DYSFUNCTION AS AN OBSTACLE IN ACHIEVING SUSTAINABLE SOCIAL ECOLOGICAL ECONOMIC DEVELOPMENT OF THE REGION (EVIDENCE FROM THE VOLGA FEDERAL DISTRICT)

Evgeniya Vladimirovna Kabitova^*

Kazan National Research Technical University, Almetyevsk, Russia

Svetlana Anatolyevna Ashirova

Kazan National Research Technical University, Almetyevsk, Russia

Svetlana Mazgutovna Nuriyahmetova

Almetyevsk State Oil Institute, Russia

Olga Aleksandrovna Fathutdinova

Almetyevsk State Oil Institute, Russia

Artem Nailevich Ashirov

Saint-Petersburg National Research University of Information Technologies, Mechanics and Optics, St. Petersburg, Russia

*Corresponding Author:

Evgeniya Vladimirovna Kabitova
Kazan National Research Technical University
Almetyevsk, Russia
Tel: +7(8553)22-15-65
Email: Evgeniya_syehugova@yandex.ru

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Abstract

The creation of a society with a vector of sustainable development predetermines the search for optimal proportions of reproduction of social ecological economic parameters of the territories. The article presents the development results of sustainable social ecological economic advancement model of the regional system and verifies the appropriateness of the social ecological economic systems’ parameters of the regions of the Volga Federal District (VFD) to the proposed sustainable development model. We introduce the notion of dysfunction (dysfunctional development) considered as an obstacle and antipode of sustainable development of the territory, and define the boundaries of normally occurring processes and the dysfunctionality for the VFD regions. We performed calculation and evaluation of the territories in terms of their conformity with sustainable development or dysfunction. The proposed method can be positioned as a way of identifying and adjusting dysfunctional territories and can be applied for further definition of effective response tools.

Keywords

Sustainable Social Ecological Economic Development, Model of Sustainable Development of the Regional System, Dysfunctional Condition of the System, The Boundaries of Dysfunctionality

Introduction

Contemporary problems of environmental degradation, the growing economic backwardness and technogenic threats lead to increase with each passing day the importance of the implementation of sustainable development concept of social ecological economic systems at different levels (from micro level to global level). The priority of financial capital along with ignoring other factors of production, mindless and voluntary approach in using natural resources (especially non-renewable ones) have led to a significant imbalance in many systems [1].

The basic principle of the implementation of the sustainable development concept is co-evolutionary unity of three components: social, environmental and economic. At that, the implementation of economic and social interests should be subordinated to the ecological imperative [2]. Unlike the technology-related, nature intensive and other models, the development model of sustainable social ecological economic system does not assign the dominant role to the economic dimension of existence, though assumes balanced and proportional interaction of all system’s components [3].

Sustainable development of social ecological economic system should be based on the consolidation of the following constitutive objectives: eco-efficiency, eco-integrity and eco-fairness [4]. The implementation of these objectives is possible only in terms of a balanced functioning of social, ecological and economic subsystems of the administrative territory under the stipulation that there should be positive (optimal) dynamics of the system parameters under sustainable conditions [5]. The most favorable model of social, economic and natural systems functioning is a mutual achievement of optimal proportions of their reproduction [6].

Methodology

Aspects of Sustainable Development

The interpretation of sustainable development in terms of economic aspect defines economic growth as a condition necessary for rational advancement rather than depressive development of the economic entity, although, the growth by its nature is not identical to the development [7]. Sustainable development can be implemented in the economic growth if it refers to the total long-term positive development trend, though there may be certain recessions in the short term. The economic system consists of interrelated elements, whose functioning is not always subordinated to the favorable development trends. The regions with development parameters below average (or minimum permissible) can be considered as territories with non-productive functioning, or in other words, dysfunctional.

The social aspect of sustainable development, if describing from a quantitative point of view, suggests a favorable condition of the territory’s demographic system. If implementing the concept of sustainable development necessitates describing the functioning of the economic system by growing trend, than the desirable condition of demographic parameters should provide a solution to the problem of under population or overpopulation of the habitat [8].

