MODELING THE CONTRIBUTION AND BENEFITS OF COMPANY STAKEHOLDERS

« DOI: 10.29141/2218-5003-2020-11-2-1

[J Irina N. Tkachenko1, Irina V. Pervukhina1, Aleksandr A. Zlygostev1

u 1Ural State University of Economics, Ekaterinburg, Russia <

| Abstract. The article reviews the theory and methodology and searches for relevant tools for modeling stakeholder contribution and benefits. The methodological framework comprises the stakeholder approach, the concept of sustainable growth and shared values. The study presents two econometric models of stakeholder value contribution and a mathematical model of stakeholder benefits. The models are built on panel data of several Russian banks. The authors look upon banks as constituents of the financial infrastructure essential for the existence of integrated business structures. Our findings show that the most appropriate proxy indicator for modeling monetary stakeholder value is sales revenue. We conclude that, for practical use, it is necessary to explore the relationships between different models and possible ways of their integration and develop a methodology for their evaluation and comparison. Further research should be related to the choice of factors affecting the model, the validity of the choice, the analysis of the regression model in order to infer the stakeholder contribution. To achieve technological breakthroughs, it is important to study value assessment procedures for stakeholders in the conditions of innovative and technological transformation of new forms of business organization, including network-based models, smart industries and ecosystems. Keywords: corporate governance; stakeholder approach; stakeholder value; econometric modeling; stakeholder contribution; stakeholder benefits; stakeholder relations.

JEL Classification: G32, G34, C50

Acknowledgements: The paper was funded by the Russian Foundation for Basic Research (RFFI) and Sverdlovsk oblast within the framework of the scientific project No. 20-410-660032 p_a.

Paper submitted: February 27, 2020

For citation: Tkachenko I.N., Pervukhina I.V., Zlygostev A.A. (2020). Modeling the contribution and benefits of company stakeholders. Upravlenets - The Manager, vol. 11, no. 2, pp. 2-15. DOI: 10.29141/2218-5003-2020-11-2-1.

INTRODUCTION

Despite the fact that the stakeholder approach has long been recognized as a management tool, it is still underdeveloped in terms of methodology and usage. Methodological and applied difficulties arise when an attempt is made to establish a powerful method for creating stakeholder value. Nevertheless, although the experience of empirical substantiation of how stakeholder value can be measured is still relatively limited, this theory generates considerable research interest. Such aspects as stakeholder partnership and interaction between stakeholders based on defined value would offer new perspectives for research and management. The relevance of the problem is connected with the translation of the stakeholder approach into the field of corporate governance (CG) and the emergence of a new paradigm of relations between business, society and the state, where corporate value is created for the benefit of not only the business owners and management, but also a wide range of internal and external stakeholders.

The first step in defining stakeholder value is to identify the most significant groups of stakeholders; analyze the prerequisites of their partnership, or integration; identify interests of different groups; evaluate stakeholders& contribution to the creation of firm value and, finally, calculate the type of payment that can be offered to cover the input of each stakeholder group. At the same time,

we should take into account that the stakeholder model should target the creation of value for stakeholders and the balance of their multiple interests. Stakeholder value is understood as value co-created for numerous actors and stakeholders, for a network of stakeholders [Agraw-al, Kaushik, Rahmanc, 2015; Hein et al., 2017]. Maximizing shareholder value should not be treated as the only measurement factor of company performance: it should be evaluated by the total expanded value for multiple stakeholders involved in co-creation of value. The measurement of stakeholder value creation helps to determine the relative importance of the contribution of each stakeholder group. However, this concept remains unclear and requires criteria to judge its performance, both financial and non-financial.

The relevance of the topic is aggravated by the apparent contradiction between numerous debates and research literature on the issues of stakeholder interest considerations and a marked lack of assessment tools. Both researchers and business practitioners are facing a number of questions related to methodology and application of the theory of stakeholders and the assessment of stakeholder value, e.g. How to maximize stakeholder value if, by increasing the value for some stakeholders, we risk to deprive others of their share, thus neglecting their interests? How do individual stakeholders create the

company value, and what reward do they receive? How to measure the created value?

In most recent studies researchers have proposed various techniques of assessing stakeholder value: monetary and non-monetary methods of evaluation; methods of assessing the contribution of stakeholders through questionnaires, interviews, expert assessments, econometric analysis, multiple regression models and others. The purpose of the paper is to review the theory and methodology of stakeholder value assessment, and search for relevant tools for modeling stakeholder value, contribution and benefits using econometric models built on panel data of the Russian banking sector.

LITERATURE REVIEW

The research in the field of measuring stakeholder value creation is still at an early stage. In their most recent ground study Tapaninaho and Kujala [2019] stated that the definition of stakeholder value itself and the understanding of how stakeholder value is created vary significantly. Stakeholder studies range from narrow to broad conceptualizations of who creates value, what kind of value is created, and with and for whom it is created. Moreover, along with the "financial" approach to stakeholder value understanding, its definition often considers non-financial values or even extends to social, environmental conditions under which firms are more likely to create ecological value [Sunny et al., 2018].

