bluuebunny/crossref_metadata_2025_split huggingface dataset:
UNSUCCESSFUL IMPLEMENTATION THE CASE OF A COMPUTER‐BASED ORDER ENTRY SYSTEM
Authors: Lucas Henry C. 
Published: June 2007

ABSTRACTThis paper discusses results of a longitudinal field experiment to evaluate the implementation of a computer‐based system. This new system includes the introduction of an optically scanned order input form and new computer programs. It is hypothesized that successful implementation would be affected by the quality of service and the personal costs and benefits to the users of the new system. The experimental results show a marked reduction in job satisfaction after implementation of the new system. The implications of the findings for the implementation of computer‐based systems in general are discussed.
OPTIMAL RENEGING DECISIONS IN A G/M/1 QUEUE
Authors: Parkan Celik , Warren E. H. 
Published: June 2007

ABSTRACTThis paper is an analysis of the optimal reneging decision of a customer who joins a G/M/1 queue, having imperfect information about the queue. It is assumed that a customer receives a constant, known reward upon completion of service and incurs a cost proportional to the time spent in the queueing system. It is also assumed that a customer revises his estimated remaining waiting time in the system based on his initial estimate and observations of service time. Thus, a customer will renege when his estimated cost of remaining in the system exceeds his reward. The probability of a customer reneging during any given service is determined. Finally, it is shown how this probability varies with the parameters of the customer.
OPTIMAL INVENTORY STOCKING LEVELS WITH DEMAND TRANSFERENCE AMONG PRODUCTS
Authors: Matthews John P. 
Published: June 2007

ABSTRACTWhen a product is temporarily unavailable it is not uncommon to find consumers buying a related product rather than postponing the purchase until the former is back in stock. This phenomenon may be observed in the sale of cigarettes, candy bars, different‐sized packages of milk, lawn fertilizer, brands of wine and a host of other consumer items. This paper suggests a model for the vendor to employ when seeking to opti mize his stocking strategy for a periodic review/replenishment system.
THE EFFECTS OF GAME COMPLEXITY ON THE ACQUISITION OF BUSINESS POLICY KNOWLEDGE *
Authors: Wolfe Joseph 
Published: June 2007

ABSTRACTCertain cognitive and affective results obtained by three increasingly complex business games were examined. All simulations taught facts and concepts but the most complex simulation produced the greatest effect. More game complexity also brought about heightened challenge, lesser monotony, and greater decision‐making comprehensiveness. Motivational and learning levels, however, were not linearly positive with increasing complexity. The intermediate game was as motivating as the complex one although it was inferior to the simple game as a teaching device. The complex game also experienced higher student mortality.
A COMPUTER SIMULATION APPROACH TO THE TEACHING OF MAIL SURVEY STRATEGY ALTERNATIVES AND CHOICE
Authors: Burns Alvin C. 
Published: June 2007

ABSTRACTThe author uses a computer simulation of mail questionnaire response rates to acquaint students with trade‐offs in terms of survey cost, accuracy, and time. In the absence of a theoretical base in the literature, the approach familiarizes students with current issues and problems, and helps to develop a decision‐making framework for this survey method. A step‐by‐step procedure emphasizing student involvement is described.
DESIGN OF AN M.B.A. SEMINAR ON THE IMPLEMENTATION OF OPERATIONS RESEARCH/MANAGEMENT SCIENCE *
Authors: Robey Daniel 
Published: June 2007

ABSTRACTThis paper reports on an innovative seminar in which implementation of operations research and management science was the primary theme. Traditional educational strategies have sought to improve OR/MS acceptance by further exposing managers and management scientists to OR/MS techniques and management problems respectively. The present approach assumes that an understanding of the barriers to successful implementation and a knowledge of possible strategies for overcoming them are potentially more productive than the study of more OR/MS techniques. The seminar was designed to combine straightforward reading and discussion with empirical research on actual implementation situations. It is suggested that educators consider the value of this type of educational exercise in OR/MS curricula and M.B.A. programs.
COMMENTS ON GLOUDEMANS AND MILLER'S MULTIPLE REGRESSION ANALYSIS APPLIED TO RESIDENTIAL PROPERTIES
Authors: Brobst Robert , Gates Roger 
Published: June 2007

