bluuebunny/crossref_metadata_2025_split huggingface dataset:
A STEPWISE PROCEDURE FOR CONSTRAINED UTILITY MAXIMIZATION*
Authors: Taj Shahram , Willis Cleve 
Published: June 2007

ABSTRACTConstrained utility maximization underlies much consumer behavior in economics. Opportunities for solving important problems are ever present. However, most potential applications remain potential because existing software packages are not able to estimate the systems of equations necessary to identify the utility function. At least three features often conspire to make these problems intractable: the size of the system of equations that must be estimated, the lack of any theory for imposing zero restrictions on many of the parameters of the nonadditive utility functions, and the necessity to insure negative definiteness consistent with the axioms of consumer behavior. This paper develops an approach and illustrates the stepwise least squares estimator of a group of equations by application to the demand for food items.
SCHEDULING PARALLEL PROCESSORS WITH SETUP COSTS AND RESOURCE LIMITATIONS
Authors: Frendewey James O. , Sumichrast Robert T. 
Published: June 2007

ABSTRACTAn integer linear programming model is presented for the scheduling of n products on m identical machines. The particular problem studied is one that occurs frequently in the fiberglass and textile industries. The model incorporates setup costs, lost production costs, and overtime costs. Due to the structure of the model, integer solutions can be obtained by explicitly restricting only a small number of the integer variables. This allows those responsible for scheduling to solve realistically sized problems in an efficient manner. Computational results are provided for a set of generated test problems.
MULTIPLE‐CRITERIA DECISION MAKING INCLUDING QUALITATIVE FACTORS: THE POST‐MODEL ANALYSIS APPROACH
Authors: Lee Jae Kyu , Hurst E. Gerald 
Published: June 2007

ABSTRACTAs a method of solving multiple‐criteria decision making problems with a single quantitative objective and multiple qualitative objectives, the post‐model analysis (PMA) approach is proposed. The essence of PMA is to support the trade‐offs between a quantitative objective and multiple qualitative objectives so that the decision maker can find a perceived most preferred nondominated solution. To this end, the optimal solution of a quantitative model is found first, without regard for qualitative factors. The solution is then evaluated in terms of qualitative objectives. When the initial quantitatively optimal solution is adjusted to allow improvement of qualitative goals, opportunity costs of achieving qualitative goals are incurred. In this process, an expert system and/or graphical display can be used. PMA therefore provides a way to incorporate quantitative models into knowledge‐based expert systems.
Replenishment Analysis in Distribution Requirements Planning*
Authors: Bookbinder James H. , Heath Donald B. 
Published: June 2007

ABSTRACTMost research on lot sizing has been for the case of a manufacturing system. In this paper, analogous issues are studied for a distribution network. Specifically, we consider the choice of shipment quantities within distribution requirements planning (DRP). A simulation model of DRP in a multi‐echelon, rolling‐schedule environment is used to examine, in conditions of both certain and uncertain demand, the performance of five lot‐sizing rules.We conducted a full‐factorial experiment in which four additional parameters were varied: distribution network structure (two options), demand distribution (three options), forecast error distribution (three options), and ordering cost (three values), as suggested by the consulting study which motivated our research.We found that for DRP, contrary to the “shop floor” wisdom on MRP, the choice of lot‐sizing method can be important. Generally the Silver‐Meal and Bookbinder‐Tan heuristics were significantly better than the other methods.
An Empirical Study of Inbound Consolidation Opportunities
Authors: Buffa Frank P. 
Published: June 2007

ABSTRACTThe current deregulated transportation environment has fostered wider freight rate differentials based on shipping weight. As a result, grouping inventory items for the purpose of consolidating inbound replenishment orders can be cost‐effective. The pressure in some industries for just‐in‐time delivery of small lots has also created new opportunities for consolidation of orders. The objective of this research is to identify inventory‐transport conditions where a consolidation strategy has cost‐reduction potential. Logistics cost generated by ordering an ensemble of items consolidated into groups is compared to those generated by two independent, item reorder strategies. Using data from 150 ensembles, the cost‐reduction potential of consolidating was correlated with characteristics of the individual inventory items in an ensemble, a dominant group of items in the ensemble, and the ensemble itself. Finally, response functions were derived and used to test the external validity of the results. For this purpose we used 25 randomly selected inventory ensembles obtained from a retail merchandising firm.
Computer‐Aided Process Structuring Via Mixed Integer Programming
Authors: Klein Gary , Beck Philip O. , Konsynski Benn 
Published: June 2007

