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Tags: Algorithmic Collusion, SelfPreferencing, Digital Markets, Game Theory, Competition Policy, Platform Economics, Regulatory Frameworks

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

  • By Dr. Shweta Mohan & Jai Singh
  • 13 Days ago
  • Downloads: 4

  • View: 24

Volume VIII 2025 Issue II GNLU Journal of Law And Economics

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

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Editorial Note

THE CURRENCY OF DELAY: A POLITICAL ECONOMY ANALYSIS OF JUDICIAL INCENTIVES IN INDIAN HIGH COURTS

In 2023, the Delhi High Court disposed of more than 87,000 cases, a recordbreaking figure. Yet its backlog grew. Across India, governments have doubled judicial strength in some states, built stateoftheart ecourts, and implemented case management software. Still, over 5.1 crore cases remain pending. The standard explanation treats this as a resource problem: too few judges chasing too many litigants. But what if the real answer is more uncomfortable What if delay is not a bug in the system, but a feature, a currency that judges spend, save, and strategically deploy This paper advances a heretical proposition: that for the Indian High Court judge, disposing of cases is not always the rational choice. In a system where the government is simultaneously the largest litigant and the arbiter of judicial careers, where a controversial judgment can trigger a punitive transfer while a safe adjournment goes unnoticed, and where forty dismissals at the admission stage count the same as one laboriously reasoned final verdict, delay emerges as the equilibrium strategy. The crisis of pending cases is not an accident of overload; it is the predictable outcome of incentives working exactly as designed. Employing a political economy framework, we model the High Court judge as a strategic actor maximizing a utility function comprised of reputation (professional prestige), leisure (workload aversion), promotion prospects (chances of elevation or postretirement appointment), and the cost of dissent (risk of punitive transfer or career backlash). The paper proposes an empirical model to test whether judicial delays correlate with political cycles and the identity of the litigant (State vs. Citizen), suggesting that strategic delay is a rational response to the institutional constraints of the Indian judiciary.

  • Tathagat Sharma
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