the social impact of their investments when choosing an investment object and strive to create added value in their investment portfolio for the benefit of future generations [7].That is why, according to Segal [8], Datsii et al [9], nowadays attention is increasingly focused on the ESG competitiveness of enterprises.
There are still no uniform criteria for its assessment [8, p. 18].The number of metrics for its assessment offered by analytical centers, rating companies and stock exchanges is growing steadily every year.The metrics proposed by the Global Sustainable Development Goals, RobecoSAM, the Global Reporting Initiative (GRI), EcoVadis 180+, Bloomberg 700+, ISS 300-500, RobecoSAM 600, Sustainalytics 300+, and companies of the DAX, MDAX, SDAX and TechDAX indices on the Frankfurt Stock Exchange (FWB) are currently used in the world practice, The London Stock Exchange (LSE) (which issued guidelines for ESG reporting in response to requests from investors for whom such information is key to their investment decisionmaking), the Warsaw Stock Exchange (WSE) (which created the WIG-ESG index, which is followed by the NN TFI fund).In May 2020, the European Central Bank issued guidelines for assessing climate and environmental risks for financial institutions, etc. [8, p. 18].
Of particular note is the methodology for assessing ESG competitiveness based on corporate sustainability indicators.It was introduced in Ukrainian practice in 2019 during the first and only professional rating assessment Sustainable Ukraine (based on the DJSI approach).This was carried out as part of a global international project on ESG rating of CIS countries and enterprises with the strategic support of Standard & Poor's Financial Services LLC, S&P Global (owner of the world's most authoritative SR/ESG rating -Dow Jones Sustainability Raitng/index).The aim of the project was to present to the international investment community a holistic picture of Ukraine's corporate sector in terms of sustainable development and corporate social responsibility [10].
Scientists have their own opinions on this matter.Thus, Datsii et al [9, p. 67] argue that in the world and domestic practice there is no single methodology for scoring (assessing) the ESG direction of business.For the first time, the author's model of scoring trends and regularities of business development is proposed in accordance with ESG-principles, in contrast to traditional trend dynamic models, which identifies and iteratively conceptualizes processes by the set of ESG-indicator components determined using the cocoupling-analysis toolkit (tools for assessing the cocoupling-effect).
There are many examples of metrics for assessing the ESG competitiveness of enterprises.Each of them has advantages and disadvantages.The main disadvantage is that when assessing the ESG competitiveness of enterprises, we believe that the limits of its optimality are ignored.This is usually of the greatest interest to investors and stakeholders in obtaining the expected effects (environmental, social and corporate governance).Any deviation from the defined limits of optimality is accompanied by ESG risks and certain losses.Taking into account the shortcomings of the methods for assessing the ESG competitiveness of enterprises, we consider it appropriate to propose our own methodology for assessing the ESG competitiveness of metallurgical enterprises.This methodology is based on a symbiosis of the integral and benchmark approaches.

Calculation methodology
The ESG competitiveness of an enterprise is characterized by a set of numerous indicators.These indicators have been prioritized by each of the components of ESG competitiveness (table 1).The defined structure includes 15 indicators.The list of indicators may vary depending on the objectives and depth of the study.These 15 indicators are grouped by each of the components E 5 , S 5 , G 5 .To simplify understanding and demonstration, the results of the modeling [11] are presented in the form of a vector: R = {r 1 ; r 2 ; . . .; r n } , n -number of indicators.With this decision, the question of the unidirectionality of the indicators E j , S j , G j .Because among the indicators identified in table 1, some of them should increase (stimulators) and others should decrease (discouragers) to ensure the ESG competitiveness of enterprises.The unidirectionality of the indicators E j , S j , G j can be achieved through normalization, in particular, by applying the combined method [12, p. 74].This is a modified method of normalization by the "range of variation", which provides: • for positive direction indicators: • for negative direction indicators: The main disadvantage of the combined method of normalization is that the standardized indicators that form the information basis for calculating the generalized and integral ones affect the latter with equal force.Their influence is equilibrium.This is not always justified in practice.This shortcoming can be neutralized by introducing hierarchy coefficients (weighting).This will divide the indicators E j , S j , G j by their significance, strength of influence on the generalized and integral indicator of ESG competitiveness of enterprises.The question arises of determining the weighting coefficients of indicators for each component of the ESG competitiveness of enterprises.This is possible using one of the approaches presented in table 2.
Table 2. Methods for determining the weighting coefficients of each component of the ESG competitiveness indicator of an enterprise [11, p. 46].

