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This study optimizes free sample diffusion using a two-stage model for dynamic markets. Repeat purchases positively impact sampling levels, while external/internal factors negatively influence them.

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Area of Science:

  • Marketing Science
  • Operations Research

Background:

  • Optimizing free sample diffusion is crucial for market penetration.
  • Dynamic market conditions and product characteristics influence diffusion effectiveness.

Purpose of the Study:

  • To develop an optimization model for free sample diffusion effects.
  • To present a two-stage method for determining optimal sampling levels.
  • To analyze the impact of key factors on sampling levels in dynamic markets.

Main Methods:

  • Developed an optimization model for diffusion effects.
  • Implemented a two-stage method to determine sampling levels.
  • Utilized logistic and regression analysis for global sensitivity analysis.

Main Results:

  • Increased external or internal coefficients negatively impact sampling levels.
  • Market change rate has no significant influence; repeat purchases positively influence sampling levels.
  • Sensitivity analysis provides a method to estimate parameter impacts and construct confidence intervals.

Conclusions:

  • The study offers a robust framework for optimizing free sample strategies.
  • Provides practical steps for improving parameter estimation accuracy.
  • Introduces an innovative approach to sampling level estimation in dynamic markets.