bluuebunny/crossref_metadata_2025 huggingface dataset:
Determining Optimal Selling Price and Lot Size When the Supplier Offers All‐Unit Quantity Discounts*
Authors: Abad Prakash L.
Published: June 2007

This paper is concerned with finding the optimal price and lot size for a retailer purchasing a product for which the supplier offers all‐unit quantity discounts. Demand for the product is assumed to be a decreasing function of price, and a procedure is developed for finding the optimal price and lot size for a class of demand functions. The procedure then is applied to two common demand functions: (1) the constant price‐elasticity function, and (2) the linear demand function.
A Sequential Selection Problem*
Authors: Kwan Clarence C.Y. , Yuan Yufei
Published: June 2007

In this study we formulate a sequential selection problem. In a setting where a choice sequence among candidates is established for filling a job position, the analysis explicitly takes into account the benefits from the hiring, the risk of rejection of the job offer, and the costs due to delays in filling the position. The proposed solution, which is both intuitive and simple, is able to capture analytically the decision process. We also illustrate the versatility of the analysis by considering several other relevant sequential selection settings.
Composite Forecasting with Dirichlet Priors*
Authors: Bessler David A. , Chamberlain Peter J.
Published: June 2007

In this paper, composite forecasting is considered from a Bayesian perspective. A forecast user combines two or more forecasts of an operationally relevant random variable. We consider the case where outperformance is modeled as a realization from a multinomial process. The user has prior beliefs about the probability that a particular method outperforms all others, information which is summarized by the Dirichlet distribution. An empirical example with hog prices in the United States illustrates the method.
An Experimental Evaluation of Articulation of Preferences in Multiple Criterion Decision‐Making (MCDM) Methods
Authors: Narasimhan Ram , Vickery Shawnee K.
Published: June 2007

This paper describes the results of a study done to determine how well multiple criterion decision‐making methods perform in helping a decision maker arrive at a preferred solution to a multicriterion problem with conflicting objectives. The study used a factorial experiment and doctoral students as subjects. Two competing methods for solving multicriterion problems were compared along with the influence of problem complexity. The methods differed in the way preferences were articulated by decision makers. The results showed that there was no difference between the methods for several performance measures, disaffirming some prior expectations. From an actual use point of view, the study suggests that methodological improvements to existing techniques must be matched by efforts to improve information presentation and interpretation to facilitate preference judgments.
Supplier/Customer Inventory Relationships Under Just In Time
Authors: Chapman Stephen N. , Carter Phillip L.
Published: June 2007

While a fairly large body of literature dealing with just‐in‐time (JIT) manufacturing exists, most of it is descriptive. JIT research consists primarily of case studies, surveys, a few analytic models (primarily dealing with Kanban), and some simulations. This research builds on the existing literature to develop and test an exploratory model of JIT purchasing with an empirical field study of an actual JIT implementation. While the results basically follow hypotheses developed from the literature, some anomalies were found. The research provides both a methodology for further JIT study and an indication of the possible relative importance of JIT purchasing characteristics as they exist in a North American installation. Especially insightful is the fact that the relative importance changes depending on whether customer inventory or supplier inventory is used as the dependent variable. With customer inventory, the variables measuring delivered lot size, the size of release changes, and supplier manufacturing lead time were significant. With supplier inventory, only supplier manufacturing lot size was significant.
Optimal and Heuristic Models for Lot Splitting in a Flow Shop
Authors: Kropp Dean H. , Smunt Timothy L.
Published: June 2007

This paper investigates optimal lot‐splitting policies in a multiprocess flow shop environment with the objective of minimizing either mean flow time or makespan. Using a quadratic programming approach to the mean flow time problem, we determine the optimal way of splitting a job into smaller sublots under various setup times to run time ratios, number of machines in the flow shop, and number of allowed sublots. Our results come from a deterministic flow shop environment, but also provide insights into the repetitive lots scheme using equal lot splits for job shop scheduling in a stochastic environment. We indicate those conditions in which managers should implement the repetitive lots scheme and where other lot‐splitting schemes should work better.
Cash Flow Modelling and Forecasting in Capital Budgeting Under Uncertainty*
Authors: Giaccotto Carmelo
Published: June 2007

