The purpose of this paper is to apply a generalized version of the Farrell measure of technical efficiency to a sample of Illinois strip mines. We disaggregate the original Farrell measure (which was designed to measure lost output or wasted inputs due to underutilization of inputs) into three mutually exclusive and exhaustive components: (1) a measure of purely technical efficiency, (2) a measure of input congestion (overutilization of some input(s)) and (3) a measure of scale efficiency. This approach has the advantage that it provides additional information on the sources of inefficiency of production, which should be useful to managers, in general, not only in strip mining. Simple linear programming techniques are derived and used in calculating these efficiency measures for our sample. We find that Illinois strip mines are fairly efficient (relative to each other). The major source of inefficiency was due to deviations from the optimal scale of production. We also find suggestive evidence that inefficient mines tend to have relatively high stripping ratios, high labor-output ratios, single rather than multiple coal seams, and lower earth-moving capacity.
The paper describes the results of an experimental test of a theoretical model which explains under what circumstances the interaction between MIS-users and EDP-specialists during the design of an information system will lead to success (i.e., efficient task-accomplishment). The research also includes an experiment about the influence of a third party playing different kinds of mediating roles. The results confirm the theoretical model. They are also corroborated by the findings in two case studies in a car-manufacturing firm, briefly discussed at the end of the paper. It appears that the users of the information system who have to deal with EDP-specialists having sanctionary power over them (a case of power asymmetry) are less inclined to implement the system exactly as the user and the specialist had agreed upon, than users not so dependent upon the EDP-specialist (i.e., no power asymmetry). This effect seems to be more pronounced when there exists a semantic gap between the user and the specialist (i.e., when they use different concepts for the task). Moreover, such defective implementation behavior (i.e., not adhere to the plan) seems to entail less efficient task-accomplishment. As predicted by the model, the presence of a third party which stimulates the user to neglect the possible implications of power asymmetry so that effective communication among the parties is reestablished nullifies the disturbing effect of power asymmetry and semantic gap mentioned above. Some organizational design implications of the findings are discussed.
This paper describes a practical algorithm for large-scale mean-variance portfolio optimization. The emphasis is on developing an efficient computational approach applicable to the broad range of portfolio models employed by the investment community. What distinguishes these from the “usual” quadratic program is (i) the form of the covariance matrix arising from the use of factor and scenario models of return, and (ii) the inclusion of transactions limits and costs. A third aspect is the question of whether the problem should be solved parametrically in the risk-reward trade off parameter, λ, or separately for several discrete values of λ. We show how the parametric algorithm can be made extremely efficient by “sparsifying” the covariance matrix with the introduction of a few additional variables and constraints, and by treating the transaction cost schedule as an essentially nonlinear nondifferentiable function. Then we show how these two seemingly unrelated approaches can be combined to yield good approximate solutions when minimum trading size restrictions (“buy or sell at least a certain amount, or not at all”) are added. In combination, these approaches make possible the parametric solution of problems on a scale not heretofore possible on computers where CPU time and storage are the constraining factors.
Due to the complexity of optimum replacement problems over finite lime horizons various asymptotic criteria based upon fixed age replacement policies have been employed in the literature and in practice. In this paper the relationships between the optimum policies under three alternative cost criteria are considered. An ordering of the accounting costs under two of these is obtained, and for distributions with Increasing Hazard Rate an ordering of the optimum replacement time is derived. For a finite time horizon the policies are compared to the optimal sequential and fixed-age replacement polices through the example of a gamma distribution previously investigated by Barlow and Proschan (Barlow, R. E., F. Proschan. 1962. Planned replacement. K. J. Arrow, S. Karlin, W. L. Smith, eds. Studies in Applied Probability and Management Science. Stanford University Press, Stanford, Cal.; Barlow, R. E., F. Proschan. 1965. Mathematical Theory of Reliability. Wiley, New York.).
