Formation of the Motivation System of PJSC "Rostelecom" employees using Theory of Generations

1.5 Interrelation of the generational and age effects on the motivational factors of people

In addition to the analysis from the point of view of generations, we can also analyze the life path. There are qualitative and quantitative methods for this. Quantitative models include regression models, Event History analysis, Sequence Analysis, APC Analysis (Mason et al., 1972).

In this study, it is more interesting to focus on APC analysis. In general, APC analysis involves the selection and analysis of three effects: age (differences associated with belonging to a certain age group), period (appears and is due to the impact of historical conditions) and cohort (changes characteristic of the group, united by some initial event (usually the year of birth).

The peculiarity of the method is that it can measure the effects of age, cohort and historical period, which, according to the concept of cohort analysis, are the most important factors in explaining social change.

In this study, in addition to the generational effect, the effect of age will be measured, since the paper puts two hypotheses: from the generational and age point of view.

The age effect, also called the life cycle effect, ageing or old age, reflects the biological and mental processes of individual development, maturation and ageing, and the differences between childhood, adulthood and old age. The effect of the historical period reflects the differences in attitudes and behavior of people, changing over time, due to the influence of different social, cultural, economic, political or climatic contextual influences. Affecting all age groups, the effect of the historical period, however, can affect certain cohorts in different ways.

Different cohorts in their own way perceive social reality and historical events that catch members of cohorts at different ages and different social status. The result is a cohort effect that reflects the differences in attitudes, values and social characteristics of members of different cohorts observed in the study of cohorts over a long period. Three effects can be displayed as a formula:

Age = Historical period (year of measurement) - Cohort (year of birth)

The age variable is determined by the difference between the period and cohort variables. All three of these effects can have an impact on the change of the trait studied by the researcher and are linked by a linear relationship, since the age and history of society are measured by the same linear time scale with a year interval.

A priori it is impossible to exclude any of the effects -- each of them is described by an equation that includes the other two effects. For such a system of equations, there are many solutions, but without additional constraints or assumptions, it is impossible to obtain a single result.

Returning to the general analysis, let us return to the formulation of hypotheses.

Based on labor values and expectations, it is possible to identify the point of change of material values to non-material ones, which serves as an indicator of the transition from generations of Soviet labor culture to modern ones. In other words, the points of generational change are at the moment when material values change to non material ones.

This assumption is a prerequisite to the first hypothesis, which relates to the generational question of work. Thus, we can formulate the first hypothesis:

Hypothesis 1: “generational differences”: The generations that were socialized in the post-Soviet period adhere to more intangible values than the generations that grew up in the USSR.

But not only generational differences affect employee expectations and their value system and, accordingly, a set of motivating factors, but also age-related ones. They must be distinguished. That is why one of the hypotheses is that with age there will be a transition from the values of self-development and approval to the values of security, stability, predictability, as there is responsibility for the lives of others - children and spouse. The second hypothesis relates to age differences and can be formulated as follows:

Hypothesis 2 “age differences”: With age, the importance of the values of security and stability begins to prevail over the values of development and self-realization approval of senior colleagues.



2. Methodological part

2.1 Economically active generations in Russia

The theory of generations, developed and described in 1991 by American scientists N. Howe and V. Strauss, has been attracting interest among scientists of various fields for decades, and the applied aspects of this concept are widely applied in all aspects of public life. In particular, the Theory of generations is particularly widespread in the field of management and management sociology, since representatives of different generations have their own characteristics and have different labor values, which means that it is important for any organization to properly stimulate and motivate representatives of different generations of its employees in order to form effective management tools and generally improve the efficiency of the company.

Initially, the consistency of the concept of generations was confirmed by the authors on the example of American history. Many of the main aspects of the theory can be positioned as universal, but the value formation of society should be considered based on the characteristics of a particular state, the specifics of its genesis and socio-cultural development. As a result, in relation to Russian realities, it is advisable to consider the concept of generations adapted by domestic researchers E. Shamis and A. Antipov. Thus, based on the analysis of the main events in our country, five generations that currently live on the territory of the Russian Federation were identified and characterized:

- The Silent generation (1923-1943);

- Baby Boomer generation (born in 1943-1963);

- Generation X (1963-1984);

- Generation Y (1984-2000);

- Generation Z (since 2001).

