Modeling- a multifaceted research method, one of the ways of cognition. It cites studies of real-life objects, phenomena, social processes, organic and inorganic systems. They cover all processes. Modeling is a specific multifunctional study. Its main task is to reproduce, on the basis of similarity with the existing object, another object (model) that replaces it. The model is an analogue of the original. It should have a resemblance to the original, but not repeat it, since in this case it is the modeling that loses its meaning. Free modeling is also unacceptable; in this case, it does not give the necessary idea of the original model, and also does not fulfill its function.
Functions of social modeling: deepening the knowledge of existing systems and objects; determination of the main parameters, ways of their further application; conducting a comparative analysis of the original and the model, identified qualitative characteristics.
Modeling also performs important heuristic functions: it reveals negative trends, determines positive ways to solve problems, and offers alternative options.
There are several types (types) of models: cognitive, heuristic; models of the future - predictive; models of the desired, given state.
Modeling goals: to reflect the state of the problem at the moment; identify the most acute "critical" moments, "knots" of contradictions; identify development trends and those factors whose influence can correct undesirable development; to intensify the activities of state, public and other organizations and individuals in search of optimal options for solving social problems.
The model must meet certain requirements:
1. Be simpler, more convenient, provide information about the object, contribute to the improvement of the object itself.
2. Contribute to the definition or improvement of the characteristics of the object, rationalization of the ways of its construction, management or knowledge of the object.
In general, the model must meet the following requirements: completeness, adequacy and evolution; be abstract in order to allow variation of a large number of variables; satisfy the conditions that limit the solution of the problem; focus on the implementation of tasks with the help of available opportunities; provide new useful information about a social object or phenomenon; be built on the use of established terminology, cause the possibility of verifying its truth, correspondence to a social object, process, phenomenon.
They define the basic principles for developing models of complex objects and phenomena used in social modeling: a compromise between the expected accuracy of modeling results and the complexity of the model, balance of accuracy, sufficient versatility of model elements, visibility of the model, block representation of the model, specialization of models, etc.
Modeling of social processes is carried out in the following forms: a predictive model of income and wages; model of the social system.
The use of mathematical models of social forecasting is carried out in the direction of forecasting the budgets of families, which are divided into groups and composition; the use of probability theory and mathematical statistics - to determine the level of well-being of the population.
Social models include: modeling of demographic processes; environmental safety models; models of social adaptation of migrants, etc.
The system-functional approach leads to the modeling of social processes at the regional level, management decisions and the like.
Modeling as a technology of social work - modeling of subjects of social work (systems, services, projects, programs, processes, specialist models); modeling ways, ways to solve problem situations; modeling the positive behavior of a person in various conditions of social life; directions of modern social work with different target groups and categories of the population.
Forecasting is a social theory of knowledge, which is in specific interaction with a number of groups of knowledge that, to one degree or another, consider the future as the main object, carry out analysis at different levels - theoretical, psychological-intuitive, practical - problems of the near and far future.
The object of the forecast is the processes (phenomena, events) to which the study is directed in order to develop a forecast. The purpose of the forecast is a correct assessment of everything new that now has a positive effect on social life, which from modern life can not only be stored, but also pass into the future. This applies to various forms of social life, principles, content and methods of activity.
Forecasting serves the preparation of pre-prepared proposals, projects, programs, recommendations and assessments, that is, it determines in which direction the development of objects in the field of study (culture, health, education, agriculture) is desirable, and how development can actually take place. In accordance with this, the types of forecasting tasks are also determined: defining and motivating the development goal; determination of means, ways, ways to achieve goals.
social forecasting- this is a study of the social system at a deeper level, which allows you to foresee, predict the future, which at the same time acts as a synthesis of versatile knowledge about society.
There are several stages of social forecasting: analytical, research, program, organizational.
The analytical stage should determine the state and development trends of the forecasting object and answer the question: what is the desired level of satisfaction of specific social needs, the achievement of which is associated with the development of the forecasting object; what results of future development and in what sectors, areas are desirable and necessary to achieve the desired level.
The experimental stage answers the following questions: what are the possible results of future development in these areas of the object under study; what problems arise due to the discrepancy between the necessary and possible results of future development; allows you to clearly formulate the problem that arises as a result of the study and is to be solved.
The program stage determines the receipt of answers to the question: what are the possible ways (options) to achieve the desired and undesirable results; a period of time will take the implementation of each of the possible outcomes; what is the degree of confidence in the implementation of each of the possible solutions (paths).
The organizational stage is the personnel, material and technical financial resources necessary for the implementation of each of the possible options; a set of organizational and technical measures that provide certain results in achieving one or another option; determination of the most rational of them.
