bluuebunny/crossref_metadata_2025_split huggingface dataset:
OPTIMAL ALLOCATIONS OF JOINT (COMMON) COSTS: A PARAMETRIC PROGRAMMING APPROACH
Authors: Jensen Robert E. 
Published: June 2007

AbstractA parametric programming model for allocating joint costs is described and illustrated. Given M mutually exclusive missions and P alternative systems for accomplishing such missions, the model first determines the optimal choice of systems for all missions simultaneously. It then allocates both joint and separable costs such that no mission receives a greater cost allocation than any other mission alternative that might be suboptimal for the mission but nonoptimal when all missions are simultaneously considered. Although the model initially assumes a mission priority ranking, this assumption is relaxed later on as alternative rankings are evaluated and cost allocation ranges under all priority rankings are evaluated.
THE EFFECT OF MASCULINE AND FEMININE BRAND NAMES ON THE PERCEIVED TASTE OF A CIGARETTE *
Authors: Friedman Hershey H. , Dipple William S. 
Published: June 2007

AbstractThe purpose of the current study was to determine whether brand name can affect the public's evaluation of a product. All subjects smoked identical cigarettes. One group of subjects, however, knew the cigarettes by the name of “Frontiersman,” a masculine name, while the other group knew the cigarettes as “April,” a feminine name. Male and female subjects were asked to rate the cigarette on seven measures. Results show that women gave a more positive evaluation to the cigarette purportedly named “April,” while men gave a more positive evaluation to the identical cigarette when they thought it was named “Frontiersman.” In addition, women reacted more strongly than did men to brand name influence.
OPTIMIZATION THROUGH EXPERIMENTATION: APPLYING RESPONSE SURFACE METHODOLOGY
Authors: Brightman Harvey J. 
Published: June 2007

AbstractThe crucial steps in a quantitative analysis of a decision problem are problem formulation, model building, analysis, and implementation. Given an initial model specification, the goal of analysis is to determine the values of the controllable or decision variables that optimize the objective function. Frequently the initial model is inadequate and must be reformulated. While modeling is an evolutionary process involving art and science, under certain conditions Response Surface Methodology (RSM) is an effective vehicle for constructing and parameterizing optimization models. RSM, which draws upon the areas of experimental design, modeling, inference, and optimization, utilizes different opening and ending strategies. Through simultaneous and sequential experimentation, the approximate region of the model's maximum response is found by employing the steepest ascent method. Subsequently, the exact values of the controllable variables that maximize the model's response are determined by canonical analysis. The RSM concepts are first developed within the context of a manufacturing problem. A potential application to simulation studies is then presented.
USING MANAGEMENT GAMES AS AN AID IN TEACHING MIS DESIGN
Authors: Courtney James F. , Bierer Julia M. , Luckew Thomas G. , Kabbes John J. 
Published: June 2007

AbstractAs an approach to teaching management information systems, students are required to play a management game. The students become aware of information needs through participation in the decision process of the game. The student then develops an integrated system to assist in playing this management game. This new approach, the gaming method, is considered an effective way of teaching integrated systems because the intimate interrelationships between decision‐making processes and information systems can be easily illustrated.
A SIMPLE PROOF THAT DOLLAR AVERAGING IS A MAXIMIN INVESTMENT STRATEGY
Authors: Whitmore G. A. 
Published: June 2007

AbstractDollar averaging is a strategy for investment timing which hedges against purchases at the market high by investing fixed amounts at regular intervals. This note gives a simple proof that it is a maximin strategy. This result complements Pye's [2] finding that dollar averaging is a minimax regret strategy. In addition to its theoretical value, the result is an excellent classroom illustration of a real‐life application of the maximin criterion.
COST, PRICE, AND THE CONTRACTING RELATION: A CASE STUDY
Authors: Roistacher Richard C. 
Published: June 2007

AbstractThe paper describes the failure of a project in which a group of computer specialists tried to help a group of scholars by automating a conference registration system. Although there was a warm and personal relationship between the group liaisons, difficulties arose because there was no agreed‐on mechanism to allocate priorities and resources. The author analyzes the price and cost mechanisms which might have been used to communicate complex trade‐offs and thus avert the ensuing disaster.
A BAYESIAN ANALYSIS OF MULTIPLICATIVE TREATMENT EFFECTS WHEN TWO INDEPENDENT SAMPLES ARE OBSERVED
Authors: Menzefricke Ulrich 
Published: June 2007

