bluuebunny/crossref_metadata_2025 huggingface dataset:
Inventory Positioning/Partitioning for Backorders Optimization for a Class of Multi‐Echelon Inventory Problems*
Authors: Rogers David F. , Tsubakitani Shigeru
Published: June 2007

Inventory management has undergone significant philosophical changes in recent decades such as the advent of the zero inventory concept. However, as attractive as the concept of minimal inventories may be, it is often unrealistic in application. Attention to basic features of inventory control systems such as order quantities, base stock levels, and reorder points remain crucial to ensure customer service at minimal cost. A nonlinear optimization model for determining base stock levels in a multi‐echelon inventory network is presented. Lagrangian relaxation results in (1) newsboy‐style relations that provide the optimal solutions, and (2) instantaneous shadow prices for the budget constraint. Sensitivity analysis of this model will facilitate making decisions concerning the desired investment in inventory for the entire system. This model may be solved on standard nonlinear programming software and is generalizable to problems in both production and distribution settings.
Standard Container Size Discounts and the Single‐Period Inventory Problem*
Authors: Pantumsinchai Pricha , Knowles Thomas W.
Published: June 2007

This paper analyzes the problem of choosing the optimal order quantity and its associated number of standard containers making up the order for single‐period inventory models under standard container size discounts. A range is determined that contains the optimal order quantity. Two algorithms are presented. The first algorithm solves the general case in which there is no restriction on the types of containers included in an order. The second algorithm solves a more restricted policy that requires the buyer to accept the order with successively smaller container sizes.
A Comparison of Three Joint Ordering Inventory Policies*
Authors: Pantumsinchai Pricha
Published: June 2007

This paper evaluates the performance of a joint ordering inventory policy which was first suggested and characterized by Renberg and Planche [14]. This paper shows that the policy is easily characterized for Poisson demands. This policy is then compared with two other joint ordering policies—the well‐known (S, c, s) or can‐order policy of Balintfy [3] and the recent periodic policies suggested by Atkins and lyogun [2]. For a continuous review operating environment, the Renberg and Planche policy utilizes a group reorder point and a combined order quantity (Q), with each item maintaining an order‐up‐to level (S). For the can‐order policy, each item in the product group has a must‐order point (s), a can‐order point (c) and an order‐up‐to level (S). The periodic policies require that item orders be grouped at some fixed scheduled intervals. Using long‐run total average costs as the basis, it is shown that no one policy is superior to the others in all the examples tested. In some cases, the Renberg and Planche policy performs surprisingly well.
A New Multiperiod Multiple Traveling Salesman Problem with Heuristic and Application to a Scheduling Problem
Authors: Gilbert Kenneth C. , Hofstra Ruth B.
Published: June 2007

A new multiperiod variation of the M‐traveling salesman problem is introduced. The problem arises in efficient scheduling of optimal interviews among tour brokers and vendors at conventions of the tourism and travel industry. In classical traveling salesman problem vocabulary, a salesman is a tour broker at the convention and a city is a vendor's booth. In this problem, more than one salesman may be required to visit a city, but at most one salesman per time period can visit each city. The heuristic solution method presented is polynomial and is guaranteed to produce a nonconflicting set of salesmen's tours. The results of an implementation of the method for a recent convention are also reported.
Partitioning Work Centers for Group Technology: Analytical Extension and Shop‐Level Simulation Investigation*
Authors: Suresh Nallan C.
Published: June 2007

This paper investigates the effects of partitioning job shop work centers to implement cellular manufacturing. Analytical models are utilized to show that partitioning leads to adverse effects on flow characteristics. The setup reduction introduced in partitioned systems has to overcome these adverse effects before leading to the benefits associated with cellular manufacturing. It is shown that partitioned systems with an insufficient degree of setup reduction are inferior to unpartitioned systems. Two new parameters relevant to this context, the breakeven setup reduction factor and flow ratio, are introduced for the design of viable cellular manufacturing systems. These insights are verified using a shop‐level simulation experiment, assuming non‐Markovian conditions. The experimental factors include lot size, setup reduction factor, cell size and allowance of inter‐cell movements. It is shown that the results are consistent with analytical insights in indicating the range of parameters in which cellular manufacturing may compare favorably with the best of the functional‐layout systems.
The Determinants of DSS Success: An Integrated Model*
Authors: Guimaraes Tor , Igbaria Magid , Lu Ming‐te
Published: June 2007

