COST MANAGEMENT AND COST CONTROL IN DECISIONAL PROCESS OF ORGANIZATIONS

In this article we wanted to show the importance of the costs of providing the necessaryinformation to the management in order to take the best decisions in crisis conditions. Under thedouble-effect of the pressure coming from the competition and the world financial crisis, theenterprises feel the need to understand better their costs in order to determine with maximumprecision the selling prices and the limits that can be achieved for each product. It’s not only aboutprevision, there should also be considered the necessary ways in order to achieve the goals. That’show we can explain the development of the today’s managerial control and of its favourite instrument,the analytic accounting of which no enterprise in Romania or Europe could be spared, and this isbecause behind the demand and offer of all price-competition there lies, indirectly, the cost-competition.managerial accounting, internal transfer prices, hidden costs

Optimal control and optimal sensor activation for Markov decision problems with costly observations

This paper considers partial observation Markov decision processes. Besides the classical control decisions influencing the transition probabilities of the Markov process, we also consider control actions that can activate the sensors to provide more or less accurate information about the system state, explicitly including the cost of activating sensors. We synthesize control laws that minimize a discounted operating cost of the system over an infinite interval of time, where the instantaneous cost function depends on the current state, the control influencing the transition probabilities, and the control actions activating the sensors. A general computationally efficient optimal solution for this problem is not known. Hence we design supoptimal controllers that only use knowledge of the value function for the full state information Markov decision problem. Our solution guarantees that the discounted cost of operating the plant increases only by a bounded amount with respect to the minimal cost for the full state information problem. A new concept of pinned conditional distributions of the state given the observed history of the plant is required in order to implement these control laws online

Thermodynamic cost of external control

Artificial molecular machines are often driven by the periodic variation of an external parameter. This external control exerts work on the system of which a part can be extracted as output if the system runs against an applied load. Usually, the thermodynamic cost of the process that generates the external control is ignored. Here, we derive a refined second law for such small machines that include this cost, which is, for example, generated by free energy consumption of a chemical reaction that modifies the energy landscape for such a machine. In the limit of irreversible control, this refined second law becomes the standard one. Beyond this ideal limiting case, our analysis shows that due to a new entropic term unexpected regimes can occur: The control work can be smaller than the extracted work and the work required to generate the control can be smaller than this control work. Our general inequalities are illustrated by a paradigmatic three-state system.Comment: 11 pages, 3 figure

Some aspects of the control and analysis of costs in the steel industry

This article aims to describe the control and cost analysis in actual conditions. There are described the types of analysis and cost control in the enterprise from steel industry of Romania, the stages which an enterprise should follow to take its control and cost analysis.estimated costs; effective costs; control; cost analysis; deviation.

Workload reduction of a generalized Brownian network

We consider a dynamic control problem associated with a generalized Brownian network, the objective being to minimize expected discounted cost over an infinite planning horizon. In this Brownian control problem (BCP), both the system manager's control and the associated cumulative cost process may be locally of unbounded variation. Due to this aspect of the cost process, both the precise statement of the problem and its analysis involve delicate technical issues. We show that the BCP is equivalent, in a certain sense, to a reduced Brownian control problem (RBCP) of lower dimension. The RBCP is a singular stochastic control problem, in which both the controls and the cumulative cost process are locally of bounded variation.Comment: Published at http://dx.doi.org/10.1214/105051605000000458 in the Annals of Applied Probability (http://www.imstat.org/aap/) by the Institute of Mathematical Statistics (http://www.imstat.org

Configurations of Control: A Transaction Cost Approach

In this paper, I present a theory of management control based on Transaction Cost Economics.This theory seeks to integrate into a single framework a set of insights as to the natureof the organization's activities, the control problems that are inherent in these activities,and the unique problem solving potential of various archetypal control structures. The gistof the argument is that activities predictably differ in the control problems to which theygive rise, whereas control archetypes differ in their problem-solving ability, and thatalignments between the two can be explained by delineating the efficiency properties of thematch. This is a contingent configuration approach. It is a configuration theory in that itoffers a set of ideal types, conceived of as internally consistent and discriminating clustersof attributes from multiple dimensions that have a specific effect on control structureeffectiveness as the variable to be explained. But it is also a contingent approach in that itspecifies the conditions in which each of the archetypes is most effective.transaction cost economics;management control theory;configuration theory

A Formal Approach to Modeling the Cost of Cognitive Control

This paper introduces a formal method to model the level of demand on control when executing cognitive processes. The cost of cognitive control is parsed into an intensity cost which encapsulates how much additional input information is required so as to get the specified response, and an interaction cost which encapsulates the level of interference between individual processes in a network. We develop a formal relationship between the probability of successful execution of desired processes and the control signals (additive control biases). This relationship is also used to specify optimal control policies to achieve a desired probability of activation for processes. We observe that there are boundary cases when finding such control policies which leads us to introduce the interaction cost. We show that the interaction cost is influenced by the relative strengths of individual processes, as well as the directionality of the underlying competition between processes.Comment: 6 pages, 3 figures, Conference pape