AbstractA Bayesian analysis of multiplicative treatment effects is given for a normally distributed population. The two samples taken, one for each treatment, are used to make inferences on the multiplicative effect. An analysis of the general problem with uneven sample sizes and prior information is rather untractable, which leads to the use of numerical integration methods. A special case for which analytical results are available is discussed. Finally, the method suggested in this paper is compared with an approach utilizing a logarithmic transformation.
SOME TESTS OF BINOMIAL PROBABILITY ASSESSMENTS
Authors: Peters William S. 
Published: June 2007

AbstractA replication of the Alpert‐Raiffa probability assessment experiment is used to motivate the development of several tests for evaluating assessors. The tests permit an evaluation of an assessor's accuracy in estimating target quantities and in estimating his own uncertainty as well.Assumption of normal subjective distributions permits the determination of subjective variances. Data from trial assessments are employed to test models which assert that assessed quantities are equal to subjectively assessed error variances. Several tests of the latter type are compared using data from individual, as well as pooled, assessors.
ANALYZING MODELS WITH MULTIPLE‐OUTCOME VARIABLES *
Authors: Ryan Michael J. 
Published: June 2007

AbstractMultivariate designs have been useful in testing models with more than one output variable. This paper explains the use of the step‐down F statistic, a technique that allows a more refined analysis than does the traditional multivariate or univariate F test by examining sequential interactions among dependent variables in a multiple‐response set. An illustration is presented within the context of a laboratory experiment designed to examine a manipulation effect on a three‐variable causal chain. The example illustrates the misleading interpretation that could result without the information provided by the step‐down statistic.
QUANTITATIVE TECHNIQUES IN MARKETING: AN ASSESSMENT OF TEACHING AND USAGE PATTERNS
Authors: Capella Louis M. , Jain Subhash C. 
Published: June 2007

ABSTRACTThis paper presents the perspectives of quantitative techniques in academics and practice. Based on the findings of an empirical study, the academicians and practitioners emphasize different techniques and prefer different journals for keeping abreast. This reveals the areas for curriculum improvement to orient the program toward the practitioners.
THE USE OF MODERATED REGRESSION IN JOB REDESIGN DECISIONS*
Authors: Peters William S. , Champoux Joseph E. 
Published: June 2007

ABSTRACTThis paper describes the use of moderated regression in job redesign decisions. The procedures outlined are intended to augment the job redesign strategy described by Hackman and his colleagues. Different regression models based on a theory of job design are shown to lead to different job redesign decisions. Comparisons are also made between the moderated regression procedures and the more commonly used subgroups analysis.
INTRODUCING OR/MS INTO ORGANIZATIONS: NORMATIVE IMPLICATIONS OF SELECTED INDIAN EXPERIENCE*
Authors: Mohan Lakshmi , Bean Alden S. 
Published: June 2007

ABSTRACTThere is considerable evidence that firms and institutions that have adopted and utilized operations research and related management sciences (OR/MS) experience severe internal disruptions and changes as the new technology is introduced. In some cases the reactions have been adverse enough to result in temporary rejection of the technology and a period of three to five years has been necessary for reintroduction of OR/MS. Such lags represent lost opportunities with attendant costs that firms and institutions can ill afford. There is obvious need to manage the introduction of OR/MS into organizations to minimize the inevitable resistances to change and to expedite institutional acceptance and practice. This paper presents a normative framework for this purpose based on four case studies of Indian implementation experience. The selected firms, which represent different sectors of industry, adopted different strategies for introduction and diffusion of OR/MS. The authors have noted several points of similarity between the Indian experience and the experience of U.S. organizations which indicate a fair measure of general validity for the proposed normative framework.
DYNAMIC DISAGGREGATE CHOICE MODELS, WITH AN APPLICATION IN TRANSPORTATION
Authors: Krishnan K. S. , Beckmann Martin J. 
Published: June 2007

