bluuebunny/crossref_metadata_2025_split huggingface dataset:
REVEALING TIME SERIES INTERRELATIONSHIPS
Authors: Pack David J. 
Published: June 2007

ABSTRACTBox and Jenkins [3] have specified a procedure for the development of a “transfer function model,” a model which expresses the interrelationships between two time series. Involving the iterative repetition of identification, estimation, and checking stages, this procedure is comparable to their procedure for the development of an autoregressive‐intergrated‐moving average model for a single time series. The transfer function model development procedure has not been widely applied due to the absence of explanations understandable to the non‐statistician and reasonably priced computer algorithms.The intent of this paper is to provide the non‐statistician with an explanation of the identification stage of the Box‐Jenkins transfer function model development procedure. An extensive class of possible models is logically developed. The identification stage is specified step‐by‐step and is illustrated by three pairs of generated time series analyzed using computer algorithms written by the author. The paper presumes a general knowledge of the Box‐Jenkins identification procedure for single series models.
TIME‐LAGS IN CROSS‐LAG CORRELATION STUDIES: A COMPUTER SIMULATION
Authors: Sims Henry P. , Wilkerson David A. 
Published: June 2007

ABSTRACTThe cross‐lag correlation method has gained increased use in recent years as a technique which can be used to evaluate causality in longitudinal behavioral research. However, the effect of selecting an incorrect time‐lag has remained largely unexplored. This research reports the results of a computer simulation designed to evaluate what happens to the cross‐lag correlation under different time‐lags. The results of the simulation indicate that the cross‐lag method is relatively insensitive to errors in the selection of the time‐lag. Nevertheless, it is better to err on the “early” side than on the “late” side. A research design is suggested for further empirical investigation of the effect of the choice of time‐lags.
A HEURISTIC PROCEDURE FOR DETERMINING IN‐PROCESS INVENTORIES
Authors: Davis K. Roscoe , Taylor Bernard W. 
Published: June 2007

AbstractMost prior studies that examine in‐process inventory requirements associated with a manufacturing facility employ an optimizing algorithm; this article proposes a heuristic procedure for determining such requirements. A procedure is given for determining “active” and “banked” work‐in‐process requirements. The two are combined to give total in‐process requirements.A key factor presented in the paper is the relationship between in‐process inventory requirements and the “balancing” of a production facility. Most prior researchers examine these problems independently. It will be shown that both problems can be resolved concurrently. The concepts are applicable to both an existing as well as a new manufacturing facility.
PORTFOLIO MODELING IN MULTIPLE‐CRITERIA SITUATIONS UNDER UNCERTAINTY
Authors: Muhlemann Alan Paul , Lockett Alan Geoffrey , Gear Anthony Edward 
Published: June 2007

AbstractThere have been many models for portfolio selection, but most do not explicitly include uncertainty and multiple objectives. This paper presents an approach that includes these aspects using a form of stochastic integer programming with recourse.The method involves the use of a time‐based decision tree structure called a “project tree.” Using this basic format, an illustrative six‐project example is presented and analyzed. Various forms of objectives are discussed, ranging from the maximization of expected portfolio value to the maximization of the minimum weighted portfolio deviation from two goals. In each case, formulated numerical problems are given, and the solutions derived are presented. The approach is shown to be very flexible and capable of handling a variety of situations and objectives.
A SIMULATION AND STATISTICAL ANALYSIS OF STOCHASTIC VEHICLE ROUTING WITH TIMING CONSTRAINTS
Authors: Cook Thomas M. , Russell Robert A. 
Published: June 2007

AbstractThis paper examines a generalization of the vehicle‐dispatch problem in which time constraints as well as stochastic demand and travel times are considered. The objective is to minimize total travel time subject to vehicle load capacities and sequencing restrictions, meaning that certain points may be serviced only in specified time intervals. Intra‐city travel times are estimated via multiple regression, and an effective heuristic is tested on single‐estimate travel times. A GPSS simulation is used to evaluate the heuristic on stochastic travel times and also to examine the effects of other decision variables such as route configuration. Computational experience with an actual refuse collection problem involving 163 points per day is reported.
THE INTERACTION OF TRANSPORTATION AND INVENTORY DECISIONS
Authors: Constable Gordon K. , Whybark D. Clay 
Published: June 2007

