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ISSN Approved Journal No: 2320-2882 | Impact factor: 7.97 | ESTD Year: 2013
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Paper Title
DEMAND FORECASTING FOR E-COMMERCE PLATFORMS IN INDIA USING TIME SERIES MODELS
Authors
Shatabdi Mandal, Dr. Pradip Chourasia
Keywords
ARIMA, TBATS, Artificial Neural Network (AR-NN), Time Series Forecasting, E-commerce Demand, Inventory Optimization, Indian Market, Predictive Analytics, Machine Learning in Retail, Supply Chain Forecasting, Seasonal Demand Prediction, Consumer Behavior Analysis, Retail Sales Forecasting, Data-Driven Decision Making, Demand Planning, E-commerce Logistics, AI in Demand Forecasting, Business Intelligence in Retail, Sales Trend Analysis, Deep Learning for Demand Estimation.
Abstract
The Indian e-commerce sector has witnessed rapid expansion with the advent of digital marketplaces, leading to challenges in demand forecasting and inventory management. This study aims to predict product demand using time series models such as ARIMA, TBATS, and Autoregressive Neural Networks (AR-NN). Historical sales data from Indian e-commerce platforms is analyzed to identify trends, seasonal variations, and demand fluctuations. The models are evaluated based on Root Mean Square Error (RMSE) to determine their forecasting accuracy. The results indicate that ARIMA performs best for stable seasonal patterns, TBATS for irregular trends, and AR-NN for non-linear demand fluctuations. This research provides valuable insights for Indian e-commerce businesses to optimize inventory management, enhance supply chain efficiency, and improve overall customer satisfaction.
IJCRT's Publication Details
Unique Identification Number - IJCRT2502494
Paper ID - 277503
Page Number(s) - e201-e205
Pubished in - Volume 13 | Issue 2 | February 2025
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Publisher Name - IJCRT | www.ijcrt.org | ISSN : 2320-2882
E-ISSN Number - 2320-2882
Cite this article
Shatabdi Mandal, Dr. Pradip Chourasia, "DEMAND FORECASTING FOR E-COMMERCE PLATFORMS IN INDIA USING TIME SERIES MODELS", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.13, Issue 2, pp.e201-e205, February 2025, Available at :http://www.ijcrt.org/papers/IJCRT2502494.pdf
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Volume 14 | Issue 3
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Submit Manuscript Online Impact Factor: 7.97 Review Results : Within 02-03 Days Paper Publication : Within 02-03 Days
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ISSN: 2320-2882 Impact Factor: 7.97 and ISSN APPROVED Journal Starting Year (ESTD) : 2013
ISSN and 7.97 Impact Factor Details
ISSN: 2320-2882 Impact Factor: 7.97 and ISSN APPROVED Journal Starting Year (ESTD) : 2013
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