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Model for evaluating the efficiency of Russian water utilities
Utilities Policy 62 (2020) 100986
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Model for evaluating the efficiency of Russian water utilities Аleksandr Tskhai a, b a b
Altai State Technical University, 46, Lenin Av., Barnaul, 656038, Russian Federation Institute for Water and Environmental Problems, Siberian Branch, Russian Academy of Science, Molodyozhnaya Str. 1, Barnaul, 656038, Russian Federation
A R T I C L E I N F O
A B S T R A C T
Keywords: Efficiency Water utilities
The objective of this study is to assess the efficiency of Russian water utilities based on a set of characteristic indicators. The novelty of the research is in the application of tools of the theory of economic “growth points” for analyzing water utility performance. The generalized development of a water utility is defined in terms of the efficiency of external and internal resources use. Conclusions on the development of water utilities in the six regional administrative centers of Siberia (Barnaul, Chita, Irkutsk, Novosibirsk, Omsk and Tomsk) in the 2013–2016 period were made.
1. Introduction The search for the most effective ways to develop water utilities is ongoing for both developed and developing countries (Eggimann, 2016). The lack of information on the financial and technological status of enterprises hampers analysis in this area. The available information is frequently incomplete and poorly structured for using traditional tools, such as production functions. Often, only the data on spent resources (inputs) and results (outputs) serve the evaluation of production processes. In such a situation, researchers can employ a Data Envelopment Analysis, hereinafter DEA (Cooper et al., 2007). A comparison of each producer with the virtual “best” is made through a linear programming approach. The measure of an entity’s efficiency is the proximity of the actual position relative to its reference one. In recent years, the DEA method has been used to analyze the performance of water utilities in Australia (Byrns et al., 2010); Brazil (Seroa da Motta and Moreira, 2006); Japan (Aida et al., 1998); Italy (Romano and Guerrini, 2011); the Netherlands, England, Wales, Portugal and Belgium (De Witte and Marques, 2010); Spain (Picazo-Tadeo, 2009); UK (Thanassoulis, 2000), the United States (Shih et al., 2006). In our case, there is not enough data to apply the DEA to the consideration of Russian water utilities. However, in this paper, it was possible to develop a method close to DEA with the use of an “inputsoutputs” model. Unlike DEA, resources (inputs) and results (outputs) are grouped into internal and external categories. We analyze how the conversion of resources available to the utility occurs when the results are classified in this way. In various countries, the set of accessible indicators for water utilities
differ markedly. Therefore, the results of DEA (sensitive to inputs and outputs selection) are not comparable for a different list of indicators. The scope and results of the analysis, to a large extent, depend on the diversity and completeness of the official data available to researchers. Thus, modernization of the reporting indicators for entities involved in supporting the quality of life of the population is currently a pressing problem (Cantele et al., 2018). A reporting form of enterprises proposed by Guerrini et al. (2016) is useful for the assessment of their economic efficiency and sustainability. The “points-of-growth” methodology used here links classical eco nomic theory with the technological development of industries. The concept of points or centers of economic growth began with Perroux (1954). This concept is used in the assessment of the effect that an economic entity makes on its socio-economic environment at different stages of its activity. It is found in scientific papers (Shvetsov, 2005; Tskhai and Ananchenko, 2008; Vertakova et al., 2016; etc.) as well as official documents (Presidential, 2017) of the Russian Federation. In line with governmental policy (Resolution, 2013), the Russian water utilities should publicly present the essential information of their annual accounting and other production and financial reports. These data allow us to follow some concepts of the theory of economic “growth points” when analyzing the production activity of water utilities. It ac counts for peculiarities of the utility’s development from its start, when most resources are spent on solving its internal problems. As they mature, water may utilities begin to influence their socio-economic environment significantly, and the share of resources spent on external results begins to grow. In the financial analysis, a number of commonly used indicators (indices) are used to characterize economic entities such as current
E-mail address: [email protected]. https://doi.org/10.1016/j.jup.2019.100986 Received 7 March 2019; Received in revised form 4 November 2019; Accepted 5 November 2019 Available online 25 November 2019 0957-1787/© 2019 Elsevier Ltd. All rights reserved.
А. Tskhai
Utilities Policy 62 (2020) 100986
liquidity, financial independence, etc © <2019> this version of the manuscript is available under CC-BY-NC-ND 4.0 license http://cre ativecommons.org/licenses/by-nc-nd/4.0/ (Methodological Recom mendations, 2002). To describe the aspects of water utility activity, the paper provides a definition of some performance indicators and for mulates the procedure for calculating their numerical values. The paper evaluates the relationship between resource efficiency and considered results
Table 1 Model for evaluating water utility efficiency. External resources
Internal resources
2. Materials and methods Efficiency characteristics are formulated by assuming that both re sources and performance are divided into internal and external cate gories, as proposed by Lobach (2000). Considering water utility efficiency and results, we also distinguish between internal (organiza tional) and external (environmental) results. Internal results include net profits and salaries at the disposal of the utility. External results, such as the volume of water supply and wastewater treatment, are of interest to the city in the utility’s environment. Additionally, the question of whether the “organization” or the “environment” impacts the value of the considered results is of great importance. To identify the source of the “growth point”, we also distinguish between the internal and external costs and resources used by the utility. All of the organization’s resources come into play and give grounds to consider its effectiveness in converting resources into results. The inclination of water utilities to increase revenue through prices has no limit. The amount of revenue raised for the organization largely depends on the ability of the environment (the city) to pay for water services. In this sense, “revenue” is considered an “external” resource. The specific list of variables (internal and external resources and results) is limited because of the established Russian standards of in formation disclosure in the field of water supply and wastewater treat ment (Resolution, 2013). However, estimates of our proposed indicators of efficiency can be obtained from the standard data on the enterprises. In this paper, the simplest case of two external and internal results, as well as two external and two internal resources, is considered: External results:
External results
Internal results
K1 Local indicator of external efficiency for external resources usage (a multiplicity indicator of efficiency) K2 Local indicator of external efficiency for the usage of internal resources (synergy indicator of efficiency)
K3 Local indicator of internal efficiency for the usage of external resources (adaptability indicator of efficiency) K4 Local indicator of internal efficiency for the usage of internal resources (intensity indicator of efficiency)
K1 is the average sum of proportions for each type of external results to each type of external resources for the final (τ) and initial (τ-1) moment of the studied period. This order of calculation of the multiplicity indi cator K1 is written in a mathematical form as: 2 P 2 P
K1 ðτÞ ¼
i¼1 j¼1
τ=
βij τ
1
τ=
; where βij τ
4
1
¼
βτij βτij
1
; βτij ¼
Ai ðτÞ Bj
(1)
Here, β is the local performance indicator (element of the matrix); i the number of the result indicator; j - the number of the resource indi cator; τ - the year. The same calculation procedure is applied to other local performance indicators with the corresponding indices i and j 2 P 4 P
K2 ðτÞ ¼
i¼1 j¼3
4
τ=
βij τ
4 P 2 P
1
; K3 ðτÞ ¼
i¼3 j¼1
4
τ=
βij τ
4 P 4 P
1
; K4 ðτÞ ¼
i¼3 j¼3
4
τ=
βij τ
1
(2)
As summarized in Table 2, the multiplicity indicator K1 represents the ratio of growth rates for external results to growth rates in external resources. As a demonstration, supposing that K1 > 1, the rise of water utilities’ role in the environment is more intense than the growth of their external resources, which indicates multiplicity. If K2 > 1, then the extension of water utility influence on the envi ronment is greater than the growth of internal results. The use of internal resources occurs primarily for the environment indicates synergy. When K3 > 1, the increase in the utility’s growth due to the use of external resources is higher than the change in impact on the environ ment. Growth that happens mainly for the organization itself indicates adaptability. When K4 > 1, growth of the water utility takes place essentially at the expense of internal resources, which indicates intensity. External and internal resources interact with each other; if water utility services are available to consumers, its efficiency can be defined as the measure to turn resources into results. Some of the results, such as net profit, involve putting additional resources at the disposal of the water utility. Others are directed to improving the condition of the external environment (volumes of water supply and treatment), which may, in turn, be relevant to the condition of the utility. The integrated priority index P is calculated as the arithmetic mean of four summary performance indicators Ki. The maximum potential of the utility as the “point of growth” corresponds to the maximum value of P. However, a comprehensive analysis of the constituents’ contribution is required for the correct interpretation of P. Such concepts as positive and negative growth are defining features. Negative trends in water utility development can significantly reduce investment efficiency as a result of altered incentives and preferences. In contrast, the investment of funds allows achievement of the desired performance level of services when the utility is ready to most effec tively utilize them. The general question arising is how to distinguish water utilities by important features, such as the “prospect” for their growth. A method of “points of growth” monitoring for water utilities of the Russian cities
A1 – the volume of municipal wastewater (km3) A2 – the volume of drinking water (km3) Internal results: A3 – the net profit (thousand dollars) A4 – the payment of production and administrative personnel (thousand dollars) External resources: B1 - the revenue (thousand dollars) B2 – the loans and external funding (thousand dollars) Internal resources: B3 – the fixed assets (thousand dollars) B4 – the own investment (thousand dollars) Our model for determining the efficiency of water utilities is sum marized in Table 1 and elaborated in Fig. 1. For example, we define K1 is a “multiplicity” indicator that characterizes the impact of changes in external resources on external results during the period under review. The indicators of “adaptability” (K2), “synergy” (K3) and “intensity” (K4) for water utilities are defined similarly. This typology was adapted from the investigations by Lobach (2000) (Shvetsov, 2005), for regional development. We use the simplest version of the identification of K1. The value of 2
А. Tskhai
Utilities Policy 62 (2020) 100986
Fig. 1. Model for evaluating water utility efficiency.