The subject of this paper is modelling and forecasting of cash flows generated by a capital investment. The paper proposes the application of autoregressive, moving average, and mixed autoregressive moving‐average processes to capital budgeting. In addition, models for deterministic, stochastic and seasonal trends are considered. For each class of cash flows, analytical expressions are developed for the mean and variance of a project's net present value (NPV). Also considered are several equilibrium pricing models. For two of them, the forecasting methodology developed here is integrated into the pricing equation. Although the overall emphasis of the paper is on modelling and forecasting of cash flows, the implications for NPV pricing and risk analysis are also investigated. Several examples are used to illustrate the impact of particular cash flow models on the price and risk of a project.
Correction Constants for Present Values of Sub‐Annual Cash Flows*
Authors: McMath H. Kent
Published: June 2007

When future cash flows are expected to occur at sub‐annual intervals, it is widely recognized that present value estimates are biased by the common assumption that each year's flows occur at year‐end. Although a “brute force” remedy for the end‐of‐year (EOY) bias is well known, the method does not appear to be generally used for financial decisions. The author suggests the possible reasons for continued tolerance of EOY bias are that the present method for eliminating the bias is too cumbersome or that the amount of bias is thought to be negligible. The paper also (a) examines the current remedy, indicating several features that hamper its use, (b) presents a correction constant approach that simplifies calculation of unbiased present values for streams of sub‐annual cash flows, (c) derives expressions for correction constants under two alternative assumptions about sub‐annual discounting, and (d) demonstrates use of the constants and the possible decision‐relevance of EOY bias by a simple capital budgeting example.
A Note on Consistency in Utility Assessment*
Authors: Hughes Warren R.
Published: June 2007

A methodology for determining a von Neumann‐Morgenstern utility function is outlined based on the axioms crucial to such a function. Reconciliation of inconsistent judgments is facilitated using the theory of reciprocal matrices. Numerical measures of the collective divergence of a set of judgments from perfect consistency or coherency are provided.
Forecasting Seasonal Time Series of Corporate Earnings: A Note*
Authors: Jarrett Jeffrey
Published: June 2007

The purpose of this paper is to compare the accuracy of various models for forecasting time series of corporate earnings. Previous research indicated that user‐identified time series (ARIMA) models were less useful for forecasting corporate earnings than prespecified models of the Watts‐Griffin and Brown‐Rozeff type. In this study, these research results are disputed. Specifically, prespecified models did not produce models having smaller forecast errors in the statistical sense than did user‐identified models for the same time series data for the same time period. The user‐identified models are those selected by the prescriptive methods of Box‐Jenkins identification, estimation, and diagnostic testing. Furthermore, the magnitude of the forecasting error may be understated for the prespecified models indicating that Box‐Jenkins models may even be more useful than indicated by measures of forecast error.
A Comparison of Linear Programming and Parametric Approaches to the Two‐Group Discriminant Problem*
Authors: Rubin Paul A.
Published: June 2007

Recent simulation‐based studies of linear programming models for discriminant analysis have used the Fisher linear discriminant function as the benchmark for parametric methods. This article reports experimental evidence which suggests that, while some linear programming models may match or even exceed the Fisher approach in classification accuracy, none of the fifteen models tested is as accurate on normally distributed data as the Smith quadratic discriminant function. At the minimum, further testing is warranted with an emphasis on data sets that arise from significantly non‐Gaussian populations.
Discretionary Use of Computers: An Empirically Derived Explanatory Model*
Authors: Howard Geoffry S. , Mendelow Aubrey L.
Published: June 2007

This study identifies variables that explain variations in computer use. Factor analysis of data gathered from 422 business administration faculty reveal eight themes among the independent variables. Seven of these factors significantly discriminate among non, minimal, and high users. These results suggest an empirical model for future studies and provide policy insights for decision makers seeking to stimulate computer usage. Additionally, the study shows that there is much commonality between the previously separate organizational innovation and information systems implementation streams. It also demonstrates that motivation theory may be a valid framework within which to study computer use.
Graphical Presentations of Data Envelopment Analyses: Management Implications from Parallel Axes Representations*
Authors: Desai Anand , Walters Lawrence C.
Published: June 2007

The conversion of multivariate data analysis into information that managers can readily use in their decision making has always been a challenging task. In this paper we provide a parallel axis representation of multivariate data and demonstrate how this representation may be used as a tool for implementing the results of data envelopment analysis. We use an analysis of the efficiency of electricity generating plants to illustrate the technique.
An Optimization Approach for Scheduling Internal Audits of Divisions
Authors: Knechel W. Robert , Benson Harold P.
Published: June 2007

