2015. No. 1 (31)

Victor P. Romanov - Professor, Department of Information Systems in Economics and Management, Faculty of Mathematical Economics and Informatics. Plekhanov Russian University of Economics.
Address: 36, Stremyanny lane, Moscow, 117997, Russian Federation.
E-mail: victorromanov1@gmail.com

Bulat A. Akhmadeev - Post-graduate student, Department of Information Systems in Economics and Management, Faculty of Mathematical Economics and Informatics. Plekhanov Russian University of Economics.
Address: 36, Stremyanny lane, Moscow, 117997, Russian Federation.
E-mail: bulat.a@mail.ru

      This paper provides insights into a concept and essence of corporate merger & acquisition processes, as well as an analytical review of these processes in research and professional literature. Drivers and purposes of parties to these transactions, as well as their types have been identified. The most significant corporate mergers and acquisitions in the IT sector over the last decade have been considered. A synergetic effect in their operations resulting from these processes has been shown; such effect appears when an acquisition is aimed to get access to new technologies or head-hunting. Corporate merger & acquisition implications have been demonstrated from the perspective of natural ecosystem development, analogies with biological relationships – “predator-prey” mergers have been drawn. Objects in economic and biological systems are found out to behave alike. It has been demonstrated that a biological ecosystem may be innovative to a certain extent, when it is being formed by means of establishing effective financial, informational and other kinds of feedback links between economic entities. The concept of innovative ecosystem has been analyzed, and its major growth drivers have been investigated. Author’s own model of innovative ecosystem dynamic development based on the Lotka–Volterra model (the “predator-prey” model) has been suggested, where predators refer to corporations and preys – to small-scale innovative enterprises (SIE). This model has been implemented in author’s software program, and under certain system parameters it shows monotonic exponential growth of populations. Conclusions have been made that innovative ecosystem growth can be achieved thanks to proper regulation of corporate taxation parameters and SIE subsidies, as well as regulation of intraspecific competition and corporation/SIE acquisition ratio.

Alexander I. Gromoff - Professor, Department of Business Processes Modeling and Optimization, Faculty of Business Informatics, National Research University Higher School of Economics. 
Address: 20, Myasnitskaya str., Moscow, 101000, Russian Federation.
E-mail: agromov@hse.ru

Julia A. Bilinkis - Lecturer, Department of Business Processes Modeling and Optimization, Faculty of Business Informatics, National Research University Higher School of Economics. 
Address: 20, Myasnitskaya str., Moscow, 101000, Russian Federation.
E-mail: ystavenko@hse.ru

Albert Fleischmann - Owner, Interaktiv Unternehmensberatung
Address: 16, Burgfriedenstraße, Pfaffenhofen, 85276, Germany
E-mail: albert.fleischmann@interaktiv.expert

Tatiana V. Novikova - Lecturer, Department of Business Processes Modeling and Optimization, Faculty of Business Informatics, National Research University Higher School of Economics. 
Address: 20, Myasnitskaya str., Moscow, 101000, Russian Federation.
E-mail: tvnovikova@hse.ru

Eugene I. Khudobin - Director, Center of Efficient Organizations   
Address: 19, build, 6, Leninskaya Sloboda Street, Moscow, 115280, Russian Federation.
E-mail: eugenex@yandex.ru     

Dmitry V. Torshin - Investment Director, IT Group  
Address: 19, build, 6, Leninskaya Sloboda Street, Moscow, 115280, Russian Federation.
E-mail: dtorshin@it.ru 

      This paper examines the possibility of structuring innovation activities that entails formation of innovation process and management techniques in evolving external and internal environment. It reviews studies focusing on innovation generation in knowledge management processes and innovation process models based on knowledge and learning. Actually organizations have been facing challenges instigated by obsolete collective activity concepts caused by geopolitical and economic issues that impel them to identify ways to involve not only their own employees in expert communities, but also customers, partners and other persons capable to participate in collective creative activities. In this context a new approach has been suggested to determine the innovation process as an ad-hoc process to be implemented in the subject-oriented business process management methodology (S-BPM). The new approach implies identification of innovation process peculiarities that will determine a modeling methodology and requirements for innovation process automation with due regard to a simulation modeling method and Russian business environment specifics.  
      The study relies on a survey of Russian companies over the recent 20 years, where process drawbacks had been detected, that were basically typical for all companies.  The review findings have enabled to identify innovation process peculiarities specific to Russian companies.
      As a result an alternative approach to business process analysis and management has been elaborated: it involves analysis of real content (i.e. substantive content in real time) of a process environment rather than analysis of discrete characteristics.

