bluuebunny/crossref_metadata_2025_split huggingface dataset:
ORGANIZATIONAL CONTEXT, USER INVOLVEMENT, AND THE USEFULNESS OF INFORMATION SYSTEMS*
Authors: Franz Charles R. , Robey Daniel 
Published: June 2007

ABSTRACTThis study investigates organizational factors related to user involvement in information system development and perceived system usefulness. Using a sample of 118 usermanagers in 34 companies, the results show that user involvement in design and implementation is related positively to users' perceptions of system usefulness. However, organizational factors were not found to be related significantly to user involvement, as had been originally hypothesized. Rather, organizational factors either had a direct relationship with perceived usefulness or moderated the relationship between involvement and usefulness. Two factors reflecting an MIS department's maturity (size and age) were found to reduce users' perceptions of system usefulness. Also, users at higher levels and those making more structured decisions found their systems more useful, although the user's level was found to moderate perceptions of system usefulness during the design stage. Three other organizational factors (level of MIS manager, MIS department scope, and decentralization of authority) also were found to have moderating effects.
COMPUTERIZED INFORMATION SYSTEMS SUPPORTING MULTICRITERIA DECISION MAKING*
Authors: Minch Robert P. , Sanders G. Lawrence 
Published: June 2007

ABSTRACTThis paper addresses two issues critical to the success of decision support systems in multiattribute/multicriteria decision‐making contexts. A relationship is established between normative (prescriptive) work in the area of multicriteria decision making and behavioral (descriptive) decision research involving choice strategies. A conceptual system architecture based on the state‐space approach to problem solving is presented. This architecture will enable decision makers to incorporate both prescriptive and descriptive strategies in the course of computer‐aided multiple alternative/attribute problem resolution.
A COMPARISON OF LEARNING CURVE ANALYSIS AND MOVING AVERAGE RATIO ANALYSIS FOR DETAILED OPERATIONAL PLANNING*
Authors: Smunt Timothy L. 
Published: June 2007

ABSTRACTThis study tests the use of learning curve analysis for production planning at the detailed component level under various conditions, represented by factors of product turnover rate, learning rate, variance levels, and planning horizon length. It also presents an alternative to learning curve analysis that considers aggregation of cost data across time. This alternative is periodic revision of standard cost data using moving average forecasts to reflect productivity trends. Results of this study indicate that in most circumstances a moving average analysis can provide better estimates of short‐term, detailed component operations costs than either a learning curve analysis or a standard analysis.
IMPACT OF PARTICIPATION IN THE BUDGETARY PROCESS ON MANAGERIAL ATTITUDES AND PERFORMANCE: UNIVERSALISTIC AND CONTINGENCY PERSPECTIVES*
Authors: Govindarajan Vijay 
Published: June 2007

ABSTRACTData from responsibility‐center managers reveal that greater budgetary participation contributes to managerial performance and attitudes in high‐environmental‐uncertainty situations but hampers performance and attitudes in low‐uncertainty situations. Higher budgetary participation reduces managers' propensity to create slack in high‐ (but not in low‐) uncertainty conditions.
AN EMPIRICAL EXAMINATION OF THE BIASING EFFECTS OF FRAMING ON BUSINESS DECISIONS*
Authors: Mowen Maryanne M. , Mowen John C. 
Published: June 2007

ABSTRACTThis paper presents results of three studies testing whether decision bias due to framing, found in consumer purchase contexts, also would occur in a business setting. In the first study, business‐student subjects displayed framing‐induced decision bias just as subjects had in an earlier study by Tversky and Kahneman [12]. When the consumer problem was recast into a business decision in the second study, student subjects trained to handle the problem still revealed bias, although to a lesser extent. In the third study, experienced business managers revealed the same pattern of decision bias as the student subjects. Implications of this bias for business decision makers are discussed.
INFORMATION CHANNEL DISPOSITION AND USE*
Authors: Swanson E. Burton 
Published: June 2007

ABSTRACTThe use of information channels by individuals in organizations is substantially discretionary. Although much studied, variation in patterns of discretionary use has yet to be explained adequately in terms of an accepted integrative theory validated across varieties of channel types and organizational settings. In a step toward the development of such a theory, the present paper proposes a basic channel‐disposition model that relates an individual's attitude or disposition toward a channel to his/her actual use of the channel in the context of information and channel supply‐and‐demand structures in the organization. An exploratory study of the dispositions of 186 users of ten management information system (MIS) reports in four organizational settings provides limited evidence in support of the model proposed.
A KNOWLEDGE‐BASED DSS FOR MANAGERIAL PROBLEM DIAGNOSIS
Authors: Courtney James F. , Paradice David B. , Ata Mohammed Nassar H. 
Published: June 2007

