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1. Introduction

The issues of enterprise management based on the forma- tion of effective business models that are implemented using a number of balanced and well-grounded business processes are still gaining a separate relevance. The choice of an effective business model requires the use of a wide range of tools for mak- ing managerial decisions, because it affects the vital activity and competitiveness of an economic entity in the long term. At the same time, the problem arises of assessing the effectiveness of management decisions when choosing certain variations of the impact on the effective indicator. World experience shows that the modern dynamically developing market of goods and services, increased competition, low volume of innovations at enterprises lead to a decrease in the competitiveness of prod- ucts. There is an emergence of barriers in international trade, the raw material orientation of exports necessitates the search for new tools and methods for managing the innovation of busi- ness processes. One of the progressive methods of managing the manufacturability of existing business processes, which can optimize the economic and innovative activities of enterprises, will improve the competitiveness and quality of products. The business process in the field of technological innovation is of particular importance in building an effective business model of an enterprise, has its limits and is characterized by inputs

to the process, which can be the results of research and devel- opment. The process ends with results – the emergence of a new technology for the production of traditional, improved or fundamentally new products, the introduction of information systems, new energy sources, and the like.

The efficiency of business process management in the field of technological innovation at an enterprise directly depends on the quality and completeness of information used in the process of implementing a business process management system. The more factors the management system selected (developed) by the enterprise takes into account, the faster, more accurately and more adequately the management respond to changes in the external and internal environment of the enterprise.

One of the most important conditions for the activities of aviation enterprises in modern economic conditions is to provide management with effective tools for analysis and fore- casting. Aviation enterprises need to be guided by the trends of the global air transportation market with the subsequent adop- tion of management decisions based on analytical information.

Aviation enterprises must constantly use the latest innovative technologies, introduce new business processes and analyze all current activities.

That is why, the development of an integrated approach to assessing the effectiveness of the business model of an aviation enterprise based on the innovativeness of business

COMPREHENSIVE APPROACH TO THE EFFICIENCY ASSESSMENT OF THE BUSINESS MODEL OF THE AVIATION ENTERPRISE BASED ON BUSINESS PROCESS INNOVATION

Z a r i n a P o b e r e z h n a

PhD, Associate Professor Department of Economics and

Business Technology National Aviation University Liubomyra Guzara ave., 1, Kyiv, Ukraine, 03058 E-mail: [email protected]

The improvement of theoretical and methodological approaches to the formation of innovativeness of business processes of enterprises has been carried out. A model of innovativeness of business processes has been formed, which takes into account the principles, goals, methods of improving the management of business processes and the factors of influence on them.

The main directions of the formation of an effective business model of an aviation enterprise based on the innovativeness of business processes are investigated and strategic directions of its provision are proposed. At the same time, the following aspects of enhancing the innovative activity of an aviation enterprise are highlighted as: the influence of the external and internal environment, innovative activity, analysis of the innovative potential and innovativeness of business processes.

An integrated approach to assessing the effectiveness of the business model of an aviation enterprise based on the innovativeness of business processes has been formed. This approach allows to provide the necessary level of innovative flexibility of the aviation enterprise and independence in the application of innovative business processes. The author has carried out a practical implementation of the applied approach at aviation enterprises. The study made it possible to identify the most important business processes for aviation enterprises. These include: the level of support (provision) of innovation, the turnover ratio of current assets, the provision of material and technical resources. As a result of the assessment, these business processes have the highest scores (4.55;

4.43 and 4.26, respectively). The assessment of the financial stability of aviation enterprises in the market was carried out and the indicators of the assessment were calculated. An integral indicator of the financial stability of aviation enterprises has been determined, according to which the problems of the effective functioning of Ukrainian aviation enterprises have been identified. At the same time, small aviation enterprises suffer losses and are characterized by a low level of financial stability

Keywords: business model, integrated approach, innovativeness of business processes, aviation enterprise, business model of an aviation enterprise, innovative potential, business processes

UDC 330.44:005.591.6 DOI: 10.15587/1729-4061.2021.243118

How to Cite: Poberezhna, Z. (2021). Comprehensive approach to evaluation of efficiency of airline business model on the basis of business process innovation. Eastern-European Journal of Enterprise Technologies, 5 (13 (113)), 44-57.

doi: 10.15587/1729-4061.2021.243118 Received date 07.09.2021

Accepted date 21.10.2021 Published date 29.10.2021

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It should be understood that the relevant components of the business model have a great influence on the level of aviation enterprise operation. That is why, in [6], four main components are identified that affect the business model of an aviation enterprise: value proposition; market segmentation;

value chain; profit structure. However, the work does not take into account methodological approaches to determining and predicting the results of an aviation enterprise’s activities, depending on the proposed components of the business model.

In the scientific work [7] it is noted that the current level of international competition determines rather stringent requirements for aviation enterprises to create a successful business. All this allows us to assert that it is advisable to be involved in innovation and the creation of flexible organiza- tional structures. This leads aviation enterprise executives to increasingly consider reorganizing financial and econom- ic relations as a means to create competitive business models based on innovation. The implementation of innovations in business models allows for the provision of better customer service and the provision of new forms of activity.

