bluuebunny/crossref_metadata_2025 huggingface dataset:
Fading Frames: Data Presentation and Framing Effects*
Authors: Diamond Lester , Lerch F. Javier
Published: June 2007

This article describes three experiments that investigate the impact of data presentation on framing, which is the differential evaluation of objectively equivalent information given different frames of reference. The experiments were designed to vary the amount of information and the format of presentation (tables versus graphs) provided to the decision maker to gain an understanding of the mechanism underlying framing. The inferred information model proposed by Johnson and Levin [11] is utilized to explain the results of the three experiments in terms of the redistribution of weights attached by the decision makers to the attributes of the prospective outcomes. The results of the three experiments indicate that framing effects are observed only when the presentation of data facilitates the shifting of weights among the attributes of the available alternatives. The results further indicate that framing is eliminated as more information is displayed. However, presentation of additional information does not eliminate framing when a graphical format is utilized. Finally, no framing effects are observed when uneven amounts of information are used to describe two alternatives in the same decision task.
Stochastic and Intransitive Behavior in a State‐Preference Model of Asset Choice*
Authors: Bernardo John J. , Upton David E.
Published: June 2007

Most models of investor behavior assume a time‐state independent utility function and result in a deterministic solution where a given set of inputs uniquely specifies the decision. In contrast, a state preference model using a time‐state dependent utility function is derived in this paper. The model allows the investment choice decision to be analyzed in a game theoretic context. The general solution is a mixed strategy which allows for a probabilistic interpretation of the decision. The approach presented in this paper can accommodate anomalies such as intransitivity of preference and satisficing as rational behavior. An example of a possible implementation is given along with interpretations of the outcomes.
Constrained Forecasting: Some Implementation Guidelines
Authors: Fliedner Eugene B. , Mabert Vincent A.
Published: June 2007

Constrained forecasting has become a popular approach to the complex task of predicting future sales. Mixed performance results have been obtained by companies employing constrained forecasting systems software packages which probably reflects the lack of any clear system implementation guidelines. A number of important operational parameters such as the number of product families, criterion used to define product families, number of system levels, etc. must be specified. This study reports on an investigation of two of these parameters: product group size and appropriate grouping criterion. Different tests are performed with the constrained forecasting system and compared to a traditional forecasting approach using product data from the Cummins Engine Company of Columbus, Indiana.
Real Estate Taxation and Commercial Mortgage Underwriting
Authors: Shilton Leon , O'Connor Walter , Teall John , Webb James R.
Published: June 2007

Recent disclosures about problem commercial real estate loans have exposed the underwriting process to intense scrutiny. This study focuses on mortgage loan underwriters of life insurance companies. After a review of the tax changes that affected commercial real estate from 1969 through 1988, the study tests how loan underwriters reacted to changes in tax benefits. To overcome the interdependent effects of interest rates and capitalization rates, a variation of the Black‐Scholes pricing model is used to test the impact of changes in tax benefits. The results indicate that the underwriters do not fully incorporate the value of tax benefits in the underwriting decision. During the period of the largest tax benefits, 1982 to 1986, underwriters became more conservative and increased their equity requirements.
A Study of the Impact of an Integrated Information Technology on the Time Utilization of Information Workers
Authors: Sulek Joanne M. , Marucheck Ann S.
Published: June 2007

This paper examines the impact of the implementation of an integrated information technology (IIT) on the time utilization of information workers as mediated by the content of the information work performed. The IIT in this study is a system of personal computers linked together in a network for sharing computing, data, and communication resources. The subjects of the study were two groups of information workers in an academic field setting. One group consisted of knowledge workers whose chief activity was to advise and counsel students. The other group represented lower level information workers who provided support service to an academic department. A two‐dimensional framework was used to classify each of the activities an information worker performs relative to its importance and programmability within the context of the information work. Using work sampling methodology, it was determined that the IIT was associated with the knowledge workers' reallocation of work time to important yet relatively unstructured tasks. The lower level information workers became more efficient in performing highly structured skill‐based activities. However, there was no statistically significant improvement in the effectiveness of the work completed as perceived by the clients of both groups of information workers. The results suggest that when an IIT is implemented, the manner in which newly available time is utilized depends on the nature of the information work performed by the users.
Judgment Error and Expert Critics in Forecasting Tasks*
Authors: Silverman Barry G.
Published: June 2007

