scholarly journals Empirical Study on the Relationship between Highway Construction and Economic Growth Based on Big Data Analysis

2021 ◽  
Vol 1744 (3) ◽  
pp. 032011
Author(s):  
Wenjing Wang
Keyword(s):  
Economic Growth ◽  
Big Data ◽  
Data Analysis ◽  
Empirical Study ◽  
Highway Construction ◽  
Big Data Analysis ◽  
The Relationship

An empirical study on Cross-Border E-commerce Talent Cultivation-—Based on Skill Gap Theory and big data analysis

2022 ◽  
Vol 30 (7) ◽  
pp. 0-0
Keyword(s):  
Big Data ◽  
Data Analysis ◽  
Empirical Study ◽  
Big Data Analysis ◽  
Skill Level ◽  
University Research ◽  
Research Cooperation ◽  
Cross Border ◽  
Knowledge And Practice ◽  
Increasing Demand

To solve the dilemma between the increasing demand for cross-border e-commerce talents and incompatible students’ skill level, Industry-University-Research cooperation, as an essential pillar for inter-disciplinary talent cultivation model adopted by colleges and universities, brings out the synergy from relevant parties and builds the bridge between the knowledge and practice. Nevertheless, industry-university-research cooperation developed lately in the cross-border e-commerce field with several problems such as unstable collaboration relationships and vague training plans.

scholarly journals THE IMPLEMENTATION OF BIG DATA ANALYSIS IN REGULATING ONLINE SHORT-TERM RENTAL BUSINESS: A CASE OF AIRBNB IN BEIJING

2019 ◽  
Vol IV-4/W9 ◽  
pp. 79-86
Author(s):  
J. Li ◽  
F. Biljecki
Keyword(s):  
Machine Learning ◽  
Big Data ◽  
Data Analysis ◽  
Housing Prices ◽  
Big Data Analysis ◽  
Price Sensitivity ◽  
Short Term ◽  
New Business ◽  
The Impact ◽  
The Relationship

Abstract. With the fast expansion and controversial impacts of short-term rental platforms such as Airbnb, many cities have called for regulating this new business model. This research aims to establish an approach to understand the impact of Airbnb (and similar services) through big data analysis and provide insights potentially useful for its regulation. The paper reveals how Airbnb is influencing Beijing’s neighbourhood housing prices through machine learning and GIS. Machine learning models are developed to analyse the relationship between Airbnb activities in a neighbourhood and prevailing housing prices. The model of the best fit is then used to analyse the neighbourhood price sensitivity in view of increasing Airbnb activities. The results show that the sensitivity is variable: there are neighbourhoods that are likely to be more price sensitive to Airbnb activities, but also neighbourhoods that are likely to be price robust. Finally, the paper gives policy recommendations for regulating short-term rental businesses based on neighbourhood’s price sensitivity.

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