scholarly journals Opportunities, Relational Embeddedness and Network Structure

Author(s):  
Ulf Andersson ◽  
Desireé Blankenburg Holm ◽  
Martin Johanson
2019 ◽  
Vol 11 (12) ◽  
pp. 3249 ◽  
Author(s):  
Youn Kue Na ◽  
Sungmin Kang ◽  
Hye Yeon Jeong

It is important to understand the creative processes of social value networks in terms of the interdependent connections between fashion sharing economy businesses and consumers. In particular, when the similarity in the values of each member is shared in the sub-network, the closeness of the relationships can be further strengthened. In such value chains, the overall process is important because the content, which is originally provided through the distribution process, is reinterpreted from the consumer’s point of view and it is reproduced as new creative output with high added value. In this study, the characteristics of sub-network structure, the characteristics of social relations, and network externality are proposed and analyzed as influential variables of information diffusion behaviors that explain the diffusion of shared information in fashion sharing economy platforms. We examined the shared information diffusion performance of the sharing economy platform as a multidimensional influential factor including the network characteristics, and proposed a structural model that integrated network research and mobile information diffusion research. We surveyed 400 people with experience of fashion information activity on sharing economy platforms. Frequency, validity, reliability, measurement model and path analyses were conducted using SPSS and AMOS statistical packages. The results showed that trust value, profit/risk sharing, interdependence, and cultural/social similarity of the sub-network structure characteristics affected social relations, while trust value and cultural/social similarity also influenced relational embeddedness. Social relations and relational embeddedness, in turn, affected perceived complementarity and social interaction, both of which affected fashion information diffusion behaviors. Finally, social pressure, social ties, and social unity affected trust values. The results of this study can be applied not only to social connections among the members of the sub-network of a fashion sharing economy platform, but also as an effective means to explain the maintenance and reinforcement of mutual relations, thereby advancing the current academic research and practical applications.


2017 ◽  
Vol 102 (9) ◽  
pp. 1360-1374 ◽  
Author(s):  
Travis J. Grosser ◽  
Vijaya Venkataramani ◽  
Giuseppe (Joe) Labianca

2017 ◽  
Vol 4 (1) ◽  
pp. 82-109 ◽  
Author(s):  
Mustafa Yakar ◽  
Fatma Sert Eteman

Türkiye'de 20.yy'ın ortasından itibaren başlayan iç göçler zamanla kurulan göçmen ağları ile süreklilik kazanmış ve ülke içinde nüfusun kır-kent dağılımını değiştirecek boyutlara erişmiştir. Araştırma, göçün doğum yeri verisinden hareketle ikamet edilen yerdeki nüfus miktarına göre alınan ve verilen göç akışının büyüklüğünü iller ölçeğinde yönlü ağlar kullanılarak analiz edilmesini amaçlamaktadır. Araştırmada, TÜİK tarafından yayınlanmış olan 2015 yılına ait, iller ölçeğinde doğum yerine göre ikamet yeri verisi kullanılmıştır. Göçün kaynak ve hedef sahaları arasındaki akışını incelemek için NodeXL ile oluşturulan tek modlu, yönlü ve ağırlıklandırılmış göç ağının istatistiksel olarak tam ağ yapısına sahip olduğu görülmüştür. Ağ grafiklerinden ve istatistiklerinden göç hareketinin doğudan batıya doğru gerçekleştiği ve İstanbul’ un ülkenin tamamına hâkim bir görünüme sahip olduğu anlaşılmaktadır. Türkiye nüfusunun cumhuriyet tarihi içinde geçirdiği iç göç süreçleriyle birlikte ülke içinde kurulmuş ve oldukça karmaşık bir görünüme sahip ağ yapısının olduğu ileri sürülebilir. Kurulan ağlar göçlerin devamını sağladığı gibi, göçün yöneldiği merkezlerde daha heterojen nüfus yapılarının ortaya çıkmasına yol açmıştır.ABSTRACT IN ENGLISHSocial Network Analysis of Migration Inter Provinces In Turkey with Nodexl The internal migrations which started in Turkey in the middle of the 20th century have gained permanency with the migration networks that were established at the time and reached dimensions which have the potential to change the rural-urban distribution of the population within the country.  The study aims to analyze the magnitude of the incoming and outgoing migration flow at the provincial scale based on the population data for place of birth according to place of residence by using directional networks. Place of residence according to place of birth at the provincial scale data for 2015 published by TÜİK was used in the study. A single mode, directional and weighted migration network created with NodeXL to examine the migration flows between the source and target has a statistically complete network structure. The network graphs and statistics show that the migrations have taken place from east to west and Istanbul has a view as dominant of the country. It can be argued that internal network structure of Turkish population has  a very complex view because of internal migration in the history of the republic. The established networks have enabled the continuation of migration and have manifested as the emergence of more heterogeneous population structures in centers where migration had been directed.


2019 ◽  
Vol 22 (4) ◽  
pp. 336-341
Author(s):  
D. V. Ivanov ◽  
D. A. Moskvin

In the article the approach and methods of ensuring the security of VANET-networks based on automated counteraction to information security threats through self-regulation of the network structure using the theory of fractal graphs is provided.


2020 ◽  
Vol 2020 (17) ◽  
pp. 2-1-2-6
Author(s):  
Shih-Wei Sun ◽  
Ting-Chen Mou ◽  
Pao-Chi Chang

To improve the workout efficiency and to provide the body movement suggestions to users in a “smart gym” environment, we propose to use a depth camera for capturing a user’s body parts and mount multiple inertial sensors on the body parts of a user to generate deadlift behavior models generated by a recurrent neural network structure. The contribution of this paper is trifold: 1) The multimodal sensing signals obtained from multiple devices are fused for generating the deadlift behavior classifiers, 2) the recurrent neural network structure can analyze the information from the synchronized skeletal and inertial sensing data, and 3) a Vaplab dataset is generated for evaluating the deadlift behaviors recognizing capability in the proposed method.


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