in terms of growth and development (column 1 in Table 3), makes it possible to find analogs for each selected type, which allows us to further analyze and predict the utility’s life cycle. The following assumptions are used as the basis for the classification. A positive point of growth (development) is when all four indicators are more than 1, that is:
Table 2 Specification of the efficiency indicators. Indicator
Specification of the efficiency indicator
K1 – multiplicity indicator of efficiency K2 – synergy indicator of efficiency
Average ratio of growth rate for external results to external resources change. Average ratio of growth rate for external results to internal resources change. If this indicator >1, the own resources for the external environment is used. Average ratio of growth rate for internal results to external resources change. If this indicator >1, external resources are used mainly for the utility’s own growth. Average ratio of growth rate of internal results to internal resources change. If this indicator >1, intensification of the own growth is mainly due to its own resources.
K3 – adaptability indicator of efficiency K4 – intensity indicator of efficiency
Ki ji¼1;2;3;4 > 1
(3)
Four types of positive points of growth (development) are identified depending on the indicator Ki with its maximum value. The first type is characterized by: K4 ¼ max Ki ji¼1;2;3;4
(4)
In this case, internal growth is accounted for by the expense of the internal resources of the water utility. This is typical for firm innovation and restructuring in the particular region and the country as a whole. We introduce the definition of the coefficient L|k¼1, that is the firsttype “point” identification: � Ljk¼1 ¼ 3 K4 K1 K2 K3 > 0
was developed and applied in this work. Initially, the utility organiza tion enters a phase of growth related to the creation of material and technical base, as well as the provision of resources and the regulation of technological procedures. The production processes are implemented more effectively in accordance with current tasks. With an increase in output, the utility enters a phase of development, when the impact of its activity on the environment becomes noticeable. In the proposed approach, the predominance of the growth rate of internal results over external ones is evidence of the growth phase and the predominance of growth rates of external results over internal ones distinguishes the development phase. The classification of water utilities
Due to the relationship of (3) and (4), a negative coefficient L|k¼1 indicates that some of the basic assumptions of the first type are violated. We next assume that the closer the “point” trajectory to the first type is, the higher the calculated value of L|k¼1. Similarly, other types of “points of growth (development)” are characterized, and other co efficients L|k, (levels of “point” identification) for the rest seven types are introduced. 3
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Utilities Policy 62 (2020) 100986
Table 3 Classification of enterprises by types of growth (development). Type of points
Multiplicity indicator K1
Synergy indicator K2
Adaptability indicator K3
Intensity indicator K4
Level of “point” identification L
1
growth point with internal source
K3 < K4, K3 > 1 K3 > 1
3 K4– K1– K2– K3
growth point with external source development point with internal source
4
development point with external source
5
negative growth point with internal source
K4 < K3, K4 > 1 K4 < K2, K4 > 1 K4 < K1, K4 > 1 K4 < 1
3 K3– K1– K2– K4
3
K2 < K4, K2 > 1 K2 < K3, K2 > 1 K2 > 1
K4 > 1
2
K1 < K4, K1 > 1 K1 < K3, K1 > 1 K1 < K2, K1 > 1 K1 > 1
6
negative growth point with external source
K1 þ K2 þ K4 -3 K3
7
negative development point with internal source negative development point with external source
K4 > K3, K4 < 1 K2 < K4, K4 < 1 K4 > K1, K4 < 1
8
K1 > K4, K1 < 1 K1 > K3, K1 < 1 K1 > K2, K1 < 1 K1 < 1
K3 < K2, K3 > 1 K3 < K1, K3 > 1 K3 > K4, K3 < 1 K3 < 1
K2 < K1, K2 > 1 K2 > K4, K2 < 1 K2 > K3, K2 < 1 K2 < 1
K2 < K3, K3 < 1 K3 > K1, K3 < 1
K2 > K1, K2 < 1
The second type is characterized by:
3 K2– K3- Kι- K1 3 K1– K2– K3– K4 K1 þ K2 þ K3 -3 K4
K1 þ K2 þ K3 - 3 K2 K2 þ K3 þ K4 - 3 K1
K3 ¼ min Ki ji¼1;2;3;4
K3 ¼ max Ki ji¼1;2;3;4
The seventh type is:
Here, internal growth happens typically at the expense of external resources, that is, when the utility spends loans (external investment) on wage payments. The third type is characterized by:
K2 ¼ min Ki ji¼1;2;3;4 when the determining process is the internal degradation of the negative “point”. Inefficient economic actors tend to end their life cycle along this path. Inefficient economic actors will have to move towards some of the strategic choices, including restructuring. The eighth type is the most dangerous. The negative “point” absorbs external resources, which has a negative effect on the socio-economic environment. The aggravation of environmental development is accel erated. This “point” is a type of multiplier of economic degradation:
K2 ¼ max Ki ji¼1;2;3;4 The acceleration of the utility’s organizational development and structural transformation in the environment arise mainly from internal resources available. The Japanese technopolises, which were basically established at the expense of local government resources, are a good case in point. At the same time, the development impetus from the introduction of new industries, technologies, and technopolises had a significant influence on the development of industrially backward areas in Japan (Maruyama, 1985). The fourth type is characterized by:
K1 ¼ min Ki ji¼1;2;3;4 Parametric features of “points of growth (development)” with the formula for assessing the level of identification (L) by comparing the coefficients are summarized in Table 3. A combination of several types of points (excluding the “pure” one) is characteristic of each particular utility. Therefore, the utility performance is analyzed in terms of the proximity to a particular type. The volumes of supply of drinking water are many times higher than the volumes of supply of technical water (such as for heating systems, etc.). So far, this is the reality for the six water utilities that had been studied in this work.
