nep-net New Economics Papers
on Network Economics
Issue of 2008‒08‒14
four papers chosen by
Yi-Nung Yang
Chung Yuan Christian University

  1. The World-Trade Web: Topological Properties, Dynamics, and Evolution By Giorgio Fagiolo; Javier Reyes; Stefano Schiavo
  2. An agent-based retail location model on a supply chain network By Arthur Huang; David Levinson
  3. A Review of Research on Planned and Unplanned Disruptions to Transportation Networks By Shanjiang Zhu; David Levinson
  4. Multi Agent Systems in Logistics: A Literature and State-of-the-art Review By Lang, N.A.; Moonen, J.M.; Srour, F.J.; Zuidwijk, R.A.

  1. By: Giorgio Fagiolo; Javier Reyes; Stefano Schiavo
    Abstract: This paper studies the statistical properties of the web of import-export relationships among world countries using a weighted-network approach. We analyze how the distributions of the most important network statistics measuring connectivity, assortativity, clustering and centrality have co-evolved over time. We show that all node-statistic distributions and their correlation structure have remained surprisingly stable in the last 20 years -- and are likely to do so in the future. Conversely, the distribution of (positive) link weights is slowly moving from a log-normal density towards a power law. We also characterize the autoregressive properties of network-statistics dynamics. We find that network-statistics growth rates are well-proxied by fat-tailed densities like the Laplace or the asymmetric exponential-power. Finally, we find that all our results are reasonably robust to a few alternative, economically-meaningful, weighting schemes.
    Keywords: Weighted Networks; World Trade Web; Distribution Dynamics; Power Laws; Econophysics
    Date: 2008–07–28
  2. By: Arthur Huang; David Levinson (Nexus (Networks, Economics, and Urban Systems) Research Group, Department of Civil Engineering, University of Minnesota)
    Abstract: Clusters of business locations, which considerably impact daily activities, have been promi- nent phenomena. Yet the question of how and why Þrms cluster in certain areas has not been sufÞciently studied. This paper investigates the emergence of clusters of business locations on a supply chain network comprised of suppliers, retailers, and, consumers. Krugman (1996) argued that urban concentration involved a tension between the ÒcentripetalÓ and the Òcen- trifugalÓ forces. Based on that notion, this research proposes an agent-based model of retail- ersÕ location choice in a market of homogeneous products. In this game, retailers endeavor to maximize their proÞts by changing locations. RetailersÕ distribution patterns are measured by entropy and cluster density. Simulation results reveal that as more retailers engage in the game, clusters autonomously emerge and the entropy of clusters increases. Once retailers exceed a certain number, average density of clusters begins to decline; all discrete clusters gradually merge to a large cluster, spreading out uniformly. This research thus Þnds that the centripetal force attracts retailers to supplier locations; with even more retailers entering the market, the centrifugal force disperses them. The sensitivity results on model parameters and consumersÕ demand elasticity are also discussed.
    Keywords: clustering, supply chain network, location choice, distribution pattern
    JEL: R41 R48 D63
    Date: 2008
  3. By: Shanjiang Zhu; David Levinson (Nexus (Networks, Economics, and Urban Systems) Research Group, Department of Civil Engineering, University of Minnesota)
    Abstract: Travel decisions may be very stable in an environment with which they are familiar. Major network disruptions such as the I-35W bridge collapse disrupt habitual behavior. Such "natural" experiments provide unique opportunities for behavioral studies, but the time window for such studies is limited. A well-developed methodology is crucial for both data collection and analysis, and thus the soundness of behavioral models, especially in such a limited time window. Therefore, this paper reviews both theoretical and empirical studies on traffic and behavioral impacts of network disruptions. Findings from this paper others prospective ideas about capturing the impacts of network disruption.
    Keywords: Network disruption; Travel survey; Travel behavior
    JEL: R41 R48 D63
    Date: 2008
  4. By: Lang, N.A.; Moonen, J.M.; Srour, F.J.; Zuidwijk, R.A. (Erasmus Research Institute of Management (ERIM), RSM Erasmus University)
    Abstract: Based on a literature survey, we aim to answer our main question: “How should we plan and execute logistics in supply chains that aim to meet today’s requirements, and how can we support such planning and execution using IT?†Today’s requirements in supply chains include inter-organizational collaboration and more responsive and tailored supply to meet specific demand. Enterprise systems fall short in meeting these requirements The focus of planning and execution systems should move towards an inter-enterprise and event-driven mode. Inter-organizational systems may support planning going from supporting information exchange and henceforth enable synchronized planning within the organizations towards the capability to do network planning based on available information throughout the network. We provide a framework for planning systems, constituting a rich landscape of possible configurations, where the centralized and fully decentralized approaches are two extremes. We define and discuss agent based systems and in particular multi agent systems (MAS). We emphasize the issue of the role of MAS coordination architectures, and then explain that transportation is, next to production, an important domain in which MAS can and actually are applied. However, implementation is not widespread and some implementation issues are explored. In this manner, we conclude that planning problems in transportation have characteristics that comply with the specific capabilities of agent systems. In particular, these systems are capable to deal with inter-organizational and event-driven planning settings, hence meeting today’s requirements in supply chain planning and execution.
    Keywords: supply chain;multi agent systems;MAS
    Date: 2008–07–31

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