:Burkov V. N. / Marin L. F. / Enaleev A. K. / Kondratev V. V. : ( ): Wydawnictwo Politechniki Wroclawskiey : 1981 : : Scientific Papers of the Institute of Technical Cy () : 63 : Burkov V.N., Marin L.F., Enaleev A.K., Kondratev V.V. Design of functioning mechanism for two-level organizational systems with the center incompletely informed. Wroclaw: Wydawnictwo Politechniki Wroclawskiey. Scientific Papers of the Institute of Technic : ( ) : : :
:Burkov V. N. / Novikov D. A. : : 1994 : : Proceedings of X-th IC on Systems Engineering : B.H., .. Active systems theory and contract theory: comparison of ideas and results. Coventry: Proceedings of X-th IC on Systems Engineering. 1994 : ( ) : : :
:Burkov V. N. : : 1972 : .. : Control and Cybernetics () : 1/2 : Vol. 1 : Burkov V.N. Problems of optimum distribution of resources // Control and Cybernetics. 1972. Vol. 1. N. 1/2. P. 27-41. : The optimum distribution of a limited quantity of resources, is one of the most important trend in the theory of network planning and of control. Problems of an optimum distribution of resources, are in principle extremal problems of combinational type. At present there are no effective and accurate methods for the solution of such problems. A satisfactory developed theory exists only for the problems where ordering of the network events is assumed. The paper considers basic results and methods of optimum distribution of resources, when the network events are ordered.
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Problemy optymalnego rozdziału ograniczonych zasobów są jednym z najważniejszych kierunków teorii sterowania i planowania sieciowego. Optymalny rozdział zasobów jest w zasadzie zagadnieniem ekstremalnym typu kombinatorycznego. Obecnie nie ma efektywnych i dokładnych metod rozwiązywania takich zagadnień. Wystarczająco opracowana jest jedynie teoria dotycząca zagadnień, w których zakłada się uporządkowanie zdarzeń sieci. W pracy niniejszej rozpatrzono
podstawowe wyniki i metody optymalnego rozdziału zasobów uzyskane przy założeniu, że zdarzenia sieci są uporządkowane. : : :
:Burkov V. N. / Enaleev A. K. : : 1994 : : Mathematical Social Sciences : Vol. 27 : Burkov V.N., Enaleev A.K. Stimulation and decision-making in the active systems theory: review of problems and new results // Mathematical Social Sciences. 1994. Vol. 27. P. 271 291. : : ( ) : : :
:Burkov V. N. / Lerner A. . : ( ): North-Holland Publishing Company : 1971 : : Differential games and related topics : Burkov V.N., Lerner A. Ya. Fairplay in control of active systems / Differential games and related topics. Amsterdam, London: North-Holland Publishing Company, 1971. P. 164 168. : Large-scale manmachine systems incorporate subsystems whose goals do not generally coincide with the of the system. A single man or a group of people make a subsystem actively maximize its objective function by reporting the information on its model (in other words on its potential) to an external control unit. Besides the subsystem has certain information on the strategy applied by the external control unit and by other subsystems and uses this information in its own interests. This lecture is concerned with control of such active systems that incorporate men and groups of people that are after their own goals. The control problem is to find an optimal plan for the system so that the subsystems plans be also optimal. A solution of the control problem based on the fair play principle is proposed. This principle largely recognizes the active nature of the subsystems.
