bluuebunny/crossref_metadata_2025 huggingface dataset:
Profit Maximizing Perceptual Positions: An Integrated Theory for the Selection of Product Features and Price
Authors: Hauser John R. , Simmie Patricia
Published: November 2008

An important component of marketing strategy is to “position” a product in perceptual space. But to realize a perceptual position we must model the link from physical characteristics to perceptual dimensions and we must use this model to maximize profit. This paper integrates psychological theories on how consumers process information with economic models and psychometric measurement, and it develops a theory for selecting physical features and price to achieve a profit maximizing perceptual position.

The theory begins with a Lancaster-like transformation from goods space to characteristics space and investigates the implications of a mapping to a third space, perceptual space. We show that all products efficient in perceptual space must be efficient in characteristics space but not conversely. But consumers vary in their preference and the way they perceive products. Thus we introduce distributional components to the theory and derive both geometric and analytic methods to incorporate this consumer heterogeneity. Next, we investigate costs and derive a perceptual expansion path along which a profit maximizing position must exist. Conjoint analysis and quantal choice models provide the measurements to implement the theory.

The theory is illustrated with a hypothetical example from the analgesics market and some of the potential psychometric measurements are illustrated with an empirical application in the communications market.
The Determinants of Information Value: Synthesizing Some General Results
Authors: Hilton Ronald W.
Published: November 2008

This paper identifies the determinants of information value and synthesizes some general results concerning their effects. While some attributes of an information system exhibit a consistent directional effect on information value, attributes of the decision setting and decision maker do not.
Applying Classical Control Theory to Energy-Economics Modeling—A Tool to Explain Model Behavior in Response to Varied Policy Decisions and Changing Inputs
Authors: Mar B. W. , Bakken O. A.
Published: November 2008

Classical control theory is applied to the field of energy-economics using the Dartmount model COAL as an illustration. Control theory can assist in establishing the credibility of existing energy-economic systems models, since it presents a better understanding of model response. The application of these models requires a translation of DYNAMO type conventions into differential equations and flow diagram usually used for control system analysis. The response of the model to parameter changes and model inputs can become routine analyses using classical control theory methodology. In the case of the COAL model it was shown that the model output does not experience detectable oscillations even when input oscillations are introduced. The model as formulated represents a well damped system, which may not be what the authors expected in their representation of the real system.
A Hybrid Method for the Solution of Some Multi-Commodity Spatial Equilibrium Problems
Authors: Pang Jong-Shi
Published: November 2008

This paper describes a hybrid method for solving the multi-commodity transportation and transshipment spatial equilibrium models. The method is basically a specialization of the block successive overrelaxation method for solving a linear complementarity problem with certain block structure and consists of solving a sequence of subproblems of the single-commodity type. These subproblems are solved by a special-purpose principal pivoting algorithm developed in an earlier paper. Under some mild conditions, convergence of the proposed method is established. Finally, computational experience of solving some fairly large randomly generated problems by the proposed hybrid method is presented.
Strategic Control of Corporate Development Under Ambiguous Circumstances
Authors: Ruefli Timothy , Sarrazin Jacques
Published: November 2008

The theory of corporate strategic decision-making has traditionally been dominated by a planning orientation. The corporation was assumed to have reliable information and few strategic constraints over its development horizon. While this approach may have been relevant during the 1950's and 1960's, the emergence of public interest groups and increased activities of government agencies in the 1970's and 1980's has constrained corporate influence and has increased the ambiguity in the environment for strategic decisions. This state of affairs has been noted in a general manner by practitioners and some theorists. This paper, after reviewing various approaches to strategic decision-making, develops an analytic model that places corporate development in a control framework. In this new approach managers are not required to set precise long-range goals nor is the information required expected to be as reliable in the long run as it is in the short run, nor equally reliable across all dimensions of decision-making. The strategic control approach links a relatively ambiguous long-range environment to a more certain short run environment through the concept of a mid-range corporate development window. Planning per se is then a short-range process directed, not at precise long-range goals, but rather at a mid-range performance window the attainment of which will position the corporation so that it will have a high probability of reaching the loosely defined set of long-range goals. Strategic control is a new framework for assessing the theory and guiding the practice of strategic decision making for corporate development.
A Parametric Representation of Additive Value Functions
Authors: Keelin Thomas W.
Published: November 2008

