Suchergebnisse

This paper investigates whether the impact of Brexit on financial markets is consistent with rational asset pricing models using 34 financial indices. Our results indicate that, whilst Brexit events affect both the risk and returns of stocks, the returns on event days are largely justified by the risk and the risk premium on those days. Our results support the appropriateness of rational asset pricing models even in a period of such high political uncertainty and potentially raised sentiment.

© 2020 Elsevier Ltd The challenge of food waste in the foodservice sector of China is under-examined. This paper advances knowledge by exploring the food waste management practices adopted in a sample of Shanghai full-service restaurants. Through 22 in-depth semi-structured interviews with senior managers it establishes the significance of the food waste challenge and identifies Chinese food consumption habits as a major cause. Despite the pronounced role of consumers in food waste generation, restaurateurs largely fail to engage them in mitigation. To mitigate food waste occurring on customer plates, changes to the Chinese dining culture should be facilitated via nation-wide campaigns aiming to raise public awareness of food waste when eating out. The government of China should lead on the design of such campaigns, ideally involving celebrities for better consumer appeal and academics for the assessment of their effectiveness. The national government should also provide free-to-attend specialist training to restaurant managers and staff on how to mitigate food waste occurring in kitchens.

In the big data era, real-time log data analysis is becoming the important demands for Internet enterprises, behind these data hiding big value. Map Word, the National Platform for Common GeoSpatial Information Services in China, is a one-stop website providing geospatial information services to personal users, enterprises, professional agencies and governments. After 7 years' development of the platform, the traffic increased significantly, reaching 200 million service requests per day. But due to the lack of effective analysis and processing technology, the log data did not play its value, which lead to disconnection between the top-level design of national common geospatial information services and the actual demands of the users in a way. Now, the geospatial information service in China is trying to shift from the data production driven to the demand driven actively, and how to understand the demands of users became one imperious issue for research. In addition, the access behaviour of group users to common geospatial information services has a social nature and there is a certain group access behaviour pattern. This mode has high intensity of access aggregation and spontaneity, and determines the demand of common geospatial information services for cloud computing resources. Parts of the above demands can be analysed from the log data. Therefore, how to develop a log analysis system for unified real-time collection, real-time analysis, centralized storage, and graphical display is the key to support the demands. Flume, Kafka, Storm, Redis and HBase have been integrated to design and implement a distributed real-time log analysis system supporting online and offline log analysis. The system is composed of log collection module, asynchronous communication module, real time analysis and calculation module, data cashing and storage module, and visualization module. The system was release and integrated with Map World in June 2017 successfully, and the implementation of the system indicates that it can efficiently solve the problems of real-time log data collection, real-time analysis, real-time storage, real-time query, massive data storage, offline analysis, etc. It played an important role in map data update, policy making, product decisions, online server load prediction, resource allocation optimization, Internet security improvement and operation funs evaluation.

In the big data era, real-time log data analysis is becoming the important demands for Internet enterprises, behind these data hiding big value. Map Word, the National Platform for Common GeoSpatial Information Services in China, is a one-stop website providing geospatial information services to personal users, enterprises, professional agencies and governments. After 7 years' development of the platform, the traffic increased significantly, reaching 200 million service requests per day. But due to the lack of effective analysis and processing technology, the log data did not play its value, which lead to disconnection between the top-level design of national common geospatial information services and the actual demands of the users in a way. Now, the geospatial information service in China is trying to shift from the data production driven to the demand driven actively, and how to understand the demands of users became one imperious issue for research. In addition, the access behaviour of group users to common geospatial information services has a social nature and there is a certain group access behaviour pattern. This mode has high intensity of access aggregation and spontaneity, and determines the demand of common geospatial information services for cloud computing resources. Parts of the above demands can be analysed from the log data. Therefore, how to develop a log analysis system for unified real-time collection, real-time analysis, centralized storage, and graphical display is the key to support the demands. Flume, Kafka, Storm, Redis and HBase have been integrated to design and implement a distributed real-time log analysis system supporting online and offline log analysis. The system is composed of log collection module, asynchronous communication module, real time analysis and calculation module, data cashing and storage module, and visualization module. The system was release and integrated with Map World in June 2017 successfully, and the implementation of the system indicates that it can efficiently solve the problems of real-time log data collection, real-time analysis, real-time storage, real-time query, massive data storage, offline analysis, etc. It played an important role in map data update, policy making, product decisions, online server load prediction, resource allocation optimization, Internet security improvement and operation funs evaluation.