ABSTRACTSystems development managers today are working with increasingly complex systems, revealing a need for computer‐aided techniques in software system definition, design, and construction. The ultimate task of the software engineer is the development of tools and procedures which reduce the effort involved in production of effective software. To be effective, software must possess characteristics of correctness, reliability, efficiency, documentation, and flexibility. This paper develops a measure for software effectiveness and a computer aid for determining process structure in program module specification. The proposed method uses various criteria and a mixed integer program to decompose a system graph into program modules.
Identifying the Coarse and Fine Structures of Market Segments
Authors: Dowling Grahame R. , Midgley David F. 
Published: June 2007

ABSTRACTNumerical taxonomy methods have been used to represent marketing data in one of four ways: as discrete groups, dendograms, overlapping groups, or fuzzy classification schemes. This paper introduces a fifth representation—a nested relationship between groups at two (or more) discontinuous levels of aggregation. In the context of a market segmentation application, we call these groups the coarse and fine structures of the market. This paper discusses why this fifth representation is needed and how it differs from existing approaches. The method is illustrated by using it to recover the coarse/fine structures of artificial and actual survey data. The results obtained with the survey data demonstrate the theoretical and practical power of the proposed approach, which provides useful insight into certain marketing decisions. Steps to further validate and extend this new approach to market segmentation are outlined.
Order Promising and the Master Production Schedule*
Authors: McClelland Marilyn K. 
Published: June 2007

ABSTRACTPrevious research on material requirements planning (MRP) systems has rarely considered the impact of the master production scheduling method used to promise customer orders and to allocate production capacity. Based on a simulation study of an MRP environment, we show that the correct selection of a master production schedule (MPS) method depends on the variance of end‐item demand. In addition, we find evidence that the effectiveness of a particular MPS method can be enhanced by holding buffer inventory at the same level in the product structure as in the MPS.
Capacity Management in Health Care Services: Review and Future Research Directions*
Authors: Smith‐Daniels Vicki L. , Schweikhart Sharon B. , Smith‐Daniels Dwight E. 
Published: June 2007

ABSTRACTHealth care has undergone a number of radical changes during the past five years. These include increased competition, fixed‐rate reimbursement systems, declining hospital occupancy rates, and growth in health maintenance organizations and preferred provider organizations. Given these changes in the manner in which health care is provided, contracted, and paid for, it is appropriate to review the past research on capacity management and to determine its relevance to the changing industry. This paper provides a review, classification, and analysis of the literature on this topic. In addition, future research needs are discussed and specific problem areas not dealt with in the previous literature are targeted.
Compensation Schemes, Skill Level, and Task Performance: An Experimental Examination*
Authors: Dillard Jesse F. , Fisher Joseph G. 
Published: June 2007

ABSTRACTThe effect of budget‐based incentive compensation schemes is a fundamental issue in developing and implementing organizational control systems. This study investigates the effect of alternative compensation schemes on performance and satisfaction. A theoretical model outlining the primary relationships is formulated and related hypotheses specified. The hypotheses reflect an integration of agency theory and organization behavior research. Across‐group and within‐group effects are investigated using both single‐period and multiperiod analyses. A laboratory study involving 40 subjects is undertaken and the findings provide insights into the individual and group effects of alternative compensation schemes and the dynamics of changing Compensation schemes on productivity and satisfaction. Specifically, a relationship is found between compensation schemes and performance. The effect on performance is independent of the compensation scheme's perceived fairness. Satisfaction is a function of the congruence between the preferred scheme and the implemented scheme.
Some Extensions of Domain Criteria in Decision Making under Uncertainty*
Authors: Eiselt Horst A. , Langley Ann 
Published: June 2007

ABSTRACTThis paper examines some approaches to decision problems under uncertainty. Starr's [29] domain criterion is presented and modified to take into account different philosophies concerning the desirability of winning versus the importance of avoiding losses. The concept of expected value of distribution information is defined and its computation is illustrated with a numerical example. Target values are then introduced into the model and a parametric procedure is used to maximize the chances of achieving a certain level of the given objective. Finally, we show how the concepts developed in this paper might provide further insight into some decision situations reported in the literature.
A Multiperiod Audit Staff Planning Model Using Multiple Objectives: Development and Evaluation*
Authors: Gardner John C. , Huefner Ronald J. , Lotfi Vahid 
Published: June 2007

ABSTRACTThe audit staff planning problem, a specific type of manpower planning problem, has been modeled using goal programming and, more recently, multiple objective linear programming. Prior studies developed single‐period models and did not go beyond the model building stage. This study develops a multiperiod audit staff planning model and evaluates the model using a test application involving actual decision makers (partners in public accounting firms).The multiperiod model includes seven objectives to be optimized: profit (to be maximized), late completion of work, work declined, staff augmentation, staff reduction, underutilization of the work force, and shortfall in meeting professional development targets (all to be minimized). Over a four‐quarter planning horizon with one “busy season,” the model is subject to constraints with respect to the projected audit work load, ability to substitute personnel and to perform interim audit work, available staff hours (including overtime limitations), supervisory requirements, and professional development targets.Results of the test application showed that the model was capable of producing a range of values for each objective. The participants were exposed to much of that range when making their decisions. The results also showed that all objectives were important and that participants were consistent in choosing their preferred level of each objective over several runs of the model. These results and the reactions of the participants demonstrate that the model is usable by actual decision makers and has potential for a number of specific applications.
Note on Second‐Order Polynomial Regression Models
Authors: Chatterjee Sangit , Greenwood Allen G. 
Published: June 2007