K1 ¼ max Ki ji¼1;2;3;4 The external resources are used to accelerate their own growth and influence on the surrounding area. The Chinese special economic zones and techno-industrial parks established with financial and administra tive assistance from the state are a vivid example (Peebles, 1986). This type of “points of development” is the most important for an economy in transition. The negative type of growth (development) is found when all four indicators are as follows:
3. Analysis and results Water utilities in six regional administrative centers of Siberia, with comparable population size and conditions for enterprise operation, became the focus of our study. At the first stage of the analysis, the integrated priority indicator P was calculated for water utilities in the cities of Barnaul (“Barnaul Vodokanal”, 2019), Chita (“Vodokanal-Chita”, 2019), Irkutsk (“Vodo kanal”, 2019), Novosibirsk (“Gorvodokanal”, 2019), Omsk (“OmskVo dokanal”, 2019) and Tomsk (“TomskVodokanal”, 2019) (see Table 4). The calculations based on the given primary data showed that during the period from January 1, 2013, to December 31, 2014, the water utility of Irkutsk was the fastest developing utility, being far ahead of the rest (with a priority index of 13.149). It can be assumed that this was a period of profound change as compared to other utilities in terms of the financial and economic policies of the utility. The activity of the rest water utilities was characterized using the indicator P: Tomsk (1.547), Chita (1.432), Barnaul and Novosibirsk (1.01), and “OmskVodokanal” (0.775). In the second period (from January 1, 2015, to December 31, 2016),
Ki ji¼1;2;3;4 < 1 Four options of negative “points of growth (development)” are identified due to the indicator Ki with the lowest value. The fifth type is characterized by: K4 ¼ min Ki ji¼1;2;3;4 It includes negative “points” with negative growth. Such a “point” inefficiently uses its own resources, thus being unprofitable. The in crease in unemployment in fast-growing cities is a case in point. External resources can be used in negative growth processes. The state cannot leave its citizens without water services of the natural monopoly and is forced to allocate resources to the unprofitable water utility. Such policies are potentially the highest priority because of the possible rationale to prevent social disaster. Their negative economic consequences should be properly resolved as appropriate. This sixth type of negative “points” is characterized by:
4
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Utilities Policy 62 (2020) 100986
Irkutsk water utility had the strongest impact on its socio-economic environment over the four years (average indicator - 7.756). Next, in descending order, are the enterprises of Tomsk (1.244), Chita (1.048), Novosibirsk (0.914), Omsk (0.890) and Barnaul (0.750). The parametric analysis was performed for water utilities according to the classification of types (see Table 6). For all types, the higher value corresponds to the greater proximity. For example, in 2013–2014, the proximity of the Barnaul utility to the 1st type of the “point of growth” with internal resources was 0.151; to the 2nd type with external re sources was 0.663; and to the 3rd type with internal resources was 0.613. In this analysis, the negative value of the indicator does not mean enterprise degradation; it simply means that the indicator cannot belong to the considered type. Thus, the value of L|k¼1 equal to 0.151 for the Barnaul water utility shows that in the first period this utility did not belong to the type of the “point of growth” with an internal source, and it was not the negative “point of growth” with an internal source. The largest value in the column (the Barnaul enterprise, 2013–2014) in the 2nd line (0.663) means the greater utility’s correspondence to the 2nd type (“point of growth” with an external source) than that for other seven types. The results of the parametric analysis for all enterprises are pre sented in Table 6. The bottom line indicates the type of the “point of growth (development)” for the utility, fitted best of all. The bottom line in Table 6 shows that in 2013–2016 all water utilities referred to positive types of “points of growth” (N� 1, 2, 3, 4). In both periods under study, the water utility in Barnaul represented the “point of growth” with external sources, which is indicative of the utility’s potential to affect the socio-economic environment. The Chita water utility in both studied periods corresponded to the “point of growth”. Unlike the Barnaul utility, its progress was made due to internal resources. To hold this position, the search for external sources was of particular importance. During the periods under consideration, qualitative changes were observed in Irkutsk and Omsk. Both enterprises lowered their level of development: they dropped from the “point of development” (the first period) to the “point of growth” with external sources (the second period). This option would be acceptable for water utilities. Municipal authorities may be interested in more intensive usage of internal re sources and early return to a higher level of providing public services in the cities. The water utility of Novosibirsk was the “point of growth” during both studied periods. It should be noted that in 2013–2016, the utility was reoriented from the internal to external resources. The Tomsk water utility experienced transformation as the “point of growth”. In contrast to Novosibirsk, the utility was reoriented from external to internal sources. Parametric proximity to the “point of development” with an external source allows us to identify the most promising for investment, namely, the Omsk utility in the first period. At the same time, “points of growth” and “points of development” with internal sources are the most effective when their own resources are used.
Table 4 Dynamics of priority indicator values for water utilities. N�
Water utility (city)
Priority indicator 2015–2016
Priority indicator 2013–2014
1 2 3 4 5 6
Barnaul Chita Irkutsk Novosibirsk Omsk Tomsk
0.704 1.569 0.944 1.274 0.898 1.279
1.010 1.432 13.149 1.010 0.775 1.547
the enterprises intensified their activities somewhat as compared to the first period (2013–2014): Chita (from 1.432 to 1.569), Novosibirsk (from 1.01 to 1.274), and Omsk (from 0.775 to 0.898). Only in Novo sibirsk and Chita was the priority indicator P > 1 in both periods, sug gesting that the rest four enterprises have the potential to improve their performance. After a “breakthrough” first period in 2015–2016, the water utility of Irkutsk had the priority indicator P < 1. Thus, an important task of the utility was to maintain sustainable performance. The analysis suggests the potential for management improvement at almost all water utilities. The multiplicity and synergy indicators, which characterize the transformation of internal and external resources into external results, deserve thorough consideration (see Table 5). During the first period under review (2013–2014), water utilities of Tomsk (1.462), Irkutsk (1.125), Omsk (1.083) and Barnaul (1.01) showed the highest values of the first indicator, that is, K1 < 1, compared to the enterprises of Chita (0.938) and Novosibirsk (0.878). In the second period (2015–2016), only Novosibirsk and Chita enterprises managed to make good progress (1.074 and 1.069, respectively). The water utilities of Barnaul, Irkutsk, Omsk, and Tomsk demon strated reduced multiplicity indicators during the second period (0.651, 0.899 and 0.919, respectively), which is evidence of decreased effi ciency of water supply and wastewater treatment. This might be explained by a more complex macroeconomic situation in the second period, during which water utilities of Chita and Omsk experienced in creases in the synergy indicator (from 1.017 to 1.167 and from 0.735 to 0.811, respectively), which implies a high possibility of the enterprises to achieve external results at the expense of their internal resources. By the synergy indicator, the Irkutsk enterprise was in the lead during the first period (28.289). By the second period, in the new macroeconomic situation, its internal resources drastically decreased to an unsatisfactory level of 0.716. Of the rest enterprises, only Chita (1.167) and Tomsk (1.224) showed satisfactory external results at the expense of internal resources, i.e. K2 > 1. The dynamics of the sum of the first two indicators suggest that the Table 5 Dynamics of efficiency indicator values for water utilities: (a) Multiplicity in dicator values for water utilities: (b) Synergy indicator values for water utilities. N�
Water utility (city)
Multiplicity indicator (2015–2016)
Multiplicity indicator (2013–2014)
1 2 3 4 5 6
Barnaul Chita Irkutsk Novosibirsk Omsk Tomsk
0.651 1.069 0.892 1.244 0.929 0.919
1.010 0.938 1.125 0.878 1.083 1.462
N�
Water utility (city)
Synergy indicator 2015–2016
Synergy indicator 2013–2014
1 2 3 4 5 6
Barnaul Chita Irkutsk Novosibirsk Omsk Tomsk
0.481 1.167 0.716 0.564 0.811 1.224
0.857 1.017 28.289 0.968 0.735 1.370
4. Conclusion An approach to assessing the efficiency of Russian water utilities based on the application of the theory of “growth points” is proposed. It combines a set of quantitative indicators related to the sustainability of water utilities and the assessment of the relationship between resources and results. The methodology was used to study the development of six water enterprises in Siberian regional administrative centers (similar in population and conditions) providing water supply and wastewater treatment services. The research revealed very different patterns in the use of external and internal resources. Municipal authorities, often granting tax preferences to utility monopolies, are interested in inten sive use of the utility’s internal resources. On the other hand, the posi tive development of a utility cannot always be realized only through 5
А. Tskhai
Utilities Policy 62 (2020) 100986
Table 6 Parametric characteristics of the proximity of water utilities to types of «growth points». N� п/п
1 2 3 4 5 6 7 8 9
Types of “growth point”
“Growth point” with internal source “Growth point” with external source “Development point” with internal source “Development point ” from external source Negative “growth point” with internal source Negative “growth point” with external source Negative “development point” with internal source Negative “development point” with external source Number of type for “growth point”
Barnaul Vodokanal
Vodokanal-Chita
Vodokanal of Irkutsk
Novosibirsk Gorvodokanal
OmskVodokanal
TomskVodokanal
I 2013–2014
II 2015–2016
I
II
I
II
I
I
I
II
0.044
2.123
2.160
36.588
0.087
0.562
0.304
1.677
1.056
1.514
1.449
1.033
0.133
0.051 0.663 0.613
0.890
1.661
1.608
0.000
0.209
1.976
2.001
0.051
0.044
2.123
2.160
1.056
1.514
1.449
0.663 0.613
0.890
1.661
1.608
0.000
0.209
1.976
2.001
2
2
1
1
49.051 60.560
0.991
0.167
2.839
48.098
0.209
0.528
0.121
36.588
0.087
0.562
1.033
0.133
60.560
0.991 3.951
0.911
0.167
2.839
48.098
0.209
0.528
0.121
3
2
1
2
II 1.027
3.951
0.911
49.051
internal resources. The proposed methodology provides the basis for an objective assessment. It can be expanded by considering additional indicators relevant to the sustainable development of water utilities (for instance, characteristics of the region, where water utilities are located, and management structures). In particular, the developed approach can be used with regard to Federal projects for the development of water management strategies in the regions. In addition to the methodological contribution, the application of the approach to the Russian water utilities offers two other notable results related to policy. First, it is a tool for choosing the moment when external investments or tax preferences for the development of the utility will be most effective for the city. When making an investment decision, it is necessary to take into account the readiness of the utility to make use of these resources, which depends on its development status. Second, it is a tool for the evaluation of the Russian water utilities in terms of management. However, in practice, accounting for all potential factors, including those beyond this analysis, is required. For example, if a water utility is located in an area with a poor macroeconomic situa tion, this factor will be manifest in performance. It should be borne in mind that the proposed approach can be combined with other meth odologies. Further investigations will enable the assessment of Russian utilities according to evolving international standards in water man agement. The obtained results could find application in the development of a water use strategy in Siberia. This research did not receive any specific grant from funding agencies in the public, commercial or not-for-profit sectors.