AbstractThe management of inventories and determination of transportation policy are normally carried out by different groups of people in an organization. These activities interact, however, when the transportation is used to replace inventory and when the transportation alternatives have different speed, reliability, and cost characteristics. This paper presents exact and heuristic procedures for jointly determining the inventory reorder points, order quantities, and transportation alternatives that provide minimum total transportation and inventory costs. The effectiveness of each procedure is demonstrated for a broad range of problems. The heuristic procedure was also applied to actual company data to determine the potential for cost savings. The results showed that savings were possible both from improving the current procedures and from applying the procedure developed in this study.
THE SEU CALCULUS: EFFECTS OF RESPONSE MODE, SEX, AND SEX ROLE ON UNCERTAIN DECISIONS *
Authors: Bonoma Thomas V. , Schlenker Barry R. 
Published: June 2007

ABSTRACTSubjects were instructed on how to use simple subjective probability and utility scales, and they were asked to actively role‐play a decision maker in seven risk‐dilemma situations. Each scenario provided subjects with specific subjective expected utility (SEU) information for both a certain and uncertain decision alternative, but left out one critical SEU component. Subjects supplied either the lowest probability or the lowest utility for success that they found necessary before they would select the uncertain over the certain alternative in each dilemma. Three experiments examined: (a) the degree to which Ss' estimations deviated from a pattern predicted by SEU models; (b) differences in choice patterns induced by response format variations (e.g., probability vs. utility estimation); (c) the effects of sex of S; and (d) the effects of the sex‐role framing of the decision problems. Ss generally chose in accord with SEU maximization principles and did so with decreasing deviations from theoretical values as practice over situations increased (Experiments I, II and III). Decisions were initially more conservative on items requesting probability estimates (Experiment I), but this effect washed out over situations. Sex differences were revealed (Experiments I and III), but in limited fashion. Rather, a replicable (Experiments I, II and III) sex‐by‐sex role appropriateness by response format interaction was found, in which females responded “rationally” under both probability and utility estimation conditions and under both role sets (male and female). Males, however, responded extremely conservatively under female‐framed, probability estimate conditions. Ss' choices were stable over a three‐week interval (Experiment III).
A NOTE ON THE ASSESSMENT OF THE RESULTS IN A DISCRIMINANT ANALYSIS *
Authors: Gau George W. 
Published: June 2007

ABSTRACTThis paper describes two statistical measures that can be applied to the analysis of the results in a discriminant analysis. These measures, similar to R2 and R2 in multiple regression, assess the “goodness of fit” of the model or the degree of separation established by the discriminant functions among the groups in the sample and in the population.
LINEAR PROGRAMMING WITH DISCRETE STOCHASTIC RESOURCES: AN ALTERNATIVE APPROACH ACCOUNTING FOR INFEASIBILITY*
Authors: Hughes Warren R. 
Published: June 2007

ABSTRACTIn this paper an alternative to, or extension of, the chance‐constrained method of stochastic programming is presented whereby an expected cost of infeasibility is included in the objective function. The problem is to select a solution to implement before the available resources are known where the adaption of a non‐feasible solution to the resources available involves a system cost. While increasing the amount of computation required, the model enables the decision maker to more effectively trade off increased payoff for decreased likelihood of feasibility.
LOCUS OF CONTROL, TRUST, AND DECISION MAKING*
Authors: Bonoma Thomas V. , Johnston Wesley J. 
Published: June 2007

