Managing crash risks through supply chain transparency:evidence from China

Using data on Chinese non-financial listed firms covering 2009 to 2022,we explore the effect of supply chain transparency on stock price crash risk.Two proxies for supply chain transparency are constructed using the number of supply chain partners’names and the proportion of their transactions disclosed in annual reports.The results reveal that enhancing supply chain transparency can decrease crash risk,specifically by mitigating tax avoidance and earnings management.Moreover,the analysis suggests that this risk-reduction effect is more prominent in companies where managers are more incentivized to hide negative information and investors possess superior abilities to acquire information.Interestingly,supplier transparency is more influential in mitigating crash risk than customer transparency.These findings emphasize the significance of supply chain transparency in managing financial risk.

Combining permissioned blockchain and Bayesian best-worst method for transparent supplier selection in supply chain management

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.