On Inventory Abatement via Manufacturing Randomness Reductions*

Under a continuous improvement framework, the policy of abating inventory via reductions in manufacturing randomness is considered. To explore this policy, a model of a real-world production-inventory system is developed, tested, and studied. The results suggest that manufacturing randomness reductions, even substantial ones, may not necessarily lead to inventory abatement, and paradoxically may lead sometimes to an inventory increase. In these cases, however, manufacturing randomness reductions will translate into higher customer service levels.     

Predicting the Winner's Curse

If 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.     

A Stochastic,Psychometric Valuation Model for Personnel Selection Systems*

This 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.     

An Analysis of the Pedagogical Effects of Expert System Use in the Classroom

An experiment that examines the use of expert systems to enhance student learning in an introductory Production and Operations Management (POM) class is discussed. An experimental expert system, SCHEDULER, was built within the domain of scheduling. It provided students with the opportunity to experience working with and integrating scheduling heuristics, constraints, and management requirements. The experiment also exposed students to using, rather than having to build, computerized decision aids, and expert systems in particular. Measurements of student learning and assessments of student perception regarding use of expert systems indicate expert systems can provide a valuable enhancement to the learning environment.     

A Game-Theoretic Approach to Quantity Discount Problems*

The traditional quantity discount problem is analyzed from the perspective of game theory, including both noncooperative and cooperative models. For the noncooperative case, the Stackelberg equilibrium is derived. For the cooperative case, the Pareto Optimality criteria are used to find a group of optimal strategies. Both scenarios are illustrated through an example which quantifies the benefits resulting from cooperation between the buyer and the seller for game-theoretic solutions using geometric programming.     

A Decision Model for the Robot Selection Problem Using Robust Regression*

Industrial robots are increasingly used by many manufacturing firms. The number of robot manufacturers has also increased with many of these firms now offering a wide range of models. A potential user is thus faced with many options in both performance and cost. This paper proposes a decision model for the robot selection problem. The proposed model uses robust regression to identify, based on manufacturers' specifications, the robots that are the better performers for a given cost. Robust regression is used because it identifies and is resistant to the effects of outlying observations, key components in the proposed model. The robots selected by the model become candidates for testing to verify manufacturers' specifications. The model is tested on a real data set and an example is presented.     

An Instrument for Assessing the Organizational Benefits of IS Projects

This paper reports the development of an instrument to measure the organizational benefits of IS projects. The basis for this instrument was a published framework that suggests three categories of such benefits: strategic, informational, and transactional. In a cross-sectional study of 178 IS projects proposed and approved for development, this framework was operationalized and empirically tested using the measurement model of LISREL. The analysis culminated in the validation and refinement of the these categories. The final instrument offers items under three separate subdimensions of strategic benefits: competitive advantage, alignment, and customer relations. Informational benefits are similarly comprised of information access, information quality, and information flexibility. Finally, transactional benefits are also shown to be of three types: communications efficiency, systems development efficiency, and business efficiency. Implications of this multidimensional instrument for IS practitioners and researchers are discussed.     

A Generalized Loss Function for Process Optimization

The use of loss functions for measuring the undesirability associated with failure to achieve target values for manufacturing product characteristics is widespread in industry. This study presents a generalization of one of the most commonly used loss functions and compares the two functions based on five theoretical criteria. A simulation involving multiple probability distributions for a single product characteristic is used to compare the performance of the loss functions. An example from the manufacture of helicopter transmission gears is used to empirically demonstrate the superiority of the generalized loss function over the conventional loss function.     

Assigning Students to Groups for Class Projects: An Exploratory Test of Two Methods

Beheshtian-Ardekani and Mahmood [1] recently offered a means of assigning students to groups for class projects to achieve a balanced distribution of student skills within groups. They assumed- but did not show-that the instructor would give weaker students a better chance to learn from stronger group members, that there would be greater synergistic learning effects, and that students would be happier with the project experience. This experiment tests the balanced-group method of assigning students using the people-sequential heuristic by comparing its effectiveness against the results achieved by random assignment to groups. The findings show that balanced groups have a modest advantage over groups formed randomly. Students in balanced groups felt slightly more satisfied with and challenged by the group and shared the work load more evenly. Within randomly assigned groups, student perceptions of the quality of the group-project learning experience were less homogeneous.     

Fostering Risk Taking in Research and Development: The Importance of a Project's Terminal Value

Large firms face a conflict in managing a portfolio of high-risk projects. When an ongoing project is thought to have a low likelihood of success, project team members take risks to improve its chances of success. However, upper-level managers who allocate resources tend to withhold resources from a project with a low likelihood of success in favor of others in the portfolio that look more promising. Because this paucity of resources influences project team members to avoid risk, the total effect of success likelihood on risk taking is conflicted. The influence on risk taking of a project's terminal value—defined as the value that remains in the firm in the event of project failure—is unequivocally positive, because both senior management resource allocation and project team risk-taking propensity are encouraged by terminal value. Thus, firms can override the ambivalent effect of likelihood of success on project decision making by focusing attention on a project's terminal value.     

