bluuebunny/crossref_metadata_2025_split huggingface dataset:
A Bicriterion Maximal Covering Location Formulation Which Considers the Satisfaction of Uncovered Demand
Authors: Church Richard , Current John , Storbeck James 
Published: June 2007

There have been many applications of the maximal covering location problem (MCLP). An underlying assumption of the MCLP is that demand not covered (i.e., not within a prespecified maximal distance of a facility) is not served. This may be an unrealistic assumption in many location planning scenarios, especially in the public sector. For example, in cases such as fire protection or ambulance service, calls not technically covered will still be serviced. The MCLP, however, does not consider the distances or travel times necessary to service such demand.This paper presents a bicriterion locational covering model which explicitly considers the travel distance or time necessary to service demand not within the maximal covering distance of a facility. The model may be used to generate noninferior (Pareto optimal) siting configurations which demonstrate the inherent trade‐offs between a siting scheme designed to maximize total coverage and one designed to minimize total travel time for uncovered demand to reach its nearest facility. In addition, it is shown that for any particular weighting scheme on the two objectives, the problem can be solved as a p‐median problem; a problem for which several efficient solution methods exist.
An Experimental Study of the Effectiveness of Three Debiasing Techniques*
Authors: Büyükkurt B. Kemal , Büyükkurt Meral Demirbag 
Published: June 2007

Subjective probability distributions constitute an important part of the input to decision analysis and other decision aids. The long list of persistent biases associated with human judgments under uncertainy [16] suggests, however, that these biases can be translated into the elicited probabilities which, in turn, may be reflected in the output of the decision aids, potentially leading to biased decisions.This experiment studies the effectiveness of three debiasing techniques in elicitation of subjective probability distributions. It is hypothesized that the Socratic procedure [18] and the devil's advocate approach [6] [7] [31] [32] [33] [34] will increase subjective uncertainty and thus help assessors overcome a persistent bias called “overconfidence.” Mental encoding of the frequency of the observed instances into prespecified intervals, however, is expected to decrease subjective uncertainty and to help assessors better capture, mentally, the location and skewness of the observed distribution. The assessors' ratings of uncertainty confirm these hypotheses related to subjective uncertainty but three other measures based on the dispersion of the elicited subjective probability distributions do not. Possible explanations are discussed. An intriguing explanation is that debiasing may affect what some have called “second order” uncertainty. While uncertainty ratings may include this second component, the measures based on the elicited distributions relate only to “first order” uncertainty.
A Simulation Study of Sequencing Rules in a Kanban‐Controlled Flow Shop*
Authors: Berkley Blair J. , Kiran Ali S. 
Published: June 2007

This paper addresses the problem of sequencing in decentralized kanban‐controlled flow shops. The kanban production control system considered uses two card types and a constant withdrawal period. The flow shops are decentralized in the sense that sequencing decisions are made at the local workstation level rather than by a centralized scheduling system. Further, there are no material requirements planning (MRP)‐generated due dates available to drive dispatching rules such as earliest due date, slack, and critical ratio.Local sequencing rules suitable for the decentralized kanban production‐control environment are proposed and tested in a simulation experiment. These rules are designed so that they can be implemented with only the information available at the workstation level. Example sequencing problems are used to show why the shortest processing time rule minimizes neither average work‐in‐process inventory nor average finished‐goods withdrawal kanban waiting time. Further, it is shown how work station supervisors can use the withdrawal period, in addition to the number of kanbans, to manage work‐in‐process inventories.
Relative Performance Evaluation and Risk Taking in Delegated Investment Decisions*
Authors: Chow Chee W. , Haddad Kamal M. 
Published: June 2007

Providing proper incentives to firm managers is increasingly important in the current competitive environment. Analytical research has suggested that evaluating a manager's performance relative to that of a peer group, in conjunction with standard‐based pay, can induce efficient risk‐sharing between firm owners and managers while maintaining the latter's incentives to exert effort. To date, direct empirical tests of this proposition have not been reported.This study uses a laboratory experiment to test the effect of relative performance evaluation on the risk‐aversion of delegated investment decisions. Project‐specific risk is operationalized using operating leverage, in part because the variability of a project's operating profits generally increases with this variable, and in part because many of the new manufacturing approaches held to be important to competitive advantage require significant capital investments and attendant increases in operating leverage. Across two levels of environmental uncertainty, subjects under a relative (as opposed to absolute) performance standard selected investments with significantly higher project‐specific risk. Also, as environmental uncertainty increased, subjects under an absolute standard significantly reduced the riskiness of their investments. In contrast, subjects shielded from environmental uncertainty by a relative standard chose investments of about equal riskiness under both low and high uncertainty conditions. If supported by future research, these findings would suggest that relative performance evaluation may reduce managers' reluctance to adopt risky capital investments, especially in firms operating in high‐risk economic or technological environments.
Interface Style and Training Task Difficulty as Determinants of Effective Computer‐Assisted Knowledge Transfer*
Authors: Gal Graham , Steinbart Paul John 
Published: June 2007