This paper presents an approach to elicit and critique intuitive forecasts. It attempts to retain the valid component of experts' judgments while correcting some biases. Decision science and expert system techniques were unified with the design of an expert critiquing system. A real world application of the resulting critic verifies the approach. A discussion addresses how to create a similar critic for other forecast settings.
A Goal Programming Model for Effective Segment Determination: A Comment and Application
Authors: McGlone Teresa A. , Calantone Roger J.
Published: June 2007

This note presents a model for the effective market segment determination problem. The integer goal programming model was developed for a nonprofit health care organization. The approach is an alternative application of a model presented by McClure and Wells [7]. The model includes input from the organization's clients as well as the organization's decision makers. A distinctive element is the simultaneous development of market segments and the consideration of management, institutional, and resource constraints. The purpose of the model was to aid the decision makers in determining if effective market segments exist which can be reached with information and educational materials concerning infant nutrition and breastfeeding. The model was tested and found to be effective in helping the decision makers segment their clients.
How Prevalent Are Stable‐Paretian Distributed Financial Variables?
Authors: Lau Hon‐Shiang , Gribbin Donald W. , Harris Randy
Published: June 2007

Many studies have claimed that the stable‐Paretian distribution should be used to model a wide variety of financial variables, ranging from stock and futures prices to exchange rates. Using a newly developed method, this study shows that the stable distribution is unsuitable for modeling most financial variables that are stable‐distributed. We found that the distributions of a few accounting ratios may be stable. Our conclusions support a change in the future directions of financial‐variable modeling.
The Design of a Knowledge‐Based Decision Support System to Support the Information Analyst in Determining Requirements
Authors: Dalal Nikunj P. , Yadav Surya B.
Published: June 2007

Decision support system (DSS) researchers and designers continue to look for unstructured organizational tasks where there is a critical need for intelligent computer‐based support. One such decision task is information requirements determination. Requirements determination is recognized as the most crucial phase of the systems development life cycle. Unfortunately, most methodologies and CASE tools focus only on how to specify the requirements once they are determined. There is very little computer support for the process of determining requirements. This paper discusses the conceptual design and development of a knowledge‐based DSS to support information analysts in the critical decision task of determining requirements for the design of effective information systems. The expert modeling support system has the expertise to assist the analyst in studying the organization as a whole and in modeling the system under study in the context of the overall organization's goals and needs. The focus of the paper is on the problems associated with building the knowledge base component of the intelligent decision support system. A prototype implementation of the system is described.
A Knowledge Based Decision Support System for Setup Reduction
Authors: Kim Seung‐Lae , Arinze Bay
Published: June 2007

The issue of setup reduction is important for firms seeking to incorporate advanced procedures and concepts such as flexible manufacturing systems (FMS) and just‐in‐time (JIT) manufacturing to improve manufacturing productivity. Investing adequate amounts in setup reduction is a complex decision affected by many factors including the existing level of automation, worker characteristics, product features, and the manufacturing environment. The consequences of improper investment (i.e., over‐ and underinvestment) includes possible disruption of manufacturing operations as well as wasted resources. Much of the knowledge involved in the investment decision is heuristic and experience‐based, and takes on greater significance when the form of the setup reduction function is not known a priori. This paper describes the development of a knowledge‐based decision support system (KBDSS) that combines both heuristic and procedural knowledge to provide support for the setup reduction investment decision. The system uses codified manufacturing expertise to improve both the accuracy and effectiveness of setup‐reduction decision making. Use of the KBDSS is illustrated by two examples based on disparate manufacturing contexts.
Generating Explanations for Goal‐Based Decision Making*
Authors: Slade Stephen
Published: June 2007

As information systems make the transition from decision support to decision making, there will be a concomitant need for the programs to explain or justify their actions. Without such explanations, humans will not readily cede authority to a machine. This paper describes an automated decision‐making program, VOTE, which generates natural language explanations for its decisions in both English and French. The program domain is Congressional roll call voting. VOTE simulates voting decisions of specific members of the United States House of Representatives on given bills. VOTE's natural language generation facility is also used by the underlying databases to interpret the knowledge representations. These underlying knowledge representations are described and applications of this decision making model to the general business domains of strategic planning, investment, and marketing are suggested.
Insights from Attempts to Validate a Multi‐Attribute Model of Problem Definition Quality
Authors: Massey Anne P. , O'Keefe Robert M.
Published: June 2007