II
0.043
0.138 0.364
0.162
0.740
0.348
0.017
0.706
0.219
1.232
0.123
0.338
1.440
1.027
0.138
0.304
1.677
0.043 0.162
0.364 0.348
1.232 4
0.123 2
0.740
0.017
0.706
0.219
0.338
1.440
2
1
Cantele, S., Tsalis, T., Nikolaou, I., 2018. A new framework for assessing the sustainability reporting disclosure of water utilities. Sustainability 10, 433–444. https://doi.org/10.3390/su10020433. Cooper, W., Seiford, L., Tone, K., 2007. Data Envelopment Analysis - A Comprehensive Text with Models, Applications, References and DEA-Solver Software, second ed. Springer, US. https://doi.org/10.1007/978-0-387-45283-8. De Witte, K., Marques, R.C., 2010. Designing performance incentives, an international benchmark study in the water sector. Cent. Eur. J. Oper. Res. 18 (2), 189–220. Eggimann, S., 2016. The Optimal Degree of Centralisation for Wastewater Infrastructures. A Model-Based Geospatial Economic Analysis. University of Zurich, Switzerland. Diss. ETH 23915. The “Gorvodokanal” of the Novosibirsk Municipal Unitary Utility, 2019. gorvodokanal. com/info/?item¼32. (Accessed 25 May 2019). Guerrini, A., Romano, G., Ferretti, S., Fibbi, D., Daddi, D., 2016. A performance measurement tool leading wastewater treatment plants toward economic efficiency and sustainability. Sustainability 8. https://doi.org/10.3390/su8121250, 1250-163. Lobatch, A.I., 2000. Growth points as an instrument of management of the exportoriented economy. Diss. Minsk: Belarus State Economic University, p. 185. Republic of Belarus (in Russian). Maruyama, M., 1985. Report on a new technological community: the making of a technopolis in an international context. Technol. Forecast. Soc. Chang. 27 (1), 75–98. Methodological recommendations for the analysis of financial and economic activities for organizations, 2002. The Federal State Statistics Service. Moscow, Russian Federation (in Russian). The “OmskVodokanal” Joint Stock Utility, 2019. http://www.e-disclosure.ru/po rtal/files.aspx?id¼21901&type¼3. (Accessed 25 May 2019). Peebles, G., 1986. In: Jao, Y.C., Leung, C.K. (Eds.), China’s Special Economic Zones: Policies, Problems, and Prospects. Oxford University Press, Hong Kong, p. 246. Perroux, F., 1954. Europe without Shores. Grenoble university publishing house, Grenoble (in French). Picazo-Tadeo, A.J., Gonzalez-Gomez, F., Saez-Fernandez, F.J., 2009. Accounting for operating environments in measuring water utilities’ managerial efficiency. Serv. Ind. J. 29 (6), 761–773. https://doi.org/10.1080/02642060802190300. Presidential decree, 2017. Presidential decree No. 13 of the 16th January On Approval of the State Policy of Regional Development of the Russian Federation for the Period until 2025. Moscow, Russian Federation (in Russian). Resolution of the Russian Federation Government, 2013. Resolution of the Russian Federation Government No. 6 of the 17th January About Standards of Information Disclosure in the Field of Water Supply and Wastewater Treatment. Moscow, Russian Federation (in Russian). Romano, G., Guerrini, A., 2011. Measuring and comparing the efficiency of water utility enterprises: a data envelopment analysis approach. Util. Policy 19 (3), 202–209. https://doi.org/10.1016/j.jup.2011.05.005. ISSN 0957-1787. Seroa da Motta, R., Moreira, A., 2006. Efficiency and regulation in the sanitation sector in Brasil. Util. Policy 14, 185–195. Shih, J., Harrington, W., Pizer, W., Gillington, K., 2006. Economies of scale in community water systems. J. Am. Water Work. Assoc. 98, 100–108. Shvetsov, I.V., 2005. Formation of Territorial “growth Points” as a Factor of the Regional Development. Diss. Moscow: RASS, Russian Federation (in Russian). Thanassoulis, E., 2000. The use of data envelopment analysis: in the regulation of UK water utilities: water distribution. Eur. J. Oper. Res. 126 (2), 436–453. https://doi. org/10.1016/S0377-2217(99)00303-3.
Declaration of competing interest None. References Aida, K., Cooper, W.W., Pastor, J.T., Sueyoshi, T., 1998. Evaluating water supply services in Japan with Ram: a range-adjusted measure of inefficiency. OMEGA-Int. J. Manag. Sci. 26 (2), 207–232. The “Barnaul Vodokanal” Limited Liability Utility, 2019. barnaulvodokanal.ru/. (Accessed 25 May 2019). Byrnes, P., Crase, L., Dollery, B., Villano, R., 2010. The relative economic efficiency of urban water utilities in regional New South Wales and Victoria. Resour. Energy Econ. 32 (3), 439–455.
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The “TomskVodokanal” Limited Liability Utility, 2019. www.vodokanal.tomsk.ru/. (Accessed 25 May 2019). Tskhai, A.A., Ananchenko, Yu.S., 2008. A model-based approach to the assessment of the development character for innovation cluster and its components. In: Actual Problems of Economics and Law at the Present Stage of Development of the Russia: International Conf. Barnaul, Russian Federation, pp. 94–97 (in Russian).
Vertakova, Yu., Grechenyuk, O., Grechenyuk, A., 2016. Identification of clustered points of growth by analyzing the innovation development of industry. Procedia Econ. Financ. 39, 147–155. The “Vodokanal” of Irkutsk Municipal Unitary Utility, 2019. www.irkvkx.ru/. (Accessed 25 May 2019). The “Vodokanal-Chita” Joint Stock Utility, 2019. vodokanalchita.ru/. (Accessed 25 May 2019).