In this paper, we develop an optimization model for efficiently scheduling internal audits of multiple units within a business enterprise. The model determines an optimal mix of audit frequencies for the audit units given the risks and costs involved in the audit process. We also show one method for estimating the audit cost and loss functions needed as input to the model and demonstrate how to obtain a solution for the model. To illustrate the model's use, we solve a sample problem with eight audit units and examine the sensitivity of the solution to misestimation of the risk parameters. Our results indicate that the model is readily solvable on a personal computer, useful for choosing an efficient mix of audit frequencies and an overall audit budget, and relatively insensitive to misestimation of the risk parameters.
Dogmatism and Systems Development Personnel Performance
Authors: Swanson N. E. , Cornette W. R. , Keith N. K.
Published: June 2007

This research explores the relationship between the personal variable, dogmatism, and the performance evaluations of systems analysts within a Fortune 500 company. The Rokeach Dogmatism Scale was used to measure the analysts’ level of dogmatism. The analysts’ performance measurement was the product of the company's annual evaluation process. The results of the research indicate that personnel with the highest dogmatism scores generally receive the extreme performance ratings. The results of this study provide further support to consider dogmatism as an important personal variable influencing systems analyst job performance.
On the Measurement of Perceived Consumer Risk
Authors: Havlena William J. , DeSarbo Wayne S.
Published: June 2007

The role of perceived risk in consumer behavior has been studied extensively by academic researchers. This paper introduces a methodology for the measurement of the effects of product features, marketing mix components, and individual differences on perceived consumer risk based on theoretical foundations in the literature. A conjoint‐type model based on paired comparison judgments is estimated to provide attribute weights. A modification of a stochastic multidimensional scaling‐based vector model is then used to measure and summarize individual consumer differences with respect to the impact of brand attributes and marketing mix components on latent levels of perceived consumer risk. An illustration is provided using students’ risk perceptions of sports cars.
Critical Dimensions of Strategic Information Systems Planning
Authors: Lederer Albert L. , Sethi Vijay
Published: June 2007

Strategic information systems planning (SISP) is the process whereby an organization establishes a long‐range plan of computer‐based applications in order to achieve its goals. A number of problems can potentially impede information systems planners as they carry out the process. A survey of 80 firms who completed the SISP process revealed that the problems constitute five factors: the organization, implementation, database, hardware, and cost. A discriminant analysis showed that three factors—the organization, implementation, and database—best distinguished satisfied from dissatisfied information systems planners. A research application of the five factors suggested that organizations with more sophisticated business planning endure significantly less severe hardware and implementation problems.
Separation Failure in Linear Programming Discriminant Models
Authors: Rubin Paul A.
Published: June 2007

Linear programming discriminant analysis (LPDA) models are designed around a variety of objective functions, each representing a different measure of separation of the training samples by the resulting discriminant function. A separation failure is defined to be the selection of an “optimal” discriminant function which incompletely separates a pair of completely separable training samples. Occurrence of a separation failure suggests that the chosen discriminant function may have an unnecessarily low classification accuracy on the actual populations involved. In this paper, a number of the LPDA models proposed for the two‐group case are examined to learn which are subject to separation failure. It appears that separation failure in any model can be avoided by applying the model twice, reversing group designations.
An Information Theoretic Framework for Exploratory Multivariate Market Segmentation Research*
Authors: Hosseini Jamshid C. , Harmon Robert R. , Zwick Martin
Published: June 2007

State‐of‐the‐art market segmentation often involves simultaneous consideration of multiple and overlapping variables. These variables are studied to assess their relationships, select a subset of variables which best represent the subgroups (segments) within a market, and determine the likelihood of membership of a given individual in a particular segment. Such information, obtained in the exploratory phase of a multivariate market segmentation study, leads to the construction of more parsimonious models. These models have less stringent data requirements while facilitating substantive evaluation to aid marketing managers in formulating more effective targeting and positioning strategies within different market segments. This paper utilizes the information‐theoretic (IT) approach to address several issues in multivariate market segmentation studies. A marketing data set analyzed previously is employed to examine the suitability and usefulness of the proposed approach [12]. Some useful extensions of the IT framework and its applications are also discussed.
Tax Professionals Belief Revision: The Effects of Information Presentation Sequence, Client Preference, and Domain Experience
Authors: Pei Buck K.W. , Reckers Philip M.J. , Wyndelts Robert W.
Published: June 2007

Based on a belief revision model recently proposed by Hogarth and Einhorn [35], the present research investigates the effects of information presentation orders on tax professionals’ belief revisions about ambiguous tax treatments. Also examined in the study are the impacts of the tax professionals’ experience and the client's tax preference on the belief revision. The results show that the experienced tax professionals’ belief revisions are affected by the presentation order manipulations, but unaffected by the client preference manipulations. In contrast, the inexperienced tax professionals’ belief revisions display a reverse pattern.
A Credit Limit Decision Model for Inventory Floor Planning and Other Extended Trade Credit Arrangements*
Authors: Fewings David R.
Published: June 2007

This paper analyzes the dealership credit limit problem in terms of the valuation of a Markov process of cash flows with sequential credit decisions over an infinite planning horizon. The formulation distinguishes between the upper bound on credit applicable at the account formation stage and the upper bound applicable to periodic reorders. The result is a closed form solution to the problem which serves as a criterion function for approving or denying credit on a customer‐by‐customer basis.