Problem definitions are often used as part of the problem structuring process in decision sciences. We report an attempt to validate a multi‐attribute model of problem definition quality in the context of an experiment based upon the definition of the ‘alcohol problem’ on a campus. Three independent raters assessed values for the attributes of the model for 57 written problem definitions, and their rating was compared to three subjective ‘expert’ ratings made by individuals with some responsibility for alcohol policy. Our study shows that the experts exhibited considerable stakeholder bias in their assessments of the definitions, suggesting that a definition that is evaluated as good may not be subjectively acceptable to others. We present some evidence that the best definitions are those that provide direction with regard to solution, neither suggesting firm solutions to the problem nor being too open‐ended. It is shown that the multi‐attribute model is a reasonable tool for eliminating poorer definitions. Further, we relate our work to recent conceptual developments in understanding problem definition.
Integrative Cycle Scheduling Approach for a Capacitated Flexible Assembly System*
Authors: Kim DaeSoo , Mabert Vincent A. , Pinto Peter A.
Published: June 2007

This study revisits the traditional single stage, multi‐item, capacitated lot‐sizing problem (CLSP) with a new integrative focus on problem structuring. Unlike past research, we develop integrative cycle scheduling approaches which simultaneously address lot‐sizing, capacity, and sequencing issues. Our purposes are to (1) explore the effect of sequencing on inventory levels, (2) examine the problem of infeasibility in the economic lot scheduling problem (ELSP), and (3) provide a simple methodology of generating low‐cost cycle schedules in an environment with discrete shipping, dynamic demands, limited capacity, zero setup cost, and sequence‐independent setup times. Our procedures are compared to benchmark cycle scheduling approaches in terms of both inventory cost and computation time under different demand scenarios, using the operating data from a flexible assembly system (FAS) at the Ford Motor Company's Sandusky, Ohio plant.
Labor Utilization Effects of Labor Scheduling Flexibility Alternatives in a Tour Scheduling Environment
Authors: Jacobs Larry W. , Bechtold Stephen E.
Published: June 2007

This study used a factorial experimental design and a new modeling methodology to investigate the impact of a number of labor scheduling flexibility alternatives and labor requirements characteristics on labor utilization within a tour scheduling environment. Break‐placement flexibility and shift‐length flexibility were found to be extremely effective in improving labor utilization for all labor requirement distributions used. Flexibility with respect to the number of days included in a tour schedule resulted in substantial improvement in labor utilization for all labor requirements distributions exhibiting daily and/or weekly variation. Surprisingly, virtually no improvement in labor utilization was achieved for any labor requirement distribution by the removal of requirements for consecutive days off. In addition, almost no improvement was found by allowing the shift start time to vary across the working days included in tours. High labor requirement amplitude was found to have a strong adverse effect on labor utilization while longer operational days were associated with improved labor utilization for all labor requirement distributions. We discuss the implications of these results for service operations management and provide suggestions for future research.
The Effectiveness of Graphical Presentation for Information Extraction: A Cumulative Experimental Approach*
Authors: Tan Joseph K.H. , Benbasat Izak
Published: June 2007

Three laboratory experiments were conducted to assess the relative strengths and weaknesses of bar, symbol, and line graphs for performing a variety of elementary information extraction tasks using two dependent variables, time and accuracy. The findings indicate that the degree of support provided by a particular graph format for a particular data extraction task depends on the matching of format and task in terms of their anchoring characteristics. Anchoring, in this context, refers to the phenomenon that specific and diverse parts of a graph are segmented by the reader to act as salient and relevant cues, or anchors, when different classes of information are to be extracted from the graph. A data extraction task has high x‐value (y‐value) anchoring if the x‐axis (y‐axis) component is represented in the question as either a given value or an unknown value. Conversely, a task has low x‐value (y‐value) anchoring if the x‐axis (y‐axis) component is not represented in the question as either a given value or as an unknown value.

Data extraction accuracy was not significantly affected by presentation format. Bars provided the best time performance for data extraction tasks having high anchoring on both axes but were not appropriate for tasks having low anchoring on either the y axis or both the x and y axes. Line graphs tended to be worse in terms of time performance for tasks having high anchoring on both axes although they were as fast or better than other representations for tasks having low anchoring on both axes. Symbol plots appeared to possess anchoring characteristics associated with both bars and line graphs. Symbols (as with bars) tended to produce a time performance superior to that of line graphs for tasks having high anchoring on both axes; and (as with line graphs) symbols allowed faster results than bar graphs for tasks having low anchoring on either the y axis or both the x and y axes.
Simulation Tests of FCFS and SPT Sequencing in Kanban Systems
Authors: Berkley Blair J.
Published: June 2007

