Entrepreneurial Innovative Network and the Design of Socio-Economic Neural Systems

Introduction

As a rule, innovation is considered as a process of creation of new technics and/or technologies. A common understanding often equates innovation and invention, and innovation and creativity. In the 19^th century, separate inventors, engineers, and business leaders created unique ideas, machines, technologies, and businesses. In the current global world, all companies and businesses are interdependent, thus they have to interact and cooperate to get their own goals.

Now is the time to discuss how separate innovators, organizations, and different distributed settings become a driver of creativity and innovation.

The main research questions of this study are: What the entrepreneurial innovative network is; how it creates the socio-economic neural system, and how inter-organizational networking becomes a driver of innovation.

The problem is that “creativity” refers to human, while “innovation” is relevant to companies. As a result, the following question arises: How do creative individuals turn into an “innovative company”? Separate individuals (inventors and researchers) and separate small companies or start-ups characterize the current scenario. They do not interact with each other, but produce innovation (e.g., new technologies and machines, and inventions and new materials) and, in the end, human progress. How does this happen?

The main aims of this research are following:

• 1.

  To research of the process of innovation creation from the point of view of collective interaction and self-organization;

• 2.

  To study the innovation as a non-linear process;

• 3.

  Development of a model of collective collaboration and interaction;

• 4.

  Studying the collective decision-making as a basis for creation of innovation;

• 5.

  Development of a model of network – socio-economic neural systems, which is based on the synthesis of system approach methodologies, information theory, General system theory and nonlinear dynamics;

• 6.

  Development of formulas for calculating the synergetic effect.

Methodology and research design are based on the synthesis of methodologies of the following Sciences: synergetic and theory of nonlinear systems, systems theory, system approach, information theory. This allowed the author to explore the process of creating innovations in social systems from several points of view, which, in turn, allowed us to get closer to the answer to the question of the nature of the innovations. Innovative processes and social systems do not obey the laws of linearity and cannot be modeled on the basis of linear dynamics. Therefore, we have to study innovation from the nonlinearity. Moreover, innovation cannot be “imposed from above”, i.e. innovation processes are initiated by intra-system processes. Hence, we conclude that the innovation is a self-organizing process. But the question is following: how do individual innovation agents come together for an innovation leap? It is obvious that these processes are in the field of information interaction.