The results of a field study investigating the determinants of decision support systems (DSS) success are presented. A multivariate model was developed and tested using multiple regression hierarchical analysis on responses from 118 DSS users. Several specific hypotheses are also proposed and tested. Data analyses indicate that DSS success, as measured by DSS satisfaction and perceived benefits, depends on several factors: previous user experience with DSS, user involvement, user training, top management support, information sources, the level of managerial activity, and task structure, difficulty and interdependence. Based on the research results, several suggestions are made to improve the likelihood of successful DSS implementation.
An Empirical Investigation of the Effects of Decision Aids on Problem‐Solving Processes*
Authors: Mackay Jane M. , Barr Steve H. , Kletke Marilyn G.
Published: June 2007

Despite the growing number of investigations examining decision support systems (DSS), relatively few empirical studies have evaluated the effects of DSS on problem‐solving processes. This study uses protocol analysis to investigate the impact of a specific decision aid on problem‐solving processes in a semi‐structured problem. Results indicate that decision aids influence the problem‐solving processes of decision makers. The effect of a decision aid is found to be contingent on familiarity with the decision aid, task familiarity, and the interaction of these two factors. Suggestions for incorporating interaction effects and problem‐solving processes into future examinations are proposed.
Artificial Intelligence and Generalized Qualitative‐Response Models: An Empirical Test on Two Audit Decision‐Making Domains
Authors: Hansen James V. , McDonald James B. , Stice James D.
Published: June 2007

Machine learning methods are currently the object of considerable study by the artificial intelligence community. Research on machine learning carries implications for decision making in that it seeks computational methods that mimic input‐output behaviors found in classes of decision‐making examples. At the same time, research in statistics and econometrics has resulted in the development of qualitative‐response models that can be applied to the same kind of problems addressed by machine‐learning models—particularly those that involve a classification decision. This paper presents the theoretical structure of a generalized qualitative‐response model and compares its performance to two seminal machine‐learning models in two problem domains associated with audit decision making. The results suggest that the generalized qualitative‐response model may be a useful alternative for certain problem domains.
Marketing Communication Intensity Across Industries
Authors: Zinkhan George M. , Cheng C. S. Agnes
Published: June 2007

Marketing communication intensity (i.e., the ratio of advertising and promotional expenditures to sales) has been an important topic for both business managers and academics. Here, we investigate cross‐sectional and time‐series variation of communication intensity due to: type of offering (product versus service) and type of market (consumer versus industrial). Overall, we find that both of these factors affect variation of communication intensity across industries and over time. However, the effect of market type is much more dramatic than the effect of offering type. Such knowledge about patterns in communication intensity levels helps managers make decisions about how much to spend on advertising and promotion.
Toward Computerizing a Causal Modeling Approach to Strategic Problem Framing*
Authors: Heintz Timothy J. , Acar William
Published: June 2007

This paper proposes an object‐oriented approach to the development of interactive software for the purpose of managerial problem solving. A prototype is being developed using CSM causal mapping to represent each manager's perceptions of the relationships between key variables of a firm's strategic situation. This paper suggests the design of GDSS that would enable a group of managers to discuss, learn from each other, and possibly develop consensus about decisions or their causes. Issues involving future development are discussed.
An Application of the AXIS Solution Framework to Multiple Objective Aggregate Production Planning
Authors: MacLeod Kenneth R. , Reeves Gary R.
Published: June 2007

This paper provides data on the first application of a prototype of the AXIS solution framework. AXIS (algorithms combined with knowledge systems in an interactive sequence) is a framework for interactively combining structured algorithms that seek a best solution with knowledge‐based expert systems that seek expert heuristic solutions. This paper tests the framework using an interactive multiple objective integer programming algorithm combined with heuristics taken from the domain of aggregate production planning. The results indicate the AXIS framework can be successful in generating high quality solutions, in vastly reduced solution times compared to the structured algorithms, at much lower costs compared to the expert heuristics working alone.
Determining Order Quantity and Selling Price by Geometric Programming: Optimal Solution, Bounds, and Sensitivity*
Authors: Lee Won J.
Published: June 2007

This paper presents a geometric programming (GP) approach to finding a profit‐maximizing selling price and order quantity for a retailer. Demand is treated as a nonlinear function of price with a constant elasticity. The proposed GP approach finds optimal solutions for both no‐quantity discounts and continuous quantity discounts cases. This approach is superior to the traditional approaches of solving a system of nonlinear equations. Since the profit function is not concave, the traditional approaches may require an exhaustive search, especially for the continuous discounts schedule case. By applying readily available theories in GP, we easily can find global optimal solutions for both cases. More importantly, the GP approach provides lower and upper bounds on the optimal profit level and sensitivity results which are unavailable from the traditional approaches. These bounding and sensitivity results are further utilized to provide additional important managerial implications on pricing and lot‐sizing policies.
A New Framework for Manufacturing Planning and Control Systems*
Authors: Sum Chee‐Chuong , Hill Arthur V.
Published: June 2007