The environmental essence of sustainable development is set out in its definition, which is that meeting the needs of the present, one should not jeopardize the satisfaction of needs of future generations [9]. Therefore, the society in its economic activities should not forget about the natural scarcity and depletion of natural resources associated with high rates of their consumption.

Important is the question of establishing the optimal functioning parameters of the social ecological economic system which would correspond to its sustainable condition. The creation of sustainable society is possible only through achievement of the optimal proportions of social, economic and natural systems reproduction. Therefore, it is necessary to develop model on the relationship between ecological parameters, economic and social indicators satisfying the conditions of sustainable advancement of the system [10].

Characteristics of the Research Object

The investigation of sustainable development will be carried out in relation to social ecological economic system of the Volga Federal District (VFD). The VFD consists of six republics, seven regions and one territory, which create not only territorial association, but are interrelated also through the following integrative factors. All Volga regions are located along the largest river in Europe, namely the Volga River, which is used for cargo transportation and agricultural needs. The next integration factor consists in rich hydrocarbon reserves, and therefore the VFD is focused on oil and gas refinery processing and is also a monopolist in the production and processing of potassium salts. Another factor consists in concentration in the region of the automotive industry and aerospace technology. These facts are both the results of the VFD socio-economic system functioning as well as the factors of economic growth.

A model of sustainable social ecological economic development of the region

The article proposes a model of sustainable social ecological economic development which includes economic, environmental and social (demographic) parameters interrelated by the following inequality:

(1)

Where I_IPI – is the industrial production index (in regional mining operations);

I_PG – is the index of population growth in the region;

I_GRP – is the index of physical volume of gross regional product.

Sustainable development of the region is characterized by the fulfillment of inequality (1) which can be interpreted as follows:

1) I_IPI → min, I_IPI < 100 – the reduction of mineral output characterizes the reduction of anthropogenic load on the environment;

2) I_PG > 100, ensuring this condition characterizes the population growth of the region over the certain period and predetermines the expanded reproduction of the population that contributes to the problem of under population; the fulfillment of the ratio I_IPI< I_PG corresponds to the implementation of the ecological sustainability principle;

3) I_GRP > 100 characterizes the economic growth of the regional system; the fulfillment of inequality I_PG < I_GRP should lead to the welfare gain of the population and achievement of economic sustainability. The sustainability of economic growth is reflected in the progressive increase of per capita income produced in the country [11] and covering all levels of the population (not just the top decile).

Using the data of the Federal State Statistics Service (www.gks.ru), we define the degree to which the status of the social ecological economic systems of the VFD regions corresponds to conditions of the model (1). Data corresponding to the period from 2000 to 2014 is taken as a sample frame of indicators (Tables 1A and 1B).

Table 1A: Compliance assessment of social ecological economic systems’ parameters of the VFD regions to the sustainable development model for a period from 2000 to 2007.

Table 1B: Compliance assessment of social ecological economic systems’ parameters of the VFD regions to the sustainable development model for a period of 2008-2014.

The comparison of sustainable development indicators of the Volga Federal District in general shown in Tables 1A and 1B leads to conclusion that the conditions of the model (1) in the period from 2000 to 2014 are not met. Energy source specialization of the regional economy is identified through nonfulfillment of the conditions I_IPI→ min and I_IPI<100. The analyzed period is characterized by the annual expansion of mining capacity; the highest growth in mining occurred in 2003 and 2010 that characterizes the increase of anthropogenic load on the environment. An analysis of the economic indicator of the VFD is characterized in general by growth, which was marked by the opposite trend just in 2009, being in line with the global trends. The main problem with the VFD when implementing the concept of sustainable social ecological economic development is the status of demographic system: the condition I_PG > 100 never was fulfilled during the period from 2000 to 2014, that is, every year there was a contracted reproduction of the population, and therefore a problem, which is typical for the whole Russian Federation, i.e. under population, is not being solved, though it is merrily aggravated. For these reasons, the probability of implementing conditions for sustainable development of the VFD in general, as evidenced by Figure 1, is zero.

Figure 1: The probability of fulfillment of sustainable development conditions for the VFD regions (for sample frame over the period from 2000 to 2014).