Data for a sample of manufacturing firms are employed to estimate typical ranges for criterion function parameters. Upper bounds on credit limits are then calculated and graphically presented for median parameter values as well as for values at the 5th and 95th percentiles for the sample data. Finally, an empirical study is conducted of actual trade credit extended by firms. The results support the hypothesis that the variables in the decision model are important determinants of the amount of trade credit outstanding.
Locating Emergency Warning Sirens
Authors: Current John , O'Kelly Morton
Published: June 2007

In this paper, we report on the application of set covering and maximal covering location models to the problem of locating emergency warning sirens in a midwestern city. Two siren types are available, each having different costs and covering radii. Using a modified version of the set covering location model, we analyze the cost implications of several policy options being considered by the city's planners. Results of the study indicate that location covering models can be powerful and efficient tools in the design of such systems, and their use can lead to significant cost savings. In addition, such models provide decision makers the flexibility to examine the inherent costs associated with various policy options.
Evaluating USAF Vehicle Maintenance Productivity Over Time: An Application of Data Envelopment Analysis
Authors: Clarke Richard L.
Published: June 2007

In response to increasing costs and reductions in manpower, the Tactical Air Command (TAC) of the USAF experimented with a specialized productivity measurement model known as data envelopment analysis (DEA). A medium‐sized application of DEA was employed by TAC to evaluate the productivity of its seventeen subordinate vehicle maintenance sections over a four‐year period. The application reports gains in productivity and the reactions of the field managers to the use of DEA.
Formulation Tactics and the Success of Organizational Decision Making*
Authors: Nutt Paul C.
Published: June 2007

One hundred and seventy‐seven cases profiling organizational decisions were analyzed to determine how managers carry out formulation as they initiate a decision‐making process. Analysis revealed that formulation was carried out by applying problem, idea, target, and reframing tactics. Decision adoption rates, decision value, and time to carry out the decision‐making process were used to determine the success of these tactics, controlling for situational effects of importance, urgency, resources, and management level. Reframing was found to be the most successful tactic under all conditions, but was the least frequently used by decision makers. Problem and idea tactics were the least successful and success did not improve with additional resources, but these tactics were used more often than the other tactics. Problem tactics were even less successful when applied to urgent and important decisions. Target tactics were surprisingly effective for crises and important decisions. Decision makers seem prone to use ineffective formulation tactics and give little consideration to the opportunities or constraints imposed by the situation as a tactic is selected.
Coordinated Replenishments from a Common Supplier
Authors: Russell Randolph M. , Krajewski Lee J.
Published: June 2007

Coordinated replenishment strategies may be implemented by jointly ordering multiple items from a common supplier. A major benefit of coordinated replenishment is that it increases the size of shipments, permitting the buyer to enjoy transportation economies without a major increase in average inventory levels. The coordinated replenishment problem is complex because side constraints govern the attainment of transportation rate breaks. The problem is further complicated by the presence of purchase quantity discount opportunities. Thus, the buyer must decide which items to order independently, which items to include in a group order, and the order quantities of each item, governed by the frequency of independent or group orders.

We present a mathematical model and a heuristic solution procedure that provide analytical support to the buyer seeking to minimize total costs of replenishing multiple items from a common supplier. The relevant costs are purchase prices, ordering costs, holding costs, and transportation costs. Coordinated replenishment provides nearly a 30 percent reduction in controllable costs relative to independent control. Experimentation with the heuristic has yielded optimal solutions over 88 percent of the time. When optimality was not obtained, the mean penalty was much less than one percent. The average heuristic search was more than two orders of magnitude faster than branch and bound, even for small problems, and possessed a much tighter distribution around the mean search time.
Due Date Assignment, Job Order Release, and Sequencing Interaction in Job Shop Scheduling*
Authors: Ahmed Imtiaz , Fisher Warren W.
Published: June 2007

