Study on the Function and Evolution Mechanism of Urban Innovation System

2018 ◽  
pp. 894-900
Author(s):  
Yan Ningning
Keyword(s):  
Innovation System ◽  
Evolution Mechanism

scholarly journals Simulating the Evolution Mechanism of Inner Innovation in Large-Scale Construction Enterprise with an Improved NK Model

2018 ◽  
Vol 10 (11) ◽  
pp. 4221 ◽  
Author(s):  
Tao Chen ◽  
Guangqiu Huang ◽  
Ayokunle Olanipekun
Keyword(s):  
Large Scale ◽  
Innovation System ◽  
Punctuated Equilibrium ◽  
Innovation Performance ◽  
Scale Construction ◽  
K Value ◽  
Evolution Mechanism ◽  
Construction Enterprise ◽  
Construction Enterprises ◽  
Two Parameters

The aim of this study is to simulate the self-organized evolution mechanism of inner innovation of large-scale construction enterprises (LSCE) under different contexts. Based on NK stochastic combinatorial optimization model with two parameters (N, K), this study proposes three modules—ambidexterity, punctuated equilibrium, and automation—to simulate the change behaviors of the inner innovation system. Furthermore, this study analyses the influence of factor correlation on inner innovation performance under discusses nine different combination situations. The research results show that (a) regardless of how the relationship strength changes, fitness increases with an increasing K value; and (b) the comparison of optimization modes show that the punctuated equilibrium mode can guarantee the long- and short-term inner innovation performance LSCE. This study therefore reveals the mutual effects of the factors in the inner innovation system in LSCE and provides an effective model for internal systems analyses in the construction industry and in other sectors.

Evolution Analysis of Popularity of “Cloud Computing”: Using Co-Integration and Causality Test

2012 ◽  
Vol 452-453 ◽  
pp. 817-822
Author(s):  
Si Qi Tan ◽  
Shu Hang Guo ◽  
Yan Chao Ding
Keyword(s):  
Cloud Computing ◽  
Innovation System ◽  
Test Methods ◽  
Potential Interaction ◽  
Specific Knowledge ◽  
Causality Test ◽  
Evolution Mechanism ◽  
Academic Fields ◽  
Evolution Analysis ◽  
Integration Analysis

Under the innovation system integrated with production, teaching and researching, the evolution mechanism of knowledge theme becomes central point in academic fields. However, previous researches mostly focused on analyzing the tendency of academic achievements, didn’t bring the potential interaction between the production and researching into consideration. In this paper we will use the co-integration analysis and Granger causality test methods, which are prevalent in economics research, to study the evolution of specific knowledge theme – “Cloud computing”. Our main purpose is to reveal the evolution mechanism as well as general principle of popularity of one theme.

“Triple Helix” in Russia’s Innovation System

2007 ◽  
pp. 123-135 ◽  
Author(s):  
I. Dezhina ◽  
V. Kiseleva
Keyword(s):  
Triple Helix ◽  
Government Regulation ◽  
Innovation System ◽  
Innovation Systems ◽  
Modern Theory

The article analyzes modern theory that explains the specificity of relationships among government, science and business in innovation systems - the "triple helix" concept. Factors that determine the appearance of new theory are systematized. The peculiarities of formation of "triple helix" in Russia are described, including the development of science, business and the system of government regulation in innovation sphere. The conclusion is made that currently in Russia only double linkages are formed.

Analisys of Innovation System Models

2006 ◽  
Vol 2 (3) ◽  
pp. 118-126
Author(s):  
I. S. Kuznecova ◽  
Keyword(s):  
Innovation System ◽  
System Models

Modeling and optimizing logistics, information, economic and financial intercluster cooperation using the ant colony optimization algorithm

2020 ◽  
Vol 26 (11) ◽  
pp. 2427-2447
Author(s):  
S.N. Yashin ◽  
E.V. Koshelev ◽  
S.A. Borisov
Keyword(s):  
Ant Colony Optimization ◽  
Optimization Algorithm ◽  
Population Decline ◽  
Innovation System ◽  
Federal District ◽  
Original Model ◽  
Ant Colony ◽  
Industrial Agglomeration ◽  
Ant Colony Optimization Algorithm

Subject. This article discusses the issues related to the creation of a technology of modeling and optimization of economic, financial, information, and logistics cluster-cluster cooperation within a federal district. Objectives. The article aims to propose a model for determining the optimal center of industrial agglomeration for innovation and industry clusters located in a federal district. Methods. For the study, we used the ant colony optimization algorithm. Results. The article proposes an original model of cluster-cluster cooperation, showing the best version of industrial agglomeration, the cities of Samara, Ulyanovsk, and Dimitrovgrad, for the Volga Federal District as a case study. Conclusions. If the industrial agglomeration center is located in these three cities, the cutting of the overall transportation costs and natural population decline in the Volga Federal District will make it possible to qualitatively improve the foresight of evolution of the large innovation system of the district under study.

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