ABSTRACTA standard assumption of disaggregate mode‐choice models is that an individual faced with a choice among several available alternative transportation modes compares their utilities. These utilities are almost always expressed as a linear composite measure of various perceived benefits which are assumed constant. However, the individual's perceptions change as he learns, acquires new habits, or adapts to different physical, economic, and social circumstances. In order to account for these changes, two dynamic models of model‐choice behavior are developed herein. These two models are based on two common postulates. (1) One alternative is preferred over another only if the absolute difference in their utilities exceeds a positive constant; otherwise, the decision maker is indifferent toward the two alternatives. (2) If an alternative is preferred, it will be chosen with certainty.In the indifference state, the individual is postulated to randomly choose one of the two alternatives (Model 1) or choose the same alternative as was most recently chosen (Model 2). Choice probabilities derived from these two models are shown to differ from those obtained using the conventional logit model. If there is a strong loyalty toward a mode, the logit model underestimates its choice probability when that mode is less attractive than the competing mode. The results are illustrated using numerical examples.
AN OPERATIONAL APPROACH TO THE EVALUATION OF LEASES BY HOSPITALS*
Authors: Ofer Aharon R. 
Published: June 2007

ABSTRACTThe evaluation of the lease versus purchase alternative by not‐for‐profit hospitals presents a problem that stems from the interaction between investment and financial decisions. This paper provides an analytical framework that resolves this issue by neutralizing the impact of the lease contract on the hospital's financial structure and debt capacity. The formulation incorporates the special operating characteristics of not‐for‐profit hospitals: namely, they are not subject to federal income tax, and part of their revenue is generated through cost‐based reimbursement.
A COMPARISON OF DECISION QUALITY UNDER NOMINAL AND INTERACTING CONSENSUS GROUP FORMATS: THE CASE OF THE STRUCTURED PROBLEM*
Authors: Herbert Theodore T. , Yost Edward B. 
Published: June 2007

ABSTRACTThe applicability of the Nominal Grouping Technique (NGT) to a structured problem was investigated. NGT and interacting consensus groups were compared on the criteria of decision quality, utilization of best resource, and improvement in quality over average‐member decision quality. Nominal groups' decisions were significantly (p = .005) better than those of interacting groups on all three criteria. Problems with criteria assessment in unstructured tasks were discussed, as were the implications of the present study for prescriptions for NGT use.
AN ANALYSIS OF THE USEFULNESS OF DISAGGREGATED ACCOUNTING DATA FOR FORECASTS OF CORPORATE PERFORMANCE*
Authors: Barnea Amir , Lakonishok Joseph 
Published: June 2007

AbstractThe purpose of this paper is to derive the conditions under which disaggregated accounting data contribute to more accurate forecasts of corporate performance. A comparison formula is derived and applied to actual data. The results obtained indicate that disaggregated data do not necessarily produce better forecasts of corporate performance than do aggregated data. The paper concludes with implications of the results to some reporting issues.
A BAYESIAN APPROACH TO PLANT‐LOCATION DECISIONS*
Authors: Carroll Thomas M. , Dean Robert D. 
Published: June 2007

AbstractThe paper addresses the problem of plant location in the formal context of decision making under uncertainty and presents a framework employing Bayesian analysis in the collection and assessment of information. As a general model, the Bayesian approach is shown to subsume two practical approaches common to plant‐location literature: satisficing and spatial hierarchy of plant‐site characteristics.
HEURISTIC ALGORITHMS FOR CAPITAL‐BUDGETING DECISIONS IN MULTIDIVISION FIRMS
Authors: Rosenblatt Meir J. , Freeland James R. 
Published: June 2007

AbstractThis paper presents two versions of a heuristic algorithm to solve a model of the capital‐budgeting problem in a decentralized multidivision firm involving no more than two exchanges of information between headquarters and divisions. Headquarters makes an allocation of funds to each division based upon its cash demand and its potential growth rate. Each division determines which projects to accept. Then, an additional iteration is performed to define the solution. More than one thousand examples were simulated resulting in an average relative error of less than one percent.
QUANTITATIVE MEASURES FOR CHARACTERISTICS OF A STATE‐DEPENDENT ASSIGNMENT POLICY
Authors: Halpern Jonathan , Wand Yair 
Published: June 2007