The system of forecasting methods and techniques is called a forecasting methodology, which covers the following stages: 1) pre-forecast orientation: determining the object of study (health, students, pensioners, etc.), the subject of study (for example, the level of economic security of students), problems, goals, objectives, the time of the event; advancement of working hypotheses, choice of methods; determination of the structure and organization of the study; 2) forecast background - collection of data that affect the development of the object: decisions, new documents, immediate events, while taking into account processes in related areas; 3) search model - a generalized vision of an object in the system of key indicators, parameters that reflect its nature and structure; 4) search forecast - the projection of the original model into the future in accordance with the trend that is observed taking into account the factors of the forecast background in order to identify problems to be solved; 5) normative forecast - the projection of the original model into the future in accordance with the set goals and norms according to certain criteria; 6) assessment of the degree of reliability and refinement of predictive models using an expert survey system; 7) development of recommendations for the preparation of optimal solutions based on a comparison of predictive models.
Currently, there are more than 200 forecasting methods. Among them, the most common are the methods of extrapolation and expertise, which are based on time and parametric series of the retrospective development of the forecasting object. Other methods are based on the use of computer technology, the development of special algorithms and programs that require significant resources and higher qualification of forecast developers: multilevel morphology, multilevel expertise, matrix methods.
Associative Methods- forecasting procedures based on the construction of specific analog models of real objects and processes.
Games are a method used in direct pre-planning studies, as well as for verification of forecasts.
Simulation is the construction of a mathematical model for the purpose of learning and verifying solutions as the results of a predictive study.
An individual prediction of an expert is an assessment of a leading specialist-leader, an expert in a certain area of analysis, research.
Intuitive methods (predictions) - the most widely used in the management system, as well as in predicting various social phenomena, are based on the wide involvement of the most competent experts and the constant improvement of their qualifications for responsibility for expertise.
Historical analogy - the transfer in time or from other areas of knowledge of the identified patterns, trends in the development of similar events.
Causal modeling - establishing causal relationships of known facts.
The classification features of forecasting methods are specific differences in the degree of formatting, in the principle of operation and in the method of obtaining information.
Classification of methods - the choice of methods that are adequate to the tasks that are being solved.
The Delphi method leads to several stages of an autonomous survey of experts who are grouped. There are several special methods for processing and selecting the results of expert surveys.
Advanced information methods - a group of methods based on the properties of scientific and technical information to get ahead of the practical implementation of scientific achievements.
Brainstorming is a collective assessment, regulated by special rules, which are based on stimulating the creative activity of experts through a joint discussion of the problem.
Statistical modeling is the development and analysis of models that are created on the basis of statistical material of the past and present.
Scenario - development and description of the expected course of events in the area under study (environment, system) and its environment, starting from a specific initial stage and ending with the lead time of the forecast.
Heuristic methods - based on the analysis of historical and systemic determining relationships. The prediction mechanism is based on extrapolation, scenario, probable forecasts, statistical modeling.
Among the types and technologies of social forecasting, there are: forecasting the standard of living and employment of the population, pension provision, economic security (poverty, unemployment), forecasting environmental processes, etc.
Forecasting as a technology of social work is the study of a social system in order to predict the effectiveness of forms, methods, approaches, design and programming of social work with an individual client at the level of individual work, a group, community, society at the mesolevel, the activities of social services, organizations and institutions at the macrolevel of social work. The choice of forecasting methods depends on the content of social work, its specific direction, categories of clients, etc.
Main literature
Gershunsky B.S. Pedagogical prognostics: Methodology, theory, practice. - M., 1986.
Fundamentals of social forecasting: Proc. method, manual / Ed. G.E. Shepitko. - M., 2001.
Safronova V.M. Forecasting and modeling in social work: Proc. allowance. - M.: Ed. center "Academy", 2002. -192 p.
Tyuptya L, T., Ivanova I.B. Social work (theory and practice): Proc. allowance. - M.: Vmurol "Ukraine", 2004. - S. 237-242.
Topics for discussion
1. The essence of social modeling as a multifaceted research method, a way of knowing; social modeling functions.
2. Features of models in social work: cognitive, heuristic, prognostic, models of the desired or given state.
3. Goals of modeling, professional requirements for social modeling.
5. Stages of social modeling and forecasting.
6. Characteristics of the types of social forecasting.
Basic management models. Model building process. Decision-making methods: payment matrix, "decision tree". Methods for forecasting managerial decisions. Types of forecasts.
Decisions are one of the most important components of the management process. The entire management process is a continuous chain of decisions of varying complexity and importance, differing in their nature, duration of influence, levels affected and functions performed.
The place of decisions and their use in the management process are determined by the compliance of the decisions made with the goals of the functioning of the organization for which they are made. It is also necessary to single out such a feature of a management decision as its directiveness and compulsion, which, as it were, automatically generates the action of a controlled system to implement the adopted directives, commands, and instructions.
