По дороге разочарований
Today the increasing number of constant consumers is a strategic aim for any organization which is possible to be achieved only under condition of continuous perfection of organizational activity quality. If the service representation doesn't correspond to the consumers’ expectations they lose their interest to the service organization, if it does correspond or surpass their expectations they probably would readdress to service provider. For this reason the service organization should more precisely reveal consumers requirements and expectations, namely provider should constantly measure its service quality.
In the given work approaches by the Russian and foreign researchers in the field of quality management are studied and analyzed in details, namely:
- approaches to the «service quality» definition;
- the basic components of service quality management process;
- service organization quality model.
The purpose of research work consists of ISQM (Innovation System of Quality Management) model creation taking into account features of TCS providing, which, in turn, is targeted on TCS company purposes achievement in the field of quality by means of:
- setting the control values of TCS quality indicators;
- measuring of the reached results and their comparison with expected results;
- effective management decision making as a result of carrying out the analysis of managerial activity in the field of quality on the basis of the report containing recommendations for the company activity improvement, prepared due to the results of measuring and collecting quality indicators.
The data book presents the results of statistical innovation surveys in the Russian Federation. It contains internationally compatible indicators characterizing the level of innovative activity in industry and services. The publication covers statistical data reflecting innovation expenditure and output, co-operational linkages, and factors hampering innovation. Specific chapter is devoted to ecological innovation. International comparisons with a wide range of innovation indicators are provided as well. The data book includes information of the Federal Service for State Statistics, Organisation for Economic Co-operation and Development, European Commission, Eurostat, national statistical agencies, and results of own methodological and analytical studies of the HSE Institute for Statistical Studies and Economics of Knowledge.
Since 2008, the world economy has been facing consequences of the global financial crisis. One of them is rapid growth in public debt in most advanced economies, which resulted from an overoptimistic estimate of fiscal situation before the crisis, declining government revenue and increasing social expenditure during the crisis, costs of the banking system restructuring, countercyclical fiscal policies, etc.
For this reason, many governments are trying to determine a ‘safe’ level of fiscal deficit and public debt. However, this is not an easy task. There is no single standard of fiscal safety for all economies. Besides, a globalized economy and irregular business cycle make it difficult to find out in which phase of the cycle a given economy is at the moment, while this is essential to assess fiscal indicators.
Historical experience shows that default risk may materialize at different levels of public debt, sometimes seemingly very low. In fact, a ‘safe’ borrowing level is country-specific and depends on many factors and often unpredictable circumstances. However, given the tense situation in global markets, the ‘safe’ level of public debt is lower than it used to be a decade ago. Another argument for a cautious approach concerns a highly pro-cyclical nature of such measures as the fiscal deficit to GDP or public debt to GDP ratios.
Lessons of the latest crises also indicate importance of more accurate estimation of countries’ contingent fiscal liabilities, particularly of those relating to the stability in the financial sector. If looking into the future, a correct estimation of other contingent liabilities, particularly those related to social welfare systems (implicit debt of the public pension and health systems) are of primary importance in the context of the ageing society and population decline. These liabilities far exceed official statistics on the public debt in some counties. As a result, such statistics does not present an adequate picture of the nation's public debt and actual fiscal burden that will be imposed on the shoulders of the following generations of taxpayers.
This paper studies fiscal policy in Russia 2004–2010 with the aid of structural budget balance and fiscal impulse measures. To check for robustness several methods estimating the potential GDP are employed. The research suggests a hypothesis that the output in Russia is subject to two types of shocks: persistent outward shocks and short-term internal shocks. In 2004–2010, fiscal policy coped with the internal shocks but could not smooth outward instability. Fiscal policy in Russia is procyclical; it does not stabilize the output.
Partisan governments play an impor tant role in the elaborat ion of macroeconomic policies of the Organization for Economic Co-operation and Development (OECD) countries: they manage ﬁscal policy and coordinate with a Central Bank that conducts monetary policy. Ideology is a crucial parameter of the ruling coalition. This study focuses on the inﬂuence of the ideology of the ruling coalition on macroeconomic policies of the OECD countries. Using statistical methods, the analysis examines the relationship between the “rightism” of the ruling coalition and such characteristics of budgetary policy as budget balancing, state expenditures and tax collection. The ﬁndings show that the inﬂuence of ideology is determined by a set of social and economic factors, so the nature of the inﬂuence that ideology wields may work in diﬀerent directions depending on the conditions.
The paper examines the structure, governance, and balance sheets of state-controlled banks in Russia, which accounted for over 55 percent of the total assets in the country's banking system in early 2012. The author offers a credible estimate of the size of the country's state banking sector by including banks that are indirectly owned by public organizations. Contrary to some predictions based on the theoretical literature on economic transition, he explains the relatively high profitability and efficiency of Russian state-controlled banks by pointing to their competitive position in such functions as acquisition and disposal of assets on behalf of the government. Also suggested in the paper is a different way of looking at market concentration in Russia (by consolidating the market shares of core state-controlled banks), which produces a picture of a more concentrated market than officially reported. Lastly, one of the author's interesting conclusions is that China provides a better benchmark than the formerly centrally planned economies of Central and Eastern Europe by which to assess the viability of state ownership of banks in Russia and to evaluate the country's banking sector.
The paper examines the principles for the supervision of financial conglomerates proposed by BCBS in the consultative document published in December 2011. Moreover, the article proposes a number of suggestions worked out by the authors within the HSE research team.
We address the external effects on public sector efficiency measures acquired using Data Envelopment Analysis. We use the health care system in Russian regions in 2011 to evaluate modern approaches to accounting for external effects. We propose a promising method of correcting DEA efficiency measures. Despite the multiple advantages DEA offers, the usage of this approach carries with it a number of methodological difficulties. Accounting for multiple factors of efficiency calls for more complex methods, among which the most promising are DMU clustering and calculating local production possibility frontiers. Using regression models for estimate correction requires further study due to possible systematic errors during estimation. A mixture of data correction and DMU clustering together with multi-stage DEA seems most promising at the moment. Analyzing several stages of transforming society’s resources into social welfare will allow for picking out the weak points in a state agency’s work.