This paper introduces a new parameter for measuring deterministic preference tradeoffs between pairs of attributes. In terms of this parameter, necessary and sufficient conditions for a value function to be additive are established. When additivity conditions are satisfied, a set of these parameters is shown to characterize the value function uniquely up to a set of scaling constants. Implications for assessment, for transforming a nonadditive representation into an additive one, and for multiattribute utility functions are presented.
Multiple Unit Dispatches in Emergency Services: Models to Estimate System Performance
Authors: Chelst Kenneth R. , Barlach Ziv
Published: November 2008

One emergency service system model that has undergone extensive development and testing is the hypercube queuing model and its approximate analog, which were developed by Larson. The model estimates key system performance measures, such as individual unit workloads and travel times. One limitation of this model, as well as other probabilistic deployment models, is that they assume only a single unit is dispatched to each call. In the police environment, if two officers are assigned to each unit, this assumption is generally valid. However, most fire services dispatch multiple vehicles to a serious fire, and in police departments with one-officer units, a second unit will be sent to all potentially dangerous calls.

The need for a new model goes beyond an interest in more accurately estimating standard performance measures when multiple units are dispatched. New models are required to predict new performance measures that are relevant only when multiple units are dispatched. For example, what are the paired travel times of the first- and second-arriving units at an emergency? How long will the first unit be exposed at a potentially dangerous situation until a backup unit arrives? Which unit most frequently arrives first at calls requiring multiple units?

In this paper we build on Larson's work and present two models, one exact, the other, approximate, which can capture the simultaneous response of two identical units dispatched to a single call. We present an example from the police context to illustrate both models and compare the speed and accuracy of the approximate model to the exact one. The workload and travel time estimates of both models differ on the average by only two percent. We conclude our presentation with a brief discussion of model extensions with a focus on the analysis of a merger of police, fire and emergency medical services into a public safety service.
Optimal Testing Procedures for Special Structures of Coherent Systems
Authors: Ben-Dov Yosi
Published: November 2008

Consider the problem of minimizing the expected cost of identifying the state of a coherent system (as “functioning” or “failed”). The system is composed of components (that either fail or work), and only individual components can be tested. Efficient algorithms are presented for some special cases of coherent systems: parallel-series, series-parallel and k-out-of-n systems. Examples are given to demonstrate the algorithms.
Efficiency of the Market for Racetrack Betting
Authors: Hausch Donald B. , Ziemba William T. , Rubinstein Mark
Published: November 2008

Many racetrack bettors have systems. Since the track is a market similar in many ways to the stock market one would expect that the basic strategies would be either fundamental or technical in nature. Fundamental strategies utilize past data available from racing forms, special sources, etc. to “handicap” races. The investor then wagers on one or more horses whose probability of winning exceeds that determined by the odds by an amount sufficient to overcome the track take. Technical systems require less information and only utilize current betting data. They attempt to find inefficiencies in the “market” and bet on such “overlays” when they have positive expected value. Previous studies and our data confirm that for win bets these inefficiencies, which exist for underbet favorites and overbet longshots, are not sufficiently great to result in positive profits. This paper describes a technical system for place and show betting for which it appears to be possible to make substantial positive profits and thus to demonstrate market inefficiency in a weak form sense. Estimated theoretical probabilities of all possible finishes are compared with the actual amounts bet to determine profitable betting situations. Since the amount bet influences the odds and theory suggests that to maximize long run growth a logarithmic utility function is appropriate the resulting model is a nonlinear program. Side calculations generally reduce the number of possible bets in any one race to three or less hence the actual optimization is quite simple. The system was tested on data from Santa Anita and Exhibition Park using exact and approximate solutions (that make the system operational at the track given the limited time available for placing bets) and found to produce substantial positive profits. A model is developed to demonstrate that the profits are not due to chance but rather to proper identification of market inefficiencies.
Minimizing Variation of Flow Time in Single Machine Systems
Authors: Kanet John J.
Published: November 2008

This paper addresses the problem of n jobs to be scheduled on a single machine in such a way that flow time variation is minimized. When the measure of variation is total absolute difference of completion times (TADC) the problem is shown to be quite simple. Sufficient conditions are shown for minimal TADC and a simple method for generating an optimal solution is provided.

