=Paper=
{{Paper
|id=Vol-2713/paper29
|storemode=property
|title=Model for assessing and implementing resource-efficient strategy of industry
|pdfUrl=https://ceur-ws.org/Vol-2713/paper29.pdf
|volume=Vol-2713
|authors=Nadiia Shmygol,Francesco Schiavone,Olena Trokhymets,Dariusz Pawliszczy,Viktor Koval,Ruslan Zavgorodniy,Andrii Vorfolomeiev
|dblpUrl=https://dblp.org/rec/conf/m3e2/ShmygolSTPKZV20
}}
==Model for assessing and implementing resource-efficient strategy of industry==
https://ceur-ws.org/Vol-2713/paper29.pdf
277
Model for assessing and implementing resource-efficient
strategy of industry
Nadiia Shmygol1[0000-0001-5932-6580], Francesco Schiavone2[0000-0001-9219-6714],
Olena Trokhymets3[0000-0001-7587-7948], Dariusz Pawliszczy4[0000-0003-1328-7891],
Viktor Koval5[0000-0003-2562-4373], Ruslan Zavgorodniy3[0000-0002-6137-1310] and
Andrii Vorfolomeiev6[0000-0001-5789-5149]
1 National University “Zaporizhzhia Polytеhniс”,
64 Zhukovsky Str., Zaporizhzhia, 69063, Ukraine
2 Parthenope University of Naples, 38 Via Ammiraglio Ferdinando Acton, 80133 Napoli, Italy
3 Classic Private University, 70B Zhukovsky Str., Zaporizhzhia, 69602, Ukraine
4 Gromadka Commune Office, 9 General Wł. Sikorskiy Str., Gromadka, 59-706, Poland
5 Kyiv National University of Trade and Economics, 19 Kyoto Str., Kyiv, 02156, Ukraine
6 National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute”,
37 Peremohy Ave., Kyiv, 03056, Ukraine
nadezdash@ua.fm
Abstract. The authors of the article determined that a number of scientists were
involved in the development of a balanced system of indicators of the
development of the oil and gas sector. Though an urgent scientific problem that
needs further consideration is the development of a model of resource
efficiency diagnostics in the oil and gas sector of the economy of Ukraine,
taking into account the peculiarities of statistical monitoring. The scientific
novelty of the paper is: this study improved the model of diagnostics of
resource efficiency in oil and gas sector in the economy of Ukraine based on the
additive-multiplicative compression of the formed system, which, unlike the
existing ones, takes into account their variation while defining weighting
coefficients which show the experts’ system of preferences. It is reasonable to
use the proposed model at the further economic assessment of the consequences
of realization of resource-efficient strategy at enterprises of the oil and gas
sector of the economy of Ukraine.
Keywords: resource-efficient strategy, oil and gas complex, model of
assessment.
1 Introduction
The concept of resource efficiency in the modern and current practice of economic
activity analysis has been widespread, since the efficient consumption of economic
resources of any kind is associated, first of all, with intensive economic growth. That
is why a lot of scientists addressed the issues of ensuring a resource-efficient
economy as a necessary condition for sustainable development. According to 2018
___________________
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the oil and gas sector of Ukraine provided more than 40% of the economy’s needs for
energy resources. At the same time oil and gas sector accounted for 42.2% of total
consumption. Due to high dependency, the research of many domestic scientists is
devoted to various aspects of the operation of oil and gas extraction and processing
enterprises.
2 Actual scientific researches and issues analysis and the
research objective
Management of any economic system is always based on its current state, the
definition of which is a separate scientific task. The main tendencies of development
and value of innovative technologies in the oil and gas sector were studied by foreign
scientists, the following scientists are among them: Adi Karev [8], Konstantin N.
Milovidov [12] and others. Various scientists were involved in the methodological
bases of economic diagnostics, including the development of a balanced system of
indicators for the development of the oil and gas sector, including Inesa Khvostina
[9], T. F. Mantserova [10], Dani Rodrik [18], O. A. Tolpegina [26] and others.
This demonstrates that the scientific problem that needs to be solved in the
framework of this research is the development of a model of resource efficiency
diagnostics in the oil and gas sector of the economy of Ukraine, taking into account
the existing peculiarities of statistical monitoring by the State statistical authorities.