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Contents lists available at ScienceDirect
Utilities Policy journal homepage: http://www.elsevier.com/locate/jup
Model for evaluating the efficiency of Russian water utilities Аleksandr Tskhai a, b a b
Altai State Technical University, 46, Lenin Av., Barnaul, 656038, Russian Federation Institute for Water and Environmental Problems, Siberian Branch, Russian Academy of Science, Molodyozhnaya Str. 1, Barnaul, 656038, Russian Federation
A R T I C L E I N F O
A B S T R A C T
Keywords: Efficiency Water utilities
The objective of this study is to assess the efficiency of Russian water utilities based on a set of characteristic indicators. The novelty of the research is in the application of tools of the theory of economic “growth points” for analyzing water utility performance. The generalized development of a water utility is defined in terms of the efficiency of external and internal resources use. Conclusions on the development of water utilities in the six regional administrative centers of Siberia (Barnaul, Chita, Irkutsk, Novosibirsk, Omsk and Tomsk) in the 2013–2016 period were made.
1. Introduction The search for the most effective ways to develop water utilities is ongoing for both developed and developing countries (Eggimann, 2016). The lack of information on the financial and technological status of enterprises hampers analysis in this area. The available information is frequently incomplete and poorly structured for using traditional tools, such as production functions. Often, only the data on spent resources (inputs) and results (outputs) serve the evaluation of production processes. In such a situation, researchers can employ a Data Envelopment Analysis, hereinafter DEA (Cooper et al., 2007). A comparison of each producer with the virtual “best” is made through a linear programming approach. The measure of an entity’s efficiency is the proximity of the actual position relative to its reference one. In recent years, the DEA method has been used to analyze the performance of water utilities in Australia (Byrns et al., 2010); Brazil (Seroa da Motta and Moreira, 2006); Japan (Aida et al., 1998); Italy (Romano and Guerrini, 2011); the Netherlands, England, Wales, Portugal and Belgium (De Witte and Marques, 2010); Spain (Picazo-Tadeo, 2009); UK (Thanassoulis, 2000), the United States (Shih et al., 2006). In our case, there is not enough data to apply the DEA to the consideration of Russian water utilities. However, in this paper, it was possible to develop a method close to DEA with the use of an “inputsoutputs” model. Unlike DEA, resources (inputs) and results (outputs) are grouped into internal and external categories. We analyze how the conversion of resources available to the utility occurs when the results are classified in this way. In various countries, the set of accessible indicators for water utilities
differ markedly. Therefore, the results of DEA (sensitive to inputs and outputs selection) are not comparable for a different list of indicators. The scope and results of the analysis, to a large extent, depend on the diversity and completeness of the official data available to researchers. Thus, modernization of the reporting indicators for entities involved in supporting the quality of life of the population is currently a pressing problem (Cantele et al., 2018). A reporting form of enterprises proposed by Guerrini et al. (2016) is useful for the assessment of their economic efficiency and sustainability. The “points-of-growth” methodology used here links classical eco nomic theory with the technological development of industries. The concept of points or centers of economic growth began with Perroux (1954). This concept is used in the assessment of the effect that an economic entity makes on its socio-economic environment at different stages of its activity. It is found in scientific papers (Shvetsov, 2005; Tskhai and Ananchenko, 2008; Vertakova et al., 2016; etc.) as well as official documents (Presidential, 2017) of the Russian Federation. In line with governmental policy (Resolution, 2013), the Russian water utilities should publicly present the essential information of their annual accounting and other production and financial reports. These data allow us to follow some concepts of the theory of economic “growth points” when analyzing the production activity of water utilities. It ac counts for peculiarities of the utility’s development from its start, when most resources are spent on solving its internal problems. As they mature, water may utilities begin to influence their socio-economic environment significantly, and the share of resources spent on external results begins to grow. In the financial analysis, a number of commonly used indicators (indices) are used to characterize economic entities such as current
E-mail address: [email protected]. https://doi.org/10.1016/j.jup.2019.100986 Received 7 March 2019; Received in revised form 4 November 2019; Accepted 5 November 2019 Available online 25 November 2019 0957-1787/© 2019 Elsevier Ltd. All rights reserved.
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liquidity, financial independence, etc © <2019> this version of the manuscript is available under CC-BY-NC-ND 4.0 license http://cre ativecommons.org/licenses/by-nc-nd/4.0/ (Methodological Recom mendations, 2002). To describe the aspects of water utility activity, the paper provides a definition of some performance indicators and for mulates the procedure for calculating their numerical values. The paper evaluates the relationship between resource efficiency and considered results
Table 1 Model for evaluating water utility efficiency. External resources
Internal resources
2. Materials and methods Efficiency characteristics are formulated by assuming that both re sources and performance are divided into internal and external cate gories, as proposed by Lobach (2000). Considering water utility efficiency and results, we also distinguish between internal (organiza tional) and external (environmental) results. Internal results include net profits and salaries at the disposal of the utility. External results, such as the volume of water supply and wastewater treatment, are of interest to the city in the utility’s environment. Additionally, the question of whether the “organization” or the “environment” impacts the value of the considered results is of great importance. To identify the source of the “growth point”, we also distinguish between the internal and external costs and resources used by the utility. All of the organization’s resources come into play and give grounds to consider its effectiveness in converting resources into results. The inclination of water utilities to increase revenue through prices has no limit. The amount of revenue raised for the organization largely depends on the ability of the environment (the city) to pay for water services. In this sense, “revenue” is considered an “external” resource. The specific list of variables (internal and external resources and results) is limited because of the established Russian standards of in formation disclosure in the field of water supply and wastewater treat ment (Resolution, 2013). However, estimates of our proposed indicators of efficiency can be obtained from the standard data on the enterprises. In this paper, the simplest case of two external and internal results, as well as two external and two internal resources, is considered: External results:
External results
Internal results
K1 Local indicator of external efficiency for external resources usage (a multiplicity indicator of efficiency) K2 Local indicator of external efficiency for the usage of internal resources (synergy indicator of efficiency)
K3 Local indicator of internal efficiency for the usage of external resources (adaptability indicator of efficiency) K4 Local indicator of internal efficiency for the usage of internal resources (intensity indicator of efficiency)
K1 is the average sum of proportions for each type of external results to each type of external resources for the final (τ) and initial (τ-1) moment of the studied period. This order of calculation of the multiplicity indi cator K1 is written in a mathematical form as: 2 P 2 P
K1 ðτÞ ¼
i¼1 j¼1
τ=
βij τ
1
τ=
; where βij τ
4
1
¼
βτij βτij
1
; βτij ¼
Ai ðτÞ Bj
(1)
Here, β is the local performance indicator (element of the matrix); i the number of the result indicator; j - the number of the resource indi cator; τ - the year. The same calculation procedure is applied to other local performance indicators with the corresponding indices i and j 2 P 4 P
K2 ðτÞ ¼
i¼1 j¼3
4
τ=
βij τ
4 P 2 P
1
; K3 ðτÞ ¼
i¼3 j¼1
4
τ=
βij τ
4 P 4 P
1
; K4 ðτÞ ¼
i¼3 j¼3
4
τ=
βij τ
1
(2)
As summarized in Table 2, the multiplicity indicator K1 represents the ratio of growth rates for external results to growth rates in external resources. As a demonstration, supposing that K1 > 1, the rise of water utilities’ role in the environment is more intense than the growth of their external resources, which indicates multiplicity. If K2 > 1, then the extension of water utility influence on the envi ronment is greater than the growth of internal results. The use of internal resources occurs primarily for the environment indicates synergy. When K3 > 1, the increase in the utility’s growth due to the use of external resources is higher than the change in impact on the environ ment. Growth that happens mainly for the organization itself indicates adaptability. When K4 > 1, growth of the water utility takes place essentially at the expense of internal resources, which indicates intensity. External and internal resources interact with each other; if water utility services are available to consumers, its efficiency can be defined as the measure to turn resources into results. Some of the results, such as net profit, involve putting additional resources at the disposal of the water utility. Others are directed to improving the condition of the external environment (volumes of water supply and treatment), which may, in turn, be relevant to the condition of the utility. The integrated priority index P is calculated as the arithmetic mean of four summary performance indicators Ki. The maximum potential of the utility as the “point of growth” corresponds to the maximum value of P. However, a comprehensive analysis of the constituents’ contribution is required for the correct interpretation of P. Such concepts as positive and negative growth are defining features. Negative trends in water utility development can significantly reduce investment efficiency as a result of altered incentives and preferences. In contrast, the investment of funds allows achievement of the desired performance level of services when the utility is ready to most effec tively utilize them. The general question arising is how to distinguish water utilities by important features, such as the “prospect” for their growth. A method of “points of growth” monitoring for water utilities of the Russian cities
A1 – the volume of municipal wastewater (km3) A2 – the volume of drinking water (km3) Internal results: A3 – the net profit (thousand dollars) A4 – the payment of production and administrative personnel (thousand dollars) External resources: B1 - the revenue (thousand dollars) B2 – the loans and external funding (thousand dollars) Internal resources: B3 – the fixed assets (thousand dollars) B4 – the own investment (thousand dollars) Our model for determining the efficiency of water utilities is sum marized in Table 1 and elaborated in Fig. 1. For example, we define K1 is a “multiplicity” indicator that characterizes the impact of changes in external resources on external results during the period under review. The indicators of “adaptability” (K2), “synergy” (K3) and “intensity” (K4) for water utilities are defined similarly. This typology was adapted from the investigations by Lobach (2000) (Shvetsov, 2005), for regional development. We use the simplest version of the identification of K1. The value of 2
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Utilities Policy 62 (2020) 100986
Fig. 1. Model for evaluating water utility efficiency.