One of the basic tenets of scheduling theory is that the SPT sequencing rule maximizes average production rates and minimizes average in‐process inventories. This paper shows that on single‐card kanban‐controlled lines FCFS often has greater average production rates than SPT. Further, the performance of SPT declines relative to FCFS for larger queue capacities and less frequent material handling. Results for the single‐card system are also compared to those of Berkley and Kiran [1]. In that article it was shown that for two‐card systems with periodic material handling, SPT has larger average inventories than FCFS. This paper shows that these surprising results can be attributed to Berkley and Kiran's material‐handling mechanism.
Interaction Between Concurrent Transactions in the Design of Distributed Databases
Authors: Kulkarni Uday R. , Jain Hemant K.
Published: June 2007

A distributed database system allows concurrent execution of transactions from multiple users at multiple locations. This paper presents a general scheme of including the effect of interaction between such transactions in the design process of distributed databases. This scheme allows the decision maker to choose the most appropriate design for a distributed database. The interaction effect is a consequence of concurrency control procedures and contention for system resources. Prior research has not included all components of the interaction effect in the design process. A separate module, called an interaction module, was built to measure the interaction effect using a comprehensive simulation model of a general purpose relational distributed database management system (DBMS). The interaction module can be interfaced with any distributed database design system as an add‐on module so that the interaction effect can be included in the design process. A detailed example demonstrates the use of the interaction module in the decision‐making process. Experiments conducted using the module show that the interaction effect can be significant and that it can affect the choice of the design. Experiments were also conducted to measure the sensitivity of design choices under changing input conditions.
Optimal Selection Strategy for the Group Interview Problem
Authors: Chun Young Hak , Moskowitz Herbert , Plante Robert D.
Published: June 2007

We propose a more generalized version of the secretary problem, called the group interview problem, in which each group contains several alternatives and each group of alternatives is presented and evaluated sequentially over time. Using the assumptions corresponding to the classical secretary problem, we derive an optimal selection strategy which maximizes the probability of winning or selecting the single best choice in a given sequence of groups. We further address the problem of choosing at the beginning of the evaluation process a sequence of groups to maximize the winning probability. Because of formidable computational requirements to obtain an optimal solution to this sequencing problem, we then develop a heuristic algorithm based on several properties inherent in an optimal selection strategy. The heuristic procedure is evaluated experimentally using Monte Carlo simulation and is shown to be effective in obtaining near‐optimal (within 5 percent) solutions.
Single‐Stage and Serial Production Line Systems with Unreliable Machines and General Probability Distributions
Authors: Koulamas Christos P.
Published: June 2007

This paper presents stochastic models for analyzing production to stock and production on demand systems with arbitrary demand, production, machine breakdown and repair processes, and a finite buffer. Expressions are developed for the transition probabilities among the different states, the proportion of transitions that take the process to a particular state, the probabilities that the process is at a particular state, and the expected state residence times. Also, expressions are developed for some quantities of interest, like average inventory, percentage of lost sales, and expected waiting time. Applications are discussed for various demand, production, machine breakdown, and repair processes and numerical examples are presented. Guidelines are given for utilizing the models in evaluating the economic performance of production systems. Using an approximation procedure, the models are used for modeling multi‐stage serial production to stock and production on demand lines. Simulation results indicated that the quality of the approximation is very good. The multi‐stage models are useful in practical situations, because they allow the use of different probability distributions for the various processes (production, machine failure, etc.) of each stage.
Automating Knowledge Acquisition and Refinement for Decision Support: A Connectionist Inductive Inference Model*
Authors: Deng Pi‐Sheng
Published: June 2007

An important application of expert systems technology is to provide support for nonstructured decision making. Usually, nonstructured decision making is characterized by heavy reliance on heuristic knowledge, which is very difficult to articulate or document, and therefore traditional knowledge acquisition approaches are not very successful. The quality and effectiveness of an expert system supporting unstructured decision making is affected when traditional knowledge acquisition approaches are used. To alleviate this problem a model is proposed that combines inductive inference and neural network computing, and an example is presented that illustrates the potential of this model in unstructured decision support.
Modelbase Construction with Object‐Oriented Constructs*
Authors: Huh Soon‐Young
Published: June 2007