The methods of economic analysis for estimation of resource efficiency,
normalization method for bringing indicators to comparative appearance, method of
additive-multiplicative convolution (compression) for generalization of results in
different directions of evaluation, statistical methods of estimation of variation for
substantiation of values of weight coefficients in the model of diagnostics were used.
3 Tools and models for effective development of resource
efficiency in the oil and gas sector of Ukraine
In order to develop action for effective development of the resource-efficiency in the
oil and gas sector of Ukraine we use the following [6; 25]:
─ a system of indicators for assessing the resource efficiency of the oil and gas
sector. Taking into account peculiarities of the measurement of the studied object
by the State Statistics Service of Ukraine, the effective development of resource
efficiency in any field of activity requires consideration in the analysis of all types
of economic resources: raw materials, fixed assets, labor resources, total capital
(aggregate capital);
─ a model of the index of resource efficiency IRE based on the additive-
multiplicative convolution (compression). Convolution of indicators is carried out
by weighing their normalized o standard values on the basis of an agreed system of
expert preferences. In this case, it is believed that individual indicators with equal
279
level of influence on the group should have the same values of the root-mean-
square deviates;
─ intersectoral comparative analysis of resource intensity (resource capacity) and
structure of added value in the oil and gas sector. The need for this analysis is due
to the fact that to diagnose the current state and efficiency of the enterprises’
activity, it is appropriate to use the relevant base of comparison in economic
analysis;
─ scenario analysis of price equilibrium in oil and gas sector with the help of
intersectoral Leontiev’s model. It allows not only to perform appropriate
calculations, but also to find out how these changes affect resource efficiency,
including by changing the ratios of direct costs, intermediate consumption, added
value and gross profit;
─ assessment of the consequences of resource efficiency based on the IRE model.
This allows getting recommendations on areas and mechanisms to ensure resource
efficiency in the production and processing of oil and gas.
The peculiarities of the measurement of resource efficiency in oil and gas sector of
economy of Ukraine include:
1. The available volume of input statistics on the basis of the State Statistics Service
of Ukraine reports, with free access, significantly limits the possibilities for
comprehensive assessment of the resource efficiency by all types of economic
resources used in public production;
2. The change in methodology of organization of statistical observation during the
recent years, and, accordingly, reporting instruments and documentation do not
allow to carry out a retrospective analysis of resource efficiency indicators over a
long-term period. The geopolitical changes that occurred in 2014 in the South-East
of Ukraine resulted in temporary occupation of the Crimea and parts of Donetsk
and Luhansk Regions, have undoubtedly had a significant impact on the oil and gas
sector activity as well. That is why comparative analysis of the time periods cannot
provide with objective information on the dynamics of the target indicators due to
alterations in the special aggregate according to which they are calculated;
3. Some of the input data for 2016-2018 are not shown in the State Statistic Service
reports due to its confidential status. First of all, it concerns assets conditions,
volume of production and corresponding costs, fixed assets and a number of
employees, financial results of crude oil production, natural gas extraction and
production of refine products [6; 25].
4. Any diagnostics in economic analysis is possible if there is a respective base of
comparisons. In scoring models of diagnostics such a turning point are the classes
of indicators stability; in the models of multiplicative discriminant analysis – the
intervals of stability of integral index that determine the probability of the
bankruptcy of economic entities; in the express-analysis – industry standards and
cross-industry comparisons; in complex analysis – dynamics and plan value of
indicators, industry standards etc. As for the oil and gas sector of the economy, for
the diagnostics of its resource efficiency considering available data, we will use
280
cross-industry comparison and analysis of time periods applying methods of
statistic theory.
4 The model of resource efficiency in oil and gas sector of
economy of Ukraine diagnostics
Thus, taking into account the leading experience of analysis of economic activity [1;
14; 15; 21; 22; 24; 28] and mentioned above peculiarities of information support, a
model of diagnostics of resource efficiency of oil and gas sector of the economy of
Ukraine has a set of indicators as its basis, which consist of the following areas of
assessment: material resources, fixed assets, labor resources and aggregate capital.
Let’s consider them in more detail.
1. Material resources (MR1). Technological underdevelopment (backwardness),
associated with initial processing of resources, is always characterized by low
added value and high material (output) ratio. That is why effective use of material
resources is the priority in the development not only of oil and gas sector, but of
the economy of Ukraine. This group consists of the following indicators:
─ material productivity (К11) – characterizes the volume of output of the inquiry
period by 1 UAH of material costs. This indicator should be maximized and is
calculated by the formula:
К = , (1)
М
where VO1, MC1 – accordingly, volume of output and material costs in the inquiry
period.