Brandenburger and Stuart [1996] based their calculation of stakeholder value on the analysis of the value chain suggested by Michael Porter in his book Competitive Advantage [1985]. They suggested that stakeholder value might be calculated by the difference between the supplier&s willingness to pay and the buyer&s opportunity costs.

The importance of measuring the creation of stakeholder value was reported by Figge and Schaltegger [2000]. Shareholder value can be expressed as the cash value of all the surplus funds available in future for distribution to shareholders. The shareholder value approach therefore attempts to determine how much a company is worth as far as the shareholders are concerned. On the other hand, stakeholder value can be interpreted as a value contributed by a specific stakeholder towards helping the firm meet its business goals or enhancing its value.

Harrison and Wicks [2013] argued that stakeholder value is created when each interested party provides resources or influence expecting to receive some material and/or intangible asset in return. The outcome of this situation is an allocation of value from which all of the firm&s stakeholders benefit. Mitchell et al. [2015] introduced a theory of value-creation stakeholder accounting, emphasizing the role of stakeholder partnerships. Hall, Millo and Barman [2015] examined the use of social return on investment as an accounting methodology that allows managers to manage and communicate about the

social value created for different stakeholders. In his most ° recent research Fisher [2018] looked upon the creation of d stakeholder value as an organizing principle for the firm&s I strategic planning, the need to involve the stakeholders | in defining what value means to them. £

Another narrative concerns understanding the role § of various stakeholders in value creation. As an example, g Ramírez and Tarziján [2018] considered the distribution x of stakeholder values for one group of stakeholders, i.e. ¡I employees, and concluded that stakeholder value might 5 increase in response to the impact of exogenous factors H (changes in the price of the firm&s products), as well as S of changes in institutional structures and types of ownership, and quality of management. Eskerod and Ang [2017] viewed the role of various stakeholders from a broader perspective and investigated the role of five specific stakeholder types (i.e. project owners, project members, local businesses and non-profit organizations, local citizens, and the general public). They also acknowledged that different types of stakeholders might relate to different kinds of values.

The issue of stakeholder value can be addressed from a social aspect. Castro-Martinez and Jackson [2017] suggested that the interaction between the firm and its external stakeholders may generate trustworthiness signals which may become factors for creating stakeholder value.

Some researchers have attempted to design instruments for measuring stakeholder value. Apitz et al. [2017] presented the Stakeholder Values Assessment (SVA) tool that was developed to quantitatively address environmental, economic and social costs and benefits based upon diverse stakeholder values. A similar approach aiming to find a balance between interests of different stakeholder groups was suggested by Abrosimova and Sedelnikova [2011]. They presented the evaluation scale which enabled one to identify stakeholders whose interests were most or least satisfied. The total values of the scale then were used to calculate the "balancing" average.

The tools offered to measure stakeholder value vary from the index of stakeholder value impact [Dreyer et al., 2017; Novozhilova, 2017]; and the index of sustainable growth, where the stakeholder contribution was expressed as long-term sustainable company growth, and the index of balanced interests where value was created for strategic stakeholders [Dolmatova, 2013] to a stakeholder value index, which is computed as the proportion of the created economic benefit (financial indicator) to the costs related to building relationships with stakeholders [Ivashkovskaya, 2016] and a multiple regression model which combined monetary valuation of the company and non-monetary valuation of indicators and factors of stakeholder value creation, which showed how satisfied (or dissatisfied) were stakeholders with their interaction with the company [Samokhina, 2014; Efimova, 2013; Efimova, Samokhina, 2014]. The value of the company showed its utility for the stakeholders and resulted from

g synergy of resources and benefits of economic and non-3 economic nature [Kharin, Gareev, 2014; Tkachenko, 2017]. £ On the basis of the assumption that stakeholders have § a financial value to the firm that can and should be ac-[J counted for through the firm&s financial reporting system, £ Carlon and Downs [2014] proposed a three-step "stake-| holder valuing" process which started with codifying the Ü firm&s identity as a stakeholder entity, moved to assessing stakeholder value consistent with that identity, and concluded with accounting for and reporting that value.

Based on the value-creation perspective, Tantalo and Priem [2016] made an attempt to integrate business strategy, stakeholder theory and essential stakeholders& multi-attribute utility functions. They developed the stakeholder synergies theory showing how top managers can create new versatile value for several essential stakeholder groups simultaneously, thereby increasing the size of the utility "pie" for those system members.

A thread of literature addresses the question of how stakeholder value is created in cooperative relationships. Some studies provide managers with ideas on how to conceive value creation through stakeholder networks [Schneider, Sachs, 2015; Hein et al., 2017]. Firm-stakeholder relationships are examined from the managerial or organizational perspective, as well as through understanding the accrued effects of the networks in which firms participate. In stakeholder value networks, economic and social exchanges are represented by value flows between stakeholders. Sease et al. [2018] propose a tool to visualize the data created during the stakeholder value network analysis and to model stakeholder and their value exchanges.