This paper presents a new framework for manufacturing planning and control systems which we call iterative manufacturing planning in continuous time (IMPICT) that appears to have several advantages over the well‐known material requirements planning (MRP) framework. IMPICT explicitly considers capacity constraints and total system cost (including tardiness) to determine order sizes, order release/due dates, and operation schedules in a deterministic, multi‐level, finite horizon, dynamic demand environment. Continuous time scheduling variables allow setups to be carried over from one period to the next.

Three new heuristics built on the IMPICT framework are presented and tested in a simulation‐based, full‐factorial experiment with a wide variety of problem environments. The benchmark for the experiment was materials requirements planning with operations sequencing (MRP/OS) implemented with best‐case, fixed planned lead times. The experiment showed that all three heuristics were statistically better than MRP/OS. The total cost for the order merging (OM) heuristic was 25 percent better than the total cost for MRP/OS. Computational times for OM were substantially larger than for MRP/OS; however, the computational times in the experiment suggest that OM is still computationally viable for large‐scale batch manufacturing environments found in industry.

IMPICT is superior to standard MRP systems because it explicitly considers capacity constraints and total system costs when it creates a materials plan. IMPICT is superior to linear programming‐based approaches to finite loading and scheduling found in the literature because it allows setups to be carried over from one period to another and because it is computationally viable for realistic‐sized problems.
An Investigation of Scheduling Policies in a Dual‐Constrained Manufacturing Cell*
Authors: Wirth Glen T. , Mahmoodi Farzad , Mosier Charles T.
Published: June 2007

In previous group scheduling studies, labor has essentially been ignored by assuming that enough labor is assigned to each machine in the cell. In reality, however, management usually does not have the resources to employ a laborer at each machine in the cell (i.e., machines need to share labor). Both labor scheduling and group scheduling heuristics need to be administered to manage the cell effectively. This study develops and examines scheduling procedures for a dual‐constrained (i.e., machine and labor) manufacturing cell. Eleven decision rules are developed and tested under 16 different experimental conditions. The experimental factors used are interarrival time distribution, cell load, setup‐to‐run‐time ratio, and transfer‐to‐run‐time ratio. Results show that interarrival time distribution and cell load have the greatest impact on the performance of the cell. This suggests that effective production planning aimed at reducing job arrival variation and leveling the cell load can substantially improve cell performance. Among the experimental factors, setup and transfer‐to‐run‐time ratio factors had the strongest influence on the rankings of the decision rules. These rankings were fairly robust across all experimental conditions and performance measures. The results also indicated that the inclusion of labor as a contraint in the cell had a significant impact on the performance of several group scheduling heuristics. Finally, it was shown that the best performing decision rules consider both transfer time and subfamily setup times.
Structure of Uncertainty and Decision Making: An Experimental Investigation*
Authors: Ghosh Dipankar , Crain Terry L.
Published: June 2007

Decisions in the real world usually involve imprecise information or uncertainty about the precesses by which outcomes may be determined. This research reports the results of a laboratory experiment which examined whether the structure of uncertainty, namely, both the center and the range of the probability distribution describing the uncertainty, is an important determinant of choice. Specifically, it examines how the uncertainty of audit by the Internal Revenue Service of income tax returns affects taxpayers' decisions about intentional noncompliance. The context is relevant as almost nothing is known about how taxpayers assess detection risks using the probability information they have.

The study focuses on intentional noncompliance. The factors affecting it are distinct and separate from those affecting unintentional noncompliance. Other factors that affect intentional tax noncompliance, such as risk, tax rates, and penalty rates, were controlled in the experiment. It was hypothesized that the lower the mean and the lesser the range (ambiguity) of the perceived audit probability, the greater the international noncompliance. As hypothesized, the analysis indicates that both the mean and the range of the perceived audit probability rate affect intentional noncompliance, though the effect of ambiguity is greater at a relatively higher level of mean. This result suggests that the strength of the information describing an uncertain event is captured better by both the mean and the range of the uncertainty than either of those components singly.
A Dynamic Model of Product Quality and Pricing Decisions on Sales Response
Authors: Narasimhan Ram , Ghosh Soumen , Mendez David
Published: June 2007