Depending on the techniques employed, the due date assignment, release, and sequencing procedures in job shop scheduling may depend on one another. This research investigates the effects of these interactions with a simulation model of a dynamic five‐machine job shop in which early shipments are prohibited. Performance of the system is measured primarily in terms of the total cost (work‐in‐process cost, finished goods holding cost, and late penalty) incurred by the shop, but a number of non‐cost performance measures are also reported. The results support existence of a three‐way interaction between the due date, release, and sequencing procedures as well as interaction between shop utilization and procedure combination. Statistical tests are used to identify those rules that perform best both overall and in combination with other rules.
Rule‐Based Expert Systems and Linear Models: An Empirical Comparison of Learning‐By‐Examples Methods*
Authors: Chung Hyung‐Min Michael , Silver Mark S.
Published: June 2007

Building models of expert decision‐making behavior from examples of experts’ decisions continues to receive considerable research attention. In the 1960's and 70's, linear models derived by statistical methods were studied extensively. More recently, rule‐based expert systems derived by induction algorithms have been the focus of attention. Few studies compare the two approaches. This paper reports on a study that compared linear models derived by logistic regression with rule‐based systems produced by two induction algorithms—ID3 and the genetic algorithm. The techniques performed comparably in modeling the experts at one task, graduate admissions, but differed significantly at a second task, bidder selection.
A Simple Minimum‐Bias Percentile Estimator of the Location Parameter for the Gamma, Weibull, and Log‐Normal Distributions
Authors: Muralidhar Krishnamurty , Zanakis Stelios H.
Published: June 2007

Estimating the unknown minimum (location) of a random variable has received some attention in the statistical literature, but not enough in the area of decision sciences. This is surprising, given that such estimation needs exist often in simulation and global optimization. This study explores the characteristics of two previously used simple percentile estimators of location. The study also identifies a new percentile estimator of the location parameter for the gamma, Weibull, and log‐normal distributions with a smaller bias than the other two estimators. The performance of the new estimator, the minimum‐bias percentile (MBP) estimator, and the other two percentile estimators are compared using Monte‐Carlo simulation. The results indicate that, of the three estimators, the MBP estimator developed in this study provides, in most cases, the estimate with the lowest bias and smallest mean square error of the location for populations drawn from log‐normal and gamma or Weibull (but not exponential) distributions. A decision diagram is provided for location estimator selection, based on the value of the coefficient of variation, when the statistical distribution is known or unknown.
The Positive Effects of Easy Goals on Decision Quality and Risk Propensity in an MCPLP Task
Authors: Taylor Lewis A. , Cosier Richard A. , Ganster Daniel C.
Published: June 2007

In this study the potential performance benefits of easy goals were examined within the multiple cue probability learning paradigm (MCPLP). Specifically, the effects of varying levels of goal difficulty on performance and risk propensity (used to define a form of commitment) were investigated. With few exceptions, previous studies demonstrated support for difficult goals. In this study, contrary to the majority of past evidence, as goals became easier decision quality significantly improved. Moreover, risk propensity increased with easier goals and, as suggested by a post‐hoc analysis, had more direct impact on decision makers’ behaviors than goal levels. Goal‐related behavior in complex MCPLP tasks appears to significantly differ from the majority of goal evidence in other types of research due to the tendency for subjects to view complex task properties in the same context as goal levels.
Improving the Utilization of Front‐Line Service Delivery System Personnel*
Authors: Thompson Gary M.
Published: June 2007

There are two types of work typically performed in services which differ in the degree of control management has over when the work must be done. Serving customers, an activity that can occur only when customers are in the system is, by its nature, uncontrollable work. In contrast, the execution of controllable work does not require the presence of customers, and is work over which management has some degree of temporal control. This paper presents two integer programming models for optimally scheduling controllable work simultaneously with shifts. One model explicitly defines variables for the times at which controllable work may be started, while the other uses implicit modeling to reduce the number of variables. In an initial experiment of 864 test problems, the latter model yielded optimal solutions in approximately 81 percent of the time required by the former model. To evaluate the impact on customer service of having front‐line employees perform controllable work, a second experiment was conducted simulating 5, 832 service delivery systems. The results show that controllable work offers a useful means of improving labor utilization. Perhaps more important, it was found that having front‐line employees perform controllable work did not degrade the desired level of customer service.
Sensitivity Analysis Revisted and Extended
Authors: Wendell Richard E.
Published: June 2007

The tolerance approach to sensitivity analysis in linear programming provides a framework for dealing with simultaneous and independent variations of the coefficients and terms. Specifically, the approach yields a maximum tolerance percentage which in turn characterizes a region of variability for the coefficients or terms. This paper shows how to expand this region of variability yielding ordinary sensitivity analysis as a special case of the tolerance approach.
Integrating Neural Networks and Semi‐Markov Processes for Automated Knowledge Acquisition: An Application to Real‐time Scheduling*
Authors: Liang Ting‐Peng , Moskowitz Herbert , Yih Yuehwern
Published: June 2007