When the measure of variation is variance of flow time the problem is much more difficult. For this case a heuristic method for scheduling is proposed. The heuristic is simple and provides solutions which compare favorably with others found in the literature.
Note—Comments on the Complexity Rating Factor for Layout Problems
Authors: Gupta Rajiv M. , Deisenroth Michael P.
Published: November 2008

In a recently published Note, Block (Block, T. E. 1979. On the complexity of facilities layout problems. Management Sci. 25 (3) 280–285.) attempted to provide a definitive method to evaluate the complexity of facilities layout problems. He proposed a complexity rating factor that is based on flow dominance and the number of facilities. Mathematically, the rating factor suffers from the use of an incorrect upper bound for flow dominance. Also, there is a problem with regard to its interpretability. These shortcomings are discussed in this Note. The sensitivities of flow dominance and the rating factor to changes in a single element of the flow matrix are examined and their implications discussed.
Forecasting and Planning: An Evaluation
Authors: Hogarth Robin M. , Makridakis Spyros
Published: November 2008

The formal practice of forecasting and planning (F&P) has risen to prominence within a few decades and now receives considerable attention from both academics and practitioners. This paper explicitly recognizes the nature of F&P as future-oriented decision making activities and, as such, their dependence upon judgmental inputs. A review of the extensive psychological literature on human judgmental abilities is provided from this perspective. It is argued that many of the numerous information processing limitations and biases revealed in this literature apply to tasks performed in F&P. In particular, the “illusion of control,” accumulation of redundant information, failure to seek possible disconfirming evidence, and overconfidence in judgment are liable to induce serious errors in F&P. In addition, insufficient attention has been given to the implications of numerous studies that show that the predictive judgment of humans is frequently less accurate than that of simple quantitative models. Applied studies of F&P are also reviewed and shown to mirror many of the findings from psychology. The paper subsequently draws implications from these reviews and suggests reconceptualizing F&P through use of decision-theoretic concepts. At the organizational level this involves recognizing that F&P may perform many, often conflicting, manifest and latent functions which should be identified and evaluated through a multi-attribute utility framework. Operationally, greater use should be made of sensitivity analysis and the concept of the value of information.
Note—Prediction Intervals for Warranty Reserves and Cash Flows
Authors: Patankar Jayprakash G. , Worm George H.
Published: November 2008

This paper presents estimates of cash flows associated with a given warranty policy. Included in the results are prediction intervals for warranty reserves and cash flows. A numerical example is given to illustrate these results.
A Decision Process Model of R&D Resource Allocation in Hierarchical Organizations
Authors: Winkofsky E. P. , Baker N. R. , Sweeney D. J.
Published: November 2008

A mathematical model is presented which incorporates many descriptive characteristics of decentralized R&D resource allocation processes. In general it is a member of the class of models referred to as decision process models. In specific it is representative of an R&D resource allocation process involving a number of subunits at three hierarchical levels. An important feature is the model's ability to represent a number of different interlevel information and organizational coordination mechanisms relating subordinate to ordinate and ordinate to superordinate. A series of 0–1 goal programs with preemptive priority factors provide models for each of the subunits. The subunit models are linked through very general information flows. R&D project or portfolio characteristics are passed upward; while R&D goals and/or budgets and associated levels are passed downward. The eventual purpose of this research is to construct a simulator capability suitable for experimentation concerning coordination in a decentralized resource allocation process involving R&D projects. Such a capability would be an important tool for analyzing existing or proposed decision processes and would be useful for policy analysis at the level of both the firm and the federal government. An illustrative experiment is discussed.
The Marketing Channel as an Equilibrium Set of Contracts
Authors: Zusman Pinhas , Etgar Michael
Published: November 2008

Nash bargaining theory and recent developments in economic contract theory are employed in the analysis of the marketing channels. Individual dyadic contracts involving payment schedules between members of a simple 3 level channel are investigated with particular reference to monitoring problems and intrachannel power relations. The interrelations between individual contracts are examined and the equilibrium set of contracts constituting the channel derived. The performance of the channel in terms of risk sharing, allocative efficiency and the distribution of gains is then evaluated. It is found that the risk aversion of channel members and the cost of monitoring and enforcement affect channel efficiency, and that under certain types of interdependencies and externalities, the nature of the power structure is crucial to channel efficiency.
A Perspective on the Use of Control Variables to Increase the Efficiency of Monte Carlo Simulations
Authors: Lavenberg S. S. , Welch P. D.
Published: November 2008

This is a survey paper on the application of control variables to increase the efficiency of discrete event simulations. The emphasis is on the practical problems and potential of applying the method in the simulation of complex systems. The basic theory of control variables is reviewed and the equivalence of control variables and multiple estimators is discussed. Techniques for generating control variables are described. Inefficiencies resulting from the statistical estimation of control variable coefficients and the problem of confidence interval generation are treated. This is done both within the context of the method of independent replications and the regenerative method. The application literature is reviewed and the conditions under which control variables could be profitably applied in practical simulations are described. Finally, there is a set of recommended directions for future research.
A Survey of Methods for Pure Nonlinear Integer Programming
Authors: Cooper Mary W.
Published: November 2008