─ net profit (income) for 1 UAH of material costs (К12), should be maximized.
According to its economic essence, this indicator is the analogue of cost
effectiveness (profitability), which allows to evaluate the efficiency of raw
materials and supplies in the process of profit generation in the enterprises of the
industry:
К = , (2)
М
where NP1 – net profit in the inquiry period.
─ coefficient of correlation of the growth rate of product output and material costs
(К13). Intensive economic development involves obtaining the final result not due
to the greater consumption of resource productivity. That is why this coefficient
should be К13 > 1.
М
К = : , (3)
М
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where VPO0, MC0 – accordingly, volume of product output and material costs in base
period.
─ the share of material costs in the cost of production (К14). According to 2018,
material costs for the economy in general were 74.3% from the cumulative costs
(total costs) for production output. Accordingly, depreciation accounted for 6.7%,
labor costs – 14.1%, benefits related deduction – 2.9%, and other costs – 2.0%
from cumulative costs (total costs).
As we can see, the high share of material costs – is a system problem for the entire
economy of Ukraine. It indicates not only the low level of social production, but also
hinders increase in wages and living standards of the population. That is why this
indicator should be minimized and calculated by the formula:
М
К = , (4)
where VCCP1 – volume of cumulative costs (total costs) for production in the inquiry
period.
The main production factors which are part of economic resources, are fixed
assets and labor resources (human capital). In most cases they determine the
production capacity of business entities and industries of the economy in general.
According to the results of 2018, the residual value of fixed assets in Ukraine was
3783.5 billion UAH, and the volume of production – 6207.7 billion UAH.
Accordingly, return on assets was 1.64 UAH. The number of employed population for
the same period was 16360.9 thousand persons. Thus, the annual labor productivity
was 379.4 thousand UAH per employee or 31.6 thousand UAH monthly.
Thus, complex diagnostics of the resource efficiency of oil and gas sector should
include comparative assessment in these areas.
2. Fixed assets (К2). This group includes the following indicators:
─ return on assets (К21) – characterizes the volume of production output for the
inquiry period at the rate of 1 UAH of residual value of fixed assets, and should be
maximized:
К = , (5)
where FA1 – the value of fixed assets in the inquiry period.
─ return on assets (К22) – equals the net profit on 1 UAH of residual value of fixed
assets, and it should be maximized:
К = , (6)
─ coefficient of correlation of the growth rate of product output and fixed assets costs
(К23). Intensive development implies an increase in aggregate production output
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not at the expense of additional production capacity attraction, but due to the return
on assets increase. That is why this coefficient should have the inequality К23 > 1.
К = : , (7)
where FA0 – residual value of fixed assets in base period.
3. Labor resources (К3). The indicators of resource efficiency of this group include:
─ labor productivity (К31) – characterizes the production output for the inquiry period
per one employee and should be maximized:
К = , (8)
where AAEP1 – average annual number of employed population in the inquiry period.
─ ROI of employees (К32) – equals net profit per one employee, and should be
maximized:
К = , (9)
─ share of labor costs in the cost of production (К33). According to statistics, in most
of Eurozone countries this indicator is 30-35%, which is more than 2 times ahead
of the similar level of the economy of Ukraine. That is why one of the reserves for
the growth of the average level of remuneration of labor is adjustment of the
production cost structure, and should be maximized К33:
К = , (10)
where RL1 – amount of remuneration of labor cost in the inquiry period.
Aggregate capital is generated from both equity and borrowed sources and is
allocated to fixed assets and current assets and is also an economic resource and a
focus of the researches interest in terms of its effective use.
4. Aggregate capital (total capital) (К4). In order to characterize the efficiency of
capital use, in the practice of financial analysis, along with profitability indicators,
indicators of turnover and duration of turnover are calculated. Let’s consider them
in more detail.
─ aggregate capital (total capital) turnover (К41) – shows how many the income of the
inquiry period exceeds the corresponding amount of the raised total capital The
increase in turnover shows an increase of its use:
К = , (11)
СК
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where CI1 – cumulative income of the inquiry period from all types of economic
activity; СК1 – average annual amount of capital of the inquiry period, taking into
account own and borrowed sources of income.