in terms of growth and development (column 1 in Table 3), makes it possible to find analogs for each selected type, which allows us to further analyze and predict the utility’s life cycle. The following assumptions are used as the basis for the classification. A positive point of growth (development) is when all four indicators are more than 1, that is:
Table 2 Specification of the efficiency indicators. Indicator
Specification of the efficiency indicator
K1 – multiplicity indicator of efficiency K2 – synergy indicator of efficiency
Average ratio of growth rate for external results to external resources change. Average ratio of growth rate for external results to internal resources change. If this indicator >1, the own resources for the external environment is used. Average ratio of growth rate for internal results to external resources change. If this indicator >1, external resources are used mainly for the utility’s own growth. Average ratio of growth rate of internal results to internal resources change. If this indicator >1, intensification of the own growth is mainly due to its own resources.
K3 – adaptability indicator of efficiency K4 – intensity indicator of efficiency
Ki ji¼1;2;3;4 > 1
(3)
Four types of positive points of growth (development) are identified depending on the indicator Ki with its maximum value. The first type is characterized by: K4 ¼ max Ki ji¼1;2;3;4
(4)
In this case, internal growth is accounted for by the expense of the internal resources of the water utility. This is typical for firm innovation and restructuring in the particular region and the country as a whole. We introduce the definition of the coefficient L|k¼1, that is the firsttype “point” identification: � Ljk¼1 ¼ 3 K4 K1 K2 K3 > 0
was developed and applied in this work. Initially, the utility organiza tion enters a phase of growth related to the creation of material and technical base, as well as the provision of resources and the regulation of technological procedures. The production processes are implemented more effectively in accordance with current tasks. With an increase in output, the utility enters a phase of development, when the impact of its activity on the environment becomes noticeable. In the proposed approach, the predominance of the growth rate of internal results over external ones is evidence of the growth phase and the predominance of growth rates of external results over internal ones distinguishes the development phase. The classification of water utilities
Due to the relationship of (3) and (4), a negative coefficient L|k¼1 indicates that some of the basic assumptions of the first type are violated. We next assume that the closer the “point” trajectory to the first type is, the higher the calculated value of L|k¼1. Similarly, other types of “points of growth (development)” are characterized, and other co efficients L|k, (levels of “point” identification) for the rest seven types are introduced. 3
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Table 3 Classification of enterprises by types of growth (development). Type of points
Multiplicity indicator K1
Synergy indicator K2
Adaptability indicator K3
Intensity indicator K4
Level of “point” identification L
1
growth point with internal source
K3 < K4, K3 > 1 K3 > 1
3 K4– K1– K2– K3
growth point with external source development point with internal source
4
development point with external source
5
negative growth point with internal source
K4 < K3, K4 > 1 K4 < K2, K4 > 1 K4 < K1, K4 > 1 K4 < 1
3 K3– K1– K2– K4
3
K2 < K4, K2 > 1 K2 < K3, K2 > 1 K2 > 1
K4 > 1
2
K1 < K4, K1 > 1 K1 < K3, K1 > 1 K1 < K2, K1 > 1 K1 > 1
6
negative growth point with external source
K1 þ K2 þ K4 -3 K3
7
negative development point with internal source negative development point with external source
K4 > K3, K4 < 1 K2 < K4, K4 < 1 K4 > K1, K4 < 1
8
K1 > K4, K1 < 1 K1 > K3, K1 < 1 K1 > K2, K1 < 1 K1 < 1
K3 < K2, K3 > 1 K3 < K1, K3 > 1 K3 > K4, K3 < 1 K3 < 1
K2 < K1, K2 > 1 K2 > K4, K2 < 1 K2 > K3, K2 < 1 K2 < 1
K2 < K3, K3 < 1 K3 > K1, K3 < 1
K2 > K1, K2 < 1
The second type is characterized by:
3 K2– K3- Kι- K1 3 K1– K2– K3– K4 K1 þ K2 þ K3 -3 K4
K1 þ K2 þ K3 - 3 K2 K2 þ K3 þ K4 - 3 K1
K3 ¼ min Ki ji¼1;2;3;4
K3 ¼ max Ki ji¼1;2;3;4
The seventh type is:
Here, internal growth happens typically at the expense of external resources, that is, when the utility spends loans (external investment) on wage payments. The third type is characterized by:
K2 ¼ min Ki ji¼1;2;3;4 when the determining process is the internal degradation of the negative “point”. Inefficient economic actors tend to end their life cycle along this path. Inefficient economic actors will have to move towards some of the strategic choices, including restructuring. The eighth type is the most dangerous. The negative “point” absorbs external resources, which has a negative effect on the socio-economic environment. The aggravation of environmental development is accel erated. This “point” is a type of multiplier of economic degradation:
K2 ¼ max Ki ji¼1;2;3;4 The acceleration of the utility’s organizational development and structural transformation in the environment arise mainly from internal resources available. The Japanese technopolises, which were basically established at the expense of local government resources, are a good case in point. At the same time, the development impetus from the introduction of new industries, technologies, and technopolises had a significant influence on the development of industrially backward areas in Japan (Maruyama, 1985). The fourth type is characterized by:
K1 ¼ min Ki ji¼1;2;3;4 Parametric features of “points of growth (development)” with the formula for assessing the level of identification (L) by comparing the coefficients are summarized in Table 3. A combination of several types of points (excluding the “pure” one) is characteristic of each particular utility. Therefore, the utility performance is analyzed in terms of the proximity to a particular type. The volumes of supply of drinking water are many times higher than the volumes of supply of technical water (such as for heating systems, etc.). So far, this is the reality for the six water utilities that had been studied in this work.
