bluuebunny/crossref_metadata_2025_split huggingface dataset:
Designing Distribution Systems to Support Vendor Strategies in Supply Chain Management*
Authors: Robinson E. Powell , Satterfield Ronald K. 
Published: June 2007

ABSTRACTThe interactions among a firm's distribution strategy, market share, and distribution costs are an important consideration in the design of supply chain networks. However, these interactions are largely ignored by existing distribution system design methodologies, which assume demand is constant regardless of the firm's distribution strategy. This paper describes a multidisciplinary framework that considers these interactions in the design of “profit maximizing” distribution networks. The framework employs two major decision support methodologies: (1) binary logit models for estimating market share considering various demand‐influencing parameters such as product price and distribution service, and (2) a mixed‐integer programming (MIP) model for finding optimal distribution network designs. We applied the framework to an actual design problem facing a national distributor of industrial chemical products. The test results verify the framework's large‐scale capability and the potential benefit of the integrated solution methodology.
An Efficient Heuristic Procedure for Practical‐Sized Capacitated Warehouse Design and Management*
Authors: Jayaraman Vaidyanathan 
Published: June 2007

ABSTRACTThe purpose of this paper is to refine and test a distribution system design model and evaluate its performance with respect to solution quality, model validation, and algorithm performance. The paper reports on the development of a multiproduct warehouse logistics model. The logistics model is used to predict the performance of distribution companies that typically have to deal with product costs, the cost to distribute the products from a set of warehouses to customer outlets, the level of service provided to its customers, and flexibility for each product group and market segment.
Learning by Objectives for Adaptive Shop‐Floor Scheduling*
Authors: Bhattacharyya Siddhartha , Koehler Gary J. 
Published: June 2007

ABSTRACTEffective production scheduling requires consideration of the dynamics and unpredictability of the manufacturing environment. An automated learning scheme, utilizing genetic search, is proposed for adaptive control in typical decentralized factory‐floor decision making. A high‐level knowledge representation for modeling production environments is developed, with facilities for genetic learning within this scheme. A multiagent framework is used, with individual agents being responsible for the dispatch decision making at different workstations. Learning is with respect to stated objectives, and given the diversity of scheduling goals, the efficacy of the designed learning scheme is judged through its response under different objectives. The behavior of the genetic learning scheme is analyzed and simulation studies help compare how learning under different objectives impacts certain aggregate measures of system performance.
A Risk‐sharing Approach to Transfer Pricing and Incentive Compensation Problems under Exchange Rate Uncertainty*
Authors: Yahya‐Zadeh Massood 
Published: June 2007

ABSTRACTThis study examines the transfer pricing and incentive compensation problems in a multinational enterprise facing currency risk. It is shown that, in the presence of diverse risk preferences among managers, the Hirshleifer (1956) transfer pricing rule results in inefficient resource allocation decisions by division managers. Following the approach developed by Kanodia (1979), two transfer pricing and compensation systems are proposed. The proposed systems enable central management to achieve efficient resource allocation and partial or global risk sharing. It is also argued that the proposed plans can be implemented in conjunction with existing transfer pricing systems that primarily serve tax and tariff concerns.
The Value of Using Scheduling Information in Planning Material Requirements*
Authors: Kanet John J. , Sridharan V. 
Published: June 2007

ABSTRACTCurrent research and practice in the field of production and inventory planning is dominated by hierarchical, material requirements planning‐based methods. The objective of this research is to determine the merits of a major redirection for the design of manufacturing planning systems—a direction that more directly exploits the capabilities of modern computer technology. We test the relative performance of two fundamentally different classes of manufacturing planning systems: (1) those that make no use of sequencing and scheduling information in the planning of material deliveries (for example, traditional MRP‐based systems), and (2) those that use sequencing and scheduling information to plan delivery of materials. We first derive an analytical expression for the expected benefit (in terms of flow time reduction) of using scheduling information for a single machine system. We then describe and test a simple heuristic for predicting the improvement that could be realized in more complicated multimachine systems, under certain conditions. Results from controlled simulation experiments, over a wide range of operating environments, suggest that although the value of scheduling information is influenced by the operating environment, it could be substantial.
Computer Simulation Success: On the Use of the End‐User Computing Satisfaction Instrument: A Comment
Authors: McHaney Roger , Cronan Timothy Paul 
Published: June 2007