A Comprehensive Model for Measuring the Potential Impact of Information Technology on Organizational Strategic Variables*

The existing literature on the impact of information technology (IT) does not include rigorous theory building or empirical studies. This research seems to be the first comprehensive investigation towards the development of an empirically validated comprehensive model for understanding the potential impact of IT on organizational strategic variables. More specifically, organizational and industrial variables that appeared to be affected by IT are identified, measured, and operationalized in the form of a comprehensive model. This study is based on structured interviews with a carefully selected sample of 31 strategic managers who had experience using IT for strategic decisions. In addition, the variables included in the model are well grounded in the information systems literature. The variables are then empirically validated and their reliabilities critically tested. A comprehensive model is derived from these validated variables. The model is a first step towards measuring the overall potential impact of IT on an organization. The model can also be used to gauge IT's potential impact on individual strategic variables. A set of hypotheses is also presented for future research. The hypotheses primarily relate to the impact of IT on organizational strategic performance. The model provides an empirically validated foundation for testing of such hypotheses.     

Strategic Assessment Model (SAM): A Multiple Criteria Decision Support System for Evaluation of Strategic Alternatives*

The evaluation of strategic alternatives is a particularly difficult task. This difficulty is due to the complexities inherent in the evaluation process and the lack of structured information. The evaluation process must consider a multitude of relevant information from both the internal and external environments of the organization. Various analytical and normative models have helped decision makers utilize large volumes of information in strategic evaluation; however, most of these models have some limitations. We present a multiple criteria decision support system, called strategic assessment model (SAM), that addresses some of the limitations inherent in the existing models. SAM captures the decision maker's beliefs through a series of sequential, rational, and analytical processes. The environmental forces—decomposed into internal, task, general opportunities, and threats—are used along with the analytic hierarchy process (AHP), subjective probabilities, the entropy concept, and utility theory to enhance the decision maker's intuition in evaluating a set of strategic alternatives.     

Developing Measures for Assessing the Organizational Impact of Information Technology: A Comment on Mahmood and Soon's Paper

In a recent study, Mahmood and Soon [26] identified and operationalized a set of variables that can be potentially impacted by information technology. The lack of factor analysis to verify the dimensionality of different variables is a notable omission in the study. This paper describes and employs the limited-information factor analysis approach and the minimum average partial criterion for testing the unidimensionality of different variables in the Mahmood and Soon study. While reconfirming the construct validity of eight variables, our results question the unidimensionality of two original variables. Further testimony is provided in favor of our results by citing previous research studies.     

A Heuristic Algorithm for the Capacitated Multiple Supplier Inventory Grouping Problem

This paper presents and solves a model for the multiple supplier inventory grouping problem, which involves the minimization of logistics costs for a firm that has multiple suppliers with capacity limitations. The costs included in the model are purchasing, transportation, ordering, and inventory holding, while the firm's objective is to determine the optimal flows and groups of commodities from each supplier. We present an algorithm, which combines subgradient optimization and a primal heuristic, to quickly solve the multiple supplier inventory grouping problem. Our algorithm is tested extensively on problems of various sizes and structures, and its performance is compared to that of OSL, a state-of-the-art integer programming code. The computational results indicate that our approach is extremely efficient for solving the multiple supplier inventory grouping problem.     

An Alternative FMEA Method for Simple and Accurate Ranking of Failure Modes

Failure modes and effects analysis (FMEA) is a methodology for prioritizing actions to mitigate the effects of failures in products and processes. Although originally used by product designers, FMEA is currently more widely used in industry in Six Sigma quality improvement efforts. Two prominent criticisms of the traditional application of FMEA are that the risk priority number (RPN) used to rank failure modes is an invalid measure according to measurement theory, and that the RPN does not weight the three decision criteria used in FMEA. Various methods have been proposed to mitigate these concerns, including many using fuzzy logic. We develop a new ranking method in this article using a data‐elicitation technique. Furthermore, we develop an efficient means of eliciting data to reduce the effort associated with the new method. Subsequently, we conduct an experimental study to evaluate that proposed method against the traditional method using RPN and against an approach using fuzzy logic.     

