Problem taxonomy: a step towards effective information sharing in supply chain management

Information sharing is a key enabler for supply chain management. The type of information required depends upon the supply chain problem to be solved. In this paper, supply chain problem taxonomy is proposed as the theoretical basis for designing information required for problem-solving. Problem taxonomy provides the overall framework under which problem-oriented information system components can be designed, and implemented. Supply chain problem taxonomy comprises: (a) classification of supply chain problems, (b) classification of problem solving methodologies for supply chain management, and (c) hierarchical classification of variables or factors necessary for dealing with problems. A reference model is proposed for formally representing these components. This paper also describes problem-specific information modeling implementation and how it can be applied in solving real-world problems.

[1]  Yosef Sheffi.  Some analytical problems in logistics research , 1985 .

[2]  D. Lambert,et al.  Issues in Supply Chain Management , 2000 .

[3]  Marinos Themistocleous,et al.  Evaluating the integration of supply chain information systems: A case study , 2004, Eur. J. Oper. Res..

[4]  William L. Berry,et al.  Approaches to mass customization: configurations and empirical validation , 2000 .

[5]  Jeffery K. Cochran,et al.  A set covering formulation for agile capacity planning within supply chains , 2005 .

[6]  Paul W. H. Chung,et al.  Knowledge-based process management - an approach to handling adaptive workflow , 2003, Knowl. Based Syst..

[7]  Paul E. Fischer,et al.  Special Issue on Design and Development: Performance Measurement and Design in Supply Chains , 2001, Manag. Sci..

[8]  C. D. Brennan.  Integrating the healthcare supply chain. , 1998, Healthcare financial management : journal of the Healthcare Financial Management Association.

[9]  Raymond Reiter,et al.  Temporal Reasoning in Logic Programming: A Case for the Situation Calculus , 1993, ICLP.

[10]  Fu-Ren Lin,et al.  A generic structure for business process modeling , 2002, Bus. Process. Manag. J..

[11]  Nam P. Suh,et al.  Axiomatic Design Theory for Systems , 1998 .

[12]  Fabrizio Salvador,et al.  Supply-chain configurations for mass customization , 2004 .

[13]  A. Claudio Garavelli,et al.  Flexibility configurations for the supply chain management , 2003 .

[14]  Alexander V. Smirnov,et al.  E‐management of supply chain: general models taxonomy , 2002 .

[15]  Charu Chandra,et al.  A DATA DRIVEN APPROACH TO AUTOMATED SIMULATION MODEL BUILDING , 2003 .

[16]  Ronald H. Ballou,et al.  Unresolved Issues in Supply Chain Network Design , 2001, Inf. Syst. Frontiers.

[17]  Steffen Schulze-Kremer.  Discovery in the human genome project , 1999, Commun. ACM.

[18]  H.L. Lee,et al.  Aligning Supply Chain Strategies with Product Uncertainties , 2002, IEEE Engineering Management Review.

[19]  Benita M. Beamon,et al.  Supply-chain network configuration for product recovery , 2004 .

[20]  M. Shaw,et al.  A strategic analysis of inter organizational information sharing , 2006, Decis. Support Syst..

[21]  D. Towill,et al.  Analysis and design of focused demand chains , 2002 .

[22]  M. Frohlich,et al.  Arcs of integration: an international study of supply chain strategies , 2001 .

[23]  Victoria C. P. Chen,et al.  Performance analysis of conjoined supply chains , 2001 .

[24]  M. Caridi,et al.  Improving supply-chain collaboration by linking intelligent agents to CPFR , 2005 .

[25]  Lotfi A. Zadeh,et al.  General System Theory , 1962 .

[26]  Andi Cakravastia,et al.  A two-stage model for the design of supply chain networks , 2002 .

[27]  Ian P. McCarthy,et al.  Manufacturing classification: Lessons from organizational systematics and biological taxonomy , 1995 .

[28]  Takashi Kobayashi,et al.  Business process integration as a solution to the implementation of supply chain management systems , 2003, Inf. Manag..