The most successful regions in terms of the fulfillment of the sustainability conditions (according to the general form of inequality) are the following entities: Republic of Bashkortostan (with probability of 0.333), Kirov Region (0.4) and Penza Region (0.4). The basic inequality for the Republic of Bashkortostan for 2000-2004 is satisfied through the implementation of the conditions of environmental sustainability and economic growth, though the demographic component, albeit it fits into the framework of the model, is based on population decline due to excess of death rate over birth rate. With regard to Penza and Kirov regions, basic inequality is fulfilled in 40% of cases,though demographic security conditions in the regions are violated because even with an overall positive dynamics of birth rate, the population trend in these regions decreases. In the period from 2000 to 2014, Perm Region never had approached to the implementation of the sustainability concept: the region annually increases the mineral output, and this certainly is a factor of economic growth; expanded reproduction of the demographic system was expected only since 2012, at that the production life index violates ecological sustainability.

The calculation of the event probability is performed according to the formula (2) [12]:

(2)

where q_i – is the event probability (the probability of fulfillment of the sustainable development model conditions for the concerned region);

n_i – is the number of the i-th event occurrence (the number of compliances with the sustainable development model conditions by the i-th region over the analyzed period);

Σn_i − is the total number of monitoring events (a total number of event observations for the i-th region, or the length of the time series corresponding to the sample frame).

The only region of the Volga Federal District, where all the conditions of the model (1) are fulfilled most efficiently, though not completely (with a probability of 0.133), is the Republic of Tatarstan. Although here the frequency of event occurrence is not the highest one over the Volga Federal District, but since 2007 there has been population growth, and the regional economy is characterized by growth over the period under review. The most favorable results were obtained in 2010: 100.0 < 100.1< 104.3, that is, the mineral output does not exceed the level of the previous year, the excess of births over deaths has led to the increase in population, and there was economic growth as well. By the end of 2012 the values of similar figures were as follows: 100.5 <100.6 < 105.5, i.e. the increase in population was accompanied by welfare gain, though extended mineral output was not unimportant factor in the existing situation.

Results

Dysfunction as a Manifestation of the Sustainable Development Violation

Sustainability can be achieved through the optimal functioning of all the elements of the social ecological economic system. Failure in their operation is considered as dysfunctional development, or dysfunction. Accordingly, dysfunction is perceived as a violation of the optimal (normal) condition of social ecological economic system.

Dysfunction defines the type of relationships, where the consequences of activities of certain system’s element, other than the optimal ones, become unfavorable for the other element of the system [13].

Dysfunction of social ecological economic system is determined by the deviation of the parameter characterizing the system’s element from its optimal criterion value, corresponding to the sustainable development conditions. To conduct applied research, it is necessary assigning to dysfunctional condition not only its qualitative characteristics, but also identifying its formalized nature. In this context, the indicator of dysfunction for different regions will characterize on a case-by-case basis the degree of prosperity or instability in development of each territory. This indicator should be defined for a number of key socio-economic factors, as well as the integrated criterion should be calculated. It is necessary to conduct the analysis of dysfunctionality not only in static conditions but also over time that will give a comprehensive idea about the state of research object. Dynamic analysis allows building a trend that visualizes both states of well-being and dysfunction. The proposed model of sustainable social ecological economic development predetermines that the demographic and economic components must adhere to a growing trend, i.e. be characterized by growth, while achieving environmental sustainability should be described by a declining trend. Accordingly, the deviations from a positive trend will identify the dysfunctional development. In the framework of this approach, it is necessary to resolve the problem concerning the stateof normally (positively) occurring processes.

Multidirectional dynamics of individual indicators may cause certain complexity for the researcher. Therefore, completely natural solution would be using balanced scorecards and scoring systems, which involve creative approach and high flexibility [1].