─ return on aggregate capital (total capital) (К42). Any borrowed capital, involved in
the activity of business entities, has its price. The condition of the expediency of its
use is always the excess of return on aggregate capital (total capital) over the
weighted average price of the loan. Otherwise, according to financial leverage
effect, economic activity will lead to a gradual decrease in equity.
К = , (12)
СК
where BP1 – balance (gross) profit of the inquiry period, excluding income tax.
─ duration of circulation of aggregate (total) capital (К43) – shows how many days it
will take for the income received during economic activity to be equal to the
amount of attracted aggregate (total) capital Speeding up the turnover means
reduction of the duration of circulation and vice versa. The formula for К43
calculation is the following:
К = , (13)
К
In the numerator, in this case, there is a number of days for the inquiry period.
Fixed assets form production capacity of the economic entities and do not directly
participate in the circulation. The efficiency of the use of aggregate (total) capital is
directly influenced by the turnover of the operating capital according to the formula:
К = , (14)
О
where OC1 – average annual amount of the operating capital in the inquiry period.
─ duration of operation capital turnover (К45) – shows how many days it will take for
the received income to be equal to the amount of operating capital and is calculated
by the formula:
О
К =К × , (15)
СК
Thus, we have formed a system of indicators for assessing the resource efficiency of
oil and gas sector of the economy of Ukraine taking into account available statistics.
Taking into account that all the indicators are relative indicators we will use cross-
industry comparisons for diagnostics of its condition.
By direct comparison we have an opportunity to define competitive advantages or
backlog of the oil and gas sector by every indicator. However, summarizing the
results of such multifactor evaluation requires the corresponding compression based
on the integrated index. For this reason, first of all, it is necessary to bring the value of
all indicator of resource efficiency to one base of comparison, which means to
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normalize them. The current practice of rationing involves setting up values to the
range [0, 1] using formula:
′
= , (16)
where K, K' – accordingly, input and normalized value of resource efficiency
indicator, which belong to і group; Kw, Kb – accordingly, the worst and the best value
of the indicator К, among other industries.
Since there are some indicators that should be maximized as well as minimized,
then to determine the worst indicators Kw and the best indicators Kb we should follow
the rule:
─ if К should be maximized, then К = ( ), = ( );
─ if К should be minimized, then К = ( ), = ( ).
The use of formula (16), observing the rule, allows to arrange the normalized values
of indicators in such a way that the best value of indicator corresponds with the
normalized and vice versa.
With its help, each of the indicators (1) - (15) is reduced to a comparative form.
The compression of normalized values to group and integral indexes is based on the
additive-multiplicative model:
=∑ ( × ), =∑ × (17)
for all і = 1…n, where ІРЕ – integral index of resource efficiency; Кі, аі –
accordingly, summary (consolidated) index of resource efficiency of і group and its
weighing coefficient; , аіj – accordingly, normalized j indicator of і group and its
weighing coefficient; n – a number of indicator groups; mi – a number of indicators of
і group.
There are certain limitations for weighing coefficients аі and аіj. First of all, their
values should range from 0 to 1; second of all, the sum of coefficients of a certain
group should equal 1.
Considering the mentioned above information, we have obtained a system of
equations using numerical method for diagnostics of resource efficiency in oil and gas
sector in the economy of Ukraine, taking into account equal influence of indicators,
which allowed presenting a more detailed equation (18):
IPE = 0.328K1 + 0.261K2 + 0.244K3 + 0.167K4,
K1 = 0.162K11 + 0.267K12 + 0.452K13 + 0.119K14,
K2 = 0.325K21 + 0.318K22 + 0.358K23,
K3 = 0.290K31 + 0.354K32 + 0.356K33,
K4 = 0.183K41 + 0.241K42 + 0.191K43 + 0.210K44 + 0.174K45. (18)
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5 Diagnosis of resource efficiency of the oil and gas sector
of Ukraine taking into account the opinions of experts
If, according to the experts’ preferences, individual indicators should influence
differently on the group or integral index of resource efficiency, this also should be
reflected in the proportions between root-mean-square deviants of such indicators
considering corrective weighing coefficients.
In this case, there is a need for quantitative coordination of expert judgments,
based on qualitative initial assessments. Therefore, the sequence of actions, taking
into account the theory of decision-making, should be the following [24]:
1. Each of the experts, based on their personal system of preferences, organizes the
sequence of evaluation of the components of the index of resource efficiency
according to their importance.
2. On the basis of individual rankings of the experts, with the help of the methods of
arithmetic mean ranks calculation of the generalized group ranking is carried out.
