Summary of Magnitude Properties of Topologically Distinct Channel Networks and Network Patterns

1976 ◽  
pp. 16-38 ◽  
Author(s):  
M. F. Dacey
Parasitology ◽  
2021 ◽  
pp. 1-36
Author(s):  
Thiago dos Santos Cardoso ◽  
Cecilia Siliansky de Andreazzi ◽  
Arnaldo Maldonado Junior ◽  
Rosana Gentile

2021 ◽  
Vol 13 (2) ◽  
pp. 947
Author(s):  
Shanshan Wu ◽  
Lucang Wang ◽  
Haiyang Liu

The development of tourism is based on tourism flow and studying a tourism flow network can help to elucidate its mechanism of operation. Transportation network is the path to realize the spatial displacement of tourism flow. This study used “Tencent migration” big data to explore the spatial distribution characteristics and rules of tourism flow in China, providing suggestions for the development of tourism. The results demonstrate that the 361 cities studied can be divided into three types: destination-oriented, tourist-origin-oriented, and destination-oriented and tourist-origin-oriented. There are significant differences in the quantity of flow, the area of concentration, and the factors affecting the flow in the three types of cities. The larger the flow of tourism between cities, the higher the network level, and the wider the network range. The high-level nodes are closely related, while the peripheral nodes are more widely distributed, with weak attractiveness and inconvenient traffic, forming a “core-edge” structure. Different network patterns are established for different modes of transportation. The degree of response of different types of transportation to distance is the main factor influencing the network patterns of diverse paths. These findings have practical implications for the choice of appropriate travel destinations and transportation modes for tourists.


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Sanghee Kim ◽  
Hongjoo Woo

Purpose According to the perspective of evolutionary economic theory, the marketplace continuously evolves over time, following the changing needs of both customers and firms. In accordance with the theory, the second-hand apparel market has been rapidly expanding by meeting consumers’ diverse preferences and promoting sustainability since 2014. To understand what changes in consumers’ consumption behaviors regarding used apparel have driven this growth, the purpose of this study is to examine how the second-hand apparel market product types, distribution channels and consumers’ motives have changed over the past five years. Design/methodology/approach This study collected big data from Google through Textom software by extracting all Web-exposed text in 2014, and again in 2019, that contained the keyword “second-hand apparel,” and used the Node XL program to visualize the network patterns of these words through the semantic network analysis. Findings The results indicate that the second-hand apparel market has evolved with various changes over the past five years in terms of consumer motives, product types and distribution channels. Originality/value This study provides a comprehensive understanding of the changing demands of consumers toward used apparel over the past five years, providing insights for retailers as well as future research in this subject area.


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