Establishing the Boundaries of Normally Occurring Processes and The Dysfunctionality

Establishing the boundaries of normally occurring processes and the dysfunctionality can be done through defining the reference level to determine the deviation. The mathematical expectation can be used as such reference level. Though, since most of the analytical calculations are performed for the sample frame, it is better to dwell on the mathematical expectation of the sample. In the mathematical interpretation, this criterion is a random variable, distributed according to the normal probability law [14]. In this context, if we base on sufficient predictability of the behavior of the probability density of a random variable criterion, it is admissible to introduce the gradation of the federal district regions with regard to the mathematical expectation. In our situation, we take the parameters describing the status of federal district on the average as a mathematical expectation. In this context, the regions whose parameters lie above the line of mathematical expectation, i.e. above the average for the VFD in the concerned period, can be deemed prosperous (sustainable), while the regions with the coordinates located below the line of mathematical expectation, will be deemed dysfunctional. Since this statement will be extended to the model of sustainable social ecological economic development (1), the interpretation of the demographic and economic factors behavior will correspond to the proposed terms, though the behavior of the ecological component of the model will be interpreted vice versa: the excess of the mathematical expectation characterizes the dysfunction, while lower values indicate stability condition.

Because the value of the probability density function under the integral equals to unity, and the probability density reduces with distance from the line of mathematical expectation μ (the greater the variation the greater the expectation), it is logical to set the boundaries of normally occurring processes and the dysfunctionality based on the calculations by the three-sigma rule [15]. This rule suggests that practically all values of a random variable with a normal distribution lie within the interval [μ−3σ;μ+σ]. But the interpretation of this rule is only valid for the case of studying just general population, where the mathematical expectation is the true value. In this article we study the sustainable development factors in the form of the sample frame over the years from 2000 to 2014 with the increment of one year. For this reason, it is necessary to use standard deviation (s) rather than the root-mean-square deviation (σ).Therefore the “three sigma rule” is converted into “three s rule”. We select μ ± n · s, where n = 1, 2, 3, as the boundaries of status levels [16]. Thus, we determine three levels in a zone of conditionally prosperous (sustainable) regions and conditionally dysfunctional regions. We define conditionally sustainable levels as low sustainable, moderately sustainable, and highly sustainable ones. The conditionally dysfunctional levels are defined in a similar way: low dysfunctional (that is, experiencing slight manifestations ofdysfunction), moderately dysfunctional, and highly dysfunctional (with strong manifestations of dysfunction) levels. Thus, the proposed approach covers 99.7% of the studied objects. That is, normally distributed value is within the specified interval with a given accuracy, while the probability of the region for being not classified based on proposed approach is just 0.27% [17].

Discussion

Calculate mathematical expectation for each sustainable development factor of model (1) by applying the following formula:

(3)

where x_i – is the possible value of the sustainable development factor;

p_i – is the probability of occurrence of x_i event [18].

According to the Federal Service of State Statistics (for sample frame) we performed calculations of annual mathematical expectation for the regions of the Volga Federal District for the period from 2000 to 2014 with regard to the sustainable development factors of the model (1), as visualized in Figures 2-4. We apply “three s rules” as a method for determining the affiliation of a certain region to the group of sustainable or dysfunctional regions. The implementation of this method requires calculation of standard deviation using the following formula [19]:

(4)

Applying the previous calculations of the mathematical expectation and the data of the Federal State Statistics Service, we used formula (4) to calculate the annual standard deviations of the sustainable development factors in the regions of the Volga Federal District. The results are shown in Figures 2-4. The proposed approach to the gradation of the VFD regions is based on the calculations of the criteria allowing us to attribute certain region to one of three levels in the zone of conditionally sustainable or conditionally dysfunctional development.

Figure 2 defines the boundaries of the sustainable and dysfunctional zones for the environmental factor of the VFD regions over the period from 2000 to 2014. When developing the model (1) to achieve sustainable social ecological and economic development of the regional system it is necessary to reduce anthropogenic load on the environment by reducing extraction of minerals [20]. Therefore, the dysfunctional state of the system is characterized by an increase and excess of the mathematical expectation for a given parameter. Accordingly, the higher the industrial production index in the extraction of natural resources, the more pronounced is the status of the system’s dysfunction.

Figure 2: The boundaries of the sustainability and dysfunctional zones for the environmental factor of VFD regions.

