Examining online labor platforms to understand hiring bias and health consequences of the gig economy (30007601)

Business & Economics

1. Hiring 100%
2. Health 70%
3. Labor 68%
4. Employers 64%
5. Work Place 53%
6. Health Workers 45%
7. Monitoring System 42%
8. Gender Bias 35%
9. Contractors 30%
10. Healthcare 29%
11. Workers 25%
12. Field Experiment 18%
13. Asymmetric Information 16%
14. Information Asymmetry 16%
15. Managers 16%
16. Income 16%
17. Demographics 15%
18. Bid 14%
19. Chinese Americans 14%
20. Planning 14%
21. Contingent Workers 13%
22. Technology Monitoring 13%
23. Data Mining 12%
24. Monitoring 12%
25. Decision Heuristics 12%
26. Decision Bias 12%
27. Transaction Costs 12%
28. Societal Impact 12%
29. Information Policy 11%
30. Equal Opportunities 11%
31. Employee Benefits 11%
32. Econometric Modelling 10%
33. Bid Price 10%
34. Entry Barriers 10%
35. Scientific Knowledge 10%
36. Government Subsidies 10%
37. Peer to Peer 9%
38. Substitution Effect 9%
39. Health Status 9%
40. Long-term Relationships 9%
41. Natural Experiment 9%
42. System Design 9%
43. Pricing Policy 9%
44. Reorganization 8%
45. Government Agencies 8%
46. Market Efficiency 8%
47. Screening 8%
48. Experimentation 8%
49. Obligation 7%
50. Discrimination 7%
51. New Business 7%
52. Decision Making 7%
53. African Americans 7%
54. Substitute 7%
55. Car 7%
56. Policymaker 7%
57. Policy Implications 6%
58. Premium 6%
59. Decision-making Process 6%
60. Workforce 6%
61. Business Model 6%
62. Paradigm 6%
63. Wages 6%