ABSTRACTGloudemans and Miller [6] provide an interesting and useful application of regression analysis to the problem of residential property assessment. However, there are a number of problems with their model. These problems include: failure to consider the pitfalls of using stepwise regression in exploratory studies; failure to discuss levels of significance and appropriateness of signs of individual regression results; the use of ordinal data in the regression analysis; the use of an obscure and incorrect procedure for inflation adjustment; and, a general lack of a priori reasoning in the development and analysis of the article. These problems are discussed and possible remedies are considered.
MULTIPLE REGRESSION ANALYSIS APPLIED TO RESIDENTIAL PROPERTIES A REPLY
Authors: Gloudemans Robert J. 
Published: June 2007

ABSTRACTThe reviewers' [1] comments generally relate to the design and development of multiple regression‐based appraisal models, a subject area of great promise and open to further research, although somewhat broader than the specific issues addressed in the authors' paper [5]. The purpose of this reply is to briefly restate the nature and conclusions of that paper and to offer comment upon the broader, more important, questions of model development raised by the reviewers.
TREATMENT PLANNING MODELS: AN APPLICATION *
Authors: Leonard Michael S. , Kilpatrick Kerry E. 
Published: June 2007

ABSTRACTThis paper presents a systematic approach to treatment planning using an analytical model of the underlying decision‐making activity. Patient diagnostic classifications, augmented by a history of prior treatment applications, provide the state descriptions for a Markovian decision model of the treatment‐selection process. Patient records from four university dental clinics serve as the data base for model construction and validation.This analytical model provides a means of duplicating the treatment plans of experts. Approximately 93% of the treatment planning model's treatment selections concurred with decisions made by two dental educators. Moreover, the models permit an examination of the critical considerations associated with therapy selection. This capability is discussed in terms of possible applications of the model in the practice of dentistry and in teaching.
A BEHAVIORAL STUDY OF NURSES, SUPERVISORS, AND DIAGNOSTICIANS IN A HOSPITAL SETTING
Authors: Lyon Herbert L. , Ivancevich John M. 
Published: June 2007

ABSTRACTA hospital is a highly complex organization that is based on the mutual cooperation of a large and heterogeneous mix of interdependent professionals, semiprofessionals, and nonprofessionals. The present study focuses upon role clarity, need for clarity, job satisfaction, and anxiety‐stress perceptions among administrators, nurses, and diagnosticians in a large and complex 450‐bed teaching‐referral hospital.
FORECAST MODIFICATION BASED UPON RESIDUAL ANALYSIS: A CASE STUDY OF CHECK VOLUME ESTIMATION
Authors: Mabert Vincent A. 
Published: June 2007

ABSTRACTThe inability to identify all causal variables in a linear regression demand model may result in serial correlation which is generally considered undesirable; but it may be possible to take advantage of such an event. This case study, based upon Chemical Bank of New York, investigates the use of simple and exponential smoothing for modifying initial estimates from a regression model by using prior forecast error patterns to obtain better forecasts. The smoothing approaches are combined with a regression model to test for improved performance in predicting daily check volumes.
BARGAINING BEHAVIOR IN A BUSINESS SIMULATION GAME *
Authors: Slusher E. Allen , Sims Henry P. , Thiel John 
Published: June 2007

ABSTRACTThree studies of labor‐management negotiations were conducted within the context of a business simulation game. Face‐to‐face bargaining lasted approximately two hours and resulted in settlements that were incorporated into the simulation game parameters. A total of 56 simulated companies, each comprised of five MBA students, were studied. Results from the first study showed that extending low initial offers, extracting large first concessions, and making a high number of concessions were management bargaining tactics associated with obtaining a low wage rate. These findings were supported by study two. The third study found that an intrateam power mode of orientation was positively correlated with bargaining success and was negatively correlated with overall game success. The results support the use of a simulation game for teaching and research in bargaining.
OPTIMAL SELECTION OF MATCHED PAIRS FROM LARGE DATA BASES
Authors: Sibley A. M. , Burch E. Earl 
Published: June 2007

