Understanding the dynamics of industrial networks using Kauffman Boolean networks

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https://doi.org/10.1142/S0219525908001544
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Understanding the dynamics of industrial networks using Kauffman Boolean networks. / Easton, G ; Brooks, R J; Georgieva, C et al.
In: Advances in Complex Systems, Vol. 11, No. 1, 2008, p. 139-164.

Research output: Contribution to Journal/Magazine › Journal article › peer-review

Harvard

Easton, G , Brooks, RJ, Georgieva, C & Wilkinson, I 2008, 'Understanding the dynamics of industrial networks using Kauffman Boolean networks', Advances in Complex Systems, vol. 11, no. 1, pp. 139-164. https://doi.org/10.1142/S0219525908001544

APA

Easton, G., Brooks, R. J., Georgieva, C., & Wilkinson, I. (2008). Understanding the dynamics of industrial networks using Kauffman Boolean networks. Advances in Complex Systems, 11(1), 139-164. https://doi.org/10.1142/S0219525908001544

Vancouver

Easton G , Brooks RJ, Georgieva C, Wilkinson I. Understanding the dynamics of industrial networks using Kauffman Boolean networks. Advances in Complex Systems. 2008;11(1):139-164. doi: 10.1142/S0219525908001544

Author

Easton, G ; Brooks, R J ; Georgieva, C et al. / Understanding the dynamics of industrial networks using Kauffman Boolean networks. In: Advances in Complex Systems. 2008 ; Vol. 11, No. 1. pp. 139-164.

Bibtex

@article{96056290a9ad4f3081e7b2274f27849e,

title = "Understanding the dynamics of industrial networks using Kauffman Boolean networks",

abstract = "Industrial networks offer a prime example of the tension between system stability and change. Change is necessary as a response to environmental variation, whereas stability provides the underpinning for long-term investment and the exploitation of efficiencies. Whilst one of the key themes in industrial network research has been the dynamics of change, relatively little work, empirical or theoretical, has been devoted to the dynamics of stability. This paper presents a new approach to this problem by using Boolean networks, which were originally devised by Stuart Kauffman as an abstract model of genetic networks. The elements in the model are connected by rules of Boolean logic, and a novel aspect of this research is that the elements represent the industrial network exchanges rather than stock entities (the organizations). The model structure consists of interactions between the exchanges, and the results represent the pattern of exchange episodes. A total of 42 networks were modeled and the dynamics analyzed in detail, and five of these cases are presented in this paper. The models produced realistic behavior and provided some insights into the reasons for stability in industrial networks.",

author = "G Easton and Brooks, {R J} and C Georgieva and I Wilkinson",

year = "2008",

doi = "10.1142/S0219525908001544",

language = "English",

volume = "11",

pages = "139--164",

journal = "Advances in Complex Systems",

issn = "0219-5259",

publisher = "World Scientific Publishing Co. Pte Ltd",

number = "1",

}

RIS

TY - JOUR

T1 - Understanding the dynamics of industrial networks using Kauffman Boolean networks

AU - Easton, G

AU - Brooks, R J

AU - Georgieva, C

AU - Wilkinson, I

PY - 2008

Y1 - 2008

N2 - Industrial networks offer a prime example of the tension between system stability and change. Change is necessary as a response to environmental variation, whereas stability provides the underpinning for long-term investment and the exploitation of efficiencies. Whilst one of the key themes in industrial network research has been the dynamics of change, relatively little work, empirical or theoretical, has been devoted to the dynamics of stability. This paper presents a new approach to this problem by using Boolean networks, which were originally devised by Stuart Kauffman as an abstract model of genetic networks. The elements in the model are connected by rules of Boolean logic, and a novel aspect of this research is that the elements represent the industrial network exchanges rather than stock entities (the organizations). The model structure consists of interactions between the exchanges, and the results represent the pattern of exchange episodes. A total of 42 networks were modeled and the dynamics analyzed in detail, and five of these cases are presented in this paper. The models produced realistic behavior and provided some insights into the reasons for stability in industrial networks.

AB - Industrial networks offer a prime example of the tension between system stability and change. Change is necessary as a response to environmental variation, whereas stability provides the underpinning for long-term investment and the exploitation of efficiencies. Whilst one of the key themes in industrial network research has been the dynamics of change, relatively little work, empirical or theoretical, has been devoted to the dynamics of stability. This paper presents a new approach to this problem by using Boolean networks, which were originally devised by Stuart Kauffman as an abstract model of genetic networks. The elements in the model are connected by rules of Boolean logic, and a novel aspect of this research is that the elements represent the industrial network exchanges rather than stock entities (the organizations). The model structure consists of interactions between the exchanges, and the results represent the pattern of exchange episodes. A total of 42 networks were modeled and the dynamics analyzed in detail, and five of these cases are presented in this paper. The models produced realistic behavior and provided some insights into the reasons for stability in industrial networks.

U2 - 10.1142/S0219525908001544

DO - 10.1142/S0219525908001544

M3 - Journal article

VL - 11

SP - 139

EP - 164

JO - Advances in Complex Systems

JF - Advances in Complex Systems

SN - 0219-5259

IS - 1

ER -

Research

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