The subject of this paper is a classification and discussion of algorithms for solution of nonlinear pure integer programming problems. The survey is organized by characterizing the mathematical form of the nonlinear optimization problems addressed by the various algorithms. If any method can be used without changes to solve mixed integer nonlinear programming problems that fact is mentioned in the description of the algorithm. However algorithms which must be applied only to mixed integer problems are not surveyed.
A Linear Goal Programming Model for Developing Economies with an Illustration from the Agricultural Sector in Egypt
Authors: Bazaraa Mokhtar S. , Bouzaher Aziz
Published: November 2008

In this study we formulate a multi-regional single time period linear goal programming model for agricultural planning in a developing economy. In addition to specifying different levels of input and output for each activity, we describe explicit crop interdependencies which account for rotational requirements. Constraints are developed for land, labor, water, machinery, fertilizer, and capital resources. Economic aspects are addressed through the use of different production functions and the incorporation of several objectives. This last point marks a departure from conventional models which stress maximization of “economic welfare” defined as efficiency through maximum social product without consideration for income distribution. The emphasis on income distribution is reflected in our model in delineation of regional employment goals. In addition, foreign exchange expenditures and regional demand satisfaction goals reflect the importance of limiting foreign trade deficit and providing basic nutrition for the population. The decisions suggested by the solution include acreage allocated to different crops, sequences of crop rotations, fertilization levels, and transportation and distribution of crops and livestock among the regions. We illustrate the model using data from the agricultural regions with three cropping seasons: winter, summer, and nili (autumn). The activities covered by the model consist of ten winter crops, seven summer crops, three nili crops, two permanent crops, two pasture types, four livestock types, and three types of fertilizers. The crops are modeled in sequences to minimize the detrimental effects of cotton. The results suggested by the model show the need for using improved farming techniques through labor-intensive means to obtain a relatively higher degree of specialization and a relatively lower cotton production. This latter conclusion confirms that reached by an independent study of the U.S. Agency for International Development and the Ministry of Agriculture in Egypt. Several computer runs are conducted to test sensitivity of the results to major assumptions and goal targets. It is felt that the model presented in this study would be useful to management scientists, agricultural planners, especially those in developing countries, and to various United Nations organizations such as the International Bank for Reconstruction and Development.
Portfolio Optimization Models for Property-Liability Insurance Companies: An Analysis and Some Extensions
Authors: Cummins J. David , Nye David J.
Published: November 2008

This paper presents a model to assist property-liability insurance companies in making product and investment mix decisions. A quadratic programming approach is used to generate mean-variance efficient frontiers that reflect the covariability of returns on insurance lines and assets. The solution indicates the overall premium-to-surplus ratio, the distribution of premiums among insurance lines, and the proportion of assets in each major investment class that are consistent with the minimum level of risk for a given expected rate of return on net worth. Recognition is given to the tendency for some insurance lines to generate more investable funds than others due to longer lags between claim occurrence and settlement. The importance of federal income taxes in insurance company decision making is recognized, and a method is suggested for including taxes in the model.

The traditional model for selecting insurance company operating strategies is safety-first decision making (ruin theory). More recently, utility theory has been suggested as an alternative approach. This paper discusses the linkages between ruin theory and utility theory and indicates how these decision rules can be used to select operating points along the efficient frontier. A numerical example is given based on the published financial data of a major insurance company to illustrate the development of an efficient frontier and the use of ruin and utility-based decision rules. The results indicate that these decision rules generally lead to different operating strategies and that efficiency can be improved using the quadratic programming approach.
Disaggregation and Resource Allocation Using Convex Knapsack Problems with Bounded Variables
Authors: Bitran Gabriel R. , Hax Arnoldo C.
Published: November 2008

The allocation of a specific amount of a given resource among competitive alternatives can often be modelled as a knapsack problem. This model formulation is extremely efficient because it allows convex cost representation with bounded variables to be solved without great computational efforts. Practical applications of this problem abound in the fields of operations management, finance, manpower planning, marketing, etc. In particular, knapsack problems emerge in hierarchical planning systems when a first level of decisions need to be further allocated among specific activities which have been previously treated in an aggregate way.

