2. Cluster analysis in SPSS Statistics with the aim of dividing the total sample of respondents into clusters based on the attitude towards digitalization in the company and in the industry as a whole;

3. Content analysis in order to identify inconspicuous significant factors for each previously obtained cluster.

The first was the associative analysis. Below we consider the results of the conducted analysis for 12 respondents.

According to the in-depth interview results, we received the following pool of respondents:

A. Age:

- 18-23 years old - 2 respondents;

- 24-29 years old - 5 respondents;

- 30-35 years old - 1 respondent;

- 36-41 years old - 3 respondents;

- 42-47 years old - 1 respondent;

- 48-53 years old - 0 respondents;

- 54-59 years old - 0 respondents;

- 60 years old or older - 0 respondents.

B. Work experience:

- Less than 1 year - 2 respondents;

- 1-3 years - 4 respondents;

- 4-7 years - 3 respondents;

- 8-11 years - 1 respondent;

- More than 11 years - 2 respondents.

As mentioned earlier, this analysis should show the presence or absence of associative links between the respondent's age and his attitude to digitalization, as well as work experience and attitude to digitalization.

The attitude of digitalization to strategy is determined by the following questions from the in-depth interview:

1. In your opinion, is there a favorable environment in Russia for the development of digitalization in the oil industry?

2. Do you think that digitalization will be able to improve business processes in the company?

3. Do you think that the existing digital strategy will lead to an improvement in the company's business processes?

4. If you had the opportunity to influence the formation of the company's digitalization strategy, for example, in the form of voluntary participation in projects related to testing the application of digital technologies in business processes, would you participate in this?

Therefore, it is now necessary to check the presence or absence of associative links between the following pairs:

A-1; A-2; A-3; A-4; B-1; B-2; B-3; B-4. Total, starting the deployment analysis of communication, we get 8 possible associations. We denote that for significant correlations or associations, the P-value should be less than 0.05. If the value exceeds a given digit, the relationship between the variables is assignable. (Appendix B)

Comparing the first pair of A-1, we obtain P-value = 0.2953. This is a designation that this association is insignificant and it is meaningless to work with it further. (Appendix C)

Comparing the second pair of A-2, we obtain P-value = 0.6387. This is a designation that this association is insignificant and it is meaningless to work with it further. (Appendix D)

Comparing the third pair of A-3, we obtain P-value = 0.3594. This is a designation that this association is insignificant and it is meaningless to work with it further. (Appendix E)

Comparing the fourth pair of A-4, we obtain P-value = 0.8583. This is a designation that this association is insignificant and it is meaningless to work with it further. (Appendix F)

Comparing the fifth pair of B-1, we obtain P-value = 0.4764. This is a designation that this association is insignificant and it is meaningless to work with it further. (Appendix G)

Comparing the sixth pair of B-2, we obtain P-value = 0.2548. This is a designation that this association is insignificant and it is meaningless to work with it further. (Appendix H)

Comparing the seventh pair of B-3, we obtain P-value = 0.4238. This is a designation that this association is insignificant and it is meaningless to work with it further. (Appendix I)

Comparing the eighth pair of B-4, we obtain P-value = 0.2818. This is a designation that this association is insignificant and it is meaningless to work with it further. (Appendix J)

Finally, in view of the small sample, which is more typical for qualitative than quantitative analysis, it was impossible to obtain relevant results during the course of an associative analysis.

The next analysis was carried out in the cluster program SPSS Statistics. Below are the data of the analysis, based on which primary conclusions were made.

As can be seen in the table, the first significant jump in the data occurs from stage 9 to stage 10, to the size of the coefficient - 3,705. Thus, we have determined the step at which the first jump of the coefficient -10 occurs. Further, to determine the optimal number of clusters, it is necessary to subtract the obtained value from the total number of observations (sample size).