In general, scientists pay special attention to the forma- tion, assessment, management of business processes and its components, as well as the essence of the main types of busi- ness models of enterprises, which will improve the resulting indicators and ensure the competitiveness of the enterprise in a strategic perspective. All this allows to assert that it is advisable to use an integrated approach to assessing the effectiveness of the business model of an aviation enterprise based on the innovativeness of business processes. At the same time, it is important to take into account the possibil- ities of the financial stability of the aviation enterprise and establish the level of margin for achieving the desired goal.

3. The aim and objectives of research

The aim of research is to develop an integrated approach to assessing the effectiveness of the business model of an aviation enterprise based on the innovativeness of business process- es. This will make it possible to promote the stimulation of economic activity, the growth of the competitiveness of the enterprise and its adaptation to the conditions of the external environment.

To achieve the aim, the following objectives were set:

– to consider and improve the theoretical and method- ological approaches to the study of the innovativeness of the business processes of the enterprise;

– to improve the directions of forming an effective business model of an aviation enterprise based on the innovativeness of business processes;

– apply mathematical tools to determine the stages of the approach to assessing the effectiveness of the business model of an aviation enterprise;

– assess the level of financial stability of aviation enter- prises in competitive markets and determine their competitive position.

4. Materials and methods of research

The research was carried out using the methods of sys- tems analysis and theoretical generalization, observation and comparison. These methods were used to form the concept of an effective business model of an enterprise, it is achieved in processes is gaining relevance. After all, it is the application

of this approach that allows to determine which business processes affect the activities of the aviation enterprise and which it is better to abandon, or reorient your activities.

2. Literature review and problem statement A great contribution to the creation of a scientific basis for the formation and functioning of business processes of business entities has been made in many works by both Ukrainian and foreign authors. So, in work [1] it is deter- mined that business processes at an enterprise are capable of increasing the efficiency and effectiveness of an enterprise by improving and introducing innovations. However, there is no direction for an integrated approach to solving this issue. It is also advisable to consider the features of the for- mation of individual components of the innovative potential in accordance with the conditions of the enterprise and the relationship between them in the implementation process.

In [2], it is proposed to consider business processes as activities aimed at creating a product. Businesses can benefit from providing new services or improving existing business processes. But there are still unresolved issues related to the achievement of the efficiency and effectiveness of the enter- prise, it becomes possible only on the basis of coordinated preventive actions of the management and development strategy. The option to overcome this is the flexibility of the enterprise depending on changes in the external envi- ronment, the formation of rational business plans and the presentation of effective business models.

The work [3] defines the business model as a way of doing business, functions in conjunction with innovation.

This is why businesses that commercialize new ideas and technologies through business models see them as a place for innovation. However, there is no definition of the volume of investments in the development and implementation of inno- vations and the effectiveness of the results obtained. There- fore, it is important to monitor the dynamics of performance indicators of an enterprise under the influence of changes in the business model and parameters of innovation.

The authors of the work [4] determined that the business model acts as a mediator in the process of value creation. It operates between the technical and social spheres, selects and filters technologies, transforms them into specific con- figurations that will be offered on the market. This article focuses on developing value propositions and seizing oppor- tunities for sustainable development in the long term, based on the innovativeness of the business model. However, the work does not highlight the further mechanism and limiting capabilities of enterprises to finance innovation.

In modern conditions of doing business, it is business pro- cesses that correspond to the technology of production activities, the opportunities to form an innovative enterprise. In work [5], the concept of an innovative business model is proposed, which consists in designing new or transforming existing business models. A way to overcome this can be a combination of in- dividual business processes, which depend on their efficiency and the formation of effective business models on their basis.

The study of business models for doing business by air enterprises requires an understanding of the essence of or- ganizing the air transportation itself, because it is not only aviation equipment, but also methods and methods of trans- portation, personnel, logistics, etc.

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assessing the sources of the available resources of the enterprise and the innovativeness of its development, as well as analyzing the existing business processes at the enterprise.

On the basis of theoretical concepts, an analysis was made of the possibility of their application in practice for aviation enterprise. In particular, an integrated approach was used to assess the business processes of an aviation en- terprise and their combination to determine which business processes have the greatest impact on the efficiency of the business model of an aviation enterprise.

This approach allows ensuring the competitiveness of the aviation enterprise and determining the level of financial stability in a changing external environment.

5. Results of the study on the formation of the effectiveness of the business model of an aviation enterprise based on the

innovativeness of business processes

5. 1. Formation of a theoretical and methodological ap- proach to the study of innovativeness of business processes of an enterprise

An enterprise as an open economic system has many in- terrelated processes that, by their functioning, determine its state and development prospects in the future. The processes occurring within the enterprise are interconnected and the

general condition of the entire enterprise directly depends on them. In today’s changing external environment, enterprises should use an innovative way of development, because it is the principle of innovative management based on the effec- tive application and implementation of business processes that allows them to adapt to changes. Achieving the desired synergistic interaction between the strategy and the financial goals of the enterprise is one of the areas of innovativeness of business processes as a component of enterprise management as a whole. That is why it is optimal to ensure the efficiency of business processes of an enterprise and to attract modern information technologies, which will allow rational use of time when describing the relationship between the results of business processes and the costs of achieving them. Thus, to ensure the innovativeness of the business processes of an enterprise, it is necessary to take into account the principles, goals, methods of improving the management of business processes and factors influencing the innovativeness of busi- ness processes. It should be noted that the issues of business process management arise sharply at the enterprise, when at a certain stage of its development there are disruptions in the work of departments and production. If they are of a regular nature and significantly affect the efficiency of the enterprise itself, it is necessary to quickly respond to them. With this in mind, Fig. 1 shows a model of the formation of innovativeness of business processes of an enterprise.