While most studies focus on monetary approaches to assessing stakeholder value, some authors challenge non-monetary and integrated approaches. Neto et al. [2018] study how value judgments of stakeholders will affect decision-making on the incorporation of new health technologies when budgetary resources are limited. Lankoski, Smith and Van Wassenhove [2016] suggested that stakeholders judge the value created or destroyed by firms not in absolute but in relative terms - as losses and gains against a reference state that might differ across stakeholders and change over time, and where losses weigh more heavily than equally sized gains. The authors highlight direct managerial relevance of understanding stakeholder judgments of value, since it is managers who make decisions about how to allocate resources and this affects the value that stakeholders receive.

There were made attempts to focus on modeling stakeholder value. Fernández-Guadaño and Sarria-Pedro-za [2018] aimed to discover whether the development of corporate social responsibility (CSR) generated value for certain stakeholders. They calculated value added as: Value Added = Financial year result + Corporation Tax + Personnel Expenses + Depreciation Charges + Financial Expenses and so on. The results showed that CSR had a

negative influence on the distribution of value in favor of employees as primary stakeholder; a positive influence on the state as secondary stakeholder and had no influence on other stakeholders.

The reviewed research allows us to conclude that, to date, the issues of stakeholder value creation and stakeholder value assessment have been approached from many different perspectives, including financial, non-financial and integrated ones.

RESEARCH METHOD

Sampling

The sample comprises 11 medium-sized banks which represents 2.2 % of a universe composed of 447 operative banking institutions in Russia as of the first half of 2019. The banks are comparable in terms of assets and represent 2.97 % of the banking sector&s total assets (Fig. 1). In total, the sample panel consists of 83 observations between 2010 and 2017 (Table 1).

Fig. 1. Sample of banks by assets, as of February 1,20191 Рис. 1. Выборка банков по размеру активов (по состоянию на 1 февраля 2019 г.)

Table 1 - The sample panel Таблица 1 - Выборка исследования

Bank Period Observations (n=83)

Absolut Bank 2010-2017 8

Vozrozhdenie Bank 2010-2017 8

Bank Zenit 2010-2017 8

Vostochny Bank (Orient Express Bank) 2010-2017 8

ING Bank 2010-2017 8

Moscow Industrial Bank 2010-2017 8

Renaissance Credit 2013-2017 5

Surgutneftegasbank 2010-2017 8

Transkapitalbank 2010-2017 8

Ural Bank for Reconstruction and Development (UBRiR) 2010-2017 8

For analysis purposes, consolidated data collected from databases available on the IFRS website were considered. As to the type of control, three banks are under public control, four are federal banks, and four are state banks. The other banks are controlled by private entities.

Model specification and construction

The econometric specification for the study is that stakeholder value is determined by proxy values. In order to identify factors that determine company&s stakeholder value, four proxies are constructed. These are conventional measurement tools of finance by value: (1) market value or capitalization, (2) EVA (Economic Value Added), (3) net profit, and (4) sales revenue.

The research aims to design a model that allows assessing stakeholder value. The study was divided into three stages. The models were tested on the basis of three database sets (Table 2). The econometric model was built with the use of the R Project for Statistical Computing (https://www.r-project.org).

In assessing stakeholder value, we proceed from the following assumptions: (1) stakeholder value changes along with a proxy-indicator vector; (2) a proxy-indicator does not equal stakeholder value; and (3) changes in a proxy-indicator reflect changes in stakeholder value.

At Stage 1 the study utilized an econometric analysis approach which was chosen for the following reasons. First, econometric models enable one to statistically estimate the relationships among variables. Second, by carrying out regression analysis, it is possible to measure how each variable relates to the resulting quantity.

The econometric model was built with the use of the R Project for Statistical Computing (https://www.r-project. org). However, the results received at Stage 1 were not convincing enough as the number of observations was too small (n=24). Moreover, though the constructed "market value" proxy is quantifiable and takes into account numerous factors and data sources available in the market, ° it has some limitations. The main challenge to promote d market value as a proxy is that it is related to listed com- I panies only, which virtually excludes unlisted companies | since they cannot be assessed in terms of capitalization. £ The findings of Stage 1 are discussed in [Tkachenko, Zly- « gostev, 2018]. §

Stage 2 x

At Stage 2 we made an attempt to identify factors that H determined stakeholder value for unlisted companies. 5 The number of observations increased significantly to 240 H observations from 80 banks in the period of 2010-2016. £ Two proxies were tested: EVA and net profit. Both proxies can be applied to analyze listed as well as unlisted companies. The model was constructed for EVA since, in contrast to net profit, it allowed tracking market trends in interest rates. However, R-squared was quite low (0.32), thus the search for a more appropriate proxy was still an issue. The findings of Stage 2 were discussed in [Zlygostev, 2018].

At Stage 3 the study was carried out using the data sourced from 11 companies& sites and totaled 84 observations. The model was tested with sales revenue as a proxy. The sales revenue factor has certain advantages over EVA and net profit as it is never a zero value, which made it possible to logarithm the value and design an econometric model. In addition, sales revenue might be easily correlated with stakeholder groups, which allowed us to build two contribution models. These models provided a different perspective on the patterns of created stakeholder value.