The method Calculation methodology Advantages
The method of sensitivity theory allows adjusting the weighting coefficients in each period to make them more relevant to the real economy The method of principal components characterizes the set of weighting coefficients required to form the indicator in additive or multiplicative form Determination of the indicator of ESG competitiveness of enterprises by the method of integral assessment makes it possible to observe changes in this indicator in the dynamics and to carry out a multicriteria analysis of the competitiveness of enterprises.However, this is not enough to make informed management decisions on maintaining the competitive position of enterprises and improving them in the context of accelerated competition.
For a more realistic assessment of the ESG competitiveness indicator of enterprises and the possibility of forecasting its changes in the medium and long term, we consider it advisable to apply a methodology based on the synthesis of integral and benchmark approaches to assessing business homeostasis.This methodology is adapted to the information support of the Management Report prepared in accordance with the GRI (Global Reporting Initiative) and SASB (Sustainability Accounting Standards Board) standards.It provides for the assessment of the extended homeostatic plateau of the dynamic system for determining the thresholds for the optimality of the ESG competitiveness indicator of enterprises and its components.This can become the basis for ESG rating and the fundamental basis for determining strategic imperatives for managing the competitiveness of enterprises in the context of accelerated global ESG integration.That is why, for each of the components E j , S j , G j of the competitiveness of enterprises, it is necessary to determine the vector of threshold values, namely: lower critical (x low_k ); lower threshold (x low_lim ); lower optimal (x low_opt ); upper optimal (x h_opt ); upper threshold (x h_lim ); upper critical (x h_k ) [13, p. 52].
There is a fairly large number of methods for determining the threshold vector.The most adequate, from our point of view, for this task is the stochastic method of the tcriterion.According to this method, probability density functions should be constructed for given samples of statistical data of competitiveness indicators and statistical characteristics should be calculated: mathematical expectation, standard deviation and coefficient of asymmetry [14, p. 22].
Based on the results of the analysis of statistical data, it was found that the competitiveness indicators assume the hypotheses of normal and exponential distributions.They include formulas for calculating the vector of threshold values [12, p. 70-72], [14, p. 29]: for the exponential law (tail to the right) for the exponential law (tail to the left) t -Student's criterion; µ -mathematical expectation; σ -standard deviation; k as -coefficient of asymmetry.
Establishing thresholds can help build a simulation model of optimal business immunity (homeostasis).To do this, it is necessary to identify: I -zone of low ESG competitiveness; II -zone of conditionally acceptable ESG competitiveness (low); III -zone of optimal ESG competitiveness; IV -zone of conditionally acceptable ESG competitiveness (high); V -zone of critical ESG competitiveness.
Under conditions of variability and uncertainty, the limits of optimality of ESG competitiveness and threshold values of the I E , I S , I G indicators may change under the influence of both endogenous and exogenous factors [15, p. 43].Indicators of immunity (homeostasis) of ESG competitiveness of enterprises are indicators of statics.However, for management decisionmaking and strategizing, dynamics indicators are currently more important, as they make it possible to observe existing trends and see the future.Therefore, when studying the ESG competitiveness of enterprises, an equally important stage as the previous ones is to assess the vulnerability of ESG competitiveness immunity under the influence of ESG risks and threats.

