Norbert Lloyd Enrick

The meta-model of OR/MS

The purpose of this paper is twofold: (1) to discuss the relevance of Operations Research/Management Science (OR/MS) models to the planning and control process in management; and (2) to suggest a meta-model and a meta-modeling approach to facilitate the identification of the characteristics of a problem and the selection of the appropriate model for solving it. The approach used here is conceptually founded, and its objective is to provide a framework for presentation of OR/MS models to a potential user independently of mathematical derivations. An incidental result is that OR/MS models can be related to other disciplines, such as economic equilibrium theory and statistical inference.

An Analysis of Means in a Three-Way Factorial

Traditional analysis of variance, emphasizing significance tests, covers only one aspect of the analysis of an experiment. The information content, particularly of factorially designed studies, can be expanded markedly by a multi-comparative plotting of..

Classical error pairs and the Bayesian prior

SummaryWe have attempted to show the way in which Bayesian and classical approaches are both similar and divergent. The vehicle for discussion, primarily, involved considerations of cost consequences, planning horizons and numbers of alternatives. In turn, these variables were related to the statistical problem continuum, with classical and Bayesian approaches at opposite ends of the scale. By relating problem variables to this continuum, the question of which approach is most appropriate in a particular situation can be more readily resolved.

Analysis of means in marketing research

Analysis of variance, often the method of choice in evaluating the outcomes of marketing tests, can be significantly enhanced in its decision-support value. For this purpose one may apply more recently developed supplementary approaches: (1) Evaluation of main effects and interactions with Decision-Line (DL) criteria; (2) graphic multi-comparative analysis contrasted against the DLs; and (3) estimation of net component of variance for factor and interaction effects. An illustrative case history serves to highlight the more comprehensive overview and better understanding of experiment outcomes thus achieved.

A Monte Carlo approach for the solution of the simple quadratic and cubic self-avoiding random walk

A procedure for virtually memory-free Monte-Carlo simulation of the self-avoiding random walk (SAW) in a two-dimensional network and in a simple cubic lattice has been developed. It is highly efficient in yielding values of the intrachain meansquare end-to-end distance n > for chains up to n = 1000 and n = 400 steps, for the two and three-dimensional cases respectively. The number N of walks per each chain of n steps involved n = 500 to N = 3000.Accessing a medium-sized computer via a portable terminal, it was possible to obtain values for n up to 21, with N up to 1000, in minutes, and to obtain values for n up to 400 and 1000 with N up to 300 in approximately an hour of computing time.The principal finding is that for n > = anγ, the value of the exponent remains stable at approximately 6/5, consistent with the results of prior work involving complete enumeration for n up to 16 and n up to 10 in the two-dimensional and three-dimensional cases. No comparative data are available for higher levels of n because of the time constraints of memory-dependent computer programs.

Planned Production Experiments for Cost and Energy Savings

The major portion of the anticipated 4.5 percent increase in industrial capital spending, forecast for this year, will be spent on energy saving installations. Manufacturers expect a very short pay-back period for this investment. Often, however, they overlook the more ready sources of savings obtainable from effective quality control and planned production experimentation.

Developing a cost-effective marketing information system

Management needs properly compiled, analyzed and evaluated data as a basis for planning, decision-making and control in sales and marketing operations. The cost-effectiveness of the various activities can then serve as a guide to future allocation of effort. The types of data available for comparative analysis of sales and marketing performance are reviewed and classified. The information may be used to justify costs, judge the degree of success attained from various operations, and, wherever applicable, isolate problem areas. Two case-history type examples are presented. The first of these compares customer loss rates with customer gains, and by how much losses must be offset just to keep current total sales even, before growth can be achieved. By categorizing and classifying these types of data by type of customer and type of product, management will isolate specific areas where problems exist and require attention and remedial action. Another example, applicable in a parallel manner by customer and product type, shows how accumulated information can be used to determine the optimal time allocation for individual sales visits, based on curvilinear statistical relationships. The desirability for graphic-comparative presentation of analysis results is emphasized, and is illustrated for the case histories presented.

The matrix approach to market analysis

Assessment of current and future market development is enhanced by systematic review, analysis and evaluation of accumulated records. The information matrix provides such an approach. Its primary purpose is to present past data, current experience and projections for the future. An illustrative example shows how this method works for data analysis by product and market area for sales volume, contribution to profit and overhead, and the costs of production, marketing and distribution. The development and evaluations of projections is facilitated by means of the matrix approach.

A logic system for the choice of risk levels in hypothesis testing

We have examined current, traditional practice of establishing risk levels, favoring use of small α and implicitly accepting correspondingly larger β errors. There are both loses and gains associated with this approach. In particular, small a minimizes the probability of erroneously rejecting Ho, but it also increases the chances that a new model, representing a real improvement, may be discarded. There is no overwhelming logic that one type of error is always more important than the other, since relative costs vary with the conditions surrounding the research investigation.

Coping with sales decay: Case and techniques

Multi-product manufacturers of consumer goods find for most of their items that, at some point in the marketing cycle, sales have peaked. The decline that follows will normally proceed along an approximately stable rate described by the particular decay constant applicable. Often, action to alter or even reverse declining trends may be feasible and desirable. But in order to be aware of these meeds, to know when and how strongly to proceed, one must understand the nature of decay rates, be able to analyze decay patterns, and set up effective surveillance controls. The problem or recognizing and dealing with sales decay is explored with the aid of a case.