ABSTRACTThis comment is part of a comprehensive study to develop a contingency model of simulation success. The current study focuses on the psychometric stability of the end‐user computing satisfaction (EUCS) instrument by Doll and Torkzadeh (1988) when applied to users of computer simulation. Using a survey of 411 users, the researchers provide evidence that the EUCS instrument is a valid and reliable measure of computer simulation success. Given this evidence, managers and simulation software product developers can confidently apply the instrument in the investigation of competing tools, features, and technologies.
Selecting a Portfolio of Technologies: An Application of Decision Analysis
Authors: Jackson Jack A. , Kloeber Jack M. , Ralston Brian E. , Deckro Richard F. 
Published: June 2007

ABSTRACTThe Department of Energy is faced with the critical and complex decision of selecting technologies for waste site remediation. This research focuses on developing a decision support tool which assists the decision maker to find an optimal portfolio. A portfolio consists of selecting the appropriate processes for a remediation site and, subsequently, selecting a technology for each process so that the decision maker's objectives are achieved. The measures supporting the objectives are risk, life‐cycle cost, and time required for remediation. The model uses exponential attribute utility functions with an additive objective function. The model provides the decision maker with estimates of the cost and time distributions, and their associated utility. Cumulative frequency distributions illustrate the dominance of technology choices and the variance in the results. The model permits sensitivity analysis in the form of rainbow and tornado diagrams to display the effects of changes in the values of the input variables. Overall, the model provides a generic technology selection tool that can be used to make better informed decisions and may be easily manipulated to reflect changes in the remediation process.
Are Individual Differences Germane to the Acceptance of New Information Technologies?
Authors: Agarwal Ritu , Prasad Jayesh 
Published: June 2007

ABSTRACTPersuading users to adopt new information technologies persists as an important problem confronting those responsible for implementing new information systems. In order to better understand and manage the process of new technology adoption, several theoretical models have been proposed, of which the technology acceptance model (TAM) has gained considerable support. Beliefs and attitudes represent significant constructs in TAM. A parallel research stream suggests that individual difference factors are important in information technology acceptance but does not explicate the process by which acceptance is influenced. The objective of this paper is to clarify this process by proposing a theoretical model wherein the relationship between individual differences and IT acceptance is hypothesized to be mediated by the constructs of the technology acceptance model. In essence then, these factors are viewed as influencing an individual's beliefs about an information technology innovation; this relationship is further supported by drawing upon extensive research in learning. The theoretical model was tested in an empirical study of 230 users of an information technology innovation. Results confirm the basic structure of the model, including the mediating role of beliefs. Results also identify several individual difference variables that have significant effects on TAM's beliefs. Theoretical contributions and practical implications that follow are discussed.
Axiomatic Justification for a Geometric Quality Aggregation Function
Authors: Sampson Scott E. 
Published: June 2007

ABSTRACTA central issue in many decision‐making situations is the need to consider multiple factors. A special case of multifactor modeling is the quality aggregation problem, which is to derive an overall quality measurement from a set of component quality measurements. Although much research has been published regarding the components of a quality construct, alternative methods for aggregating quality components have been largely ignored. The function generally used for this aggregation is an arithmetic weighted average. This article proposes four axioms that are intuitively desirable in a quality aggregation function. Concepts are drawn from related disciplines such as utility theory, decision theory, and microeconomics. Empirical evidence is presented to support the axioms. The arithmetic weighted average function is found to be inconsistent with all four axioms. A geometric, or multiplicative, function form is presented as a superior alternative, consistent with the four axioms. Model specification issues and other implications are discussed.
A DEA Framework to Assess the Efficiency of the Software Requirements Capture and Analysis Process*
Authors: Chatzoglou Prodromos D. , Soteriou Andreas C. 
Published: June 2007

ABSTRACTIn this paper a theoretical framework to assess the efficiency of the Requirements Capture and Analysis (RCA) process in software development is introduced. Although it is widely recognized that successful implementation of the first stages of the software development process is critical for the overall development process, RCA efficiency assessments have not been given much attention. The presented theoretical framework to assess RCA efficiency follows a production approach to model the early stages of a software project. An approach based on Data Envelopment Analysis that utilizes the proposed framework to isolate the effects of exogenous factors, such as the environment or the type of project, on the project's RCA efficiency is also presented. Finally, the applicability of the methodology through an exploratory empirical study is demonstrated, and managerial implications are discussed.
A Contingent View of Quality Management‐The Impact of International Competition on Quality
Authors: Das Ajay , Handfield Robert B. , Calantone Roger J. , Ghosh Soumen 
Published: June 2007

