Dynamic pricing strategies for efficient inventory management with auto-correlative stochastic demand forecasting using exponential smoothing method

Lalji Kumar · Kajal Sharma · Uttam Kumar Khedlekar

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Supply Chain and Inventory Management Consumer Market Behavior and Pricing Forecasting Techniques and Applications

Abstract

The research presents a novel approach to inventory modelling, emphasizing stochastic demand and dynamic pricing strategies for a seasonal sales framework. The methodology divides the sales season into intervals, each associated with distinct pricing strategies influenced by stochastic factors. The study employ exponential smoothing for demand forecasting, optimizing inventory replenishment and dynamic pricing strategies through developed algorithms. Notably, the study determine the optimal smoothing parameter for demand forecasting, balancing responsiveness to recent demand patterns with long-term stability. Proposed research achieves a comprehensive framework empowering businesses to enhance competitiveness and profitability by addressing challenges of stochastic demand and dynamic pricing. Dynamic pricing strategies outperformed classical strategies, allowing businesses to respond promptly to demand fluctuations and optimize profit margins during sales seasons. Incorporating stochastic demand models enabled organizations to implement safety stock and buffer inventory levels effectively, mitigating risks associated with uncertain demand patterns. Real-time data analysis was crucial for adjusting price dynamics and making effective management decisions, leading to improved financial performance. The iterative nature of dynamic pricing strategies emphasized the importance of continuous refinement to adapt to evolving market dynamics. This approach enables data-driven decisions, adaptation to market fluctuations, and improved inventory management despite unpredictable demand. Ultimately, this study provides valuable insights and methodologies applicable across industries for efficient and profitable inventory management.

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References

2000The M3-Competition: results, conclusions and implications 1994Optimal Dynamic Pricing of Inventories with Stochastic Demand over Finite Horizons 2004Revenue Management Under a General Discrete Choice Model of Consumer Behavior 2000The impact of exponential smoothing forecasts on the bullwhip effect 1985Forecasting Trends in Time Series 2003A new approach to forecasting intermittent demand for service parts inventories 2008On the Structure of Lost-Sales Inventory Models 2022Energy demand forecasting in China: A support vector regression-compositional data second exponential smoothing model

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