In this paper we provide a recursive procedure to solve such problems. The method differs from classical optimization algorithms of convex programming in that it determines at each iteration the optimal value of at least one variable. Applications and computational results are presented.
Combining Probability Distributions from Dependent Information Sources
Authors: Winkler Robert L.
Published: November 2008

Inferences or decisions in the face of uncertainty should be based on all available information. Thus, when probability distributions for an uncertain quantity are obtained from experts, models, or other information sources, these distributions should be combined to form a single consensus distribution upon which inferences and decisions can be based. An important feature of information from different sources is the possibility of stochastic dependence, and a consensus model which formally allows for such dependence is developed in this paper. Under normality, the model yields reasonably tractable results, and the consensus distribution is quite sensitive to the degree of dependence.
Bayesian Estimation and Control of Detailing Effort in a Repeat Purchase Diffusion Environment
Authors: Lilien Gary L. , Rao Ambar G. , Kalish Shlomo
Published: November 2008

This paper develops a model and an associated estimation procedure to forecast and control the rate of sales for a new product. A repeat-purchase diffusion model is developed, incorporating the effect of marketing variables—detailing force effects in particular—as well as a word-of-mouth effect. Bayesian estimation, with priors developed from past products is used to estimate and update the parameters of the model. The procedure is used to develop marketing policies for new product introduction.
Bed Allocation in a Public Health Care Delivery System
Authors: Kao Edward P. C. , Tung Grace G.
Published: November 2008

Due to changing patient loads and demand patterns over time, assigning bed complements for various medical services in a hospital is a recurring problem facing the administrators. For a large public health care delivery system, we present an approach for periodically reallocating beds to services to minimize the expected overflows. Using a queueing model to approximate the patient population dynamics for each service—with admission rates provided by forecasts—the expected overflows under each configuration are computed via a Normal loss integral. Bed allocation is done in two stages. First, we establish a base line requirement for each service so that it can handle a prescribed amount of patient load based on a yearly projection of demand. We then use marginal analysis to distribute the remaining beds to minimize the expected total average overflows while taking month-to-month demand fluctuations into account. The proposed model requires only a modest amount of computation, because of several simplifying assumptions, which were tested for reasonableness. For the two largest services, we used empirical data to evaluate the nonhomogeneous Poisson representation of admissions, and we performed simulation experiments to assess the extent of discrepancy in performance characteristics caused by the ignorance of day-of-week effect on admission rates. In view of the intrinsic complexity of the underlying system, the results obtained from the validation studies suggest that the model is relatively "robust" with respect to the case under consideration. It is hoped that the simplicity of the model and the usefulness of the results will induce practitioners to use this type of formal analysis for bed allocation in an institutional setting on a routine basis.
A Branch and Bound Algorithm for the List Selection Problem in Direct Mail Advertising
Authors: Dwyer F. Robert , Evans James R.
Published: November 2008

This paper describes a branch and bound approach for optimizing a media selection problem, namely, to choose the best set of mailing lists to maximize audience reach. Prompted by a national retailer's interest in more effective and efficient direct mail catalogue distribution, the algorithm exploits current heuristic approaches which improve computational efficiency. A numerical example and computational experience using actual data are discussed, along with extensions to other practical situations.
Decision Problems Under Risk and Chance Constrained Programming: Dilemmas in the Transition
Authors: Hogan Andrew J. , Morris James G. , Thompson Howard E.
Published: November 2008

Some important conceptual problems concerning the application of chance constrained programming (CCP) to risky practical decision problems are discussed by comparing CCP to stochastic programming with recourse (SPR). We expand on Garstka's distinction between mathematical equivalence and economic equivalence showing that much of practical usefulness is lost in the transition between SPR and CCP. By examining the literature on CCP applications we conclude that there is little evidence that CCP is used with the care that is necessary. Finally we conclude that CCP is seriously deficient as a modeling technique and of limited value as a computational device.
An Investigation of Competitive Preference Structures and Posterior Performance Through a Bayesian Decision-Theoretic Approach
Authors: Eliashberg Jehoshua
Published: November 2008

In this paper we analyze competitive decision-making situations in terms of their preference structures and posterior performance, through a Bayesian decision-theoretic framework. The setting is that of a two-by-two, two-person, non-zero-sum and noncooperative game which is repeated over time. The dynamic behavior of the competitors for different classes of games, as identified by their preference structures, is examined and a classification scheme is proposed for the purpose of unification. The competitors' dynamic behavior and posterior performance for some general classes of games is then derived, and the relationship to the results implied from game-theoretic considerations is discussed. Illustrative examples are given, too.
A Model for Optimizing Retail Space Allocations
Authors: Corstjens Marcel , Doyle Peter
Published: November 2008