Much of the research on quality practices and performance reflects a resource‐based perspective of the firm, dealing primarily with internal issues of managerial and technological competence in developing and executing an effective TQM strategy. The neoclassical perspective on the influence of the competitive environment on quality practices and performance remains conspicuously absent in the empirical quality literature. Our study aims to address this gap by examining the contingent role of international competition on quality management and performance.We develop and test an integrative framework of quality management, consisting of high involvement work practices, quality practices, quality performance, and firm performance. We then examine the contingent effects of international competition on the constructs and relationships of the framework. International competition was found to moderate the relationship between quality practices and customer satisfaction performance, as well as the relationship between high involvement work practices and firm performance. The moderator effects suggest interesting implications for quality theory and practice.
The Joint Effects of Effort and Quality on Decision Strategy Choice with Computerized Decision Aids*
Authors: Chu P. C. , Spires Eric E. 
Published: June 2007

ABSTRACTResearch has recently focused on the effort‐reduction or minimization role of computerized decision aids, and how users may employ aids to manage their effort, which in turn affects their choice of decision strategies. In this paper, it is argued that consideration of effort reduction or minimization by itself is not sufficient for inducing changes in decision strategy. Instead, decision aid effects on effort must be considered jointly with the decision quality associated with the various decision strategies. This is true even if the decision aid has no effect on decision quality. We adapt and extend a theoretical framework that can be used to evaluate the joint effects of effort and quality on decision strategy choice. In addition, we reinterpret past research results in light of the framework and present new experimental evidence on the descriptive validity of the framework.
Distribution of Aggregate Utility Using Stochastic Elements of Additive Multiattribute Utility Models
Authors: Moskowitz Herbert , Tang Jen , Lam Peter 
Published: June 2007

ABSTRACTConventionally, elements of a multiattribute utility model characterizing a decision maker's preferences, such as attribute weights and attribute utilities, are treated as deterministic, which may be unrealistic because assessment of such elements can be imprecise and erroneous, or differ among a group of individuals. Moreover, attempting to make precise assessments can be time consuming and cognitively demanding. We propose to treat such elements as stochastic variables to account for inconsistency and imprecision in such assessments. Under these assumptions, we develop procedures for computing the probability distribution of aggregate utility for an additive multiattribute utility function (MAUF), based on the Edgeworth expansion. When the distributions of aggregate utility for all alternatives in a decision problem are known, stochastic dominance can then be invoked to filter inferior alternatives. We show that, under certain mild conditions, the aggregate utility distribution approaches normality as the number of attributes increases. Thus, only a few terms from the Edgeworth expansion with a standard normal density as the base function will be sufficient for approximating an aggregate utility distribution in practice. Moreover, the more symmetric the attribute utility distributions, the fewer the attributes to achieve normality. The Edgeworth expansion thus can provide a basis for a computationally viable approach for representing an aggregate utility distribution with imprecisely specified attribute weights and utilities assessments (or differing weights and utilities across individuals). Practical guidelines for using the Edgeworth approximation are given. The proposed methodology is illustrated using a vendor selection problem.
Telecommunications Network Design—Comparison of Alternative Approaches
Authors: Premkumar G. , Chu Chao‐Hsien , Chou Hsinghua 
Published: June 2007

ABSTRACTThe design and development of the network infrastructure to support mission‐critical applications has become a critical and‐complex activity. This study explores the use of genetic algorithms (GA) for network design in the context of degree‐constrained minimal spanning tree (DCMST) problem; compares for small networks the performance of GA with a mathematical model that provides optimal solutions; and for larger networks, compares GA's performance with two heuristic methods—edge exchange and primal algorithm. Two performance measures, solution quality and computation time, are used for evaluation. The algorithms are evaluated on a wide variety of network sizes with both static and dynamic degree constraints on the network nodes. The results indicate that GA provides optimal solutions for small networks. For larger networks it provides better solution quality compared to edge exchange and primal method, but is worse than the two methods in computation time.
A Comparison of Selected Artificial Neural Networks that Help Auditors Evaluate Client Financial Viability
Authors: Etheridge Harlan L. , Sriram Ram S. , Hsu H. Y. Kathy 
Published: June 2007

ABSTRACTThis study compares the performance of three artificial neural network (ANN) approaches—backpropagalion, categorical learning, and probabilistic neural network—as classification tools to assist and support auditor's judgment about a client's continued financial viability into the future (going concern status). ANN performance is compared on the basis of overall error rates and estimated relative costs of misclassificaticn (incorrectly classifying an insolvent firm as solvent versus classifying a solvent firm as insolvent). When only the overall error rate is considered, the probabilistic neural network is the most reliable in classification, followed by backpropagation and categorical learning network. When the estimated relative costs of misclassification are considered, the categorical learning network is the least costly, followed by backpropagation and probabilistic neural network.
Evaluation of Embedded Intelligent Real‐time Systems*
Authors: Grabowski Martha , Sanborn Stephen D. 
Published: June 2007