At Stage 3 along with constructing the models of stakeholder value contribution (Contribution Model), we designed a model of stakeholder benefits (Benefit Model). Unlike the contribution models, the benefit model is non-regressional and is computed by simple summation of known benefits for each stakeholder group.

Table 2 - Database used in the econometric analysis Таблица 2 - Данные для эконометрического анализа

Parameter Database 1 Database 2 Database 3

Source Company sites (IFRS) Moscow Exchange SPARK (Section "Banks"). Russian Accounting Standards (RAS) Company sites (IFRS)

Designed model Contribution Model 1 Contribution Model 2 Contribution Model 1. Contribution Model 2. Benefit Model

Proxy indicator Market value EVA. Net profit Sales revenue

Observations 24 240 84

Ownership Public limited companies Unlisted companies Unlisted companies

Stakeholder type Shareholders (owners). Employees Shareholders (owners). Employees. Borrowers Shareholders (owners). Employees. Borrowers. Clients (users of fee-based services)

R-squared 0.88 0.32 0.77 (Contribution Model 1) 0.86 (Contribution Model 2)

£ The stakeholder value constructs associated with the vari-<

| ous stakeholder types are presented in Table 3. Is Each stakeholder group was assigned with a quantitative index that, as assumed, directly or indirectly characterizes contribution or benefits for the stakeholder. Thus, this index serves as a stakeholder group&s impact factor for stakeholder value (target function). However, we do admit that the chosen indicators may not fully reflect the contribution or benefits of stakeholders.

RESULTS AND DISCUSSION

In this paper, we seek to establish a methodology for modeling stakeholder value. As reported earlier, the data obtained at Stage 1 were unconvincing due to a small sample size and limitations of the market value proxy. At Stage 2 we managed to design a model that enabled us to assess stakeholder value of unlisted companies. For now, Stage 3 appears to be the most consistent and satisfactory in terms of results obtained, since it reflects on the experiences with the challenges of modeling at Stage 1 and Stage 2.

To exemplify our calculations of stakeholder contribution patterns based on Database 3, we randomly selected two banks from the sample panel: the Ural Bank for Reconstruction and Development (UBRiR) and Surgutneft-egasbank. Stakeholder value contribution was computed for these banks for a period of 2010-2017 using Contribution Model land Contribution Model 2.

The Database 3 statistics for the variables used in Contribution Model 1 can be found in Table 4 (UBRiR) and Table 5 (Surgutneftegasbank).

Table 3 - Stakeholders in the banking sector: contribution and benefits Таблица 3 - Стейкхолдеры в банковском секторе: вклад и выгоды

Stakeholder groups Stakeholder subgroups Stakeholder benefits Stakeholder contribution

Internal

Business owners Majority shareholders. Bondholders. Depositors Dividends. Interest on bonds and deposits Provide bank financing

Employees Front office. Head office Salary. Compensation and benefits (monetary). Working conditions and reasonable work time (non-monetary) Create value for customers and bank

External

Clients Corporate. Private Interest on deposits. Cash back (monetary). Non-cash transactions, money transfers, accounts. Borrowings. Other (non-monetary) banking services Generate demand for banking services, resulting in bank profit

Local community Local residents. Municipal authorities Local budget taxes. Investments in local infrastructure (monetary). Job creation. Production of goods and services (non-monetary) Source of human capital

Government Regional authorities. Federal authorities Local budget taxes. Investments in local infrastructure (monetary). Job creation. Production of goods and services. Smooth functioning of national banking system (non-monetary) Protection of private property. Creation of "rules for the game". Protection of rights

Table 4 - Data for building Contribution Model 1, UBRiR, 2010-2017, thousand rubles Таблица 4 - Данные для построения Модели 1 - Вклада стейкхолдеров для УБРиР за период 2010-2017 гг., тыс. руб.

Year T_income ClientMoney Sk kom_inc Nma_Os

Table 5 - Data for building Contribution Model 1, Surgutneftegasbank, 2010-2017, thousand rubles Таблица 5 - Данные для построения Модели 1 - Вклада стейкхолдеров для Сургутнефтегазбанка за период 2010-2017 гг., тыс. руб.

Year T_income ClientMoney Sk kom_inc Nma_Os

T_income is sales revenue totaling fees and interest for the reporting period; ClientMoney is customers& account balance at the end of the reporting period; Sk is bank stock at the end of the reporting period; kom_inc is fee-based income for the reporting period; Nma_Os is total intangible assets and fixed assets at the end of the reporting period.a4_brochure_ipos_eng_print.pdf; База данных IPO/SPO. URL: http://www.preqveca.ru/placements/

Contribution Model 1 presents the contribution of four stakeholder groups: (1) business owners; (2) employees; (3) depositors, and (4) clients using fee-based services.