Table 2

Order of agglomeration outcomes

	Merged cluster		First appearance stage cluster
Stage	Cluster 1	Cluster 2	Coefficients	Cluster 1	Cluster 2	Next stage
1	1	12	,000	0	0	5
2	10	11	,000	0	0	3
3	8	10	,000	0	2	6
4	3	4	,000	0	0	7
5	1	9	1,760	1	0	7
6	5	8	2,588	0	3	8
7	1	3	3,175	5	4	9
8	2	5	4,529	0	6	11
9	1	6	5,198	7	0	10
10	1	7	8,903	9	0	11
11	1	2	11,432	10	8	0

The total sample size in this case is 12 respondents; therefore, the estimated optimal number of clusters is 12-10=2. In this case, the identified number of clusters was the most optimal. The first cluster combines employees with a positive attitude to digitalization, the second on the contrary - with a negative attitude. Based on the updated data, 7 employees belonged to the first cluster, 5 employees to the second. Details of the analysis may be found in Appendix K, L.

Table 3

Cluster analysis results

Age, years old	Work experience, years old
	Cluster 1	Cluster 2		Cluster 1	Cluster 2
18 - 23	1	1	Less than 1	2	2
24 - 29	4	1	1 - 3	2	0
30 - 35	1	0	4 - 7	2	1
36 - 41	1	2	8 - 11	1	0
42 - 47	0	1	More than 11	0	2
48 - 53	-	-
54 - 59	-	-
60 or older	-	-

As can be seen from the results of the analysis, the first cluster includes younger employees of the units: 5 people out of 7 aged 18 to 29, 2 people out of 5 aged 30 to 47; when the second cluster includes more mature employees: 2 people out of 7 aged 18 to 29 years and 3 people aged 30 to 47. From this, it may be concluded that the older the employee of the company, there is a more skeptical attitude he or she has to digitalization.

Regarding experience, the first cluster includes 4 people with experience from less than a year to 3, two people with experience from 4 to 7, 1 person with experience from 8 or more; the second cluster - 2 people with experience from less than a year to 3, 1 person with experience from 4 to 7, 2 people with experience from 8 to 11 years. Therefore, the conclusion is that the less experience an employee has the more open he is to digital transformation.

Further, the last stage of this part is content analysis. First, it was necessary to identify the categories, as well as codes - specific words for each of the categories.

Category 1 - Digitalization of the oil industry;

Code 1 - efficiency, Code 2 - modern technologies, Code 3 - digital projects, Code 4 - development, Code 5 - prospects, Code 6 - costs, Code 7 - changes, Code 8 - acceleration, Code 9 - simplification, Code 10 - complication, Code 11 - positive, Code 12 - negative, Code 13 - transparency, Code 14 - time, Code 15 - quality.

Category 2 - Barriers to digitalization in the oil industry;

Code 1 - law, Code 2 - regulation, Code 3 - conservative, Code 4 - requirements, Code 5 - competence, Code 6 - qualified, Code 7 - foreign, Code 8 - responsibility, Code 9 - professionals.

Category 3 - Digitalization in the company's development strategy;

Code 1 - efficiency, Code 2 - competence, Code 3 - KPI, Code 4 - product, Code 5 - indicators, Code 6 - goals, Code 7 - opportunities, Code 8 - achievement, Code 9 - political, Code 10 - economic, Code 11 - social, Code 12 - sanctions, Code 13 - favorable (conditions).

Further, after the categories and codes have been broken down, it is necessary to calculate the number of words suitable for each cluster and each category.

Table 4

Content analysis results with categories and codes

Cluster 1	Cluster 2
Cathegory 1, words	Cathegory 2, words	Cathegory 3, words	Cathegory 1, words	Cathegory 2, words	Cathegory 3, words
Code 1	3	Code 1	0	Code 1	2	Code 1	1	Code 1	3	Code 1	0
Code 2	0	Code 2	0	Code 2	1	Code 2	1	Code 2	1	Code 2	0
Code 3	0	Code 3	1	Code 3	1	Code 3	1	Code 3	1	Code 3	0
Code 4	0	Code 4	2	Code 4	1	Code 4	0	Code 4	0	Code 4	0
Code 5	0	Code 5	1	Code 5	2	Code 5	0	Code 5	0	Code 5	1
Code 6	1	Code 6	1	Code 6	2	Code 6	2	Code 6	0	Code 6	0
Code 7	0	Code 7	1	Code 7	1	Code 7	2	Code 7	0	Code 7	1
Code 8	0	Code 8	0	Code 8	1	Code 8	1	Code 8	0	Code 8	0
Code 9	0	Code 9	1	Code 9	1	Code 9	1	Code 9	0	Code 9	1
Code 10	0			Code 10	1	Code 10	0			Code 10	2
Code 11	5			Code 11	0	Code 11	3			Code 11	1
Code 12	3			Code 12	3	Code 12	4			Code 12	1
Code 13	0			Code 13	3	Code 13	0			Code 13	1
Code 14	1					Code 14	2
Code 15	0					Code 15	0