This paper presents a dynamic model that examines the influence of price and customer perception of product quality on the sales rate of a firm producing durable goods. The sales rate of the firm is modeled as a function of its price, average product life, perceived quality, and market potential. Specifically, the model considers: (1) the process by which perceived quality is determined by including the effects of the average life of a product and quality weighted units in the market; (2) the time delay in the influence of actual quality on perceived quality; (3) the process by which demand (i.e., potential sales) is converted to realized sales due to the effects of price and perceived quality; and (4) the saturation effect and associated non‐linearity in the demand function. The model presented is a reformulation and extension of the model originally proposed by Bass [2]. The validity of the model is tested using historical data on For Mustang.
Scheduling in a Management Context: Uncertain Processing Times and Non‐Regular Performance Measures*
Authors: Robb David J. , Silver Edward A.
Published: June 2007

Decision makers often face scheduling problems in which processing times are not known with certainty. Non‐regular performance measures, in which both earliness and tardiness are penalized, are also becoming more common in both manufacturing and service operations. We model a managerial environment with task processing times (which include sequenceindependent set‐up times) prescribed by three‐parameter lognormal distributions. Upon completion, each task derives a reward given by a particular piecewise‐linear reward function. The objective is to select a sequence of tasks maximizing the expected total reward.

The relative generality of the problem renders many enumerative methods inapplicable or computationally intractable. To overcome such difficulties we develop efficient priorityinduced construction (PIC) heuristics which build up a complete schedule by inserting tasks (singly from a list) into a partial sequence of tasks. In each partial and complete sequence a period of idle time is permitted prior to the first task. Performance on realistic‐sized problems is very encouraging, with cost penalties averaging less than one percent.
A Latent Class Binomial Logit Methodology for the Analysis of Paired Comparison Choice Data
Authors: Wedel Michel , DeSarbo Wayne S.
Published: June 2007

A latent class model for identifying classes of subjects in paired comparison choice experiments is developed. The model simultaneously estimates a probabilistic classification of subjects and the logit models' coefficients relating characteristics of objects to choices for each respective group among two alternatives in paired comparison experiments. A modest Monte Carlo analysis of algorithm performance is presented. The proposed model is illustrated with empirical data from a consumer psychology experiment that examines the determinants of perceived consumer risk. The predictive validity of the method is assessed and compared to that of several other procedures. The sensitivity of the method to (randomly) eliminate comparisons, which is important in view of reducing respondent fatigue in the task, is investigated.
Organizing for Global Competition
Authors: Jarvenpaa Sirkka L. , Ives Blake
Published: June 2007

Global information technology (i.e., computer hardware, software, and data communications shared across country boundaries) can support the multinational firm as it seeks to coordinate global operations, diffuse innovations worldwide, or provide integrated service to a global corporate customer. The current study uses information processing theory as the basis for examining alternative organizational designs for information technology in a globally competing firm. Mail survey data gathered from information technology managers in 109 multinationals provide evidence that multinational firms use different and distinct ways of organizing their global information technology activities. The survey data also reveal that in nearly half of the organizations, the way information technology activities are organized is inconsistent with the way the organization is reportedly structured. A follow‐up interview‐based study sought explanations for these misfits. Several contingency variables were identified that may shed some light to the misfits. These included factors from both the firm's internal and external environments.
Cellular Versus Functional Layouts Under a Variety of Shop Operating Conditions*
Authors: Shafer Scott M. , Charnes John M.
Published: June 2007

This paper addresses the suitability of cellular manufacturing under a variety of operating conditions. Queueing theoretic and simulation models of cellular and functional layouts are developed for various shop operating environments to investigate several factors believed to influence the benefits associated with a cellular manufacturing layout. The queueing models show how operations overlapping, which is more practical with a cellular layout, becomes more beneficial as the lot size increases. The simulation models are developed to study the performance of cellular and functional layouts in a wide variety of operating environments by varying the levels of four factors: (1) the degree to which natural part families occur, (2) the number of operations required to process the parts, (3) the processing times of the parts at each machine, and (4) the lot size. Two response variables are used to measure shop performance: the average time spent by a batch in the system, and the average work‐in‐process level. Statistically significant reductions in the average time in the system and average work‐in‐process measures were detected for the cellular layouts in all the operating environments studied.
A Game‐Theoretic Approach to Quantity Discount Problems*
Authors: Chiang Wen‐Chyuan , Fitzsimmons James , Huang Zhimin , Li Susan X.
Published: June 2007