Principles - minimal typification of

processes;

- autonomy of business processes;

- unified control over business processes;

- simplifying the consistency of the execution of functions

Goals - optimization of the

organizational structure;

- minimization of expenses;

- reduction of losses of working time;

- improving the quality of products (services)

Methods - continuous

improvement of business processes;

- reengineering of business processes;

- methods of rapid analysis;

- benchmarking

contributing factors -

- -

Innovation of business processes of the enterprise

influencing factors - emotional and

cognitive;

- technological;

- consumer;

- material and technical Business

process creation (ideas)

Analysis of feasibilitythe

innovative

support Enterprise implementation

Promotion

Strategic directions for ensuring the innovativeness of business - Strategic directions for ensuring the innovativeness of business processes - the formation of new competitive advantages;

- creation and implementation of innovations at all stages of enterprise development;

- technological modernization of the existing infrastructure of the enterprise;

- creation and implementation of an innovative development program financial income

-

financing of innovative projects;

intellectualization of assets;

personal competencies;

f und f or support of innovative developments

Fig. 1. The model of the innovativeness formation of enterprise business processes

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In order to ensure the innovativeness of business processes at the enterprise, it is proposed to apply a theoretical and meth- odological approach to improve and implement business pro- cesses. This approach allows to diagnose the existing business processes of the enterprise and establish qualitative and quanti- tative characteristics that determine the degree of management and functioning efficiency. It also allows continuous improve- ment and optimization, therefore it is very important to form a system for improving the business processes shown in Fig. 2.

The first stage consists in analyzing the existing business processes in the enterprise, at the second stage, an assess- ment of opportunities and problems in existing business processes is carried out. At the third stage, there is a process of improving business processes and the implementation of the proposed activities, at the fourth stage – control over the implementation of the proposed activities to improve business processes.

The effective formation of the innovativeness of business processes at the enterprise is proposed to be carried out in the following ways:

– selection of the most promising innovative business projects;

– differentiation of criteria for the selection of invest- ment business projects;

– ensuring the compliance of the proposed investment business processes with the production and financial poten- tial of the enterprise;

– ensuring the consistency of investment business pro- cesses for the most important indicators of the enterprise.

5. 2. Directions of the formation of an effective business model of an aviation enterprise based on the innovativeness of business processes

One of the key points in shaping the business model of an enterprise is identifying sources of sus- tainable competitive advantage that will create max- imum value for consumers. The successful commer- cialization of new technologies also depends on the business model in which they are brought to market.

The dynamic development and trends of business intellectualization, the increasing role of innovation in increasing the competitiveness of the enterprise should have a comprehensive impact on the develop- ment of the enterprise, therefore, building an effective business model covers all aspects of enterprise man- agement. As a key component of an effective business model are business processes, which should be based on an innovative aspect. Innovative business prac- tices involve the use of radical and open innovation.

Aviation enterprises that enter the market with inno- vative business processes and appropriate competitive strategies have significant market advantages and can set their own rules with a strong competitive edge over competitors. The business model of the aviation enterprise must ensure a systemic combination of goals and business processes with the realities of the external environment, which is changing insidiously and rapidly.

The business processes of the aviation enterprise are very diverse and rather complicated, thanks to which the aviation enterprise can operate successfully and meet the needs of customers. In today’s environ- ment, the overall business model must change in line with the rapid changes in the market environment.

This requires managers to analyze, check, improve, and sometimes reorganize business processes in order to achieve even greater efficiency. At the same time, you need to focus on what is the specificity of a given aviation enterprise, on which customers it focuses, in what geographic areas it operates. This is what will allow you to achieve the best effect, that is, focusing on those basic elements of business processes that can bring maximum results. An important issue remains the correct distribution of business processes into elements and the definition of their individual components from the point of view of the possible process of their modeling and presentation in the form of an interconnected structure.

Modern directions for the development of effective en- terprise activity require a rational choice of ways to manage business processes. Monitoring the economic sustainability of business processes of an enterprise consists in tracking in- dicators of economic activity aimed at timely identification and early prevention of problems, as well as deviations from their criteria [8].

To implement an effective business model of an aviation enterprise, it is necessary to:

Analysis of existing business processes at the enterprise 1. Research of all available business processes.

2. Formation of indicators for assessment.

3. Diagnostics of the state of research of business processes.

Stage 1

Assessing opportunities and challenges in existing business processes

1. Identification of business processes that provide the largest number of key success factors.

2. Assessment of business process management capabilities.

3. Identification of problems of business processes and reserves for their improvement.

Stage 2

Improvement of business processes and proposed activities 1. Development of goals for improving business processes.

2. Development of directions for improving business processes.

3. Calculation of integrated indicators of the proposed.

Stage 3

Control over the implementation of the proposed activities 1. Checking the planned goals.