Recently, artificial neural networks (ANN) have gained attention as a promising modeling tool for building intelligent systems. A number of applications have been reported in areas varying from pattern recognition to bankruptcy prediction. In this paper, we present a creative methodology that integrates computer simulation, semi‐Markov optimization, and ANN techniques for automated knowledge acquisition in real‐time scheduling. The integrated approach focuses on the synergy between operations research and ANN in eliciting human knowledge, filtering inconsistent data, and building competent models capable of performing at the expert level. The new approach includes three main components. First, computer simulation is used to collect expert decisions. This step allows expert knowledge to be obtained in a non‐intrusive way and minimizes the difficulties involved in interviewing experts, constructing repertory grids, or using other similar structures required for manual knowledge acquisition. The data collected from computer simulation are then optimized using a semi‐Markov decision model to remove data redundancies, inconsistencies, and errors. Finally, the optimized data are used to build ANN‐based expert systems. The integrated approach is evaluated by comparing it with the human expert and using ANN alone in the domain of real‐time scheduling. The results indicate that ANN‐based systems perform worse than human experts from whom the data were collected, but the integrated approach outperforms human experts and ANN models alone.
The Use of Stochastic Simulation in Knowledge‐Based Systems
Authors: Raghunathan Srinivasan , Tadikamalla Pandu
Published: June 2007

Knowledge‐based systems support the decision‐making process with the help of domain specific knowledge bases. The knowledge bases almost always have uncertainty associated with them. A variety of approaches have been proposed in the artificial intelligence (AI) literature for the construction of and reasoning with uncertain knowledge bases. Building on this stream of research, we focus on how stochastic simulation can be used to construct and reason with knowledge bases that have uncertainties. An advantage of the simulation methodology is that it may not have to make many of the assumptions made by other approaches. It also allows the designer of the knowledge‐based system to control the methodology based on accuracy and time requirements. The simulation approach to knowledge base construction is a modified version of the concept induction procedure used in AI. However, it incorporates, as does simulation modeling, statistical tests to identify the best rule that describes the relationship among the variables. We show that when simulation is used to reason with uncertain knowledge bases, under certain conditions, the number of simulation trials needed to achieve a given level of accuracy is independent of the characteristics, such as the size, of the knowledge base. Empirical results obtained from an experiment confirm our theoretical results and provide evidence that simulation methodology is practical for real life knowledge‐based systems.
Single and Multiple Period Decision Models for Analysis of Quality and Quantity of Validation*
Authors: O'Leary Daniel E.
Published: June 2007

This paper investigates a single period model for the analysis of the impact of the quality of the validation effort. The single period model uses a Bayesian approach to find that validation is a critical point process. That model is then extended to allow for the uncertainty of the validation process to determine the quality of the underlying model. Some monotonicity results are developed for the model and investigated in light of the process being a critical point process. The model indicates that, consistent with comments from real world settings, the impact of the quality of the validation effort can be substantial.

The paper also presents two multiperiod models of the impact of the quantity of the validation effort. In practice, the development of an expert system may follow a recurring multiperiod life cycle, where a prototype is built, the system is validated to determine how well it performs, and based on that performance, is either funded or not funded. The first multiple period model assumes that validation and funding occurs at each point in the PVF budget cycle. The model employs Bayesian revision of probabilities to update the prior probability of obtaining a model with an appropriate level of success. It is found that the critical point for multiperiod problems is different than that for single period problems. This model forms the basis of the second model. The second multiple period model extends the first by assuming that the quantity of validation can be varied. The more validation, the more likely that flaws in the model will be found. Thus, the more validation, the better the understanding of the level of performance of the model.
Automated Discovery in Managerial Problem Formulation: Formation of Causal Hypotheses for Cognitive Mapping
Authors: Billman Beth , Courtney James F.
Published: June 2007

Development of knowledge acquisition techniques known as automated discovery systems has occurred in deep and narrow domains of knowledge. Automated discovery is the generation of new knowledge by a computer system on its own, without the help of another knowledge source. This paper describes research and validation of an automated discovery system for a wide and shallow domain—business management. The system continues recent advances in expert systems research which have enhanced cognitive mapping, a problem formulation tool. The system perceives the behavior of distal variables in the environment through probabilistic cues‐to‐causality, and generates previously unknown hypotheses by aggregating the probabilities into a single criterion of causal relatedness. The system is validated against the source code of a simulated managerial environment, and causal relationships posited by decision makers experienced in the play of the gaming simulator.
A Model‐Based Approach to Investigate Performance Improvements in Rule‐Based Expert Systems
Authors: Gulati D. , Tanniru Mohan R.
Published: June 2007

