scholarly journals The Influence of Alliance Innovation Network Structure upon Enterprise Innovation: A Case Study of China’s Energy-Saving and Environment-protection Industry

2018 ◽  
Vol 13 (2) ◽  
pp. 208
Author(s):  
Meng Xu
Keyword(s):  
Energy Saving ◽  
Network Structure ◽  
Betweenness Centrality ◽  
Path Length ◽  
Clique Number ◽  
Average Path Length ◽  
Clustering Coefficient ◽  
Environment Protection ◽  
Different Types ◽  
Enterprise Innovation

The Energy-saving and environment-protection industry, an important strategic and emerging industry in China, will develop into a pillar industry. In view of global climate change, environmental pollution, resource depletion and the defects and deficiencies in traditional technology, technology and product innovation constitute the lifeline of energy-saving and environment-protection industry. The alliance network of enterprises will influence, stimulate, and regulate enterprise innovation greatly. A comprehensive analysis of alliance data of China's energy-saving and environment-protection industry from 2000 to 2013 by using Ucinet software can reveal the network structure parameters such as degree, clique number, average path length, clustering coefficient, and betweenness centrality, which reflects different types of enterprise networks and different positions of enterprises in different types of networks. A negative regression analysis of enterprise patent data and network structure parameters by using Stata software can make some conclusions that the influences of network characteristics on enterprise innovation reach the maximum in the second year of the window period end, that innovation accumulation, clustering coefficient, betweenness centrality are related to the enterprise innovation, that clique number, network density are negatively related to the enterprise innovation, and that there is an inverted U relationship between average path length and enterprise innovation. It is suggested to increase the accumulation level of innovation, appropriately control the network density, reduce the average path length, improve the betweenness centrality and clustering coefficient of enterprises, so as to improve the overall innovation level. 

Technological Alliance Networks Analysis under Complex Network Perspective - Case of China's TD-SCDMA Industry

2013 ◽  
Vol 756-759 ◽  
pp. 2774-2778
Author(s):  
Liang Mei
Keyword(s):  
Complex Network ◽  
Path Length ◽  
Small World ◽  
Average Path Length ◽  
Clustering Coefficient ◽  
Structure Characteristics ◽  
Alliance Networks ◽  
Different Types ◽  
Networks Analysis

This paper discusses the structure characteristics of Chinas TD-SCDMA industry alliance from complex network perspective. We use the basic two parametersaverage path length and clustering coefficient to do the analysis. Results show that comparing to the different types of complex network, Chinas TD-SCDMA industry alliance has relatively high clustering coefficient and low average path length, implicating the obvious small-world characteristic.

ANALISIS PERINGKAT TOP BRAND OJEK ONLINE MENGGUNAKAN JEJARING SOSIAL PERCAKAPAN TWITTER

2019 ◽  
Vol 24 (2) ◽  
pp. 88-104
Author(s):  
Ilham Aminudin ◽  
Dyah Anggraini
Keyword(s):  
Social Media ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Path Length ◽  
Average Path Length ◽  
Average Degree ◽  
Clustering Coefficient ◽  
R Programming

Banyak bisnis mulai muncul dengan melibatkan pengembangan teknologi internet. Salah satunya adalah bisnis di aplikasi berbasis penyedia layanan di bidang moda transportasi berbasis online yang ternyata dapat memberikan solusi dan menjawab berbagai kekhawatiran publik tentang layanan transportasi umum. Kemacetan lalu lintas di kota-kota besar dan ketegangan publik dengan keamanan transportasi umum diselesaikan dengan adanya aplikasi transportasi online seperti Grab dan Gojek yang memberikan kemudahan dan kenyamanan bagi penggunanya Penelitian ini dilakukan untuk menganalisa keaktifan percakapan brand jasa transportasi online di jejaring sosial Twitter berdasarkan properti jaringan. Penelitian dilakukan dengan dengan mengambil data dari percakapan pengguna di social media Twitter dengan cara crawling menggunakan Bahasa pemrograman R programming dan software R Studio dan pembuatan model jaringan dengan software Gephy. Setelah itu data dianalisis menggunakan metode social network analysis yang terdiri berdasarkan properti jaringan yaitu size, density, modularity, diameter, average degree, average path length, dan clustering coefficient dan nantinya hasil analisis akan dibandingkan dari setiap properti jaringan kedua brand jasa transportasi Online dan ditentukan strategi dalam meningkatkan dan mempertahankan keaktifan serta tingkat kehadiran brand jasa transportasi online, Grab dan Gojek.