One of the characteristics of a managerial decision is the definition of a system of means for implementing the intended task, persons responsible for the relevant actions, and the timing of the implementation of decisions. And, finally, it is necessary to mention such a property of decisions as the existence of a system of rules that determine the procedure for development, discussion, adoption, entry into force, amendment and cancellation.
There are two groups of methods for choosing solutions: methods for finding a solution by formalizing the problem and then solving it using mathematics and methods for choosing a solution that have a heuristic estimate, i.e. such methods of choosing a solution that are based on intuitive-logical conclusions.
It should be noted that as formal management methods improve, the role of a person in decision-making not only does not decrease, but also increases, since he is freed from performing the work of formalized procedures.
When making a decision, it is very important to ensure the right combination of formal and informal methods, to make the most of the opportunities that the automation of decision-making brings with it, but these opportunities should not be overestimated.
Modeling is that a model is created, i.e. something similar to a real system and retaining its essential properties as the original. Models can be physical, analog and mathematical.
Physical model represents what is being explored with the help of an enlarged or reduced description of an object or system.
analog model represents the object of interest as an analogue that behaves like a real object, but does not look like it.
Mathematical models characterize the real system by symbolic equations or inequalities. The universality of the mathematical language makes mathematical models the most convenient tool for studying an object and its basic properties.
The second part of the model - its constraint - is a mathematical record of the conditions under which the decision is made.
After the model is built, its economic and mathematical analysis begins, the main purpose of which is to find the optimal solution.
Payment matrix
In the words of N. Paul Loomba, “A payoff is a monetary reward or utility that results from a specific strategy combined with specific circumstances. If payments are presented in the form of a table (or matrix), we get a payoff matrix" , as shown in 8.4. The words "in combination with specific circumstances" are very important to understand when a payoff matrix can be used and to assess when a decision made on it basis is likely to be reliable. In its most general form, the matrix means that the payment depends on certain events that actually occur. If such an event or state of nature does not actually occur, the payment will inevitably be different.
In general, a payoff matrix is useful when:
1. There is a reasonably limited number of alternatives or strategies to choose from.
2. What can happen is not known with complete certainty.
3. The results of the decision taken depend on which alternative is chosen and what events actually take place.
decision tree
Another popular management science method used to select the best course of action from available options. "A DECISION TREE is a schematic representation of a decision problem". Like the payoff matrix, the decision tree gives the manager the opportunity to "take into account various courses of action, correlate financial results with them, adjust them in accordance with the probability assigned to them, and then compare alternatives" . The concept of expected value is an integral part of the decision tree method.
The decision tree method can be used in situations similar to the one described above in connection with the consideration of the payoff matrix. In this case, it is assumed that data about results, probabilities, etc. do not affect all subsequent decisions. However, a decision tree can be built for a more complex situation where the results of one decision affect subsequent decisions. Thus, a decision tree is a useful tool for making consistent decisions.
forecasting methods.
The forecasting method is a method of studying the object of forecasting, aimed at developing a forecast. A set of special rules, techniques and methods constitutes a forecasting methodology.
The most common forecasting methods include: expert forecasting, technological forecasting, normative forecasting, scenario method.
Let's take a closer look at each of these methods.
1. Method of technological forecasting.
Technological forecasting is divided into exploratory (sometimes also called exploratory) and normative.
Exploratory forecasting is based on the orientation towards the opportunities presented, the establishment of trends in the development of situations on the basis of information in the development of the forecast.
Moving in the technology space from lower-level technologies to higher-level technologies is referred to as exploratory forecasting. Or otherwise it can be said that the needs and goals should correspond to the means and capabilities of a commercial organization.
2. Method of expert forecasting.
With this method of forecasting, most of the problems that arise in the development of forecasts can be solved. There are several main stages in expert forecasting:
1. Preparation for the development of the forecast;
2. Analysis of retrospective information, internal and external conditions;
3. Determining the most likely options for the development of internal and external conditions;
4.Conducting an examination;
5. Development of alternative options;
7. Monitoring the progress of the implementation of the forecast and adjusting the forecast;
3. Method of exploratory forecasting.
One of the main methods used in exploratory forecasting is the extrapolation of time series - statistical data about the object of interest to us. Extrapolation methods are based on the assumption that the law of growth that took place in the past will continue in the future, taking into account corrections due to the possible saturation effect and the stages of the object's life cycle.
Among the curves that accurately reflect the change in the predicted parameters in a number of common situations is the exponent, that is, a function of the form:
where t is time,
a and b-parameters of the exponential curve.
Among the most famous exponential curves used in forecasting is the Pearl curve, derived from extensive research in the field of growth of organisms and populations, and having the form:
Y = L/(1+a*(e-bt),
where L is the upper limit of the variable y.
