scholarly journals Research on the Impact of the Coronavirus Disease 2019 (COVID-19) Pandemic on the Global Trade Economy Based on Big Data Analysis

2021 ◽  
Vol 33 (6) ◽  
pp. 1-18
Author(s):  
Jianfei Li ◽  
Juxing Li ◽  
Jin Ji ◽  
Shengjun Meng
Keyword(s):  
Big Data ◽  
Data Analysis ◽  
Industrial Development ◽  
Modern Society ◽  
Big Data Analysis ◽  
Development Pattern ◽  
Global Trade ◽  
Global Trend ◽  
Study Results ◽  
The Impact

The coronavirus disease 2019 (COVID-19) epidemic that began in early 2020 quickly formed a global trend, bringing unprecedented shocks to many countries’ and even the global trade economy. Big data is the main feature of the Internet era, which has transformed the industrial development pattern of modern society and has now flourished in the field of trade economy; therefore, it is of great significance to apply the big data analysis technology to study the impact of the COVID-19 epidemic on the global trade economy. On the basis of summarizing and analyzing previous research works, this paper, expounded the research status and significance of the impact of the COVID-19 epidemic on the global trade economy, elaborated the development background, The study results of this paper provide a reference for further researches on the impact of the impact of the COVID-19 epidemic on the global trade economy based on big data analysis.

scholarly journals Research on the Impact of the Coronavirus Disease 2019 (COVID-19) Epidemic on the Global Trade Economy Based on Big Data Analysis

2021 ◽  
Vol 33 (6) ◽  
pp. 0-0
Keyword(s):  
Big Data ◽  
Data Analysis ◽  
Industrial Development ◽  
Modern Society ◽  
Big Data Analysis ◽  
Development Pattern ◽  
Global Trade ◽  
Global Trend ◽  
Study Results ◽  
The Impact

The coronavirus disease 2019 (COVID-19) epidemic that began in early 2020 quickly formed a global trend, bringing unprecedented shocks to many countries’ and even the global trade economy. Big data is the main feature of the Internet era, which has transformed the industrial development pattern of modern society and has now flourished in the field of trade economy; therefore, it is of great significance to apply the big data analysis technology to study the impact of the COVID-19 epidemic on the global trade economy. On the basis of summarizing and analyzing previous research works, this paper, expounded the research status and significance of the impact of the COVID-19 epidemic on the global trade economy, elaborated the development background, The study results of this paper provide a reference for further researches on the impact of the impact of the COVID-19 epidemic on the global trade economy based on big data analysis.

scholarly journals Challenges of Big Data analysis

2014 ◽  
Vol 1 (2) ◽  
pp. 293-314 ◽  
Author(s):  
Jianqing Fan ◽  
Fang Han ◽  
Han Liu
Keyword(s):  
Big Data ◽  
Data Analysis ◽  
Measurement Errors ◽  
Modern Society ◽  
Big Data Analysis ◽  
Small Scale ◽  
Paradigm Change ◽  
Statistical Inferences ◽  
The One ◽  
And Storage

Abstract Big Data bring new opportunities to modern society and challenges to data scientists. On the one hand, Big Data hold great promises for discovering subtle population patterns and heterogeneities that are not possible with small-scale data. On the other hand, the massive sample size and high dimensionality of Big Data introduce unique computational and statistical challenges, including scalability and storage bottleneck, noise accumulation, spurious correlation, incidental endogeneity and measurement errors. These challenges are distinguished and require new computational and statistical paradigm. This paper gives overviews on the salient features of Big Data and how these features impact on paradigm change on statistical and computational methods as well as computing architectures. We also provide various new perspectives on the Big Data analysis and computation. In particular, we emphasize on the viability of the sparsest solution in high-confidence set and point out that exogenous assumptions in most statistical methods for Big Data cannot be validated due to incidental endogeneity. They can lead to wrong statistical inferences and consequently wrong scientific conclusions.

Application of Statistical Analysis Tools and Concepts to Big Data and Predictive Analytics to New Product Development

2020 ◽  
Vol 3 (1) ◽  
pp. 17-35
Author(s):  
Brian J. Galli
Keyword(s):  
Decision Making ◽  
Big Data ◽  
Data Analysis ◽  
Product Development ◽  
Competitive Advantage ◽  
New Product Development ◽  
New Product ◽  
Big Data Analysis ◽  
Life Cycles ◽  
The Impact

In today's fiercely competitive environment, most companies face the pressure of shorter product life cycles. Therefore, if companies want to maintain a competitive advantage in the market, they need to keep innovating and developing new products. If not, then they will face difficulties in developing and expanding markets and may go out of business. New product development is the key content of enterprise research and development, and it is also one of the strategic cores for enterprise survival and development. The success of new product development plays a decisive role both in the development of the company and in maintaining a competitive advantage in the industry. Since the beginning of the 21st century, with the continuous innovation and development of Internet technology, the era of big data has arrived. In the era of big data, enterprises' decision-making for new product development no longer solely relies on the experience of decision-makers; it is based on the results of big data analysis for more accurate and effective decisions. In this thesis, the case analysis is mainly carried out with Company A as an example. Also, it mainly introduces the decision made by Company A in the actual operation of new product development, which is based on the results of big data analysis from decision-making to decision-making innovation. The choice of decision-making is described in detail. Through the introduction of the case, the impact of big data on the decision-making process for new product development was explored. In the era of big data, it provides a new theoretical approach to new product development decision-making.

