Global supply chain network design and Asian analysis with material-based carbon emissions and tax

2017 ◽  
Vol 113 ◽  
pp. 779-792 ◽  
Author(s):  
Tomoyuki Urata ◽  
Tetsuo Yamada ◽  
Norihiro Itsubo ◽  
Masato Inoue
2018 ◽  
Vol 2018 ◽  
pp. 1-19 ◽  
Author(s):  
Xianglan Jiang ◽  
Jiuping Xu ◽  
Jiarong Luo ◽  
Fei Zhao

Sustainable supply chain network design has attracted great attention of academia and industry in recent years. Baijiu is one of the world’s oldest distilled alcoholic beverages and plays a significant role in Chinese culture and Chinese people’s daily life. As the production and consumption of Baijiu have a significant influence on the economic, environmental, and social performance of supply chain management, sustainable supply chain network design decisions are critical to the long-term success of the industry. In concert with the rapidly growing Chinese economy, there is a growing demand for a sustainable Baijiu industry. Therefore, this paper constructs and optimizes a network decision-support model for a sustainable Baijiu industry network design. To achieve this, the Baijiu supply chain is examined and a model is proposed for a design that encompasses economic (costs), environmental (carbon emissions), and social (local employment and regional per capita GDP) dimensions. R language programming is then applied to solve the model. A case example indicated that S1 was the optimal decision for reducing costs, S2 was the optimal solution for minimizing carbon emissions, and S3 was the best for maximizing the social impact. Considering the situation of the Baijiu industry and the focal enterprise, it was concluded that S1 would be the best solution for the case company. And the results verified the effectiveness of the framework. This paper develops a systematic and effective approach that decision-makers can use to conduct sustainable network design for Baijiu enterprises.


Kybernetes ◽  
2019 ◽  
Vol 48 (5) ◽  
pp. 930-948 ◽  
Author(s):  
Xinxuan Cheng ◽  
Guoqing Yang ◽  
Longfei Fan

Purpose This paper aims to develop an uncertain global supply chain network design (GSCND) model with rules of origin (RoOs) and limited import quotas, and to discuss the international factors’ effects on location decisions. Design/methodology/approach The authors establish an uncertain GSCND model with the international factors. The transportation costs and customers’ demands are characterized as random variables. To deal with the risk of uncertainty, the authors introduce the customers’ demand service level. A sample approximation approach (SAA) is used to deal with the service level constraint and turn the proposed model into a mixed integer programming. On the basis of the properties of the proposed model, a hybrid memetic algorithm (MA) is designed to solve it. Findings The authors find that the proposed MA is efficient to the real supply chain network design problem. Besides, the RoOs and limited import quotas can affect the optimal choices of plant and distribution center locations. Originality/value The authors propose an uncertain GSCND model with RoOs and limited import quotas. An MA with SAA is designed to solve the proposed model. The authors apply the proposed model into a real global supply chain of an apparel corporation in East Asia, and give some managerial insights.


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