Based on the analysis we can draw the following conclusions:

1. Cluster 1. In category 1, the most common codes were 1 (efficiency) - 3 repetitions, 11 (positive) - 5 repetitions, 12 (negative) - 3 repetitions. Based on this, we can conclude that the respondents of this cluster consider the digitalization in the oil industry to be quite significant and effective, and they see more positive than negative effects of digitalization on the business.

2. Cluster 2. In category 1, the most frequently encountered codes were11 (positive) - 3 repetitions, 12 (negative) - 4 repetitions. Based on this, we can conclude that the respondents of this cluster consider the digitalization in the oil industry more ineffective than effective. The average number of repetitions for codes 6 (costs), 7 (changes) and 14 (time) - 2 repetitions. These factors indicate that respondent's digitalization makes its own changes in the industry, and allows reducing both time and production costs.

3. Comparing the results for clusters 1 and 2, we can conclude and confirm that respondents from cluster 1 are more positive about the changes taking place in the industry due to digitalization than respondents from cluster 2.

4. Cluster 1. In category 2, the most common code was code 3 (conservatively) - 2 repetitions. Based on this, we can conclude that the respondents of this cluster consider the conservatism of some employees and companies in General the most significant and decisive barrier today for digitalization in Russia.

5. Cluster 2. In category 2, the most common code was code 1 (law) - 3 repetitions. Based on this, we can conclude that the respondents of this cluster consider the unprepared legislation the most significant and decisive barrier today for digitalization in Russia.

6. Comparing the results of clusters 1 and 2, we can conclude that the respondents of both clusters see barriers to digitalization in the country and they are intangible, requiring radical and long-term changes.

7. Cluster 1. In category 2, the most common codes were code 12 (sanctions) -3 repetitions and code 13 (favourable (conditions)) - 3 repetitions. The average number of repetitions was in codes 5 (indicators) and 6 (goals) - 2 repetition. Based on this, we can conclude that the respondents of this cluster believe that digitalization directly affects the various indicators of the company, its short-term and long-term goals, and moreover, find its impact favorable. The only disadvantage is the us sanctions policy, because if sanctions affect the development of digitalization in Russia and in the company in particular, they affect the company's development strategy.

8. Cluster 2. In category 2, the most common code was code 2 (economic) - 2 repetitions. The average number of repetitions was in codes 11 (sanctions) and 13 (favorable (conditions)) - 1 repetition. Based on this, we can conclude that the respondents of this cluster believe that digitalization has a positive impact on the economic performance of the company in the first place, and their increase causes a growing level of production and sale of petroleum products, which is what digitalization affects in the first place.

9. Respondents of this cluster have a similar opinion with the respondents of the first cluster regarding the impact of sanctions on the company's development strategy.

Based on the foregoing, previously set hypotheses may be rejected or confirmed, duplicate them below:

1. The development strategy of company is closely related to digitalization and digital economy - п confirmed;

2. The more time employees work in the company, the more negative attitude they have towards digitalization - confirmed;

3. Company employees see only the theoretical, non-practical development of the company's digital strategy - rejected, in view of the fact that today employees are involved in digital projects and touch them; the strategic development of the company involves the use of digital tools in many business processes: from mining to purchasing;

4. Company has Incremental development strategy, rather than Evolutionary or Grand design - confirmed.

We will also answer the previously raised research and subsidiary questions:

Research Question: How does intellectual capital in the form of digitalization and its products affect the development strategy of the oil producing company PJSC Gazprom Neft? Digitalization, as part of intellectual capital, has a direct positive impact on the company's long-term development strategy, by providing unique solutions for industry issues and problems.