scholarly journals A Big Data Analysis on Distributed File Storage System

2019 ◽  
Vol 9 (2) ◽  
pp. 2383-2388
Keyword(s):  
Big Data ◽  
Data Analysis ◽  
Storage System ◽  
Real Life ◽  
File Systems ◽  
Big Data Analysis ◽  
Distributed File Systems ◽  
File Storage ◽  
Recent Developments ◽  
The Impact

Nowadays, the digital technologies and information systems (i.e. cloud computing and Internet of Things) generated the vast data in terabytes to extract the knowledge for making a better decision by the end users. However, these massive data require a large effort of researchers at multiple levels to analyze for decision making. To find a better development, researchers concentrated on Big Data Analysis (BDA), but the traditional databases, data techniques and platforms suffers from storage, imbalance data, scalability, insufficient accuracy, slow responsiveness and scalability, which leads to very less efficiency in Big Data (BD) context. Therefore, the main objective of this research is to present a generalized view of complete BD system that consists of various stages and major components of every stage to process the BD. In specific, the data management process describes the NoSQL databases and different Parallel Distributed File Systems (PDFS) and then, the impact of challenges, analyzed for BD with recent developments provides a better understanding that how different tools and technologies apply to solve real-life applications.

scholarly journals A Risk Assessment Algorithm for College Student Entrepreneurship Based on Big Data Analysis

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Chengjun Zhou ◽  
DuanXu Wang
Keyword(s):  
Risk Factors ◽  
Risk Assessment ◽  
Big Data ◽  
Data Analysis ◽  
College Student ◽  
Big Data Analysis ◽  
Technical Support ◽  
Assessment Process ◽  
Student Entrepreneurship ◽  
Study Results

College student entrepreneurship is a complex and dynamic process, in which the potential risks faced by entrepreneurial enterprises are interactive and diverse. The changes in risk assessment for college student entrepreneurship are also dynamic and nonlinear and are affected by many factors, which make the risk assessment process for college student entrepreneurship quite complicated. Big data analysis technology is a new product formed under the background of cloud computing and Internet technology, which has the characteristics of large data scale, multiple data types, and strong data value and provides more technical support for the researches on the risk assessment algorithm for college student entrepreneurship. On the basis of summarizing and analyzing previous research results, this article expounded the research status and significance of the risk assessment algorithm for college student entrepreneurship, elaborated the development background, current status, and future challenges of big data analysis technology, introduced the basic principles of support vector machine (SVM) and hierarchical analytic process, constructed a risk assessment model for college student entrepreneurship based on big data analysis, analyzed the risk factors and assessment indicators of the entrepreneurial model, proposed a risk assessment algorithm for college student entrepreneurship based on big data analysis, performed the discrimination coefficient calculation and comprehensive correlation optimization, and finally conducted a case experiment and its result analysis. The study results show that the risk assessment algorithm for college student entrepreneurship based on big data analysis can effectively realize the comprehensive management of risk factors, make full use of the value of assessment parameter data, and significantly improve the accuracy and efficiency of the risk assessment for college student entrepreneurship, providing more technical support for the researches on the risk assessment algorithm for college student entrepreneurship. The study results of this article provide a reference for further researches on the risk assessment algorithm of college student entrepreneurship based on big data analysis.

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.

scholarly journals The impact of big data analysis on competitive advantage support (Field study on industrial companies listed on the Palestine Stock Exchange)

2021 ◽  
Vol 10 (3) ◽  
pp. 630-646
Author(s):  
Abd El Rahman Mohammed Rashwan ◽  
Mohammed Atef Madi
Keyword(s):  
Big Data ◽  
Data Analysis ◽  
Competitive Advantage ◽  
Stock Exchange ◽  
Big Data Analysis ◽  
Quality Of Data ◽  
Industrial Companies ◽  
General Managers ◽  
Leadership Strategy ◽  
The Impact

The study was aimed at identifying the impact of big data analysis on supporting the competitive advantage of industrial companies listed on the Palestine Stock Exchange, the study used the descriptive analytical approach, and conducted the study on a sample of (49) general managers, financial and administrative in the industrial companies listed on the Palestine Stock Exchange, and concluded the study there is a significant impact of the analysis of big data on (strengthening competitive position, cost leadership strategy, strategy of excellence, strategy of focus) in the industrial companies listed on the Palestine Stock Exchange, and recommended that companies listed industrial in Palestine work on Do more big data analysis to support and enhance investors' decision-making ability by improving the quality of data obtained, and you need to have correct information about customers, products and the environment around the company in the fastest and least time to access the competitive advantage that big data analysis can provide.

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