This paper proposes modelbase construction mechanisms in a decision support system (DSS) for representing and managing models of diverse management science/operations research modeling paradigms, using object‐oriented database management systems (ODBMS) constructs. It focuses on the construction of a modelbase that maintains logical independence among the DSS components including modelbase, database, and solvers, but relieves the mismatching characteristics by facilitating intelligent and stabilized integration of them. As a conceptual framework to build such a modelbase, this research uses generic model concepts, and adopts structured modeling language (SML) as a paradigm‐neutral model representation sublanguage. In the modelbase, three model abstraction layers including model type, model structure, and model instance are devised to facilitate the capture of multiple modeling paradigms and specific application models in different instantiation levels. The constructs and methods discussed are flexible enough to be applied to a wide variety of decision‐making and problem‐solving paradigms. A prototype system is developed under a commercial ODBMS called OBJECTSTORE with the C++ programming language, and diverse model manipulation commands are illustrated by an object‐oriented structured query language (OSQL).
Estimating the Geographic Extent of Part‐Time Labor Markets: U.S. Army Reserves*
Authors: Sohn So Young , Thomas George W.
Published: June 2007

Local labor market supportability is becoming an increasingly important issue for the United States Army Reserves. As military bases close and Reserve units are consolidated at fewer Reserve centers, the appropriate reassignments of units to Reserve centers require accurate measures of the ability of local labor markets to support such consolidations. A two‐stage random effect model is applied to evaluate the geographical extent of the labor market for Army Reserve centers. In the first stage model, a lognormal distribution is used to describe the commuting distance behavior of the Reserve center members. In the second stage model, we estimate the mean of log transformed commute distance as a function of regional characteristics of the Reserve center. An iterative weighted stepwise selection method is used to find a set of characteristics that adequately predict variation of the mean commute distance over Reserve centers. The resulting model is used as inputs to location and market assessment models to assist the marketing decisions of the Army Recruiting Command.
Dimensions of Market Attractiveness: Competitively Interactive Spatial Models*
Authors: Cromley Robert G. , Hempel Donald J. , Hillyer Clayton L.
Published: June 2007

This paper presents a normative, multidisciplinary approach for evaluating market entry strategies with concern for the effects of spatial assumptions on performance expectations. An assessment framework is linked to a series of models that show the value of adding spatial and competitive perspectives to typical baseline conceptualizations of market opportunity. Criteria for assessing market attractiveness are discussed with special concern for the problems of field service firms whose market boundaries are not limited by fixed facility locations. The problem is conceptualized as the managerial decision to locate a new brokerage office in a highly competitive regional market area. Realistic constraints are established by focusing the market entry decision through aggregate data from secondary sources that are readily available to an outsider who had not been active in the geographic markets considered. A simple model based on market potential is progressively enhanced with spatially adjusted measures of market attractiveness and competitive resistance. Empirical tests highlight the impact of alternative model formulations and choice criteria on the decision‐making process.
Redesigning a Cellular Manufacturing System to Handle Long‐Term Demand Changes: A Methodology and Investigation*
Authors: Vakharia Asoo J. , Kaku Bharat K.
Published: June 2007

Cellular manufacturing systems have been proposed as an alternative to the job shop since they provide some of the operational benefits of a flow line production process, while retaining to some extent the flexibility of job shops. However, this must be balanced against the possibility of additional initial investments in equipment to form the cells and a certain loss in manufacturing flexibility, particularly in terms of the ability to deal with long‐term demand changes. This paper presents a model‐based heuristic cell system redesign methodology to deal with such demand changes. The methodology is validated and applied to system designs generated from several data sets published in the literature. Results show that different kinds of demand changes incur distinct kinds of costs. Further, characteristics of cell designs that can handle long‐term demand changes at least cost are identified.
A Computerized Approach to Decision Process Tracing for Decision Support System Design*
Authors: Cook Gary J. , Swain Monte R.
Published: June 2007

We propose the use of computerized process tracing (CPT) tools as an appropriate approach for monitoring the information acquisition and evaluation phase of specific decision processes. CPT tools are unobtrusive and seem particularly relevant for evaluating certain decision tasks that may be supported by decision support systems (DSS). CPT tools can be an important component of DSS development. An information systems research taxonomy developed by previous researchers [29] [36] is used to position research work involving the methodology of CPT. Using a critique suggested by Libby [28], CPT tools are evaluated and compared to alternative process tracing tools. A brief empirical example using CPT is provided, and future uses relative to DSS are suggested. The appendix includes an example of a specific CPT tool.
An Experimental Comparison of Time‐Based and Economic‐Based Scheduling Methods to Maximize Net Present Value*
Authors: Rohleder Thomas R. , Scudder Gary D.
Published: June 2007

In the past, performance in dynamic‐scheduling environments was primarily measured in terms of time or physical shop characteristics. Objectives such as mean tardiness, flow time, and work‐in‐process inventory were commonly used. Today, there is increasing interest in the use of more advanced economic performance measures. These measures have the more comprehensive objective of maximizing ownership wealth by economically scheduling jobs and tasks.

