Innovative supply chain optimization models with multiple uncertainty factors

被引:38
作者
Choi, Tsan-Ming [1 ]
Govindan, Kannan [2 ]
Li, Xiang [3 ]
Li, Yongjian [4 ]
机构
[1] Hong Kong Polytech Univ, Inst Text & Clothing, Kowloon, Hong Kong, Peoples R China
[2] Univ Southern Denmark, Dept Technol & Innovat, Ctr Sustainable Supply Chain Engn, DK-5230 Odense M, Denmark
[3] Nankai Univ, Coll Econ & Social Dev, Tianjin 300071, Peoples R China
[4] Nankai Univ, Sch Business, Tianjin 300071, Peoples R China
关键词
Supply chain management; Multiple uncertainty factors; Risk management; ENTERPRISE RISK-MANAGEMENT;
D O I
10.1007/s10479-017-2582-4
中图分类号
C93 [管理学]; O22 [运筹学];
学科分类号
070105 ; 12 ; 1201 ; 1202 ; 120202 ;
摘要
Uncertainty is an inherent factor that affects all dimensions of supply chain activities. In today's business environment, initiatives to deal with one specific type of uncertainty might not be effective since other types of uncertainty factors and disruptions may be present. These factors relate to supply chain competition and coordination. Thus, to achieve a more efficient and effective supply chain requires the deployment of innovative optimization models and novel methods. This preface provides a concise review of critical research issues regarding innovative supply chain optimization models with multiple uncertainty factors. It also introduces the special issue's research papers and their respective insights.
引用
收藏
页码:1 / 14
页数:14
相关论文
共 21 条
[1]   Contracting with demand uncertainty under supply chain competition [J].
Ai, Xingzheng ;
Chen, Jing ;
Ma, Jianhua .
ANNALS OF OPERATIONS RESEARCH, 2012, 201 (01) :17-38
[2]   Is enterprise risk management real? [J].
Arena, Marika ;
Arnaboldi, Michela ;
Azzone, Giovanni .
JOURNAL OF RISK RESEARCH, 2011, 14 (07) :779-797
[3]   The organizational dynamics of Enterprise Risk Management [J].
Arena, Marika ;
Arnaboldi, Michela ;
Azzone, Giovanni .
ACCOUNTING ORGANIZATIONS AND SOCIETY, 2010, 35 (07) :659-675
[4]   Competition and diversification effects in supply chains with supplier default risk [J].
Babich, Volodymyr ;
Burnetas, Apostolos N. ;
Ritchken, Peter H. .
M&SOM-MANUFACTURING & SERVICE OPERATIONS MANAGEMENT, 2007, 9 (02) :123-146
[5]   Supply chain risk analysis with mean-variance models: a technical review [J].
Chiu, Chun-Hung ;
Choi, Tsan-Ming .
ANNALS OF OPERATIONS RESEARCH, 2016, 240 (02) :489-507
[6]   Risk management of logistics systems [J].
Choi, Tsan-Ming ;
Chiu, Chun-Hung ;
Chan, Hing-Kai .
TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW, 2016, 90 :1-6
[7]   Supply chain risk management: a new methodology for a systematic literature review [J].
Colicchia, Claudia ;
Strozzi, Fernanda .
SUPPLY CHAIN MANAGEMENT-AN INTERNATIONAL JOURNAL, 2012, 17 (04) :403-418
[8]   Quantitative models for managing supply chain risks: A review [J].
Fahimnia, Behnam ;
Tang, Christopher S. ;
Davarzani, Hoda ;
Sarkis, Joseph .
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 2015, 247 (01) :1-15
[9]   Interrelationships of risks faced by third party logistics service providers: A DEMATEL based approach [J].
Govindan, Kannan ;
Chaudhuri, Atanu .
TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW, 2016, 90 :177-195
[10]   Investigating risk and robustness measures for supply chain network design under demand uncertainty: A case study of glass supply chain [J].
Govindan, Kannan ;
Fattahi, Mohammad .
INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS, 2017, 183 :680-699