AbstractThe paper presents an analytical description of a state‐dependent assignment policy, where different assignments of attributes to objects are employed under different states. Various considerations, other than optimizing an objective function, present themselves for such cases—for example, the existence of groups of assignees with certain levels of intragroup assignment uniformity, the stability of the policy over states, the presence of a revealed preference ordering of the assignments, and others. An approach towards a quantitative treatment of such features of a state‐dependent assignment policy is discussed, and in particular a uniformity measure is defined and its properties are investigated. Potential uses of the model are suggested for urban emergency services, questionnaire analysis, task allocation, medical diagnosis, and dynamic computer program behavior. Three implementations for questionnaire analysis are reported.
DISTRIBUTIONAL TESTING OF DATA FROM MANUFACTURING PROCESSES
Authors: Jacobs Fredric , Lorek Kenneth S. 
Published: June 2007

AbstractA common characteristic of classical variance investigation models includes the assumptions that the in‐control cost observations from manufacturing processes are independently and normally distributed. The purpose of this paper is to empirically assess the appropriateness of the above assumptions in an accounting setting. Several sets of data generated from manufacturing processes were examined, with the following results. First, normality and independence assumptions appeared to be violated with the daily data. In addition, several transformations commonly employed in the statistics literature did not alter this conclusion. Second, the above assumptions were not violated with the weekly data. It was then demonstrated that these findings will, in general, hold.These results, subject to the inherent limitations of a case study approach, led to the following inferences and recommendations. Using classical statistical techniques and daily data to control a process incurs costs that have been previously overlooked, costs resulting from distributional assumption violations. If these costs exceed the benefits of using daily data, a manager should (1) use classical techniques to monitor weekly data, (2) use Tchebycheff inequalities to monitor daily data, and/or (3) use variance investigation models that more formally incorporate the serial dependencies of daily data.
GOAL PROGRAMMING IN A FUZZY ENVIRONMENT
Authors: Narasimhan Ram 
Published: June 2007

AbstractThis paper illustrates the application of “fuzzy subsets” concepts to goal programming in a fuzzy environment. In contrast to a typical goal‐programming problem, the goals are stated imprecisely when the decision environment is fuzzy. The paper first considers a fuzzy goal‐programming problem with multiple goals having equal weights associated with them. A solution approach based on linear programming is developed. Next, the solution approach is extended to the case where unequal fuzzy weights are associated with multiple goals. Numerical examples are provided for both cases to illustrate the solution procedure.
A STOCHASTIC MULTIATTRIBUTE HEURISTIC MODEL OF INVESTOR CHOICE
Authors: Bernardo John J. , Upton David E. 
Published: June 2007

AbstractMost models of investor behavior consider only two attributes of assets, risk and return, and are deterministic in that only one unique choice is allowed. This paper develops a multiattribute model in which investor choice is described in terms of the probability of various choices occurring. The model is solved by standard linear programming techniques and allows for investor behavior that is not explained by the usual models.
AN INFORMATION PROCESSING PROBE INTO CONJOINT ANALYSIS*
Authors: Olshavsky Richard W. , Acito Franklin 
Published: June 2007

AbstractProtocol analysis was used to identify the actual choice rule used by respondents in a conjoint analysis interview under two different card‐sorting instruction conditions. In both conditions respondents used a noncompensatory rule (conjunctive or lexicographic) andnot the additiverule assumed in many conjoint analysis studies. Predictions based upon either the additive rule or the noncompensatory rule were, however, found to be consistent with preference ranks in a holdout sample. The protocols were further analyzed to provide partial validation of the conjoint weights and to investigate the nature of prediction errors observed in the conjoint analysis.
FUTURE DIRECTIONS FOR DEVELOPING DECISION SUPPORT SYSTEMS*
Authors: Bonczek Robert H. , Holsapple Clyde W. , Whinston Andrew B. 
Published: June 2007