SCALE-FREE AND SMALL-WORLD PROPERTIES OF A SPECIAL HIERARCHICAL NETWORK

Fractals ◽  
2019 ◽  
Vol 27 (02) ◽  
pp. 1950010
Author(s):  
DAOHUA WANG ◽  
YUMEI XUE ◽  
QIAN ZHANG ◽  
MIN NIU
Keyword(s):  
Degree Distribution ◽  
Path Length ◽  
Small World ◽  
Average Path Length ◽  
Clustering Coefficient ◽  
Hierarchical Network ◽  
Scale Free

Many real systems behave similarly with scale-free and small-world structures. In this paper, we generate a special hierarchical network and based on the particular construction of the graph, we aim to present a study on some properties, such as the clustering coefficient, average path length and degree distribution of it, which shows the scale-free and small-world effects of this network.

scholarly journals A Complex Network Approach for Quantitative Characterization and Robustness Analysis of Sandstone Pore Network Structure

Geofluids ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Yuhao Hu ◽  
Guannan Liu ◽  
Feng Gao ◽  
Fengtian Yue ◽  
Tao Gao
Keyword(s):  
Pore Structure ◽  
Complex Network ◽  
Degree Distribution ◽  
Path Length ◽  
Robustness Analysis ◽  
Pore Network ◽  
Average Path Length ◽  
Clustering Coefficient ◽  
Random Disturbance ◽  
Pagerank Algorithm

The rational characterization and quantitative analysis of the complex internal pore structure of rock is the foundation to solve many underground engineering problems. In this paper, CT imaging technology is used to directly characterize the three-dimensional pore network topology of sandstone with different porosity. Then, in view of the problem, which is difficult to quantify the detailed topological structure of the sandstone pore networks in the previous study, the new complex network theory is used to characterize the pore structure. PageRank algorithm is based on the number of connections between targets as a measure index to rank the targets, so the network degree distribution, average path length, clustering coefficient, and robustness based on PageRank algorithm and permeability-related topological parameters are studied. The research shows that the degree distribution of sandstone pore network satisfies power law distribution, and it can be characterized by scale-free network model. The permeability of rock is inversely proportional to the average path length of sandstone network. The sandstone pore network has strong robustness to random disturbance, while a small number of pores with special topological properties play a key role in the macroscopic permeability of sandstone. This study attempts to provide a new perspective of quantifying the microstructure of the pore network of sandstone and revealing the microscopic structure mechanism of macroscopic permeability of pore rocks.

scholarly journals Improvising Climate Smart Agricultural Practices Using Design Thinking by Undergraduate Student of Agriculture under Central Agricultural University, Imphal: A Case of Social Network Analysis

2020 ◽  
pp. 1-7
Author(s):  
Elly Kirwa ◽  
Rajkumar Josmee Singh
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Path Length ◽  
Design Thinking ◽  
Agricultural Practices ◽  
Average Path Length ◽  
Average Degree ◽  
Clustering Coefficient ◽  
Collaborative Problem Solving

Aims: This study uses Social Network Analysis (SNA) to investigate the social interaction that shape student collaborative problem solving activity when undergoing Design Thinking (DT) to improvise Climate Smart Agricultural Practices (CSAPs). Place and Duration of Study: The study was conducted at the three Colleges of Agriculture (CoAs) under Central Agricultural University, Imphal at Manipur viz., the (1) CoA, Imphal at Manipur, (2) CoA, Pasighat at Arunachal Pradesh; and (3) CoA, Kyrdemkulai at Meghalaya. The study was conducted between November 2019 and February 2020. Methodology: A sample of 28 respondents who constituted fifty percent of population of final year B.Sc. (Agriculture) students was selected through simple random sampling without replacement from the three CoAs. SNA of respondent-students was analyzed using Gephi 0.9.2 software with the following attributes to understand the student community viz., average degree, modularity, average clustering coefficient and average path length. Results: The network for CoA, Imphal displayed the following characteristic as ‘Average Degree’ of 5.69, ‘Modularity’ of 0.149, ‘Average Clustering Coefficient’ of 0.468 and ‘Average Path Length’ of 1.57. In case of CoA, Pasighat, the attributes of social network were as ‘Average Degree’ of 3.63, ‘Modularity’ of 0.513, ‘Average Clustering Coefficient’ of 0.099 and ‘Average Path Length’ of 1.52j; while for the case of CoA, Kyrdemkulai, it had ‘Average Degree’ of 3.86, ‘Modularity’ of 0.024, ‘Average Clustering Coefficient’ of 0.650 and ‘Average Path Length’ of 1.360. Conclusion: For meaningful improvising of CSAPs using DT, the efficiency of social network was more functional on smaller collaborative working groups as information flow was found to be high in small groups leading to development of more ideas on DT.

