This study delves into the formation dynamics of alliances within a closed-loop supply chain(CLSC)that encom-passes a manufacturer,a retailer,and an e-commerce platform.It leverages Stackelberg game for this explorati...This study delves into the formation dynamics of alliances within a closed-loop supply chain(CLSC)that encom-passes a manufacturer,a retailer,and an e-commerce platform.It leverages Stackelberg game for this exploration,contrasting the equilibrium outcomes of a non-alliance model with those of three differentiated alliance models.The non-alliance model acts as a crucial benchmark,enabling the evaluation of the motivations for various supply chain entities to engage in alliance formations.Our analysis is centered on identifying the most effective alliance strategies and establishing a coordination within these partnerships.We thoroughly investigate the consequences of diverse alliance behaviors,bidirectional free-riding and cost-sharing,and the resultant effects on the optimal decision-making among supply chain actors.The findings underscore several pivotal insights:(1)The behavior of alliances within the supply chain exerts variable impacts on the optimal pricing and demand of its members.In comparison to the non-alliance(D)model,the manufacturer-retailer(MR)and manufacturer-e-commerce platform(ME)alliances significantly lower both offline and online resale prices for new and remanufactured goods.This adjustment leads to an enhanced demand for products via the MR alliance’s offline outlets and the ME alliance’s online platforms,thereby augmenting the profits for those within the alliance.Conversely,retailer-e-commerce platform(ER)alliance tends to increase the optimal retail price and demand across both online and offline channels.Under specific conditions,alliance behavior can also increase the profits of non-alliance members,and the profits derived through alliance channels also exceed those from non-alliance channels.(2)The prevalence of bidirectional free-riding behavior largely remains constant across different alliance configurations.Across these models,bidirectional free-riding typically elevates the equilibrium prices in offline channel while negatively affecting the equilibrium prices in other channel.(3)The effect of cost-sharing shows relative uniformity across the various alliance models.Across all configurations,cost-sharing tends to reduce the manufacturer’s profits.Nonetheless,alliances initiated by the manufacturer can counteract these negative impacts,providing a strategic pathway to bolster CLSC profitability.展开更多
In a peer-to-peer file-sharing system, a free-rider is a node which downloads files from its peers but does not share files to other nodes. Analyzing the free-riders’ impact on system throughputs is essential in exam...In a peer-to-peer file-sharing system, a free-rider is a node which downloads files from its peers but does not share files to other nodes. Analyzing the free-riders’ impact on system throughputs is essential in examining the performance of peer-to-peer file-sharing systems. We find that the free-riders’ impact largely depends on nodes behavior, including their online time and greed of downloading files. We extend an existing peer-to-peer system model and classify nodes according to their behavior. We focus on two peer-to-peer architectures: centralized indexing and distributed hash tables. We find that when the cooperators in a system are all greedy in downloading files, the system throughput has little room to increase while the cooperators throughput degrade badly with the increasing percent of greedy free-riders in the system. When all the cooperators are non-greedy with long average online time, the system throughput has much room to increase and the cooperators throughput degrade little with a high percent of greedy free-riders in the system. We also find that if a system can tolerate a high percent of greedy free-riders without suffering much throughput degradation, the system must contain some non-greedy cooperators that contribute great idle service capacity to the system.展开更多
The underlying premise of peer-to-peer(P2P)systems is the trading of digital resources among individual peers to facilitate file sharing,distributed computing,storage,collaborative applications and multimedia streamin...The underlying premise of peer-to-peer(P2P)systems is the trading of digital resources among individual peers to facilitate file sharing,distributed computing,storage,collaborative applications and multimedia streaming.So-called free-riders challenge the foundations of this system by consuming resources from other peers without offering any resources in return,hindering resource exchange among peers.Therefore,immense effort has been invested in discouraging free-riding and overcoming the ill effects of such unfair use of the system.However,previous efforts have all fallen short of effectively addressing free-riding behaviour in P2P networks.This paper proposes a novel approach based on utilising a credit incentive for P2P networks,wherein a grace period is introduced during which free-riders must reimburse resources.In contrast to previous approaches,the proposed system takes into consideration the upload rate of peers and a grace period.The system has been thoroughly tested in a simulated environment,and the results show that the proposed approach effectively mitigates free-riding behaviour.Compared to previous systems,the number of downloads from free-riders decreased while downloads by contributing peers increased.The results also show that under longer grace periods,the number of downloads by fast peers(those reimbursing the system within the grace period)was greater than the number of downloads by slow peers.展开更多
基金This work was supported by the Humanities and Social Science Fund of Ministry of Education of China(No.20YJA630009)Shandong Natural Science Foundation of China(No.ZR2022MG002).
