Article
Разработка модели прогнозирования численности клиентской базы компании
This article concerns the problem of predicting the size of company's customer base in case of solving the task of managing its clients. The author purposes a new approach to segment-oriented predicting the size of clients based on adopting the Staroverov's employees moving model. Besides the article includes the limitations of using this model and its modification for each type of relations of the client and the company.
In work the developed model of adaptive management by the vertically integrated companies based on the system approach supporting the mechanism of an operational management in a uniform cycle of strategic planning, within the limits of faster time is presented. Thus for a finding of optimum values of operating parameters special algorithms of a class of genetic algorithms are used, neural networks the example of the developed system of adaptive management for the vertically-integrated oil company is etc. presented.
We use a Markov chains models for the analysis of Russian stock market. First problem studied in the paper is the multiperiod portfolio optimization. We show that known approaches applied for the Russian stock market produce the phenomena of non stability and propose a new methods in order to smooth it. The second problem addressed in the paper is a structural changes on the Russian stock market after the financial crisis of 2008.We propose a hidden Markov chains model to analyse a structural changes and apply it for the Russian stock market.
Companies are increasingly paying close attention to the IP portfolio, which is a key competitive advantage, so patents and patent applications, as well as analysis and identification of future trends, become one of the important and strategic components of a business strategy. We argue that the problems of identifying and predicting trends or entities, as well as the search for technical features, can be solved with the help of easily accessible Big Data technologies, machine learning and predictive analytics, thereby offering an effective plan for development and progress. The purpose of this study is twofold, the first is an identification of technological trends, the second is an identification of application areas and/or that are most promising in terms of technology development and investment. The research was based on methods of clustering, processing of large text files and search queries in patent databases. The suggested approach is considered on the basis of experimental data in the field of moving connected UAVs and passive acoustic ecology control.
портовый менеджмент, показатели деятельности, анализ эффективности, система учета, распределение издержек, методы анализа деятельности портовой системы
At present many industries reveal tendency for setting up of vertically integrated companies (VIC) the structure of which unites all technological processes. This tendency proved its efficiency in oil industry where coordination of all successive stages of technological process, namely, oil prospecting and production -oil transportation - oil processing - oil chemistry - oil products and oil chemicals marketing, is necessary. The article considers specific features of introduction of "personnel management" module at enterprises of oil and gas industry.
vertically integrated companies; personnel management