The allocation of scarce shelf space among competing products is a central problem in retailing. Space allocation affects store profitability through both the demand function, where both main and cross space elasticities have to be considered, and through the cost function (procurement, carrying and out-of-stock costs). A model is developed which uniquely incorporates both effects. A case study is used to estimate the parameters and the problem is solved within a geometrical programming framework. An extensive comparison with alternative procedures suggests this general model leads to significantly different allocation rules and superior profit performance.
Note—On a Modified One-Center Model
Authors: Drezner Zvi
Published: November 2008

The objective of the one-center model (single facility minimax location in the plane) is changed to be the maximum weighted number of demand points within a given weighted distance from the facility. The paper presents an O(n2 log n) algorithm for the model along with some computational experience.
Design of a Receivable Collection System: Sequential Building Heuristics
Authors: Stone Bernell K.
Published: November 2008

This paper extends previous work on the use of sequential building heuristics for the design of a collection system, a linear fixed-charge problem that includes the design of a lock-box system as an important subproblem. The heuristic extensions in this paper first present simple methods for eliminating “premature termination” (stopping the heuristics while there are still worthwhile alternatives not included in the collection system) and unprofitable inclusion (including collection alternatives with net benefits less than the fixed cost). Initiation procedures that increase computational efficiency and reduce the likelihood of significant suboptimization are presented. Finally, the simple one-at-a-time building procedure is extended to include joint exclusion-building (a limited switching plus building) and combination switching-building rules that consider combinations of alternatives rather than one-at-a-time evaluation.
A Two Stage Solution Procedure for the Lock Box Location Problem
Authors: Fielitz Bruce D. , White Daniel L.
Published: November 2008

New lock box solution techniques have recently been suggested by Stone and Nauss-Markland. This paper briefly discusses these new methodologies and shows how the algorithms can be combined into a third solution procedure which exploits the computational efficiency of the Stone heuristic and retains the optimizing property of the Nauss-Markland algorithm.
A Stochastic Cutting Stock Procedure: Cutting Rolls of Insulating Tape
Authors: Sculli D.
Published: November 2008

This paper develops a one-dimensional cutting stock procedure which will minimize material wastage when a batch of small pieces are cut from several long pieces. The problem differs from the classical one-dimensional cutting stock problem in that the dimensions of the material to be cut are random variables due to fringe defects caused by the production process. Examples of such processes include the production of flat glass, laminated board, corrugated board, adhesive tape, carpeting, and insulating tape. The cutting procedure inevitably generates some material wastage and process delays caused by the need to set cutting knives in required positions. The approach followed in this paper is to minimize material wastage when cutting a batch of identical rolls of insulating tape from several long rolls with stationary cutting knives. An exact solution is presented for the case in which the variability of defects at both ends is independently distributed and the two distributions differ by a location parameter only. An approximate solution is also presented when the two end defect distributions differ by both scale and location parameters. The wastage resulting from the use of these procedures is then compared with the wastage generated when the positioning of the knives is altered every time an original piece is cut. This comparison enables management to decide when the positioning of the cutting knives should be fixed.
Note—On the Aggregation of Individual Probability Estimates
Authors: Bordley Robert F. , Wolff Ronald W.
Published: November 2008

This Note considers the problem of aggregating individual probability estimates of an event to obtain a group estimate. Norman Dalkey has argued that no rigorous theory of probability aggregation is possible for the following reasons:

(1) There is no consistent way of aggregating individual probability estimates (Dalkey's Impossibility Theorem).

But Dalkey's Impossibility Theorem makes what we call the context-free assumption, namely that the group estimate of an event's probability is a function only of the estimates of the individuals and, in particular, is not dependent on the event in question. We argue that the context-free assumption is unreasonable and present several known aggregation methods which don't make it.

(2) Although there is a Bayesian approach to the problem, it requires that the estimates of all but at most one of the experts be independent of the event in question.

To make this argument, Dalkey assumed both:

a1: The individual estimates are independent random variables, and

a2: Given the occurrence or nonoccurrence of the event, the individual estimates are independent random variables.

This paper presents an alternate derivation of the result, abstracting from Dalkey's context. The point is that Dalkey's result is simply a consequence of assuming both a1 and a2. It is unreasonable to assume both a1 and a2. And hence Dalkey's result does not discredit the Bayesian approach.

