ПЕРВАЯ МЕЖДУНАРОДНАЯ КОНФЕРЕНЦИЯ «УПРАВЛЕНИЕ БИЗНЕСОМ В ЦИФРОВОЙ ЭКОНОМИКЕ» СБОРНИК ТЕЗИСОВ ВЫСТУПЛЕНИЙ
СПб.: Санкт-Петербургский государственный университет, 2018.
Полынская Г. А.
Academic editor: И. А. Аренков, Ю. В. Крылова, Т. А. Лезина, М. К. Ценжарик, Д. В. Ябурова
Editor-in-chief: М. К. Ценжарик
Титова Е. В. Вопросы экономики и права. 2010. № 11. С. 24-29.
Added: Apr 13, 2012
Сысоева А. С., Сысоев И. В. В кн.: Прогнозирование инновационного развития национальной экономики в рамках рационального природопользования. Т. 2. Пермь: Пермский государственный национальный исследовательский университет, 2012. С. 136-141.
Added: Jan 17, 2013
Проблемы и перспективы развития инновационно-креативной экономики: Материалы Международной научной конференции
М.: Креативная экономика, 2011.
Added: Feb 2, 2013
Развитие человеческого капитала в контексте модернизации российской экономики: анализируя прошлое, оценивая настоящее, планируя будущее
Мешкова Т. А. Вестник международных организаций: образование, наука, новая экономика. 2010. № 1. С. 4-10.
Added: Sep 28, 2012
Княгинин В. Н., Щедровицкий П. Г. Новая экономика - Новое общество - Новое государство. WP5. Высшая школа экономики, 2003. № 02.
Added: Mar 24, 2013
Управление человеческими ресурсами - основа развития инновационной экономики: Материалы III Международной научно-практической конференции
Edited by: О. Подвербных Ч. 1. Красноярск: Изд-во СибГАУ, 2011.
Added: Jan 31, 2013
Волков А. Е., Кузьминов Я. И., Реморенко И. М. и др. В кн.: Российское образование: тенденции и вызовы. М.: Дело, 2009. С. 19-46.
Added: Jan 16, 2013
Гохберг Л. М. Новая экономика - Новое общество - Новое государство. WP5. Высшая школа экономики, 2002. № 02.
Added: Mar 24, 2013
Abdrakhmanova G. I., 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
Северо-запад в системе макрорегионов России: проблемы формирования инновационной экономики и многоуровневой системы управления качеством
Edited by: В. В. Окрепилов СПб.: ГУАП, 2012.
Added: Mar 6, 2013
Титова Е. В. Качество. Инновации. Образование. 2011. № 7. С. 33-37.
Added: Apr 13, 2012
Антипов Е. А., Покрышевская Е. Б. В кн.: Инновационная экономика: реалии и перспективы: научная конференция, Санкт-Петербург, 27 сентября 2011 года. СПб.: Отдел оперативной полиграфии НИУ ВШЭ – Санкт-Петербург, 2012. С. 167-170.
Added: Mar 21, 2013
Экономика и управление: проблемы и перспективы развития. Сборник научных статей по итогам международной научно-практической конференции г.Волгоград 15-16 ноября 2010 г.
Ч. 1. Волгоград: Волгоградское научное издательство, 2010.
Added: Jan 18, 2013
Anisimova A. I., Muradyan P. A., Vernikov A. V. SSRN Working Paper Series. Social Science Research Network, 2011. No. 1919817.
This empirical paper adds to competition and industrial organization literature by exploring the interplay between industry structure and competitiveness on local, rather than nation-wide, markets. We use micro-level statistical data for banks in two Russian regions (Bashkortostan and Tatarstan) to estimate Herfindahl-Hirschman index, Lerner index, and Panzar-Rosse model. We estimate Panzar-Rosse model in two ways: via the widely used price-equation that accounts for scale effects and then via a revenue-equation that disregards scale effects as suggested by Bikker et al. (2009). We find both regional markets to be ruled by monopolistic competition, although estimation by revenue-equation does not reject monopoly hypothesis for Tatarstan. Existence of sizeable locally-owned and operated institutions does not necessarily lead to higher competitiveness of the given regional market, and the results from non-structural methods of estimation suggest that bank competition in Bashkortostan is stronger than in Tatarstan. Going further away from aggregated analysis we compute Lerner indices in two product segments of Tatarstan – retail and corporate loans – and find that retail segment is significantly more competitive. Local banks exert more market power in corporate loans, while federal branches – in retail loans.
Added: May 14, 2012
Added: Feb 22, 2013
Трунин П. В., Дробышевский С. М., Евдокимова Т. В. М.: Издательский дом «Дело» РАНХиГС, 2012.
Added: Mar 26, 2013
Яковлев А. А. Общественные науки и современность. 2008. № 4. С. 21-37.
Added: Sep 22, 2012
Penikas H. I. Financial Economics. FE. Высшая школа экономики, 2012. No. 03.
The Basel Committee of Banking Supervision initiated a discussion on the most efficient practices to prevent bank managers from excessive risk-taking. This paper proposes a game-theoretical approach, describing the decision-making process by a bank manager who chooses his own level of risk and effort. If the level of risk implies the variability of the future outcome, the amount of effort applied affects the probability of a positive outcome. Although effort is unobserved for the bank’s stakeholders, the risk level is under control, and is associated with certain indicators such as capital adequacy ratio or leverage level. The risk-neutral utility function of a bank manager and a binary game outcome of gaining profit or loss for a bank are assumed. Starting from the general incentive contract scheme having the fixed and variable parts of remuneration, it is proposed that differentiating the variable part of remuneration is sufficient to motivate bank managers to make fewer risky decisions. More precisely, the variable part of remuneration (e.g. the share of the bank’s profit) needs to be higher in proportion to the higher variance of outcome for the high -risk outcome case to stimulate a bank manager to opt for lower-risk decisions in place of higher-risk situations.
Added: May 3, 2012
Уринсон Я. М. Вестник Европы. 2014. № 38-39.
Added: Feb 5, 2018
Penikas H. I., Titova Y. Financial Economics. FE. Высшая школа экономики, 2012. No. 02.
In this paper we elaborate a simple model that allows for the predicting of possible reactions from financial institutions to more stringent regulatory measures introduced by the Basel Committee on Banking Supervision (BCBS) in regard to global systemically important banks (G-SIBs). The context is framed by a 2011 BCBS document that proposes higher capital requirements for global systemically important banks. We attempt to analyze bank interactions in an oligopolistic market that is subject to demand constraints on loan amounts and additional loss absorbency requirements introduced by the regulator. We distinguish between the bank’s announced funding cost that determines both the loan amount issued and the market interest rate, and the bank’s true funding cost that has a direct impact on retained earnings. We conclude that in a two-stage game both banks will announce the highest funding cost, thus reducing the amount of loans granted (in line with the regulator’s objective), but at the expense of a higher cost of borrowing established in the market. If the game is repeated, then both banks also choose lower loan amounts in the periods prior to the last one in which the declared funding cost is the lowest possible. It should be noted that the designated outcome also coincides with the findings of the Monetary Economic Department of the Basel Committee on Banking Supervision.
Added: May 3, 2012
Added: Jun 24, 2011