A Path Analytic Model of a Theory of Quality Management Underlying the Deming Management Method: Preliminary Empirical Findings*

Despite the impact that Deming and his 14 Points have had on the practice of quality management, empirical support for the effectiveness of the Deming Management Method has not advanced beyond the presentation of anecdotal, case-study evidence. In part, this is because theory to guide the conduct of empirical research has not been available. Only recently has such a theory of quality management to describe and explain the effectiveness of the Deming Management Method been articulated in the literature. This paper continues the journey of theory development; it reports the results of an exploratory empirical analysis of an articulated theory of quality management underlying the Deming Management Method. The constructs in the proposed theory are operationalized using measurement statements developed by the World-Class Manufacturing research project team at the University of Minnesota and Iowa State University. Path analysis is applied to the World-Class Manufacturing project data to explore the empirical strength of relationships advanced in the theory. The path analytic results provide support for several of the proposed relationships in the theory, and more importantly, suggest a number of new relationships which have not heretofore been proposed.     

The Impact of Information System Personnel Skill Discrepancies on Stakeholder Satisfaction

System development efforts depend to a large degree upon how well information systems (IS) managers, IS specialists, and IS users work together in a project team structure. Yet, these individuals frequently work under different perceptions about matters of importance to development, management, and success. This paper introduces a framework for examining IS specialists' skill requirements from a multiple‐stakeholder perspective. Derived from discrepancy theory, the framework concedes that different stakeholders hold a variable set of expectations for IS personnel skill levels as well as a perception of skills held by IS personnel. We examine differences in expectation and performance expressed by each group and describe the impact of the discrepancy on user satisfaction, career satisfaction of IS specialists, and on job performance evaluations by IS managers. Results confirm that a discrepancy between an IS specialist's expectations of skill and their perceived skill self‐proficiency impacts career satisfaction. Similar relations hold for IS managers and users. Since different stakeholders may hold different perceptions, satisfaction of all parties becomes problematic unless a common frame of reference can be determined.     

Strategic Decisions of New Technology Adoption under Asymmetric Information: A Game‐Theoretic Model*

In this paper we explore strategic decision making in new technology adoption by using economic analysis. We show how asymmetric information affects firms' decisions to adopt the technology. We do so in a two‐stage game‐theoretic model where the first‐stage investment results in the acquisition of a new technology that, in the second stage, may give the firm a competitive advantage in the product market. We compare two information structures under which two competing firms have asymmetric information about the future performance (i.e., postadoption costs) of the new technology. We find that equilibrium strategies under asymmetric information are quite different from those under symmetric information. Information asymmetry leads to different incentives and strategic behaviors in the technology adoption game. In contrast to conventional wisdom, our model shows that market uncertainty may actually induce firms to act more aggressively under certain conditions. We also show that having better information is not always a good thing. These results illustrate a key departure from established decision theory.     

Using Davis's Perceived Usefulness and Ease-of-use Instruments for Decision Making: A Confirmatory and Multigroup Invariance Analysis

As key components of Davis's technology acceptance model (TAM), the perceived usefulness and perceived ease-of-use instruments are widely accepted among the MIS research community as tools for evaluating information system applications and predicting usage. Despite this wide acceptance, a series of incremental cross-validation studies have produced conflicting and equivocal results that do not provide guidance for researchers or practitioners who might use the TAM for decision making. Using a sample of 902 “initial exposure” responses, this research conducts: (1) a confirmatory factor analysis to assess the validity and reliability of the original instruments proposed by Davis, and (2) a multigroup invariance analysis to assess the equivalence of these instruments across subgroups based on type of application, experience with computing, and gender. In contrast to the mixed results of prior cross-validation efforts, the results of this confirmatory study provide strong support for the validity and reliability of Davis's sixitem perceived usefulness and six-item ease-of-use instruments. The multigroup invariance analysis suggests the usefulness and ease-of-use instruments have invariant true scores across most, but not all, subgroups. With notable exemptions for word processing applications and users with no prior computing experience, this research provides evidence that the item-factor loadings (true scores) are invariant across spread sheet, database, and graphic applications. The implications of the results for managerial decision making are discussed.     

A Multiple Objective Embedded Network Model for Human Resource Planning and an Implementation of the Tchebycheff Method

A multiple objective embedded network model is proposed to model a variety of human resource planning problems including executive succession planning, compensation planning, training program design, diversity management and human systems design. The Tchebycheff Method, an interactive multiple objective programming solution procedure developed by Steuer and Choo [32], is implemented using NETSIDE, a computer routine for solving network problems with side constraints developed by Kennington and Whisman [17]. This paper demonstrates how the network structure common to many types of human resource planning problems can be exploited to improve solution efficiency, and how our approach extends the use of network models in human resource planning by including multiple objectives and extranetwork constraints. An illustrative example demonstrating the modeling and solution approach is presented, and the potential applications of these approaches in two specific areas of human resource planning are discussed.