3.1. Analyzing the Theoretical Features of the Bioeconomy, Green Economy and Circular Economy in Terms of Sustainable Development of the Russian Arctic
The declarations of the UNO summits, scientific papers, conference reports and other works lack any convincing proof of the practical use of sustainable development (or, which is more obvious, inclusive and sustainable development [
46] for business). At the same time, along with the opportunities that are so good for sustainable development, there is a point of doubt, skepticism and criticism [
26,
47,
48,
49]. It is not necessary to consider the “dark side” of sustainable development [
50]. It is possible to find a far more precise and “wise” judgement about sustainable development among the general public in [
37] (p. 1): sustainable development is the term that everybody knows, but nobody knows what it means (anyway, it sounds better than “unsustainable development”). A civilized human being wants to have essential resources such as clean air, spring water and organic food. At the same time, he or she is also willing to use the fruits of modern civilization, such as, for example, the internet, TV, air travel, videogames, mobile digital devices, etc., whose production damages the environment and limits the consumption of clean air, spring water and organic food, necessary for quality life. Not touching upon the fundamentals of today’s socio-economic systems, we need to pay attention to new economic models, which, in our opinion, reflect the objectives of the practical implementation of sustainable development. Such new economic models include the bioeconomy, the green economy and the circular economy.
The bioeconomy can be defined as an economy where the main building blocks for materials, chemicals and energy are obtained from renewable biological resources [
51]. The bioeconomy is seen as a “greener” alternative to previous unsustainable models of economy, where resources (materials, chemical substances, energy) are presented by renewable biological resources, such as genetic resources, organisms or their parts, populations, or any other biotic components of ecosystems, which have real or potential value for humankind. The conceptual grounds of the bioeconomy are presented as a new epistemic paradigm inextricably entwined with sustainable development [
52]. However, in comparison with the green economy, the bioeconomy in the Arctic should be seen as a narrower domain, where the concept of sustainable development can be put into practice. This happens thanks to the contrasting of the scale of activity of animated and inanimate nature in favor of the latter due to the harsh climate. The main difficulty in developing the bioeconomy in the Arctic, we believe, is the natural essence of the value carriers in bioeconomic systems, which create a set of obstacles in bioeconomic supply chains (extraction/production, processing, transportation, storage of biological objects). Differently from the obstacles for the development of the bioeconomy in Europe [
53], they have to consider the harsh climate and excessively long supply chains as the major serious handicap to the growth of the bioeconomy in the Arctic.
Talking of the prospects of the model of the green economy in the Arctic, above all, it should be mentioned that politics has had a considerable influence on this matter [
54]. This phenomenon is demonstrated in the form of the trajectory of the upper gray graph in
Figure 2. Then, content analysis (
Section 2) shows that the number of papers discussing “green” economy or its goals is much greater than the number of articles suggesting methods for building the green economy. Moreover, it is possible to see direct contradictions between the socio-economic goals of the green economy and the constraints for building this economy (
Table 1). What is more, the concept of the “green” economy itself is sometimes criticized as an inadequate response to the unsustainability and inequality that appeared at the previous historical stages of capitalism [
55]. At the same time, it is worth highlighting the very rational approach of the EU towards the green economy, which includes the following vectors [
56]: (1) using technological, organizational and social innovations; (2) resource efficiency; (3) waste treatment; (4) managing water resources; and (5) maintaining the sustainable system of consumption and production. Transferring from the common issues of the green economy in today’s world to its implementation in the Arctic, we should note that the ambitious plans of sustainable development in the Russian Arctic also demonstrate the features of the green economy [
57]. Here, the “green” political motive of sustainable development prevails too, defining the objectives, rather than the methods of pursuing the Russian Arctic policy.
The concept of the circular economy offers business new opportunities in the Arctic. The circular economy is usually presented in the light of the economy using the so-called 5R mnemonic (reduce + reuse + renovate + repair + recycle) [
61,
62] (
Figure 3).
