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Title: A modeling approach for quality inspection in supply chain quality management
Other Titles: Gong ying lian zhi liang guan li zhong zhi liang jian ce de yi zhong mo xing hua fang fa
Authors: Yan, Jiaqi (顏嘉麒)
Department: Department of Information Systems
Degree: Doctor of Philosophy
Issue Date: 2010
Publisher: City University of Hong Kong
Subjects: Business logistics -- Management.
Quality control.
Notes: CityU Call Number: HD38.5 .Y336 2010
vii, 169 leaves : ill. 30 cm.
Thesis (Ph.D.)--City University of Hong Kong, 2010.
Includes bibliographical references (leaves 147-169)
Type: thesis
Abstract: Supply chain quality management (SCQM) has been facing three major difficulties in both research and practice: 1) the supply chain is a self-interested and distributed system; 2) information asymmetry exists in the production process; 3) quality is difficult to measure accurately and no perfect inspection technology exists. How to deal with these problems has recently received a great deal of attentions from researchers in disciplines such as management science and operations research (MS/OR). Traditional SCQM studies use mathematical models to investigate how to design supply chain contracts to control the self-interested and distributed system under the information asymmetry of the production process. Effective supply chain contracts, such as incentive, warranty, and vendor certification, are employed to leverage the quality performance of the supply chain. However, quality inspection as a fundamental and direct means for SCQM has not been fully investigated, and has been usually suggested to be replaced by other strategies. That’s because quality inspection is related to domain knowledge and is difficult to analyze via traditional MS/OR methodologies. In the decision making of quality inspection in SCQM, domain specific knowledge is required as well as the analysis of different partners’ goals. Traditional modeling methodologies in MS/OM mainly focus on mathematical modeling and the analysis of conflicting goals between supply chain partners. Domain specific knowledge, however, relies on domain quality experts and cannot be represented by traditional mathematical models. This research aims to overcome the limitations of traditional modeling methodologies in MS/OR and provides a new modeling approach, the development process of which follows a design science research paradigm in information systems research, to deal with problems of quality inspection faced in SCQM. In particular, we first discuss how to gain a particular focus, conceptualization, dedication and visualization of the quality inspection problems that are faced in SCQM from a service dominant modeling perspective. By aligning the service-dominant view and service oriented framework, modeling guidelines are provided to develop the model. We provide the detailed modeling process which consists of knowledge level and symbol level modeling and several case studies to illustrate the modeling process. The modeling process adopts goal-oriented modeling technique and belief-desire-intention modeling technique, which not only considers the goal analysis of partner enterprises, but which also has a knowledge representation framework and reasoning mechanism for domain specific knowledge based decision making. A prototype is developed to illustrate how the proposed modeling approach is applied to real world situations. This study contributes to literature from several perspectives. First, we propose a new modeling approach to support decision making of quality inspection in SCQM. This modeling approach enables the solution of problems hitherto unsolved by traditional modeling methodologies, which contributes to the theory literature of SCQM. Second, the creative development and evaluation process of a modeling approach provide design science research contributions. Third, the innovative adoption of a service-dominant perspective on quality management extends and improves the theory foundations of the service dominant logic. Further, the exploration of applying goal-oriented and BDI modeling techniques in SCQM extends and improves existing knowledge representation methodologies.
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