A multi-criteria approach to selecting an optimal portfolio of refinery upgrade projects under margin and tax regime uncertainty
This work deals with investment decision in downstream, and as is wellknown no two refineries are exactly alike, even if they are owned by the same company(Cheremisinoff 2001). Each was designed with a combination of several technologies to meet requirements (market opportunities, availabilities, financial capability, environmental realities) (Energy 2009). One of the most commonly used methods for the comparison of refineries is the comparison by the single technical and economic indicator, the so-called “Nelson Index” (Johnston 1996) (hereinafter referred to as the NCI), which shows the complexity of the equipment installed in relation to the primary distillation process. The NCI index indicates not only the intensity of the investment or index value of the plant but also its potential for added value. Thus, the higher the NCI index, the higher the cost of the oil refinery, and the higher the quality and level of its products.
Supply chain management is rather new scientific field that reflects the concept of integrated business planning. This concept should be experts and practitioners in logistics and strategic management. Today, integrated planning to become a reality thanks to the development of information technology and computer technology. At the same time to achieve a competitive advantage is not enough high-speed, low-cost data transfer process. In order to effectively apply information technology tools necessary to develop a quantitative analysis of the effectiveness of supply chain management. The mam element of this tool are optimization models that reveal the complex interactions, the wave and the synergies that arise in supply chain management. In this article we consider one of the classes of such models - the so-called dynamic models of conveyor systems, processing of applications.
Uncertainty is a concept associated with data acquisition and analysis, usually appearing in the form of noise or measure error, often due to some technological constraint. In supervised learning, uncertainty affects classification accuracy and yields low quality solutions. For this reason, it is essential to develop machine learning algorithms able to handle efficiently data with imprecision. In this paper we study this problem from a robust optimization perspective. We consider a supervised learning algorithm based on generalized eigenvalues and we provide a robust counterpart formulation and solution in case of ellipsoidal uncertainty sets. We demonstrate the performance of the proposed robust scheme on artificial and benchmark datasets from University of California Irvine (UCI) machine learning repository and we compare results against a robust implementation of Support Vector Machines.
The paper focuses on the concept of ‘financial strategies’ and addresses two problems: first, how to define the concepts of financial strategy and strategizing, and second, how to operationalize them into indicators for empirical research. The introduction to this new concept is based on the conviction that strategizing (which is understood as a specific attitude to life held by people who do not live for the moment, think about their future even if it is rather uncertain, set long-term financial goals and act towards achieving them), is an intrinsic factor in the financial behavior of people. It is argued that it is not possible to define financial strategy or to operationalize it objectively and universally since people operate in very different circumstances; i.e. in different institutional environments or at different stages of life, etc. The solution must be found in the interactionist sociological perspective with the emphasis on the construction of the interpretation of a situation: how individuals themselves make sense of financial strategizing in their own environment, the options they perceive and the constraints they feel.
In this article we describe a system allowing companies to organize an efficient inventory management with 40 suppliers of different products. The system consists of four modules, each of which can be improved: demand planning, inventory management, procurement planning and KPI reporting. Described system was implemented in a real company, specializing on perishable products totaling over 600 SKUs. The system helped the company to increase its turnover by 7% while keeping the same level of services.
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.