:Novikov D. A. / Burkov V. N. : ( ): Technica : 1995 : : Business and management : .., .. Active systems theory and problems of large-scale projects management / Business and management. Vilnius: Technica, 1995. Vol. 1. P. 93 103. : ( ) : : :
:Burkov V. N. / Novikov D. A. : ( ): Proceedings of 14-th IFAC World Congress : 1999 : : Burkov V.N., Novikov D.A. Fuzzy incentive problem / Proceedings of 14-th IFAC World Congress. Beijing. China. 1999. Vol. L. P. 345 349. : Game-theoretical model of the incentive mechanism is considered for the agency, which is embedded in fuzzy environment. The paper includes the solution of fuzzy incentive problem and the analysis of uncertainty influence on the efficiency of management. : ( ) : : :
:Burkov V. N. / Novikov D. A. / Petrakov S. N. : : 1999 : : Systems Science () : 1 : 25 : Burkov V.N., Novikov D.A., Petrakov S.N. Mechanism design in economies with private goods: truthtelling and feasible message sets // Systems Science. 1999. Vol. 25. N 1. P. 71 - 78. : ( ) : : : /
:Burkov V. N. / Novikov D. A. : : 1999 : : Systems Science () : 2 : 25 : Burkov V.N., Novikov D.A. Models and methods of multiprojects' management // Systems Science. 1999. Vol. 25. N 2. P. 5 - 14. : : / : /
:Burkov V. N. / Novikov D. A. / Balashov V. G. / Zalojnev A. Y. : : 2003 : : Journal of business economics and management () : 2 : 4 : Balashov V.G., Burkov V.N., Novikov D.A., Zalojnev A.Yu. Incentives in hierarchical organizations // Journal of business economics and management. 2003. Vol. IV. 2. P. 81 - 85. : ( ) : / : / :
: ( ): SPbGU : 2011 : : Burkov V. N., Goubko M. V. Combining Incentive Schemes with Mechanisms of Counter Planning and Plan Adjustment // Game theory and Management. Collected abstracts of papers presented on the Fifth International Conference Game theory and Management. SPb.: Graduate School of Management SPbU, 2011. P. 40-42. : Planning is an essential function of management in an organization. Plans and forecasts help organizations to meet future events and conditions. For instance, sales forecasts are used to calculate production schedules, stock reserves, and purchases. Plan failures result in substantial transaction costs due to overstocks and cash deficiency, or, in contrast, emergency work, imperfect logistics, and violation of delivery terms. The expectable medium output is often preferable to the unplanned success.
A typical planning mechanism met in business is centralized, i.e. the plan is set by a principal to her agents on the basis of historical data, current circumstances, and corporate strategy. A disadvantage of such approach is that detailed private information available to agents is missed. A counter planning mechanism where agents are asked for their plans provides an alternative.
Counter planning mechanisms for individual employees were introduced in the late 60th of the XX century in Soviet economy to motivate employees enhanced obligations. The responsibility for the plan quality in the process of counter planning is supported by a system of penalties. Now, fees for deviations from the planned consumption level are typical in wholesale energy and natural gas contracts, but are less common within organizations.
Counter planning mechanisms were first studied from the game-theoretic point of view by Burkov (1977). Linear penalties were shown to be enough to achieve any specific desired plan stringency (the probability of plan underfulfilment), which is determined by the ratio πO/(πU + πO), where πU and πO are the penalty rates for plan underfulfilment and overfulfilment respectively. Surprisingly, in the linear case the principal need not even know the probability distribution of output to implement the first best. In last decades the counter planning mechanisms were implemented in several industries and demonstrated their applicability and high effectiveness.
Unfortunately, the classic theory fails to explain the absolute values of the optimal penalty rates. In this paper we equip the model of counter planning with agents planning costs and efforts and immerse it into the moral hazard framework. The aim of the analysis is to develop the policy recommendations on penalty strength. The policy must be simple enough to be used in management consulting projects under time pressure and lack of statistics.
Additional information arrives in the process of plan execution by an agent. When agents output expectations change during the planning period the principal is interested in plan adjustment. To motivate timely re-planning requests the agent is faced with another system of re-planning penalties of smaller strength, as compared to the plan failure penalties.
Analogous to the simplest moral hazard model, no problem arises in the case of a risk neutral agent. The optimal combined mechanism replicates principals profits and costs to an agent, while constant payment is chosen to fulfill individual rationality. In the more realistic situation of a risk-averse agent (including the important case of guaranteed payment constraints) a number of biases arise from principals efforts to maximally secure an agent. We perform the detailed analysis of these biases to justify the following extensively used policy recommendations:
When H(z) is monotone, the incentive function is also monotone in z.
Any desired plan stringency can be implemented by the principal.
etc... : ( ) : : :
: : 2013 : .. : Advances in Systems Science and Application () : Vol. 13. 1 : V.N. Burkov, M.V. Goubko, N.A. Korgin, D.A. Novikov Mechanisms of Organizational Behavior Control: A Survey // Advances in Systems Science and Application. 2013. Vol. 13. 1. P. 1 20. : Basics are surveyed of a version of mechanism design theory tailored to solve management problems. The concept of a mechanism of organizational behavior control is introduced. Methodological grounds of the theory are discussed along with mechanisms classification. Mechanism implementation process is characterized. Also, basic mechanisms are sketched, which help solving important management problems on all stages of management cycle. An example of the mechanism of incentive-compatible planning is considered.