2. Identification of untapped opportunities for effective business process management.

3. Adjustment and clarification of directions and measures for improvement.

Stage 4

Fig. 2. Theoretical and methodological approach to improving the innovativeness of business processes of an enterprise

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1. Determination of new key factors of success, which are determined when assessing the internal environment of the enterprise, its internal potential.

2. Development and provision of innovativeness of busi- ness processes.

3. Increasing the innovative activity of the enterprise, which manifests itself in the main activities of the aviation enterprise: the purchase of air tickets is carried out via the Internet, the technological update of aircraft, the provision of additional services for passengers, etc.

4. Assessment of the strategic analysis of the innovative potential of an aviation enterprise necessitates an analysis of the strengths and weaknesses of its activities, an analysis of the innovation climate and goals and trends in the develop- ment of the air transport industry.

Sustainable development of an enterprise is characterized by the ability to carry out continuous economic activities at any time in conditions of uncertainty of environmental im- pact. The implementation of measures for the sustainable de- velopment of the enterprise has a number of economic, social and environmental directions. So these areas include:

– increasing the level of enterprise management;

– opening up new market opportunities;

– growth of the investment attractiveness of the enter- prise;

– innovative approach to the development of goods and services;

– minimization of risks;

– improving the efficiency of resource allocation and reducing costs.

However, to ensure sustainable development of the en- terprise, there are a number of problems that need to be addressed through monitoring, reengineering and redesign of existing business processes [9–11].

Fig. 3 shows the system of forming an effective business model of an aviation enterprise based on the innovativeness of business processes.

Thus, the successful implementation of the business model of an aviation enterprise makes it necessary to har- monize the use of innovative business processes, analysis of the external and internal environment of the enterprise and strategic analysis of innovative potential.

Fig. 3. The system of forming an effective business model of an aviation enterprise based on the innovativeness of business processes

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Thus, any enterprise that plans to develop or survive in a dynamic environment has to face constant change as its ability to continue to operate is under threat. In such cases, the modern economic environment for most enterprises is forced to become flexible, constantly react to changes in the external environment. To develop and implement various lo- cal and global projects of changes in their business activities should be developed without loss of control [12].

It should also not be forgotten that investments play a crit- ical role in ensuring the innovative potential of an enterprise.

There are several factors that characterize the investment attrac- tiveness of an enterprise. Among them, one can single out the stability of the financial condition and the level of financial in- dicators, the competitiveness of products, the degree of riskiness of investments, as well as the existing potential for expanding innovations. Investments play an important role in the develop- ment of the enterprise, which means that they will contribute to its development and improvement, as well as the overall improvement of the innovation climate in the country [13].

5. 3. Mathematical tools for applying the stages of the approach to assessing the effectiveness of the business model of an aviation enterprise

Choosing an effective business model for an aviation enter- prise in the face of uncertainty requires the use of a wide range of decision-making tools, among which methods of data mining or data mining stand out. These methods are based on the provisions of the theory of fuzzy sets, including using the fuzzy inference algorithm, which consists of the following stages [14]:

1. Stage 1. Formation of a set of input linguistic variables:

( )

= *1 *2 *

* , ,..., n ,

Х х х х (1)

where x1, x2, …, xn – the name of the incoming linguistic variables 1, 2 ... n – the ordinal number of the incoming variable.

2. Stage 2 is fuzzification, that is, the formulation of membership functions for the terms of all input variables, the compilation of logical rules for fuzzy inference and determi- nation of the weight of each rule.

According to [15], if to denote the membership function of the i-th input fuzzy variable хi) from the interval х хi, i to j-th fuzzy term as tij for the input variable or dij for the output variable. Then the fuzzy term-set can be specified as a definite integral bounded by the function x to some fuzzy membership set μj(xi) on the segment х хi, i, where хi – the left bound- ary of the interval, хi – the right boundary of the interval.

In this study, let’s use membership functions of the Gaussian type, corresponding to the normal distribution density of the data [16]:

( )

⋅

µ =

1 2

2 ,

х b

х е c (2)

where b – coordinate of the maximum of the membership function, c – concentration coefficient of the membership function, which is determined based on the distribution of the attribute in the general population.

The fuzzy knowledge base also contains a set of rules that are specified by fuzzy term sets [15]:

 = Θ 

= Θ Θ = α⇒ =

 

 =

  

1 1 2

2

... withweight ,

j j

j

j j j n nj j

x t x

t x t y d

=1, ,

j m (3)

where t t 1j, ,...,2j t – value of the input linguistic variable, j – nj ordinal number of the linguistic term, y – name of the output linguistic variable; d – value of the output linguistic vari-j able; θj – one of two possible logical AND or OR operations.

The measure of fulfilling the premise of each rule for a set of input variables:

( )

( ) ( ) ( )

( )

µ =

= µ 1* Θ 2* Θ Θ *

*

... ,

j

j j j j j j j n

X

w x w x w x j=1, ,m (4)

where wj denotes the significance of the j-th rule in the fuzzy knowledge base.

3. Stage 3 “Logical inference” [15]: the measure of the truth of the conclusion of each of the rules of the created knowledge base is determined by prod-activation. It occurs by identifying the membership function of the j-th term of the output vari- able (μdj(ω)), taking into account the degree of truth of the premise of each rule for the vector of input variables (μj(X*)).