According to the Federal state statistics service, at the beginning of 2018 in Russia, representatives of generation X (people born in 1963-1984) dominated quantitatively - 30% of the total population of the Russian Federation. Older generations-the silent and baby boomers, together give the same number. Generation Y (born in 1984- 2000) make up only 21% of the total number of Russian citizens. Generation Z -19 % of the total population (gks.ru, 2020). In General, today representatives of Mature generations (X and older) are numerically predominant, which leaves its mark on the overall characteristics of Russian society, including the features of the available labor resources.

The study of the labor potential of the country's generations should begin with the consideration of indicators of their economic activity, the definition of able-bodied generational groups. Women aged 16 to 55 and men aged 16 to 60 are considered to be able to work in our country. Using official statistics and information about the age limits of citizens considered to be able-bodied, you can make an approximate conditional percentage of generations in the total number of able-bodied population. Thus, the baby Boomer generation will make up 9% of the total, generation X - 54%, generation Y - 37%, and the youngest generation Z - 2%.

For clarity, we can consider the population pyramid of Russia in 2018. The pyramid illustrates the age and sex structure. The population is distributed along the horizontal axis, with males shown on the left and females on the right. The male and female populations are divided into 5-year age groups represented as horizontal bars along the vertical axis, with the youngest age groups at the bottom and the oldest at the top.



Figure 1. Age-sex pyramid in Russia 2020

As we can see, we can assume that the Russian labor force consists mainly of four generations, most of which are generations X and Y, all of which are currently able-bodied in terms of age characteristics. Their total percentage relative to all economically active citizens is 89%. The Baby Boomer generation makes up a small percentage of economically active citizens, as they are already completing their working life due to retirement age. The youngest generation Z is just beginning its working life and is represented in the smallest volume,and therefore can not yet be considered an economically active population. Thus, representatives of the economically active population of Russia in our time are baby boomers (1923-1963), generation X (people 1963-1984) and Y (1984- 2000). However, in the future, it is worth investigating generations X, Y and Z, since these generations will form the basis of the labor force in the next decades, and the efforts of modern researchers in the field of sociology, management and HR branding should be aimed at these generational groups (Gurova, 2016).



2.2 General characteristics of the PJSC “Rostelecom”

PJSC “Rostelecom” is Russia's largest provider of digital services and solutions with presence in all market segments, passing through millions of Russian households, governmental and private organizations.

PJSC “Rostelecom” holds a leading position in the market of high-speed Internet access and pay-TV services. Broadband services are used by more than 13.2 million subscribers, pay TV-10.4 million users, of which more than 5.6 million are connected to the Interactive TV service. Rostelecom is a widely recognized technology leader offering innovative solutions in e-government, cybersecurity, DC and cloud computing services, biometrics, healthcare, education, housing and utilities services.

The company's revenue for 2019 amounted to 337.4 billion rubles, OIBDA reached 106.5 billion rubles (31.6% of revenue), and net profit -- 16.5 billion rubles.

PJSC “Rostelecom” is the market leader in telecommunications services for Russian government authorities and corporate users at all levels.

The company is a recognized technology leader in innovative solutions in the fields of e-government, cybersecurity, data centers and cloud computing, healthcare, education, and housing and utilities.

The company's stable financial position is confirmed by the following credit ratings: Fitch Ratings at BBB -, Standard & Poor's at BB+, and ACRA at AA(RU).

Rostelecom's strategic development vector is continuing transformation from a Telecom operator to a digital partner of the population, business and the state.

The company values professionals and offers employees various ways and opportunities for career growth. Participation in large - scale projects, training opportunities, corporate culture and a team of professionals are key factors of growth in the company. Corporate values are shared by every employee of the company:

* Manufacturability: looking for a solution in technology;

* Humanity: working for people;

* Simplicity: making complex things easier;

* Development: creating the future.

Figure. Regional structure of the company:

Figure 2. Macroregional Division of PJSC “Rostelecom”

Each Macroregional division is divided into regional divisions. The head office is a Corporate Center, where the research will be conducted (https://moscow.rt.ru/, 2020).

Organizational structure of the company (structure in the corporate center, which is copied to the regional structure):

Commercial unit Technical unit Service divisions

B2C Technical infrastructure HR Marketing and communications

B2B Technical support IT Block of administration

B2O Customer service Finances Legal support

Marketing and products Internal audit

Strategic Innovations

Table 1. Organizational structure of the PJSC “Rostelecom”

2.3 Methodology for the survey within the company

An empirical approach was chosen for our research, so in this case we proceed from real behavior, values, and attitudes.