3. Verification of the consistency of the results of individual assessments of experts is
performed using the variance (dispersion) coefficient of concordance.
4. If at the previous stage the verification was successfully passed, on the basis of
application of procedure of pair comparison for each direction of an estimation of
an index of resource efficiency, the calculation of correction factors is carried out.
If the concordance coefficient indicates a high inconsistency of experts’ opinions,
the procedure for adjusting the parameters of equations (18) should be interrupted
to find out the reasons for such inconsistency.
5. Based on the calculation of the correcting coefficients, the parameters of equations
(18) are changed in order to consider the agreed and confirmed experts’ opinion on
the importance of areas for assessing the components of resource efficiency.
Methodical support of the planned sequence of actions should be considered in more
detail. In particular, in order to decide on the correction of the parameters of equations
(18), according the experts’ estimation, the following are used: the method of
arithmetic mean ranks, the variance (dispersion) coefficient of concordance and the
method of pairwise comparison [24; 27].
To apply the arithmetic mean method, each of the experts makes individual
rankings regarding the weight of the factors that affect the target coefficient.
Moreover, the most important factors have the lowest rank and vice versa. Let’s
indicate the corresponding set of matrixes as following:
[ ] , = 1, ; = 1, , (19)
where m – the number of factors by which the expert assessment is conducted; d – the
number of experts; ris – the ranks of the і factor, which was given by the s expert.
Next, for each factor, the sum of the ranks assigned by the experts is calculated
and divided by their number. Thus, the arithmetic mean simple is calculated. The
weighted average can be used if the experts have different levels of competence.
286
Generalized group ranking [ ] is obtained on the basis of the calculated arithmetic
means.
A measure of consistency of the experts’ estimations is the variance (dispersion)
coefficient of concordance W. Depending on the nature of the input data, its
calculation is carried out as following:
─ if individual expert assessments do not contain related ranks:
= ( )
× , (20)
=∑ (∑ − ) , (21)
= ∑ ∑ , (22)
─ if individual expert assessments contain related ranks:
= ( ) ∑
, (23)
=∑ ℎ −ℎ , (24)
where Ts – indicator of the related ranks of the s expert; Hs – the number of groups of
equal rank in the assessment of the s expert; hk – the number of ranks equal to each
other of the k group of related ranks of the s expert.
It’s necessary to mention, that the formula (20) is a partial or a finite case (23). If
the expert assessemnts do not contain related ranks, then we will have: Hs = 0; hk = 0;
Ts = 0. Accordingly, (23) is transformed into (20).
The variance (dispersion) coefficient of concordance changes within 0 ≤ ≤ 1.
If W=1, then all individual rankings of experts are similar to each other and vice
versa. The following scale is used to interpret its values: W [0, 0.3] – the level of
consistency of expert assessments is very weak; W [0.3, 0.5) – weak; W [0.5, 0.7)
– average (moderate, medium); W [0.7, 0.9) – high; W [0.9, 1] – very high.
High inconsistency of experts assessments, if W < 0.7, it may indicate a low level
of competence of individual members of the group, or a low awareness of this issue.
In this case, after additional study of the problem situation, it is necessary to repeat
the expert survey (questionary).
We use the method of pairwise comparison to define adjusted coefficients on the
basis of a generalized group ranking [ ] in the case if ≥ 0.7. The elements of
the matrix of pairwise comparisons s = are determined on the basis of the
rule:
= 2, ≻
= 1, ≈ , (25)
= 0, ≺
Then, the adjusted coefficients of the parameters of equations (25) are calculated by
the formula:
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∑
=∑ ∑
, (26)
Accordingly, the adjusted weighting coefficients of the integrated resource efficiency
index, taking into account the agreed opinion of the expert group, should satisfy the
ratio: (а К )⁄ а К = ⁄ , for all ≠ , or а К′ а К′ = ⁄ , for
all і = 1, …, n, ≠ . That is, the ratio between the standard deviations of each
weighted factor should be equal to the corresponding ratio between the adjusted
coefficients of the generalized ranking of experts.
Within the framework of this study, the expert group consisted of three experts
who expressed their opinion on the importance of the components of the resource
efficiency index of the oil and gas sector of Ukraine. The difficulty of objectively
assessing individual preferences for the efficient use of material resources, fixed
assets, labor resources and total capital was due to the crucial role of each component
in the formation of the target indicator. That is why, first of all, it was decided to
perform an expert assessment based on the existing advantages and disadvantages in
the resource efficiency of oil and gas sector enterprises, compared to other industries
and the economy of Ukraine in general [24]. And since the enterprises of the oil and
gas sector are part of both the extractive and processing industries, it is advisable to
make intersectoral comparisons with them [5; 13; 16; 17].
