nep-net New Economics Papers
on Network Economics
Issue of 2012‒05‒22
seven papers chosen by
Yi-Nung Yang
Chung Yuan Christian University

  1. A network analysis of cities hosting ICT R&D By Nepelski, Daniel; De Prato, Giuditta
  2. Global technological collaboration network. Network analysis of international co-inventions By De Prato, Giuditta; Nepelski, Daniel
  3. Prescriptions for network strategy: Does evidence of network effects in cross-section support them? By Baum, Joel A.C.; Cowan, Robin; Jonard, Nicolas
  4. Research Network Position and Innovative Performance: Evidence from the Pharmaceutical Industry By Maureen McKelvey; Bastian Rake
  5. Call Me if You Can – An Experimental Investigation of Information Sharing in Knowledge Networks By Christoph Helbach; Klemens Keldenich; Michael Rothgang; Guanzhong Yang
  6. Sharing a polluted river network By Dong, Baomin; Ni, Debing; Wang, Yuntong
  7. Strategic Sharing of a Costly Network By Hernández, Penélope; Peris, Josep E.; Silva-Reus, José A.

  1. By: Nepelski, Daniel; De Prato, Giuditta
    Abstract: We apply network analysis to study the ICT R&D locations at the city level. We use a dataset on the location and R&D activity of over 3000 R&D centres belonging to 175 MNEs, located in over 1300 cities around the world. The results show that most of the cities have few R&D connections and are grouped into "cliques", linked through network hubs. Hence, not only is the R&D activity concentrated in space, but also the nexus of connections between locations is limited. Asian and Japanese cities are favoured as a source of R&D services, as compared to European or US cities.
    Keywords: Networks; innovation and R&D; globalization; R&D complexity; network
    JEL: M2 O32 M10
    Date: 2012–04–01
  2. By: De Prato, Giuditta; Nepelski, Daniel
    Abstract: Global innovation networks are emerging as a result of the international division of innovation processes through, among others, international technological collaborations. At the aggregate level, the creation of technological collaboration between countries can be considered as mutually beneficial (or detrimental) and their random distribution is unlikely. Consequently, the dynamics and evolution of the technological collaborations can be expected to fulfil the criteria of a complex network. To study the structure and evolution of the global technological collaboration network, we use patent-based data of international co-inventions and apply the network analysis. In addition, extending the gravity model of international technological collaboration by measures controlling for countries position in the network, we show that that a country's position in the network has very strong impact on the intensity of collaboration with other members of the network.
    Keywords: globalisation of technology; technological collaboration; co-invention; network analysis; patent
    JEL: O30 F23 O57 D8 O14
    Date: 2012–05–15
  3. By: Baum, Joel A.C. (University of Toronto); Cowan, Robin (UNU-MERIT/MGSoG, Maastricht University, and BETA, Universite de Strassbourg); Jonard, Nicolas (University of Luxembourg)
    Abstract: Although intuitively appealing (and common), drawing network strategy implications from empirical evidence of network performance effects in pooled cross-section is not necessarily warranted. This is because network positions can influence both the mean and variance of firm performance. Strategic prescriptions are warranted if empirically observed network effects reflect increases in mean firm performance. If network effects reflect increases in firm performance variance, however, such prescriptions are warranted only if the increase in the odds of achieving high performance is sufficient to compensate for the concomitant increase in the odds of realizing poor performance. Our simulation study, designed to examine network performance effects in both pooled cross-section and within-firm over time across a wide range of conditions, counsels caution in drawing implications for network strategies. We discuss the implications of our findings for research on network effects, and more broadly for drawing strategic inferences from studies of firm performance in pooled cross-section.
    Keywords: network formation, strategic alliances, innovation, network strategy, interfirm networks
    JEL: L14 L20 D85 O30
    Date: 2012
  4. By: Maureen McKelvey (University of Gothenburg, Institute for Innovation and Entrepreneurship, School of Business, Economics and Law); Bastian Rake (Friedrich Schiller University Jena, Graduate College "The Economics of Innovative Change")
    Abstract: This paper explores how and why collaboration with different types of partners and the position within a research network can affect firms' innovative performance in terms of product innovations. A detailed empirical analysis is carried out in the biotechnology and pharmaceutical industry. This industry is characterized by a rapidly developing, complex, and dispersed knowledge base, where one would expect positive benefits from collaboration and the position within a network for innovative output. The paper uses a unique dataset in pharmaceutical cancer research based on scientific co-publications and new drug approvals. We apply social network analysis and count data regressions. We observe that collaboration with a diverse set of partners from academia and the network position in terms of eigenvector centrality is positively related to product innovation. However, we do not find a general positive association between collaboration, particularly with biotechnology companies, and product innovation or between central network positions and product innovation. Therefore, these results require a re-assessment of the role of scientific collaboration and biotechnology companies in the development of the pharmaceutical industry.