Research results
The authors consider it expedient to do this by rating them according to the scale presented in table 3. The choice of values on the scale of 0.63 and 0.37 is due to the convenience of the calculations: 0.63 ≈ 1−(1/e), 0.37 ≈ 1/e.The value of di = 0.37 usually corresponds to the limit of acceptable values.
In accordance with the defined categories of ESG risks and threats, the correction factor k r should be determined.It should be used to adjust the limits of optimality of ESG competitiveness and thresholds of the I E , I S , I G indicators.
The frequency of reviewing the limits of optimality of ESG competitiveness and the thresholds of the I E , I S , I G indicators (annual, quarterly) should be specified in the standards for assessing and rating the ESG competitiveness of enterprises.
To confirm the viability of the proposed methodology for assessing the ESG competitiveness of enterprises, we applied it to the assessment of the competitiveness of Arcelor Mittal Group enterprises (table 4).To ensure ESG competitiveness, some indicators should increase (stimulators) and others should decrease (disincentives).The unidirectionality of the indicators E j , S j , G j can be achieved through norming.Therefore, indicators r i (i = 1, 15) should be understood as standardized dimensionless values obtained from the values of E j , S j , G j (j = 1, 5).
Since the partial indicators of ESG competitiveness of enterprises have different dimensions, to determine the integral indicators of each of the components E-, S-and G-, we will carry out the procedure of normalizing the indicators E j , S j , G j .For a correct comparison, each of the indicators must be normalized (i.e., reduced to the interval from 0 to 1).0 corresponds to the worst (unacceptable) values of this indicator, and 1 corresponds to the best (optimal) values of this indicator.
To normalize the indicators, it is necessary to determine the minimum and maximum values.Next, we normalize using a formula, the form of which depends on the nature of the indicator: whether it is a stimulator or, conversely, a discourager of the enterprise's ESG competitiveness.
Stimulators of ESG competitiveness of enterprises are indicators that contribute to positive changes in the competitive position of the enterprise.This leads to an increase in the ESG competitiveness indicator.Destimulators are indicators that contribute to negative changes in the ESG competitiveness of an enterprise.
The integral indicators E, S, G will be calculated, taking into account the values of the weighting coefficients, using the following formulas: We perform convolutions (10)-( 12) for the components E-, S-, G-.Next, it is necessary to simultaneously perform integral convolutions for their thresholds with an offset by the asymmetry coefficient in relation to the number of metallurgical enterprises under consideration.We obtain the dynamics of the E-, S-, G-components of the integral ESG competitiveness index vector compared to the integral thresholds.This makes it possible to assess the level of ESG competitiveness by components E-, S-, G.
To fully assess the level of ESG competitiveness of metallurgical enterprises, we consider it necessary to carry out a comprehensive assessment of the level of competitiveness of a metallurgical enterprise by the module of the vector of the integrated competitiveness indicator.To do this, we need to normalize it using the formula: is the largest possible value of the vector's modulus, given the values of its components in the interval [0, 1].
Similarly, having calculated the threshold values of the integrated ESG competitiveness indicator, it was found that only Metinvest (Ukraine), ArcelorMittal Bremen (Germany) and, starting from 2017, ArcelorMittal Asturias (Gijon) Spain meet the optimal competitiveness limits of metallurgical enterprises during the period under study.This confirms the correctness of the ESG competitiveness indicators calculations presented in table 4.
Within the framework of the proposed simulation model of the limits of optimality of ESG competitiveness of enterprises (figure 1), it is necessary to establish the compliance of each enterprise with the ESG competitiveness zones.
For the defined thresholds (table 6), the following zones of ESG competitiveness are defined for each of the indicators I E , I S , I G : I -zone of insufficient ESG competitiveness; II -zone of conditionally low ESG competitiveness; III -zone of optimal ESG competitiveness; IV -zone of conditionally high ESG competitiveness; V -zone of critical ESG competitiveness.The ESG competitiveness of metallurgical enterprises is determined by the amount of invested capital.To assess the forecast of ESG competitiveness, let us find out whether there is a relationship between the ESG competitiveness indicator and total ESG investments.Let's determine the total ESG investments: It is proposed to use the hyperbolic tangent function for the functional dependence of the integrated ESG competitiveness indicator on total ESG investments.This function has a right IOP Publishing doi:10.1088/1755-1315/1254/1/01212610 asymptote of one.The value of the index is also limited to one.Using correlation and regression analysis [15], the authors propose the following model of nonlinear multivariate regression: The coefficients of the multivariate nonlinear regression (15) after initial smoothing and linearization by logarithmization were found by the generalized least squares method in matrix form [8]. The value of the coefficient of determination R2 = 0.7529 is quite close to one.There is a relationship between the indicator and the selected factors.The Fisher's test, F = 67.05> F crit(0.95; 4; 66) = 2.51, showed that with a reliability of 95% (significance level), we can assume that the corresponding R 2 are statistically significant.The proposed mathematical model ( 15) is adequate to the statistical data.It can be used to diagnose ESG competitiveness.
The regression level surfaces of ( 15) are shown in figure 2. Arcelor Mittal Kryvyi Rih has the lowest level of ESG competitiveness (table 4).We consider the possibility of its improvement if the volume of investments is doubled by 2050 compared to 2021.However, the IESG value does not reach the lower level of the optimality boundary.
According to [13], steel production will remain unchanged in 2050 at the level of 2021, and metallurgical enterprises will need capital investments of 1 thousand USD per ton of steel, i.e. 4,700 million USD.It was found that, subject to an increase in ESG investment, Arcelor Mittal Kryvyi Rih will be able to enter the zone of conditionally low ESG competitiveness under the baseline scenario.
In the case of the optimistic scenario, the company may get into the zone of optimality.
The threshold values of the limits of optimality of the integrated indicator of ESG competitiveness of metallurgical enterprises and its components E j , S j , G j are determined.This made it possible to form a simulation model of the optimality limits, which should become the fundamental basis for making decisions on ESG investment in metallurgical enterprises.