Thus this paper resolves some theoretical objections to the possibility of a rigorous theory of aggregation. Furthermore, it clarifies the nature of the context-free assumption and the independence assumptions: a1 and a2.
Note—On the Relationship of Adaptive Filtering Forecasting Models to Simple Brown Smoothing
Authors: Bretschneider Stuart I. , Gorr Wilpen L.
Published: November 2008

This Note establishes two linkages between adaptive estimation procedures used in the analysis and forecasting of multivariate time series and the simple Brown smoothing technique. First, for a simple model it is shown that AEP and LMS are identical to the Brown technique. Thus they are accorded the theoretical properties possessed by the Brown estimator for the simple model. This linkage establishes that the Brown technique has been extended in two complementary directions: to higher order smoothing models which use explicit functions of time and implicitly include effects of other variables and to adaptive time-varying parameter models which explicitly include the influences of other variables and implicitly incorporate time. Second, for the same simple model, Stochastic Approximation, Kalman Filtering, and Bayesian Analysis reduce to a form similar to the Brown technique except that they have a time-varying smoothing constant which approaches zero as the sample size grows large. Hence, while they provide optimal estimates which converge in mean square error, they are not responsive to change.
Predicting Future Random Events Based on Past Performance
Authors: Morrison Donald G. , Schmittlein David C.
Published: November 2008

There are many situations where one is interested in predicting the expected number of events in period 2 given that x events occurred in period 1. For example, insurance companies must decide whether or not to cancel the insurance of drivers who had 3 or more accidents during the previous year. In analyzing marketing research data an analyst may wish to predict the number of future purchases to be made by those customers who made x purchases in the previous 3 months. The owner of a baseball team may wish to estimate the number of home runs a batter will hit this year given he hit (say) 40 home runs last year. When the events (e.g., accidents, purchase occasions, home runs) can be assumed to occur randomly over time a very general result due to Robbins (Robbins, H. 1977. Prediction and estimation for the compound Poisson distribution. Proc. National Acad Sci. USA 74 2670–2671.) is available. This approach has certain advantages and disadvantages with respect to the negative binomial model that is commonly used to analyze purchasing and accident data. The Robbins result is particularly appropriate for predicting what the zero class in period 1 will do in period 2. The main purpose of this paper is to present the Robbins result in a form that can be readily understood by applied researchers in a variety of disciplines. Data on consumer purchases, motor vehicle violations and accidents are analyzed and applications to other areas are discussed.
Multiple Objective Linear Fractional Programming
Authors: Kornbluth Jonathan S. H. , Steuer Ralph E.
Published: November 2008

This paper presents a simplex-based solution procedure for the multiple objective linear fractional programming problem. By (1) departing slightly from the traditional notion of efficiency and (2) augmenting the feasible region as in goal programming, the solution procedure solves for all weakly efficient vertices of the augmented feasible region. The article discusses the difficulties that must be addressed in multiple objective linear fractional programming and motivates the solution algorithm that is developed.
Expectations and Share Prices
Authors: Elton Edwin J. , Gruber Martin J. , Gultekin Mustafa
Published: November 2008

It is generally believed that security prices are determined by expectations concerning firm and economic variables. Despite this belief there is very little research examining expectational data. In this paper we examine how expectations concerning earning per share effect share price. We first show that knowledge concerning analyst's forecasts of earnings per share cannot by itself lead to excess returns. Any information contained in the consensus estimate of earnings per share is already included in share price. Investors or managers who buy high growth stocks where high growth is determined by consensus beliefs should not earn an excess return. This is not due to earnings having no effect upon share price since knowledge of actual earnings leads to excess return. Much larger excess returns are earned if one is able to determine those stocks for which analysts most underestimate return. Finally, the largest returns can be earned by knowing which stocks for which analysts will make the greatest revision in their estimates. This pattern of results suggests that share price is affected by expectations about earnings per share. Given any degree of forecasting ability managers can obtain best results by acting on the differences between their forecasts and concensus forecasts.
Note—Some Equivalent Objectives for Dynamic Network Flow Problems
Authors: Jarvis John J. , Ratliff H. Donald
Published: November 2008

Many important problems can be modeled as dynamic (time-expanded) network flow problems. For example, in building evacuation we might use twenty nodes to represent a room at 3 minute intervals over an hour, and use arcs to indicate the feasible passages, over time, among the various rooms. The purpose of this note is to demonstrate that it is possible to satisfy at least three important objectives simultaneously in a maximal dynamic network flow problem. These are (1) construction of an earliest arrival schedule (i.e., a solution which maximizes flow in the first p periods, for every p), (2) minimization of the period at which the last unit of flow arrives at the sink, and (3) minimization of the average time for all flow to arrive at the sink.
An Experimental Study of the Impact of Judgment-Based Marketing Models
Authors: McIntyre Shelby H.
Published: November 2008