No less common is the Gompertz curve, derived from the results of research in the field of income distribution and mortality (for insurance companies), where k is also an exponential parameter.
The Perl and Gompertz curves were used to forecast such parameters as the increase in the efficiency of steam engines, the increase in the efficiency of radio stations, the increase in the tonnage of merchant fleet ships, etc.
4. Method of normative forecasting.
Normative forecasting is an approach to developing a forecast based on the goals and objectives that an organization sets for itself in the forecast period. The main method used in normative forecasting is the method of horizontal decision matrices, when the priority of the implementation of the projects proposed to achieve the set goals is determined.
Usually two-dimensional and three-dimensional matrices are used. Most often, horizontal decision matrices are used to determine the optimal allocation of resources under given constraints. At the same time, cash, labor, its quality and qualifications, equipment, energy resources, etc. can act as resources.
5. Scenario method.
In the development of managerial decisions, the scenario method is widely used, which also makes it possible to assess the most probable course of events and the possible consequences of the decisions made.
Scenarios for the development of the analyzed situation developed by specialists allow, with one level of certainty or another, to determine possible development trends, relationships between acting factors, to form a picture of possible states that the situation may come to under the influence of certain influences.
Professionally developed scenarios allow you to more fully and clearly determine the prospects for the development of the situation, both in the presence of various control actions, and in their absence.
Strategic management.
The essence of strategic management, its objectives and principles. Development of goals and strategies for the development of the organization. Target ranking. Classification of strategies of organizations. Strategic planning. Analysis of alternatives and choice of organization strategy. Methods for planning strategic alternatives. Features of strategic management in the USA, Japan, Finland.
Strategic management- this is such management that relies on human potential as the basis of the organization, orients production activities to the needs of consumers, responds flexibly and makes timely changes in the organization that meet the challenge from the environment and allow achieving competitive advantages, which together makes it possible for the organization to survive in the long term. perspective while achieving their goals.
The objects of strategic management are organizations, strategic business units and functional areas of the organization.
The subject of strategic management are:
Problems that are directly related to the general goals of the organization.
Problems and solutions related to any element of the organization, if this element is necessary to achieve the goals, but is not currently available or is not available in sufficient quantity.
Problems associated with external factors that are uncontrollable.
“Problems of strategic management most often arise as a result of the action of numerous external factors. Therefore, in order not to make a mistake in choosing a strategy, it is important to determine what economic, political, scientific, technical, social and other factors influence the future of the organization.
The essence of strategic management is the answer to 3 important questions:
What is the current state of the company?
In what position would it like to be in 3, 5, 10 months?
How to achieve the desired result?
To solve the first question, an information base with relevant data is needed to analyze past, present and future situations. The second question reflects such an important feature for strategic management as its orientation to the future. It is necessary to determine what to strive for, what goals to set. The third issue is related to the implementation of the chosen strategy, during which the two previous stages can be adjusted. The most important components of this stage are the available or available resources, the management system, the organizational structure and the personnel who will implement this strategy.
Thus, the essence of strategic management is the formation and implementation of an organization's development strategy based on continuous monitoring and evaluation of ongoing changes in its activities in order to maintain the ability to survive and function effectively in an unstable environment.
Strategic management in the enterprise is expressed in the following five functions:
Strategy planning.
Organization of the implementation of strategic plans.
Coordination of actions for the implementation of strategic tasks.
Motivation to achieve strategic results.
Control over the implementation of the strategy.
Strategy planning involves the implementation of such sub-functions as forecasting, strategy development and budgeting.
Forecasting precedes the actual drawing up of strategic plans.
Choice of development strategy
Based on the existing database of strategic data, forecasts and assumptions, the company proceeds to the choice of strategic alternatives for its development.
There are four types of alternatives:
limited growth;
Reduction;
A combination of the three previous alternatives in varying proportions.
The growth strategy involves the annual growth of the main indicators of the organization, it is most often used by enterprises in dynamically developing sectors of the national economy, with rapidly changing technologies, as well as enterprises seeking to diversify (wide penetration into new areas of activity). It happens that firms cannot withstand rapid and short-term growth, and go bankrupt, so most firms adhere to a limited growth strategy, expanding their activities taking into account the real possibilities of the achieved level and external efforts. This is the least risky course of action.
Strategic reduction is expressed in the fact that the results of the company's work in the planning period are expected to be lower than in the previous period. This strategy is used when it comes to a fundamental restructuring of the organization.
And if short-sighted leaders try to restructure the organization's activities while maintaining the same growth, then the results are usually negative.