[29]  D. Lambert,et al.  Supply Chain Management: Implementation Issues and Research Opportunities , 1998 .

[30]  Christopher M. McDermott,et al.  Configurations in manufacturing strategy: a review and directions for future research , 1998 .

[31]  P. Andersen,et al.  Bridges over troubled water: suppliers as connective nodes in global supply networks , 2005 .

[32]  Gérard P. Cachon,et al.  Supply Chain Coordination with Revenue-Sharing Contracts: Strengths and Limitations , 2005, Manag. Sci..

[33]  P. Fiala.  Information sharing in supply chains , 2005 .

[34]  Augustine A. Lado,et al.  Strategic purchasing, supply management, and firm performance , 2004 .

[35]  Mark S. Fox,et al.  Agent-Oriented Supply-Chain Management , 2000 .

[36]  R. Lamming,et al.  A Taxonomy of Supply Networks , 2001 .

[37]  Chu‐Hua Kuei,et al.  Designing and Managing the Supply Chain Concepts, Strategies, and Case Studies , 2000 .

[38]  Keith Ridgway,et al.  Organisational diversity, evolution and cladistic classifications , 2000 .

[39]  Ernst Mayr,et al.  Principles of systematic zoology , 1969 .

[40]  Vitaly Dubrovsky,et al.  Toward system principles: general system theory and the alternative approach , 2004 .

[41]  Ricardo Ernst,et al.  Evaluation of supply chain structures through modularization and postponement , 2000, Eur. J. Oper. Res..

[42]  M. Fisher,et al.  CONFIGURING A SUPPLY CHAIN TO REDUCE THE COST OF DEMAND UNCERTAINTY , 1997 .

[43]  W. Wilhelm,et al.  Strategic, tactical and operational decisions in multi-national logistics networks: A review and discussion of modelling issues , 2000 .

[44]  D. Simchi-Levi.  Designing And Managing The Supply Chain , 2007 .

[45]  Enver Yücesan,et al.  The impact of ERP on supply chain management: Exploratory findings from a European Delphi study , 2003, Eur. J. Oper. Res..

[46]  H. Lau,et al.  On a responsive supply chain information system , 2000 .

[47]  Perakath C. Benjamin,et al.  Towards a truly integrated enterprise modeling and analysis environment , 2003, Comput. Ind..

[48]  J. Bramham,et al.  The demand driven chain [product configurator] , 2004 .

[49]  P. Rich.  The Organizational Taxonomy: Definition and Design , 1992 .

[50]  Keith Ridgway,et al.  Cladistics: a taxonomy for manufacturing organizations , 2000 .

[51]  Yossi Aviv,et al.  The Effect of Collaborative Forecasting on Supply Chain Performance , 2001, Manag. Sci..

[52]  Nam P. Suh,et al.  Design and operation of large systems , 1995 .

[53]  B. McKelvey.  Organizational Systematics-Taxonomy, Evolution, Classification , 1982 .

[54]  B. Beamon.  Supply chain design and analysis:: Models and methods , 1998 .

[55]  Hans-Jörg Bullinger,et al.  Analysing supply chain performance using a balanced measurement method , 2002 .

[56]  Gordon Stewart,et al.  Supply‐chain operations reference model (SCOR): the first cross‐industry framework for integrated supply‐chain management , 1997 .

[57]  Janis Grabis,et al.  Application of multi-steps forecasting for restraining the bullwhip effect and improving inventory performance under autoregressive demand , 2005, Eur. J. Oper. Res..

[58]  Martin Verwijmeren,et al.  Software component architecture in supply chain management , 2004, Comput. Ind..

[59]  Brennan Cd.  Integrating the healthcare supply chain. , 1998 .

[60]  Rajiv Khosla,et al.  Unified problem modeling language for knowledge engineering of complex systems , 2004, Soft Comput..

[61]  Charu Chandra,et al.  Ontology driven knowledge design and development for supply chain management , 2004 .

[62]  Gene Fliedner,et al.  CPFR: an emerging supply chain tool , 2003, Ind. Manag. Data Syst..