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Statistical properties of the international seed trade networks for rice and maize.

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Title: Statistical properties of the international seed trade networks for rice and maize.
Authors: Liu, Hao-Ran1 (AUTHOR) hrliu@mail.ecust.edu.cn, Sun, Li-Jie2 (AUTHOR) lijiesun@ecust.edu.cn, Zhou, Wei-Xing3 (AUTHOR) wxzhou@ecust.edu.cn
Source: International Journal of Modern Physics C: Computational Physics & Physical Computation. May2023, Vol. 34 Issue 5, p1-23. 23p.
Subjects: Seed industry, International trade, Rice industry, Corn, Exporters
Abstract: International seed trade networks (iSTNs) are complex networks formed by the trade of seeds between economies. We investigate the statistical properties of the international trade networks for maize seeds and rice seeds from the viewpoint of temporal directed and weighted networks. We find that most properties, including node and edge numbers, average in- and out-degrees, total and average trade values, network density and clustering coefficient, showed an increasing trend, which indicates that the increasing globalization of seed trade has led to more and more complete and dense trade networks. We also find that links with larger trade values have greater stability. In addition, we observe positive correlations between in-degree and out-degree, link reciprocity and in- and out-degrees, link reciprocity and in- and out-strengths and clustering coefficient and in- and out-degrees. In contrast, there are negative correlations between clustering coefficient and in- and out-strengths. Furthermore, we find that both networks are assortatively mixed in most years, which indicates that large exporters and importers are more likely to trade with other large exporters and importers. The structural properties of the two iSTNs of maize and rice share many qualitative similarities, but exhibit quantitative differences. [ABSTRACT FROM AUTHOR]
Copyright of International Journal of Modern Physics C: Computational Physics & Physical Computation is the property of World Scientific Publishing Company and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
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Header DbId: egs
DbLabel: Engineering Source
An: 162326052
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
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Items – Name: Title
  Label: Title
  Group: Ti
  Data: Statistical properties of the international seed trade networks for rice and maize.
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Liu%2C+Hao-Ran%22">Liu, Hao-Ran</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> hrliu@mail.ecust.edu.cn</i><br /><searchLink fieldCode="AR" term="%22Sun%2C+Li-Jie%22">Sun, Li-Jie</searchLink><relatesTo>2</relatesTo> (AUTHOR)<i> lijiesun@ecust.edu.cn</i><br /><searchLink fieldCode="AR" term="%22Zhou%2C+Wei-Xing%22">Zhou, Wei-Xing</searchLink><relatesTo>3</relatesTo> (AUTHOR)<i> wxzhou@ecust.edu.cn</i>
– Name: TitleSource
  Label: Source
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  Data: <searchLink fieldCode="JN" term="%22International+Journal+of+Modern+Physics+C%3A+Computational+Physics+%26+Physical+Computation%22">International Journal of Modern Physics C: Computational Physics & Physical Computation</searchLink>. May2023, Vol. 34 Issue 5, p1-23. 23p.
– Name: Subject
  Label: Subjects
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Seed+industry%22">Seed industry</searchLink><br /><searchLink fieldCode="DE" term="%22International+trade%22">International trade</searchLink><br /><searchLink fieldCode="DE" term="%22Rice+industry%22">Rice industry</searchLink><br /><searchLink fieldCode="DE" term="%22Corn%22">Corn</searchLink><br /><searchLink fieldCode="DE" term="%22Exporters%22">Exporters</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: International seed trade networks (iSTNs) are complex networks formed by the trade of seeds between economies. We investigate the statistical properties of the international trade networks for maize seeds and rice seeds from the viewpoint of temporal directed and weighted networks. We find that most properties, including node and edge numbers, average in- and out-degrees, total and average trade values, network density and clustering coefficient, showed an increasing trend, which indicates that the increasing globalization of seed trade has led to more and more complete and dense trade networks. We also find that links with larger trade values have greater stability. In addition, we observe positive correlations between in-degree and out-degree, link reciprocity and in- and out-degrees, link reciprocity and in- and out-strengths and clustering coefficient and in- and out-degrees. In contrast, there are negative correlations between clustering coefficient and in- and out-strengths. Furthermore, we find that both networks are assortatively mixed in most years, which indicates that large exporters and importers are more likely to trade with other large exporters and importers. The structural properties of the two iSTNs of maize and rice share many qualitative similarities, but exhibit quantitative differences. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of International Journal of Modern Physics C: Computational Physics & Physical Computation is the property of World Scientific Publishing Company and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1142/S0129183123500687
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 23
        StartPage: 1
    Subjects:
      – SubjectFull: Seed industry
        Type: general
      – SubjectFull: International trade
        Type: general
      – SubjectFull: Rice industry
        Type: general
      – SubjectFull: Corn
        Type: general
      – SubjectFull: Exporters
        Type: general
    Titles:
      – TitleFull: Statistical properties of the international seed trade networks for rice and maize.
        Type: main
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      – PersonEntity:
          Name:
            NameFull: Liu, Hao-Ran
      – PersonEntity:
          Name:
            NameFull: Sun, Li-Jie
      – PersonEntity:
          Name:
            NameFull: Zhou, Wei-Xing
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 01
              M: 05
              Text: May2023
              Type: published
              Y: 2023
          Identifiers:
            – Type: issn-print
              Value: 01291831
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            – Type: volume
              Value: 34
            – Type: issue
              Value: 5
          Titles:
            – TitleFull: International Journal of Modern Physics C: Computational Physics & Physical Computation
              Type: main
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