Evaluating supply chain integration: a case study using fuzzy logic

被引:20
作者
Cigolini, R. [1 ]
Rossi, T. [1 ]
机构
[1] Univ Carlo Cattaneo LIUC, Inst Technol, Castellanza, Italy
关键词
supply chain management; fuzzy set; case study;
D O I
10.1080/09537280801916249
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
This paper aims at investigating a new methodology to evaluate supply chain integration by applying the fuzzy sets theory. Fuzzy sets proved successful in environments similar to supply chain management in that they help to formalise human reasoning patterns and to develop high-performance expert systems in contexts where data are affected by uncertainty and/or vagueness: e.g. fuzzy sets have been already used in inventory planning, to improve organisational effectiveness, to perform suppliers' evaluation etc. In particular, the study presented here deals with the ways to measure and achieve supply chain integration and it mainly focuses on the external integration (i.e. on the ability to leverage partnerships within the chain), clustered in two areas, i.e. the network design and the management policies. The new methodology has been applied to a case study which consists of a 3-stage supply chain belonging to the beauty and personal care industry. Results of the case-study indicate that the companies still have important edges for improvement towards a complete integration of their supply processes. In particular, the considered supply chain should prioritise the integration of technology-driven investments and in the distribution area.
引用
收藏
页码:242 / 255
页数:14
相关论文
共 47 条
[1]  
[Anonymous], SUPPLY CHAIN STRUCTU
[2]  
[Anonymous], 1993, INTEGRATED DISTRIBUT
[3]  
[Anonymous], 2003, Collaborative manufacturing: Using real time information to support the supply chain
[4]   A new model for the strategic management of inventories subject to peaks in market demand [J].
Brandolese, A ;
Cigolini, R .
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH, 1999, 37 (08) :1859-1880
[5]   Improving supply-chain collaboration by linking intelligent agents to CPFR [J].
Caridi, M ;
Cigolini, R ;
De Marco, D .
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH, 2005, 43 (20) :4191-4218
[6]   Fuzzy production inventory for fuzzy product quantity with triangular fuzzy number [J].
Chang, SC .
FUZZY SETS AND SYSTEMS, 1999, 107 (01) :37-57
[7]   RANKING FUZZY NUMBERS WITH MAXIMIZING SET AND MINIMIZING SET [J].
CHEN, SH .
FUZZY SETS AND SYSTEMS, 1985, 17 (02) :113-129
[8]   New methods for students' evaluation using fuzzy sets [J].
Chen, SM ;
Lee, CH .
FUZZY SETS AND SYSTEMS, 1999, 104 (02) :209-218
[9]   Improving productivity of automated tissue converting lines: an empirical model and a case study [J].
Cigolini, R ;
Rossi, T .
PRODUCTION PLANNING & CONTROL, 2004, 15 (05) :550-563
[10]   A new framework for supply chain management - Conceptual model and empirical test [J].
Cigolini, R ;
Cozzi, M ;
Perona, M .
INTERNATIONAL JOURNAL OF OPERATIONS & PRODUCTION MANAGEMENT, 2004, 24 (1-2) :7-41