4. Stage 4 “Composition” –fuzzy terms of the output variables are combined by aggregation (agg) according to the maximum operation [15]:

( ) ( )

ω = аgg d d 1*, ,...,2* d*m =max d d 1*, ,...,2* d*m , (5) 5. “Defuzzification” stage, as a result of which a set of fuzzy inferences turns into a crisp number based on the Su- geno algorithm, which involves the use of one of two types of fuzzy inference rules:

a) the original variable is calculated as the linear de- pendence of the output variable on combinations of input variables [17]:

ω = ε × +1 x1 x2× + + ε ×u2 ... n x n, (6) where x1, x2…xn – the quantitative values of the linguistic variables; ε1, ε2…εn – weight coefficients of the correspond- ing equations;

b) the original variable is defined as a constant [17]:

ω=γn, (7)

where yn – the constant value of the output variable.

The given algorithm of fuzzy inference may be appro- priate for determining the stages of an integrated approach in solving various problems in the field of economics and enterprise management, since it shows the influence of each parameter of the business model of an enterprise in various sectors of the economy [18].

According to the approach: financial result, profitability and performance indicators are indicators that accumulate the results of various types of activities of enterprises for the previous period. And in accordance with this, they can serve as indicators that signal a successful or unsuccessful choice of a business model by an enterprise.

The software implementation of fuzzy inference was carried out using Matlab (USA) using the Sugeno fuzzy inference algorithm.

The resulting indicator is proposed to determine the coef- ficient of operational efficiency (y). This indicator is defined as the ratio of net income from the sale of products, goods, works, services (NI) to the cost of sales of products, goods,

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works, services (Cost). This indicator has less variability than the profitability indicators, but at the same time it accurately reflects the effectiveness of the business model chosen by the aviation enterprise.

Stage 1. It is assumed that the effectiveness of the chosen business model of the aviation enterprise “γ” is formed as a result of the following factors:

– x1 – motivational and managerial component or the level of material incentives to motivate personnels. It is a generaliz- ing value of the ability of an enterprise to retain and develop its own workers, to provide them with working conditions. Can be described by the terms “low” and “high” level of material incentives for motivation;

– x2 – provision with material and technical resources. It has a double meaning, firstly, it shows how much material and technical resources are optimally used in the process of activi- ty. Secondly, it shows how well the company is forming assets, since if there are idle or surplus assets on the balance sheet, the indicator will be below the optimal value. Can also be described using the terms “high” and “low” logistics level;

– x3 – level of support (provision) of innovation activity.

Shows the company’s ability to switch to an innovative de- velopment model, but, as rightly noted in [19], “a high level of development of intangible assets may be accompanied by low innovation activity, and vice versa.” The indicator can be given a linguistic assessment using the terms “low” and “high” level of innovation provision;

– x4 – current assets turnover ratio. Estimated by the terms

“fast” and “slow” speed of one revolution;

– x5 – balance of the enterprise’s debt is measured as the ratio of the amount of accounts receivable to accounts payable.

Based on the considerations that a significant excess of ac- counts receivable over accounts payable, as well as its too low level, negatively affect the efficiency of the current activities of the enterprise. This indicator can be indicators of imbalance in cash flows and future destruction of progressive production activities. The level of this indicator is described using the following three terms: “insufficient”, “balanced”, “super-high”

level of receivables;

– x6 – coefficient of autonomy (the ratio of equity capital to the company’s liabilities). It shows the structure of the com-

pany’s funding sources. In the analyzed sample, the majority of enterprises have a rather low value of the indicator, which in some cases is less than zero. The reason for this is the losses incurred in previous periods, which exceeded the cost of equity capital, which indicates the extremely low financial stability of the enterprise and the high risk of loss of financial stability.

To facilitate calculations, the equity capital of such enterprises in the calculations was equated to zero, as recommended in a number of similar calculations [20]. The capital structure is assessed using the terms “equity-oriented” and “debt-oriented”.

It is proposed to determine the influence of the above fac- tors on the efficiency of an enterprise using a six-factor hierar- chical model (Fig. 4).

In order to design a system of fuzzy inference, an in-depth study of a sample of 15 observations of operating aviation enterprises for 2017–2019 was carried out, which provided a sufficient array of information.

Stage 2. A fuzzy inference system has been created by means of the Matlab Fuzzy Logic Toolbox (USA) using a fuzzy inference system of the Sugeno type, which is the result of de- signing and training a neuro-fuzzy hybrid model.

For training a hybrid network, the hybrid method was selected with an error level of 0 and the number of cycles as a result of training the network, an error of 0.1626 percentage points, which is sufficient to diagnose the effectiveness of en- terprise business models.

For the input factors x1–x6 and the initial y, the model “six inputs one output” is obtained. So, the input variables x1–x4, x6 each have two terms with the corresponding graphs of the membership functions, and the variable x5 has three.

Using the membership functions of the input variables, fuzzification is carried out, that is, the transition from the nu- merical parameters of the input variables to the fuzzy values of linguistic variables. The fuzzification stage includes the choice of fuzzy terms for linguistic assessment of influencing factors, given on the corresponding universal sets [21]. That is, mem- bership functions are selected for the terms of the variables x1–x6, which allow for any value for a number of input data to determine its degree of membership in a fuzzy set. In this case, all six input variables are assigned membership functions of the gausmf type (Gaussian function).

