Разработка и оценка концепции нового для компании туристического продукта
турпродукт, туристическое направление, прогнозирование спроса, анализ портфеля, анализ ассортимента, MDA-анализ, матрица БКГ, матрица McKinsey, Греция, Доминиканская Республика
The methodology of forecasting demand for the generic drugs manufacturer is proposed, a forecast hierarchy is developed. The forecasting business process model is proposed. An algorithm for forecasting process management is developed.
The forecast of passenger demand in Revenue Management is usually based on historical booking data that reflects the number of sales rather than true demand which is constrained by booking limits. That is why the process of demand forecasting under such circumstances is called unconstraining. The goal of every unconstraining approach is to get empirical or theoretical estimation of true demand. The application of the maximum likelihood method to unconstraining problems in Revenue Management is advocated in the paper based on the construction of the distribution function for the censored demand depending on availability of the censoring information. Numerical results are presented of comparative analysis of existing unconstraining methods and the method used in the paper. It is demonstrated that maximum likelihood method proves to be more efficient in case of high percentage of censoring. Another important advantage of the method connected to the fact that it enables one to process the situation of censoring information incompleteness when some elements of the observed sample data are known to be censored or not and for the others this information is not available. Mathematical computer environment Wolfram Mathematica has been used for obtaining all the numerical results presented in the paper.
The authors propose a new statistical unconstraining method which is based on the construction of the distribution function for the censored demand and application of the maximum likelihood approach to estimate distribution parameters. Numerical results are presented of comparative analysis of existing unconstraining methods and the method advocated in the paper. It is demonstrated that the new method has proven to be more efficient in the case of a high percentage of observed censored elements of sample data. Yet another important advantage of the method connected to the fact that it enables one to process the situation of censoring information incompleteness when some elements of the observed sample data are known to be censored or not and for the others this information is not available. Mathematical computer environment Wolfram Mathematica has been used for obtaining all the results presented in the paper.
The paper analyses the demand planning process from supply chain management perspective. The place of the analyzed process in SCOR and GSCF models is investigated. Main steps of the process are clarified: analysis and preparation of historical data; statistical forecasting; manual expert correction of the forecast; forecast verification and confirmation; quality monitoring of forecast and process. Approaches to process data organization are investigated; terminology in this area is presented. The key forecasting methods are analyzed including: qualitative/subjective, cause and effect, time series. Key forecasting models for demand planning in supply chains are systemized. The importance of the quality monitoring of forecasts is highlighted. Main methods of determination of exceptional situations are presented. Key requirements for informational systems of demand planning are formalized. Overview of popular software tools for demand planning is presented.
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.