Table 6 provides the descriptive statistics for the variables used in Model 1. Multicollinearity is absent (correlation matrix, ViF test). The Breusch-Pagan Test showed the presence of homoscedasticity in the regression model. Positive autocorrelation is observed, which shifts the nominal estimates of the resulting indicator, but it does not affect the relative contributions of each factor. All coefficients are statistically significant; the number of observations is sufficient. F-statistic is <0.05, adjusted R-squared equals 0.769, which indicates a close relationship between the factors (group of stakeholders) and the target variable.

The analyzed banks are comparable in terms of contribution values of different stakeholder groups, e.g. employees& contribution at both UBRiR and Surgutneftegasbank ranged from 15 % to 18 %. The patterns of contributed stakeholder value seem to be similar at both banks. At the same time, as shown at Fig. 21 during the analyzed period, the proportion of employees& contribution at UBRiR was higher than at Surgrutneftegasbank (17.38-16.37 % vs 16.56-15.35 %). The analysis of the depositors& contribution showed the difference in trends: while at UBRiR the depositors& contribution demonstrated an upward trend, at Surgutneftegasbank the dynamics displayed an irregular pattern (Fig. 3).

Table 6 - Model 1 of Stakeholder Value Contribution (Contribution Model 1) Таблица 6 - Модель 1 - Вклад в стейкхолдерскую стоимость (Модель 1 - Вклад стейкхолдеров)

Formula log(T_income) = ClientMoney + log(Sk) + kom_inc + log(NMA_Os)

Coefficients: Estimate Std. Error t value Pr(>|t|)

(Intercept) 7.00900000000 2.51200000000 2.791 0.007 **

ClientMoney 0.00000000442 0.00000000110 4.023 0.000 ***

log(Sk) 0.28880000000 0.11810000000 2.446 0.017 *

kom_inc 0.00000003752 0.00000001177 3.187 0.002 **

log(NMA_Os) 0.28900000000 0.05997000000 4.820 0.000 ***

Signf. Codes:0 &***&0.001 &**& 0,01 &*&

Residual standard error: 0.3795 on 78 degrees of freedom

Adjusted R-squared: 0.769

F-statistic: 69.42, p-value <0.000

Confidence interval 2.50 % 97.50 %

(Intercept) 2.00859200000 12.00938000000

ClientMoney 0.00000000223 0.00000000661

log(Sk) 0.05375240000 0.52392640000

kom_inc 0.00000001408 0.00000006096

log(NMA_Os) 0.16966280000 0.40843570000

Contribution Model 2 of stakeholder groups was constructed for the same sample panel which integrated Database 3 and the proxy (Table 7). The statistics for the variables for Model 2 were similar to Model 1 (see Tables 4 and 5). 8 92

-•-Depositors —a—Owners » Clients » Employees ■ Other (fee-basedservices)

Fig. 2. Contribution Model 1, UBRiR (2010-2017) Рис. 2. Модель 1 - Вклад стейкхолдеров для УБРиР за период 2010-2017 гг.

Fig. 4. Contribution Model 2, UBRiR (2010-2017) Рис. 4. Модель 2 - Вклад стейкхолдеров для УБРиР за период 2010-2017 гг.

» Clients

(fee-basedservices)

Fig. 3. Contribution Model 1, Surgutneftegasbank (2010-2017) Рис. 3. Модель1 - Вклад стейкхолдеров для Сургутнефтегазбанка за период 2010-2017 гг.

• - Depositors —•— Borrowers —•— Employees —■— Other

Fig. 5. Contribution Model 2, Surgutneftegasbank (2010-2017) Рис. 5. Модель 2 - Вклад стейкхолдеров для Сургутнефтегазбанка за период 2010-2017 гг.

Table 7 - Model 2 of Stakeholder Value Contribution (Contribution Model 2) Таблица 7- Модель 2 - Вклад в стейкхолдерскую стоимость (Модель 2 - Вклад стейкхолдеров)

Formula log(T_income) = ClientMoney + log(Sk) + kom_inc + log(NMA_Os)

Coefficients: Estimate Std. Error t value Pr(>|t|)

(Intercept) 13.45000000000 0.49190000000 27.346 0.000 ***

ClientMoney 0.00000000356 0.00000000074 4.808 0.000 ***

log(Sk) 0.00000002796 0.00000000265 10.574 0.000 ***

kom_inc 0.15710000000 0.03584000000 4.385 0.000 ***

log(NMA_Os) 0.28900000000 0.05997000000 4.820 0.000 ***

Signf. Codes:0 &***&0.001 &**& 0,01 &*&

Residual standard error: 0.3795 on 78 degrees of freedom

Adjusted R-squared: 0.860

F-statistic: 169.3, p-value <0.000

Confidence interval 2.50 % 97.50 %

(Intercept) 12.47137000000 14.42943000000

ClientMoney 0.00000000208 0.00000000503

X.inc 0.00000002270 0.00000003323

log(Nma_Os) 0.08580774000 0.22846880000

log(NMA_Os) 0.16966280000 0.40843570000

Figures 4 and 5 illustrate the patterns of contributed values in the two sampled banks.