Taking into account the developed model (18), the results of diagnostics of
resource efficiency for 2015-2018 are presented in table 1.
Table 1. The results of diagnostics of the resource efficiency of oil and gas sector of the
economy of Ukraine according of data of 2015-2018 years.
Industries of the economy Years P1 P2 P3 P4 ІРЕ
2015 0.293 0.345 0.260 0.306 0.301
Total
2018 0.316 0.388 0.334 0.466 0.364
2015 0.281 0.360 0.233 0.540 0.333
Industry, including:
2018 0.297 0.435 0.327 0.661 0.401
Mining industry (primary sector) and quarrying, 2015 0.300 0.382 0.283 0.483 0.348
including: 2018 0.391 0.468 0.500 0.670 0.484
2015 0.372 0.406 0.266 0.666 0.404
Crude oil and natural gas production*, including:
2018 0.667 0.468 0.786 0.751 0.658
Crude oil production* 2015 0.276 0.252 0.252 0.500 0.301
Extraction of natural gas* 2015 0.448 0.548 0.320 0.785 0.499
Provision of ancillary services in the field of oil and 2015 0.306 0.252 0.345 0.577 0.347
natural gas* 2018 0.300 0.735 0.395 0.861 0.530
2015 0.272 0.387 0.213 0.609 0.344
Processing industry, including:
2018 0.285 0.542 0.300 0.748 0.433
Production of oil processing* 2015 0.255 0.503 0.223 0.733 0.392
Gas production, distribution of gaseous fuel through 2015 0.312 0.593 0.366 0.190 0.378
local pipelines* 2018 0.243 0.285 0.350 0.195 0.272
In the table 1 the asterisk symbol marks the types of economic activity which are a
part of oil and gas sector. As for the separate crude oil production and natural gas
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extraction, and refined products production in 2018 as well, the access to the relevant
statistics is limited due to their confidential character.
Special qualitative changes have taken place in the consumption of raw materials
and the use of labor resources. The result of such changes was that the oil and gas
sector began to outrun the extractive and all industries, as well as the average level of
Ukraine’s economy in terms of resource efficiency. Thus, on the one hand, we had a
positive trend of increasing resource efficiency [3; 4; 11; 29]. On the other hand, it
was achieved by a significant increase in product prices in recent years.
Regarding the production of oil and gas products, as well as the gas distribution
system, it can be seen that in terms of the use of fixed assets and capital there is a
significant lag behind other enterprises of the processing industry and the average
level in the economy [2; 19; 30].
Thus, the diagnosis of resource efficiency of the oil and gas sector indicated the
existing problems at refineries and significant improvements in oil and gas production
[7; 20; 23]. That is why, in the formation of individual preferences, experts proceeded
from the most important problems of resource efficiency in enterprises for the
production of refined products and gas, table 1.
The system of preferences or advantages of each of the experts had the form:
─ the first expert – К ≈ К ≻ К ≈ К , which means the equivalence of indicators
of efficiency of use of material resources and total capital due to their importance,
as refineries in the oil and gas sector have the biggest problems in these areas of
assessment. Therefore, these groups of indicators are more important than the
efficiency of use of fixed assets and labor resources, which are also equivalent to
each other;
─ the second expert – К ≻ К ≈ К ≈ К , that is, the problem of ensuring the
efficient use of material resources, taking into account the current situation,
outweighs other areas of assessment that are equivalent to each other;
─ the third expert – К ≻ К ≻ К ≈ К . In contrast to the first system of advantages
or preferences, the group of indicators К4 is inferior to К1 in terms of importance.
The results of the calculation of the generalized group ranking by the method of
arithmetic mean ranks, taking into account the individual preferences of experts, are
given in table 2. As we see, it completely coincides with the assessment of the third
expert.
Table 2. The results of the calculation of generalized group ranking by the method of
arithmetic mean ranks.
