Comparative Analysis and Legality of Anti-poaching Agreements in the Indian Context

Adhip Narayan Banerjee & Maryam Ishrat Beg

The International Journal of Comparative Labour Law and Industrial Relations2025https://doi.org/10.54648/ijcl2025016article
AJG 1ABDC B
Weight
0.50

What the paper says

Anti-poaching and wage-fixing agreements in labour markets represent a significant, yet largely unaddressed, antitrust concern in India. This paper argues that the Competition Commission of India (CCI) possesses both the legislative mandate under the Competition Act, 2002, and a compelling jurisprudential basis to proactively investigate and penalise such collusive practices. Drawing on a comparative analysis of enforcement trends in jurisdictions like the US, EU, and Canada, and a doctrinal review of Indian contract and competition law, this paper contends that the CCI’s current reluctance to engage with these issues, often deferring them to employment law, is a critical lacuna. It demonstrates that existing provisions, particularly section 3 of the Competition Act, are sufficient to address these anti-competitive agreements. The paper concludes by offering specific policy and enforcement recommendations for the CCI, urging a shift towards robust scrutiny to safeguard labour mobility, to ensure fair wages, and promote overall economic efficiency in India’s rapidly evolving labour markets.

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https://doi.org/https://doi.org/10.54648/ijcl2025016

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@article{adhip2025,
  title        = {{Comparative Analysis and Legality of Anti-poaching Agreements in the Indian Context}},
  author       = {Adhip Narayan Banerjee & Maryam Ishrat Beg},
  journal      = {The International Journal of Comparative Labour Law and Industrial Relations},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.54648/ijcl2025016},
}

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Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.