The Economics of Market Allocation

2019 ◽  
pp. 41-65
Author(s):  
Steven C. Hackett
Keyword(s):  
Market Allocation

Do Stop-loss Rules Add Value in International Equity Market Allocation?

2020 ◽  
Author(s):  
Bochuan Dai ◽  
Ben R. Marshall ◽  
Nhut H. Nguyen ◽  
Nuttawat Visaltanachoti
Keyword(s):  
Equity Market ◽  
International Equity ◽  
Market Allocation ◽  
Stop Loss

Do stop-loss rules add value in international equity market allocation?

2021 ◽  
pp. 1-14
Author(s):  
Bochuan Dai ◽  
Ben R. Marshall ◽  
Nhut Hoang Nguyen ◽  
Nuttawat Visaltanachoti
Keyword(s):  
Equity Market ◽  
International Equity ◽  
Market Allocation ◽  
Stop Loss

The pure market allocation of land between forestry and agriculture

2018 ◽  
Vol 97 ◽  
pp. 122-131 ◽  
Author(s):  
Peter Deegen ◽  
Andreas Halbritter
Keyword(s):  
Market Allocation

MARKET ALLOCATION AND OPTIMUM GROWTH

1968 ◽  
Vol 7 (10) ◽  
pp. 17-27 ◽  
Author(s):  
H. UZAWA
Keyword(s):  
Optimum Growth ◽  
Market Allocation

scholarly journals Structural Holes in the Multi-Sided Market: A Market Allocation Structure Analysis of China’s Car-Hailing Platform in the Context of Open Innovation

2019 ◽  
Vol 11 (20) ◽  
pp. 5813 ◽  
Author(s):  
Lei Huang ◽  
Yandong Zhao ◽  
Liang Mei ◽  
Peiyi Wu ◽  
Zhihua Zhao ◽  
...  
Keyword(s):  
Open Innovation ◽  
Personal Data ◽  
Data Driven ◽  
Edge Weight ◽  
Data Allocation ◽  
Structural Holes ◽  
Data Resource ◽  
Platform Governance ◽  
Sustainable Innovation ◽  
Market Allocation

Car-hailing platform governance is an emerging topic of research and practice. The governance of the data-driven platform economy is challenging the research paradigm of competition regulation in the context of open innovation. This research is trying to reveal the market allocation structure of China’s online car-hailing industry from the perspective of personal data allocation by the study of Application Programming Interface (API) of sample platforms. On the basis of the networked nature of personal data allocation via APIs, this research constructs a mathematical model of the edge weight of data resource connections between platforms. Furthermore, this research optimises the structural hole analysis of complex networks to discuss the state of personal data resource allocation in China’s car-hailing industry. Results reveal that there are obvious structural holes within the sample network. When compared with related indicators, we found that accessing personal data resources is an essential component of the sample network competition capability and sustainable innovation. Social media platforms and online payment platforms more greatly impact car-hailing platform competition than other types of platforms within the multi-sided market context. This research offers a research perspective of personal data allocation for further study of competition, regulation and sustainable innovation of data-driven platform economies.

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