Contribution Model 1 described a larger proportion of stakeholder value and, in addition, identified four groups as compared with the three groups in Contribution Model 2. On the other hand, Model 2 featured the borrowers& contribution, which was not evident in Model 1, while the contribution of clients using fee-based services was exhibited in Model 1 only. As a result, the pattern of stakeholder value contribution revealed in Model 2 was different from Model 1. The share of other groups in Model 1 accounted for 58-60 % while in Model 2 it was bigger - 85-90 %. On the contrary, adjusted R-squared in Model 2 was higher than in Model 1: 0.76 vs 0.86, respectively. For each modeling object, Model 1 and Model 2 showed similar dynamics of contribution to stakeholder value for the same group of stakeholders (employees and depositors). This made it possible to measure which year stakeholders performed better or worse. Analyzing the relative increase in contribution in each bank in Model 1 and Model 2, it is evident that they coincide almost to the decimal, while the share of the stakeholder group contribution may vary, e.g. in 2017 UBRiR employees& contribution accounted for 16.37 % (Model 1) and 6.74 % (Model 2) (Figures 3 and 5).

The comparison of the two models leads to the following conclusions. The model shows an "averaged" pattern for all objects studied. At the same time the model can show distinct patterns of objects, but only for decimals. Sales revenue seemed to be the most appropriate proxy indicator as compared with EVA and net profit as it responded more flexibly to changes in variables, which allowed finding better correlation.

The rationale lying behind selecting sale revenue as a proxy for monetary stakeholder value is explained by the thesis that a firm is a "hub" of communication, creation and distribution of values for a stakeholder network. In that case, all sales revenues received by the company are the value generated by stakeholders, which is then shared among the members of the network as salary, payment to suppliers, dividends, etc. Clients make up a special group of stakeholders as it is their presence that makes the value creation possible, i.e. a created demand for a good or service.

Model 3 aimed to evaluate the impact of benefits on stakeholder value for five types of stakeholders: owners,

employees, borrowers, depositors and clients using fee- °

based services. This model is non-regressional and was d

computed by simple summation of known benefits in I

each stakeholder group. |

The stakeholder benefit constructs associated with £

various stakeholder types and the Database 3 statistics § for the variables used in Benefit Model 3 for UBRiR are g presented in Table 8. As can be seen from Table 8, bank x borrowers accounted for the largest proportion of ben- Ц efits - around 77 %. 5

Comparison of Contribution and Benefit Models si

To reconcile the contribution and benefit models, we S had to take some assumptions. The first assumption is that we have estimated all major benefits for the most significant stakeholders, i.e. we assumed that the Benefit Model allowed us to assess all stakeholders& value and we equated it to the Contribution Model. In theory, the amounts of created and distributed values should balance. The second underlying assumption concerns the understanding that tangible (financial) benefits were recognized partly, as a proportion of the total cost. Through the adjustment coefficient that can be computed by expertise, it is necessary to bring the shared stakeholder value into line with the created value. For example, if we believe that the benefit model reflected 80 % of the total created stakeholder value, then the remaining 20 % can be accountable to other factors.

Another approach to analyzing the patterns of stakeholder contribution and benefits is to find a "spread" between contribution and benefits for a certain group of stakeholders. The larger the difference between stakeholder contribution and stakeholder benefits, the higher the risk the stakeholder network is exposed to when communicating with this stakeholder group. In other words, stakeholders who contribute more and receive less are apt to face conflicts with others in order to protect their own interests.

Since stakeholder groups can vary quantitatively, it might be useful to determine stakeholder contribution per stakeholder rather than per group. Using UBRiR stakeholders as an example we assumed that in 2017 the approximate number of bank clients (both depositors and borrowers) was 200,000. Using the open data for UBRiR employees and owners we computed contribution and benefits per stakeholder group. For each group we identified the difference between contribution and benefits, or a "spread". This enabled us to describe each stakeholder group in terms of

Table 8 - Constructs and data for building Model 3, UBRiR (2017) Таблица 8 - Данные для построения Модели 3 для УБРиР в 2017 г.

Stakeholder group Annual benefits Amount, thousand rubles Proportion of the total, %

Business owners Net profit S36,496 G.62

Employees Payroll budget 3,912,S41 2.92

Borrowers Outstanding loan portfolio less interest payable 1G3,GS3,G91 7б.92

Depositors Interest earnings 26,1SG,2S6 19.S4

| With the same assumption about the number of bank Is clients in mind, the contribution and benefits per stakeholder rather than per stakeholder group were computed. The data in Table 10 show that it is business owners who contributed the most (99.91 %) hence the owner&s received benefits are the most substantial (99.19 %), proportionally almost equal to contribution. The change in the pattern also resulted in the change of group status. While the group of owners maintained its status of a "donor", insignificant contribution and benefits of employees calculated per stakeholder turned employees into "recipients", rather than "donors".

However, not all groups of stakeholders can correlate in the models of contribution and benefits. For example, Contribution Models allowed identifying the group of clients who used fee-based services, but failed to recognize borrowers. On the other hand, Contribution Models could take into account "other" categories of stakeholders that are not represented in the Benefit Model.