The reduction is carried out in different ways:
Complete liquidation of the company and the creation of a new one in its place;
Getting rid of unnecessary elements;
Narrowing the scale of the company, its activities with simultaneous reorientation (this strategy is chosen by firms if things are going badly or it is necessary to hide income).
The combination of three types of strategy is practiced by firms operating simultaneously in different industries with very different technological and economic conditions.
Successful implementation of a strategy requires reliable feedback and appropriate tools. One of the tools is tactics, when the forms and methods of action are focused on achieving immediate goals. It is developed at the level of middle management, and for a short time. To achieve strategic and tactical goals, the management of the firm develops current policies that include discrimination in hiring, increasing profits by inflating prices, using low prices to force out competitors, etc.
The role of a guideline in organizing the goals and objectives of the company is performed by rules that prescribe strictly regulated actions in certain situations, excluding freedom of choice. Rules that are executed in a strict sequence are called procedures. Procedures are applied in standard situations, which saves money.
Thus, strategy, tactics, forecasts, rules, procedures and assumptions are the basis on which the planning process can be carried out.
Optimization methods make it possible to find the best options for economic solutions according to the chosen optimality criterion. On their basis, it is possible to determine the optimal profit of the enterprise, the volume of output of various types of products, the number of employees, the amount of resources consumed and other indicators.
A model is a convenient, simplified representation of the essential characteristics of an object or situation.
Models must meet the following requirements:
1. The model should display the characteristic, essential features of the object.
2. This mapping must be expressed in a simplified form.
3. The model should allow changing some of its parameters for the purpose of research.
4. The model should be more convenient for experiments and cheaper to manufacture than the object.
The sequence of building an economic and mathematical model
When building an economic model, a number of stages are usually performed:
1. The subject and goals of the study are formulated.
2. In the considered economic system, structural or functional elements are singled out and their most important characteristics are determined.
3. A verbal description of the relationship between the elements of the model is given.
4. Symbolic designations are introduced for the considered characteristics of the modeling object and the relationships between them are formalized. Thus, a mathematical model is built.
5. Calculations are carried out according to the mathematical model, and the analysis of the obtained solution is performed.
Main types of models
Mathematical models used in the economy can be divided into classes according to a number of features related to the features of the modeled object, the purpose of modeling and the tools used:
Depending on the type of the modeled object, the models are macro and microeconomic.
Macroeconomic models describe the economy as a whole, linking together its aggregated indicators: GDP, investment, labor productivity, employment, interest rate, and other indicators.
Microeconomic models describe the interaction of structural and functional components of the economy, or the behavior of one such component in a market environment. Due to the variety of types of economic elements and forms of their interaction in the market, microeconomic modeling occupies the main part of economic and mathematical theory.
Depending on the goals of modeling, theoretical and applied models can be developed.
Theoretical models make it possible to study the general properties of the economy and its characteristic elements. Applied models make it possible to evaluate the parameters of the functioning of a particular economic object and formulate recommendations for making practical decisions.
In modeling a market economy, a special place is occupied by equilibrium models that describe the state of the economy when the resultant of all forces seeking to bring it out of this state is equal to zero, for example, models of equilibrium supply and demand.
Optimization models in a market economy are usually built at the micro level, such as profit maximization or cost minimization in corporate planning.
Depending on the tools used and the nature of the processes under study, all types of modeling can be divided into deterministic and stochastic, discrete and continuous, static and dynamic, linear and nonlinear.
Deterministic modeling depicts deterministic processes, i.e. processes in which the absence of any random influences is assumed.
Stochastic modeling displays probabilistic processes and events. In this case, a number of implementations of a random process are analyzed, and the average characteristics of the process are estimated.
Discrete modeling serves to describe processes that are assumed to be discrete, i.e. discontinuous, consisting of separate parts.
Continuous modeling allows you to display continuous processes in systems.
Models can be either static or dynamic based on time. Static models describe the state of an economic object at a particular moment or period of time, while dynamic models include the relationship of variables over time (for example, over a five-year period).
According to the degree of coarsening of the forms of structural relations of the object under study, the models are divided into linear and non-linear models. In linear models, all the desired variables are written in the first degree, and on the graphs they can be represented as straight lines.
Depending on the form of representation of the object, mental and real modeling can be distinguished.
Mental modeling is often the only way to model objects that are practically unrealizable in a given time interval, or exist outside the conditions that are possible for physical contemplation. Mental modeling can be implemented in the form of visual and mathematical.
With visual modeling, on the basis of human ideas about real objects, various visual models are created that reflect the phenomena and processes occurring in the object.
The basis of hypothetical modeling by the researcher is a certain hypothesis about the patterns of the process in a real object, which reflects the level of knowledge of the researcher about the object and is based on cause-and-effect relationships between the input and output of the object under study.
