Amid sluggish global growth and rising uncertainties,supply chain stability is vital for sustaining economic production.Although studies examine the impacts of supply chain relationships on firm performance,their efle...Amid sluggish global growth and rising uncertainties,supply chain stability is vital for sustaining economic production.Although studies examine the impacts of supply chain relationships on firm performance,their eflect on total factor productivity(TFP)remains unexplored.Using data from 1559 A-share listed companies in China(2008-2022),this study examines customer stabil-ity's impact on TFP and finds that customer stability enhances TFP by reduc-ing Type Ⅰ agency costs and improving fir reputation.It also generates significant spillover effects,increasing customer TFP through supply chain finance.This effect is more pronounced for firms in high-tech industries and regions with higher marketization and social trust.These findings offer new insights into enhancing firms’efficiency through effective supply chain relation-ship management.展开更多
We consider queueing networks （QN＇s） with feedback loops roamed by ＂intelligent＂ agents, able to select their routing on the basis of their measured waiting times at the QN nodes. This is an idealized model to di...We consider queueing networks （QN＇s） with feedback loops roamed by ＂intelligent＂ agents, able to select their routing on the basis of their measured waiting times at the QN nodes. This is an idealized model to discuss the dynamics of customers who stay loyal to a service supplier, provided their service time remains below a critical threshold. For these QN＇s, we show that the traffic flows may exhibit collective patterns typically encountered in multi-agent systems. In simple network topologies, the emergent cooperative behaviors manifest themselves via stable macroscopic temporal oscillations, synchronization of the queue contents and stabilization by noise phenomena. For a wide range of control parameters, the underlying presence of the law of large numbers enables us to use deterministic evolution laws to analytically characterize the cooperative evolution of our multi-agent systems. In particular, we study the case where the servers are sporadically subject, to failures altering their ordinary behavior.展开更多
基金supported by the Liaoning Province Social Science Fund(Grant No.L23BGL029).
文摘Amid sluggish global growth and rising uncertainties,supply chain stability is vital for sustaining economic production.Although studies examine the impacts of supply chain relationships on firm performance,their eflect on total factor productivity(TFP)remains unexplored.Using data from 1559 A-share listed companies in China(2008-2022),this study examines customer stabil-ity's impact on TFP and finds that customer stability enhances TFP by reduc-ing Type Ⅰ agency costs and improving fir reputation.It also generates significant spillover effects,increasing customer TFP through supply chain finance.This effect is more pronounced for firms in high-tech industries and regions with higher marketization and social trust.These findings offer new insights into enhancing firms’efficiency through effective supply chain relation-ship management.
基金the Fonds National Suisse de la Recherche Scientifique under Grant No.200021-109191/1the Portuguese Fundaao para a Cinca e a Tecnologica(FCT Bolsa FEDER/POCTI-SFA-1-219)The original version was presented on ICSSSM'06.
文摘We consider queueing networks （QN＇s） with feedback loops roamed by ＂intelligent＂ agents, able to select their routing on the basis of their measured waiting times at the QN nodes. This is an idealized model to discuss the dynamics of customers who stay loyal to a service supplier, provided their service time remains below a critical threshold. For these QN＇s, we show that the traffic flows may exhibit collective patterns typically encountered in multi-agent systems. In simple network topologies, the emergent cooperative behaviors manifest themselves via stable macroscopic temporal oscillations, synchronization of the queue contents and stabilization by noise phenomena. For a wide range of control parameters, the underlying presence of the law of large numbers enables us to use deterministic evolution laws to analytically characterize the cooperative evolution of our multi-agent systems. In particular, we study the case where the servers are sporadically subject, to failures altering their ordinary behavior.