A good metaphor for demonstrating the circular economy is a live cell, which through effective metabolism processes many materials inside the cell wall and reduces exchange with the external environment [
63].
The circular economy, the idea of which comes from nature itself, where, for example, food chains or natural water circulation can be the prototypes, implies that the practices of enterprises and households are transferred to create a sustainable system of production and consumption. This is the reason why a couple of definitions—industrial symbiosis [
64,
65] and socio-economic metabolism [
66] (pp. 9–10), which are so popular in discussions about the matters of the circular economy—have been borrowed from the discipline of nature. On the way to the conceptualization of this rather new model of the economy, the authors of the study present their own generalized definition (
Table 2) for better understanding the major problems of the circular economy. In turn, analyzing
Table 3, it is seen that the concept of the circular economy can be applied to the Arctic regions and is not limited by the nature of value (product/service) carriers.
On the one hand, when the two concepts of the bioeconomy and circular economy are compared, there is evidence [
45] that both of them consider development based on economic growth. On the other hand, they reasonably point out [
67] that the concept of the bioeconomy is not about being directly cyclic or resource efficient, but focuses mostly on substituting non-renewable sources of energy for renewable ones. Consequently, both concepts have their own problems in terms of coordinating reliability with sustainability [
67] (p. 13), and they do not compete with each other.
It has been mentioned multiple times [
68] that the concept of circular economy is still open for interpretation. However, the same author [
68] came up with such a good definition of the circular economy model, which is aimed at using resources efficiently through minimizing waste, long-term protection of value, reduction in primary resources and a closed cycle of products, parts of products and materials in the field of conservation of the environment and socio-economic benefits, that we are ready to accept this definition à la lettre.
The general model of the circular economy can be presented as a complex combination of related closed and semi-closed circuits of material flows distributed between production units, social/state organizations and households. Finally, when the above flows lose any of their value in the near future, they end up in dumps and landfills, which totally contrasts with the traditional model of the linear economy (take–make–consume/use–dispose). The main principles of the circular economy (
Figure 4) were laid down in the first report of the Ellen McArthur Foundation [
70] in the following way:
- (1)
“Proper design” that puts forward solutions that exclude waste from being buried in landfills, helping to preserve natural resources due to the regulated consumption of limited stock and focusing on renewable resources;
- (2)
Defining two classes of materials (“technical” and “nutrients”) and two types of circulation, respectively: (a) sharing, restoring, reusing and recycling of technical materials, and (b) bringing nutrients or biological nutrients to the biosphere or their cascading for subsequent reuse;
- (3)
Increasing the efficiency of the system due to identifying the factors negative for humans/nature, using renewable sources of energy and reducing the consumption of fossil energy.
The principles of the circular economy are quite well discussed in the available academic papers, reports and even textbooks. Transferring from the linear model of the economy to the circular one is a very complex problem that has no comprehensive practical solution and is not resolved completely on the conceptual level [
73]. The number and details of the main principles that we mentioned above vary from author to author, from 3 to 7. However, four principles [
74] (p. 15)—(1) waste equals food; (2) resilience through diversity; (3) energy from renewable resources; and (4) think in systems—are found in the so-called [
75] “butterfly graph”, either explicitly (1 and 3) or implicitly (2 and 4). The five-principle variant [
76] is different from the previous one due to the lack of the explicit (4). The following system consisting of six principles [
77]—(1) prompt thinking; (2) innovation; (3) management; (4) cooperation; (5) value engineering; and (6) transparency (a relative novelty, in our opinion)—are marked in bold. The search for these principles will stop at the “lucky number”, seven [
78], and just list them:
- (1)
Correcting the inputs in the system according to the regeneration rates;
- (2)
Correcting the outputs of the system according to the consumption rates;
- (3)
Closing the system;
- (4)
Maintaining the value of the resources in the system;
- (5)
Diminishing the size of the system;
- (6)
Designing the system completeness;
- (7)
Learning the system circularity (pay specific attention to this principle).