Vladimir A. Gurvich - Professor of Applied Mathematics and Computer Science, Rutgers Center for Operations Research, Business School, Rutgers, the State University of New Jersey, USA.
Address: 100, Rockafeller Road, Piscataway, NJ, 08854, USA.  
E-mail: gurvich@rutcor.rutgers.edu, vladimir.gurvich@gmail.com

      In this paper we give an example of a finite positional game with perfect information and without moves of chance (a chess-like game) that has no Nash equilibria in pure stationary strategies. In this example the number n of players is 4, the number p of terminals is 5; furthermore, there is only one directed cycle. On the other hand, it is known that a chess-like game has a Nash equilibrium (NE) in pure stationary strategies if (A) n £ 2, or (B) p £ 3 and (C) any infinite play is worse than each terminal for every player. It remains open whether a NE-free chess-like game exists for n = 3, or when 2 £ p £ 4, or can such a game satisfy (C) for some n and p. 

Olga I. Babina - Senior Lecturer, Department of Economics and Management of Business Processes, Institute of Business Processes Management and Economics, Siberian Federal University   
Address: 26a, Kirenskogo street, Krasnoyarsk, 660074, Russian Federation.  
E-mail: babina62@yahoo.com

      Simulation is an effective tool, which may be applied for warehouse systems planning and management. Using of simulation is related with development of a computer program and carrying out a series of experiments, allowing to define optimal scenarios of warehousing processes. During the past ten years the concept of simulation optimization was developed. Using the concept optimization software is integrated into simulation systems, allowing users to find optimal solutions automatically. A simulation optimization model can be defined as a process of discovering the best set of initial variables of the model for assessment of each of possible solutions, without participation of users. The main objective of simulation optimization modeling of a warehousing system is gaining of information about the system that is critical for efficient decision making regarding minimization of resources used in the warehouse.
      The article describes a practical case study of building simulation and optimization models for a warehouse of an industrial concrete enterprise. Warehouse system processes are modeled in ExtendSim environment, and enterprise profit is optimized with the use of evolutionary algorithm. The optimization model has been executed by means of Optimizer software integrated into ExtendSim. The modeling purpose is to examine the impact of stock management strategies parameters on warehouse performance and to maximize enterprise profit from product sales. The paper presents the description of the model building process and simulation outputs. The simulation optimization model in warehouse activity planning enables to increase the accuracy of accounting of materials and warehouse operations, to reduce the level of warehouse stocks, to reduce costs of material storage, to increase labor productivity in a warehouse and to analyze quantitative indicators of warehouse performance.

Evgeny N. Efimov - Professor, Department of Information Technologies and Information Protection, Faculty of Computer Technologies and Information Security,  Rostov State Economic University (RINE).
Address: 69, Bolshaya Sadovaya Street, Rostov-on-Don, 344002, Russian Federation.
E-mail: efimov46@mail.ru

Galina M. Lapitskaya - Professor, Department of Information Technologies and Information Protection, Faculty of Computer Technologies and Information Security, Rostov State Economic University (RINE).
Address: 69, Bolshaya Sadovaya Street, Rostov-on-Don, 344002, Russian Federation.
E-mail: gmlapickaya@mail.ru

      Uncertainty of information security system properties is inherent at all stages of its life cycle due to real exposure to random factors of external and internal environment. As a project is implemented, the system uncertainty tends to reduce, but its operation efficiency can never be adequately expressed and described by deterministic parameters. In this case probabilistic methods are most applicable to evaluate efficiency of implementation and operation of information security systems. In accordance with these methods, levels of system safeguards are transformed into confidence levels of corresponding estimates. Under these conditions, data to evaluate effectiveness of information security enhancement measures can be obtained by using simulation modeling.
      A suggested methodology for information security impact assessment at a company implies modeling of estimates of losses avoided. The value of losses avoided can be calculated on the basis of the likelihood of an information security incident and resulting possible economic losses before and after implementation of information security measures at an object.
      Total losses avoided resulting from the simulation covering all information security incidents enable to specify and to carry out scenario-based calculations of potential effects of such measures. The final evaluation of information security enhancement measures can be performed by any known method. Globally a standard method of cost-benefit analysis (CBA) is widely used to evaluate effectiveness of IT projects. Implementation of the suggested information security enhancements evaluation methodology has been based on the CBA method.
      The main advantage of the proposed information security enhancements evaluation methodology is its ability to pay due regard to the real world uncertainty thanks to simulation modeling. This enables to some extent to increase the validity of evaluation estimates.