The survey was conducted in the corporate center of PJSC “Rostelecom” (the head office of the company, coordinating the work of seven macro-regional and sixty-five regional branches), which has 2,900 employees. In this study, a survey was used to determine the main motivating factors so that respondents not only and not so much choose among the most motivating factors, but also choose the form in which they would be more interested in receiving a benefit.

Employees from different departments took part in the survey: from the unit of Organizational development, the unit of Technical infrastructure, IT unit, Commercial unit, Administrative unit and others. Approximately the same number of respondents of each department were represented - so that professional affiliation does not affect the results of the study.

The survey consists of direct and projective questions. Direct questions were aimed at respondents ' answers about themselves, and projective questions were aimed at what they think about the representatives of their generation. Using projective questions, you can also understand what people actually think about themselves, but don't "admit" it by answering differently in direct questions. The survey also contains a socio-demographic block consisting of questions about gender, age, marital status, whether or not respondents want to take out a mortgage, whether or not they have children.

It is important to note that the questions were not always asked directly, so that employees could unconsciously choose the factors that are of greatest interest to them and the form that is most understandable, pleasant and convenient.

The survey was conducted remotely. Employees of different ages/positions/departments got the survey via some of messengers and social networks (mostly WhatsApp, Telegram and Facebook) and had two days to answer it and send it back. The sample size was 280 people, with the response rate being nearly 70%. Employees had a multiple choice. The most important questions were to choose a form of benefits, which could correspond to a particular generational group (the questions about people themselves and about their opinion about the people of their generation). Besides, there were also questions about their age, sex, marital status, presence of children and the desire to take out a mortgage (social demographic issues).

A key was developed for the survey, on the basis of which the generations were divided among themselves and on the basis of which it was possible to conclude what exactly affects the belonging to a particular generation within the same company. Each generational group has developed its own priority set of benefits and the form in which they would be most interested in receiving it.

Before analysis, all the gathered data was recoded for ease of use. Also, the gathered data was prepared and checked for missing data and outliers: there are no outliers or missing data.

The gender and age distribution was illustrated in Excel graph. The average age of respondents is 34.68 years. The median is 34 years.

The theory of N. Howie and W. Strauss was used as the theoretical basis for the division of generations (their chronological framework) and related values. It served as the basis for the key to the survey determining what labor values are prescribed for each generation. Some of the direct and projective questions are based on the Maslow pyramid: some questions define the basic values of each generation, some define the needs for recognition and development. The last two needs were combined into the same question to distinguish what is more important for each generation.

The analysis was performed in R, where the regression analysis was conducted.

The clustering method was used to see how people are grouped according to the responses prescribed for each generation (generational analysis and testing the first hypothesis). Classification based on labor values allows to assess how much the prescribed values of generations correspond to the labor values of real people. Thus, using the example of a company, we can assess whether the theory is currently sound. In this way, we drew up portraits of different employees, studied their socio-demographic characteristics, and compared them with theoretical generational ideas about them.

In addition, the several models were used to search for points of change in values between generations because the second research task was to identify the "hooks" that are the tipping points in the transition to each new generation.

Cluster analysis allows to group points in a shared space into clusters in a way that makes sense. When analyzing in R, we took the variable "gower" and made a matrix where we could measure the distance between all the objects.

There are two main clustering methods: divisive and agglomerative. In the Divisive method, which performs top-down clustering, showed better fullness of metrics, so we were able to divide the data into three clusters. Dividing into two clusters was more successful in the case of the Agglomerative method (bottom-up clustering).

The silwidth variable helped draw these conclusions, since it showed how close elements in one cluster are to elements in another. In order for clusters to be more clear and logical, we wanted this variable to grow. We also used the Elbow method to find the fracture for which there will be a decline in indicators for the best cluster differentiation.?

After that, we built dendrograms in R, which for convenience were analyzed from a socio-demographic point of view in Excel.

Then we conducted analysis by age for testing the second hypothesis.

First, by constructing the distribution of variables, we saw that there was a deviation, since people from the oldest age group were the least likely to participate in this study. Therefore, we are looking primarily at medians rather than averages.

As there is a deviation, we run the Shapiro-Wilk test, a test of normality in frequentist statistics. Null hypothesis: the data is distributed normally. Then, since p-value <0.05, we rejected the null hypothesis and said that sufficient basis had been provided for the judgment that the data is not distributed normally.