ABSTRACTPolynomial regression models have applications in the social sciences and in business research. Unfortunately, such models have a high degree of multicollinearity that creates problems with the statistical assessment of the model. In fact, the collinearity may be so severe that it could lead to an incorrect conclusion that some of the terms in the model are not statistically significant and should therefore be omitted from the model. This note provides a simple transformation to achieve orthogonality in polynomial models between the linear and quadratic terms, thereby eliminating the collinearity problem. It also shows that the same procedure does not achieve orthogonality for higher‐order terms. An example data set is analyzed to show the benefits of such a procedure.
Solution Procedures for the Lot‐Streaming Problem
Authors: R. Baker Kenneth , F. Pyke David 
Published: June 2007

ABSTRACTLot streaming is the process of splitting a job into sublots so its operations can be overlapped and its progress accelerated. We present a computationally efficient procedure for solving the m‐machine, two‐sublot problem, and we discuss the bottleneck insights that emerge from the analysis. We also examine heuristic approaches for more than two sublots and discuss computational results for these procedures.
Optimal Portfolio Selection Using the General Multi‐Index Model: A Stable Paretian Framework*
Authors: Chamberlain Trevor W. , Cheung C. Sherman , Kwan Clarence C.Y. 
Published: June 2007

ABSTRACTThe problem of selecting optimal portfolios is examined using the general multi‐index model. This model is useful because it allows investors to diversify across different types of assets and thereby exploit or hedge against a wide variety of economic conditions. The analysis is carried out in a stable Paretian framework with and without short sales. As such, it not only encompasses the mean‐variance results for a variety of index models as special cases, but also provides a broad framework for applying the arbitrage pricing theory to portfolio decision making.
On Sampling Error in Market Share Estimates*
Authors: Coopersmith Lewis , Klein Steven W. 
Published: June 2007

ABSTRACTThe relative error in the usual estimator of a brand's market share is reformulated in terms of marketing parameters. Such error is shown to be influenced in an important way by market penetration, as well as by variation in brand and product category volume. Of particular interest is the result that the relative error does not depend on the actual share level. Using data from a marketing research firm that supplies share estimates to the health products industry, we find that the relative error may be substantial even when a large sample is available. An upper bound on this relative error is obtained using marketing parameters that can frequently be measured using industry data and a company's internal records, thus reducing the level of judgmental input required in the planning of sample surveys.
Analysis and Approximation of a JIT Production Line: A Comment
Authors: Berkley Blair J. 
Published: June 2007

ABSTRACTA recent Decision Sciences article by Jordan [9] presented a Markov‐chain model of a just‐in‐time (JIT) production line. This model was used to estimate average inventories and production rates to find the optimal number of kanbans. Results for expected production rate were found to be consistently lower than those obtained by Huang, Rees, and Taylor [8] in a previous Decision Sciences article. Jordan attributed this unexpected outcome to some procedural problems in Huang et al.'s simulation methodology. In this paper, Markov‐numerical analysis is used to compare the performance of Jordan's and Huang et al.'s methods of production control. Simulation analysis is then used to determine the effects of finite withdrawal cycle times. Results show that, for equal numbers of kanbans, Huang et al.'s two‐card method of production control provides substantially greater expected production rates than Jordan's method. These results suggest that the Jordan model should not be applied to the problem of setting kanban numbers on manual JIT lines. Finally, we comment on the efficiency of Jordan's iterative method to obtain performance measures of tandem queues.
AHP Is Intended for More Than Expected Value Calculations
Authors: Forman Ernest H. 
Published: June 2007

ABSTRACTIn a previous paper, Schoner and Wedley [9] presented a way to automatically compute the importance of criteria from the values of alternatives. The following discussion illustrates that the approach of [9] can only be applied if the alternatives under the criteria are measured with a single absolute scale. However, when this does occur, in part or in all of a decision problem, the approach is extraneous. The measurements can (and should) first be combined with the appropriate arithmetic of that scale which reduces that part of the problem to a single dimension and the result can be taken up with the remaining dimensions for consideration with AHP.
Resource Flexibility Issues in Multistage Manufacturing
Authors: Malhotra Manoj K. , Ritzman Larry P. 
Published: June 2007