K1 ¼ max Ki ji¼1;2;3;4 The external resources are used to accelerate their own growth and influence on the surrounding area. The Chinese special economic zones and techno-industrial parks established with financial and administra tive assistance from the state are a vivid example (Peebles, 1986). This type of “points of development” is the most important for an economy in transition. The negative type of growth (development) is found when all four indicators are as follows:
3. Analysis and results Water utilities in six regional administrative centers of Siberia, with comparable population size and conditions for enterprise operation, became the focus of our study. At the first stage of the analysis, the integrated priority indicator P was calculated for water utilities in the cities of Barnaul (“Barnaul Vodokanal”, 2019), Chita (“Vodokanal-Chita”, 2019), Irkutsk (“Vodo kanal”, 2019), Novosibirsk (“Gorvodokanal”, 2019), Omsk (“OmskVo dokanal”, 2019) and Tomsk (“TomskVodokanal”, 2019) (see Table 4). The calculations based on the given primary data showed that during the period from January 1, 2013, to December 31, 2014, the water utility of Irkutsk was the fastest developing utility, being far ahead of the rest (with a priority index of 13.149). It can be assumed that this was a period of profound change as compared to other utilities in terms of the financial and economic policies of the utility. The activity of the rest water utilities was characterized using the indicator P: Tomsk (1.547), Chita (1.432), Barnaul and Novosibirsk (1.01), and “OmskVodokanal” (0.775). In the second period (from January 1, 2015, to December 31, 2016),
Ki ji¼1;2;3;4 < 1 Four options of negative “points of growth (development)” are identified due to the indicator Ki with the lowest value. The fifth type is characterized by: K4 ¼ min Ki ji¼1;2;3;4 It includes negative “points” with negative growth. Such a “point” inefficiently uses its own resources, thus being unprofitable. The in crease in unemployment in fast-growing cities is a case in point. External resources can be used in negative growth processes. The state cannot leave its citizens without water services of the natural monopoly and is forced to allocate resources to the unprofitable water utility. Such policies are potentially the highest priority because of the possible rationale to prevent social disaster. Their negative economic consequences should be properly resolved as appropriate. This sixth type of negative “points” is characterized by:
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Irkutsk water utility had the strongest impact on its socio-economic environment over the four years (average indicator - 7.756). Next, in descending order, are the enterprises of Tomsk (1.244), Chita (1.048), Novosibirsk (0.914), Omsk (0.890) and Barnaul (0.750). The parametric analysis was performed for water utilities according to the classification of types (see Table 6). For all types, the higher value corresponds to the greater proximity. For example, in 2013–2014, the proximity of the Barnaul utility to the 1st type of the “point of growth” with internal resources was 0.151; to the 2nd type with external re sources was 0.663; and to the 3rd type with internal resources was 0.613. In this analysis, the negative value of the indicator does not mean enterprise degradation; it simply means that the indicator cannot belong to the considered type. Thus, the value of L|k¼1 equal to 0.151 for the Barnaul water utility shows that in the first period this utility did not belong to the type of the “point of growth” with an internal source, and it was not the negative “point of growth” with an internal source. The largest value in the column (the Barnaul enterprise, 2013–2014) in the 2nd line (0.663) means the greater utility’s correspondence to the 2nd type (“point of growth” with an external source) than that for other seven types. The results of the parametric analysis for all enterprises are pre sented in Table 6. The bottom line indicates the type of the “point of growth (development)” for the utility, fitted best of all. The bottom line in Table 6 shows that in 2013–2016 all water utilities referred to positive types of “points of growth” (N� 1, 2, 3, 4). In both periods under study, the water utility in Barnaul represented the “point of growth” with external sources, which is indicative of the utility’s potential to affect the socio-economic environment. The Chita water utility in both studied periods corresponded to the “point of growth”. Unlike the Barnaul utility, its progress was made due to internal resources. To hold this position, the search for external sources was of particular importance. During the periods under consideration, qualitative changes were observed in Irkutsk and Omsk. Both enterprises lowered their level of development: they dropped from the “point of development” (the first period) to the “point of growth” with external sources (the second period). This option would be acceptable for water utilities. Municipal authorities may be interested in more intensive usage of internal re sources and early return to a higher level of providing public services in the cities. The water utility of Novosibirsk was the “point of growth” during both studied periods. It should be noted that in 2013–2016, the utility was reoriented from the internal to external resources. The Tomsk water utility experienced transformation as the “point of growth”. In contrast to Novosibirsk, the utility was reoriented from external to internal sources. Parametric proximity to the “point of development” with an external source allows us to identify the most promising for investment, namely, the Omsk utility in the first period. At the same time, “points of growth” and “points of development” with internal sources are the most effective when their own resources are used.
Table 4 Dynamics of priority indicator values for water utilities. N�
Water utility (city)
Priority indicator 2015–2016
Priority indicator 2013–2014
1 2 3 4 5 6
Barnaul Chita Irkutsk Novosibirsk Omsk Tomsk
0.704 1.569 0.944 1.274 0.898 1.279
1.010 1.432 13.149 1.010 0.775 1.547
the enterprises intensified their activities somewhat as compared to the first period (2013–2014): Chita (from 1.432 to 1.569), Novosibirsk (from 1.01 to 1.274), and Omsk (from 0.775 to 0.898). Only in Novo sibirsk and Chita was the priority indicator P > 1 in both periods, sug gesting that the rest four enterprises have the potential to improve their performance. After a “breakthrough” first period in 2015–2016, the water utility of Irkutsk had the priority indicator P < 1. Thus, an important task of the utility was to maintain sustainable performance. The analysis suggests the potential for management improvement at almost all water utilities. The multiplicity and synergy indicators, which characterize the transformation of internal and external resources into external results, deserve thorough consideration (see Table 5). During the first period under review (2013–2014), water utilities of Tomsk (1.462), Irkutsk (1.125), Omsk (1.083) and Barnaul (1.01) showed the highest values of the first indicator, that is, K1 < 1, compared to the enterprises of Chita (0.938) and Novosibirsk (0.878). In the second period (2015–2016), only Novosibirsk and Chita enterprises managed to make good progress (1.074 and 1.069, respectively). The water utilities of Barnaul, Irkutsk, Omsk, and Tomsk demon strated reduced multiplicity indicators during the second period (0.651, 0.899 and 0.919, respectively), which is evidence of decreased effi ciency of water supply and wastewater treatment. This might be explained by a more complex macroeconomic situation in the second period, during which water utilities of Chita and Omsk experienced in creases in the synergy indicator (from 1.017 to 1.167 and from 0.735 to 0.811, respectively), which implies a high possibility of the enterprises to achieve external results at the expense of their internal resources. By the synergy indicator, the Irkutsk enterprise was in the lead during the first period (28.289). By the second period, in the new macroeconomic situation, its internal resources drastically decreased to an unsatisfactory level of 0.716. Of the rest enterprises, only Chita (1.167) and Tomsk (1.224) showed satisfactory external results at the expense of internal resources, i.e. K2 > 1. The dynamics of the sum of the first two indicators suggest that the Table 5 Dynamics of efficiency indicator values for water utilities: (a) Multiplicity in dicator values for water utilities: (b) Synergy indicator values for water utilities. N�
Water utility (city)
Multiplicity indicator (2015–2016)
Multiplicity indicator (2013–2014)
1 2 3 4 5 6
Barnaul Chita Irkutsk Novosibirsk Omsk Tomsk
0.651 1.069 0.892 1.244 0.929 0.919
1.010 0.938 1.125 0.878 1.083 1.462
N�
Water utility (city)
Synergy indicator 2015–2016
Synergy indicator 2013–2014
1 2 3 4 5 6
Barnaul Chita Irkutsk Novosibirsk Omsk Tomsk
0.481 1.167 0.716 0.564 0.811 1.224
0.857 1.017 28.289 0.968 0.735 1.370
4. Conclusion An approach to assessing the efficiency of Russian water utilities based on the application of the theory of “growth points” is proposed. It combines a set of quantitative indicators related to the sustainability of water utilities and the assessment of the relationship between resources and results. The methodology was used to study the development of six water enterprises in Siberian regional administrative centers (similar in population and conditions) providing water supply and wastewater treatment services. The research revealed very different patterns in the use of external and internal resources. Municipal authorities, often granting tax preferences to utility monopolies, are interested in inten sive use of the utility’s internal resources. On the other hand, the posi tive development of a utility cannot always be realized only through 5
А. Tskhai
Utilities Policy 62 (2020) 100986
Table 6 Parametric characteristics of the proximity of water utilities to types of «growth points». N� п/п
1 2 3 4 5 6 7 8 9
Types of “growth point”
“Growth point” with internal source “Growth point” with external source “Development point” with internal source “Development point ” from external source Negative “growth point” with internal source Negative “growth point” with external source Negative “development point” with internal source Negative “development point” with external source Number of type for “growth point”
Barnaul Vodokanal
Vodokanal-Chita
Vodokanal of Irkutsk
Novosibirsk Gorvodokanal
OmskVodokanal
TomskVodokanal
I 2013–2014
II 2015–2016
I
II
I
II
I
I
I
II
0.044
2.123
2.160
36.588
0.087
0.562
0.304
1.677
1.056
1.514
1.449
1.033
0.133
0.051 0.663 0.613
0.890
1.661
1.608
0.000
0.209
1.976
2.001
0.051
0.044
2.123
2.160
1.056
1.514
1.449
0.663 0.613
0.890
1.661
1.608
0.000
0.209
1.976
2.001
2
2
1
1
49.051 60.560
0.991
0.167
2.839
48.098
0.209
0.528
0.121
36.588
0.087
0.562
1.033
0.133
60.560
0.991 3.951
0.911
0.167
2.839
48.098
0.209
0.528
0.121
3
2
1
2
II 1.027
3.951
0.911
49.051
internal resources. The proposed methodology provides the basis for an objective assessment. It can be expanded by considering additional indicators relevant to the sustainable development of water utilities (for instance, characteristics of the region, where water utilities are located, and management structures). In particular, the developed approach can be used with regard to Federal projects for the development of water management strategies in the regions. In addition to the methodological contribution, the application of the approach to the Russian water utilities offers two other notable results related to policy. First, it is a tool for choosing the moment when external investments or tax preferences for the development of the utility will be most effective for the city. When making an investment decision, it is necessary to take into account the readiness of the utility to make use of these resources, which depends on its development status. Second, it is a tool for the evaluation of the Russian water utilities in terms of management. However, in practice, accounting for all potential factors, including those beyond this analysis, is required. For example, if a water utility is located in an area with a poor macroeconomic situa tion, this factor will be manifest in performance. It should be borne in mind that the proposed approach can be combined with other meth odologies. Further investigations will enable the assessment of Russian utilities according to evolving international standards in water man agement. The obtained results could find application in the development of a water use strategy in Siberia. This research did not receive any specific grant from funding agencies in the public, commercial or not-for-profit sectors.
