Abstract. The present paper presents blogosphere analysis as an alternative method of monitoring small and medium enterprise performance in Russian federation subjects. The study, carried out using publicly available online tools, reveals the main challenges facing SMEs in the Siberian Federal District of Russia, with the most widely discussed topics being the tax system and enterprise support programs. 

Keywords: monitoring, blogosphere, social networks, small and medium enterprise, federal subject classification.


1. Introduction

The goal of the present study is to set out a method of monitoring small and medium enterprise performance through both statistical (including correlation and cluster analysis) and alternative means (blogosphere analysis). The proposed method is expected to make analysing SME mesoscale performance analysis more effective.

Coined in 1999 as a joke by an Englishman named Brad L. Graham, the term blogosphere was subsequently re-introduced by William Quick. Initially used by bloggers reporting on the US war in Afghanistan, the term went on to spread outside the warblogging community. With the information society gaining prominence, since 2002 blogosphere analysis has become a staple of opinion surveys.

Recently, there has been an increased interest in the use of monitoring at different levels as a means of addressing various economic problems, with new organisations engaged in monitoring various aspects of life appearing almost daily. Using blogosphere analysis in addition to standard statistical tools to monitor SME performance allows one to instantly gauge user reaction to reforms, detect weak spots, and quickly address development issues.

2. Research into small and medium enterprise performance

Late 2000s saw SMEs becoming a point of interest for the government. With Russian SMEs responsible for just 15 to 25 per cent of the country’s GDP (compared to over 50% in most of the developed nations), President Putin tasked the government with bringing the figure up to 60-70%. The current figures indicate that small and medium enterprises still have a long way to go towards boosting the country’s economic growth [6].

According to World Bank Group’s 2014 Doing Business rating, Russia is a lowly 92nd out of 120 countries in terms of ease of doing business [5].

Using the Internet for doing business is beyond many Russian entrepreneurs’ understanding. According to the survey figures, less than 35% of Russian citizens use the Internet on a daily basis.

The causes and consequences of Russia’s geographically uneven SME development, identified with the help of the logical framework approach, are presented in Figure 1.

Figure 1. Uneven development of SMEs across Russia’s federation subjects: problems tree chart


Issues connected with taxaction, administrative burdens, real estate, bank loans, and support programs must be addressed by the local governments.

But the lack of a comprehensive monitoring system can be addressed by developing a system that would integrate both qualitative and quantitative indices of SME performance.

One of the causes of uneven regional SME development, detected by the authors of the present paper was the absence of a comprehensive regional-level SME monitoring system, which means no full picture of regional SME development is available.

It is possible to monitor small and medium enterprise performance at both federal (national) and regional levels. The main sources of information about business activity are as follows:

  1. Federal State Statistics Service’s official reports on business activity [10];
  2. Small and Medium Enterprises in Russia statistical digests;
  3. Unified Interdepartmental Statistical Information System’s website offering the relevant figures on demand [1];
  4. Regional websites on SMEs offering information on latest reforms, as well as regional statistics;
  5. Chamber of Commerce and Industry’s official website publishing SME performance monitoring data;
  6. OPORA ROSSIYI’s Conditions for doing business in Russia annual reports on SME performance according to entrepreneur surveys [15];
  7. Federal State Statistics Service’s 2012 Continuous Reading of SME performance data [14];
  8. Federal Web Portal for Small and Medium-Sized Enterprises’ statistical figures [16].

Most of the above assess SME performance using quantitative (statistical) data. To obtain a complete picture of conditions for small and medium enterprises, a monitoring system must include analysis of both quantitative and qualitative data. There are federal-level figures based on qualitative data, the so-called OPORA Index. However, reporting on only 30 of the regions, it does not provide full qualitative data for assessing mesoscale SME performance. There is, therefore, a lack of data on mesoscale SME performance.

Using the logical framework approach, Figure 2 features the above problems tree chart transformed into a goals tree chart.

Figure 2. Actions needed to even out development of SMEs and their results


An alternative means of detecting problems would be blogosphere analysis. The term, as was mentioned earlier, came into prominence after 2002. In many aspects of life, both in Russia and internationally, blogosphere analysis has become an instrument of choice. As argued by Inna Kouper in Conversations in the Blogosphere: An Analysis «From the Bottom Up», an article on blog interconnections, the blogoshpere constitutes a small world capable of influencing the international community [17].

Many major international and Russian companies place a lot of emphasis on monitoring their network traffic. Foreign companies stress the importance of this kind of control [18] [19]. However, only a small number of companies engage in analysing the blogosphere to assess the appeal of their products.

Blogosphere analysis can also be used to assess SME performance. Some of the methods here are borrowed from the Chamber of Commerce and Industry’s Monitoring SME Performance in the Russian Federation by Analysing the Blogosphere report [7]. The parameters used in the analysis were as follows:

Figure 3 presents online platforms most widely used for discussing SME issues, with their respective share of total SME-themed discussions online, according to total discussions figures per platform.