This study presents a large‐scale experiment testing time‐based and economic‐based scheduling methods in a dynamic job shop. These methods are evaluated on their ability to maximize net present value (NPV). The study considers the just‐in‐time (JIT) delivery environment. The job shop is hypothetical, but is based on models of real production situations. Results show that the use of very detailed economic information in a sophisticated manner generally improves economic performance. Where due dates are easy to achieve, however, time‐based scheduling methods are at least as good as those based on economics. Also, where utilization is high and due dates tight, early cost information in release and dispatch is detrimental to schedule value.
The Present Value Issue in a Sequential Selection Problem*
Authors: Kwan Clarence C.Y. , Yuan Yufei
Published: June 2007

This note shows that, due to the misapplication of the present value concept, the Chun and Platt (CP) formulation of a sequential selection problem, which intends to improve on the Kwan and Yuan (KY) analysis, is flawed and the decision criterion thus obtained is invalid. In the context of capital budgeting, we make necessary corrections to the CP analysis and establish a decision criterion which is more refined than the KY case. The refined decision criterion enables us to evaluate the KY analysis objectively and to refute CP's argument about its suboptimality. We also address the managerial implications of the refined decision criterion.
The Relationship between Procedural Rationality and Political Behavior in Strategic Decision Making
Authors: Dean James W. , Sharfman Mark P.
Published: June 2007

Despite the central place of rationality and political behavior in the decision‐making literature, we know little about the relationship between these two dimensions. Can decisions be made using both rational and political methods, or must managers use one approach or the other? These questions were addressed in a study of 61 strategic decisions in 24 companies using a multiple‐informant, structured interview protocol. Results indicate that procedural rationality and political behavior are independent dimensions of the strategic decision‐making process. The implications of our findings for future strategic decision‐making research are discussed.
An Evaluation of Capacity Sensitive Order Review and Release Procedures in Job Shops
Authors: Philipoom Patrick R. , Malhotra Manoj K. , Jensen John B.
Published: June 2007

We investigate the performance of capacity‐sensitive order review and release (ORR) procedures in job shop environments that have not been previously explored. Previous research has ignored the case of job shops which must perform to very tight due‐dates because of time‐sensitive customers. We propose and test a new capacity sensitive ORR procedure called path based bottleneck (PBB) in such environments, along with the modified infinite loading (MIL) procedure which has been shown to work well in several studies. We compare the performance of these two controlled release rules with that of immediate release rule under different conditions of capacity utilization and customer specified exogenous duedates. Our results indicate that PBB performs well in lowering total costs when due‐dates are tight, while MIL is a better procedure with relatively loose to medium due‐dates. We also show that in many cases, the shortest processing time (SPT) dispatching rule is a superior performer than a due‐date based rule like critical ratio (CR); a conclusion which is contrary to the existing research in this area. In addition, the shop floor control policies recommended are shown to be sensitive to the cost structure of the firm. The managerial implications of this research in providing effective shop floor control in job shops operating under tight due‐date conditions are also discussed.
Effects of Product Structure Complexity on Multi‐level Lot Sizing*
Authors: Sum Chee‐Choung , Png Daniel Oon‐Sen , Yang Kum‐Khiong
Published: June 2007

As an input to the materials requirement planning (MRP) process, the product structure interacts with the lot‐sizing rules to affect inventories, materials flow, and production costs. Despite engineering constraints, considerable latitude is still available to construct alternate product structures for the same product. An important concern of MRP managers and designers is the impact of product structure complexity on the cost performance of the lot‐sizing rules. To date, there exists no detailed research that provides managers with guidelines that relate the lot‐sizing rules to individual product structure parameters. We report on an extensive experiment to test the effects of individual product structure parameters on the relative cost performance of 11 lot‐sizing rules. Three parameters—the number of items, number of levels, and commonality index—are proposed to characterise product structure complexity and used as factors in an experiment involving a large variety of product structures. The results indicate that all three parameters affect the relative cost differences but not the ranking of the rules. The overall best lot‐sizing rule is Bookbinder and Koch's [11] rule.
Distinguishing Features of Just‐in‐Time Systems in the Make‐to‐Order/Assemble‐to‐Order Environment*
Authors: Handfield Robert
Published: June 2007