ABSTRACTA knowledge‐based system supporting managerial problem diagnosis is described. The system provides the capability to monitor values of selected variables for problem situations. When problems are located, a list of problem symptoms is delivered to a problem processor for structuring and diagnosis. Problem structuring is based on a combination of concepts from expert systems and structural modeling. User assertions about cause‐effect relationships between pairs of variables are maintained in a semantic network. Problem diagnosis uses the relationships in the semantic network to construct causation trees, the branches of which represent potential explanations of the problem symptoms. Mathematical models are constructed based on causation‐tree branches, and values from the data base are used to test whether the model confirms the diagnosis. If so, the source of the problem has been located and it is then up to the user to resolve the problem. If the model fails to explain the problem, the model apparently is deficient and the user may perform “what if…” type scenarios in attempts to improve the model and search for problem causes. Realistic applications in the accounting and health care areas are discussed.
PERFORMANCE DIFFERENCES IN THE USE OF GRAPHIC AND TABULAR DISPLAYS OF MULTIVARIATE DATA
Authors: MacKay David B. , Villarreal Angelina 
Published: June 2007

ABSTRACTIt has been suggested that graphically displayed multivariate data help decision makers better understand information they are called on to analyze. This study compares judgments made from one recently suggested multivariate display technique with judgments made from traditional tabular displas of financial figures. Significant differences in task performance are found to be related both to differences in the stimulus sets and to individual differences among the subjects. Our results suggest that the relative contribution of graphic displays to decision making may vary considerably from situation to situation.
USING A LATE‐START RESOURCE‐CONSTRAINED PROJECT SCHEDULE TO IMPROVE PROJECT NET PRESENT VALUE*
Authors: Smith‐Daniels Dwight E. , Aquilano Nicholas J. 
Published: June 2007

ABSTRACTAlthough literature on the achievement of monetary objectives in a resource‐constrained project environment is limited, the maximization of project net present value (NPV) is an important criterion of project success. This paper presents a procedure for developing a late‐start resource‐constrained project schedule using the critical path method‐material requirements planning. Using an extensive set of problems from the literature, we show that this procedure yields a higher NPV and lower average duration than schedules derived with heuristics that schedule each activity as early as possible. In addition, while the late‐start schedule on average was significantly longer than the optimal‐duration resource‐constrained schedule, no significant difference occurred in the average NPVs of the two scheduling methods.
AN IMPLICIT/EXPLICIT APPROACH TO MULTIOBJECTIVE OPTIMIZATION WITH AN APPLICATION TO FOREST MANAGEMENT PLANNING*
Authors: Harrison Terry P. , Rosenthal Richard E. 
Published: June 2007

ABSTRACTImplicit utility/value maximizationandexplicit utility/value maximizationare identified as two major classes of multiobjective optimization methods. Explicit methods have the advantage of being able to fully exploit the power of existing mathematical programming algorithms. A disadvantage is the high information burden they place on the decision maker. Implicit (i.e., interactive) methods have complementary strengths and weaknesses: they require less extensive information but do not lend themselves as easily to use with optimizing algorithms. We develop a hybrid implicit/explicit approach that attempts to combine the advantages of both by embedding within the implicit method a procedure that periodically formulates an approximate explicit representation of the multiobjective problem and then solves it optimally without user interaction. Operationally, this requires the frequent solution of two nonlinear programs.We also report on the implementation of this method in a forest management decision support system. This is a completely microcomputer‐based implementation currently undergoing field testing for use in planning the timing and intensity of timber harvests on non‐industrial forests in the southeastern United States. The system has been selected as a replacement for an earlier multiobjective program (Harrison and Rosenthal [28]) used by over 1,800 landowners.
A NEW CLASS OF MODELS FOR THE DISCRIMINANT PROBLEM
Authors: Glover Fred , Keene Sam , Duea Bob 
Published: June 2007

ABSTRACTDiscriminant analysis is relevant to business decision making in a variety of contexts, such as when one decides to make or buy a specified component, fund a venture project, or hire a particular person. Potential applications in artificial intelligence, particularly in the area of pattern recognition, have further underscored the importance of the field. A recent innovation in discriminant analysis is provided by special linear programming (LP) models, which offer attractive alternatives to classical statistical approaches. The scope of application in which discriminant analysis can be advantageously employed is broadened by the flexibility to tailor parameters in the LP approaches to reflect diverse goals and by the power to explore the sensitivity of these parameters. In spite of the promise of the LP formulations, however, limitations to their effectiveness have been uncovered in certain settings. A recent advance involving a normalization construct removes some of the limitations but entails solving the LP model twice (to allow for different signs of a normalization constant) and does not yield equivalent solutions for different rotations of the problem data. This paper introduces a new model and a new class of normalizations that remedy both remaining limitations, making it possible to take advantage of the modeling capabilities of the LP formulations without the attendant shortcomings encountered by earlier investigations. Our development shows by empirical testing and illustrative analysis that the quality of solutions from LP discriminant approaches is more favorable (relative to the classical model) than previously supposed.
A CONJUNCTIVE‐COMPENSATORY APPROACH TO THE SELF‐EXPLICATION OF MULTIATTRIBUTED PREFERENCES*
Authors: Srinivasan V. 
Published: June 2007

