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  • 标题:Collaborative Supply Chain Decision Support And Multi-Attribute Supply Chain Scenarios
  • 作者:Joseph M. Ragan ; Ian Faber ; Sean Quinn
  • 期刊名称:International Business & Economics Research Journal
  • 印刷版ISSN:1535-0754
  • 电子版ISSN:2157-9393
  • 出版年度:2004
  • 卷号:3
  • 期号:6
  • 语种:English
  • 出版社:The Clute Institute for Academic Research
  • 摘要:Todays Global economy is putting a premium on the ability of companies and their professional employees to rapidly evaluate a broad range of decisions in collaboration with both existing and prospective supply chain partners. This includes the development, evaluation and refinement of product designs, the evaluation of alternatives sourcing options, the evaluation of requests for bids, etc. A key difficulty in supporting the collaborative development, evaluation and refinement of alternative courses of action across different organizations lies in the complexity of the solutions involved (e.g. complex production schedules spanning multiple organizations, complex product designs or configurations involving large numbers of parts and components that are procured from a number of suppliers, etc.). Given a growing and ongoing need to revitalize the accounting curriculum and explore eclectic methods to teach accounting information systems, real challenges and opportunities exist to import this material into the accounting systems classroom. The Business Process Integration Lab at Saint Josephs University has developed a prototype environment for collaborative development, evaluation and refinement of supply chain management scenarios (e.g. requests for bids, product designs, sourcing options). The environment relies on the use of Enterprise Resource Planning software, using SAP R/3 to streamline and integrate the supply chain. Through the use of application scenarios, students are able to develop a total understanding of the power of the ERP technology tool as a decision maker and problem-solver, while enhancing their knowledge of the system in modules such as Production Planning and Customer Order Management. It is possible to support powerful workflow management functionality in the context of both interactive and highly automated decision making processes. This functionality has been operational for some three years and is coordinated by senior level graduate and undergraduate students who develop and test the scenarios and assist other students as they navigate through the R/3 system.
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