II
0.043
0.138 0.364
0.162
0.740
0.348
0.017
0.706
0.219
1.232
0.123
0.338
1.440
1.027
0.138
0.304
1.677
0.043 0.162
0.364 0.348
1.232 4
0.123 2
0.740
0.017
0.706
0.219
0.338
1.440
2
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Cantele, S., Tsalis, T., Nikolaou, I., 2018. A new framework for assessing the sustainability reporting disclosure of water utilities. Sustainability 10, 433–444. https://doi.org/10.3390/su10020433. Cooper, W., Seiford, L., Tone, K., 2007. Data Envelopment Analysis - A Comprehensive Text with Models, Applications, References and DEA-Solver Software, second ed. Springer, US. https://doi.org/10.1007/978-0-387-45283-8. De Witte, K., Marques, R.C., 2010. Designing performance incentives, an international benchmark study in the water sector. Cent. Eur. J. Oper. Res. 18 (2), 189–220. Eggimann, S., 2016. The Optimal Degree of Centralisation for Wastewater Infrastructures. A Model-Based Geospatial Economic Analysis. University of Zurich, Switzerland. Diss. ETH 23915. The “Gorvodokanal” of the Novosibirsk Municipal Unitary Utility, 2019. gorvodokanal. com/info/?item¼32. (Accessed 25 May 2019). Guerrini, A., Romano, G., Ferretti, S., Fibbi, D., Daddi, D., 2016. A performance measurement tool leading wastewater treatment plants toward economic efficiency and sustainability. Sustainability 8. https://doi.org/10.3390/su8121250, 1250-163. Lobatch, A.I., 2000. Growth points as an instrument of management of the exportoriented economy. Diss. Minsk: Belarus State Economic University, p. 185. Republic of Belarus (in Russian). Maruyama, M., 1985. Report on a new technological community: the making of a technopolis in an international context. Technol. Forecast. Soc. Chang. 27 (1), 75–98. Methodological recommendations for the analysis of financial and economic activities for organizations, 2002. The Federal State Statistics Service. Moscow, Russian Federation (in Russian). The “OmskVodokanal” Joint Stock Utility, 2019. http://www.e-disclosure.ru/po rtal/files.aspx?id¼21901&type¼3. (Accessed 25 May 2019). Peebles, G., 1986. In: Jao, Y.C., Leung, C.K. (Eds.), China’s Special Economic Zones: Policies, Problems, and Prospects. Oxford University Press, Hong Kong, p. 246. Perroux, F., 1954. Europe without Shores. Grenoble university publishing house, Grenoble (in French). Picazo-Tadeo, A.J., Gonzalez-Gomez, F., Saez-Fernandez, F.J., 2009. Accounting for operating environments in measuring water utilities’ managerial efficiency. Serv. Ind. J. 29 (6), 761–773. https://doi.org/10.1080/02642060802190300. Presidential decree, 2017. Presidential decree No. 13 of the 16th January On Approval of the State Policy of Regional Development of the Russian Federation for the Period until 2025. Moscow, Russian Federation (in Russian). Resolution of the Russian Federation Government, 2013. Resolution of the Russian Federation Government No. 6 of the 17th January About Standards of Information Disclosure in the Field of Water Supply and Wastewater Treatment. Moscow, Russian Federation (in Russian). Romano, G., Guerrini, A., 2011. Measuring and comparing the efficiency of water utility enterprises: a data envelopment analysis approach. Util. Policy 19 (3), 202–209. https://doi.org/10.1016/j.jup.2011.05.005. ISSN 0957-1787. Seroa da Motta, R., Moreira, A., 2006. Efficiency and regulation in the sanitation sector in Brasil. Util. Policy 14, 185–195. Shih, J., Harrington, W., Pizer, W., Gillington, K., 2006. Economies of scale in community water systems. J. Am. Water Work. Assoc. 98, 100–108. Shvetsov, I.V., 2005. Formation of Territorial “growth Points” as a Factor of the Regional Development. Diss. Moscow: RASS, Russian Federation (in Russian). Thanassoulis, E., 2000. The use of data envelopment analysis: in the regulation of UK water utilities: water distribution. Eur. J. Oper. Res. 126 (2), 436–453. https://doi. org/10.1016/S0377-2217(99)00303-3.
Declaration of competing interest None. References Aida, K., Cooper, W.W., Pastor, J.T., Sueyoshi, T., 1998. Evaluating water supply services in Japan with Ram: a range-adjusted measure of inefficiency. OMEGA-Int. J. Manag. Sci. 26 (2), 207–232. The “Barnaul Vodokanal” Limited Liability Utility, 2019. barnaulvodokanal.ru/. (Accessed 25 May 2019). Byrnes, P., Crase, L., Dollery, B., Villano, R., 2010. The relative economic efficiency of urban water utilities in regional New South Wales and Victoria. Resour. Energy Econ. 32 (3), 439–455.
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А. Tskhai
Utilities Policy 62 (2020) 100986
The “TomskVodokanal” Limited Liability Utility, 2019. www.vodokanal.tomsk.ru/. (Accessed 25 May 2019). Tskhai, A.A., Ananchenko, Yu.S., 2008. A model-based approach to the assessment of the development character for innovation cluster and its components. In: Actual Problems of Economics and Law at the Present Stage of Development of the Russia: International Conf. Barnaul, Russian Federation, pp. 94–97 (in Russian).
Vertakova, Yu., Grechenyuk, O., Grechenyuk, A., 2016. Identification of clustered points of growth by analyzing the innovation development of industry. Procedia Econ. Financ. 39, 147–155. The “Vodokanal” of Irkutsk Municipal Unitary Utility, 2019. www.irkvkx.ru/. (Accessed 25 May 2019). The “Vodokanal-Chita” Joint Stock Utility, 2019. vodokanalchita.ru/. (Accessed 25 May 2019).
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