Competitive product ranking algorithms and digital market laws

Dipankar Das ()
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Dipankar Das: Goa Institute of Management

Computational Management Science, 2025, vol. 22, issue 2, No 2, 28 pages

Abstract: Abstract The ranking algorithm used by digital platforms plays a critical role in shaping competition among vendors, and recent concerns about collusive practices in product listings have prompted regulatory responses worldwide. Upcoming digital market laws will impose strict regulations to maintain fair competition. This article covers the upcoming Digital Market Act in India and the European Union. The current article presents an algorithm that aims to uphold fair competition as mandated by various countries’ "Digital Market Laws" and to optimize the platform’s revenue. The proposed algorithm employs a Bayesian approach to information updating and two-stage assortment optimization techniques to create a fair and competitive digital marketplace. The product ranking or assortment planning model is designed to maximize expected revenue without bias. The study finds that collusive or unfair ranking practices may increase the likelihood of purchasing a product but fail to maximize expected revenue in some cases. In contrast, the proposed assortment planning method maintains competitiveness while maximizing expected revenue. If the platform uses this algorithm, then that will maintain the new digital market laws, amplifying reliability, resulting in more customers visiting the website/platform. The cost of acquiring new sellers in the marketplace will be reduced. Academic research will have some questions to start a new research horizon in the presence of digital market laws, so managerial decisions can be made accordingly.

Keywords: Search algorithm; Assortment planning; Assortment optimization; E-commerce; Bayesian statistics; Information theory (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/s10287-025-00537-2

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