Data-Driven Organizational Structure Optimization: Variable-Scale Clustering

LISS 2020 ◽  
2021 ◽  
pp. 79-89
Author(s):  
Ai Wang ◽  
Xuedong Gao
2019 ◽  
Vol 13 (2) ◽  
pp. 179-202
Author(s):  
Arianne Renan Barzilay

Abstract The changes created by platform-facilitated labor are considered fundamental challenges to the future of work. As more data accumulates on gender discrimination in online platforms, this Article explores how inequality is cultivated by platforms in the gig economy. Looking at technological architecture as organizational structure, this essay bridges a gap between three bodies of scholarship that have not yet been in conversation but considering them together is necessary if we are to think about gender equality in platform-facilitated labor. The first concerns data driven discrimination, the second concerns the role of platform affordances and the third concerns organizational policies. These point to the gender inequality regime that platforms may enact. Thus, the Article theoretically contributes to unpacking platforms’ role in perpetuating and institutionalizing gender inequality. Finally, it offers some suggestions on the ways in which law, policy and technology can disrupt the institutionalization of gender inequality in platform-facilitated labor.


2021 ◽  
Author(s):  
Patrick Jaillet ◽  
Gar Goei Loke ◽  
Melvyn Sim

A new study in the INFORMS journal Operations Research proposes a data-driven model for conducting strategic workforce planning in organizations. The model optimizes for recruitment and promotions by balancing the risks of not meeting headcount, budget, and productivity constraints, while keeping within a prescribed organizational structure. Analysis using the model indicates that there are increased workforce risks faced by organizations that are not in a state of growth or organizations that face limitations to organizational renewal (such as bureaucracies).


1989 ◽  
Vol 53 (4) ◽  
pp. 246-252
Author(s):  
DA Nash ◽  
EP Hicks ◽  
HR Laswell ◽  
GP Lewis ◽  
TT Lillich ◽  
...  

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