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.
Reliability and Coherence of Causal, Diagnostic, and Joint Subjective Probabilities
Authors: Wright M. Keith , Stokes Lynne , Dyer James S.
Published: June 2007

Probabilistic knowledge is an important input to the analysis of many decisions, and may be required for long‐range forecasting, classical decision analysis, influence diagrams, fault tree analysis, and expert systems. If objective probabilities cannot be calculated, it is vital that decision makers use the best available subjective measures of probability. Standard mathematical theory allows the analyst several choices in framing subjective probability assessments. When assessing cause‐effect probabilities, the three choices are causal, diagnostic, and joint probabilities. Choosing among these is difficult in light of conflicting reports that, due to cognitive heuristics, probability judgment may be biased in various poorly understood ways. For example, it has been reported that, when judging causal probabilities, people are subject to the causal information bias, and thus upwardly revise their prior probabilities more than when judging diagnostic probabilities. On the other hand, it has also been reported that in some cases, people do not take proper account of new evidence, which results in under‐revision of prior probabilities. Furthermore it has been reported that, when assessing joint probabilities, people are subject to the conjunction fallacy, and thus often judge a joint probability to be higher than one of the two corresponding marginal probabilities. Our research compares the relative effects of these biases in a laboratory setting: we present new empirical results comparing the test‐retest reliabilities and under(over) revision rates of causal, diagnostic, and joint probabilities. Our results suggest that the tendency to both under‐revise and over‐revise prior probabilities is greatest when judging diagnostic probabilities, as opposed to either causal or joint probabilities. Furthermore our results suggest that joint probability judgment is more reliable than either causal or diagnostic probability judgment.
Perceived Service Quality and User Satisfaction with the Information Services Function*
Authors: Kettinger William J. , Lee Choong C.
Published: June 2007

A constant concern of management information systems (MIS) researchers and practitioners has been improving user satisfaction with the information services function (USISF). Due to the growth of end‐user computing, decentralization, and alternative sources of supply, an organization's information services function (ISF) is now faced with serving customers that possess substantial discretion in their use and purchase of information systems (IS) services. This increasingly market‐oriented environment demands sensitivity to IS customers' expectations and perceived value of ISF services. One important source of guidance in such an IS management environment is to look at marketing literature for frameworks that may permit the ISF to more effectively determine and convey the value of their services. Recognizing the need to improve existing MIS measures of user satisfaction with the ISF, this study adapts the SERVQUAL measure from marketing to provide more specific information about user satisfaction with the information service function. It was found that, while the three original dimensions of the traditional user information satisfaction (UIS) measure remain strong predictors of overall ISF user satisfaction, two aspects of IS service quality, “reliability” and “empathy,” are also significant predictors. The results suggest that the original dimensions of UIS may not be comprehensive enough to capture the more detailed dimensions of ISF service quality in SERVQUAL, and that the reliability and empathy dimensions of service quality may be needed to supplement the traditional UIS measure in determining user satisfaction with the information services function. Implications for research and practice resulting from these findings are discussed.
Using Neural Networks to Determine Internally‐Set Due‐Date Assignments for Shop Scheduling*
Authors: Philipoom Patrick R. , Rees Loren Paul , Wiegmann Lars
Published: June 2007

The production control system for a shop can be viewed as consisting of three sequential stages, the order‐promising stage, the order‐release stage, and the dispatching (or shop floor) stage. The first stage, wherein a customer's job arrives and is assigned a due date, provides the focus for this research. In particular, the performance of six regression‐based due‐date assignment rules found in the literature is compared with due dates determined by a neural network. The purpose is to see whether neural networks hold any promise for application in this area.

For the particular shop and the conditions studied, it is found that the neural network outperforms all six conventional rules according to mean‐absolute‐deviation (MAD) and standard‐deviation‐of‐lateness (SDL) criteria, although for one rule on the latter criterion, the difference is not statistically significant. Further analysis indicates that this conclusion generally holds both when the amount of data available is varied and a second, more structured shop is studied. On a third shop with random routings, the neural network outperforms the best conventional method according to the MAD measure, but results are mixed for the SDL criterion. The superior performance of the neural network leads us also to evaluate a regression model nonlinear in its independent variables, a case not considered in the due‐date literature. The nonlinear model generally outperforms the conventional rules on MAD and SDL. The neural network outperforms the nonlinear model on MAD, while the results for SDL are not as clear.
Planning and Control in Multi‐Cell Manufacturing
Authors: Steele Daniel C. , Berry William L. , Chapman Stephen N.
Published: June 2007

This research compares Material Requirements Planning (MRP), Kanban, and Period Batch Control (PBC) as alternative approaches to the planning and control of multi‐cell manufacturing involving flow cells and assembly. Since previous research on performance of these systems in cellular manufacturing has been primarily conceptual, the experiments reported here provide new insights into their comparative performance.