Finally, the biggest number of principles of the circular economy (31 items, sic), grouped into six “convergent” sets [
79], where “products and services” look relatively new, proves the exceptional difficulty of the research subject. The results of the SWOT analysis are the most interesting. In order to obtain a more diverse picture and understand the idea of the circular economy with the use of various approaches, as well as to evaluate the relatively low level of its current conceptualization, we present
Table 4 (the order of the concepts is from top to bottom, which corresponds to the time they appeared).
Technically, the general task of designing and building the circular economy looks similar to an old transportation problem [
80]. However, it is complicated due to the scale of applications, the number of involved subjects and the host of conditions and trends in the logistic chain. For example, the general material flow of the logistic chain, measured in MT*mile, must be minimized; the number of participants in the logistic chain, where waste of the previous production unit are the expandable materials of the further production unit, must be maximized; the reverse logistics must tend to zero flow, etc. The complexity of the problem of building the logistic infrastructure in the Arctic [
81] and further distribution of logistic flows according to the circular economy model calls for digital modeling and flexible management. Consequently, such a great many problems to be solved for dynamic monitoring of the hypothetical Arctic circular economy must have a powerful digital support [
71,
72]. This conclusion is consistent with last year’s research of the modern state of the circular economy [
82] (pp. 29–31) [
83], which lists eight digital technologies needed for the concept of the circular economy: (1) artificial intelligence (AI); (2) Internet of Things (IoT); (3) additive production/3D printing; (4) robotic technology; (5) blockchain; (6) drones; (7) virtual reality (VR); and (8) augmented reality (AR). All of them are switched to digital transformation and can be integrated via the existing and designed digital communication networks (
Figure 4 “Red Cloud”) to monitor and manage a diverse group of objects/processes for the implementation of the concept of the circular economy.
At the end of this section of the article, a rough visualization of the intersection between the subject areas of concepts such as bioeconomy, green economy and circular economy is presented (
Figure 5). The concept of the green economy is probably popular due to its fame in political circles. In addition, most of the characteristics of the bioeconomy (for example, renewable sources of energy, biodegradable packaging) are included in the concept of the green economy. In turn, the circular economy relies on the principle of the food chain. It is enough to read carefully the papers of the recent (year 2021) collection “Sustainable Development” [
98], to make sure that all the three concepts are closely related. However, following from the organizational standpoint, it is the principles of the circular economy that organically fit in the mechanisms that are needed to implement the concept of sustainable development in the Arctic.
3.2. Resolving Practical Consumption Problems in the Russian Arctic in the Context of Sustainable Development: Creating Vertical Agricultural Farms
The most acute problem in reclaiming the Russian Arctic is to ensure food security for the population. The climatic conditions in the Arctic, the lack of local food production facilities, the delivery of food using complex supply chains and the costly food basket have always negatively affected the physical and mental health of the public. The food basket is expensive in the Northern regions of Russia because groceries are imported into the region along the Northern Sea Route during the period when navigation is possible. Food security is a situation when all people can have access to a sufficient quantity of safe and nutritious foods at any time to meet their dietary needs and dietary preferences, so as to enjoy an active and healthy life [
99].
The northern and Arctic regions of Russia still cannot offer a vitamin-rich diet to the population due to the lack of fresh vegetables and herbs [
100]. Importing from the southern regions of Russia and from abroad can hardly be seen as a satisfactory solution, neither in terms of quality (too long a supply chain) nor in terms of price (in the case of air transportation). Solutions should be looked for directly in the Russian Arctic. The article presents an example of how the principles of bio- and green economies can be integrated into the structure of the food chain of the circular economy [
101]. It is the Arctic vertical agriculture [
102] in the regions where hydrocarbon resources are extracted.
