Search

An indisputable fact in Global Value Chains (GVCs) is the rapid catching-up of China with U.S.A.; however, the convergence speed and depth have yet remained to be explored. On the one hand, the heterogeneity of different business functional activities, i.e. management, R&D, marketing and fabrication, is barely discussed. On the other hand, the international income transfers further complicate catching-up issue, since wedge between value-added and national income exists. Taking account of both them in a global multi-country input-output setting enables us to better understand the speed and depth of catching-up for China vis-à-vis U.S.A. China has made progress on narrowing the gap, albeit slowing down in the mid-2010s, but far from complete. This convergence speed is unevenly proceeded across business functions/industries. Similar catching-up finding holds for our new national income approach, but to a lesser extent. GVC participation scale enlarging and productivity improvement jointly lead to this catching-up, wherein scale contributes more than does productivity. We also find that the scale role is quite heterogeneous across business functions and industries. Despite catching-up in productivity at all levels, but starting from an extremely low level, a major lagging productivity gap remains. Also, the increasingly important role of productivity is observed. [ABSTRACT FROM AUTHOR]

Copyright of Actualidad Economica (0327585X) is the property of Instituto de Economia y Finanzas de la Facultad de Ciencias Economicas and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Potential mapping of MSMEs in Panenjoan Village, Bandung District is conducted to find out potential MSMEs in the village and is expected to bring up excellence products for the village. The purpose of this study is to see how the potential of the Panenjoan Village UMKM is based on its business function. This research method was conducted with a descriptive qualitative analysis and through in-depth interviews with business people in the Panenjoan Village. Based on the results of the mapping, it is known that MSMEs in Panenjoan Village have considerable potential because many businesses have marketed their products to the West Java region, but to support the sale of these products a business legality is needed that will support the expansion of the market for these businesses. [ABSTRACT FROM AUTHOR]

This paper explores the contribution of domestic and foreign demand to China's income growth by business function. To this end, we extend a single country input–output approach to a global multi-country setting, and further redefine the measure via forward linkages. We also propose chaining structural decomposition analysis to identify the role of domestic and foreign demand in functional income changes over 1999–2011. Using the World Input–Output Database combined with Labor Occupations Database, we distinguish functional activities in production, management, marketing and R&D. This enables us to find that domestic and foreign final demands, especially the former, jointly lead to China's income growth by business function. Dynamically, the generally upward trends in China's income hold in the aggregate as well as by industry and business function. We also find that China's income growth is quite heterogeneous across industries and business functions. [ABSTRACT FROM AUTHOR]

The functional activities, such as management, marketing, R&D and fabrication, carried out by a country or industry is of great importance for its governance and upgrading on the global value chains (GVCs). This paper provides a long-term macro-economic analysis on China's functional upgrading in GVCs and its drivers between 1999 and 2011. We combine the world input-output database with the newly compiled labour occupations database to measure China's functional income growth in internationally fragmented production networks, and then incorporate the concept into the chaining structural decomposition analysis (SDA) to explore its drivers. We find that China has achieved functional upgrading to some degree, reflected in the growth of China's domestic value added in headquarter activities, such as R&D, at the aggregate and industrial levels. However, fabrication activity still stands out, indicating that China still has a long way to go on upgrading in GVCs. Finally, through the chaining SDA, we find that among the GVC production, technology and consumption effects, the consumption level (consumer demand) is the main factor driving the growth of China's functional upgrading. [ABSTRACT FROM AUTHOR]

Copyright of Retos, Revista de Ciencias Administrativas y Económicas is the property of Universidad Politecnica Salesiana and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This paper illustrates the most recent results regarding the criticality ranking decision support classifier for an individual business function. The validated classifier is part of the business continuity points approach which estimates the recovery complexity of an individual business function and is based on the use case points method for estimating the software complexity. The business continuity points method is utilized in order to estimate specific recovery complexity parameters of a given business function. A part of the approach concerns the business function criticality ranking which is based on the recovery complexity parameters. In this paper, we measure the accuracy in the criticality ranking classifier by comparing results between the speedy and the detailed criticality ranking of a business function. The measurement is performed via the R-Studio software and the confusion matrix technique. The results are based on a learning data set prepared in MS Excel which includes the empirical calculations for constructing the specific classifier.