The results show that the production environment is a major factor in system choice. Three operating factors—Master Production Schedule (MPS) volume variation, MPS mix variation, and setup time/lot size—clearly affect system choice. All systems performed well under Justin‐Time (JIT) conditions; there was no advantage to Kanban. Under the mixed conditions of high MPS variation, but small setup time/lot sizes, PBC produced superior performance compared to Kanban and MRP. Under non‐JIT conditions, MRP was seen as clearly more effective. Finally, the results indicate that when conditions permit very small lot sizes relative to requirements, Kanban may perform best, even when MPS variation is high.
Validating Expert Systems: A Demonstration Using Personal Choice Expert, A Flexible Employee Benefit System*
Authors: Sturman Michael C. , Milkovich George T.
Published: June 2007

A method for validating expert systems, based on validation approaches from psychology and Turing's “imitation game,” is demonstrated using a flexible employee benefits expert system. Psychometric validation has three aspects: the extent to which the system and expert decisions agree (criterionrelated validity), the inputs and processes used by experts compared to the system (content validity), and differences between expert and novice decisions (construct validity). If these criteria are satisfied, then the system is indistinguishable from experts for its domain and satisfies the Turing Test.

Personal Choice Expert (PCE) was designed to help employees of a Fortune 500 firm choose benefits in their flexible benefits system. Its recommendations do not significantly differ from those given by independent experts. Hence, if the system‐independent expert agreement (criterion‐related validity) were the only standard, PCE could be considered valid. However, construct analysis suggests that re‐engineering may be required. High intra‐expert agreement exists only for some benefit recommendations (e.g., dental care and long‐term disability) and not for others (e.g., short‐term disability, accidental death and dismemberment, and life insurance). Insights offered by these methods are illustrated and examined.
Strategic Assessment Model (SAM): A Multiple Criteria Decision Support System for Evaluation of Strategic Alternatives*
Authors: Tavana Madjid , Banerjee Snehamay
Published: June 2007

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.
The Detection of Nuclear Materials Losses*
Authors: Prasad Sameer , Booth David , Hu Michael Y. , Deligonul Seyda
Published: June 2007

The identification and location of materials losses in nuclear facilities is an important issue. Many complexities arise in monitoring such losses. These complexities include the dependency among materials balance observations and the influence of errors (outliers) on parameter estimates of various monitoring methods. The proposed Joint Estimation procedure is superior to standard methods (control chart and CUSUM) and to methods that build in correlation (ARMA control chart, ARMA CUSUM, and the Generalized M procedure) in the detection of nuclear materials losses. The Joint Estimation procedure is robust to the influence of outliers, is flexible in accommodating a range of dependencies among observations, and provides information on the type of loss. Further, the procedure is reliable in that it yields a probability of false alarms and a probability of detecting losses closer to specifications.
The Role of Interorganizational and Organizational Factors on the Decision Mode for Adoption of Interorganizational Systems*
Authors: Premkumar G. , Ramamurthy K.
Published: June 2007

The dramatic growth of interorganizational systems (IOS) has changed the way organizations conduct their business, and has resulted in significant tangible and intangible benefits being realized by participating firms. However, the implementation of these IOS requires the cooperation and commitment of all the participating members. These members may have complex economic and business relationships among themselves that can result in a number of social, political, and economic factors influencing the adoption and implementation of IOS.

This study examines the role of interorganizational and organizational factors on the decision mode for adoption of IOS, in the specific context of electronic data interchange (EDI). Four interorganizational factors, based on the socio‐political framework derived from research in marketing, and five organizational factors based on research in IS were used in the study. The data for the study were collected through a large scale field survey. Two respondents, the sales/purchase manager and the IS manager, from 201 firms responded to the survey. The results of discriminant analysis of the data reveal that two interorganizational variables, competitive pressure and exercised power, and two organizational variables, internal need and top management support, are important variables to differentiate firms with proactive decision mode from firms with reactive decision mode.