Analog modeling is based on the application of analogies at various levels. The highest level is a complete analogy, which takes place only for fairly simple objects.
A mental layout can be used in cases where the processes occurring in a real object are not amenable to physical modeling.
Symbolic modeling can be linguistic or symbolic. At the heart of language modeling is a certain thesaurus, i.e. a dictionary cleared of the ambiguity inherent in an ordinary dictionary (for example, the word "KEY").
Sign modeling allows using signs to display a set of concepts, making up chains of words and sentences and thus giving a description of a real object.
Mathematical models are sets of mathematical dependencies that reflect the essential characteristics of the phenomenon under study. In many cases, mathematical models most fully reflect the object being modeled. At the same time, mathematical models are more dynamic, it is better to find the optimal parameters of the object on them. To model economic phenomena, other models, except for economic and mathematical ones, as a rule, cannot be used. Economic and mathematical models, in turn, are of two types: analytical and simulation.
For analytical modeling, the functioning processes are written in the form of some functional relations (algebraic, finite-difference, etc.). Simulation modeling imitates elementary phenomena that make up the process with the preservation of their logical structure and sequence of flow in time.
Real simulation is the most adequate, but its capabilities are very limited, taking into account the complexity of objects.
Modeling is one of the methods which is becoming more and more popular today.
Simulation ( lat. - measure, norm and French. - pattern, prototype) is a method of studying objects of knowledge with the help of their models.
Objects of knowledge - really existing systems (organic and inorganic), objects, phenomena, social processes.
Object Model- its analogue, which can be represented as a structure, scheme, sign system, function, result. Analog serves to store and expand knowledge about the properties and structures of the object. From an epistemological point of view, it is a substitute for the original in knowledge and practice.
The results of the development and research of the model are transferred to the original. From a logical point of view, such a transfer is based on the relations of isomorphism (sameness) and homomorphism (similarity) that exist between the model and what is modeled with its help.
The need for modeling arises when the study of the object itself is difficult or even impossible.
Modeling types:
- 1. subject(the model reproduces certain geometric, physical, dynamic, functional characteristics of the original).
- 2. analog(original and model are described by single mathematical relations).
- 3. iconic(Schemes, drawings, formulas serve as a model).
- 4. Logico-mathematical(construction of logical and mathematical models based on mentally visual representation of signs and operations with them).
Modeling relies heavily on reasoning by analogy based on input data. In this case, the data can change, in accordance with which the expressive possibilities of the model are expanded.
Changing object parameters data are variables that are classified into:
1) internal (own parameters of the object);
2) external (do not depend and are not determined by the object)
- 3) managed (chosen by the head or the researcher at their own discretion);
- 4) unmanaged (they do not depend on the subject's driving, their value can only be registered);
- 5) random (distributed according to some probabilistic law, uncontrollable; do not have a probabilistic nature, uncertain).
The purpose of the simulation- reproduce data that evaluate natural loads, the course of the object, as well as explore its internal processes.
The main task of modeling-- reproduce the model, which should be similar to the original, but should not be its complete analogue. This is the main condition of the simulation. Otherwise, the simulation loses its meaning.
The main difference between the original and the model is the ability for flexible predictive modeling that does not affect the initial data of the model.
A social model can be a mathematical equation, a graphical display of various factors, tables of interdependent features (events and phenomena). Unlike a physical model, a social model does not copy the objects or phenomena being studied, but transforms the value of some features of a social phenomenon or process, chosen as independent, into the value of other features, chosen as dependent.
The information value of a social model can be assessed by the degree of accuracy in displaying or predicting changes in the studied social processes or phenomena (dependent features) with new values of independent features. That is, it is necessary to breed concepts: developed scheme(in which what is independently can be represented dependently on some conditions) and real social reality with its objective independent conditions.
Simulation applied;
- a) in the study of global problems that cover all human life and narrow problems of the social sphere (for example, the state of the demographic situation in Russia);
- b) in the conditions of market relations (for example, the state of education, health care, women and families in the context of social reforms, modeling the spiritual and moral sphere of the individual, retraining systems in the conditions of market relations of workers, etc.).
Modeling of social structures creates many models that take into account the influence of certain social factors on the social processes under study.
The basis and subject of modeling is a problematic situation, which is caused by objective (contradiction between needs and ways to meet them, between the development process and the stabilization process) and subjective factors.
The most common modeling methods are: development, analysis and study of a model, a problem situation, innovative models, heuristic models, special mathematical models. Recently, models created on a computer have become widespread.
Main modeling tools are:
- - verbal description - the simplest and most accessible way to specify models;
- - graphical representation in the form of curves, drawings - this method has a limited independent value, it can be an addition to others;
- - block diagrams, decision matrices - this method can be considered intermediate between verbal and mathematical descriptions;
- – mathematical description;
- - program description (for computers).