AbstractOver the past two decades, questions have surfaced about the effectiveness and contribution of intelligent systems to decision makers in a variety of settings. This paper focuses on the evaluation challenges associated with intelligent real‐time software systems that are embedded in larger host systems. With the proliferation of such systems in operational settings such as aerospace, medical, manufacturing, and transportation systems, increased attention to evaluations of such systems, and to resulting software safety, is warranted. This paper describes one such evaluation and proposes a set of evaluation criteria for embedded intelligent real‐time systems (EIRTS). Implications of the evaluation and the evaluation criteria are discussed.
Effective Design of Products/Services: An Approach Based on Integration of Marketing and Operations Management Decisions*
Authors: Verma Rohit , Thompson Gary M. , Moore William L. , Louviere Jordan J. 
Published: June 2007

AbstractThis paper presents an integrated framework for designing profit‐maximizing products/ services, which can also be produced at reasonable operating difficulty levels. Operating difficulty is represented as a function of product and process attributes, and measures a firm's relative ease or difficulty in meeting customer demand patterns under specified operating conditions. Earlier optimum product design procedures have not considered. operational difficulty. We show that optimum profit, market share, cost, and product profiles are dependent on operating difficulty level. Empirical results from the pizza delivery industry demonstrate the value of the proposed Effective Product/Service Design approach.
A Structural Equation Model of New Product Design and Development*
Authors: Tan Keah Choon 
Published: June 2007

AbstractThis research uses structural equation modeling to analyze the effects of supplier assessment, Just‐In‐Time, and quality management strategies on new product design and development. A survey of senior managers who are members of the American Production and Inventory Control Society in the United States was used to test the relationships between the constructs in the model. In general, the survey results supported the proposed structural equation model. The data showed that supplier assessment and Just‐In‐Time strategies were correlated and affected the quality management strategy used, which in turn influenced the new product design and development strategy. The data also showed that the Just‐In‐Time strategy directly influenced the new product design and development strategy.
Organization Structure from a Loose Coupling Perspective: A Multidimensional Approach*
Authors: Beekun Rafik I. , Glick William H. 
Published: June 2007

AbstractOrganizational theories frequently rely on notions of sharing and dependence among organizational participants, but researchers usually focus on characteristics of the actors themselves instead of the relational patterns among the actors. Loose coupling is one conceptual tool that emphasizes relational patterns. Loose coupling, however, is an abstract metaphor that is simultaneously fertile and ambiguous. This paper develops a rigorous and comprehensive framework that sharpens the theoretical contributions of loose coupling to our understanding of structural relationships. Characteristics of loose coupling capture some important and underexplored features of multidimensional fit and interdependence in organizations. The proposed framework clarifies these theoretical contributions of loose coupling with concepts and equations modified from network analysis. Testable hypotheses are proposed with respect to three key independent variables that may affect patterns of coupling: organization strategy, technology, and environmental turbulence. Additional hypotheses are advanced with respect to the use of the multidimensional approach to loose coupling in studying new organizational forms. Initial psychometric and empirical evidence are presented.
The Effectiveness of Decisional Guidance: An Empirical Evaluation
Authors: Parikh Mihir , Fazlollahi Bijan , Verma Sameer 
Published: June 2007

AbstractDecisional guidance is defined as how a decision support system (DSS) influences its users as they structure and execute the decision‐making process. It is assumed that decisional guidance has profound effects on decision making, but these effects are understudied and empirically unproven. This paper describes an empirical, laboratory‐experiment‐based evaluation of the effectiveness of deliberate decisional guidance and its four types. We developed and used a comprehensive model consisting of four evaluation criteria: decision quality, user satisfaction, user learning, and decision‐making efficiency. On these criteria, we compared decisional guidance versus no guidance, informative versus suggestive decisional guidance, and predefined versus dynamic decisional guidance. We found that deliberate decisional guidance was more effective on all four criteria; suggestive guidance was more effective in improving decision quality and user satisfaction, and informative guidance was more effective in user learning about the problem domain, whereas dynamic guidance was more effective than predefined guidance in improving decision quality and user learning; and both suggestive guidance and dynamic guidance reduced the decision time.