The study also evaluates the differences between proactive and reactive firms on three implementation outcomes. Proactive firms are found to have greater extent of adaptation, more external connectivity with trading partners, and better integration of EDI information in their internal IS applications.
Structuring Conflict in Individual, Face‐to‐Face, and Computer‐Mediated Group Decision Making: Carping Versus Objective Devil's Advocacy*
Authors: Valacich Joseph S. , Schwenk Charles
Published: June 2007

Researchers and practitioners have long been interested in the effects of cognitive conflict techniques on individual and group decision making. One widely used and studied technique, devil's advocacy (DA), has been found to enhance decision‐making performance for both individuals and groups. Devil's advocacy begins with a recommended decision, followed by a critique of the decision that questions its assumptions. Researchers have not yet examined the effects of the objectivity of the devil's advocacy comments in computer‐mediated environments. This paper reports the results of a laboratory experiment that focused on this question by comparing the effects of an objective, nonemotional DA to an emotional, “carping” DA within individuals and groups using either computer‐mediated or face‐to‐face communication. In a manner consistent with prior research, both DA treatments were operationalized through the use of paper‐based consulting reports. The results suggest that individuals and computer‐mediated groups develop and consider more solution alternatives than face‐to‐face groups, and that subjects given the objective DA treatment produce higher quality decisions than those given the carping DA treatment. Face‐to‐face groups in the carping DA treatment considered the fewest alternative solutions in their decision‐making process, reached the lowest solution quality, yet reached decision consensus in the fewest voting rounds. The practical implications of the results suggest that questioning statements made by a devil's advocate should be objective, regardless of group communication condition. Carping devil's advocacy appears to stifle group decision outcomes when groups are using face‐to‐face communication.
The Influences of User Characteristics on Performance in a Logistics DSS Application
Authors: Swink Morgan
Published: June 2007

Decision Support Systems (DSS) are widely used in logistics decision applications, and a large number and variety of systems are commercially available. We investigate the contributions of user characteristics including experiences, data preferences, intuition, and effort to decision performance in a logistics DSS context. The study includes a laboratory experiment in which decision makers with varied experiences used a DSS to make facility network design decisions for problems of varying complexity. Two variants of the DSS are utilized in order to examine the interactions of a DSS decision aid with user characteristics.

We find that intuition and effort are associated with decision‐making performance. High analytic ability is not related to intuition, however. Education and previous experience are associated with performance. Yet these characteristics are also unrelated to intuition. Decision makers who highly value disaggregated data provided by the DSS tend to perform poorly. Also, the results suggest that the effects of users' experiences and preferences on performance are influenced by an analytical decision aid.
Master Production Rescheduling Policy in Capacity‐Constrained Just‐In‐Time Make‐To‐Stock Environments
Authors: Kern Gary M. , Wei Jerry C.
Published: June 2007

This paper describes a simulation experiment to evaluate the relative effectiveness of rescheduling policies in capacity‐constrained, just‐in‐time (JIT) make‐to‐stock production environments. Three performance measures were analyzed: average finished goods inventory, total units of sales lost, and a measure of schedule instability. Among the three loading methods we studied (level loading, front loading, and back loading), none was superior across all three performance measures. Level loading was the most robust, while back loading had an interaction effect with forecasting model and capacity level. Time fence scenario was found not to be as significant a factor in system performance as reported by previous research. Once an acceptable time fence scenario is selected, attempts to optimize this factor do not appear to offer significant improvement. It was found that higher demand variation, larger forecast errors, and tight capacity lead to the degradation of system performance. Judicious use of slack capacity helps a system to incorporate the periodic schedule changes typical of JIT systems.
Ramifications of Monitoring Service Quality Through Passively Solicited Customer Feedback*
Authors: Sampson Scott E.
Published: June 2007

It is common for service providers to collect data from customers as part of efforts to monitor quality. Often, this data is passively collected, meaning (a) any solicitation of feedback is done without direct customer interaction, and (b) the customer initiates any response given. Examples include customer comment cards, toll‐free telephone numbers, and comment links on World Wide Web pages. This article compares passive data collection with active methods (e.g., interviews and mail surveys). Passive methods generally have lower response rates and are inherently biased, but have cost and sample frame advantages when used to monitor quality on a continuous basis. Despite the biased nature of passive methods, this article describes the successful validation of a common customer‐response model with passively collected empirical data. The model is expanded to consider the impact of complaint and compliment solicitation on customers' evaluation of the service provider. Results show that this impact is negative, and that customers who spontaneously register complaints generally record higher ratings of the service provider than customers who complain in response to a complaint solicitation. Discussion and conclusions are given.
Organizational Computing as a Facilitator of Operational and Managerial Decision Making: An Exploratory Study of Managers' Perceptions*
Authors: Teng James T. C. , Calhoun Kenneth J.
Published: June 2007