In everyday practice, the capabilities of the Excel computer program are often used, which have various functions for calculating trends in the change of a variable in the base period to continue the trend in the forecast lead period.
Types and functions of models
Mo deletion is a specific multifunctional study. Its main task is to reproduce, on the basis of similarity with an existing object, another object (model) that replaces it. Model- it is similar to the original. It should have a resemblance to the original, but not repeat it, since in this case the modeling itself loses its meaning. Arbitrary modeling is also unacceptable; in this case, it does not give a proper idea of the original model, and also does not fulfill its function. Models differ in the degree of closeness to reality (degrees isomorphism with reality).
All variety of models in accordance with the way of reproducing reality and the means used to build the model, it can be divided into three classes:
- 1) material models, which, due to the specificity of social objects, should be implemented in the form of models based on the participation of people in them (as a rule, these are game models);
- 2) ideal models are currently used in sociology in almost all areas of scientific research. Ideal models are usually classified according to the following criteria:
- – by scope of study distinguish between models of the social structure of society and socio-demographic processes, models of lifestyle and socio-political processes, etc.;
- – by the level of the system being modeled- micro and macro models;
- – by focusing on the reproduction of certain aspects of the original- substantial, structural, functional and mixed models;
- – the method of displaying in model constructions the laws and patterns that the object of study obeys, - deterministic and stochastic models;
- – focus on studying the functioning or development of the system- models with constant and changing structure;
- – place in the structure of scientific knowledge- measuring, descriptive, explanatory, predictive and criterial;
- – level of formalization- conceptual and formal-logical (mathematical) models;
- 3) mixed models, combining elements of the first two (the so-called man-machine models). The scope of the models of the first and third classes is very limited in sociology.
Model functions. Depending on the objectives of the study, models can be included in the cognitive process both at the empirical and theoretical levels of knowledge. Wherein at the empirical level
– measuring(measuring social characteristics) and descriptive (fixing the results of empirical research and expressing them in terms of science).
On theoretical level The knowledge of the model performs, as a rule, the following functions:
- – explanatory- disclosure of the essence of the objects under study,
- – criterial- verification of the truth of some provisions of the theory or system of hypotheses,
- – predictive- assessment of the future state of the system under consideration.
Individual functions can be performed by models both at the empirical and theoretical levels of knowledge. As for specific models, they can be designed specifically to perform one of these functions. In addition, models can be designed specifically for the simultaneous implementation of several functions. For example, simulation models perform, as a rule, both descriptive and explanatory functions, or descriptive and criterial.
What requirements should the social model meet?
The first group of requirements . The model should
- – be simple, convenient;
- - provide new information about the object;
- - contribute to the improvement of the object itself.
To the second group of requirements can be attributed:
- – determination or improvement of the characteristics of the object;
- – rationalization of ways of its construction;
- - the ability to control or cognize an object on its model.
Therefore, when developing models, it is legitimate to talk about their similarity to the original object. At the same time, on the one hand, a strict focus is observed, linking the parameters with the expected results, on the other hand, the model must be sufficiently “free”, capable of transformation depending on specific conditions and circumstances, be alternative, have the largest number of options in stock.
Model evaluation
What requirements should the social model meet? Today, the following requirements are put forward in the scientific literature for the model:
- - it should be simple, convenient;
- - allow to study the object and obtain new information about it;
- - contribute to the improvement of the object;
- - give the opportunity to consider the control of the object on its model.
When developing a model, a strict focus is observed, linking the parameters with the expected results, on the other hand, the model must be sufficiently “free”, capable of transformation depending on specific conditions and circumstances, be alternative, have the largest number of options in stock.
Model Evaluation Criteria
- 1) One of the evaluation criteria isprogressiveness of the model, which means how much it is leading in a number of parameters,
- 2) kind of reflection(intuitive reflection, qualitative description, visual imitation, quantitative description, system reproduction);
- 3) prevalence(social sphere as a whole, industry, social group, etc.);
- 4) level of development(an idea was put forward, a scheme was built, an algorithm was developed, a formalized, materialized system, etc.);
- 5) level of creativity using the model. The first level is the definition (distinction, recognition), classification of known facts, objects, events, ordering them and solving simple problems, improving the simplest model representations. The second level is the implementation of a scientific forecast of qualitatively new facts, events and their practical use.
Equally important is the consideration of the structure of the models. To the structure of the model are included three main components: a set of directions for the development of the object of knowledge; motivating forces of development; factors of external influences.
In the study, it is important to fix the degree of realized impact of all the main components at the previous stage of object cognition, which can be carried out with a retrospective analysis. Such an approach largely predetermines the foresight of the development of the object under study, based on the experience of the past, on comparison with it, and relies on representative arrays of information.
