Dynamic Pricing Strategy for Imitative and Habit‐Forming Customers

Abstract

This study employs finite‐horizon dynamic programming to examine markets with imitative and habit‐forming (IH) customers. Our findings indicate that optimal pricing and base demand increase as the number of customers who exhibit imitative and habit‐forming behaviors grows. Additionally, we analyze the impact of various stochastic parameters on optimal pricing, revealing that retailers should reduce prices when the variability among IH customers increases and raise prices when the average number of such customers rises. Notably, we challenge the conventional belief that greater uncertainty reduces profits, demonstrating that higher additive variability among IH customers can unexpectedly enhance profitability. These findings offer valuable insights for retailers into optimal pricing strategies for markets with imitative and habit‐forming customers, potentially aiding businesses in achieving growth and profitability.