Much of the current knowledge pertaining to information technology (IT) and decision making is based on decades old technologies that revolved around a central computing function and application‐specific systems. The purpose of this research is to examine the IT decision‐making relationship within the emerging organizational computing (OC) environment permeated by spontaneous utilization of both application‐and nonapplication‐specific computing and communication technologies. Specifically, this study seeks to explore managers' perceptions of the emerging OC environment as a facilitator of their decision‐making activities. To achieve a higher level of clarity than previous works, a two‐dimensional research framework is developed with the IT dimension consisting of computing and communication, and the decision‐making dimension differentiated between operational and managerial decisions. A survey instrument was constructed that measured the computing and communication dimensions of information technology use and their perceived effects upon operational and managerial decisions. The major findings of the study confirmed that managers recognize the value of general, nonapplication‐specific information technologies in decision making, and that this recognition is highly associated with how intensively these information technologies are used. Additionally, it was found that the two dimensions of IT differ in their relationships to decision making, and that IT usage relates to managerial decisions differently than operational decisions. These study findings have significant implication for practice and research, especially in the context of information resource management in which the primary purpose of the IS function is the delivery of general information service to users rather than the development of specific IS applications.
Cognitive Limitations and Investment “Myopia”*
Authors: Chi Tailan , Fan Dashan
Published: June 2007

Optimization of investment decisions in an uncertain and dynamically evolving environment is difficult due to the limitations of the decision‐maker's cognitive capacity. Thus, actual investment decisions may deviate from the dynamically optimal decision rule. This paper investigates how a potential investment rule bias affects the expected payoff from a project that has an uncertain development time and an uncertain completion cost. The result shows that the presence of a potential bias in the adopted decision rule dissipates project value and that the dissipating effect is greater for a longer term project if the completion cost is an increasing function of the time to completion.
Measuring the Congruence Between Market Requirements and Manufacturing: A Methodology and Illustration*
Authors: Bozarth Cecil C. , Berry William L.
Published: June 2007

This paper presents a measurement methodology, based on existing research in the manufacturing strategy and general strategy areas, for evaluating the congruence between market needs and manufacturing plant capabilities. The proposed methodology has several important advantages over current approaches. First, the methodology uses available data and statistical techniques to measure market‐manufacturing congruence. As a result, it is not dependent on assumptions about “classic” process choices. Second, the proposed methodology can evaluate the strategic fit between market needs and manufacturing in light of one or more performance criteria. Third, the methodology can be used to derive scalar measures of market‐manufacturing congruence, allowing users to evaluate congruence for a large number of products, customers, or market segments.

The theoretical basis, research objectives and major steps of the methodology are discussed, followed by an illustrative example from a North American manufacturer. Finally, the applicability of the methodology to a wide range of strategic manufacturing decisions is discussed.
Analysis of Local Decision Rules in a Dual‐Kanban Flow Shop
Authors: Ardalan Alireza
Published: June 2007

A recent article reported the results of a study on the effects of two kanban policy variables—the length of withdrawal cycle and the type of priority rule—on average customer wait time and total inventory. This study extends that work by adding two kanban policy variables and two performance criteria. It reports the results of simulation experiments that were conducted to determine how four policy variables—withdrawal cycle, priority rule, status of waiting withdrawal kanbans, and number of kanbans influence four performance criteria—average customer wait‐time, total inventory, and average number of full containers in the input and output stock points of stations. It was found that the information about waiting withdrawal kanbans in sequencing decisions results in the simultaneous improvement in two conflicting objectives—customer wait time and total inventory. Also, the effects of including the information regarding the status of waiting withdrawal kanbans on system performance are larger than the effects associated with the type of priority rule. The results provide insights into determining the level of each policy variable while fully considering the possible interactions among the variables and the levels of other policy variables to improve system performance. These insights allow for setting the levels of policy variables to make the improvement process smooth.
Adaptive, Agile Approaches to Organizational Architecture Utilizing Agent Technology*
Authors: Ottaway Thomas A. , Burns James R.
Published: June 2007

Intelligent agent‐based approaches to software support systems are believed to provide an unparalleled technology for integrating people, materials, and capital equipment. Software agents can be used to automate mechanization strategies for reducing the information content of work. As such, software agents diminish the need for utilizing humans to do repetitive, programmable tasks.

The purpose of studies of communities of intelligent agents is to ascertain their ability to accommodate flexible, agile organizational structures that can respond rapidly to changes in the marketplace, increase throughput, reduce costs, and improve quality. This paper presents a conceptual prototype for agent‐based structural selfdesign and describes experiments conducted regarding such studies together with the results obtained.