The purpose of forecasting in social work - give variable forecast of a change in a social object (phenomenon, process, situation, group, personality), i.e. describe its state in the future, indicating quantitative and qualitative characteristics.
In accordance with the described characteristics, the forecasts will be called: qualitative forecasts, quantitative forecasts.
A common method for describing certain processes and phenomena is modeling. Modeling is considered to be a fairly effective means of predicting the possible occurrence of new or future technical means and solutions. For the first time, for the purposes of forecasting, the construction of operating models was undertaken in the economy. The model is constructed by the research subject so that the operations reflect the characteristics of the object (relationships, structural and functional parameters, etc.) that are essential for the purpose of the research. Therefore, the question of the quality of such a mapping - the adequacy of the model to the object - is legitimate to decide only with respect to a specific goal. Designing a model based on a preliminary study of the object and highlighting its essential characteristics, experimental and theoretical analysis of the model, comparison of the results with the data of the object, and correction of the model constitute the content of the modeling method.
The modeling method, the development of which in relation to the forecasting of scientific and technological progress encounters serious difficulties, requires special attention.
The difficulty of applying the modeling method in predicting scientific and technological progress is caused by the complexity of the structure of technical development and therefore forces us to use not a single model, but a system of methods and models characterized by a certain hierarchy and sequence.
The system of models for forecasting scientific and technological progress should be understood as a set of methods and models that makes it possible to give a consistent and consistent forecast of the scientific and technological development of the industry, based on the study of technical and economic trends and patterns emerging in the current and future periods, on given targets, on existing resources, identified needs of the national economy and their dynamics.
Such a system implies a certain sequence of using models for the purposes of compiling a comprehensive forecast.
The use of a mathematical apparatus for describing models (including algorithms and their actions) is associated with the advantages of a mathematical approach to multi-stage information processing processes, the use of identical means for formulating problems, searching for methods for solving them, fixing these methods and converting them into programs designed for the use of computer technology .
The development of a system of forecasting models goes through three stages.
At the first stage of developing local forecasting methods, separate models and subsystems of forecasting models are being worked out. The developed models must be mutually linked and constitute a single system for forecasting purposes, which ensures the interaction of individual models in accordance with certain requirements. Such requirements will be fixed in the research program on the problem as a whole.
At the second stage of developing local methods for forecasting scientific and technological progress, a system of interacting forecasting models is created, subsystems of models are specified and coordinated, their interaction is checked, the sequence of using individual models is determined, as well as evaluation techniques and methods for verifying the resulting complex forecasts. At this stage, appropriate programs for solving problems on electronic computers should also be compiled.
The third stage of creating a system of forecasting models is mainly associated with the refinement and development of individual local systems and methods in the course of their practical use for the purposes of integrated forecasting of scientific and technological progress.
When drawing up detailed research programs for the first and second stages, it must be taken into account that the objectives of the methodology and the range of problems and indicators developed in the course of forecasting depend significantly on the timing of forecasts. With an increase in the activity of the forecast period, indicators are consolidated, the amount of available and accessible information of all types decreases; this corresponds to the use of enlarged (aggregated) models, the consideration of larger synthetic problems of the development of the national economy. At the same time, it is necessary to identify indicators that are linked by stable functional relationships, both among themselves and with indicators of forecasts for a shorter period, and which significantly affect the dynamics of indicators for the period as a whole and its individual parts (the principle of selecting significant and stable information).
The requirements for individual models and a system of forecasting models predetermine the methods by which these models can and should be developed, as well as the methods and means for calculating them. These requirements are mainly reduced to the following provisions:
- - the methodology should give a clear description of the sequence of rules (algorithm), which makes it possible to make a separate forecast under fairly broad assumptions about the nature and values of the information of a certain structure initial for this forecast;
- - the methodology should use methods and technical means that allow to carry out calculations in a timely manner and repeatedly, based, as a rule, on heterogeneous and large in volume information that changes according to forecast options;
- - in such methods, complex, multifactorial relationships of predicted processes and indicators should be taken into account. It is necessary to ensure the identification of the most important and stable patterns and trends in these conditions. Such identification is necessary both on the source material and in the process of analyzing the results obtained by this method and their calculations using a complex of related models;
There is a need for systemic harmonization of individual forecasts, which should ensure the consistency and mutual adjustment of the latter.
The application of mathematical methods is a prerequisite for the development and use of forecasting models, which provide high requirements for the validity, effectiveness and timeliness of forecasts of scientific and technological progress.
Modeling is the construction of a model based on a preliminary study of an object and processes, the selection of its essential features and characteristics. Forecasting using models includes its development, experimental analysis, comparison of the results of preliminary predictive calculations with actual data on the state of the process or object, refinement and correction of the model.