Subsidiary Questions:

* Does structural capital have a significant impact on the development strategy of a Russian oil company? Yes, structural capital is of high importance in the company's development strategy, since the knowledge gained by employees in preparation for working with digitalization in the form of research and pilot tests directly affected the construction of the track for the company's long-term strategy.

* Do strategies of development of other industrial enterprises in Russia influence the development strategy of oil producing companies? Yes, the development strategies of industrial companies directly influence the strategies of oil companies, since government regulation primarily relates to industry and further specializes in a specific industry, in the form of approval, for example, using drones in activities.

* Is the Russian digital economy ready for the introduction of digital products into the activities of a Russian oil company? According to the analysis of the media, as well as the company's performance, the Russian digital economy is at the initial level of development and it has yet to “get on its feet”.

* Does digitalization have barriers to development in Russian oil companies? Yes, digitalization has its own barriers to entering the Russian oil market. The two main reasons are the US sanctions policy, which does not allow, for example, the use of monograms for API products, which in turn makes it difficult to acquire a license to work with digital tools, as well as the conservatism of the industry and some employees.

* Is digitalization, according to company employees, significant in terms of strategy for the next 5 years? Yes, according to employees, digitalization is important both today and in the long-term strategy; this can be seen from the results of their deep work with digital tools.

Conclusion

The purpose of following bachelor thesis was to determine the influence of intellectual capital in the form of digitalization and its products on the development strategy of an oil producing company. Moreover, the following research question was raised: How does intellectual capital in the form of digitalization and its products affect the development strategy of the oil producing company PJSC Gazprom Neft? In the course of the analysis of theoretical works on this subject, analysis of unique case situations, as well as conducting in-depth interviews with experts, followed by three comprehensive analyses of quantitative and qualitative nature, the answer to this question was received. These components really influence each other from a positive point of view, increasing efficiency, increasing development through overcoming industry difficulties and barriers.

Moreover, in the course of the study, answers were received to 5 subsidiary questions. All the answers were positive and in General allowed us to understand and conclude that digitalization in the oil industry is taking place, as new practices are constantly emerging, there are ambitions a wholesome competition in the technology of the oil industry. However, to perfection is still far enough, because the legislative regulation, which is very important in Russia, is not yet ready to fully control the ongoing innovations.

In the course of associative, cluster and content analysis, a lot of useful and interesting information was obtained, which allowed us to work on the previously 4 hypotheses. Three of them were confirmed and one was rejected. The confirmed hypotheses suggest that the company's development strategy is directly related to the digitalization taking place in it and that the company is developing, using digital tools gradually enough, taking into account the experience and mistakes of the previous stages. Also, it turned out to confirm the fact that the more experience the employee has in the company, the more skeptical he is about innovation and digitalization in particular. Moreover, the same reaction was noted in more Mature employees. For example, in one group of people - cluster 1, with a positive attitude to digital change, young people aged 18 to 29 were 3 more than in the other group - cluster 2. The opposite result was for older employees: in cluster 2 at the age of 30, there were 1 more respondents than in cluster 1. It is also interesting to note the figures in the experience of employees in cluster 1 with an experience of not more than 3 years was 4 employees, while in cluster 2 is twice less. With an experience of over 11 years, the respondents included in the cluster 2, in cluster 1, the individuals with the experience was not all.

In the course of the work, some difficulties were revealed, which later turned into limitations. They are mainly related to the type of data collection and the sample size. The limitations of in-depth interviews do not allow for some analysis of the data obtained, as we have already seen with the associative analysis. Additional results would be very interesting, but they could only be obtained with a larger sample. Also, there is no opportunity to ask all questions of interest to the interviewer, especially with this category of respondents. Employees are usually very busy and it is extremely problematic to set aside from them even 30 minutes at a lunch break or after a working day. Moreover, due to time constraints and not always a great desire to give open and detailed answers to questions, the respondent can simply refuse some answers or respond dryly.