Few studies of just‐in‐time (JIT) implementation examine their significance in make‐to‐order manufacturing environments. This study examines the relative importance of several operating variables that are characteristic features of JIT systems within such environments in North America. The results suggest that the most salient features of JIT for make‐to‐order and assemble‐to‐order firms are the elimination of waste (in the form of time and defects), reduced setup time, reduced lotsize, and a smaller pool of suppliers. In addition, the results suggest that the use of non‐domestic suppliers can possibly hinder efforts at JIT implementation of materials procurement.
An Empirically Derived Model for the Adoption of Customer‐based Interorganizational Systems*
Authors: Grover Varun
Published: June 2007

Information systems (IS) researchers are now calling for the need to draw from the empirically rich field of organizational innovation. As the impact of strategic systems is increasingly being felt by organizations, the view that these systems are innovations or innovative uses of technology is becoming prevalent. Customer based interorganizational systems (CIOS) represent one of the most prominent types of such systems. This research investigates CIOS adoption. A model is constructed based on significant studies in innovation to identify factors facilitating the adoption decision of a CIOS. Data are gathered from 226 senior executives. Discriminant analysis is used to identify factors that distinguish adopters from nonadopters. Factor analysis of significant variables yielded a parsimonious model of CIOS adoption. The five factor model includes (1) a proactive technological orientation and (2) an internal push for the system as the two most significant sets of facilitators. Implications for research and practice are then discussed.
The Impact of Learning and Labor Attrition on Worker Flexibility in Dual Resource Constrained Job Shops
Authors: Malhotra Manoj K. , Fry Timothy D. , Kher Hemant V. , Donohue Joan M.
Published: June 2007

This study investigates the impact of worker learning, worker flexibility, and labor attrition on the system performance of a dual resource constrained (DRC) job‐shop. The effects of learning and labor attrition have not been previously addressed in DRC literature. Results from the study, consistent with previous literature, show that the greatest benefits are achieved when inter‐departmental worker flexibility is incrementally introduced into the system. In addition, the learning environment, which depends on the initial processing time of jobs and the learning rates of workers, is shown to impact the acquisition of flexibility. The study also shows that the impact of labor attrition on system performance under certain shop conditions may be significant.
The Value of Supplier Information to Improve Management of a Retailer's Inventory
Authors: van der Schouten Frank Auyn , van Eijs Marc J. G. , Heuts Ruud M. J.
Published: June 2007

The distribution of lead time demand is essential for determining reorder points in inventory systems. Usually, the distribution of lead time demand is approximated directly. However, in some cases it may be worthwhile to take the demand per unit time and lead time into account, particularly when specific information is available.

This paper deals with the situation where a supplier, who produces on order in fixed production cycles, provides information on the status of the coming production run. The retailer can use this information to gain insight into the lead‐time process. A fixed order (svQ) strategy is presented, with a set of reorder points sv depending on the time t until the first possible delivery, which is determined by the information of the supplier. A Markov model that analyzes a given (svQ) strategy is used to quantify the value of the information provided by the supplier. Some numerical examples show that the approach may lead to considerable cost savings compared to the traditional approach that uses only one single reorder point, based on a two‐moments approximation. Using this numerical insight, the pros and cons of a more frequent exchange of information between retailers and suppliers can be balanced.
A Generalized Loss Function for Process Optimization
Authors: Stevens David P. , Baker R. C.
Published: June 2007

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.
A Note on Nucleolus/MTPD Accounting Allocations
Authors: Grange Franklin E. , Kochenberger Gary A.
Published: June 2007

The nucleolus linear programming (LP) method for allocating joint costs associated with a shared resource often stops short of uniquely specifying all savings allocations. Barton [1] recently presented the minimum total propensity to disrupt (MTPD) as a secondary criterion for uniquely determining those allocations not provided by the initial LP solution. Barton demonstrated the uniqueness of his solution on a specific example with a four‐entity grand coalition. We show a practical approach for implementing Barton's two‐step procedure. Our purpose is to make the nucleolus/MTPD model readily accessible to a wide range of practitioners using commonly available spreadsheet tools. We also demonstrate the global optimality of the allocations that the model provides.
Sources and Outcomes of Competitive Advantage: An Exploratory Study in the Furniture Industry
Authors: Dröge Cornelia , Vickery Shawnee , Markland Robert E.
Published: June 2007

We examine a model of the relationships among sources and outcomes of competitive advantage. The model is integrative across business functions and research disciplines. Functional area competencies are considered as sources of advantage, and three competency constructs are introduced: marketing competency, product design and development (innovation) competency, and manufacturing competency. Each functional area construct is defined as the sum of the performance on 31 competitive items, weighted by importance and extent of responsibility. Relationships between the competency constructs (and their interactions) with performance outcomes such as ROI and market share are analyzed. Results from this exploratory study suggest that innovation is a key source of competitive advantage.
Management of Vital Customer Priorities in Job Shop Manufacturing Environments
Authors: Malhotra Manoj K. , Jensen John B. , Philipoom Patrick R.
Published: June 2007