Figure 3. Blogs and social networks most widely used to discuss SME issues


The no.1 platform for discussing SME issues is the microblogging website Twitter, used for posting individual comments and suggestions regarding SMEs. Using the Topsy [13] online tool for assessing the content of microblog entries across a period of 30 days, 1500 comments were found to mention SMEs, with around 50% expressing a positive attitude. The no.1 issue discussed was the contributions SMEs have to make to minicipal budgets. Most Twitter users think it is bound to hinder SME development. Users were supportive of reports of regional programmes aimed at encouraging the lending to SME.

The analysis of the tone of the comments made on blogging and social networking websites gave the following results: 28% of comments were negative, 32% were positive, with the remaining 45% neutral in tone, meaning, as is the case with Twitter, the number of positive and negavite comments was roughly equal. Below are the SME-themes search query figures for the Siberian Federal District. The search queries fit the causes of uneven regional SME development referenced in Figure 1. The figures were obtained using the Socialmention online tool [12]. Table 1 lists the top 10 queries.

Table 1. Search engine queries in the Siberian Federal District:

Subject No. of queries Popularity
 Sole proprietorship   23,50729  1
 Business support   16,64316   2
 Taxes   12,17677  3
 Small business   9,873061   4
 Start-up   9,732017  5
 Medium business   9,402915   6
 Quitting a business   5,171603   7
 OPORA   4,701457  8
 Credit   4,701457  9
 State registration   4,090268  10

The high number of queries indicates that users are not finding the information offered by official regional websites on SMEs adequate. In particular, analysing the related blogosphere search queries for the top 3 subjects (sole proprietorship, business support, and taxes) reveals that users are unable to find sufficient information on how to start a business, taxation, and business support programs.

Blogosphere analysis is incomplete without a study of trends. Below is a screenshot of Google Trends discussions dynamics for 2006-2014 for the Siberian Federal District.

Figure 4. Search engine queries trends


There is a noticeable rise in the number of people researching sole proprietorship. Taxes remain a popular subject although gradually less so.

The comparison of the goals tree chart (Figure 2) and the blogosphere analysis data shows that a system for monitoring SME development would facilitate access to up-to-date compresensive data on regional SME performance and a more complete implementation of the government’s SME development strategy.

Wrapping up the literary part of analysing the issues currently facing SMEs, it is clear that the goal undertaken by the present study is timely because of

A detailed description of the proposed monitoring method follows.

3. Methodology

The proposed method of monitoring SME performance across federal subjects of Russia involves the following stages:

3.1. Researching the link between SME performance and economic growth
Despite the importance of researching the link between SME performance and economic growth stressed by international studies (Joce C. Farinas, Lourdes Moreno) [2], the existing monitoring projects overlook the aspect. The study cited above offers three possible variants of the link:

This methodology has previously been tested to assess the two-way relationship between economy and entrepreneurship in 21 country, though Russia was not among them. Also, the exercise involved entire countries, not their regions. It is appropriate to apply this method to the study of a federal subject of the Russian Federation.

The statistical analysis was performed using the scientific, analytical, and statistical data on the state of SMEs, SME development predictions, information on government programmes for supporting regional SMEs, as well as studies into the link between SME performance and economic growth.

Figure 5 represent the study process in IDEF3 notation (using the ERWIN Process Modeller software). The functional structure implies creating a software implementation of the proposed monitoring method with reports on its practical results.

  1. Choosing economic indices to be monitored
  2. Checking the data’s availability per region
  3. Filtering the regions
  4. Choosing alternative indices
  5. Choosing a region for monitoring
  6. Checking for indices functional dependency
  7. Eliminating functionally dependent indices
  8. Regression analysis
  9. No correlation between SMEs and economy
  10. Direct correlation between SMEs and economy
  11. Reverse correlation between SMEs and economy
  12. Factor analysis
  13. Grouping the regions by how strong the economy influences SMEs
  14. Developing remedial actions
  15. Preparing a report summing up the findings

Figure 5. Proposed monitoring system’s functional structure


 To assess the correlation between economic and business performance two kinds of indices were used: the indices of economic performance and the indices of SME performance:

Table 2 presents correlation matrix of functionally independent indices relationship (compiled with the help of the SPSS statistical tool)

Table 2. Correlation matrix


The 60 federal subjects of Russia were broken down into clusters by the level of SME development (for complete results see Appendix 1). The regions selected were found to exhibit direct correlation between business development and SMEs.

3.2. Level of SME development in a region
The statistical measures used to assess the overall direction of SME development in a region were as follows:

Figure 6 presents a tree diagram of cluster distribution for regions of the Siberian Federal District (done using the Statistica software package).


