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Forecasting with a Repeat Purchase Diffusion Model

Author

Listed:
  • Ambar G. Rao

    (Graduate School of Business Administration, New York University, New York, New York 10006)

  • Masataka Yamada

    (Nagoya University of Commerce and Business Administration, Nagoya, Japan)

Abstract

A methodology for forecasting the sales of an ethical drug as a function of marketing effort before any sales data are available and for updating the forecast with a few periods of sales data is presented. Physicians' perceptions of the drug on a number of attributes, e.g. effectiveness, range of ailments for which appropriate, frequency of prescriptions, are used to estimate the parameters of a model originally proposed by Lilien, Rao and Kalish (Lilien, G. L., A. G. Rao, S. Kalish. 1981. Bayesian estimation and control of detailing effort in a repeat purchase diffusion environment. Management Sci. 27(May) 493--506.). This model conceptualizes the drug adoption process as a repeat purchase diffusion model; sales are expressed as a function of a drug's own and competitive marketing efforts and of word of mouth. The model is first validated in this paper via predictive testing on 19 drugs prescribed by three types of physicians. The forecasting methodology is illustrated using physicians' perceptions on these drugs. Forecasts obtained without any sales data, and updated forecasts using seven periods of sales data are presented, and are encouraging.

Suggested Citation

  • Ambar G. Rao & Masataka Yamada, 1988. "Forecasting with a Repeat Purchase Diffusion Model," Management Science, INFORMS, vol. 34(6), pages 734-752, June.
    • Handle: RePEc:inm:ormnsc:v:34:y:1988:i:6:p:734-752
    DOI: 10.1287/mnsc.34.6.734
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    Citations

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    Cited by:

    1. Nikolopoulos, Konstantinos & Buxton, Samantha & Khammash, Marwan & Stern, Philip, 2016. "Forecasting branded and generic pharmaceuticals," International Journal of Forecasting, Elsevier, vol. 32(2), pages 344-357.
    2. Kim, Namwoon & Srivastava, Rajendra K. & Han, Jin K., 2001. "Consumer decision-making in a multi-generational choice set context," Journal of Business Research, Elsevier, vol. 53(3), pages 123-136, September.
    3. M. Berk Ataman & Carl F. Mela & Harald J. van Heerde, 2008. "Building Brands," Marketing Science, INFORMS, vol. 27(6), pages 1036-1054, 11-12.
    4. Guo, Xuezhen, 2014. "A novel Bass-type model for product life cycle quantification using aggregate market data," International Journal of Production Economics, Elsevier, vol. 158(C), pages 208-216.
    5. Lee, Duk Hee & Park, Sang Yong & Kim, Jong Wook & Lee, Seong Kon, 2013. "Analysis on the feedback effect for the diffusion of innovative technologies focusing on the green car," Technological Forecasting and Social Change, Elsevier, vol. 80(3), pages 498-509.
    6. Soloviev, Vladimir, 2009. "Экономико-Математическое Моделирование Рынка Программного Обеспечения: Монография. — М.: Вега-Инфо, 2009. — 176 С [Economic and mathematical modelling of software market]," MPRA Paper 28974, University Library of Munich, Germany.
    7. Marc Fischer & Peter Leeflang & Peter Verhoef, 2010. "Drivers of peak sales for pharmaceutical brands," Quantitative Marketing and Economics (QME), Springer, vol. 8(4), pages 429-460, December.
    8. Ruiz-Conde, Enar & Wieringa, Jaap E. & Leeflang, Peter S.H., 2014. "Competitive diffusion of new prescription drugs: The role of pharmaceutical marketing investment," Technological Forecasting and Social Change, Elsevier, vol. 88(C), pages 49-63.
    9. Aslan Lotfi & Zhengrui Jiang & Ali Lotfi & Dipak C. Jain, 2023. "Estimating Life Cycle Sales of Technology Products with Frequent Repeat Purchases: A Fractional Calculus-Based Approach," Information Systems Research, INFORMS, vol. 34(2), pages 409-422, June.
    10. Ataman, B.M., 2007. "Managing brands," Other publications TiSEM 462dcbba-2ac1-46d1-a61c-f, Tilburg University, School of Economics and Management.
    11. Min Ding & Jehoshua Eliashberg, 2008. "A Dynamic Competitive Forecasting Model Incorporating Dyadic Decision Making," Management Science, INFORMS, vol. 54(4), pages 820-834, April.
    12. Kremer, Sara T.M. & Bijmolt, Tammo H.A. & Leeflang, Peter S.H. & Wieringa, Jaap E., 2008. "Generalizations on the effectiveness of pharmaceutical promotional expenditures," International Journal of Research in Marketing, Elsevier, vol. 25(4), pages 234-246.
    13. Lee, Hakyeon & Kim, Sang Gook & Park, Hyun-woo & Kang, Pilsung, 2014. "Pre-launch new product demand forecasting using the Bass model: A statistical and machine learning-based approach," Technological Forecasting and Social Change, Elsevier, vol. 86(C), pages 49-64.
    14. Chul-Yong Lee & Sung-Yoon Huh, 2017. "Technology Forecasting Using a Diffusion Model Incorporating Replacement Purchases," Sustainability, MDPI, vol. 9(6), pages 1-14, June.

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