ABSTRACTA theoretical connection was proposed between certain social personality variables, namely locus of control (Internal or External) and trust (High and Low) and the formal decision‐making model of Subjective Expected Utility (SEU). Rather than adopting the traditional definition of these variables as “generalized expectancies” for behavior of self and others, locus of control and trust were reconceptualized as intrapersonal tendencies to favor, prefer, or otherwise bias the subjective probabilities entering into a decision computation.S's high in external control orientation did not differ from internals overall, but external males were more risk averse under certain choice conditions (female‐sex‐role appropriate dilemma, probability‐estimate form). Low‐trust S's were also more risk averse than high‐trust S's, overall. Low‐trust males generated maximally risk‐averse choice solutions under the choice condition of feminine role problem appropriateness and probability estimation. In general, female S's made choices that were more consistent with SEU‐predicted solutions than males.
AN ADAPTIVE APPROACH TO TIME‐SERIES FORECASTING
Authors: Bretschneider Stuart , Carbone Robert , Longini Richard L. 
Published: June 2007

ABSTRACTThis paper extends the applicability of the Carbone‐Longini adaptive estimation procedure (AEP) to time‐series forecasting. Comparisons with adaptive filtering, the Box‐Jenkins methodology, and multiple regression analysis as it applies to time‐series analysis are provided. Specific time‐series data examined by Box and Jenkins and Box and Tiao constitute the basis for these comparisons. The analysis of the results indicate the robustness and performance superiority of the simple distributive‐lag forecast model coupled with the concept of adaptively “tracking” rather than “fitting” historical data.
A STRATEGY FOR RISK REDUCTION IN INCENTIVE CONTRACTING*
Authors: Gandhi Devinder K. 
Published: June 2007

ABSTRACTAn important question with respect to government incentive contracts that has received little attention is: What alternatives to the current practice of making single‐stage choices of incentive sharing rates can lead to situations in which these sharing rates can be chosen under reduced risk or cost uncertainty? This paper provides a decision‐theoretic framework that illustrates a possibility of reducing risk, from the viewpoints of both the contracting parties, given some negotiated estimate of costs to be incurred. It is shown that such a possibility can arise in a situation in which it is technically feasible to separate or partition the contractual work into closely related tasks or units. Specifically, it is demonstrated that for a given cost estimate (target cost) and target profit, a set of optimal sharing rates (one for each unit) yields a higher risk‐adjusted value of the contract than the single‐stage sharing rate for the entire contract.
EVOLUTION OF THE PRODUCTIVE SEGMENT AND TRANSPORTATION INNOVATIONS*
Authors: Ettlie John E. 
Published: June 2007

ABSTRACTAn evolutionary model of the development of the process segment of a firm is reviewed and the degree to which this model is appropriate for description of the innovation process in transportation firms is evaluated. In a sample of thirty‐four transportation innovations it was found that: (1) transportation firms in stage I of the evolution of the productive segment are more likely to adopt service innovations, while firms in stage III are more likely to adopt innovations designed to improve the process (p < .05); (2) no statistically significant results were found to support the hypothesis that stage I transportation firms originate more innovations than stage III firms, although the results were in the predicted direction (.10 < p < .15); (3) stage I transportation firms are more likely to adopt or consider for adoption lower‐cost innovations than stage III firms (p < .05), which is contrary to the hypothesized direction of this relationship. It was also found that transportation firms tend to originate new service innovations but adopt new process innovations (p < .05), regardless of stage of development. It was concluded that it would be premature to eliminate the model as a candidate for further empirical testing. Problems and possible revision of the model are discussed.
AN EXTENSION OF WOLFE'S STUDY OF SIMULATION GAME COMPLEXITY*
Authors: Butler Richard J. , Pray Thomas F. , Strang Daniel R. 
Published: June 2007

ABSTRACTThis study is an extension of recently reported research concerning the relationships between business simulation game complexity and student perceptions of “learning,”“monotony,” and “appropriateness of challenge.” A game of intermediate‐level complexity was used at two education levels. Findings from the current study are compared with findings from an earlier study's intermediate‐level complexity game. A number of questions with respect to the earlier findings are raised.
QUESTIONNAIRE VALIDATION BY CONFIRMATORY FACTOR ANALYSIS: AN IMPROVEMENT OVER MULTITRAIT‐MULTIMETHOD MATRICES*
Authors: Elbert Norbert F. 
Published: June 2007