Figure 6. Tree chart


Krasnoyarsk region, Novosibirsk region, Omsk region, Irkutsk region, Kemerovo region, Altai region, Republic of Tuva, Zabaykalsky region, Republic of Khakassia, Buryat Republic, Altai Republic.

The first group includes regions with the highest statistical indices, topped by the Novosibirsk and the Kemerovo regions.

The second group includes regions with the lowest number of SMEs and average workforce figures. This means SMEs in the Altai Republic, Zabaykalsky region, Buryat Republic, and Republics of Tuva and Khakassia are less well developed.

4. Results

  1. Blogosphere analysis can be used as a preliminary monitoring step for quick detection of regional SME development issues and assessing the effectiveness of proposed support programmes.
  2. The analysis of the blogosphere in the Siberian Federal District revealed the most widely discussed issues to be sole proprietorship, taxation, and support programmes. Supplying the users with detailed and up-to-date information on the subjects through regional SME support websites would facilitate private sector development both regionally and across Russia.
  3. There is a positive correlation between local economic development and SME development (above 0.6). Cluster analysis of 60 federal subjects made it possible to group them into three brackets according to local SME development. The one with a high degree of economic and SME performance included Moscow, the Sverdlovsk, and the Novosibirsk regions.

 5. References

  1. Edinaja mezhvedomstvennaja informacionno-statisticheskaja. -
  2. Firms’ Growth, Size and Age: A Nonparametric Approach [Zhurnal] / avt. Joce C. Farinas Lourdes Moreno. - [b.m.]: Kluwer Academic publishers, 2000.
  3. Types of monitoring [Zhurnal] / avt. center California Rengelands Research and Information. - 1995.
  4. Blogosfera i blogi. [V Internete]. -
  5. Gruppa Vsemirnogo banka: ocenka biznes regulirovanija [V Internete]. -
  6. Konkurentnaja Rossija. O proekte [V Internete]. - http://ko−
  7. Monitoring ocenki sostojanija malogo i srednego predprinimatel'stva: rezul'taty analiza blogosfery [Otchet] / avt. Federacii Torgovo-promyshlennaja palata Rossijskoj. - Moskva : [b.n.], 2013.
  8. Monitoring razvitija sistemy obrazovanija. Chast' 1. [Kniga] / avt. 8. Borovkova T. I. Morev I. A.. - Vladivostok: Izd−vo Dal'nevostochnogo universiteta, 2004.
  9. Maloe i srednee predprinimatel'stvo Rossii 2013. –
  10. Federal'naja sluzhba gosudarstvennoj statistiki. –
  11. Google Trendy –
  12. Socialmention – Rezhim dostupa:
  13. Topsy – Rezhim dostupa: - Zagl. s jekrana
  14. Predvaritel'nye itogi sploshnogo nabljudenija sub#ektov malogo i srednego predprinimatel'stva
  15. Predprinimatel'skij klimat v Rossii: Indeks Opory 2012 [Jelektronnyj resurs]. -
  16. Federal'nyj portal malogo i srednego predprinimatel'stva. 
  17. Conversations in the Blogosphere: An Analysis «From the Bottom Up» - Susan C. Herring, Inna Kouper, John C. Paolillo, Lois Ann Scheidt. School of Library and Information Science, Indiana University Bloomington, 2005.
  18. Why SMEs need to deploy a web-monitoring tool? GFI white paper. 2011.
  19. Production monitoring systems for SMES. Lee, H.L., Little, D. and Dancer, D. University of Huddersfield, School of Engineering, 2000 

6. Appendices

Appendix 1. Federal subjects of Russia by SME development

Cluster 1 – High SME development regions
Altai region Krasnoyarsk region
Republic of Bashkortostan  Perm region
Chelyabinsk region Nizhny  Novgorod region
Republic of Tatarstan  Novosibirsk region
Samara region  Moscow region
Rostov region  Sverdlovsk region
Krasnodar region  St. Petersburg
Tyumen region  Moscow


Cluster 2 – Medium SME development
Kaluga region  Kaliningrad region
Tver region  Vladimir region
Arkhangelsk region  Tula region
Penza region  Republic of Udmurtia
Ryazan region  Voronezh region
Smolensk region  Saratov region
Ulyanovsk region  Omsk region
Chuvash Republic  Irkutsk region
Leningrad region  Volgograd region
Tomsk region  Yaroslavl region
Khabarovsk region  Kemerovo region
Belgorod region  Primorsk region


Cluster 3 – Low SME development regions
Republic of Tuva  Kurgan region
Republic of Altai  Republic of Mordovia
Magadan region  Amur region
Kabardino-Balkar Republic  Republic of Mari El
Kamchatka region  Orel region
Republic of Dagestan  

скачать dle 10.2 јвто “юнинг кузова