ABSTRACTThe transfer of expert knowledge to novices is one means of improving decision quality. Research needs to identify (1) the knowledge to be transferred to novices, and (2) the best method for transferring that knowledge. Studies that compare the judgment behavior of experienced and novice auditors address the first issue. The present study addresses the second issue in the context of using a computer‐assisted training (CAT) program. CAT was selected for study because of evidence that it can both improve the effectiveness and reduce the costs of training. An experiment was conducted in which two factors were manipulated: (1) the design of the human‐computer interface of the CAT program, and (2) the content of training tasks. The judgment of interest involved causal reasoning about the relationships between various internal control procedures and possible errors. The results indicate that alternative styles of interaction with a CAT program differ in terms of learning effectiveness. In addition, there was also evidence that training task content affected learning.
Determining the Critical Elements of Just‐In‐Time Implementation
Authors: Mehra Satish , Inman R. Anthony 
Published: June 2007

ABSTRACTThere are a limited number of papers dealing primarily with the implementation aspect of JIT. While the literature shows almost general agreement on the critical elements of JIT implementation, few empirical studies exist to support the proposed elements. The purpose of this study is to identify the elements of JIT implementation that are required to ensure successful implementation. A number of implementation elements were identified and subsequently grouped into a hierarchical structure consisting of four broader elements. Criteria were selected as measures of the level of implementation success. Analysis revealed that only a few of the identified elements were indeed required for successful JIT implementation.
Chance Constrained Programming Approach to Empirical Analyses of Mutual Fund Investment Strategies*
Authors: Brockett Patrick L. , Charnes Abraham , Cooper William W. , Kwon Ku‐Hyuk , Ruefli Timothy W. 
Published: June 2007

ABSTRACTChance constrained programming concepts are used to formalize risk and return relations which are then modeled for use in an empirical study of mutual fund behavior during the period 1984 through 1988. The publicly announced strategies of individual funds are used to form ex ante risk classifications which are employed in examining ex post performance. Negative relations between risk and return held in every year of the period studied. The bearing of these negative risk‐return findings for the Bowman paradox, as studied in the strategic management literature, are thus extended from the industrial firms studied by Bowman (and others) and shown to be present even in these investment oriented mutual funds in each of the years of the great bull market from 1984 through 1988. Finally, our use of chance constrained programming enables us to separate risk from return behavior and evaluate their relative strengths as sources of these negative relations, which are found to be more in the returns than the risks.
Marketplace Competition in the Personal Computer Industry*
Authors: Bridges Eileen , Ensor Katherine B. , Thompson James R. 
Published: June 2007

ABSTRACTA decision regarding development and introduction of a potential new product depends, in part, on the intensity of compeitition anticipated in the marketplace. In the case of a technology‐based product such as a personal computer (PC), the number of competing products may be very dynamic and consequently uncertain. We address this problem by modeling growth in the number of new PCs as a stochastic counting process, incorporating product entries and exits. We demonstrate how to use the resulting model to forecast competition five years in advance.
The Career Advancement Prospects of Managers and Professionals: Are MIS Employees Unique?
Authors: Igbaria Magid , Greenhaus Jeffrey H. 
Published: June 2007

ABSTRACTThe present study examined the career advancement prospects of MIS and non‐MIS employees, as well as the relationships of career advancement prospects with job performance evaluations, job satisfaction, career satisfaction, and organizational commitment for MIS and non‐MIS professionals and managers. Participants included 134 MIS professionals and managers and 397 non‐MIS professionals and managers of a large communications company. The results provided no evidence that MIS employees experience more restricted career advancement prospects than non‐MIS employees. In addition, job performance evaluations generally had positive effects on career advancement prospects; career advancement prospects had a number of positive effects on job satisfaction, career satisfaction, and organizational commitment; and job satisfaction and career satisfaction had positive effects on organizational commitment. These findings are related to prior research, suggestions for future research are offered, and implications for the management of MIS employees are identified.
Introducing Discriminant Analysis to the Business Statistics Curriculum*
Authors: Ragsdale Cliff T. , Stam Antonie 
Published: June 2007