It is worth noting some limitations of the study. Our approach to stakeholder value assessment is based on some assumptions. One of the assumptions is that our benefit model reflects the total value generated by the contribution model. Another assumption is the determination of factors and indicators accountable for the total contribution and benefits of stakeholders. The choice of

or a different set of factors and indicators for a stakeholder

ie group might lead to a different pattern of stakeholder

b- value contribution and benefits. Finally, the proposed

m- models do not take into account non-financial factors of

ts value creation, which are discussed in research literature [Guglya, 2015; Efimova, 2013]. Consequently, monetary

k assessment of stakeholder value contribution and benee- fits cannot give us a full picture of what stakeholder value

jt- is, however it might tread the path to further understandrs ing of the concept.

&s Our findings on modeling created and shared stake-o- holder value were visualized in a dashboard, an instruin ment that is designed to measure, monitor, and report js. a degree of satisfaction for key stakeholder groups. This o- tool can be applied for managing stakeholder risk and rees lationships with stakeholders. More specifically, the dash-pi- board can serve as a tool unifying the existing satisfaction indices and bringing them to a 100-score scale, which will te make them comparable and will allow the management le, to shape the policy of their relationships with stakehold-:li- ers (Fig. 6).

:e One of the advantages of the dashboard is that it can

ld be built on compiling already existing but disaggregated

at data distilled from the company&s reports and surveys, for example, CSAT data for different categories of customers.

ur Along with satisfaction indices the dashboard might inin clude the patterns of stakeholder contribution and benur efits which show the stakeholders who make the most

ie tangible contribution (donors) and receive the most signi- nificant benefits (recipients). As mentioned earlier, conal tribution and benefit patters per stakeholder group and

of per stakeholder may vary significantly. For example, at

Table 9 - Contribution and benefits by stakeholder groups (UBRiR, 2017) Таблица 9 - Вклад и выгоды стейкхолдерских групп для УБРиР в 2017 г.

Stakeholder group Contribution, % Benefits, % Spread, % Group status

Business owners 17.30 0.б2 -1б.б8 Donor

Employees 17.38 2.92 -14.4б Donor

Borrowers i 7б.92 i ?

Depositors 2.1б 19.54 17.38 Recipient

Users of fee-based services 0.25 i i ?

Other б2.91 i -б2.91 ?

Note: Question marks indicate inconsistent data.

Table 10 - Contribution and benefits per stakeholder (UBRiR, 2017) Таблица 10 - Вклад и выгоды каждого стейкхолдера для УБРиР в 2017 г.

Stakeholder group Contribution, % Benefits, % Spread, % Group status

Shareholder 99.91 99.19 -0.72 Donor

Employees 0.09 0.43 0.34 Recipient

Borrowers i 0.31 i ?

Depositors 0.00 0.08 0.08 Recipient

Users of fee-based services 0.00 i 0.00 ?

Other i i 0.00 ?

Note: Question marks indicate inconsistent data.

Relationships with stakeholders dashboard

Satisfaction (0-100%)

Customers individuals Clients legal entities Employees Owners

Contribution

Contribution

Per stakeholder group

Customers individuals Clients legal entities I Employees Owners

Per stakeholder

Customers individuals Clients legal entities Employees Owners

Benefits

Fig. 6. Dashboard of relationships with stakeholders Рис. 6. Визуализация вклада-выгод стейкхолдеров

a group level, the contribution of business owners may seem to be not as large as compared to the contribution per stakeholder. It is worth mentioning that modeling contribution and benefits in the dashboard would be the most difficult action to perform since experts would be fully responsible for the selection of optimal and objective indicators describing contribution and benefits. This process seems to feature some compromises, assumptions and a high degree of generality.

Thus, the dashboard aims to provide the firm management with the information needed for decision making with regard to company strategy and tactics of interaction with stakeholders. This might lead to a more organic structure of stakeholder values and prevent risks of being involved in conflicts with stakeholders.

CONCLUSION

Since the main objective of the present article was to find tools for assessing stakeholder value, the paper considered the general theoretical provisions of the stakeholder value. The literature review showed that the stakeholder value evaluation presents measurement difficulties and the creation of the stakeholder value is still the point of continuous debates.

In an attempt to find a possible method of the stakeholder value assessment we formulated and tested a methodology based on building two econometric models of stakeholder value contribution and one mathematical model of stakeholder benefits. The results of the study indicated the problem of assessing the quality, choice and interpretation of the models.

standard - the total extended value to all stakeholders. As proxy indicators of stakeholder value the following econometric tools were tested: market value, EVA, sales revenue and net profit. Changes in the pattern of contribution to the stakeholder value for each model were analyzed. We found that the most appropriate proxy indicator for modeling monetary stakeholder value was sales revenue. However, since sales revenue shows only the external, visible movement of stakeholder values (exchange value), it is unlikely to identify non-financial factors of value creation.

