Suchergebnisse

Management in service industries are constantly faced with the problem of balancing customer service against achieving a high level of economic efficiency in managing their own resources. The problem is shown to be particularly acute in the management of Freightliner Terminals where there are extraordinary fluctuations in the demand for the service. A computer model is described which simulates operations at a terminal and assists management in predicting the likely performance of the terminal for different levels of throughput.

AbstractThis paper is an excerpt from The Electronic Oracle: Computer Models and Social Decisions (Chichester: John Wiley & Sons, 1985), by the late Donella Meadows and Jennifer Robinson. The book investigates the practice and impact of systems analysis and computer modeling, particularly as applied to social policy. The authors explore the nature of models, the biases and hidden assumptions of different modeling methods, the pragmatics of the modeling process, and the impact of modeling on the real world. These issues are approached through detailed case studies of nine models designed to address issues of economic development, resources and the environment. The models used methods including econometrics, linear programming, input/output analysis, and system dynamics. Though the models were "identified as 'better than average'" by the authors and by "other modelers, clients, and sponsors," Meadows and Robinson (p. 104) found "mismatches of methods with purposes, sloppy documentation, absurd assumptions buried in overcomplex structures, conclusions that do not even follow from model output, and project management strategies that destroy the possibility of influencing actual policy." The record in the world of business modeling is at least as dismal. The excerpt presented here focuses on implementation. The authors explore why so many modeling projects fail and present guidelines for improvement. The methods developed in the book to expose hidden assumptions, to make undiscussable values and biases discussable, remain central to anyone seeking to have an impact on the real world. The book both anticipated and shaped important developments, including the focus on 'modeling for learning,' group model building, and the systems thinking and organizational learning movements. Yet despite welcome advances in hardware, software, and modeling methods since the book was written, we have not yet realized the authors' vision of a world in which modelers are not only scientific and rigorous, but also "compassionate, humble, open‐minded, responsible, self‐insightful, and committed." John Sterman Copyright © 1985 International Institute for Applied Systems Analysis. Reprinted by permission.

ABSTRACTRecent years have witnessed a renewal of interest in the application of management science techniques to personal selling related problems. Some early applications are described in [2] [7]. Cloonan has employed simulation in examination of the salesman routing problem [3] [4]. Lodish, in CALLPLAN, has devised an interactive call planning system designed to assist sales management and/or salesmen in allocating sales call time more efficiently [6]. Armstrong has devised a system he labels SCHEDULE which estimates the value of calls on accounts [1]. Hess and Samuels have designed a computer based sales districting model which is an analogue of a legislative apportionment model [5]. The objective of this paper is to explore the nature of a call planning system entitled ALLOCATE. ALLOCATE was designed to be employed by upper sales management either as an input device for sales management decisions such as sales‐territory‐size, or as a vehicle for determining the effects of alternative call allocation strategies on territorial revenue over multiple time periods.

Real Estate Assessment –or Appraisal– is mainly employed in government for taxation purposes. There are a number of methodologies to assess the value of a property so as to calculate taxes or just its value. Normally, several attributes belonging to the property are used for this purpose, and one of the most simple method employed it is the additive method. Among the attributes used, it can be found the plot area, the area of the buildings, the improvements on the property, the intended use (e.g. production, habitation, etc.), geographical location, etc. This assessment can be used as a percentage, index, proportion, etc. to levy the taxes. There are different kinds of property tax, e.g. ad valorem, special tax, etc. We propose here the use of a general method that can be used with any of these. This method –the Logic Score of Preference (LSP) method– provides a way to aggregate different attributes of a property into a single value using a Continuous Logic. The resulting index can then be used to calculate the final value of the tax. The method is flexible and it allows a wide range of possibilities as well as a fine gradation of the value of different properties; it also allows to contemplate the varied conditions and attributes of properties to make a more precise assessment. ; Sociedad Argentina de Informática e Investigación Operativa

Projecting losses associated with hurricanes is a complex and difficult undertaking that is fraught with uncertainties. Hurricane Charley, which struck southwest Florida on August 13, 2004, illustrates the uncertainty of forecasting damages from these storms. Due to shifts in the track and the rapid intensification of the storm, real‐time estimates grew from $2 billion to $3 billion in losses late on the 12th to a peak of $50 billion for a brief time as the storm appeared to be headed for the Tampa Bay area. The storm struck the resort areas of Charlotte Harbor and moved across the densely populated central part of the state, with early poststorm estimates in the $28 to $31 billion range, and final estimates converging at $15 billion as the actual intensity at landfall became apparent. The Florida Commission on Hurricane Loss Projection Methodology (FCHLPM) has a great appreciation for the role of computer models in projecting losses from hurricanes. The FCHLPM contracts with a professional team to perform onsite (confidential) audits of computer models developed by several different companies in the United States that seek to have their models approved for use in insurance rate filings in Florida. The team's members represent the fields of actuarial science, computer science, meteorology, statistics, and wind and structural engineering. An important part of the auditing process requires uncertainty and sensitivity analyses to be performed with the applicant's proprietary model. To influence future such analyses, an uncertainty and sensitivity analysis has been completed for loss projections arising from use of a sophisticated computer model based on the Holland wind field. Sensitivity analyses presented in this article utilize standardized regression coefficients to quantify the contribution of the computer input variables to the magnitude of the wind speed.