The impact of a decision calculus model on decision quality is assessed in a laboratory setting. An experimental design assesses the effects of: (a) the size of the problem (i.e., the number of control units over which allocations are to be made), (b) the noise-to-signal ratio in the market and (c) individual differences among the model users. The aspects of individual differences studied are: (1) time taken on the task, (2) mathematical ability and (3) cognitive style. The main experiment involved 96 subjects in a full factorial design. In general, the decision calculus model had a beneficial impact on a broad range of decision quality measures, particularly profit achievement.
The Multiple-Choice Nested Knapsack Model
Authors: Armstrong Ronald D. , Sinha Prabhakant , Zoltners Andris A.
Published: November 2008

A specially-structured integer programming model, called the multiple-choice nested knapsack model, is developed in this paper. The model is characterized by variables which are partitioned into multiple-choice sets and resource constraints which are nested across the multiple-choice sets. The application of the model in the areas of merchandise catalog planning and sales resource allocation is described. An algorithm for the model is presented and the results of the computational testing of the algorithm are provided.
Improved Heuristics for Multi-Stage Requirements Planning Systems
Authors: Blackburn Joseph D. , Millen Robert A.
Published: November 2008

Most of the recent studies of heuristic lot-sizing techniques for multi-stage material requirements planning systems have investigated the problem in the context of a single stage. In this paper, the multi-stage problem is first modeled analytically to indicate the potential errors inherent in the commonly proposed single-pass, stage-by-stage approaches (e.g., Wagner-Whitin). Then, based on this analysis, several simple cost modifications are suggested to improve the global optimality of these procedures. The effectiveness of these alternative modifications is tested through a series of simulation experiments. It is concluded that some of these modifications consistently improve the performance of the stage-by-stage approaches.
Network Models for Building Evacuation
Authors: Chalmet L. G. , Francis R. L. , Saunders P. B.
Published: November 2008

How can a large building with many occupants be evacuated in minimum time, and where are bottlenecks likely to occur in such an evacuation? In order to address this question we have constructed a family of three network building evacuation models. The most general model of interest, called the dynamic model, represents the evacuation of a building as it evolves over time, where time is represented discretely by consecutive time periods. The dynamic model triply optimizes in the sense that while directly minimizing the average over the occupants of the number of periods each needs to exit the building, it simultaneously maximizes the total number of people evacuating the building during periods 1 through p for all values of p, and also minimizes the time period in which the last evacuee exits the building. Coincident with the triple optimization, each arc dual variable indicates whether or not the building component the arc represents is a bottleneck in any period during the evacuation.

The other two models in the family, referred to as the graphical model and the intermediate model, are smaller in scope than the dynamic model (they treat time as a parameter and are not time-dependent) but are easier to use, and offer alternative approaches which can provide some of the same insights as the dynamic model.

We model the evacuation of an actual eleven floor building with 323 people, four elevators, and two stairwells, and compare model results with results of an observed building evacuation.

We believe our models provide useful new tools for the analysis of building evacuability, and have the potential to facilitate the study of the interrelationships with building design, building redesign, and building evacuability.
A Multiplicative Formula for Aggregating Probability Assessments
Authors: Bordley Robert F.
Published: November 2008

This paper presents an axiomatic approach to the problem of aggregating expert assessments of an event's probability into some group probability assessment. A multiplicative formula is derived.
Computational Complexity of the Capacitated Lot Size Problem
Authors: Bitran Gabriel R. , Yanasse Horacio H.
Published: November 2008

In this paper we study the computational complexity of the capacitated lot size problem with a particular cost structure that is likely to be used in practical settings. For the single item case new properties are introduced, classes of problems solvable by polynomial time algorithms are identified, and efficient solution procedures are given. We show that special classes are NP-hard, and that the problem with two items and independent setups is NP-hard under conditions similar to those where the single item problem is easy. Topics for further research are discussed in the last section.
Group Confidence Pressures in Iterative Decisions
Authors: Boje David M. , Murnighan J. Keith
Published: November 2008

This study investigated the effects of two group decision making techniques on a set of four problems in groups of sizes 3, 7, and 11. Participants included 192 male and 132 female undergraduates. Estimates that could be evaluated for accuracy for each of the problems were collected for a series of three trials. One set of groups received face-to-face verbal feedback from each other, while the other set received written feedback. These data were compared to mean estimates obtained from randomly selected, pooled individual estimates. The results suggested that the pooled individual estimates were somewhat more accurate than those obtained from either of the interacting groups. At the same time, all individuals became more confident of their answers, suggesting the possibility of groupthink. No effects for different group sizes were found, possibly due to the constraints imposed by the structured nature of the two techniques.