ABSTRACTWe test the situational impact of two types of resource flexibility, machine flexibility and labor flexibility, in a material requirements planning (MRP)‐driven production system. Machine flexibility has not been treated in prior multistage research, only labor flexibility. Machine flexibility is closely related to a plant's positioning strategy. A process‐focused plant opts for considerable machine flexibility by choosing general‐purpose equipment. Resource flexibility, if effective, can be an attractive alternative to two other types of buffers, inflated inventories and costly capacity cushions.Our simulation results, using factor settings established earlier by a panel of managers, show that resource flexibility is indeed an effective buffer against uncertainties such as end‐item demand variability, capacity bottlenecks, equipment failures, and yield losses. Machine flexibility is especially helpful in environments characterized by high uncertainties, tight capacities, and large lot sizes. Worker flexibility has a similar, but less dramatic, impact. Benefits are most striking with customer service, rather than with inventory or labor productivity. Finally, we show that simultaneous introduction of both machine and labor flexibility yields only marginal improvements over either kind of flexibility alone.
Relative Objective Functions in Multiobjective Decision Support Models*
Authors: Schenkerman Stan 
Published: June 2007

ABSTRACTThis paper considers the importance of using the nondominated minimum in forming relative objective functions. Other minima can prevent the decision maker from reaching a preferred decision. They disturb the zero and distort the scale, thereby misguiding the decision maker by falsifying trade‐off possibilities. Worse, some of these other minima can inadvertently hide whole regions of preferred solutions. Zeleny's multiple criteria simplex method is used to find the nondominated minimum for the linear case.
A Framework for the Analysis of Error in Conjunctive, Multi‐Criteria, Satisficing Decision Processes*
Authors: Ballou Donald P. , Pazer Harold L. 
Published: June 2007

ABSTRACTThis paper examines the impact of certain types of error on ad hoc, unstructured decision making that incorporates a satisficing strategy in a multi‐criteria context using the conjunctive rule. The impacts of error in evaluation and of error in minimal or satisficing levels are systematically modelled for each of the decision criteria. Error functions, analytical expressions, and procedures are developed to obtain information such as the likelihood of correct decision making in the presence of evaluation and minimal criteria level error. These are applied to a specific research design, which is then analyzed. This highlights certain features of decision making in a satisficing context, such as the importance of keeping the number of decision criteria to a minimum. The results yield various insights, some of which confirm information obtained from previous analyses. A major advantage of the framework presented is that it can provide quantitative measurements which support ideas previously couched in qualitative terms only. Although the framework is applied in the context of decision making that uses the conjunctive rule in the case of multiple criteria, other satisficing strategies can be accommodated as well.
An Investigation of Equity as a Determinant of User Information Satisfaction
Authors: Joshi Kailash 
Published: June 2007

ABSTRACTThis paper reviews equity theory and proposes that perceived inequity in the allocation of management information systems (MIS) resources is likely to influence overall user information satisfaction (UIS). Therefore, in addition to currently identified factors such as quality of information products (QIP), user's knowledge and involvement level (KIL), and EDP staff and services (ESS), equity is also likely to be a relevant factor in determining overall UIS. The paper reports on a cross‐sectional survey to obtain data for testing the relevance of equity related issues in the MIS context. Responses from 226 users showed a strong correlation (.67, p > .001) between equity and overall UIS. Further, the addition of equity to the previously identified factors that influence overall UIS (i.e., QIP, KIL, and ESS) significantly increased the explained variance (from .48 to .56). The results support the relevance of equity related issues in determining user attitudes. It is recommended that MIS researchers and professionals take into account the likely influence of equity perceptions on user attitudes and behavior, and strive to develop and implement equitable resource allocation mechanisms. Implications of the findings for future research in the areas of MIS, UIS construct, systems implementation, and management of MIS are also discussed.
A Comparison of Due Date Setting, Resource Assignment, and Job Preemption Heuristics for the Multiproject Scheduling Problem*
Authors: Bock Douglas B. , Patterson James H. 
Published: June 2007

This research examines a heuristic, rule‐based approach for setting due dates in a multiproject, multijob, or assembly shop. Due date estimation is a challenging problem because the operating environment is capacitated, involves the allocation of multiple resources, and allows for the preemption of resources from one project or job to another. The dynamic, continuous arrival of new jobs or orders frequently results in the preemption of resources through the application of managerially determined priority policies. These preemption policies have a significant impact on the ultimate completion time of a job or a project.A three‐factor, full‐factorial computer simulation experiment is used to assess the relative effectiveness of combinations of four due date setting heuristics, five resource assignment heuristics, and three resource preemption heuristics. Recommendations are made for the selection of due date and resource assignment heuristic combinations under the three preemption policies examined.