Individual ranking Arithmetic
Group of Generalized group
Expert Expert Expert mean
indicators ranking
І ІІ ІІІ ranks
К1 1.5 1 1 1.167 1
К2 3.5 3 3.5 3.333 3.5
К3 3.5 3 3.5 3.333 3.5
К4 1.5 3 2 2.167 2
289
In order to use the generalized group ranking in further calculations, we will assess
the consistency of experts’ opinions using the variance coefficient of concordance W.
Since their individual rankings had related ranks, the calculation of W was performed
by the formula (23):
× .
= ( ) ∑
= )
= 0.855
×( ×
Since W [0.7, 0.9), it can be stated that we have a high level of consistency of
expert assessments. Therefore, generalized ranking can be used to calculate unknown
parameters. To do this, the calculation of the adjusted coefficients gi was performed
by the method of pairwise comparisons, the results of which are shown in the table 3.
Table 3. The results of the calculation of the adjusted coefficients by the method of pairwise
comparisons.
Groups of indicators К1 К2 К3 К4 Sum The adjusted coefficients gi
К1 1 2 3 4 7 0.438
К2 0 1 1 0 2 0.125
К3 0 1 1 0 2 0.125
К4 0 2 2 1 5 0.313
Sum – – – – 16 –
As it was noticed before, the adjusted coefficients determine the ratio between the
standard deviations of each weighted factor of the IRE model as follows:
(а К )⁄ а К = ⁄ for all ≠ . Considering this factor, unknown parameters
of the equation were obtained by numerical methods:
ІРЕ = 0.555К + 0.126К + 0.118К + 0.201К (27)
In determining the weighing coefficients in the equation (27) the variation of each
indicator was: (а К ) = 0.054, (а К ) = 0.016, (а К ) = 0.016,
(а К ) = 0,039.
6 Measures to implement a resource-efficient strategy at
the enterprises of the oil and gas sector of Ukraine
In order to develop further measures ti implement a resource-efficiency strategy at the
enterprises of oil and gas sector of Ukraine let’s consider the components of the IRE
index in more detail. Table 4 illustrates the results of the relevant calculations
according to the year 2018 data and considering price adjustments in production and
processing.
Table 4. The results of the calculation of controlled indicators of resource efficiency of the oil
and gas sector of Ukraine
Gas production and
Indicators Oil and gas extraction
distribution
290
Price Price
2018 2018
adjustment adjustment
Resource efficiency index
0.673 0.502 0.251 0.422
ІRЕ
Material resources К1 0.667 0.500 0.243 0.368
К11 0.809 0.639 0.107 0.171
К12 1.000 0.680 0.430 0.624
К13 0.353 0.231 0.159 0.293
К14 0.922 0.928 0.329 0.345
Fixed assets К2 0.468 0.291 0.285 0.641
К21 0.177 0.125 0.617 0.767
К22 0.989 0.675 0.000 0.769
К23 0.270 0.101 0.239 0.414
Labour resources К3 0.786 0.627 0.350 0.482
К31 1.000 1.000 0.156 0.254
К32 1.000 0.551 0.173 0.436
К33 0.399 0.398 0.684 0.713
Aggregate capital К4 0.751 0.567 0.195 0.399
К41 0.358 0.204 0.133 0.251
К42 1.000 0.749 0.408 0.799
К43 0.750 0.543 0.000 0.057
К44 0.656 0.468 0.346 0.534
К45 0.932 0.843 0.000 0.216
As can be seen from table 4, in oil and gas production, after the scenario price
adjustment, almost all indicators have decreased. The exceptions were labor
productivity K31, as well as the share of material costs and wages in the cost of
production, K14 and K33, respectively. In this case, we can distinguish 3 main groups:
1. Indicators with a slight deterioration in their values, which remain at a competitive
level relative to other industries and the economy of Ukraine in general. This group
includes: К11, К14, К31, К33, К42 and К45. Their dynamics and condition do not raise
concerns about possible problems in the future. Therefore, special attention should
be paid to the indicators that are part of the following two groups when developing
measures to optimize the use of resources.
2. Indicators that have significantly lost their positions, however, their values still
remain high. These include: К12, К22, К32, К43 and К44.
The first three indicators in this list are related to the reduction of profits, in relation to
the volume of use of material and labor resources, as well as fixed assets. This is an
291
objective consequence of the necessary price adjustment, which revealed the real
situation with resource efficiency in oil and gas production. The recommendation, in
this case, may be to optimize the number of labor resources to increase productivity
К32, without reducing the cost of its payment.
