Онлайн исследования в России 3.0

Дуэль М. Б. В кн.: Научно-техническая конференция студентов, аспирантов и молодых специалистов МИЭМ, посвященная 50-летию МИЭМ. М.: Московский государственный институт электроники и математики, 2012. С. 109-110.

Added: Apr 4, 2013

XLI Гагаринские чтения. Научные труды Международной молодежной научной конференции

Т. 4. Кн. 4: Социально-экономические аспекты развития аэрокосмических исследований. ИНФРА-М, 2015.

Added: May 15, 2015

Approaches to Defining and Measuring Russia’S Internet Economy

Abdrakhmanova G., Kovaleva G. G., Plaksin S. Science, Technology and Innovation. WP BRP. Высшая школа экономики, 2016. No. WP BRP 61/STI/2016 .

Our study object is the Russian Internet economy, i.e. economic activities of companies relying on the Russian-language segment of the World Wide Web. The purpose of this study is to classify businesses engaged in the national Internet economy and measure its size (as a share of GDP) using official statistics. The analysis of international approaches used for such studies allowed us to classify these according to the following criteria: the direct impact of the Internet on the economy, indirect economic impact of the Internet, and its indirect impact on the social sphere. To assess the size of the Russian Internet economy we used the approaches applied by international organizations (OECD, BCG, McKinsey) for the analysis of the direct impact of the Internet on the economy [BCG (2014), McKinsey (2011), OECD (2014), etc.]. The authors singled out three sectors within the Internet economy: the sector of ICT infrastructure and its maintenance; the sector of companies doing business purely on the Internet, and the sector of companies combining an online and offline business. To assess the share of the Internet economy in GDP using the production approach we first defined the above sectors in accordance with All-Russian Classification of Economic Activities (OKVED) Rev. 1.1 and subsequently calculated gross value added (GVA) for each sector. For this purpose, the GVA data calculated by Federal Service of State Statistics (Rosstat) was disaggregated while the share of the GVA contributed by the third sector companies (i.e. combining an online and offline business) was assessed using the results of special surveys and Rosstat data. To measure the size of the Internet economy using the expenditure approach we focused on consumer spending on goods bought through the Internet, ICT equipment and Internet access as well as institutions’ expenditure for ICT equipment, fixed capital investment of enterprises engaged in Internet activities, public sector ICT spending, net exports of ICT goods and services. According to our estimates obtained by two methods such as the production approach and expenditure approach, the share of the Internet economy in GDP in 2014 amounted to 2.7 and 2.6%, respectively. Future studies would require a more detailed definition and description of the Internet-related economic activities on the basis of OKVED2 with subsequent calculation of GVA for appropriate companies as well as development of statistical tools for collecting data on household spending

Added: Jun 3, 2016

Сентимент-анализ брендов в российской блогосфере как инструмент маркетинговых исследований

Андреева А. Н., Никитина М. С. Бренд-менеджмент. 2012. № 4(65). С. 226-243.

Added: Nov 20, 2012

Применение деревьев классификации к решению маркетинговых задач

Антипов Е. А. Маркетинг в России и за рубежом. 2009. № 4. С. 3-6.

Added: Oct 4, 2012

Место и роль Интернета в становлении информационного общества

Макатов З. В. В кн.: Информационное общество (философские проблемы). М.: Московский государственный институт электроники и математики, 2011. Гл. 4. С. 92-106.

Added: Apr 12, 2012

Современный менеджмент: проблемы, гипотезы, исследования : сборник научных трудов

Вып. 1. М.: Издательский дом ГУ-ВШЭ, 2009.

Added: Oct 27, 2012

Is Education a Signal on the Russian Labour Market?

Aistov A. Education. EDU. Высшая школа экономики, 2012. No. 5.

This research focuses on estimating the signalling role of education on the Russian labour market. Two well-known screening hypotheses are initially considered. According to first of these, education is an ideal filter of persons with low productivity: education does not increase the productivity of a person, but it does give him the possibility to signal about his innate productivity via an educational certicate. The second of these hypotheses admits that productivity actually does increase during the period of study, but nevertheless the main objective of getting an education is to acquire a signal about one's productivity. Information theory suggests that employees use education signals during the hiring processes whereby employers screen potential employees. Employers and other categories of self-employed workers are usually not screened by the labour market via their educational attainments. Comparison of the returns to education of employees vs. self-employed workers could show the difference between the returns to signals and the returns to human capital. Yet another way to understand the signals is to consider the time dynamics of the returns to education for employees staying in the same firm. This helps us to answer the question about whether the signals are valuable only during the hiring process, or whether they remain valuable during the whole experience with the firm. This research is based on the Mincerian-type earnings functions, estimated on RLMS-HSE and NOBUS data. On the basis of the available information, we cannot say that the returns to signals and human capital differ significantly in Russia. Nevertheless we can say that, for the majority of men, the return to educational signals decreases with time spent in the same firm, while we observe the opposite for women.

Added: May 15, 2012

Ритуалы в медиатизированном обществе

Черных А. И. Политическая теория и политический анализ. WP14. Высшая школа экономики, 2012. № 03.

Added: May 3, 2012

Общественные консультативные структуры при органах власти: опыт Санкт-Петербурга

Горный М. Б. Телескоп: журнал социологических и маркетинговых исследований. 2011. № 2. С. 14-24.

Added: Feb 7, 2013

Непосредственные вопросы

Вып. 1. М.: Некоммерческая исследовательская служба «Среда», 2011.

Added: Feb 7, 2013

Математическое моделирование социальных процессов

Edited by: А. Михайлов Вып. 14. М.: Социологический факультет МГУ, 2012.