ABSTRACTRecently a good deal of interest and effort has been directed toward making statistics courses more effective in business schools. It is believed that a key to success in this area involves giving a more prominent role to statistical tools which are useful in actual business practice. If the research literature is any indication, discriminant analysis (DA) has many potential applications in virtually all areas of business. Yet, DA is rarely taught in undergraduate business and/or M.B.A. statistics courses. This is partially due to the fact that most presentations of DA are relegated to multivariate statistics texts that assume an advanced knowledge of linear algebra. This paper attempts to rectify this situation by proposing a simplified pedagogical approach for introducing linear DA in undergraduate and/or M.B.A. business statistics courses.
Decision Processes for Developing Strategic Applications of Information Systems: A Contingency Approach*
Authors: Sabherwal Rajiv , King William R. 
Published: June 2007

ABSTRACTStrategic applications of information systems (IS) are considered by IS researchers to be determined by contextual factors such as environmental uncertainty, and influenced by attributes of the processes preceding them, such as planning and top management support. For better management of the process leading to these applications, it is essential to understand the relationship between process attributes and contextual factors. Utilizing a contingency approach, this article takes a step toward such an understanding. Based on successful strategic IS applications from 81 large companies, it examines the relationship between the context of these applications and the decision‐making process leading to them. The results indicate that the external environment is related to whether a rational or political decision‐making process is used. The IS function seems to influence the use of the decision process implied by IS researchers, one in which the top management champions the strategic application, while the IS managers contribute by conducting in‐depth analysis. However, the organization structure was not related to any decision process attribute. The implications of these findings for future research and practice are also discussed.
Non‐Normality and the Design of Control Charts for Averages*
Authors: Yourstone Steven A. , Zimmer William J. 
Published: June 2007

ABSTRACTNon‐normality has a significant effect on the performance of control charts for averages. The design considerations for a control chart for averages must include recognition of the degree of non‐normality of the underlying data. The performance of a control chart may be judged on its ability to correctly identify the probabilities of assignable causes of variation and chance causes of variation in a process. This paper examines the effects of non‐normality, as measured by skewness and kurtosis, on the performance, and hence the design, of control charts for averages and provides an alternative method of designing charts for averages of data with non‐normal distributions.
Automatic Generation of Symbolic Multiattribute Ordinal Knowledge‐Based DSSs: Methodology and Applications*
Authors: Ben‐David Arie 
Published: June 2007

ABSTRACTA learning‐by‐example algorithm, the ordinal learning model (OLM), that automatically generates symbolic rule‐bases from examples was applied to four real‐world multiattribute ordinal problem domains. The model automatically generates consistent and irredundant symbolic classification rules that mimic, in many aspects, the behavior of human subjects who solved similar problems during empirical studies. The OLM's performance is compared with those of regression analysis and with C4, a well‐known symbolic learning‐by‐example decision tree building algorithm. The OLM uses mainly comparison operations and does not attempt to optimize the rule‐bases it generates. Yet, the results show that the OLM's predictions are very accurate and the resulting rule‐bases are relatively compact. The time required for constructing the rule‐bases via the OLM was very competitive as well.
Application of the Back Propagation Neural Network Algorithm with Monotonicity Constraints for Two‐Group Classification Problems*
Authors: Archer Norman P. , Wang Shouhong 
Published: June 2007

ABSTRACTNeural network techniques are widely used in solving pattern recognition or classification problems. However, when statistical data are used in supervised training of a neural network employing the back‐propagation least mean square algorithm, the behavior of the classification boundary during training is often unpredictable. This research suggests the application of monotonicity constraints to the back propagation learning algorithm. When the training sample set is preprocessed by a linear classification function, neural network performance and efficiency can be improved in classification applications where the feature vector is related monotonically to the pattern vector. Since most classification problems in business possess monotonic properties, this technique is useful in those problems where any assumptions about the properties of the data are inappropriate.
A Microeconomic Model of the Focused Factory‐Vertical Integration Strategic Decision Problem
Authors: Tannous George F. , Mangiameli Paul M. 
Published: June 2007