Dickson D. Despommier originally saw the benefits of vertical farming [
103] as a world full of skyscrapers with several levels that would grow crops continuously throughout the year. In addition to creating a large amount of farmland on one ground level, this world of vertical farming was meant to reduce the transportation costs and carbon emissions caused by the need to ship groceries over long distances. It would also reduce the food spoilage that inevitably occurs during transportation. Introducing his innovative concept, Dickson D. Despommier set out several reasons why vertical farming could become very attractive to policymakers: year-round production of agricultural crops; higher yields (six times or more), prevention of drought, floods and pest control; recirculation of water; restoration of eco-systems; reduction in pathogens; provision of energy systems thanks to methane built up from compost; less fossil fuels as tractors; agricultural machinery and shipping would not be needed; and new jobs would be created [
103,
104,
105]. Moreover, completely fantastic horizons would open up thanks to the progress in space research; a closed environment would, probably, be suitable for transforming new food products into other planetary conditions in the context of space exploration [
106]. The declared advantages of vertical farming can be categorized and generalized in terms of economic, environmental, social and political aspects [
107,
108].
The economic benefits of vertical farming are multiple and include the prestige of marketing premium CGG food products with high export sales potential and a lower cost base because there is flood, drought and sun damage protection. In essence, no special requirements are imposed on fertilizers, herbicides or pesticides. When hydroponics are used, no soil is needed, just nutrients and water. There is no need for long-distance transportation since production is local and no agricultural machinery such as tractors, trucks or harvesters are needed. There are no seasonality issues because crop production is continuous, occurs year round and can be programmed to meet demand. Economic benefits can result from redistributing large rural farms to generate energy from solar and wind sources. Vertical farming can provide a competitive edge by combining extensive research and development with farming expertise, big data and modern technology to increase productivity.
The environmental benefits would be significant, including a supply of food that is healthy, organic and free from chemical contamination. Fossil fuels would sharply decline in use because transportation from rural areas to the urban customer base would not be required. Burning fossil fuels could be minimized if solar panels, rooftop wind turbines and storage batteries were used. This would lead to lower carbon levels in eco-systems. There would be more fresh water due to the evaporation of “black and gray” water, while water resources would be conserved. Additionally, there would be a potential for the national eco-system to regenerate if rural lands were reclaimed for green vegetation. Additionally, most importantly, vertical farming would support environmental sustainability.
The social benefits would be also numerous, as vertical agriculture provides new jobs in biochemistry, biotechnology, mechanical engineering, agriculture, construction, technical maintenance, as well as new opportunities for research and development aimed at improving and enhancing the technology. Increased productivity could lead to lower food production and energy costs and generate higher revenue. The surplus of apartments in high-rise buildings and warehouses that are not used could be reduced by using empty buildings for multi-story farms located close to their consumers and, thus, abandoned areas could be regenerated. The social benefits derive from the fact that the vertical farming model would help solve the problem of social isolation in remote rural communities by retraining workers and teaching them how to use vertical farming technologies locally in the cities and towns where they live.
The political benefits of vertical farming would mean that commitments to fight climate change would be easier to meet, while new technologies would support the adaptation and mitigate harmful effects. The technological approach that uses a closed system would maintain bio-security due to effective protection against aggressive pest species. A distributed network of vertical farms would face fewer risks of power cuts, being less dependent on a few large power plants that can be vulnerable to earthquakes or terrorist attacks.
