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Decomposable mathematical programming problems sometimes admit a certain degree of decentralization in the decision process. By an informative interplay between a central authority and a number of subdivisions one hopes to establish the overall best solution. This interplay can be organized in either of two ways: direct or indirect distribution. However, an absolute prerequisite for such procedures to be successful is the availability of an optimality criterion to the centre so as to know when to stop the iterative process. It is well known that for either of two cases the optimality conditions as derived from the Kuhn-Tucker conditions for the overall problem are not satisfactory. The present paper makes a comparison between the shortcomings of the two kinds of conditions. In the case of direct distribution this condition turns out to be necessary but unfortunately not sufficient and for indirect distribution the condition is sufficient but not necessary. The insufficiency in the direct and the absence of necessity in the indirect case, which are caused by eventual nonconvexities of the problem, are explored a bit further. A simple example is presented. [ABSTRACT FROM AUTHOR]

A number of analytic formulations of resource allocation activities in decentralized organizations have considered the effects of economic or technological externalities but most treatments have neglected concomitant organizational or behavioral effects. This paper introduces the concept of a behavioral externality and relates it to the decision-making process in decentralized organizations. Alternative analytic formulations of behavioral externalities are examined, and a numerical example is presented. [ABSTRACT FROM AUTHOR]

The organization structure of the firm has been the subject of diverse research approaches. The purpose of this paper is to provide a framework for integrating the various views and analyzing the various factors that affect centralization and decentralization. After a historical review of some milestones in organization research, a definition of decentralization which is based on the overall objectives of the firm is provided. The notions of hierarchical and mutual interaction structures are examined and contrasted with the notion of decentralization. Finally, the determinants of divisionalization are analyzed, and the suggestion is made that a study of the covariance matrix of subunit performance will guide us to the areas that need attention for possible reorganization. [ABSTRACT FROM AUTHOR]

A mathematical expression for the cost of maintaining a client-centered service organisation is derived. It shows the dependency of the total cost on the service-request load, the number of hierarchical levels of the organization, and the administrative costs. The mathematical formulation is based on a model in which the main variables are the times spent on communication between different levels of the organization and on communication between agents at the same level. The optimum number of levels for minimising cost is derived, and its sentivity to request load is investigated. [ABSTRACT FROM AUTHOR]

The article discusses a variety of topics, including cost accounting, decentralized control in management, incentives in industry and the assignment of joint costs and internal pricing. According to the author, managers should design systems of rewards for those who take risks in their decision making that give proper weight to a decision's worth to the organization. Also discussed is the theory of cooperative games as it relates to joint rewards and incentives obtained by groups of individuals acting together.

Under what conditions is decentralization of facilities rational for a client-centered system of service or administration, and when is great centralization more cost-effective? Four aspects of decentralization are identified: (1) pluralization of facilities (e.g. service points or channels); (2) dispersal in geographic space; (3) specialization by function or kind of service; and (4) adaptation to the specific requirements of each case through repeated feedback passes or negotiating queries. Different functions or kinds of service are treated as being located in a function space; the distances among them correspond to the number and cost of adjustment steps which a server or a service facility needs to shift from one function to another. For calculating the optimal number of facilities, n, the most important variables, calculated as averages, are the service load; the geographic distance; the cost of time spent in transporting a request and the response to it, and the transport speed; the functional distance or number of functions; the cost of time in adjusting to the function requested; and the adjustment speed; and the total fixed cost per facility. Other important variables are the number of negotiating queries per request, and an indicator of the value of time (i.e. of a speedier response). Under certain assumptions, such as neglecting economies or diseconomies of scale, the optimum number of facilities for a system with a single function then varies as the square root of the service load; this is also the case for a system with a single location but several functions. For a system with several functions and locations, the optimal number of facilities varies as the two-thirds power of the service load. Long-term trends may be toward decentralization when service loads and the costs of service time grow faster than capital costs and transport and adjustment speeds, as seems likely for the next several decades. Where the opposite conditions prevail, cost-effectiveness should favor centralization, such as perhaps in some earlier periods, and possibly in the more distant future. Possible applications through eventual elaborations of these oversimple models are suggested for fire, ambulance, and police, school and local government systems; hospitals and clinics; libraries, telephone exchanges, and computer systems; laboratories, repair shops, and mail order houses; law courts and judicial districts; and the numbers of administrative districts and sovereign states. [ABSTRACT FROM AUTHOR]

Long-range investment plans, particularly for expansion or decentralization, often consist of a number of separate but interacting investments spaced over a number of years. Where there is appreciable uncertainty about external conditions in the future, it is possible that a "best" scheme based on the state of current knowledge will prove during the course of the intervening years to be less than good. One way of guarding against this danger is to ensure that the early (and therefore irreversible) steps in the investment sequence keep open as many options of "good" schemes as possible. Concepts of robustness and stability are developed. As a practical example of the use of these concepts a case study is presented, which deals with the location of sites for new factories in an industrial expansion program. [ABSTRACT FROM AUTHOR]

The effect of different company organizational structures (as centralized and decentralized) on competition in coupled markets is studied using a game theory approach. By coupling it is meant that management actions taken in the market for one product have an effect on the market for another. A specific example is where advertising dollars spent in generating sales for one product have an influence on the sales of another product. In some cases competition between companies in coupled markets takes the form of a Prisoner's Dilemma and may be discussed in terms of recent research findings on this game. Various other aspects of research on competitive organizational structures in coupled markets are discussed. [ABSTRACT FROM AUTHOR]

Ronald Howard's editorial comments in the June, 1967 volume of this journal stressed the power of the pricing mechanism in the control and optimization of social systems. This article illustrates how such a concept can be applied via a decomposition algorithm for quadratic programming. A set of artificial markets for scarce resources and transfer goods is introduced into a model of a divisionalized firm and a quadratic decomposition algorithm is used to find the optimal (profit maximizing) set of prices for these goods. The algorithm requires a minimal amount of information transmission from the divisions to corporate headquarters and can be applied to divisionalized firms operating in imperfect markets. It also has significant behavioral implications not found in other decomposition algorithms for the firm which employs a profit-center method of control. The value of the algorithm is evident in those situations where decentralization is either desirable or a necessity and where interdependencies exist. [ABSTRACT FROM AUTHOR]

An exploration of the margin of error entailed in using a "one-point move" algorithm for solving a class of fixed-charge problems. The algorithm is of interest both from the viewpoint of numerical analysis and also from the analogy with market mechanisms. Despite the presence of economies-of-scale, there is the possibility of operating a decentralized system. This is a two-price system; it implies discriminatory and also marginal cost pricing. [ABSTRACT FROM AUTHOR]

The decomposition procedure for the solution of large scale linear programs is described in an elementary manner with illustrative calculations. Its economic interpretation as a procedure for decentralized decision by the multidivision firm or the multi-sector economy is explained in detail. Decomposition is shown to provide internal prices for decentralized decision making in the presence of external economies or diseconomies. However, it is demonstrated that in many cases there exist no prices which will lead divisions to make independent decisions that are optimal from the point of view of the company (or the economy) as a whole. [ABSTRACT FROM AUTHOR]

The design of a long term research program on the organization of R and D in decentralized companies is presented. The decentralized firm and the various deployments of R and D in such firms are described. Data is given on the incidence of the various organizational forms in five industry groups. The classes of decisions commonly encountered in R and D are indicated. Categories for describing and analyzing the assigned mission of an R and D lab are presented. [ABSTRACT FROM AUTHOR]