ABSTRACTConsumer choice among multiattributed products is modeled as a two‐stage process in which a conjunctive stage (that eliminates products with one or more “totally unacceptable” attribute levels) is followed by a compensatory stage (that trades off remaining products on multiple attributes). A self‐explicated preference measurement procedure based on the two‐stage model yielded a slightly larger predictive validity compared to conjoint analysis.
MULTIDIMENSIONAL ASSIGNMENT PROBLEMS
Authors: Gilbert Kenneth C. , Hofstra Ruth B. 
Published: June 2007

ABSTRACTEach of the many two‐dimensional variations of the classical assignment problem has at least one counterpart in higher dimensions. This paper is a tutorial on these higher dimensional assignment models and their applications. It is a synthesis of a vast literature scattered throughout a great variety of journal articles and other miscellaneous sources.We have attempted to make the paper a complete bibliography with the emphasis on topics important to practitioners of decision sciences. These topics include original results by the authors, most notably, a polynomial solution approach for a class of multidimensional assignment problems which often arise in scheduling applications.
IMPLICIT OPTIMAL AND HEURISTIC LABOR STAFFING IN A MULTIOBJECTIVE, MULTILOCATION ENVIRONMENT*
Authors: Bechtold Stephen E. 
Published: June 2007

ABSTRACTThis paper presents a tractable set of integer programming models for the days‐off scheduling of a mix of full‐ and part‐time employees working α to β days/week (cycle) in a multiple‐objective, multiple‐location environment. Previous models were formulated to specifically schedule part‐time employees working either two or three days per week. These models were intractable because they required complete employee schedule information. The new models are deemed implicit optimal since they are required to supply only essential information. While the number of variables in previous models is an exponential increasing function of β‐α, the size of three of the new models is independent of α and β.The first three models developed here (as in [18]) deal with the trade‐offs between idle time, the number of employees required to work at multiple “locations,” and the size of the total labor pool. The inherent flexibility of the implicit modeling approach is illustrated by the presentation of various modifications of the basic models. These modifications permit the use of preference weights on the number of employee work days/week (cycle) or the minimization of payroll costs where differential pay rates exist. These latter models may also be formulated such that idle time is ignored, constrained or minimized.The execution time for the implicit models (on a CDC CYBER 730 computer with commercially available software) averaged well under five seconds on 1200 trial problems for the type of application considered in [18]. A solution was obtained in less than 46 seconds of CPU time for a trial problem which would have required over 1.4 million integer variables with previous models.The availability of optimal solutions was invaluable in the development of two heuristics designed to deal with the trade‐offs of [16]. In an experimental analysis a previous heuristic produced results which averaged from 74 to 508 percent above optimum across six experimental conditions. The comparable new heuristic produced results which averaged from 3 to 8 percent above optimum for the same experimental conditions.The paper concludes by developing a framework to integrate the results of this research with the tour scheduling problem and by identifying several other areas for related research.
A Stochastic, Psychometric Valuation Model for Personnel Selection Systems*
Authors: Wyer Jean C. 
Published: June 2007

ABSTRACTThis paper describes a method for the valuation of personnel selection systems that is based on contributions from accounting, utility theory, psychometric techniques, Markov processes, labor economics, and present‐value analysis. The model developed here can be used by managers to assess the usefulness of proposed selection procedures. It extends previous work in the area by including both the stochastic nature of the employment process and the time value of the associated costs and benefits.
Alternate Routing Strategies in Batch Manufacturing: An Evaluation
Authors: Bobrowski Paul M. , Mabert Vincent A. 
Published: June 2007

ABSTRACTBatch manufacturing firms are experiencing significant changes because of technological developments in work center design, such as flexible manufacturing systems (FMS) and planning/control tools like computer‐aided process planning (CAPP). These new developments provide production managers with some solutions to a number of complex problems. For example, numerical‐controlled (NC) machine center installations are effective in providing quality parts because of tight tolerance specifications built into the equipment. However, these highly efficient centers create bottlenecks that constrain shop throughput, since production planners tend to rely too much on them.To help improve manufacturing planning, we introduce an important element to the batch production scheduling component of CAPP's mission—evaluating possible alternate routes. Production scheduling encompasses job route selection as well as machine center assignment (loading), job releasing, and setting due dates. In this paper, three routing strategies requiring different levels of shop floor information are tested and evaluated using computer simulation. Shop performance is measured by total cost and traditional measures of job flow time, lateness, and tardiness.
An Experimental Analysis of Capacity‐Sensitive Setup Parameters for MRP Lot Sizing
Authors: Raturi Amitabh S. , Hill Arthur V. 
Published: June 2007