Therefore, we did not use parametric methods (ANOVA). Instead, we use a nonparametric analog - the Kraskel-Wallis test (to check the equality of medians of several samples). In this case, there is no dependence on which distribution the data is taken from.

Then we took all the variables in the dataset and built boxplots based on them. Boxplots show the average value, whereas Kruskal-Wallis test is focused on medians, so we mainly focus not on graphs, but on tests, using graphs mainly for visualization (the most illustrative and informative graphs are illustrated in this paper). These graphs show differences in the average age for those who answered a particular question in a particular way.

A test was performed for all variables: those cases where p-value <0.05 were suitable for further analysis. After getting a list of variables that have different averages, we could look at the conjugacy tables (which contain the following information: encoded response options, the number of responses, the average value, and the median).

Next, it was necessary to find a critical age when people's principles and work values change. We had all the necessary information: questions with different ages for different answers. The next important task was to choose the age that gives the greatest differentiation. We created a separate variable called "age groups" that divided respondents into "younger" and "older" groups. It divided the respondents into only two groups, since the previous steps show that more groups are not necessary, because there is usually only one significant change of values in the answers to questions: two of the three options usually converge in the composition of the respondents, and the third is in the other side.

Using this methodology, we used the Chi-squared test, which shows how the available numbers differ from the expected ones. Seeing that p-value <0.05, we rejected the non-zero hypothesis (data differs from equidistributed, i.e. independent) and said that there is some measure of Association between variables. We used the concept of "residuals" (the difference between observed and expected values) and measured dissociation using them. This logic was worked out with all the variables to find the age at which the associative force of separation is strong enough. We took ages from 30 to 40 years - if we took the boundaries wider, there would be a small number of observations, which would reduce the quality of the test. That is why we used these borders, because we do not have a warning in them that the test might be unreliable. These limits are suitable for us, because previously all the averages were in this range. Then we took all the variables that had some difference in the median values. At this step, a new array was created that contained only these variables. Next, we calculated the Chi-squared test for all variables, so that this number is as large as possible, so that it has a discriminating force.



3.Analytical part

3.1 Data preparation and age-gender structure

Before analysis, all the data from the survey was recoded for ease of use.

The gathered data was prepared and checked for missing data and outliers. No missing data or outliers were detected.

In the graph below, we can see the distribution of respondents by age, without taking into account their gender, to see what ages and in what proportion by each age people took part in the survey.

The average age of respondents is 34.68 years. The median is 34 years.

Figure 3. Age distribution of the respondents of the survey

A graph with a gender and age breakdown allows us to see the distribution by gender and age at the same time and shows how evenly these indicators are distributed in the company.



Figure 4. Age-gender structure of the respondents

Despite the even distribution by gender, we can see that there is a deviation, since people from the oldest age group were the least likely to participate in the study.

As there is a deviation, we run the Shapiro-Wilk test.

Null hypothesis: the data is distributed normally. Then, since p-value <0.05, we reject the null hypothesis and say that sufficient basis has been provided for the judgment that the data is not distributed normally. Therefore, we are looking primarily at medians rather than averages.



Figure 5. Check for normal distribution

3.2 Motivation by generational clusters and finding the "breaking point"

For generational clustering, a cluster analysis was performed, which allowed to group the responses of respondents in a common space so that the division into clusters makes sense.

The meaning of clustering is reflected by measuring the distance between objects. For this purpose, we used the variable "gower": we made a matrix where we measured the distance between objects.

For clarity, two main clustering methods were used: divisive (top-down) and agglomerative (bottom-up).

First, for both methods, we used the "silhouette" metric (silwidth): they showed how close the elements of one cluster are to the elements of another.



Our goal is to select the number of clusters so that the average silhouette width is as high as possible, so that the distance between the clusters is large enough, otherwise we will not be able to divide the data into clusters.

In both cases, the division into two clusters is most successful. However, in the divisive method, we can also try dividing into 3 clusters, since the metrics (average silhouette width) in the divisive method are slightly better in this case (the fullness will be higher).

Next, we turned to the elbow method, which allows us to find the fracture to which the indicators will decline. To do this, we can look at the change in the sum of the squares of the distance along the Y axis on the charts below.



Next, we do the same as with the silhouette method. It is important for us that the change in the sum of squares increases, but we want to try to divide the sample into more than two clusters. We can see that on the chart of the divisive clustering there is a strong decline on the 3rd cluster (that is, we exactly do not consider more complex clustering), so we can consider dividing into three clusters.