ABSTRACTThis paper considers the problem of selecting matched pairs of observations for the reduction of bias in statistical hypothesis testing. A Euclidean distance function is suggested for measuring the similarity between paired observations. The matching process is then formulated initially as an assignment problem. Alternative formulations of the problem that would reduce computational difficulty are considered.
HEURISTIC LOT‐SIZING AND SEQUENCING RULES IN A MULTISTAGE PRODUCTION‐INVENTORY SYSTEM
Authors: Biggs Joseph R. 
Published: June 2007

ABSTRACTMaterial Requirements Planning (MRP) is currently being applied and used extensively in industry and is being proclaimed as the solution to many of the problems of traditional production‐inventory control problems. While the latter may be true, MRP is not without its own problems, two of which are the decisions concerning the appropriate lotsizing and sequencing rules to use in order to improve system performance. This paper describes a computer simulation study which was conducted to determine the effects of using various sequencing and lot‐sizing rules on various performance criteria in a multistage, multiproduct, production‐inventory system using MRP.The results of the study indicate that the application of various rules causes changes in system performance and that an interaction effect exists between lot‐sizing and sequencing rules. What is more important is that a set of guidelines is developed to enable the practitioner to choose a lot‐sizing rule and a sequencing rule that will tend to improve the performance of his system for the various performance criteria.
EFFECTS OF LEARNING ON RESOURCE ALLOCATION DECISIONS
Authors: Liao Woody M. 
Published: June 2007

ABSTRACTLearning curves have important implications for managerial planning and control. This paper considers the effect of learning on managerial planning models for productmix problems that can be handled by a linear‐programming formulation. An approach to incorporate learning effects in the planning model is proposed in this paper. The feasibility and superiority of the proposed approach over the traditional approach are discussed through the use of a linear‐programming problem.
A STOCHASTIC DOMINANCE ORDERING OF SCHEDULING RULES
Authors: Weeks James K. , Wingler Tony R. 
Published: June 2007

ABSTRACTThis paper applies stochastic dominance (SD) preference‐ordering criteria to job shop scheduling rules. A simulation model of a hypothetical dual‐constrained job shop is used to derive several measures of shop performance for a number of dispatching/due‐date scheduling policies. The results presented suggest that previous research conclusions concerning the relative performance of dispatching scheduling rules may need to be reconsidered if production schedulers are risk‐averse utility maximizers.
USE OF OPTIMIZATION AND SIMULATION MODELS TO ANALYZE OUTPATIENT HEALTH CARE SETTINGS*
Authors: Carlson Robert C. , Hershey John C. , Kropp Dean H. 
Published: June 2007

ABSTRACTAn important problem facing the manager of an outpatient health care clinic involves determining the best combination of services, facilities, and personnel to maximize profits and simultaneously achieve acceptable measures of the clinic's daily performance. This problem is often attacked using either linear programming or computer simulation. This paper uses a recursive optimization‐simulation approach which takes advantage of the best features of both optimization and simulation while minimizing the disadvantages of each method used alone. Results from a hypothetical setting using data from several actual settings demonstrate the value of the recursive method.
MODEL FORMULATION FOR FLEET SIZE ANALYSIS OF A UNIVERSITY MOTOR POOL
Authors: Williams William W. , Fowler Oscar S. 
Published: June 2007

ABSTRACTA GPSS/360 model was developed to investigate the behavior of a university's motor pool dispatch fleet. Time‐series data were collected and frequency distributions were constructed for vehicle request patterns and trip‐duration times. Regression analysis was performed to formulate trip mileage generators as functions of service time. Appropriate statistical goodness‐of‐fit tests were conducted to ascertain the extent of congruence between actual system behavior and expectations based on a number of theoretical distributions. Analysis of simulated response variables indicates that the model's internal structure reproduces reality to a high degree. Fifteen years of simulated experience were generated for six alternative fleet size configurations; results suggest that reductions in existing fleet capacity could be realized without effecting undue impairment in service levels.
A NOTE ON RENEGING DECISIONS
Authors: Parkan Celik 
Published: June 2007