Effectiveness of aviation enterprise business models (y)

x1motivational and managerial component

low high

x2provision of material and technical resources

low high

x5balance of enterprise debt insufficient super-high

x4current asset turnover швидка повільна x3level of resource support for

innovation

low high

Fig. 4. Estimated terms for linguistic variables x1–x6

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Next, membership functions are formed to build a fuzzy inference algorithm, Table 1.

Table 1 Membership functions used to build a fuzzy

inference algorithm

Term Analytic expression

Variable x1 “level of material support for personnel motivation”

Low µ

( )

=  >

 ≤

2

1 1

—0.007272

1 , if 1.62

2 1.622 1

1, if 1 1.62

l ,

х ow

х

х е

х

High µ

( )

=  <

 ≥

1 2 1

—4.1452

1 , if 2.56

2 1.585 1

1, if 1 2.56

i h ,

х

g

х

h х е

х

Variable x2 “provision of material and technical resources”

Low µ

( )

=  >

 ≤

2 2—0.0341 2

1 , if 3.963

2 3.62 2

1, if 2 3.963 ,

х х

low х е

х

High µ

( )

=  <

 ≥

2

2 2

—8.48

1 , if 4.81

2 3.67 2

1, if 2 4.81

high ,

х х

х е

х

Variable x3 “level of support for innovative activities”

Low µ

( )

=  >

 ≤

2 3—0.00576 3

1 , if 3.92

2 3.863 3

1, if 3 3.92

l ,

х ow

х

х е

х

High µ

( )

=  <

 ≥

2

3 2

—9.087

1 , 5.2

2 3.88 3

1, 3 2

, if 5.

х if

g

х

hi h х е

х Variable x4 “current assets turnover ratio”

Low µ

( )

=  >

 ≤

2 4—0.01799 4

1 , if 3.72

2 3.71 4

1, if 4 3.72 ,

х х

low х е

х

High µ

( )

=  <

 ≥

2 4—8.849 1

1 , if 5.16

2 3.685 4

1, if 4 5.16

high ,

х х

х е

х Variable x5 “debt management level”

Low µ

( )

=  >

 ≤

2

5 5

—0.03313

1 , if 1.34

2 1.303 5

1, if 5 1.34

l ,

х ow

х

х е

х

Average µ

( )

=  ⋅

 ≤ ≤

2

5—3.058 5 5

1 , if 1.57 or 4.46 2 1.397

5

1, if 1.67 5 4.

, 46

х х х

average х е

х

High µ

( )

=  <

 ≥

2

5 5

—6.217

1 , if 4.86

2 1.356 5

1, if 5 4.86

high ,

х х

х е

х Variable x6 “capital structure”

Focused on equity µ

( )

=  <

 ≥

2 6—0.05259 6

1 , if 0.56

2 0.4581 6

1, if 6

,

hi 0.56

х gh

х

х е

х

Focused on equity µ

( )

=  >

 ≤

2

6 6

—0.8947

1 , if 0.42

2 0.4745 6

1, if 6 0.42 ,

х х

low х е

х

By default, the Anfis-editor add-in of the MatLab envi- ronment develops and tests fuzzy inference algorithms with rules, in which a combination of terms of input variables. It is a complete set of all possible combinations of the member-

ship functions of the input variable in the designed Sugeno system – constants. Their justification is given in combination with a description of the base of rules for fuzzy inference.

Since there are six input variables in the system, five of which have two terms, and one of them has three terms, the maxi- mum number of rules in the knowledge base for formulating all possible deposits between factors and consequences should be 3∙25=96. However, not all rules are needed to adequately reflect the relationship between inputs and outputs.

Stage 3 – inference. In the process of fuzzy logic, all calcua- lations can be illustrated in the form of a set of graphs (Fig. 5).

In the designed algorithm, for each of the 96 rules, seven graphs are built, six of which correspond to the input variables х1–х6, and one output to y. The results of activation of the rules for each of the studied indicators, having a measure of truth above zero, are displayed in yellow, and for the output variable – in blue. If the membership function has zero truth, then there is no color on the graph. The resulting graph, which determines the clear value of the resulting indicator, calculated as a result of comparing all membership functions, is placed at the end, after all the graphs of the output variable (Fig. 5).

The system of rules for displaying fuzzy dependencies between the level of enterprise efficiency and factors x1–x6

is shown in Table 2.

Table 2 A system of rules for displaying fuzzy dependencies between

the level of enterprise efficiency and factors x1–x6

No. Rule Const

1 If (x1 is high) and (x2 is low) and (x3 is low) and (x4 is low) and (x5 is high) and (x6 is borrowed)

then (output is out1mf5);

1.631

2

If (x1 is low) and (x2 is low) and (x3 is low) and (x4 is high) and (x5 is high) and (x6 is equity)

then (output is out1mf12); 0.7571 3 If (x1 is low) and (x2 is low) and (x3 is high) and

(x4 is low) and (x5 is low) and (x6 is borrowed) then (output is out1mf13);

