Advancing Oligopoly Pricing Predictions through Machine Learning within the Indian Telecommunication Industry
Year: 2025
Type: preprint
Abstract: This paper looks at how machine learning can be used to predict revenue in the Indian telecommunication industry, which is mainly controlled by Reliance Jio, Bharti Airtel and Vodafone Idea.Quarterly data on subscriber numbers and average revenue per user was collected from company reports.Three models were tested: Linear Regression, Decision Tree Regression and Random Forest Regression.The data was divided into a training set and a test set using a 70 to 30 ratio.Model accuracy was measured using Mean Squared Error and Mean Absolute Error.The results showed that Random Forest gave the best predictions, followed by Decision Tree and then Linear Regression.The study shows that machine learning can help companies make better pricing and planning decisions in a competitive market.It also suggests that future research could use more advanced models and include outside factors like government policies or economic changes to improve predictions further.
DOI: 10.58445/rars.3120
Authors: Kartik Nayak, Vitri Lukito
Institution: Mentor
Language: English
Field: Decision Sciences
Domain: Social Sciences
Open Access status: gold
OpenAlex ID: W4414582220
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