One of the major issues in the development of large, rule‐based expert systems is related to improving their performance efficiency. One way to address this issue is by reducing the number of unsuccessful tries a system goes through before executing a rule to establish a goal or an intermediary fact. On the average, the number of unsuccessful tries can be reduced if the rules that are tried first are those that are expected to execute most frequently, and this can be established by extracting information on the probability distributions of the input parameters. In this paper, a rule base is modeled as a network and simulated to investigate potential performance improvements by changing the order used to test the rules. The model of the rule base is also used to investigate performance gains achieved by parameter factorization and premise clause reordering.
Evaluating Consumer Preferences for Existing Multiattribute Products: A Non‐Metric Approach
Authors: Lau Kin‐nam , Post Gerald V.
Published: June 2007

A model evaluating consumer preferences for multiattribute products is derived. The model possesses the following features: (1) the method works for existing products; (2) the input data require only overall product rankings and attribute rankings; (3) the distribution of part worths (utility) for particular attributes is derived and used to judge the trade‐offs among different attributes; (4) the procedure can be implemented with existing software; and (5) the attributes do not need to be quantifiable.
The Information Problems in Organizations: A Research Model for the Value of Information and Information Systems*
Authors: West Lawrence A. , Courtney James F.
Published: June 2007

Growing recognition of the need for better management information system (MIS) theory and practice centers around problems with identifying the value of information and information systems in organizations. This paper addresses this issue by showing that existing theory in organizational economics and industrial organization directly relates to information problems in organizations (their nature, and their effects in terms of organization structure and performance). The paper categorizes these problems and associated theories into four distinct classes and shows that MIS research and practice can be mapped to information problems of each type. Because the economic theory pertinent to specific information problems includes the nature of the organizational response to information constraints, it also provides insight into the nature of the improvement to be realized if information constraints can be overcome. These improvements can then be interpreted as the value of the associated information systems which suggests using the resultant classification scheme to map between information problems and system value. The paper shows that this methodology provides a more appropriate level of focus than either traditional normative or business value methods, especially because many improvements have structural as well as performance consequences.
Testing Prospect Theory in a Deterministic Multiple Criteria Decision‐Making Environment*
Authors: Salminen Pekka , Wallenius Jyrki
Published: June 2007

Prospect theory by Kahneman and Tversky [7] is tested in a deterministic multiple criteria decision‐making context. In two experiments conducted in classroom settings subjects made pairwise preference comparisons of condominiums for sale. The results of the experiments indicate that the traditional value model did not explain the subjects' revealed preferences as well as the prospect model. We conclude that prospect theory is a reasonable model of choice for many individuals in such a context.
Production Competence and Business Strategy: Do They Affect Business Performance?
Authors: Vickery Shawnee K. , Droge Cornelia , Markland Robert E.
Published: June 2007

The purpose of this article is threefold. First, a comprehensive measure of production competence that assesses the level of support that manufacturing provides for the strategic objectives of a firm is developed. Second, hypotheses relating production competence to several financial measures of business performance are tested using data from a large sample of firms (n=65) in the furniture industry. Third, the impact of business strategy both directly on performance and as a moderating variable in relation to production competence is analyzed. The results of the study suggest that production competence may have more of an effect on business performance for certain strategies than for others.
Generalizing the Announced Price Increase Problem*
Authors: Arcelus Francisco J. , Srinivasan Gopalan
Published: June 2007

This paper generalizes the announced price increase problem to consider a variety of practical concerns arising out of applications ranging from foreign exchange fluctuations to upper limits on the purchase of discounted supermarket items. These include limitations on the amount that can be purchased at the old price and/or on the length of the grace period, within which buyers may take advantage of this lower price. These constraints give rise to 16 possible situations. For each situation purchasing and inventory decision rules are developed. A numerical example is discussed to highlight the main features of the models.
Developing Measures for Assessing the Organizational Impact of Information Technology: A Comment on Mahmood and Soon's Paper
Authors: Sethi Vijay , Carraher Shawn
Published: June 2007

In a recent study, Mahmood and Soon [26] identified and operationalized a set of variables that can be potentially impacted by information technology. The lack of factor analysis to verify the dimensionality of different variables is a notable omission in the study. This paper describes and employs the limited‐information factor analysis approach and the minimum average partial criterion for testing the unidimensionality of different variables in the Mahmood and Soon study. While reconfirming the construct validity of eight variables, our results question the unidimensionality of two original variables. Further testimony is provided in favor of our results by citing previous research studies.
Sensitivity of Linear Programs to Related Changes in Multiple Inputs*
Authors: Schenkerman Stan
Published: June 2007