Liliya A. Demidova -Professor, Department of Computational and Applied Mathematics, Faculty of Computer Engineering, Ryazan State Radio Engineering University.
Address: 59/1, Gagarina street, Ryazan, 390005, Russian Federation.
E-mail: liliya.demidova@rambler.ru

      Models of short-term forecasting of short-time series on the base of strictly binary trees and modified clonal selection algorithm are considered. These enable to increase forecast accuracy by selecting analytical dependences to be formed on the antibodies base, coding strictly binary trees and adequately describing known values of time series,.
      The antibody constitutes a symbolical line, which elements are selected from three preset symbolical alphabets: alphabet of arithmetic operations; alphabet of functionalities and alphabet of terminals. When implementing the modified clonal selection algorithm the use of three symbolical alphabets ensures correct transformation to analytical dependences of antibodies formed in a random way, which structure can be described by means of strictly binary trees.
      When antibodies are coded on the base of strictly binary trees all knots of strictly binary tree are consecutively recorded in a symbolical line, beginning from left to right and from bottom to top. When analytical dependences are formed on the base of antibodies the recursive procedure of antibodies interpretation is applied.
      The modified clonal selection algorithm belongs to a group of evolutionary algorithms, which enable to carry out simultaneous search among several decision alternatives to make the best choice. The main distinctive feature of the modified clonal selection algorithm is use of mechanisms of clonal selection, hypermutation and suppression during alternation of generations of antibodies populations, used to form required analytical dependences.
      A new approach to quality estimation of forecasting models on the base of strictly binary trees and modified clonal selection algorithm has been offered and investigated. The paper has shown the expediency of simultaneous accounting of mean relative forecast error rate and tendencies discrepancy indicator in antibodies affinity calculations for the purpose of forecasting models quality estimation to be defined by involving analytical dependences, formed on the base of strictly binary trees. When applying the modified clonal selection algorithm the considered approach to forecasting models quality estimation enables to exclude from further consideration forecasting models, which are characterized by great values of tendencies discrepancy indicator.
      The offered forecasting models enable to reduce significantly time needed to retrieve an analytical dependence, which gives the best description of shorttime series known values, and can be recommended to address short-term forecasting tasks (for 1-3 steps forward).

Armen L. Beklaryan - Lecturer, Department of Business Analytics, Faculty of Business Informatics, National Research University Higher School of Economics
Address: 20, Myasnitskaya street, Moscow, 101000, Russian Federation.
E-mail: abeklaryan@hse.ru

Andranik S. Akopov - Professor, Department of Business Analytics, Faculty of Business Informatics, National Research University Higher School of Economics
Address: 20, Myasnitskaya street, Moscow, 101000, Russian Federation.
E-mail: aakopov@hse.ru

      This paper elaborates a phenomenological approach to simulation of human crowd behavior. We consider a continuous stochastic agent-based model of human behavior in a confined space with a given geometry by using refinements of both an agent status and agent’s decision-making system, presented in Helbing’s models (molecular approach).
      Such integration seems to be the most promising development of this class of tasks due to the fact that the phenomenological approach (Beklaryan-Akopov’s model) enables to introduce natural discretization of a task and then to calculate the increment of all agent’s characteristics at any specific time, and the use of elements of the molecular approach (Helbing’s model) enables to describe the most realistic decision-making system of an agent. This removes a complicated issue of numerical integration of Newton’s equations underlying Helbing’s model and offers explicit calculations of all system characteristics.
      As a result, an agent based model has been devised in AnyLogic simulation modeling system, enabling to investigate agent movement dynamics with due regard to “the crowd effect” in various scenarios, in particular, in extreme situations, when exposure to “crowd crush” and “turbulence” effects exists.