ABSTRACTThe Campbell and Fiske criteria for assessing the construct validity of multitrait‐multimethod (MTMM) matrices has had a long history of use. While various statistical techniques, including ANOVA, have attempted to provide rigor to the MTMM matrix design, numerous problems still remain unsolved. Part of the problem in using an MTMM matrix is the assumption of measurement independence. This study attempts to illustrate the misleading inferences that often occur from MTMM analysis when method variance overlap is not accurately assessed. Three questionnaires were designed that were not method independent. Traditional procedures for assessing MTMM matrices suggested the three scaling formats used were not burdened with unusual method variance. A reanalysis of the MTMM matrix employing a Confirmatory Factor Analysis technique illustrated that method variance was a problem. Finally, the need for studies that concentrate on the nature of method variance, its causes and effects, is discussed.
METHODS FOR ANALYZING EXPERIMENTS WITH MULTIPLE CRITERIA*
Authors: Messmer Donald J. , Homans Richard E. 
Published: June 2007

AbstractAn approach to analyzing experimental data with multiple criteria is explained and demonstrated on data from a test of the effectiveness of two posters. As a supplement to traditional multivariate analysis of variance and covariance, the application of a step‐down F test is advocated when an ordering of the criterion is meaningful, and an analysis of contrasts is recommended when such an ordering is not managerially relevant. The step‐down procedure has the advantage of simultaneously testing an overall hypothesis and hypotheses on each criterion variable.
STOCHASTIC LINEAR PROGRAMMING WITH RECOURSE: A TUTORIAL*
Authors: Hansotia Behram J. 
Published: June 2007

AbstractPresented here is an introduction to stochastic linear programs with recourse. The paper is by no means a comprehensive survey of the field; that would be an encyclopedic task at best. This paper discusses formulation, interpretation, and computational aspects of stochastic linear programs with simple and fixed recourse. The paper is pedagogical in nature and is aimed to whet the interest of the decision scientist that has little or no background in stochastic programming. Moreover, the papers in this field have appeared in diverse journals not always readily available to the typical management scientist or practitioner and quite often at a very sophisticated mathematical level. For the practitioner, Wets's algorithm for solving stochastic linear programs with simple recourse may be particularly interesting since Wets shows in that paper how the problem can be reduced to an equivalent deterministic linear program of the same dimensionality.
PORTFOLIO MODELING IN MULTIPLE‐CRITERIA SITUATIONS UNDER UNCERTAINTY: COMMENT
Authors: Harrington Thomas C. , Fischer William A. 
Published: June 2007

AbstractIn a recent issue of Decision Sciences, Muhlemann, Lockett, and Gear [8] developed a multiple‐objective, stochastic linear programming formulation of the multiperiod portfolio selection problem under uncertainty. The purpose of this note is to offer some extensions to their multicriteria approach which is otherwise viewed as an excellent attempt at modeling realistic aspects of the portfolio selection problem. Further, integer goal programming combined with simulation is suggested as an alternate approach for solving the dynamic multiple‐objective problem.
ON THE CHOICE OF REALTOR
Authors: Janssen C. T. L. , Jobson J. D. 
Published: June 2007

AbstractThe paper presents a multivariate analysis of single‐family‐home sales data to investigate differences in performance among real estate firms. The decision considered is which firm should be chosen by a homeowner selling through an agent.Factor analysis of property features was used to obtain orthogonal dimensions. This permitted analysis of the influence of other variables with only limited multicollinearity. Broker effects on listing and selling price were studied through regression analysis with dummy variables and slope shifters on the factors and through analysis of variance on the regression residuals after removal of house characteristics. A number of performance differences of consequence for the choice of selling agent were observed. Some of the reasons for these differences are discussed.
ASSESSING THE EXTREMES OF PROBABILITY DISTRIBUTIONS BY THE FRACTILE METHOD*
Authors: Selvidge J. E. 
Published: June 2007