AbstractA formal, generic description of decision support systems is introduced. This description views a decision support system as having three principal components: a language system, a knowledge system, and a problem processing system. Several systems that fit the generic decision support system idea, but are (for the most part) not the customary kinds of systems encountered in business applications, are described. The concepts and techniques employed in these systems can make important contributions to the emergence of more powerful business‐oriented decision support systems.
COST‐VOLUME‐PROFIT ANALYSIS IN STOCHASTIC PROGRAMMING MODELS
Authors: Chen Joyce T. 
Published: June 2007

AbstractThis paper applies mathematical programming to cost‐volume‐profit (CVP) analysis under contribution margin uncertainty. Three CVP probabilistic chance‐constraint models based on various safety‐first criteria for decisions under uncertainty are presented and compared. It is shown that a break‐even segment of the mean‐standard deviation frontier is a set of optimal solutions for the proposed models. An operational parametric quadratic programming (QP) model is constructed, and the efficiency frontier is generated. The procedures for locating an optimal solution on the efficiency frontier are then presented. The recommended QP procedure offers both technical relief from the computational difficulties posed by the probabilistic constraints and a desired flexibility in generating and presenting the relevant information for decisions under uncertainty.
SOME CAUTIONARY NOTES ON THE USE OF CONJOINT MEASUREMENT FOR HUMAN JUDGMENT MODELING*
Authors: Messier William F. , Emery Douglas R. 
Published: June 2007

AbstractConjoint measurement has been suggested as a methodology that might be useful in assisting research concerned with the identification of the structural form of a judge's model. This paper synthesizes the results of some recent research that examined the robustness of this methodology. This research suggests that conjoint measurement has three major weaknesses: (1) certain biases exist when diagnosing model structure, (2) model diagnosis is limited to a small set of potential models, and (3) error substantially compromises conjoint measurement's ability to diagnose model structure. An empirical example that demonstrates some of the difficulties of using this methodology with experimental data is also presented.
ACCOUNTING SYSTEMS: THE RELIABILITY APPROACH TO INTERNAL CONTROL EVALUATION
Authors: Stratton William O. 
Published: June 2007

Recent developments have increased the value to management of objective methodologies for the evaluation of accounting internal control systems (AICS). The Foreign Corrupt Practices Act requires management to assure the accuracy of these systems. The process of evaluation of AICS by both management and external auditors is judgmental in nature. The few attempts at modeling AICS have not been implemented by firms due to the lack of realism, difficulty of modeling behavioral systems, lack of cost effectiveness, and lack of understanding by practitioners. For these reasons, the role of the decision scientist has been limited.The research reported here attempts to demonstrate feasibility of a reliability model. A typical accounting system for raw material purchases is modeled via a simulation routine. The effects of internal control weaknesses on ending dollar balances is determined by performing sensitivity analysis. After summarizing these effects, the reliability model is formulated for the same control system, and the analysis is repeated and the results compared with those obtained in a simulation model.
A NOTE ON THE USE OF SELECTED NONFINANCIAL RATIO VARIABLES TO PREDICT SMALL‐BUSINESS LOAN PERFORMANCE*
Authors: Cowen Scott S. , Page Albert L. 
Published: June 2007

ABSTRACTSmall business loan applications have not been evaluated successfully by traditional methods. This paper explores the possibility of using three types of nonfinancial ratio variables (owner, firm, and loan characteristics) to predict whether a small business will pay off or default its loan. The owner and loan variables were better predictors of loan success than the firm variables.
ON THE IMPLICATIONS OF SPECIFICATION UNCERTAINTY IN FORECASTING*
Authors: Benson P. George , Barry B. 
Published: June 2007

ABSTRACTForecasters typically select a statistical forecasting model from among a set of alternative models. Subsequently, forecasts are generated with the chosen model and reported to management (forecast consumers) as if specification uncertainty did not exist (i.e., as if the chosen model were the “true” model of the forecast variable). In this note, a well‐known Bayesian model‐comparison procedure is used to illustrate some of the ambiguities and distortions of forecasts that do not reflect specification uncertainty. It is shown that a single selected forecasting model (however chosen) will generally misstate measures of forecast risk and lead to point and interval forecasts that are misplaced from a decision‐theoretic point of view.