ECONOMIC ANALYSIS OF ALGORITHMIC COLLUSION AND SELFPREFERENCING IN DIGITAL MARKETS: COMPETITION CHALLENGES AND REGULATORY RESPONSES

The global digital markets are stimulating traditional market competition frameworks. This is with respect to the algorithmic systems empowering innovative methods of coordination andexclusion in the digital markets. The present research is an attempt to inspects the economic aspect underlying the same. Numerous studies reveals that algorithmic pricing system are selfreliant in achieving coordinated results. Evidences from global enforcement cases have shown the use of selfpreferencing practices through gametheory. The current Google Shoppingdecision, RealPage investigation, by the U.S. Department of Justices and the Competition Commission of Indias ongoing AmazonFlipkart investigation reveals selfpreferencing practices as a threat to consumer surplus. This paper attempts to throws light on the trials faced by the oldschool competition law frameworks. Moreover, this research explores about competitive injury upon selfreinforcing market dynamics. Besides, with Indias Draft Digital Competition Bill 2024 offering expected global trends, this research delves to evaluate hybrid amalgamation with traditional execution of algorithmic pricing. At the end the study concludes the need of constructive policy, enabling disclosure abilities and calibrating the legal standards which protects novelty in rapidly emerging digital economies.

Recommended Citation

Dr. Shweta Mohan & Jai Singh (2026) "ECONOMIC ANALYSIS OF ALGORITHMIC COLLUSION AND SELFPREFERENCING IN DIGITAL MARKETS: COMPETITION CHALLENGES AND REGULATORY RESPONSES", GNLU Journal of Law And Economics : Volume VIII 2025, Issue II
Available at: https://gnlu.ac.in/GJLE/Publications/ECONOMIC ANALYSIS OF ALGORITHMIC COLLUSION AND SELFPREFERENCING IN DIGITAL MARKETS: COMPETITION CHALLENGES AND REGULATORY RESPONSES