Despite the many advantages of vertical farming, disadvantages are also there. Despommier’s original vision of vertical farming [
103] is criticized because the range of crops suitable for this business model is limited, including mostly plants such as lettuce, strawberries and tomatoes. Only a small proportion of the population can be served in this way and at the same time energy costs are high. Stan Cox [
109] argued that only the plants at the top level would really benefit from solar radiation in a greenhouse environment, while the energy supplied by photovoltaic systems would be limited because plants cannot be stacked in vertical layers. Stan Cox’s arguments have become less powerful due to constant advances in the technology. For example, solar panels are now more efficient in generating energy and exposure to light is less expensive because new low-cost and energy-efficient LED lighting is available. Additional exposure to light is possible when layers of plants are rotated one above the other inside a high-rise building. The cost of batteries is going down quickly. New LED sources significantly increase the yield in greenhouse conditions because the spectral characteristics can be coordinated with the type and physiology [
110]. More specific problems of vertical farming are about dealing with irregularities in the rural sector, attracting investment capital and training skilled manpower. As Kurt Benke and Bruce Tomkins [
111] have shown, for a hypothetical 10-level vertical farm, “infrastructure depreciation and improved productivity will eventually lead to parity with the annual running costs of outdoor agriculture, but it is not clear when this will happen. If the yield per hectare for indoor farming is much higher than rural outdoor farming, perhaps as much as up to 50 times, this factor will eventually outweigh the initial cost of land acquisition. The break-even point is the number of years from startup, and this will largely determine when the availability of CGG food is not hampered by the cost structure. In the case of Victoria, comparing the previously stated urban and rural prices, and assuming 50-fold improved productivity, the break-even point may well be an estimated 6–7 years” [
111], p. 21.
Potential problems for organic farming include EU Regulations (Directive 834/2007 and EU Directive 889/2008), which include the current requirements for the production, processing, sale and import of organic food within the European Union. To ensure that organic products produced in non-EU countries also meet the requirements of these regulations and undergo controls comparable to European requirements, it is necessary to follow the control method for imported products.
Figure 6 shows a schematic solution to the food security problem in the Russian Arctic using vertical greenhouses.
It is true that the Russian Arctic has lots of locations with oil and gas enterprises. Therefore, the solutions with vertical greenhouses, which could also be called a multi-chain system of sustainable consumption and production [
34], can be useful for supplementing the daily menu of people working in the Arctic and their families. Vertical greenhouses offer the following advantages: (1) no logistic risks (such as delayed delivery and/or damage or loss of cargo); and (2) minimized production costs due to cheap production resources (natural gas can be used as the main source of energy practically free of charge; waste processing [
112] instead of using fertilizers; sea containers can be reused/reconstructed instead of delivering special structures; new jobs are created). The market offers small gas power-generating units (<1 MW) [
113], which are good for supplying container greenhouse modules with light and heat.
Maintaining the sustainability of the Arctic ecosystem is a must for the sustainable development of both Arctic territories with sparse population [
114] and the entire Arctic region, which needs a long-term comprehensive sustainability policy.
The statement [
115] that the governments of the North European countries have not been able to effectively address the factors that end up in unsustainable consumption and production patterns can be especially true in the case of the Russian Arctic. These include lack of commitment, prices that do not factor in true resources, environmental and social costs and limited shell life, slow transition to greener business models, limited incentives to prevent waste through reuse and other ways and no sustainable alternatives to heavy consumption [
116,
117]. Finally, the Arctic, as a remote and still relatively underdeveloped region that has no deep-rooted patterns of unsustainable consumption or a complex supply system, has fewer obstacles to reaching SDG 12 than the central and more densely populated regions with traditional consumption.
Let us consider a simulated project of vertical farm technology to be introduced in the Russian Arctic, using the example of a vertical lettuce farm. The vertical lettuce farm is going to be located in the Yamalo-Nenets Autonomous Okrug. It is a multi-level farm with a cultivation area of 4000 m
2. At the same time, the area of the premises is 1000 m
2 and the ceiling height must be at least 5 m. The number of workers is about 25 people. The production capacity is 10,000 kg per month (
Table 5).
The main elements of the vertical farm are:
- -
Multi-layer iron structures;
- -
Equipment (LED lighting and power supplies for lamps, a solution unit, industrial osmotic water treatment plants, trays and covers for them, IoT sensors, surveillance cameras, etc.);
- -
A germination chamber;
- -
Consumables (seeds, peat, fertilizers, cups, etc.).