In view of the fact that the topic turned out to be quite interesting and relevant for the study, it can be developed in the following directions:

- Conducting research based on respondents from the production units, that is, those people who directly work on oilrigs, processing plants, work on the shelf, in the Arctic fields;

- Conducting a study based on respondents from other departments, who this time interacts with digitalization much less and knows about it;

- Conducting research based on the respondents from the top management of the company, that is, with the group of people who directly determine the development vector, working on short-term and long-term strategies, working together with the public sector;

- Conducting research based on the industry level, with the participation of the top 5 oil and oil and gas Russian vertically integrated oil company.

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Appendix 1

Interview questions

Dear Colleagues!

In order to determine the impact of digitalization, as well as digital technologies on the current activities of the company and its development strategy, we ask you to take a survey consisting of 31 questions.

1. Please indicate your age (full years):

2. Please indicate your experience in the company:

Please tell us about the main activities of the company.

3. In which department do you work?

4. How long has your department been on the market?

5. How many employees are in your department permanently?

6. What are you your current duties? What are the main areas of the department under your development?

7. What are your the long term development goals?

Block 1. Digitization

8. What attitude do you have to digitalization in the oil industry?

9. What are the positive and negative effects associated with digitization in the oil industry?

10. Is there a favorable environment in Russia for the development of digitalization in the oil industry?

11. Is the Russian digital economy ready for the introduction of digital products into the business processes of Russian VIOCs?

12. Does digitalization have barriers to development in Russian VIOCs? If so, which ones?

Block 2. Strategy

13. Tell about your company's strategy. What does term strategy mean to you?

14. Who from employees are involved in long term planning of the company's activities? How roles are distributed?

15. How would you describe the process of formation a strategy (the company's long term activities) in your company? What kind of events would you highlight?

16. How and how often do these events take place?

17. What activities have the greatest effect on the company's strategy? Why?

18. What is important for you in formation a strategy? What information do you take into account?

19. What factors would you call decisive in the formation of a strategy?

20. How would you describe the external environment of your business? Are these conditions favorable? Why?

21. How do these conditions affect your company's strategy? How important is the strategy for a company running a business in such conditions?

22. How does the activity of your company depend on external economic factors? Have there ever been cases when a company's strategy had to be revised or adapted? How it was?

23. Do the development strategies of the industrial sector in Russia influence the development strategies of Russian VIOCs?

Block 3. Digitalization in business processes and development strategy of a company

24. Is Gazprom Neft's development strategy connected with digitalization today?

In 2018, Gazprom Neft approved the digital business transformation as one of its priorities. Moreover, the company decided to create a digital transformation directorate.

25. How do you relate to the process of digitization of the company's business processes in the context of the introduction of digital technologies? (such as Internet of things, cloud technologies, augmented reality, machine learning)

26. Do you think that digitalization can improve business processes in a company?

27. Do you think that the existing digital strategy will lead to an improvement in the company's business processes?

28. Do you think that the digitization of your department will have a positive impact on the performance of the company?

29. Do you think that companies should give more coverage to employees about the ongoing digitalization of business processes?

30. Do you think that companies should give more coverage to employees about future plans related to the digitization of business processes?

31. If you had the opportunity to influence the formation of a company's digitalization strategy, for example, in the form of voluntary participation in projects related to testing the application of digital technologies in business processes, would you take part in this?

Appendix 2

Associative analysis, Deployment analysis of communication

Appendix 3

Associative analysis, Pair A-1

Appendix 4

Associative analysis, Pair A-2

Appendix 5

Associative analysis, Pair A-3

Appendix 6

Associative analysis, Pair A-4

Appendix 7

Associative analysis, Pair B-1

Appendix 8

Associative analysis, Pair B-2

Appendix 9

Associative analysis, Pair B-3

Appendix 10

Associative analysis, Pair B-4

Appendix 11

Cluster analysis

Appendix l2

Cluster analysis, Dendrogram

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