This paper describes the nature and design of post-industrial organizations. It begins with an assessment of the popular literature on post-industrial society, and finds that this literature is an inappropriate basis for inferring the nature of post-industrial organizations. Partly as a consequence of this finding, the paper turns to systems theory as a basis for determining both the nature of post-industrial society and the nature of the increased demands that this environment would impose on post-industrial organizations. The middle three sections of the paper describe design features that post-industrial organizations will employ to deal with these demands. In particular they examine designs for making more effective three processes that will exhibit increased importance in post-industrial organizations: (1) decision-making, (2) innovation, and (3) information acquisition and distribution. In addition to its conclusions concerning the design features that post-industrial organizations will possess, the paper sets forth three general conclusions. One of these is that, even though the aggregate of the demands on post-industrial organizations will be qualitatively greater than that experienced by previous organizations, there are design features that organizations can adopt that will enable them to cope with even worst-case loadings of these demands. A second conclusion is that the nature of the post-industrial environment will cause decision-making, innovation, and information acquisition and distribution to take on added importance in post-industrial organizations, and that one result of this will be that organizations will attempt to ensure routine effectiveness of these processes through increased formalization. In some cases this formalization will have as its purpose ensuring the existence of informal (or at least unstructured) activities, such as experimentation by “self-designing” organizations or acquisition of “soft” information by top managers. The third conclusion set forth is that during the current transition period between the industrial and post-industrial societies we can expect many organizations to fail, or to flee to less than wholly desirable niches, because they are ignorant of the post-industrial technologies, structures, and processes that would enable them to successfully engage the post-industrial environment and to become viable post-industrial organizations. It appears that an important task of organizational and management scientists during this period will be to aid in the development, transfer, and implementation of post-industrial design features and in this way help reduce the possibility of unnecessary failure or flight.
The Dialectical Inquiry System (DIS) and the Devil's Advocate (DA) have been recommended as strategic decision-making aids and as improvements on the traditional expert (E) approach in which strategic decisions are based on preliminary analyses and proposals by staff experts. Previous research on the effects of the DIS and DA has produced conflicting results. In the present study, subjects produced alternative strategies and recommendations for a company described in a case. They were given the E, DA, or DIS treatment either in written form or via videotape. In addition, some were assigned to a control (C) group and received no planning assistance. The results showed that the written DA, the videotape DI, and the videotape E treatment caused subjects to generate fewer functional area alternatives than the C subjects. Further, the subjects receiving the written DA generated more strategic alternatives than those receiving the written DIS or E. The DA also reduced the effects of an “expert report” on subjects' final recommendations while the DIS did not. Subjects given the DA and DIS reported greater satisfaction with the process than those given the E.
We develop a production planning model in the context of a system of assembly lines or production lines. The model is a large-scale linear program and we provide a polynomial column generation technique for its efficient solution. The column generation technique and the approach therein are also of interest in certain other problems. A numerical example to illustrate the algorithm is included. Finally computational experience with the algorithm is summarized.
An interactive goal programming approach for assessing scenario probabilities used in long-range forecasting and decision analysis is developed and illustrated using a small numerical example. The method only requires marginal event probability and ordinal or interval first-order conditional probability assessments of a limited number of events constituting the scenarios and guarantees the consistency of the assessments in terms of the laws of probability calculus.
Risk analysis and policy analysis can play important roles in facilitating the siting of potentially hazardous facilities if one recognizes the descriptive features of the decision process. The case of siting a liquified natural gas (LNG) facility in California illustrates the multi-party sequential nature of the process and the role that widely differing risk estimates play in fueling conflicts between stakeholders. Risk analysis does have a useful function in clarifying the nature of the potential losses, particularly if rules of evidence are instituted for evaluating different studies. Policy analysis can facilitate the negotiation process by the use of compensation to redistribute gains and losses between the different parties. Examples from case studies are presented to illustrate the challenges for risk analysis and policy analysis in the siting process.
This paper develops two stochastic models of an internal mail delivery system in which a single clerk picks up, sorts and delivers mail to a closed loop of offices. The two models differ in whether deliveries are made at scheduled times or not. For a model in which all mail picked up each round is sorted before the next delivery, we assume that mail is generated in the system by a stationary Poisson process and derive an expression for the expected delay between generation of a letter and its ultimate delivery. These results are then extended to systems in which letters are generated according to a stationary compound Poisson process and to multiple clerk delivery systems. A second model in which mail is delivered at scheduled times only is shown to be equivalent to a classical storage process. For this model, we derive bounds on the expected number of letters left unsorted at the start of a scheduled delivery and the expected delivery delay. This model is also generalized to multiclerk systems.