The Twofold Complexity of Economy Under the Domination of Network Processes and its Manifestation in the Theoretical Landscape and Reality

The Twofold Complexity of Economy Under the Domination of Network Processes and its Manifestation in the Theoretical Landscape and Reality

Alexey A. Baryshev (Big Data Science and Society Problems Laboratory, National Research Tomsk State University, Tomsk, Russia)
DOI: 10.4018/IJANTTI.2016100102
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Abstract

Complex networks methodology has permeated the spheres of knowledge that deal with heterogeneous networks, introduced by Actor-Network Theory. In the context, cognition of macro socio-economic processes that have determinants, different in ontological sense, does not seem to be so efficient. The author addresses the twofold complexity of these phenomena. The author identifies different types of macro socio-economic complexity as various combinations of ontological and intrinsic network heterogeneities. Extant networks theories are classified in accordance with a particular type of complexity, with which they deal, and thereby the real background of these theories is revealed. The concept of twofold complexity and its types is applied to the economic category of value. The near-term prospects for the creation of Networks Economics are hypothesized. Networks Economics is viewed on as a theory of preferential attachment value interacting with the non-network mode of value.
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1. Introduction

The paradigm shift engendered by advances of Network science perplexed a lot of areas of knowledge. Applied to economics and humanities, it has a great run for the description of interpersonal ties of economic agents (Barabasi, A. 2004), stock correlation networks, stock ownership networks, trading webs, banks’ credit networks (Caldarelli 2016). However, the basic economic issues that suggest comprehension of the wholeness of socio-economic reality are still out of network science domain.

The following two approaches to explanation of the situation are possible. Firstly, network theory does not have proper tools to deal with this matter now. Secondly, economics and humanities have some characteristics of their subjects that do not enable them to immediately employ network methodology. Probably, both the explanations are equally veracious since social reality is much more complex in relation to the natural reality because of the presence of axiological components within it. That is why network science has advance when valuables can be taken off from the table or addressed as “all other things being equal” without a serious loss of the sense of the processes or phenomena under consideration. With this in mind, the following questions are to be considered:

  • 1.

    What things constitute impediments to the development of network methodology in respect to macro socio-economic phenomena?

  • 2.

    What factors stipulate the multitude of network approaches and theories employed in human and economic sciences?

  • 3.

    How is the type of social ontology correlated with network the ontology presented in the complex network theory?

  • 4.

    How can the basic category of economic value be perceived with regard to the economy of networks and network science?

2. Formal Homogeneity Of Networks In The Period Of Early Network Theory And Ontological Heterogeneity Of The Social World

The theory of social networks began to emerge in the late 19th – early 20th centuries due to the interest of sociologists in the formation of groups of people. In the 30s, J. L. Moreno developed the first analytical tools for research and description of interpersonal relationship patterns in a small group (Moreno 1957, Moreno 1953). The term “social network” was first suggested by James Barnes in 1954. It was defined as “…not a corporate body, but rather a system of social relations through which many individuals carry on certain activities, which are only indirectly coordinated with one another” (Barnes 1954: 48-49). In the first half of the 20th century, anthropology, psychology and sociology of small groups focused on interactive processes in human communities, which were characterized as networking due to their adaptability, flexibility, alternativeness, and absence of the single center and clear boundaries. The relationist spirit of these studies totally correlated with the analytical tools that had been developed by mathematicians to describe social networks. The theory of random graphs or Poisson random networks (Dorogovtsev 2010) ensured description of networks that did not have obvious principles of construction. It was critical to regard networks as non-deterministic formations.

Those ways of thinking opposed to the traditional comprehension of society as a holistic body with stable ties between its different parts. As a result, the increased attention shifted from formal attributes of individuals to their relations in attempt to build a theory of society on the homogeneous base of humans` interactions. However, the interactionist principles of networking homogeneity proved ineffective to explain social macro processes. As a result, the network studies showed only limited success, focusing on social objects with clearly expressed local empirical specificity. It occurred because they, theoretically, neglected heterogeneity of the means, by which society maintains its stability and integrity.

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