ABSTRACTMost material requirements planning (MRP) systems apply standard costing (absorption costing) approaches to define setup costs that are used as fixed (time invariant) setup parameters in single‐level lot‐sizing methods. This paper presents a computationally simple approach for estimating more appropriate setup parameters based on estimates of work‐center shadow prices. These setup parameters then are used in traditional single‐level MRP lot‐sizing procedures.The shadow price of capacity at each work center is calculated as the increase in the overall inventory carrying cost for each additional hour of capacity lost to setups. The opportunity cost of a setup for an order subsequently is determined based on the routing information for each order and is used by traditional MRP lot‐sizing procedures to calculate lot sizes.A simulation experiment compares the performance period order quantity lot sizing with capacity‐sensitive setup parameters with the fixed accounting‐based setup parameters. The simulation replicates the planning and control functions of a typical MRP system. The results of the experiment show that capacity‐sensitive setup parameters can make significant reductions in both carrying cost and lateness and can achieve many of the benefits of optimized production technology in the context of an MRP system.
An Examination of Two Screen/Report Design Variables in an Information Recall Context*
Authors: Umanath Narayan S. , Scamell Richard W. , Das Sidhartha R. 
Published: June 2007

ABSTRACTScreen/report design for output organization is still very much a common sense‐driven activity. This paper identifies a preliminary set of factors beyond display format for examination as screen/report design variables. A laboratory experiment was conducted to assess the influence of one of these factors, spatial layout of information, along with display format in an information recall context. Individual imagery orientation (verbalizer/visualizer) was used as a moderating variable in the experimental design. The findings indicate that spatial layout of information significantly influenced performance when the recall task involved pattern detection. In fact, a central location of data in a document was the most conducive to pattern recall performance. Further, terminal items facilitated pattern recall better than early input items. With respect to display format, the results support previous findings that a tabular display enhances performance for point‐value recall tasks while graphs exhibit an edge over tables for pattern types of recall tasks. Overall, the verbalizers demonstrated a complete supremacy in performance. Interaction between individual imagery orientation and display format indicates that, while the verbalizers and the mixed type were immune to display format variations, the graphical stimulus enhanced the pattern recall performance of the visualizers.
An Approximate Solution to Deterministic Kanban Systems
Authors: Moeeni Farhad , Chang Yih‐Long 
Published: June 2007

ABSTRACTThis paper presents a simple heuristic for computing the number of kanbans in a kanban system. The production systems under consideration have a multistage, uncapacitated, assembly tree structure, with every stage producing only one item at a time. The experimental results show that this method generates very good solutions. In more realistic problems where the master production schedule incorporates a smoothed demand, the solution found under the proposed method is identical to that of the linear programming approximation. This simple heuristic can be used in the real world to quickly determine the number of kanbans for daily just‐in‐time operations.
A Multiobjective Approach and Empirical Application of Sales‐Organization Design
Authors: Mahajan Jayashree , Vakharia Asoo J. 
Published: June 2007

ABSTRACTThis paper addresses the critical issue of determining the appropriate structural design of a sales organization. We propose a new approach for organizing the selling function using multiobjective modeling techniques. The proposed approach considers the situational characteristics under which the sales organization operates, trade‐offs among multiple sales‐effectiveness criteria, and the “fit” between the situational characteristics and the structural dimensions (i.e., the structure‐contingency relationships). Using data collected from sales branches of brokerage firms, we develop appropriate structural designs for a sales organization using the proposed procedure. The paper concludes by outlining the various decision‐making implications of the approach.
Improved Linear Programming Models for Discriminant Analysis*
Authors: Glover Fred 
Published: June 2007

ABSTRACTDiscriminant analysis is an important tool for practical problem solving. Classical statistical applications have been joined recently by applications in the fields of management science and artificial intelligence. In a departure from the methodology of statistics, a series of proposals have appeared for capturing the goals of discriminant analysis in a collection of linear programming formulations. The evolution of these formulations has brought advances that have removed a number of initial shortcomings and deepened our understanding of how these models differ in essential ways from other familiar classes of LP formulations. We will demonstrate, however, that the full power of the LP discriminant analysis models has not been achieved, due to a previously undetected distortion that inhibits the quality of solutions generated. The purpose of this paper is to show how to eliminate this distortion and thereby increase the scope and flexibility of these models. We additionally show how these outcomes open the door to special model manipulations and simplifications, including the use of a successive goal method for establishing a series of conditional objectives to achieve improved discrimination.