Hash Based Two Gateway Payment Protocol Ensuring Accountability with Dynamic ID-Verifier for Digital Goods Providers

Author(s):  
Venkatasamy Sureshkumar ◽  
R. Anitha ◽  
N. Rajamanickam
2022 ◽  
pp. 126-146
Author(s):  
S. G. Marichev

The paper attempts to estimate, in monetary terms, the volume of free digital services in GDP while assessing the contribution of digitalization to changes in welfare and economic growth. Approaches to such an estimation are analyzed and criticized. In particular, the calculation of the added value created in the digital sector does not properly reflect the economic effect of digitalization. Alternative auxiliary methods for estimating the contribution of digitalization to GDP growth are considered: the creation of satellite accounts of the digital economy within the SNA; the categorization and calculation of “purely” digital goods. The paper analyzes the methodology of calculating GDP which takes into account consumer surpluses from the use of free digital goods. The advantages of this methodology are outlined, including the consideration of a significant part of the digital sector of the economy in the calculation of GDP, as well as the relative ease of its use. This methodology was tested by drawing on the example of the Republic of Bashkortostan.


2015 ◽  
Vol 40 (2) ◽  
pp. 107-117
Author(s):  
Manyi Chen ◽  
Qi Wang ◽  
Hongzhi Liu

Abstract The development of digital goods has profoundly changed the economic relationship and trading methods. Among all the digital goods recommendation information, ranking information is of prominent significance. The rankings impact consumers positively as they make decisions on buying digital products. We serve rankings and consumer psychologies as the object of this study, and will offer references and suggestions for the customization of the mobile terminal. Combining factor and cluster analysis, we subdivide the rankings into three groups first based on consumers’ values and lifestyles: reputation ranking, consumption behavior ranking and purchase intention ranking. Then, we use a correspondence analysis method to conclude the matching relationship between different types of rankings and various consumption psychology groups.


Sign in / Sign up

Export Citation Format

Share Document