: : 2013 : .. : Advances in Systems Science and Application () : Vol. 13. 3 : Burkov V.N., Goubko M.V., Korgin N.A., Novikov D.A. Integrated Mechanisms of Organizational Behavior Control // Advances in Systems Science and Application. 2013. Vol. 13. No 3. P. 217 225. : Problems of control mechanisms integration are formulated and discussed in the framework of mechanism design for organizational behavior control. Unified schemes for control mechanisms description and design are proposed. An example of the integrated production cycle optimization mechanism is considered.
: ( ): Nova Publishers : 2013 : : Burkov V., Goubko M., Kondratev V., Korgin N., Novikov D. Mechanism Design and Management: Mathematical Methods for Smart Organizations (for managers, academics and students). - New York: Nova Publishers, 2013. (Print and e-book) : Mechanism Design (MD) is a branch of game theory which deals with conflict situations involving a principal and a set of active agents (usually in the presence of asymmetric information). Mechanism design theory delivers a solution to many management problems in the form of a control mechanism, (i.e., a formalized routine of decision-making). Formal results of MD can change the fundamentals of managerial practice by introducing decision-making mechanisms in organizations, which are efficient and robust with respect to employees self-serving behaviour.
The proposed book seeks a more intensive application of MD methodology and its formal results in organizations. The main aim of the book is to provide readers with the basics of an MD-based view on managerial problems, so that intra-firm policies can be analysed through the looking glass of employees behavioural response. A systematic introduction of the underlying MD methodology is combined with a collection of ready-to-use mechanisms for solving typical management problems. The use of MD by individual managers is facilitated by bringing together mathematical and business literature in a single treatise.
This book is not a purely academic monograph as it contains as few formulas as possible, and no formal proofs (references to formal results are provided throughout the text). Courses on MD for managers are not common in business schools now, and our book represents the perfect material for such a course. (Imprint: Nova)
Table of Contents:
Preface
Introduction
Part I. Control Methodology: An Introduction
Chapter 1. Organization, Activity, Control
Chapter 2. Control Systems
Chapter 3. Control Efficiency
Part II. Organizational Behavior and Control Mechanisms
Chapter 4. Control of Organizational Behavior
Chapter 5. Analysis and Synthesis of Control Mechanisms
Part III. Basic Control Mechanisms
Chapter 6. Planning Mechanisms
Chapter 7. Organization Mechanisms
Chapter 8. Incentive Mechanisms
Chapter 9. Assessment and Control Mechanisms
Chapter 10. Examples of Integrated Control Mechanisms
References
Index
Series:
Business Issues, Competition and Entrepreneurship
Management Science - Theory and Applications
Binding: Hardcover
Pub. Date: 2013 - 3rd Quarter
Pages: 7x10 - (NBC-C)
ISBN: 978-1-62618-609-5
: ( ): CRC Press : 2015 : : Burkov V. N., Goubko M., Korgin N., Novikov D. Introduction to Theory of Control in Organizations. - Boca Raton: CRC Press. 2015 : Features
Describes how to integrate advanced formal methods of optimization, game theory, and mechanism design into daily managerial practice
Requires no prior knowledge of game theory or mechanism design
Supplies a systematic introduction to the underlying methodology of control theory and systems analysis
Introduces novel models of informational control unique to this book
Includes a set of exercises in each chapter that vary from simple to advanced
Summary
Introduction to Theory of Control in Organizations explains how methodologies from systems analysis and control theory, including game and graph theory, can be applied to improve organizational management. The theory presented extends the traditional approach to management science by introducing the optimization and game-theoretical tools required to account for the special nature of human beings being viewed as control objects.
The book introduces a version of mechanism design that has been customized to solve the problems that todays managers must contend with. All mathematical models and mechanisms studied are motivated by the most common problems encountered by managers in firms and non-profit organizations.
Requiring no prior knowledge of game theory or mechanism design, the book includes a systematic introduction to the underlying methodology of modern theory of control in organizations. The authors use formal methods to construct robust and efficient decision-making procedures which support all aspects and stages of management activity over all decision horizonsfrom operational to strategic management.
The mathematical and methodological backgrounds of the organizational mechanisms discussed are not limited to game theory but also include systems analysis, control theory, operations research, and discrete mathematics.
The book includes a set of exercises in each chapterfrom simple to advancedthat provide the reader with the understanding required to integrate advanced methods of optimization, game theory, and mechanism design into daily managerial practice.