AbstractWhen people are asked to express uncertainty in the form of probability distributions (by assessing several fractiles of the cumulative distributions), experiments have shown that most subjects exhibit systematic biases in describing the extremes or tails of the distributions. This paper discusses methods designed to refine the assessments of such extremes of probability distributions. The techniques were tested on large samples of assessors; the effectiveness of different methods is reported. The methods include asking for the assessment of additional fractiles in the extremes, asking for different fractiles in the extremes (.10 and .90 instead of .01 and .99 fractiles), making the assessment a two‐step process by separating the questions about central fractiles from those requesting extreme values, and varying the order in which different fractile values are requested. All these methods except the two‐step process resulted in improved estimation of the extreme values of the distributions when compared to some of the early work in this field where five fractile assessments were made.
SCHEDULING TO MINIMIZE MAKESPAN ON UNEQUAL PARALLEL PROCESSORS
Authors: De Prabuddha , Morton Thomas E. 
Published: June 2007

AbstractThe problem of scheduling n independent jobs on m unequal parallel processors to minimize makespan is known to be very difficult for the nonpreemptive case. Until recently, research on this problem has consisted primarily of investigating the “worst case” behavior for simple approximation algorithms for the special cases of equal or uniform processors. Recently, Ibarra and Kim [10] have completed a similar analysis on five simple heuristics for general unequal processors. The approach in the present paper is to investigate the “average” behavior via large‐scale computational testing. A new heuristic is devised. It is tested on a large number of problems (about 9,000) for both uniform and general processors, and the results are compared with the best solutions obtained from a truncated branch‐and‐bound procedure. It is observed that, although the heuristic takes negligible time compared to the branch‐and‐bound procedure, on the average it is within 5 percent of the latter in the uniform case and within 1.3 percent in the general case. It also performs better than a composite heuristic whose output, for any given problem, is the best of all previously suggested heuristics.
A MINIMUM‐COST AUDIT SAMPLING METHODOLOGY UNDER CONDITIONS OF PREDETERMINED BETA RISK
Authors: Boockholdt James L. , Finley D. R. 
Published: June 2007

AbstractThis paper presents a minimum‐cost methodology for determining a statistical sampling plan in substantive audit tests. In this model, the auditor specifies β, the risk of accepting an account balance as correct when it is not, according to audit evidence requirements. Using β as a constraint, the auditor then selects a sampling plan to optimize the trade‐off between sampling costs and the costs of follow‐up audit procedures. Tables to aid in this process and an illustration are provided.
A NOTE ON MODELING PROJECT INTERDEPENDENCE IN RESEARCH AND DEVELOPMENT*
Authors: Gear Tony E. , Cowie Grant C. 
Published: June 2007

AbstractThis note is concerned with the problem of resource allocation under uncertainty in a research and development laboratory. A distinction is defined between project interrelationships that are specific (or internal) to certain projects and interrelationships resulting from external environmental factors. Formulations are introduced that allow both types of interrelationships to be formally included in a resource allocation optimization model. In the case of external environmental factors, an example is presented and analyzed.
PERCEIVED INFORMATION STRUCTURE: IMPLICATIONS FOR DECISION SUPPORT SYSTEM DESIGN
Authors: Watkins Paul R. 
Published: June 2007

ABSTRACTTop‐level decision making in business organizations is characterized by high degrees of uncertainty, incomplete information, and conflicting objectives. To support top‐level decision making effectively, decision support systems (DSSs) have been proposed. Information supplied by a DSS must be selective in that not all possible information sets may be feasibly or economically represented in the data base. This study suggests that discovery of perceptual complexity (dimensionality) of information items, and the subsequent categorization of decision makers having the same perceptions of those information items, is a first step in the ultimate design of an effective DSS. Through the use of multidimensional scaling in a field setting, this study shows the feasibility of creating relatively homogeneous groups of decision makers according to the content and number of dimensions associated with various information items. Further results of the research suggest that information can be tailored to classes of users, which has cost‐benefit implications as well as the potential to improve the quality of the resultant decisions.