ABSTRACTThis note is an extension of the approach to the problem of reneging introduced in Parkan and Warren [1]. It is assumed customers consider joining an M/M/1 queuing system with a prior gamma distribution over the values of the mean service time. Thus, each customer has an initial estimate of his total waiting time in the system. The customers associate the same sunk value with the waiting time and obtain the same reward at service completion. Having joined a system each customer may consider reneging in view of his revision of his initial service time estimate based on service observations. The bounds on the stationary state probabilities for such a system are obtained and examples are provided to compare the cases with and without reneging.
TWO‐PIECE VON NEUMANN‐MORGENSTERN UTILITY FUNCTIONS*
Authors: Fishburn Peter C. , Kochenberger Gary A. 
Published: June 2007

ABSTRACTThirty empirically assessed utility functions on changes in wealth or return on investment were examined for general features and susceptability to fits by linear, power, and exponential functions. Separate fits were made to below‐target data and above‐target data. The usual “target” was the no‐change point.The majority of below‐target functions were risk seeking; the majority of above‐target functions were risk averse; and the most common composite shape was convex‐concave, or risk seeking in losses and risk averse in gains. The least common composite was concave‐concave. Below‐target utility was generally steeper than above‐target utility with a median below‐to‐above slope ratio of about 4.8. The power and exponential fits were substantially better than the linear fits. Power functions gave the best fits in the majority of convex below‐target and concave above‐target cases, and exponential functions gave the best fits in the majority of concave below‐target and convex above‐target cases. Several implications of these results for decision making under risk are mentioned.
DECISION MAKING INVOLVING SEQUENTIAL EVENTS: SOME EFFECTS OF DISAGGREGATED DATA AND DISPOSITIONS TOWARD RISK*
Authors: Snowball Doug , Brown Clif 
Published: June 2007

ABSTRACTThis paper concerns human processing of disaggregated data in a business decision setting involving sequential events. Subjects currently employed in trust banking institutions chose between two mutually exclusive alternatives in a series of decision trials. The outcome for each alternative was the result of a two‐stage process; an unsuccessful outcome resulted from failure at either the first or second stage. The probabilities of success at each stage and the overall (joint) probability of success were provided for each alternative. Participants showed strongest preferences for an optimal (expected‐value) strategy in processing the data; however, significant preferences for two suboptimal strategies also were observed. Preferences for suboptimal strategies were influenced by the magnitude of differences in the alternatives' joint probabilities of success, by the magnitude of differences in the alternatives' stage probabilities of success, and by subjects' dispositions toward risk.
CONFLICT RESOLUTION IN INVESTMENT DECISIONS: IMPLEMENTATION OF GOAL PROGRAMMING METHODOLOGY FOR DUAL‐PURPOSE FUNDS*
Authors: Kumar P. C. , Philippatos G. C. 
Published: June 2007

ABSTRACTGoal programming (GP) is designed to resolve allocation problems with conflicting goals. Both goals and constraints are incorporated in the allocational decision, and the objective function is stated in a way that, upon solution, yields a result “as close as possible” to the priority‐weighted goals. The present paper applies GP methodology to the investment decision of dual‐purpose funds (DPFs), that are required by law to pursue allocational decisions with potentially conflicting objectives. It provides an empirical demonstration that DPF managers could have improved their investment selection and subsequent performance by the use of GP methodology. Finally the paper stresses the importance of sensitivity analysis to improve both the goal‐ranking and target‐selection aspects of the methodology and provides a limited but illuminating empirical demonstration of post‐optimality analysis.
INTEGER GOAL PROGRAMMING IN ADVERTISING MEDIA SELECTION
Authors: Keown Arthur J. , Duncan Calvin P. 
Published: June 2007

