PMID- 31877860
OWN - NLM
STAT- MEDLINE
DCOM- 20200505
LR  - 20200505
IS  - 1660-4601 (Electronic)
IS  - 1661-7827 (Print)
IS  - 1660-4601 (Linking)
VI  - 17
IP  - 1
DP  - 2019 Dec 22
TI  - Supplier Selection and Order Allocation under a Carbon Emission Trading Scheme: A 
      Case Study from China.
LID - 10.3390/ijerph17010111 [doi]
LID - 111
AB  - In implementing carbon emission trading schemes (ETSs), the cost of carbon 
      embedded in raw materials further complicates supplier selection and order 
      allocation. Firms have to make decisions by comprehensively considering the cost 
      and the important intangible performance of suppliers. This paper uses an 
      analytic network process-integer programming (ANP-IP) model based on a 
      multiple-criteria decision-making (MCDM) approach to solve the above issues by 
      first evaluating and then optimizing them. The carbon embedded in components, 
      which can be used to reflect the carbon competitiveness of a supplier, is 
      integrated into the ANP-IP model. In addition, an international large-scale 
      electronic equipment manufacturer in China is used to validate the model. 
      Different scenarios involving different carbon prices are designed to analyze 
      whether China's current ETS drives firms to choose more low-carbon suppliers. The 
      results show that current carbon constraints are not stringent enough to drive 
      firms to select low-carbon suppliers. A more stringent ETS with a higher carbon 
      price could facilitate the creation of a low-carbon supply chain. The analysis of 
      the firm's total cost and of the total cost composition indicates that the impact 
      of a more stringent ETS on the firm results mainly from indirect costs instead of 
      direct costs. The indirect cost is caused by the suppliers' transfer of part of 
      the low-carbon investment in the product, and arises from buying carbon permits 
      with high carbon prices. Implications revealed by the model analysis are 
      discussed to provide guidance to suppliers regarding the balance between soft 
      competitiveness and low-carbon production capability and to provide guidance to 
      the firm on how to cooperate with suppliers to achieve a mutually beneficial 
      situation.
FAU - Wang, Chen
AU  - Wang C
AD  - Donlinks School of Economics and Management, University of Science and Technology 
      Beijing, Beijing 100083, China.
FAU - Yang, Qingyan
AU  - Yang Q
AD  - Donlinks School of Economics and Management, University of Science and Technology 
      Beijing, Beijing 100083, China.
FAU - Dai, Shufen
AU  - Dai S
AD  - Donlinks School of Economics and Management, University of Science and Technology 
      Beijing, Beijing 100083, China.
LA  - eng
PT  - Journal Article
PT  - Research Support, Non-U.S. Gov't
DEP - 20191222
PL  - Switzerland
TA  - Int J Environ Res Public Health
JT  - International journal of environmental research and public health
JID - 101238455
RN  - 7440-44-0 (Carbon)
SB  - IM
MH  - *Carbon
MH  - China
MH  - Commerce
MH  - Costs and Cost Analysis
MH  - *Decision Making
MH  - Electrical Equipment and Supplies
PMC - PMC6982311
OTO - NOTNLM
OT  - carbon emission trading scheme
OT  - integer programming
OT  - multiple-criteria decision-making
OT  - order allocation
OT  - supplier selection
COIS- The authors declare no conflicts of interest.
EDAT- 2019/12/28 06:00
MHDA- 2020/05/06 06:00
PMCR- 2020/01/01
CRDT- 2019/12/28 06:00
PHST- 2019/11/18 00:00 [received]
PHST- 2019/12/15 00:00 [revised]
PHST- 2019/12/17 00:00 [accepted]
PHST- 2019/12/28 06:00 [entrez]
PHST- 2019/12/28 06:00 [pubmed]
PHST- 2020/05/06 06:00 [medline]
PHST- 2020/01/01 00:00 [pmc-release]
AID - ijerph17010111 [pii]
AID - ijerph-17-00111 [pii]
AID - 10.3390/ijerph17010111 [doi]
PST - epublish
SO  - Int J Environ Res Public Health. 2019 Dec 22;17(1):111. doi: 
      10.3390/ijerph17010111.