Conclusion
Based on the results of the study, taking into account the requirements of the EU Taxonomy, Regulation (EU) 2020/852, the CSRD, and stakeholder requests for information support for assessing the ESG competitiveness of business, the authors propose a system of criteria for assessing the competitiveness of enterprises.This system is formed according to the cognitive approach, which is based on a lateral understanding of the clarity of the distinction between criteria and sub-criteria for assessing the ESG competitiveness indicator.The implementation of the proposed system in practice will ensure obtaining realistic results, making informed decisions to strengthen the competitive advantages of enterprises in a competitive environment and improving their attractiveness to a new generation of "conscious investors".The article proposes a methodology for an integrated assessment of the ESG competitiveness of metallurgical enterprises.The methodology is based on the synthesis of integral and reference approaches to assessing the homeostasis of competitiveness.It is adapted to the information support of the Management Report prepared in accordance with the GRI (Global Reporting Initiative) and SASB (Sustainability Accounting Standards Board) standards.Unlike the generally known methods, the methodology provides for the assessment of the extended homeostatic plateau of the dynamic system for determining the thresholds of the optimality of the ESG competitiveness indicator of enterprises and its components.This is the basis of ESG rating and the fundamental basis for determining the strategic imperatives of managing the competitiveness of enterprises in the context of global ESG integration.

Figure 1 .
Figure 1.Schematic representation of the threshold zones of the ESG competitiveness indicator of metallurgical enterprises.

Figure 2 .
Figure 2. Regression level surfaces of the ESG competitiveness indicator at a fixed value at the level of 2021.

Table 1 .
A set of indicators for assessing the ESG competitiveness of metallurgical enterprises.

Table 3 .
Scale for assessing the intensity of threats to the ESG competitiveness of metallurgical enterprises from decarbonization pressure.

Table 5 .
A set of indicators for assessing the ESG competitiveness of metallurgical enterprises.

Table 6 .
Threshold values of the integrated ESG indicator and its components.

Table 7 .
Forecast of the ESG competitiveness indicator of Arcelor Mittal Kryvyi Rih in 2050.Years Q E,t , mln USD Q S,t , mln USD Q G,t , mln USD I ESG Adding this amount to Q G,t , then rises above the lower level of the optimality bound I ESG .