ABSTRACTThe media selection decision allocates advertising dollars among competing media so as to optimize promotional and corporate objectives. Linear programming attempts to model this process have been complicated by multiple and often conflicting management goals, the need for integer solutions, and nonlinearities. This study offers a technique that is sufficiently robust to simultaneously handle these problems. An alternative media selection framework is presented and the results of an illustrative application of integer goal programming are discussed. The proposed model improves on linear programming by success fully providing for optimal, integer solutions in settings that more realistically reflect the complexity of the media decision environment.
A GOAL PROGRAMMING MODEL FOR OUTPUT PLANNING
Authors: Fisk John C. 
Published: June 2007

ABSTRACTThis paper describes a goal programming procedure for determining satisfactory output plans for a work center. The situation being modeled is one in which work center inputs are known but vary significantly across time periods. Input levels are fixed relative to a given master production schedule, and output levels can be varied only within certain prescribed limits, at least in the short term. The similarity of the output planning problem to the more familiar aggregate planning problem is noted and discussed.
BUSINESS COMBINATION DECISIONS: A U.S./CANADA STUDY*
Authors: Falk Haim , Gordon Lawrence A. 
Published: June 2007

ABSTRACTThe purpose of this paper is to clarify the motives behind business combination decisions. Twenty‐one favorable characteristics associated with the motivations for business combinations were selected to serve as the basis for an empirical survey. Our analysis revealed that there are seven motivational variables of varying import and that the motivations underlying business combination decisions are similar for U.S. and Canadian executives.
A FUZZY SUBSET CHARACTERIZATION OF A SITE‐SELECTION PROBLEM
Authors: Narasimhan Ram 
Published: June 2007

ABSTRACTThis paper presents an application of fuzzy subsets to the problem of selecting sites for locating gas stations. Cost minimization and profit maximization models represent typical approaches to location decisions. These approaches are not well‐suited to problems like site selection for gas stations because of the difficulty in identifying precise relationships, the uncertainties involved, and the qualitative and imprecise nature of much of the information used for decision making. This paper proposes the use of a model based on linguistic variables and a direct evaluation of the available alternatives via the use of fuzzy variables. Conclusions regarding the practical advantages and limitations of the approach are drawn based on the reported application.
ADAPTIVE CONTROL THEORY: SURVEY AND POTENTIAL APPLICATIONS TO DECISION PROCESSES*
Authors: Aoki Masanao 
Published: June 2007

ABSTRACTAn important and distinct feature of a class of decision processes discussed in this paper is the possibility of gathering additional information between decisions and using it to improve future decisions. The analysis of these so‐called sequential decision processes is both complicated and far‐reaching in its implications. The purpose of this paper is to describe this class of decision processes to make its potential both more readily understood and better appreciated.
IMPLICATIONS OF THE BAKKE DECISION IN IMPLEMENTING AFFIRMATIVE ACTION PROGRAMS: A DECISION MODEL*
Authors: Solomon Robert J. , Messmer Donald J. 
Published: June 2007

AbstractThe U. S. Supreme Court decision in Regents of the University of California v. Allan Bakke (98. Su. Ct. 2733, 1978) provides guidelines to educational administrators regarding the implementation of affirmative action in student admissions. This paper presents a selection model which is consistent with the Supreme Court's decision in the Bakke case. This Diversity Model integrates traditional “ability” predictors with the illustrative diversity variables of sex and work history. The effect of the Diversity Model in terms of affirmative action impact and predicted grade point average when compared to a pure Performance Model and a Quota Model was evaluated on a sample of 199 MBA students. The Diversity Model did achieve an affirmative action effect with little or no sacrifice in student quality.
EMPIRICAL VALIDATION OF ELICITED UTILITIES FOR PREDICTION AND DECISION MAKING*
Authors: Barron F. Hutton 
Published: June 2007

AbstractThe HOPE (Holistic Orthogonal Parameter Estimation) elicitation procedure assesses multiattribute utility functions via sample holistic judgments. Analyses of actual judgmental data are presented that support two simple assertions: (1) HOPE‐derived utilities are valid and (2) the resulting utility functions are useful for decision making.