There are the divisive plot and agglomerative plot below. Among the combinations of their division into clusters, we will look for the most successful.



Let us start with the agglomerative plot. As it was found out earlier, it makes sense to divide it only into two clusters (but we also illustrate the division into three clusters). Below we present a clustered (and coloured in such way) agglomerative plots.



The table with the statistics for agglomerative plots shows cluster division options and their corresponding values of various variables, including the dimension of each cluster for different division options.

Table 2. Statistics for agglomerative plots

Next, we will move on to the more appropriate divisive method and ways for dividing into two or three clusters. The graphs below are colored accordingly:

The graph where the clusters are shown in colors visually indicates that the divisive plot can be divided into three clusters much more suitable and evident than the agglomerative plot. Let us check this by checking the statistics in the table.



Table 3. Statistics for divisive plots

Indeed, dividing into three clusters according to the table shows us dividing into three relatively data-filled clusters, which are also fairly evenly filled (59 observations in the first cluster, 73 observations in the second cluster, and 64 observations in the third cluster). Therefore, we can divide the sample into three clusters using the divisive method.

Next, we plot the distribution of clusters by age using Excel in order to understand whether it is possible to operate these clusters from a generational point of view.

If we divide our data into two clusters and look at the age distribution, the agglomeration method proved to be more convenient and clear in terms of age distribution.

Figure 16. Age distribution for two clusters, the agglomeration method



According to this graph, we have two clusters, the first one (indicated in blue) mostly covers people under 35-38 years old, while the second one is gaining popularity among people over 35 years old.

Next, let us turn to the graph that divides people into three clusters.

Figure 17. Age distribution for three clusters, the agglomeration method

Here we can also see certain portraits of people. Thus, one group is mainly in the range of up to 30 years, the second - from 28 to 42, the third-from 39 to 55. Although the boundaries are somewhat blurred, and some people may belong to a different group, this may be due to sociodemographic factors, such as having financial obligations to a family, partner, mortgage, or loan. And also, more importantly, with the fact that the change of values can not occur simultaneously for everyone at a particular age, it is rather a certain range of transition. In other words, we can conclude that, even taking into account third-party factors, we can form approximate groups of people, which can be called three different clusters. There is also a variant of dividing into two groups - a clearer one. Further research, which will also take into account the age effect, will help find a more specific age or age of change in values and will help more accurately (since it is more convenient to use age) to track other factors that affect labor values.



3.3 Motivation by age and finding the "breaking point"

According to Shapiro-Wilk test, sufficient basis has been provided to say that the data is not distributed normally.

Therefore, we do not use parametric methods (ANOVA). Instead, we use a nonparametric analog - the Kraskel-Wallis test (to check the equality of medians of several samples). In this case, there is no dependence on which distribution the data is taken from.

Then we take all the variables in the dataset and built boxplots based on them. Boxplots show the average value, whereas Kruskal-Wallis test is focused on medians, so we mainly focus not on graphs, but on tests, using graphs mainly for visualization.

A test was performed for all variables: only those cases where p-value <0.05 are suitable for further analysis. After getting a list of variables that have different averages, we can look at the conjugacy tables (which contain the information about response options, the number of responses, the average value, and the median).

The graphs with boxplots below show differences in the average age for those who answered a particular question in a particular way except for fairly obvious ones (such as having children and the fact that the older the Respondent, the more likely they are to have a child over 18 or, for example, to be married).



As for the first boxplot, it refers to the section of projective questions. The answers "1" (Constant search for new solutions in the context of crises and instability. Focusing only on yourself - your experience, intuition, and social connections) and "2" (Work without a clear plan, in which there is a lot of creativity, and priority is given to tasks that promote self-search and self-development) were assigned to generations X and Y, respectively, but there was no significant difference in the respondents who chose them. However, the answer "3" (Following the plan when there is a clear statement of tasks, algorithms and rules; when it is possible to predict the development of events in advance), prescribed to baby boomers, is really chosen by people of older age (from 35 years).

The boxplot 2 refers to the group of direct questions. Those who would choose free access to all series on one of the popular online platforms («1») are the youngest respondents. Those who would choose certificate to the store for home and garden stuff («2») are the group of the middle age and those who would choose increasing the funded component of a pension («3») turn out to be the oldest people in the sample.



