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An empirical investigation of manufacturing flexibility and organizational performance as moderated by strategic integration and organizational infrastructure.

Description: The purpose of this study is empirically investigating four research questions related to manufacturing flexibility. 1) What are the components of manufacturing flexibility? 2) Is there a relationship between manufacturing flexibility and organizational performance? 3) Do integrated strategies strengthen the relationship between manufacturing flexibility and organizational performance? 4) Are there organizational characteristics that strengthen the relationship between manufacturing flexibility and organizational performance? This study used a cross-sectional survey design to collect data from manufacturing organizations in multiple industries. Organizational performance was quantified using common manufacturing measures. Strategic integration and organizational infrastructure were also measured. Data were collected using a self-administered questionnaire. Factor analysis, correlation analysis, and regression were used to analyze the data. The results indicate the variables and expected relationships exist as hypothesized. This study contributes to the manufacturing flexibility body of knowledge by identifying relationships between the manufacturing flexibility component, performance, strategic integration, and organizational infrastructure. The instrument development in this study is of particular value as there are few rigorously developed and validated instruments to measure the manufacturing flexibility components and performance. Understanding these relationships will help practitioners make better decisions in manufacturing organizations as well as enable application of the concepts in this study to other contexts such as service organizations.
Date: August 2008
Creator: Rogers, Pamela Rose Patterson
Partner: UNT Libraries

Trust and Governance in Hybrid Relationships: An Investigation of Logistics Alliances

Description: Transaction cost economics (TCE) theorists traditionally have classified transactions between firms as governed by either market or hierarchy. By assessing characteristics of the transaction - asset specificity, uncertainty, and frequency - firms choose the governance form which minimizes transaction costs, the costs of administering the business deal. During the 1980s, however, TCE has found itself unable to explain the proliferation of strategic alliances. These hybrid relationships seek the benefits of both markets and hierarchies, including quasi-integration, the control of assets without actual ownership. Further, hybrids tend to prefer trust-based relational contracting. TCE's acknowledgment of hybrids, however, raises other questions surrounding the behavioral assumptions which supposedly influence the transaction characteristic governance linkage. Various dissenting researchers have theorized that (1) trust is more dominant in business than opportunism (2) the behavioral assumptions actually function as variables in different contexts, and (3) trust offers an integration mechanism for behavioral variables.
Date: December 1998
Creator: Orr, John Patrick, 1950-
Partner: UNT Libraries

Mathematical Programming Approaches to the Three-Group Classification Problem

Description: In the last twelve years there has been considerable research interest in mathematical programming approaches to the statistical classification problem, primarily because they are not based on the assumptions of the parametric methods (Fisher's linear discriminant function, Smith's quadratic discriminant function) for optimality. This dissertation focuses on the development of mathematical programming models for the three-group classification problem and examines the computational efficiency and classificatory performance of proposed and existing models. The classificatory performance of these models is compared with that of Fisher's linear discriminant function and Smith's quadratic discriminant function. Additionally, this dissertation investigates theoretical characteristics of mathematical programming models for the classification problem with three or more groups. A computationally efficient model for the three-group classification problem is developed. This model minimizes directly the number of misclassifications in the training sample. Furthermore, the classificatory performance of the proposed model is enhanced by the introduction of a two-phase algorithm. The same algorithm can be used to improve the classificatory performance of any interval-based mathematical programming model for the classification problem with three or more groups. A modification to improve the computational efficiency of an existing model is also proposed. In addition, a multiple-group extension of a mathematical programming model for the two-group classification problem is introduced. A simulation study on classificatory performance reveals that the proposed models yield lower misclassification rates than Fisher's linear discriminant function and Smith's quadratic discriminant function under certain data configurations. Data configurations, where the parametric methods outperform the proposed models, are also identified. A number of theoretical characteristics of mathematical programming models for the classification problem are identified. These include conditions for the existence of feasible solutions, as well as conditions for the avoidance of degenerate solutions. Additionally, conditions are identified that guarantee the classificatory non-inferiority of one model over another in the training ...
Date: August 1993
Creator: Loucopoulos, Constantine
Partner: UNT Libraries

Classification by Neural Network and Statistical Models in Tandem: Does Integration Enhance Performance?

Description: The major purposes of the current research are twofold. The first purpose is to present a composite approach to the general classification problem by using outputs from various parametric statistical procedures and neural networks. The second purpose is to compare several parametric and neural network models on a transportation planning related classification problem and five simulated classification problems.
Date: December 1998
Creator: Mitchell, David
Partner: UNT Libraries

The Effect of Certain Modifications to Mathematical Programming Models for the Two-Group Classification Problem

Description: This research examines certain modifications of the mathematical programming models to improve their classificatory performance. These modifications involve the inclusion of second-order terms and secondary goals in mathematical programming models. A Monte Carlo simulation study is conducted to investigate the performance of two standard parametric models and various mathematical programming models, including the MSD (minimize sum of deviations) model, the MIP (mixed integer programming) model and the hybrid linear programming model.
Date: May 1994
Creator: Wanarat, Pradit
Partner: UNT Libraries

IS-MBNQA: A new framework for the relationship between Information Systems and organizational quality.

Description: Despite numerous frameworks and models proposed in the literature, Information Systems (IS) assessment still remains elusive. In addition, little agreement exists on the contribution of the IS function within an organization and on how IS is related to the other organizational dimensions. Frameworks that show the relationship between IS and the organization are in the developmental stage and this work proposes a more comprehensive framework to assist in better understanding the relationship between IS and organizational quality. This research examines two popular IS quality assessment frameworks - Malcolm Baldrige National Quality Award (MBNQA) and Information Systems Assessment (ISA) - and suggests a new framework, IS-MBNQA. This work integrates these two IS quality assessment frameworks into a single comprehensive model that provides a holistic view on how IS quality is interrelated to organizational quality. The existing two IS assessment frameworks attempted to measure IS quality at different levels within an organization. The MBNQA model is the most comprehensive quality framework because it takes an organization wide perspective. On the other hand, ISA employs an IS specific perspective and reflects the relationships of eight major IS success dimensions. ISA is a modified version of DeLone & McLean's model with the inclusion of a success factor for Service Quality. For this study, survey instruments are developed from the MBNQA and ISA frameworks and they are consolidated to allow testing of the single IS-MBNQA framework. Exploratory factor analysis is performed for instrument refinement and confirmatory factor analysis for validity of the models. The instruments developed in this work are utilized as a foundation for identifying the relationships among the dimensions within and between each model. A major contribution of this work is the validation of the 2000 MBNQA model and the extension of existing models/frameworks to better explain the IS contribution to an organization.
Date: December 2001
Creator: Chong, Hyonsong
Partner: UNT Libraries

A Heuristic Procedure for Specifying Parameters in Neural Network Models for Shewhart X-bar Control Chart Applications

Description: This study develops a heuristic procedure for specifying parameters for a neural network configuration (learning rate, momentum, and the number of neurons in a single hidden layer) in Shewhart X-bar control chart applications. Also, this study examines the replicability of the neural network solution when the neural network is retrained several times with different initial weights.
Date: December 1993
Creator: Nam, Kyungdoo T.
Partner: UNT Libraries