Researchers at the Goa Institute of Management (GIM) have developed a two-stage competitive assortment algorithm designed to make digital marketplaces fairer and more transparent for both sellers and consumers. Published in the journal Computational Management Science, the algorithm tackles critical challenges that currently undermine e-commerce platforms, including biased ranking systems that favour revenue, manipulated customer reviews, platform self-preferencing, and opaque search results that hide genuine sellers and mislead buyers.
The new approach models the competitive dynamics between vendors and the platform itself to counter collusive ranking behaviour. By integrating review credibility and price efficiency, it ensures fairer product visibility. According to simulation results, this design not only improves fairness but also achieves significantly higher revenue compared to models that rely solely on quality or price. Importantly, the algorithm aligns with regulatory demands for transparency and equal market access, making platforms more resistant to collusion.
Among its key features are filters that highlight products with credible reviews and competitive pricing, aligning digital marketplaces with global antitrust trends, including those emerging in India and the European Union. This model strengthens customer trust, lowers seller acquisition costs, and supports sustained profitability. For platform architects, it offers a practical framework to redesign ranking engines that balance commercial objectives with fairness, at a time of growing regulatory scrutiny over digital market practices.
Assistant Professor Dipankar Das of GIM noted the algorithm’s potential to reshape e-commerce search engines by giving equal visibility to non-sponsored vendors and presenting consumers with balanced price–quality choices. This two-stage method helps curb platform self-promotion and encourages healthy competition, ultimately helping to restore fairness in digital product rankings.