The people of younger ages chose variant «1» (Free subscription for food delivery with a limit of 1000 rubles per week). Whereas the distribution of the choice of options "2" and "3" ("a trip to a health resort for 2 weeks" and "co-financing the child's education at the University") was almost evenly among for older people choice. It can be assumed that in this case, such factors as, for example, the presence of children of a certain age in a family (children in a university or a small/adult children).

The opinion about the value system of their generation was the most different from other among older people: they chose option "3" (Responsibility, respect for the position and status, hard work). The other two options ("2" - lifelong learning, choice, self-reliance, and "1" - Change, immediate reward, self-confidence) are roughly evenly chosen by people who are younger.

Next, it is necessary to find a critical age when people's principles and work values change. So, we created a separate variable called "age groups" that divides respondents into "younger" and "older" groups. It divides the respondents into only two groups, since there are usually only one significant change of values in the answers to questions: two of the three options usually converge in the composition of the respondents, and the third is in the other side.

Take, for example, the variable "labor format". When we look at the conjugacy table, we see that the young ones in the first two answers outweigh the majority, while the others who answered otherwise are more than 35 years old. Counting the Chi-square, which shows how the real numbers differ from the expected ones, we see that p-value <0.05. We have a non-zero hypothesis, and the data is different from equidistributed, i.e. independent. In this case, we reject it and say that there is some measure of Association between variables. We can also look at how they would be positioned if they were independent (that is, if they didn't have some kind of Association) and what remains. Residuals are the difference between observed and expected. We can look at and visualize this: the darker the color, the stronger the dissociation, meaning that "older" people are more likely to choose the third answer, and "younger" people are more likely to not. That is, the power of association here is negative or positive. We "automated" this logic and applied it to all variables to find the age at which the associative force of separation is strong enough. We take the age from 30 to 40 years - if we take the boundaries wider, there will be a small number of observations, which will reduce the quality of the test. This is why we use these boundaries, because there is no warning that the test may be unreliable within these boundaries. These limits are suitable for us, because previously all the averages were in this range. Then we take all the variables that had some difference in the median values. This step creates a new array that contains only these variables. This is a container where responses will be recorded.

If the test is not significant (there is no difference, so there is no point in considering it), we write 0 to the container. And if there is a difference, we write down the module of the sum of the balances to find out what this number is. We need this number to be as large as possible, so that it has a discriminating force. As a result, if we have a plot, we see that 32 and 35 are located at the maximum, so it makes sense for us to consider 32 (this age shows the very maximum).

Below is the example: projective question about labor format.

Figure 22. The example check for 32 years for the question «labor format»

Where answers are:

* "1" - "Constant search for new solutions in the context of crises and instability. Focus only on yourself - your experience, intuition and social connections";

* "2" - "Work without a clear plan, in which there is a lot of creativity, and priority is given to tasks that promote self-search and self-development";

* "3" - "Following the plan, when there is a clear statement of tasks, algorithms and rules; when it is possible to predict the development of events in advance"

The dark color confirms a strong dissociation.

When checking the output for an error, we check that older people are really associated with the third option. Also, if you go back to the question "motivation_promotion_good_results", young people are really associated with the 1st option (free access to TV series), and older people-with the third option (increasing the funded component of the pension.

Thus, in the age analysis of data from ten questions, four "worked out": using the Kruskal-Wallis test, we showed questions that have a difference in the value of the medians. Then the method of iteration was used to find the age of the value change boundary at which the difference between the observed and expected values in these questions is maximum. That is, when people's answers to these questions are as far as possible from the case when these answers are evenly distributed.



Conclusion

We studied the theoretical approaches of dividing population into generations. We created theoretical model, which ties the Theory of Generations and the company's motivational system. Based on these theoretical approaches, we conducted research for analysis of values, expectations and motivation of employees of PJSC “Rostelecom”.

The Theory of generations allows employees of the HR Department to generalize, make assumptions based on a person's belonging to a particular generation and choose a strategy based on the available introductory, in order to increase his involvement and make his stay in the company comfortable for him. If the company meets the most important needs of the employee, then he himself, being loyal to the employer, will do his work with maximum involvement, efficiency, which will have a positive impact on the financial results of the company - this explains the bilateral importance of the Theory of generations for employees of the Talent Acquisition Department.

Despite the fact that not all the answers of employees coincide with the theoretical ideas about a particular generation, the main trends are still traced and have quite logical explanations. This study was conducted to compare two different approaches to division by generations or, in other words, whether the chronological division by generations concurs with the division by generations based on the working motivation of people.