    Keywords: Research Networks, Research Collaboration, Innovative Performance, Pharmaceuticals
    JEL: L25 O31
    Date: 2012–05–11
  5. By: Christoph Helbach; Klemens Keldenich; Michael Rothgang; Guanzhong Yang
    Abstract: In the public promotion of R&D cluster and network formation, the following situation typically arises: An initial network structure has developed over a long time span and policy measures affect the structure of links between the actors. This new network structure influences the effectiveness of the information flow in a way that is not clear from the beginning. As analyzing the effects of a change in the network structure is difficult in the field, this paper uses a laboratory experiment to analyze how information is distributed in four different network structures. Networks are modeled as five-actor groups. Every individual represents a node and possesses some private information. The experimental results suggest that the different network structures do indeed influence the way information is exchanged. Both too many possible links (causing a coordination problem) and too few possible links (introducing bottlenecks) are harmful. The participants in all network structures learn over time and achieve a faster exchange of information in the later rounds. These results suggest that when influencing communication structures, one has to be careful to balance the positive and negative effects of adding more communication possibilities.
    Keywords: Network; communication; laboratory experiment; information flow
    JEL: C93 D70 D81
    Date: 2012–04
  6. By: Dong, Baomin; Ni, Debing; Wang, Yuntong
    Abstract: A polluted river network is populated with agents (e.g., firms, villages, municipalities, or countries) located upstream and downstream. This river network must be cleaned, the costs of which must be shared among the agents. We model this problem as a cost sharing problem on a tree network. Based on the two theories in international disputes, namely the Absolute Territorial Sovereignty (ATS) and the Unlimitted Territorial Integrity (UTI), we propose three different cost sharing methods for the problem. They are the Local Responsibility Sharing (LRS), the Upstream Equal Sharing (UES), and the Downstream Equal Sharing (DES), respectively. The LRS and the UES generalize Ni and Wang ("Sharing a polluted river", Games Econ. Behav., 60 (2007), 176-186) but the DES is new. The DES is based on a new interpretation of the UTI. We provide axiomatic characterizations for the three methods. We also show that they coincide with the Shapley values of the three different games that can be defined for the problem. Moreover, we show that they are in the cores of the three games, respectively. Our methods can shed light on pollution abatement of a river network with multiple sovereignties.
    Keywords: River network; Water pollution; Cost sharing; the Shapley value
    JEL: D62 C71 D61
    Date: 2012–04–01
  7. By: Hernández, Penélope (Departamento de Análisis Económico and ERI-CES. University of Valencia .); Peris, Josep E. (Universitat d'Alacant. Departament de Mètodes Quantitatius i Teoría Econòmica); Silva-Reus, José A. (Universitat d'Alacant. Departament de Mètodes Quantitatius i Teoría Econòmica and Instituto Universitario Desarrollo Social y Paz (IUDESP))
    Abstract: We s tudy minimum cost spanning tree problems for a given set of users connected to a source. We propose a rule of sharing such that each user may pay her cost for such a tree plus an additional amount to the others users . A reduction of her cost appears as a compensation from the other users. Our first result states the existence of a sharing such that no agent is willing to choose a different tree from the minimum cost tree (mcst) offered by Prim’s algorithm. Therefore, the mcst emerges as both a social and individual optimal solu tion. Given a sharing system, we implement the above solution as a subgame perfect equilibrium of a sequential game where players decide sequentially with whom to connect. Moreover , the proposed solution is at the core of the monotone cooperative game associated with a minimal cost spanning tree problem.
    Keywords: Minimum cost spanning tree; cost allocation; subgame perfect equilibrium
    JEL: C71 D63 D70
    Date: 2012–05–09

This nep-net issue is ©2012 by Yi-Nung Yang. It is provided as is without any express or implied warranty. It may be freely redistributed in whole or in part for any purpose. If distributed in part, please include this notice.
General information on the NEP project can be found at For comments please write to the director of NEP, Marco Novarese at <>. Put “NEP” in the subject, otherwise your mail may be rejected.
NEP’s infrastructure is sponsored by the School of Economics and Finance of Massey University in New Zealand.