Book chapter
Сравнительная статика дисперсии цен на российских интернет-рынках
С. 167-170.
In book
Edited by: А. В. Бутуханов СПб.: Отдел оперативной полиграфии НИУ ВШЭ – Санкт-Петербург, 2012.
Similar publications
Added: Oct 4, 2012
Покрышевская Е. Б., Антипов Е. А. В кн.: Моделирование в задачах городской и региональной экономики: Материалы Всероссийской конференции, посвященной 75-летию со дня рождения первого директора СПб ЭМИ РАН, заместителя председателя Президиума СПб НЦ РАН, профессора Бориса Львовича Овсиевича 24-25 октября 2011 года. СПб.: Издательство Нестор-История, 2011. С. 168-171.
Added: Oct 4, 2012
Полынская Г. А. СПб.: Санкт-Петербургский государственный университет, 2018.
Added: Oct 19, 2018
Гребенников С., Казакулова Г. Р., Левова И. и др. М.: 2014.
Added: Dec 22, 2014
Added: Nov 3, 2014
Боговиз А. В., Бобровников Д. А. Экономика устойчивого развития. 2014. № 3 (19) . С. 18-23.
The paper reviews the question of developing compelling customer experience during internet navigation. The author shows features of compelling customer experience that distinguish it from ordinary one. Both factors developing compelling customer and consequences of that kind of experience are highlighted under the review of most cited foreign sources.
Added: Jan 12, 2015
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
Evgeny A. Antipov. Management. MAN. Высшая школа экономики, 2014. No. 19.
Some Internet stores manage to charge prices that are significantly higher than market averages, therefore, obtaining some sort of price premium. This paper is dedicated to building a model that can be used to explain and predict a typical price premium that an Internet store charges for a specific product based on the information about the characteristics of the store and the features of the market for this product. Such models can provide support for pricing and assortment decisions: in particular, they allow detecting products that a store is likely to sell with the highest or the lowest markup based on price premia that are charged by stores with similar characteristics on similar markets.
Added: May 14, 2014
Bazenkov N., Glamozdina E., Kuznetsova M. et al. Economics. EC. Высшая школа экономики, 2019. No. 219.
This paper considers three hypotheses about the strategic origin of price dispersion in homogeneous product online sales. The first two are the $\varepsilon$-equilibrium and the quantal-response equilibrium (QRE) in a pure Bertrand setting involving the boundedly rational behavior of sellers. The third introduces the share of loyal consumers into the model of competition. These hypotheses were supported by estimations on experimental lab data. We test the hypotheses on a set of real prices for 30 models of household appliances collected from the largest Russian online marketplace Market.Yandex.ru. In contrast to the previously reported experimental data, we found very limited support for any of these explanations. QRE showed the best performance on the data. For most of the products it accurately predicts central tendency, i.e. the mean and the median. However, the shape of the observed price distributions is not explained well by any of the models. These results pose new challenges for theoretical explanations of observed Internet prices.
Added: Jul 24, 2019