scholarly journals Statistical Analysis of Weighted Networks

2008 ◽  
Vol 2008 ◽  
pp. 1-16 ◽  
Author(s):  
I. E. Antoniou ◽  
E. T. Tsompa
Keyword(s):  
Degree Distribution ◽  
Path Length ◽  
Average Path Length ◽  
Clustering Coefficient ◽  
Weighted Graphs ◽  
Statistical Characterization ◽  
Weighted Networks ◽  
Weighted Clustering ◽  
Statistical Regularities

The purpose of this paper is to assess the statistical characterization of weighted networks in terms of the generalization of the relevant parameters, namely, average path length, degree distribution, and clustering coefficient. Although the degree distribution and the average path length admit straightforward generalizations, for the clustering coefficient several different definitions have been proposed in the literature. We examined the different definitions and identified the similarities and differences between them. In order to elucidate the significance of different definitions of the weighted clustering coefficient, we studied their dependence on the weights of the connections. For this purpose, we introduce the relative perturbation norm of the weights as an index to assess the weight distribution. This study revealed new interesting statistical regularities in terms of the relative perturbation norm useful for the statistical characterization of weighted graphs.

AN IDEAL DISASSORTATIVE NETWORK AND SYNCHRONIZATION

2006 ◽  
Vol 16 (10) ◽  
pp. 3093-3102 ◽  
Author(s):  
DONG CHENGDONG ◽  
LIU ZENGRONG
Keyword(s):  
Dynamic System ◽  
Complex Network ◽  
Network Topology ◽  
Path Length ◽  
Average Path Length ◽  
Clustering Coefficient ◽  
Novel Complex ◽  
The Impact

This paper proposes a novel complex network with disassortative property based on multicenter networks. The average path length and clustering coefficient of the network are calculated, and the impact on the network topology is investigated. A simple dynamic system established on the proposed network is used to analyze how the disassortative property of the network affects synchronization.

Complexity Analysis of Public Transportation Network in Zhangjiagang City Using Complex Network Theory

2012 ◽  
Vol 546-547 ◽  
pp. 1211-1216
Author(s):  
Yong Wang ◽  
Ta Zhou
Keyword(s):  
Complex Network ◽  
Public Transportation ◽  
Path Length ◽  
Complexity Analysis ◽  
Transportation Network ◽  
Average Path Length ◽  
Clustering Coefficient ◽  
Power Law Distribution ◽  
Complex Network Theory ◽  
Public Transportation Network

Public transportation network has been proven that it can be simulated as a complex network. In this paper, a bus transport system of Zhangjiagang city is considered. Network degree distribution, average path length, and clustering coefficient are utilized as criteria to analyze as the complexity of the network. Experimental results show that the network which is in line with power-law distribution has a smaller average path length and a large clustering coefficient. It also indicates that, the networks of Zhangjiagang public bus system are not a small-world network with scale-free property.

THE LOCALLY OPTIMAL STRUCTURE FOR SYNCHRONIZABILITY OF DYNAMICAL NETWORKS

2012 ◽  
Vol 26 (31) ◽  
pp. 1250188
Author(s):  
SHOULIANG BU ◽  
JIAN-PING WEN ◽  
QING-HU ZHONG ◽  
XUE-HUA YI
Keyword(s):  
Path Length ◽  
Average Path Length ◽  
Clustering Coefficient ◽  
Optimal Structure ◽  
Dynamical Networks ◽  
Structural Perturbations

A network is referred to have locally optimal structure for synchronizability if its synchronizability is always decreased, no matter an arbitrary edge is added to it or an arbitrarily existed edge is deleted from it or an arbitrary edge is rewired in it. Although it is difficult to generally determine which networks have locally optimal structure, this paper through various examples demonstrates that symmetrical networks indeed have this property. Actually, it is found that any structural perturbations which destruct the symmetry of an originally symmetrical network would decrease the network's synchronizability, no matter how the perturbations change the network's average path length or clustering coefficient.

An Empirical Study on the Characteristics of Complex Network of Firms' Innovation Network-Taking Taiyuan Stainless Steel Firms as an Example

2014 ◽  
Vol 644-650 ◽  
pp. 6261-6264
Author(s):  
Bin Qiao ◽  
Lin Ji ◽  
Xiao Xiao Wang
Keyword(s):  
Stainless Steel ◽  
Empirical Study ◽  
Power Law ◽  
Path Length ◽  
Average Path Length ◽  
Clustering Coefficient ◽  
Innovation Network ◽  
Power Law Distribution ◽  
Simulation Results ◽  
Two Stages

Research shows the degree distribution of firms' innovation network in accordance with power-law distribution as continuous evolution of firms' innovation network, which has larger clustering coefficient and smaller average path length. Therefore, the network structure and simulation results of two stages are compared with the data of Taiyuan stainless steel firms' innovation network. The size of Taiyuan stainless steel firms' innovation network is constantly expanding, so is the clustering coefficient, while the average path length is constantly shrinking.

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