文摘This study delves into the formation dynamics of alliances within a closed-loop supply chain(CLSC)that encom-passes a manufacturer,a retailer,and an e-commerce platform.It leverages Stackelberg game for this exploration,contrasting the equilibrium outcomes of a non-alliance model with those of three differentiated alliance models.The non-alliance model acts as a crucial benchmark,enabling the evaluation of the motivations for various supply chain entities to engage in alliance formations.Our analysis is centered on identifying the most effective alliance strategies and establishing a coordination within these partnerships.We thoroughly investigate the consequences of diverse alliance behaviors,bidirectional free-riding and cost-sharing,and the resultant effects on the optimal decision-making among supply chain actors.The findings underscore several pivotal insights:(1)The behavior of alliances within the supply chain exerts variable impacts on the optimal pricing and demand of its members.In comparison to the non-alliance(D)model,the manufacturer-retailer(MR)and manufacturer-e-commerce platform(ME)alliances significantly lower both offline and online resale prices for new and remanufactured goods.This adjustment leads to an enhanced demand for products via the MR alliance’s offline outlets and the ME alliance’s online platforms,thereby augmenting the profits for those within the alliance.Conversely,retailer-e-commerce platform(ER)alliance tends to increase the optimal retail price and demand across both online and offline channels.Under specific conditions,alliance behavior can also increase the profits of non-alliance members,and the profits derived through alliance channels also exceed those from non-alliance channels.(2)The prevalence of bidirectional free-riding behavior largely remains constant across different alliance configurations.Across these models,bidirectional free-riding typically elevates the equilibrium prices in offline channel while negatively affecting the equilibrium prices in other channel.(3)The effect of cost-sharing shows relative uniformity across the various alliance models.Across all configurations,cost-sharing tends to reduce the manufacturer’s profits.Nonetheless,alliances initiated by the manufacturer can counteract these negative impacts,providing a strategic pathway to bolster CLSC profitability.
基金the National High Technology Re-search and Development Program (863) of China(No. 2007AA01Z457)the Shanghai Science and Technology Development Funds (No. 07QA14033)
文摘In a peer-to-peer file-sharing system, a free-rider is a node which downloads files from its peers but does not share files to other nodes. Analyzing the free-riders’ impact on system throughputs is essential in examining the performance of peer-to-peer file-sharing systems. We find that the free-riders’ impact largely depends on nodes behavior, including their online time and greed of downloading files. We extend an existing peer-to-peer system model and classify nodes according to their behavior. We focus on two peer-to-peer architectures: centralized indexing and distributed hash tables. We find that when the cooperators in a system are all greedy in downloading files, the system throughput has little room to increase while the cooperators throughput degrade badly with the increasing percent of greedy free-riders in the system. When all the cooperators are non-greedy with long average online time, the system throughput has much room to increase and the cooperators throughput degrade little with a high percent of greedy free-riders in the system. We also find that if a system can tolerate a high percent of greedy free-riders without suffering much throughput degradation, the system must contain some non-greedy cooperators that contribute great idle service capacity to the system.
文摘The underlying premise of peer-to-peer(P2P)systems is the trading of digital resources among individual peers to facilitate file sharing,distributed computing,storage,collaborative applications and multimedia streaming.So-called free-riders challenge the foundations of this system by consuming resources from other peers without offering any resources in return,hindering resource exchange among peers.Therefore,immense effort has been invested in discouraging free-riding and overcoming the ill effects of such unfair use of the system.However,previous efforts have all fallen short of effectively addressing free-riding behaviour in P2P networks.This paper proposes a novel approach based on utilising a credit incentive for P2P networks,wherein a grace period is introduced during which free-riders must reimburse resources.In contrast to previous approaches,the proposed system takes into consideration the upload rate of peers and a grace period.The system has been thoroughly tested in a simulated environment,and the results show that the proposed approach effectively mitigates free-riding behaviour.Compared to previous systems,the number of downloads from free-riders decreased while downloads by contributing peers increased.The results also show that under longer grace periods,the number of downloads by fast peers(those reimbursing the system within the grace period)was greater than the number of downloads by slow peers.