In a 1991 paper in Decision Sciences, Camm and Burwell presented smart modeling techniques for obtaining the sensitivity of linear programs to simultaneous common changes in common inputs. This note addresses sensitivity analysis of simultaneous related changes in multiple inputs, and shows how related multi‐parametric analysis can be performed with software that has no or only limited parametric programming capability.
The Development Manager's Advisory System: A Knowledge‐Based DSS Tool for Project Assessment*
Authors: Liberatore Matthew J. , Stylianou Anthony C.
Published: June 2007

This research investigates whether the knowledge‐based decision support system (KBDSS) paradigm provides the necessary supporting structure and developmental framework for product development evaluation. To address the research questions posed in this study, it is necessary to develop and implement KBDSS's at specific decision points along the product development cycle. This paper describes the design, development, and implementation of a KBDSS to support a product development manager's decision concerning full‐scale development of a new product. From the systems design perspective, this paper addresses the integration and innovative use of a variety of techniques for knowledge acquisition, modeling, and processing. The approach utilized obtains the benefits of normative modeling as well as the flexibility and developmental advantages of knowledge‐based systems. Since its implementation, the system has been successfully used by a development manager to support his recommendation for an ongoing project. His complete satisfaction with this system served as the impetus for the design and development of a multi‐expert system which was implemented at the strategic level.
Examining the Joint Roles of Responsibility and Reinforcement History in Recommitment*
Authors: Goltz Sonia M.
Published: June 2007

The present study examined the combined effects of responsibility and reinforcement history on investment responses during a series of failure experiences. Subjects performed a variation of the A and S decision case [27] under one of six conditions varying in responsibility (high, low) and reinforcement history (variable partial, fixed partial, no training). When investment responses at the start of the period of continuous losses were examined, results indicated that high responsibility and a variable history of reinforcement are both necessary conditions for escalation to occur. When later responses were included in the analysis, reinforcement history and time were the main factors affecting recommitment responses. These results suggest possible refinements to current models of escalation.
Toward Development of the End User Computing Construct in a University Setting*
Authors: Rainer R. Kelly , Harrison Allison W.
Published: June 2007

The authors identify and define the end user computing (EUC) construct and operationalize the construct through development of a valid, reliable measure called the EUC activities scale. This scale is designed to distinguish specific, discrete computer activities performed on the job. The research analyzes the validity and reliability of the instrument based on data obtained from 776 university employees who participated in the initial, exploratory application. Exploratory factor analysis of the scale resulted in five factors. In order of increasing complexity of job‐related computer activities, these factors are: beginning EUC activities, intermediate EUC activities, advanced EUC activities, EUC facilitation activities, and EUC infrastructure activities. The factor analysis, reliabilities, and known‐groups analysis provide support for the construct validity of the instrument when used in a university setting. Suggestions are provided for further use of the scale in business environments to increase generalizability, refine the instrument, and help establish a coherent theoretical basis for further research in EUC.
Optimal and Heuristic Decision Strategies for Integrated Production and Marketing Planning
Authors: Lee Won J. , Kim DaeSoo
Published: June 2007

In this study we examine the effects of integrating production and marketing decisions for a short‐ to medium‐range planning horizon in a profit maximizing firm. We formulate two models for determining price, marketing expenditure, demand or production volume, and lot size for a single product with stable demand when economies of scale are present. The full integration (FI) model simultaneously determines all the decisions involved, while the partial integration (PI) model separates the lot sizing decision from the others, as happens frequently in practice. Geometric programming (GP) techniques and marginal analysis are used to compare FI and PI, and obtain important managerial implications regarding the two models.
Development of a Prediction Model for Hospital Closure Using Financial Accounting Data*
Authors: Wertheim Paul , Lynn Monty L.
Published: June 2007

Numerous research studies have examined the use of financial accounting data in the prediction of corporate bankruptcy. Partly due to a lack of available data, however, little work has been done in developing a closure prediction model specifically for hospitals. Using cost reports from the Health Care Financing Administration and a sample of 71 closed hospitals and a matched sample of 71 open hospitals, the current study examines the relationship between 21 financial accounting ratios and hospital closure. Univariate logit results indicate that hospital closure is significantly related to 17 of the 21 ratios one year prior to closure. Results are also presented using a multivariate model, and for the relationships two years prior to closure. The current study provides information helpful to users in identifying financial variables which may be important indicators of hospital closure.