A graph is a visual image that offers the best insight into creating a vertical agricultural farm. A graph is one of the flexible mathematical objects that can easily be adapted to any specific model of a vertical farm.
To present the life cycle of a vertical lettuce farm in the form of a graph, the following stages of the cycle have been considered: R&D; production; and commissioning.
Table 6 includes the specification of the tasks of the project of the alternative graph.
Figure 7 shows the alternative graph of the project of creating a vertical agricultural farm with several technical levels.
The options for carrying out the project of a vertical farm with several technical levels are presented in
Table 7.
Based on the presented project options, we will show on a graph the distribution of options depending on their cost, duration and technical level (
Figure 8). We highlight the options of the first technical level in blue, and those of the second technical level in red.
The set of effective options includes options 1 and three for technical level 1; and options 7, 8 and 12 for technical level 2.
Table 8 contains the specifications of the chosen options.
Option 8, whose specification is given below, was chosen as the project option to be implemented (
Table 9).
This option was chosen as a compromise between options 7 and 12, given the cost and duration of its creation.
Figure 9 shows the deterministic graph of the project for creating the system, based on the selected option.
3.3. Simulating the Profit Indicator of the Vertical Farm
The Arctic consumer must be provided, on the one hand, with a high-quality range of goods/services (essential for ensuring a fulfilling life and activity in such harsh conditions). On the other hand, the producer must be able to have economically feasible indicators to operate vertical farms in a sustainable way. This last condition is partially ensured by a certain profit margin. Profit is an important economic category that determines the operation of vertical farms and the prospects for their further development in the Arctic. A simulation method was chosen for a quantitative assessment of the profit generated by the vertical farm.
Simulation modeling differs from other types and technologies of modeling because it allows users to create dynamic models. Such a model is developed over time, and its status is updated either constantly or at a given frequency. Creating a simulation model implies that a set of rules is defined according to which the model will be changed over time [
118].
An important advantage of simulation models is that stochastics are taken into consideration. Any characteristic of the simulation model can be specified as a probability distribution with given parameters; for example, the duration of execution and the costs required for completing the tasks of the project. Each time the model is run, this parameter will be assigned a random value generated according to the given probability distribution. If the model is run many times, then the simulation result (for example, the execution time of a project task) can be considered as a stochastic value, a histogram or diagram can be built for it and the average value and deviations from it can be estimated. Thus, variances, reflecting the risk of overspending time or budget, can be taken into account [
119].
Modern simulation modeling uses three approaches (methodologies): discrete-event modeling, agent-based modeling and system dynamics. Each method is applied within a certain range of abstraction. System dynamics implies a very high level of abstraction and is typically used for strategic modeling. Discrete-event modeling supports medium and low levels of abstraction. Between them there are agent-based models, which can be either very detailed, when the agents represent physical objects, or extremely abstract, when the agents are used to model competing companies or state governments [
120].
The method of statistical dynamics was chosen for this work, since projecting the profit of an agricultural farm is a strategic task. The AnyLogic program was used for modeling.
The main element for modeling the profit is a diagram with drives, flows and variables. The drives characterize the state of the system. They contain the memory of the system. The model works only with a totality of objects: the individual elements contained in the drive are not perceptible. Flows represent the intensity at which these states of the system are changing [
121].
Profit can be defined as the difference between revenue and costs or the difference between the total cost of production and the value of goods actually sold. Thus, profit (P) is influenced by: X1 (revenue of the agricultural farm, RUB per month) and X2 (costs of the farm, RUB per month). Since one month is taken for one complete production cycle, the values of the factors are taken for one month. The revenue and costs of the farm also include a number of factors that can be divided into two groups: those forming the value of the price (C) for goods and those forming the demand for goods.
Table 10 contains the factors affecting the value of the price.
Table 11 presents the factors that affect the demand for the goods.
Table 12 shows endogenous variables and exogenous variables.
