Big Data Research on China’s Service Industry Under the COVID-19 Epidemic

2022 ◽  
pp. 1007-1013
Author(s):  
Yawei Jiang ◽  
Zhenhua Cai ◽  
Huali Cai
Keyword(s):  
Big Data ◽  
Service Industry

You Are What You Pay – Personal Profiling with Alternative Payment Data and the Data Protection Law

2020 ◽  
Vol 89 (4) ◽  
pp. 73-88
Author(s):  
Pauline Affeldt ◽  
Ulrich Krüger
Keyword(s):  
Big Data ◽  
Financial Services ◽  
Service Industry ◽  
Credit Scoring ◽  
Scoring Systems ◽  
Global Trend ◽  
Informationelle Selbstbestimmung ◽  
Economic Developments ◽  
Customer Profiles ◽  
Scoring Systeme

Summary: The global trend toward cashless payment started well before the corona pandemic. Along with it, investors in the data-driven tech industry are inspired by the promise of targeted behavioral scoring based on big data. It seems economically tempting to combine these two trends by using all data generated by the payment services to create personal profiles. However, this business model conflicts with the individual’s right of informational self-determination and raises questions regarding inaccuracies, discrimination, and the non-transparency of the algorithms underlying these profiles. Our article provides a short overview over the recent economic developments in the financial service industry and a legal assessment in light of the GDPR. Not everything that is feasible with big data scoring using alternative payment data is legally allowed in Europe. Nevertheless, traditional banks could have the opportunity to improve their internal credit scoring systems and use individual customer profiles to further market their financial services. Zusammenfassung: Nicht erst seit der Corona Pandemie gibt es weltweit den Trend zum bargeldlosen Zahlungsverkehr. Zudem beflügelt die Vorstellung eines zielgenauen Behavioral (Big Data) Scoring die Fantasien von Investoren in der Datentechnologiebranche. Es scheint ökonomisch verführerisch, beide Trends zusammenführen, wenn man alle Daten aus dem Zahlungsverkehr für ein persönliches Profil auswerten würde. Dieses Geschäftsmodell liegt jedoch mit dem Recht des Einzelnen auf informationelle Selbstbestimmung im Konflikt und wirft Fragen auf im Hinblick auf Ungenauigkeit, Diskriminierung und Intransparenz. Unser Artikel gibt einen Überblick über die ökonomische Entwicklung des Sektors und eine rechtliche Bewertung insbesondere aus Sicht der europäischen Datenschutz-Grundverordnung. Nicht alles was im Big Data Scoring mit alternativen Zahlungsdaten möglich sein könnte, ist in Europa auch rechtlich zulässig. Vor allem für die „klassischen“ Banken könnte sich gleichwohl eine Möglichkeit eröffnen ihre internen Credit Scoring Systeme zu verbessern und mit angepasst-individuellen Kundenprofilen weitere ihrer Finanzdienstleistungen zu vertreiben.

scholarly journals A Study on the Prospects of the Korea Beauty Industry

2021 ◽  
Vol 12 (5) ◽  
pp. 382-386
Author(s):  
Hye-Jin Kwon, Hee-Kyung Lim
Keyword(s):  
Big Data ◽  
Industrial Revolution ◽  
Service Industry ◽  
Individual Characteristics ◽  
It Industry ◽  
Self Development ◽  
New Business ◽  
Elderly Consumers ◽  
The Creation ◽  
New Jobs

The development of IT industry is playing an important role in the prevention of the COVID-19 infection in Korea. The development of IT industry is used in various fields. The beauty industry in the era of the 4th Industrial Revolution can identify the racial, regional and individual characteristics of customers through the use of big data with the AI system. It is also expected that such development will bring a change in the creation of new jobs and occupations in the service industry. Therefore, it is necessary to establish an environment that enables the development of nurturing education and creativity of outstanding individuals who will lead new business trends. In addition, a beauty-related industry that can meet the desire of new elderly consumers throughout the society is required. It is expected that the beauty industry in Korea will require a service that combines self-development, convenience and plays for companies, workers and consumers in future.

scholarly journals A Study on the Health Output Effect of Chinese Medical Service Industry Agglomeration Based on Big Data Analysis

2020 ◽  
Vol 2020 ◽  
pp. 1-9
Author(s):  
Yan Shu ◽  
Longxin Lin ◽  
Yueqian Hu
Keyword(s):  
Big Data ◽  
Medical Service ◽  
Service Industry ◽  
Fixed Effect Model ◽  
Significance Test ◽  
Eastern Region ◽  
Medical Resources ◽  
Output Effect ◽  
Industry Agglomeration ◽  
Health Level

The agglomeration health output effect of the medical service industry in the era of big data is an important part of the agglomeration innovation of medical resources. This paper used the regression model of data mining to set up the fixed effect model and system GMM model to study the relationship between the agglomeration of medical service industry and resident’s health level, based on the panel data of 31 provinces of China from 2003 to 2017. The results show that the health outcome of the medical industrial agglomeration is positive and different in provinces. The influence of medical service cluster on residents’ health level in the eastern region fails the significance test, while the medical service cluster in the central and western regions can significantly improve residents’ health level. And, this effect is also related to the characteristics of medical resources, economic development, demographic characteristics, and other heterogeneous factors. On this basis, the paper puts forward policy suggestions to promote the market structure of the medical industry from the aspects of strengthening synergies and policy guidance.

scholarly journals Analysis of the Influence Path of Guiyang Big Data Expo on Regional Economic Developments

2021 ◽  
Vol 235 ◽  
pp. 03016
Author(s):  
Qing Li
Keyword(s):  
Economic Development ◽  
Big Data ◽  
Industrial Development ◽  
Industrial Structure ◽  
Service Industry ◽  
Regional Economic Development ◽  
Regional Economic ◽  
Direct Benefits ◽  
Optimization And Upgrading ◽  
Exhibition Industry

Exhibition industry is an important part of modern service industry, and exhibition economy can play a strong driving role in regional and industrial development. At the same time, the exhibition economy is different from other industries. In addition to the direct benefits generated by the exhibition itself, the exhibition industry has a strong pulling effect on the regional economic development due to its strong clustering characteristics. The Big Data Expo is an important platform for the development of national big data industry, through the development of Guiyang Digital Expo, this paper proposes to promote the optimization and upgrading of regional industrial structure by cultivating exhibition industry chain, promoting the evolution of regional economic development path and enhancing regional comprehensive competitiveness, so as to realize the driving effect of exhibition industry and exhibition economy on regional economic development.

scholarly journals Research on Modularization and Association of Elderly Care Services in Big Data Environment

2021 ◽  
Vol 257 ◽  
pp. 03061
Author(s):  
Yan Zhao
Keyword(s):  
Big Data ◽  
Work Experience ◽  
Service Industry ◽  
Care Service ◽  
Elderly Care ◽  
The Elderly ◽  
Scientific Development ◽  
Care Services ◽  
Data Environment ◽  
Distributed Association

At this stage, China is in the stage of building a well-off society in an all-round way, and the application of big data has positive significance for the grasp of China’s national conditions and the laws of scientific development. At the same time, big data applications can also provide support for the development of the elderly care service industry. This article summarizes the modular content of elderly care services based on previous work experience. The author discusses the data association analysis of distributed elderly care services in a big data environment from four aspects: the construction of distributed association classifiers, the incremental mining of association classifiers based on constraints, the running process of the distributed association classifier model, and the evaluation of actual elderly care services.

Sign in / Sign up

Export Citation Format

Share Document