Our research reviewed that the most drystical division is for the generations with Soviet background (19650-1975) and generations who socialized after the disruption of Soviet Union (1976-2000). The value system of the respondents with Soviet background was shaped around values of security, stability, predictability and approval, whereas the value system of others was shaped about self-realisation and approval of senior colleagues.

That is, in General, we can show that the chronological division into generations according to Howie and Strauss is not quite applicable to the Russian reality, because there was a turning point during the Soviet Union. Thus, if we divide the generations into 2 groups (post-Soviet and Soviet), we see the coincidence of chronological division and division by values.

Thus, we were able to answer the main research question which was to find "breaking points" in belonging to a particular generation in PJSC “Rostelecom” and investigate how the system of values and the most motivating factors change depending on belonging to a generation. ?



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Applications

Application 1: The survey (with keys)

Dear colleagues!

I'm writing a master's thesis on how to improve our current employee incentive system. Your honest and complete answers will greatly help me cope with this task and better understand what is important to you and what motivates you.

The form is anonymous. It contains three sets of questions. All questions assume only one answer.

Filling out the form will take 7-10 minutes.

Thank you for your time!

Block 1 (Direct questions)

1. How do you think, is there a need to change something in the existing system of personnel motivation in our company?

* No, I'm fine with it

* Yes, additional social guarantees and support measures are needed (BB)

* Yes, the current system is outdated and requires a complete revision (Y)

* Yes, I want to see that the high results of my work are truly appreciated by the management (X)

2. Choose the most interesting and attractive option for you to reward for high performance (all options are equal in value):

* Increase the funded component of the pension at the expense of the employer (BB)

* Free access to all series on one of the popular online platforms (Y)

* Certificate to the store for home and cottage repairs (e.g. Obi, Leroy Merlin) (X)

3. Which incentive option would you choose from the following three (they are also equal in value)?

* Ability to work remotely once a week (Y)

* Payment of a monthly travel card or payment of gasoline for a month (X)

* Extended medical examination once a year (BB)

4. Which behavior model best describes you?

* I am a team player, I always prefer to consult with colleagues before making decisions (BB)

* I prefer to work alone, solve problems and make decisions based on my views and values (X, Y)

5. I believe I could have made a great contribution in a job where:

* There is an opportunity to establish good relationships with colleagues and which gives confidence in the future (X)

* I could show my worth as a worker (BB)

* I have the opportunity to improve and grow as a person (Y)

Block 2 (Projective questions)

6. What format of work best describes representatives of your generation?

* Following the plan, when there is a clear statement of tasks, algorithms and rules; when it is possible to predict the development of events in advance (BB)

* Constant search for new solutions in the face of crises and instability. Focus only on yourself - your experience, intuition, and social connections (X)

* Work without a clear plan, in which there is a lot of creativity, and priority is given to tasks that promote self-search and self-development (Y)

7. I believe that most of my generation would NOT want to work in a place where (please choose the most appropriate option):

* There are no clear instructions, it is not known what is required from the employee (BB)

* There is almost no feedback or it is very slow, because the management uses outdated methods and formats of communication (Y)

* Poor working conditions, even the basic needs of the middle class (X) are not met

8. What option do you think your generation would most likely choose to reward high performance?

* Co-financing of a child's University education (X)

* Free subscription for food delivery with a limit of 1000 rubles per week (Y)

* A trip to a health resort for 2 weeks (BB)

9. How do you think, if your colleague were offered a choice of several incentives, what would they prefer?

* Thanks signed by the President of the company and a special badge on the portal (BB)

* A surprise gift from colleagues (X)

* Certificate for offline or online courses (Y)

10. Which value system do you think best reflects the values of your generation?

* Responsibility, respect for the position and status, hard work (BB)

* Changes, immediate rewards, self-confidence (Y)

* Learning throughout life, choices, hope itself (X)

Block 3 (Sociodemographic)

11. Choose your gender:

* Male

* Female

12. Your age:

____

13. Do you have children?

* No

* Yes, at least one of the children is under 18 years old

* Yes, child / children over 18 years of age

14. Your marital status:

* Not in a relationship

* In a relationship, but not in a marriage

* In a registered marriage

15. Are you planning to take out a loan / mortgage in the near future?

* Already have a mortgage or loan (X)

* I plan to take out a mortgage or loan (Y)

* No and I don't plan to (BB).

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