Visualize the calculation results of the sustainability and dysfunction zones boundaries for the demographic factor of the VFD regions (Figure 3). According to the model of sustainable development of the VFD regions, the area under the analysis is characterized by the problem of under population. Optimization of the population could be achieved through its expanded reproduction. Therefore, the higher population accession rate in the concerned area, the stronger the implementation of the sustainability concept. The decline of population in the regions is regarded as a dysfunctional condition of the demographic system. In Figure 3 one can observe that the range of boundaries variation of sustainability and dysfunction zones is small that is based on the almost identical demographic indicators in various regions of the Volga Federal District, as well as low standard deviations over the whole analyzed period.

Figure 3: The boundaries of the sustainability and dysfunctional zones for the demographic factor of VFD regions.

Figure 4 shows the sustainable and dysfunctional condition boundaries of the economic system for the studied areas. Since the standard deviations are small, the gradation boundaries in terms of dysfunctionality are close to each other. The highest values on the chart correspond to the highly sustainable condition of the system as they symbolize economic growth. Thus, highly dysfunctional condition is identical to the economic recession (crisis).

Figure 4: The boundaries of the sustainability and dysfunctional zones for the economic factor of VFD regions.

Conclusion

Tables 2 and 3 present the distribution of the actual values of the sustainable development factors of the VFD regions relative to the calculated boundaries of sustainable and dysfunctional conditions. Since the presentation of all results for the analyzed period in tabular form will be capacious enough, we give the calculations data corresponding to the beginning of the concerned period (2000) and the end of the period (2014).

Table 2: The distribution of the actual values of the sustainable development factors of the VFD regions in 2000^*.

Table 3: The distribution of the actual values of the sustainable development factors of the VFD regions in 2014^*.

It turned out that according to all social ecological economic system parameters, in the year of 2000, Udmurt Republic and Perm Territory fall within the sustainability zone. Here environmental and demographic factors fall within the low sustainability zone, while in terms of economic development they can be attributed to the moderately sustainable regions. In other words, these regions are conditionally prosperous (sustainable) as of 2000. According to all system indicators, Kirov Region and Ulyanovsk Region fall within the dysfunction zone, thus as of 2000 they are recognized as conditionally dysfunctional.

In 2014, there are no regions in the Volga Federal District, which can be attributed either to sustainability or dysfunctional zones depending on the whole set of parameters. Based on just one parameter, only Mari El Republic falls within the boundaries of high dysfunctionality zone. In the Republic of Bashkortostan we observe population growth that corresponds to sustainability conditions, though there is an increase in mineral production rate that bring up to date the issue of environmental sustainability. In Mordovia, population is falling each year that exacerbates the problem of under population. This is evidenced by the dysfunctional status of a demographic parameter. Besides, there is also increase in the anthropogenic load on the natural environment. In the Republic of Tatarstan, Udmurt and Chuvash republics, there has been a sustainable growth in population of these regions, though economic growth rates are below the mathematical expectation. The population of the Perm Region increases and this is accompanied by its welfare gain, though this situation is in no small measure associated with the energy and raw materials economy, as evidenced by the environmental factor, which is within the dysfunction zone. While in 2000 Kirov Region was considered in general as a conditionally dysfunctional region, its mining performance corresponded to the principles of sustainable development. The condition of the Nizhny Novgorod Region has worsened: while in 2000 it was characterized by the highest environmental sustainability, in 2014, the production life index of mineral resources moved into the dysfunction zone. Demographic factors in Orenburg, Penza and Ulyanovsk regions are characterized by population decline. The lowest economic growth rates corresponding to a dysfunctional condition (low zone) are typical for Orenburg, Samara, Saratov, and Ulyanovsk regions.

The measure of dysfunctional condition includes the values of the criterial assessment indicators and shows the deviation from the chosen criterion that allows drawing conclusions about the degree of sustainability (prosperity) or dysfunctionality of the habitat. The proposed method can be positioned as a way to find and correct dysfunctional regions and, consequently, to define the proper response tools. Thus, the calculation of the dysfunction allows formalizing and determining the level of compliance of the conditions for achieving sustainable social ecological economic development. The calculation of the dysfunction would be useful for evaluating the actual condition and predicting the possible development for both dysfunctional and relatively sustainable regions.

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