The last two indicators characterize the slowdown in working capital due to
reduced revenues from sales. The specificity of the oil and gas sector is the high
capital intensity associated with the technological features of extraction, storage and
transportation. That is why the growth reserves of К43 and К44 are limited.
3. Indicators with a low level of resource efficiency, compared to other industries and
the economy in general: К13, К21, К23 and К41.
The coefficients К13 and К23 characterize the ratio of growth rates of output with the
consumption of material resources and the volume of fixed assets. After the
implementation of the proposed price adjustment, these indicators will return to the
level of the last reporting period, which is positive. Reserves for further growth of К13
are the introduction of new technologies, which requires significant capital investment
and, in the current economic stagnation, is impossible. At the same time, the increase
in К23 is directly related to the fullest possible utilization of available production
capacity. Therefore, the restoration of positive dynamics in this area of assessment is
possible in conditions of economic growth.
The low return on capital К21 and the turnover of total capital К41 are associated
with a high share of non-current assets (fixed assets) in their total volume. For
comparison, the average for the economy in 2018 it was 42.1%; in industry – 44.2%;
in the mining industry – 53.4%; in oil and gas production – 67.9%; oil – 49.1%; gas –
70.4%. For this reason, our object of study is significantly inferior to other industries
and the effective use of available current assets cannot correct the situation.
Therefore, the recommendations, in this case, are the decommissioning of obsolete
fixed assets and those that are not used for a long time, or with a low level of load, if
it is possible.
With regard to gas production and distribution companies, as a result of the
proposed price adjustment, all indicators of resource efficiency included in the IRE
model had a positive upward trend. The exception is a certain set of indicators, which
received a positive increase, but remained low: К11, К13, К31, К41, К43 and К45.
The high material consumption of processed products will not allow К11 and К13 to
take on competitive values in the future.
The real problem that has prospects for its solution is to increase labor productivity
К31 by reasonably optimizing the number of employees.
Problems with the turnover of working capital are caused by its high share, К43 and
К45. Thus, in gas production and distribution in 2018 it was 83.6%, and in oil refining
– 73.3%. An additional financial problem of these enterprises is the negative amount
of total capital due to retained losses of previous years.
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7 Conclusions
Analysis of the dynamics of oil and gas production shows that during 2015-2018
these enterprises significantly improved their indicators of resource efficiency on all
the areas of research, resulting in an integral index increase from 0.404 to 0.658,
which is positive. Significant qualitative shifts occurred in consumption of raw
materials and supplies and labor resources use. The result of such changes was that
the oil and gas sector outperformed both the primary (extraction) industry and the
entire industry, as well as the average level in the economy of Ukraine in terms of
resource efficiency. Thus, on the one hand, we had a positive trend in resource
efficiency increase. On the other hand, it was achieved by a significant increase in
product prices in recent years.
Thus, the obtained model of estimating the resource efficiency index takes into
account the agreed and confirmed opinion of experts on the impact of each of the
factors on the performance (effective) indicator. It is reasonable to use it in further
economic assessment of the consequences of the implementation of resource-efficient
strategy at the enterprises of the oil and gas sector of the economy of Ukraine.
Regarding the oil and gas refining, as well as gas distribution system we can
observe that according to the indicators of fixed assets and capital use there is a
significant lag from other enterprises of the processing industry and average level in
the economy in general.
Thus, the diagnostics of resource efficiency of oil and gas sector pointed to existing
problems faced by refinery enterprises and significant improvement in oil and gas
production field.
This study improved the model of diagnostics of resource efficiency in oil and gas
sector in the economy of Ukraine based on the additive-multiplicative compression of
the formed system, which, unlike the existing ones, takes into account their variation
while defining weighting coefficients which show the experts’ system of preferences.
Thus, the implementation of a resource-efficient strategy in the oil and gas sector
of Ukraine should include the following practical measures:
1. Creating conditions for the redistribution of value added between extractive and
processing enterprises of this sector in favor of the latter, through market pricing in
a demonopolized market.
2. Measures must be taken at oil and gas production enterprises to: optimize the
number of labor resources to increase labor productivity; the fullest use of existing
production capacity in the current economic stagnation and the lack of significant
capital investment in technological re-equipment; decommissioning of obsolete
fixed assets and those that are not used, or with a low level of load.
3. At oil and gas processing enterprises it is necessary to implement resource-saving
measures to: increase labor productivity by reasonably reducing the number of
employees; reduction of short-term receivables to increase capital turnover, etc.
293
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