We present a framework for managing vital customer priorities in job‐shop manufacturing environments. We introduce the notion of attaining near‐perfect on‐time delivery service to a small portion of the firm's customers who contribute to a substantial portion of its sales revenue and profits. Consequently we postulate that appropriate order review and release (ORR) policies, along with the dispatching rules used to schedule customer orders, can be combined effectively to achieve the desired customer service results. Several dispatching rules specifically designed for this study are tested under different operating environments in order to derive the recommended set of ORR and dispatching rule policies. Capacity‐based ORR procedures, in conjunction with dispatching rules that pace a job's progress through different operations in its route, provide the best overall performance. The nature of trade‐offs inherent in managing the priorities of vitally important customers are also identified and presented in the form of managerial recommendations that can be used to enhance a job shop's overall performance.
A Value Platform Analysis Perspective on Customer Access Information Technology*
Authors: Kauffman Robert J. , Lally Laura
Published: June 2007

Customer access information technologies (CAITs) provide a link between a firm and its customers. Firms invest in CAITs to reduce costs, increase revenues and market share, lock in existing customers, and capture new ones. These benefits, however, are notoriously difficult to measure. This paper proposes an evaluative method for CAIT deployment called value platform analysis, based on a conceptual model drawn from the theory of retail outlet deployment in marketing science. Value platform analysis evaluates the impact of the features of a CAIT, the features of its immediate site, and the features of the larger environment into which it is deployed on the transactions it generates and the resulting business value outcomes. Value platform analysis is then applied in an electronic banking context. Hypotheses regarding the likely impact of automatic teller machine (ATM) functionality, the immediate site's surrounding traffic, the customer demographics, and the number of competitors in the environment on ATM transactions are evaluated both before and after the merger of two regional ATM networks. The results indicate that there are a number of key features influencing ATM performance. Two distinct ATM deployment scenarios emerge: one for servicing a bank's own customers, and another for providing transaction services for customers for a fee. The merger of regional networks impacts each of these scenarios differently.
Multiattribute Data Presentation and Human Judgment: A Cognitive Fit Perspective*
Authors: Umanath Narayan S. , Vessey Iris
Published: June 2007

We assessed the ability of the cognitive fit theory to explain the performance of certain display formats on multiattribute judgment tasks. This theory suggests that for most effective and efficient problem solving to occur, the problem representation and any tools or aids employed should all support the strategies (methods or processes) required to perform that task. The theory was tested by assessing performance with schematic faces, graphs, and tables on a bankruptcy prediction task. Bankruptcy prediction involves integrating a large amount of data (a number of financial indicators over a number of years), as well as referring to ranges and/or levels of financial indicators. Schematic faces provide a cognitive fit with such tasks since the information in a face can be processed holistically; however, they do not permit decision makers to refer to the underlying data. Graphs facilitate a different integrating process; further, they preserve characteristics of the underlying data. Tables, on the other hand, do not aid the decision maker in integrating information; they provide only the underlying data values. It was hypothesized that graphs would provide the best cognitive fit for the bankruptcy prediction task since they permit processing both integrated and discrete data. Participants made judgments with two of the three display formats, at two levels of information load, in a fractional factorial design. The information load manipulation was designed to provide meaningful and meaningful plus redundant information to the decision maker in a test of information load “per se.” The research findings provided substantial support for the theory of cognitive fit. The findings also have implications for the study of information load.
Decision Analysis Approach to Competitive Situations with a Pure Infinite Regress*
Authors: Strait R. Scott
Published: June 2007

If the standard decision analysis approach was applied to a competitive situation, then the decision maker would attempt to assess a subjective probability distribution over all possible actions by the competitors or rivals. However, in assessing this robability distribution, the decision maker would quickly find him/herself in an infinite regress. There is a range of possible dependencies between the decision maker's decision and the rival's action that lead to such a regress. This paper presents an approach to overcoming this infinite regress in performing decision analyses of competitive situations with a “pure” infinite regress. In a pure infinite regress there is a dependency between the decision maker's decision and the rival's choice of action: if the decision maker prefers one alternative to any other, then the rival's actions will reflect a belief by the rival that the preferred alternative is more likely to be the decision maker's decision. The approach builds the decision maker's preferred rank order of alternatives, while simultaneously constructing a consistent model of the rival's beliefs about the decision maker's decision.