0.8179

4 If (x1 is low) and (x2 is low) and (x3 is high) and (x4 is high) and (x5 is low) and (x6 is equity)

then (output is out1mf20); 0 5

If (x1 is low) and (x2 is high) and (x3 is low) and (x4 is high) and (x5 is high) and (x6 is equity)

then (output is out1mf36); 1.393 6 If (x1 is high) and (x2 is high) and (x3 is high)

and (x4 is high) and (x5 is balanced) and (x6 is equity) then (output is out1mf46);

1.248

7

If (x1 is high) and (x2 is low) and (x3 is low) and (x4 is high) and (x5 is balanced) and (x6 is

equity) then (output is out1mf59); 1.825 8 If (x1 is high) and (x2 is low) and (x3 is high) and

(x4 is low) and (x5 is high) and and (x6 is equity) then (output is out1mf66);

1.059

9 If (x1 is high) and (x2 is high) and (x3 is high) and (x4 is low) and (x5 is balanced) and (x6 is

equity) then (output is out1mf88); 1.156 10

If (x1 is high and (x2 is high) and (x3 is high) and (x4 is high) and (x5 is low) and (x6 is borrowed)

then (output is out1mf91); 0.7174 11 If (x1 is high) and (x2 is low) and (x3 is high)

and (x4 is high) and (x5 is balanced) and (x6 is borrowed) then (output is out1mf69);

0.3969

12

If (x1 is high) and (x2 is low) and (x3 is low) and (x4 is high) and (x5 is high) and (x6 is equity)

then (output is out1mf60) 0.5699

(9)

Achievements of effective activity are possible only if all six conditions are met, but they are not equal to each other.

The significance of individual conditions is taken into account with the help of their concentration, it is achieved by raising the membership functions of a degree equal to the weight of the condition-rule (wj). That is, the minimum value of all member- ship functions determines to what extent the current state of the enterprise will ensure the efficiency of operating activities:

( ( ) ) ( ( ) ) ( ( ) ) ( ( ) ) ( ( ) ) ( ( ) ( ) )

ω ω ω

ω ω ω

µ = µ Λ µ Λ µ

Λ µ Λ µ Λ µ

×

×

1 2 3

4 5 6

1 1 2 2 3 3

4 4 5 5 6 6 ,

eff x x x

x x x

( ( ) ) ( ( ) )

( ( ) ) ( ( ) ) ( ( ) ) ( ( ) )

ω ω

ω ω ω ω

µ = µ Λ µ

Λ µ Λ µ Λ µ Λ µ

1 2

3 4 5 6

econ.safety 1 1 2 2

3 3 4 4 5 5 6 6

min ; ;

; ; ; .

x x

x x x x (8)

At the stage “Logical inference”, the measure of the truth of the conclusion of each of the rules of the knowledge base formed on the basis of fuzzy logic means is determined. To do this, we use the data of LLC Aviation Company WIND ROSE for 2019, which was not included in the sample, and therefore its indicators can be used as control values to check the accuracy of the generated algorithm.

The surveyed enterprise in 2019 had the following indi- cators.

Efficiency of the main activity (x3)=4.16; x1 (motiva- tional and managerial component or the level of material in- centives for motivating personnels)=2.07; x2 (provision with material and technical resources)=4.26; х3 (level of sup- port (provision) for innovation activity)=4.55; x4 (current assets turnover ratio)=4.43; x5 (balance of the enterprise’s debt)=3.12; x6 (autonomy coefficient)=0.492.

Based on the determination of the degree of membership of the value of the linguistic variable to its fuzzy terms, for each of the output variables, the measure of truth of each of the logical rules is established, which ranges from 0 to 1.

Zero truth means that the value of the input vector cannot belong to this term.

Stage 4. Composition. At this stage, the fuzzy terms of all initial variables are combined to the maximum. As a result of the accumulation of sub-conclusions and rules of fuzzy sets, an accumulated membership function is obtained for each of the initial variables x-1x6. The resulting membership function for each source variable is formed by combining the functions of the original variable in accordance with the conclusions of each rule. The composition is performed for each of the factors x-1x6.

Stage 5. Defuzzification. According to the system of rules formulated in Table 2 as follows:

1. Low level of material and technical support (x2), turnover of current assets (x4) and innovative activity (x3).

Due to the balanced management of accounts receivable and payable (x5), a high level of personnel motivation (x1) and the use of primarily attracted capital as sources of financing assets (x6). This will ensure the efficiency of operating activ- ities at a level close to mf12=1.631.

2. Low level of personnel motivation (x1) combined with a low level of innovative activity (x3) and material and technical support (x2). When pursuing a flexible policy for managing accounts receivable (x5) and using primarily at- tracted capital as sources of financing assets (x6). Even with a high level of current assets turnover (x4), it cannot provide sufficient operational efficiency mf12=0.7571.

3. Low level of personnel motivation (x1), material and technical support (x2), turnover of current assets (x4). And a high level of innovative activity (x3) while pursuing a flex- ible policy for managing accounts receivable (x5) and using mainly attracted capital as sources of financing assets (x6).

This will ensure the efficiency of operating activities at the level of mf12=0.8179.

4. Low level of personnel motivation (x1) and material and technical support (x2), a strict policy for managing accounts receivable (x5), a high level of innovative activ- ity (x3). Enterprise is provided mainly at the expense of equity capital (x6), even a high level of turnover of current assets (x4) cannot ensure efficient operation. In this case, the efficiency of operating activities will approach mf20=0.

