Supplier selection is an important business activity in order to realize the purchasing function in supply chain management.The supplier selection process includes four stages,i.e.,bidding inviting,bidding,group decis...Supplier selection is an important business activity in order to realize the purchasing function in supply chain management.The supplier selection process includes four stages,i.e.,bidding inviting,bidding,group decision-making,and results disclosure,involving the participation of manufacturing service demanders(MSDs),manufacturing service suppliers(MSSs),and decisionmakers.Nowadays,all the participants have raised concerns about the increased transparency in supplier selection.Therefore,this study proposes a transparent supplier selection method by considering the engagement of suppliers.In this method,the Bayesian best-worst method(Bayesian BWM)is used to aggregate decision-makers'preferences into the overall optimal weights of the alternative MSSs,and the MSS with the largest weight is considered the suitable MSS for MSDs.Furthermore,blockchain is introduced to record the decision-making process information about supplier selection through a customized smart contract,where MSSs act as supervisors to supervise the decision-making process through the distributed consensus mechanism rather than directly participate in the decision-making process.Finally,a case study of supplier selection in purchasing vibration acceleration sensors is presented.The result shows that the proposed method can support MSDs in selecting suitable MSS from alternative MSSs by aggregating decision-makers'preferences,and blockchain can provide credible information about the supplier selection process for MSSs,MSDs,and decision-makers.In this way,the transparency of supplier selection is enhanced.展开更多
Waste management strategies employed by emerging economies worldwide are often insufficient to address the new-age sustainability challenges.Especially in chemicalintensive manufacturing industries,increasing levels o...Waste management strategies employed by emerging economies worldwide are often insufficient to address the new-age sustainability challenges.Especially in chemicalintensive manufacturing industries,increasing levels of waste production are a significant environmental threat.Adopting a circular supply chain(CSC)can be a viable solution to this problem since it incorporates the components of the circular economy into an organization's supply chain,bringing an engaging viewpoint to the supply chain sustainability field.Nevertheless,the adoption of CSC in chemical-intensive manufacturing industries faces various intricate challenges in emerging economies.This study,therefore,aims to explore and evaluate the challenges associated with adopting CSC in the chemical-intensive manufacturing industries,using the empirical case of an emerging economy,Bangladesh.After a thorough literature review and expert validation,26 challenges were analyzed using a probabilistic group decision-making approach,i.e.,the Bayesian best-worst method(BWM).The result showed that the most significant challenge is the chemical composition-related complexity(global weight=0.0801),followed by strong emphasis on the take-make-dispose policy(0.0705),and insufficient investment and financial resources(0.0697).On the contrary,the least important challenge is the resistance toward the transition from conventional supply chain to CSC(0.0078).The outcomes of this study are expected to enrich existing knowledge and comprehension of the challenges linked to implementing CSC practices in Bangladesh and contribute to achieving Sustainable Development Goals(SDGs),such as SDG 3(good health and wellbeing),SDG 11(sustainable cities and communities),SDG 12(responsible consumption and production),SDG 13(climate action),and so on.展开更多
基金supported by the National Natural Science Foundation of China(Grant Nos.52375485,52275478)the Young Elite Scientists Sponsorship Program by the China Association for Science and Technology(Grant No.2021QNRC001)。
文摘Supplier selection is an important business activity in order to realize the purchasing function in supply chain management.The supplier selection process includes four stages,i.e.,bidding inviting,bidding,group decision-making,and results disclosure,involving the participation of manufacturing service demanders(MSDs),manufacturing service suppliers(MSSs),and decisionmakers.Nowadays,all the participants have raised concerns about the increased transparency in supplier selection.Therefore,this study proposes a transparent supplier selection method by considering the engagement of suppliers.In this method,the Bayesian best-worst method(Bayesian BWM)is used to aggregate decision-makers'preferences into the overall optimal weights of the alternative MSSs,and the MSS with the largest weight is considered the suitable MSS for MSDs.Furthermore,blockchain is introduced to record the decision-making process information about supplier selection through a customized smart contract,where MSSs act as supervisors to supervise the decision-making process through the distributed consensus mechanism rather than directly participate in the decision-making process.Finally,a case study of supplier selection in purchasing vibration acceleration sensors is presented.The result shows that the proposed method can support MSDs in selecting suitable MSS from alternative MSSs by aggregating decision-makers'preferences,and blockchain can provide credible information about the supplier selection process for MSSs,MSDs,and decision-makers.In this way,the transparency of supplier selection is enhanced.
文摘Waste management strategies employed by emerging economies worldwide are often insufficient to address the new-age sustainability challenges.Especially in chemicalintensive manufacturing industries,increasing levels of waste production are a significant environmental threat.Adopting a circular supply chain(CSC)can be a viable solution to this problem since it incorporates the components of the circular economy into an organization's supply chain,bringing an engaging viewpoint to the supply chain sustainability field.Nevertheless,the adoption of CSC in chemical-intensive manufacturing industries faces various intricate challenges in emerging economies.This study,therefore,aims to explore and evaluate the challenges associated with adopting CSC in the chemical-intensive manufacturing industries,using the empirical case of an emerging economy,Bangladesh.After a thorough literature review and expert validation,26 challenges were analyzed using a probabilistic group decision-making approach,i.e.,the Bayesian best-worst method(BWM).The result showed that the most significant challenge is the chemical composition-related complexity(global weight=0.0801),followed by strong emphasis on the take-make-dispose policy(0.0705),and insufficient investment and financial resources(0.0697).On the contrary,the least important challenge is the resistance toward the transition from conventional supply chain to CSC(0.0078).The outcomes of this study are expected to enrich existing knowledge and comprehension of the challenges linked to implementing CSC practices in Bangladesh and contribute to achieving Sustainable Development Goals(SDGs),such as SDG 3(good health and wellbeing),SDG 11(sustainable cities and communities),SDG 12(responsible consumption and production),SDG 13(climate action),and so on.
