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Analysis of Sampling on the Diffusion of Complementary Product under Dynamic Market Potential

  • Bing Han
  • Wei Lu
  • Zhineng Hu
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 241)

Abstract

This paper develops an optimization model group for the diffusion effects of free sampling products presented to complementary products under dynamic changes in potential market based on the characteristics of the complementary product. The simulation analysis shows that sampling has a positive role in promoting the diffusion of complementary product but it can not affect the final cumulative adopters of the complementary product. The sampling effect of dynamic changes in potential market is superior to the static potential market’s. The cumulative adopters of the complementary product decreases with the increase of the changing rate of the potential market, and the NPV increases firstly and then decreases gradually with the increasing of the changing rate of the amount potential market. In the case of limited production capacity of sampling products, both main product and complementary product appear continuous sampling. Finally, the influencial factors between main products and complementary products have a positive role in promoting the product diffusion.

Keywords

Complementary products Product sampling Dynamic potential market Product diffusion 

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References

  1. 1.
    Bass FM (1969) A new product growth model for consumer durables. Management Science 15(5):215–227Google Scholar
  2. 2.
    Peterson RA, Mahajan V (1978) Multi-product growth models. In: Shedth J (ed.). Research in Marketing. JAI press, Greenwitch 201–231Google Scholar
  3. 3.
    van den Ende J, Jaspers F, Gervin D (2008) Involvement of system firms in the development of complementary products: The influence of novelty. Technovation 28(11):726–738Google Scholar
  4. 4.
    Wei J, Zhao J, Li Y (2013) Pricing decisions for complementary products with firms’ different Market powers. European Journal of Operational Research 224(3):507–519Google Scholar
  5. 5.
    Zhou J (2003) Exploration about strategy of complementary goods. Journal of Yunnan University of Finance and Economics 19(4):85–87Google Scholar
  6. 6.
    Lammers BH (1991) The effect of free samples on the immediate consumer purchase. Consumer Marketing 8(2):31–37Google Scholar
  7. 7.
    Heiman HB, Mcwilliams B, Shen Z (2001) Learning and forgetting: Modeling optimal product sampling over time. Management Science 47(4):532–546Google Scholar
  8. 8.
    Jain DC, Mahajan V, Muller E (1995) An approach for determining optimal product sampling for the diffusion of a new product. Journal of Product Innovation Management 12(2):124–135Google Scholar
  9. 9.
    Hu Z, Li B (2013) Impact of sampling on the diffusion of independent product. Systems Engineering-Theory & Practice 33(5):1192–1199 (In Chinese)Google Scholar
  10. 10.
    Hu Z (2005) Analysis of product sampling for innovation product diffusion. Systems Engineering-Theory & Practice (3):97–100Google Scholar
  11. 11.
    Hu Z (2006) Incorporating price in optimal product sampling for diffusion. International Journal of Management Science and Engineering Management 1(2):119–136Google Scholar
  12. 12.
    Mahajan V, Muller E, Bass FM (1990) New product diffusion models in marketing: A review and directions for research. Journal of Marketing 54(1):1–26Google Scholar
  13. 13.
    Mahajan V, Peterson RA (1978) Innovation diffusion in a dynamic potential adopter population. Management Science 24(15):1589–1597Google Scholar
  14. 14.
    Sharif MN, Ramanathan K (1981) Binomial innovation diffusion models with dynamic potential adopter population. Technological Forecasting and Social Change 20(1):63–87Google Scholar
  15. 15.
    Guseo R, Guidolin M (2009) Modelling a dynamic market potential: A class of automata networks for diffusion of innovations. Technological Forecasting & Social Change 76(6):806–820Google Scholar
  16. 16.
    Guseo R, Guidolin M (2011) Market potential dynamics and diffusion of innovation: Modeling synergy between two driving forces. Technological Forecasting & Social Change 78(1):13–24Google Scholar
  17. 17.
    Meade N, Islam T (2010) Using copulas to model repeat purchase behaviour-an exploratory analysis via a case study. European Journal of Operational Research 200(3):908–917Google Scholar
  18. 18.
    Sultan F, Farely JU, Lehmann DR (1990) A meta-analysis of applications of diffusion models. Journal of Marketing Research 27(1):70–77Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  1. 1.Uncertainty Decision-Making LaboratorySichuan UniversityChengduPeople’s Republic of China

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