Fig. 5. Visualization of the process of fuzzy inference (fragment)

(10)

5. Low level of personnel motivation (x1) and innovative activity (x3) in combination with a high level of material and technical support (x2), turnover of current assets (x4), ac- counts receivable (x5). And the use of predominantly equity capital (x6) as sources of financing assets will ensure the ef- ficiency of operating activities at a level close to mf12=1.393.

6. High level of personnel motivation (x1), material and technical support (x2), current assets turnover (x4) and in- novation activity (x3). In combination with a balanced pol- icy of management of accounts receivable and payable (x5) and the use of primarily attracted capital as sources of financing assets (x6). This will ensure the efficiency of oper- ating activities at a level close to mf12=1.248.

7. High level of personnel motivation (x1), current assets turnover (x4) in combination with a low level of material and technical support (x2) and innovative activity (x3). Due to the balanced management of accounts receivable and pay- able (x5) and the use of primarily attracted capital as sources of financing assets (x6). This will ensure the efficiency of operating activities at a level close to mf12=1.825.

8. High level of personnel motivation (x1) and innovative activity (x3), combined with a strict policy for managing accounts receivable and payable (x5). And a low level of material and technical support (x2) and turnover of current assets (x4) and the use of primarily attracted capital as sources of financing assets (x6). This will ensure operational efficiency at the level of mf12=1.059.

9. High level of personnel motivation (x1), material and technical support (x2) and innovative activity (x3). In combination with a balanced policy for managing accounts receivable and payable (x5), a low level of turnover of cur- rent assets (x4) and the use of primarily attracted capital as sources of financing assets (x6). This will ensure the effi- ciency of operating activities at a level close to mf12=1.156.

10. With unbalanced management of accounts receivable and payable (x5) and the use of primarily attracted capital as sources of financing assets (x6). High level of personnel motivation (x1), turnover of current assets (x4), innovative activity (x3) and material and technical support (x2). This makes it possible to achieve an indicator of operational effi- ciency only in the amount of about mf91=0.7174.

11. High level of personnel motivation (x1), turnover of cur- rent assets (x4) and innovative activity (x3), a balanced policy for managing accounts receivable and payable (x5). With a low level of equity capital in the structure of funding sources (x6), a low level of material and technical support (x2) impedes the effective operating activities of the enterprise – mf69=0.3969.

12. If the level of personnel motivation (x1), turnover of current assets (x4) are high, the company pursues a loyal policy of managing accounts receivable and payable (x5). It has a low level of attracted funds in the structure of funding sources (x6), and is also characterized by a low level of inno- vation activity (x3) and material and technical support (x2).

This makes it possible to achieve an indicator of operational efficiency at the level of mf60=0.5699.

The given set of rules reflects the basic requirements for ensuring a high level of efficiency of the enterprise’s operat- ing activities.

Thus, the design and training of a hybrid neural fuzzy network based on an algorithm of fuzzy inference made it possible to substantiate a set of indicators that are priority for ensuring the efficiency of an enterprise. Of the six indi- cators selected for analysis, such as:

– motivational and managerial component or the level of material incentives to motivate personnel;

– provision with material and technical resources;

– level of support (provision) of innovative activities;

– current assets turnover ratio;

– balance of the enterprise’s debt.

Only the capital structure ratio does not have a suf- ficiently strong effect on the efficiency of the enterprise, and therefore it was advisable to exclude it from further research, Table 3.

Table 3 Generalized data of the analysis of the assessment of the

influence of factors on the effective indicator

Factor Relation character

Motivational and managerial component or the level of material incentives for

personnel motivation

Strong relation (2.07) Provision with material and

technical resources Strong relation (4.26) The level of support (provision) of inno-

vation activity Strong relation (4.55) Current assets turnover ratio Strong relation (4.43) Balance of the enterprise’s debt Strong relation (3.12) Capital structure ratio (autonomy) Weak relation (0.42)

These studies were fully confirmed by the analysis of LLC Aviation Company WIND ROSE, which means that regulating the values of indicators in the process of operat- ing activities of companies and choosing business models by them will allow enterprise managers to ensure the desired level of efficiency.

5. 4. Assessment of the level of financial stability of aviation enterprises in competitive markets and determi- nation of their competitive position

In the context of the study of the current state of the activities of aviation enterprises in competitive markets, we consider it necessary to use the Harrington function to assess the financial stability of aviation enterprises in the market. The Harrington function is the result of the trans- formation of any natural values of indicators into a dimen- sionless scale of desirability, reflecting the correspondence between the psychological (subjective analytical assessment) and physical (indicator values) characteristics of the object under study.

The assessments will be carried out on the basis of those indicators that best characterize the financial condition of the studied aviation enterprises (Table 4).

Let’s believe that the presented system of indicators is the most representative and comprehensive way to deter- mine the financial condition of the studied aviation enter- prises. Since they were included in their composition as the most important indicators of financial stability (determined by the general coverage ratio, the autonomy ratio, the concentration ratio of attracted capital). So are important indicators of the efficiency of economic activity (determined by the indicator of return on assets and gross profitability of production costs).

The results of the calculations of indicators for assessing the financial condition of aviation enterprises in Ukraine are presented in Table 5.

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