The study of assessing stakeholders& contribution and benefits allows us to conclude that the stakeholder model of CG may be beneficial for both unearned increment of

business and creating value for financial and non-financial stakeholders since these processes are interdependent. However, despite the approbation of new tools for the stakeholder value assessment, the latter at the moment is conventional and based upon many assumptions, which does not allow us to focus on one stakeholder value model only. For practical use, it is necessary to explore the relationships between different models and possible ways of their integration, develop a methodology for their evaluation and comparison.

Further research should also be related to the choice of factors, the validity of the choice, the analysis of the regression model in order to infer the stakeholder contribution. The impact of stakeholder networks on attaining synergy should be explored. To achieve technological breakthroughs, an important research area is stakeholder value assessment under the conditions of innovation and technology transformation of business organizations, including networks models, models of smart production and ecosystems, all forming the basis of high-tech sectors of the economy.

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Information about the authors

Irina N. Tkachenko

Dr. Sc. (Econ.), Head of Economic Theory and Corporate Economics Dept. Ural State University of Economics (62/45 8 Marta/Narodnoy Voli St., Ekaterinburg, 620144, Russia). E-mail: tkachenko@usue.ru.

Irina V. Pervukhina

Associate Professor of Business Foreign Language Dept. Ural State University of Economics (62/45 8 Marta/Narodnoy Voli St., Ekaterinburg, 620144, Russia). E-mail: ivp@usue.ru.

Aleksandr A. Zlygostev

Postgraduate of Economic Theory and Corporate Economics Dept. Ural State University of Economics (62/45 8 Marta/Narodnoy Voli St., Ekaterinburg, 620144, Russia). E-mail: letrus.alex@gmail.com.

« DOI: 10.29141/2218-5003-2020-11-2-1

я И.Н. Ткаченко, И.В. Первухина, А.А. Злыгостев1

ш 1 Уральский государственный экономический университет, г. Екатеринбург, РФ «

| Аннотация. Статья посвящена исследованию стейкхолдерской стоимости, поиска адекватного инструментария для моделирования вклада и выгод стейкхолдеров. Методологической базой исследования послужили парадигма устойчивого развития, концепция общих ценностей, стейкхолдерский подход. В исследовании представлены две эконометрические модели вклада заинтересованных сторон и математическая модель выгод для стейкхолдеров. Модели построены на панельных данных российского банковского сектора. Авторы рассматривают банки как объекты финансовой инфраструктуры, без которой невозможно существование сетевых интегрированных структур бизнеса. Протестированы с помощью эконометрических инструментов следующие прокси-переменные стейкхолдерской стоимости компании: рыночная стоимость, EVA, выручка. Проанализированы изменения структур вклада в стейкхолдерскую стоимость по каждой модели в динамике. Наиболее подходящей для оценки стейкхолдерской стоимости является монетарная прокси-переменная «выручка». Сделаны выводы о том, что для практического использования инструментария необходимо изучить взаимосвязи между различными моделями и возможные пути их интеграции, разработать методологию их оценки и сравнения. Дальнейшие исследования должны быть связаны с поиском и обоснованием факторов, влияющих на стейкхолдерскую стоимость, анализом моделей с целью определения вклада и выгод заинтересованных сторон. В условиях инновационно-технологической трансформации форм организаций бизнеса, в том числе сетевых моделей, моделей умных производств и экосистем, важны исследования процедур оценивания ценности для стейкхолдеров.

JEL Classification: G32, G34, С50

Финансирование: Исследование выполнено при финансовой поддержке РФФИ и Свердловской области в рамках научного проекта № 20-410-660032 р_а. Дата поступления статьи: 27 февраля 2020 г.

Ссылка для цитирования: Ткаченко И.Н., Первухина И.В., Злыгостев А.А. (2020). Моделирование вклада и выгод стейкхолдеров компании // Управленец. Т. 11. № 2. С. 2-15. DOI: 10.29141/2218-5003-2020-11-2-1.

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Apitz S.E., Fitzpatrick A.G., McNally A., Harrison D., Coughlin C., Edwards D.A. (2017). Stakeholder value-linked sustainability assessment: Evaluating remedial alternatives for the Portland Harbor Superfund Site, Portland, Oregon, USA. Integrated Environmental Assessment and Management, vol. 14, no. 1, pp. 43-62. DOI: 10.1002/pa.1685.

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Carlon D.M., Downs A. (2014). Stakeholder valuing: A process for identifying the interrelationships between firm and stakeholder

attributes. Administrative Sciences, vol. 4, pp. 137-154. DOI: https://doi.org/10.3390/admsci4020137.

Carroll A.B., Näsi J. (1997). Understanding stakeholder thinking: Themes from a Finnish conference. Business Ethics: A European Review, vol. 6, no. 1, pp. 46-51.

Castro-Martinez M.P., Jackson P.R. (2017). Translation of trustworthiness signals into factors for stakeholder value cocreation. Journal of Public Affairs, vol. 18, no. 3. DOI:10.1002/pa.1685.

Dreyer B., Lüdeke-Freund F., Hamann R., Faccer K. (201