ABSTRACTThe design of a manufacturing strategy incorporates the decision of whether to focus or vertically integrate, or adopt a policy somewhere between the two extremes. Unfortunately, the literature contains few models that aid a manager in this decision process. In this paper we design a model to evaluate and compare various strategic alternatives along the focused factory‐vertical integration continuum. By defining a point along this continuum as the percent of components manufactured internally that are needed to make one finished item (where 0 indicates complete focus and one manufacturing step, and 1 indicates full integration and 100 percent internal manufacturing) we are able to delineate the effects of the alternative decision strategies on flexibility and the firm's cash flow. The capital asset pricing model is invoked to assess the impact on the firm's risk and value.
Scheduling with Sequencing Flexibility*
Authors: Rachamadugu Ram , Nandkeolyar Udayan , Schriber Tom 
Published: June 2007

ABSTRACTThis study examines the effects of sequencing flexibility on the performance of rules used to schedule operations in manufacturing systems. The findings show that taking advantage of even low levels of sequencing flexibility in the set of operations required to do a job results in substantial improvement in the performance of scheduling rules with respect to mean flowtime. Differences in the mean flowtime measure for various rules also diminish significantly with increasing sequencing flexibility. Performance improvements additionally result for such due‐date related performance measures as mean tardiness and the proportion of jobs tardy. At high levels of sequencing flexibility, some nonparametric scheduling rules outperform the shortest processing time rule in terms of the mean flowtime criterion. Rules based on job due dates also outperform rules based on operation milestones in terms of tardiness related criteria at high levels of sequencing flexibility. The implications of these findings for the design of manufacturing systems and product design are noted.
Patterns of Information Source Use Across Industrial Purchase Situations*
Authors: Bunn Michele D. , Clopton Stephen W. 
Published: June 2007

ABSTRACTAn empirical taxonomy of industrial customers' information source use is developed based on a survey of 636 industrial customers across a wide range of different purchase situations. The taxonomy reveals five distinct information source mixes. Each mix consists of the combination of individual information sources used in a purchase situation. The five information source mixes are related to select underlying characteristics of purchase situations. The results indicate that the multivariate dimensions of purchase involvement, purchase complexity, and multiple influence are all significantly related to customers' choice of an information source mix. Implications of the taxonomy for marketing management and research are discussed.
An Investigation into the People‐Sequential Heuristic Method of Group Formation
Authors: Donohue Joan M. , Fox Jeremy B. 
Published: June 2007

ABSTRACTThis study investigates the people‐sequential heuristic method of group formation as proposed by Beheshtian‐Ardekani and Mahmood [2] and examined by Muller [9]. Responding to Muller's call for continued research on this topic, we first replicate the seven hypothesis investigations presented in that study and then consider several additional hypotheses designed to more fully examine the value of the process to the group members themselves. The results of this study indicate that the balanced groups assignment method is not effective as a sole means of increasing learning or satisfaction with the project. Of the twelve hypothesized relationships, which, if supported, would favor the use of balanced groups over randomly assigned groups, only one was supported. These findings and their relationship to group learning theory are discussed.
An Appellate Court Case Assignment Algorithm
Authors: Yang Jiaqin , Deane Richard H. 
Published: June 2007

ABSTRACTThis paper describes a case assignment (calendaring) algorithm for a multi‐judge appellate court system. In the algorithm, cases of unequal work content are selected for assignment to one of m panels (or clusters) from a set of N available cases. Each panel of cases is heard by a team of three judges. Each appellate case has an estimated work load and a priority ranking based on the type of appeal and filing date with the court. The algorithm balances both the total work load and the number of cases assigned to each panel while insuring that the highest priority cases are assigned to those available. The assignment problem is normally capacity constrained in that not all of the N cases can be assigned to one of the m panels on the monthly calendar. The algorithm is based on a neighborhood search and bounding principle that continually improves upon an initial feasible solution. Empirical results are presented to demonstrate the effectiveness and efficiency of the algorithm.
Predicting the Winner's Curse
Authors: Lederer Phillip J. 
Published: June 2007

ABSTRACTIf quantity uncertainty exists in a first price auction that specifies a fixed bid, a participant must answer two questions when evaluating a candidate bid: “What are my chances of winning?” and “What is the effect of the winner's curse on my quantity estimate?” The winner's curse is the tendency of the winner of a first‐price sealed‐bid auction to be the bidder that most overvalues the items being offered. When value uncertainty is due to quantity uncertainty, the winner's curse implies that the bidder that most overestimates the quantity tends to win. Thus, if there is quantity uncertainty, a participant must adjust its bid for this tendency to overestimate quantities.This paper presents an empirical method to answer the above questions by estimating a predictive distribution of the highest competing bid and the quantity bias caused by the winner's curse. The method is developed for timber auctions but is general to auctions where a fixed bid is called for and there is uncertainty in the mix and quantities of items being offered. An example that uses data from timber auctions is used to demonstrate the method.