The connection between the endogenous and exogenous variables is shown below.
The profit is determined by formula: . The revenue is calculated using the following formula: . In order to calculate the price of 1 kg of goods, the formula below is used: . The formula for estimating the demand is: . The formula for estimating the number of customers is: . The formula for estimating the purchase intensity is: . The formula for estimating the number of purchases after watching the advertisement is: . The formula for estimating the number of purchases following positive reviews on the goods: . The number of prospects is set as equal to the size of the population in the region: The formula for estimating the costs of the farm is: .
Table 13 shows the values of the statistical variables. The presented data illustrate that the largest cost items of the vertical farm are wages, rent of the premises and electricity bills. It can also be seen that growing positive reviews bring more customers than product advertising.
The sequence of simulation based on the “system dynamics” methodology is as follows. A model named “Ferma12” was created in the AnyLogic program. The unit of model time was set as a month. The elements of modeling can be seen on the open “system dynamics” palette: drive, flow, dynamic variable, relationship, parameter, table function, cycle, copy and dimension.
The model is aimed at predicting the profit of the vertical farm. Therefore, we set the profit as a drive, with an incoming flow being revenue and an outgoing flow being costs (
Figure 10).
In the model, projecting the demand of the market, the drive-prospect goes to the drive-customer through the purchase intensity flow (
Figure 11). In other words, the purchase intensity is characterized by the number of purchases made after watching the advertisement and following positive reviews on the goods.
Having created the variables affecting the revenue and costs of the farm, we can see the model for projecting the profit (
Figure 12).
Figure 12 shows the connections between all the variables and with the flows. The blue color demonstrates the connections between the variables affecting the pricing, the green one shows the connections affecting the costs and the red one shows the connections influencing the revenue.
The polarities of the connections are indicated in the model. All connections, apart from C and c7, have a positive polarity. The positive polarity means that two elements of the system dynamics change their values in the same direction, i.e., if the value of the element from which the connection is directed is reducing, the value of the other element is going down too. In case the polarity is negative, two elements have oppositely changing values.
One reinforcing and two balancing cycles are identified in the model. The balancing cycle is designated as B, the reinforcing one as R. The reinforcing feedback occurs when the effect in the system is transmitted to the input of the system and the initial change is reinforced, leading to even bigger changes in the same direction. The balancing feedback occurs when changes in the system reduce the initial impact [
122].
The reinforcing cycle is characterized by communication. The goods purchase flow increases the number of product consumers, which raises the intensity of goods purchasing under the influence of communication with product consumers, and, consequently, increases the intensity at which goods are purchased. The balancing cycles are characterized by the saturation of the sales market through advertising. The goods purchase flow reduces the number of prospects, which, in turn, reduces the goods purchase intensity. The balancing cycles are also characterized by the saturation of the sales market due to positive reviews.
The launch of the model is characterized by the fact that it was set for the model to stop the launch after 15 years.
Figure 13 shows a graph illustrating the dynamics of profits over 15 years of operation of the vertical agricultural farm.
The profit margin as of the fifteenth year of operation of the farm amounts to RUB 12,614,122.12, at the price of RUB 68.44 for 1 kg of goods, and a number of customers equal to 388,090 people.
Based on the graph shown in
Figure 13, the agricultural farm operated at a loss for the first five years. This suggests that the demand on the market is going to be insufficient to make a profit.
According to the simulation results, the costs of building the vertical farm, with a cultivation area equal to 4000 m2 and average yield of greens being 10,000 kg, are going to amount to RUB 11,000,000.
Thus, the model demonstrates that 15 years is enough to recoup the costs of building a vertical agricultural farm in the Russian Arctic. In order to diminish the payback period, the area of the agricultural farm can be enlarged, which will lead to lower investment and operating costs per unit of cost of an agricultural product. Alternatively, the sales market can be expanded, taking into account the specifics of the territories in the Russian Arctic.