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A novel Bass-type model for product life cycle quantification using aggregate market data

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  • Guo, Xuezhen

Abstract

Product Life Cycle (PLC) is a widely accepted concept that has been given significant attention in operations management and marketing literature. However, its quantification remains a major challenge. This study aims to develop a unique and original analytical model for quantifying PLCs using aggregate market data. The Bass diffusion model is used to forecast consumers׳ first purchases of the product. Next, the Novelty–Loyalty Based Consumer Utility (NLBCU) theory, which has a confirmed neuropsychological basis, is used to model repeat (or replacement) purchases. The unique contribution of this work is that it synthesizes the prevailing innovation diffusion theory and the NLBCU theory to provide a distinct, dynamic and endogenous perspective on consumer purchasing behavior across the entire PLC. The model׳s advantages include its simple mathematical formulation, its minimal use of data and its harmony with the predominating ideas of the innovation diffusion literature. Through simulation studies and empirical investigations, the descriptive power and data-fitting performance of the model are demonstrated.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:proeco:v:158:y:2014:i:c:p:208-216
    DOI: 10.1016/j.ijpe.2014.07.018
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    1. John A. Norton & Frank M. Bass, 1987. "A Diffusion Theory Model of Adoption and Substitution for Successive Generations of High-Technology Products," Management Science, INFORMS, vol. 33(9), pages 1069-1086, September.
    2. M. Berk Ataman & Carl F. Mela & Harald J. van Heerde, 2008. "Building Brands," Marketing Science, INFORMS, vol. 27(6), pages 1036-1054, 11-12.
    3. Manel Baucells & Rakesh K. Sarin, 2010. "Predicting Utility Under Satiation and Habit Formation," Management Science, INFORMS, vol. 56(2), pages 286-301, February.
    4. Qin, Ruwen & Nembhard, David A., 2012. "Demand modeling of stochastic product diffusion over the life cycle," International Journal of Production Economics, Elsevier, vol. 137(2), pages 201-210.
    5. Hyman, Michael R., 1988. "The timeliness problem in the application of bass-type new product-growth models to durable sales forecasting," Journal of Business Research, Elsevier, vol. 16(1), pages 31-47, January.
    6. Thomassey, Sébastien, 2010. "Sales forecasts in clothing industry: The key success factor of the supply chain management," International Journal of Production Economics, Elsevier, vol. 128(2), pages 470-483, December.
    7. Frank M. Bass, 2004. "A New Product Growth for Model Consumer Durables," Management Science, INFORMS, vol. 50(12_supple), pages 1825-1832, December.
    8. Klepper, Steven, 1996. "Entry, Exit, Growth, and Innovation over the Product Life Cycle," American Economic Review, American Economic Association, vol. 86(3), pages 562-583, June.
    9. Faison, Edmund W J, 1977. "The Neglected Variety Drive: A Useful Concept for Consumer Behavior," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 4(3), pages 172-175, December.
    10. Becker, Gary S, 1992. "Habits, Addictions, and Traditions," Kyklos, Wiley Blackwell, vol. 45(3), pages 327-345.
    11. Chien, Chen-Fu & Chen, Yun-Ju & Peng, Jin-Tang, 2010. "Manufacturing intelligence for semiconductor demand forecast based on technology diffusion and product life cycle," International Journal of Production Economics, Elsevier, vol. 128(2), pages 496-509, December.
    12. Vijay Mahajan & Eitan Muller & Roger A. Kerin, 1984. "Introduction Strategy for New Products with Positive and Negative Word-of-Mouth," Management Science, INFORMS, vol. 30(12), pages 1389-1404, December.
    13. Menon, Satya & Kahn, Barbara E, 1995. "The Impact of Context on Variety Seeking in Product Choices," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 22(3), pages 285-295, December.
    14. Amini, Mehdi & Wakolbinger, Tina & Racer, Michael & Nejad, Mohammad G., 2012. "Alternative supply chain production–sales policies for new product diffusion: An agent-based modeling and simulation approach," European Journal of Operational Research, Elsevier, vol. 216(2), pages 301-311.
    15. Michael Kosfeld & Markus Heinrichs & Paul J. Zak & Urs Fischbacher & Ernst Fehr, 2005. "Oxytocin increases trust in humans," Nature, Nature, vol. 435(7042), pages 673-676, June.
    16. Yan, Xiaoming & Liu, Ke, 2009. "Optimal control problems for a new product with word-of-mouth," International Journal of Production Economics, Elsevier, vol. 119(2), pages 402-414, June.
    17. Read, Daniel & Loewenstein, George & Rabin, Matthew, 1999. "Choice Bracketing," Journal of Risk and Uncertainty, Springer, vol. 19(1-3), pages 171-197, December.
    18. Polli, Rolando & Cook, Victor, 1969. "Validity of the Product Life Cycle," The Journal of Business, University of Chicago Press, vol. 42(4), pages 385-400, October.
    19. William E. Cox & Jr., 1967. "Product Life Cycles as Marketing Models," The Journal of Business, University of Chicago Press, vol. 40, pages 375-375.
    20. Gary S. Becker, 1992. "Habits, Addictions, and Traditions," Kyklos, Wiley Blackwell, vol. 45(3), pages 327-345, August.
    21. Bauer, Hans H. & Fischer, Marc, 2000. "Product life cycle patterns for pharmaceuticals and their impact on R&D profitability of late mover products," International Business Review, Elsevier, vol. 9(6), pages 703-725, December.
    22. Frank M. Bass, 1969. "A New Product Growth for Model Consumer Durables," Management Science, INFORMS, vol. 15(5), pages 215-227, January.
    23. Mark Uncles & Andrew Ehrenberg & Kathy Hammond, 1995. "Patterns of Buyer Behavior: Regularities, Models, and Extensions," Marketing Science, INFORMS, vol. 14(3_supplem), pages 71-78.
    24. Gary L. Lilien & Ambar G. Rao & Shlomo Kalish, 1981. "Bayesian Estimation and Control of Detailing Effort in a Repeat Purchase Diffusion Environment," Management Science, INFORMS, vol. 27(5), pages 493-506, May.
    25. Rink, David R. & Swan, John E., 1979. "Product life cycle research: A literature review," Journal of Business Research, Elsevier, vol. 7(3), pages 219-242, September.
    26. Muller, Eitan, 1983. "Trial/awareness advertising decisions : A control problem with phase diagrams with non-stationary boundaries," Journal of Economic Dynamics and Control, Elsevier, vol. 6(1), pages 333-350, September.
    27. Ambar G. Rao & Masataka Yamada, 1988. "Forecasting with a Repeat Purchase Diffusion Model," Management Science, INFORMS, vol. 34(6), pages 734-752, June.
    28. Joe A. Dodson, Jr. & Eitan Muller, 1978. "Models of New Product Diffusion Through Advertising and Word-of-Mouth," Management Science, INFORMS, vol. 24(15), pages 1568-1578, November.
    29. Frank M. Bass, 2004. "Comments on "A New Product Growth for Model Consumer Durables The Bass Model"," Management Science, INFORMS, vol. 50(12_supple), pages 1833-1840, December.
    30. Hirschman, Elizabeth C, 1980. "Innovativeness, Novelty Seeking, and Consumer Creativity," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 7(3), pages 283-295, December.
    31. Felipe Caro & Victor Martínez-de-Albéniz, 2012. "Product and Price Competition with Satiation Effects," Management Science, INFORMS, vol. 58(7), pages 1357-1373, July.
    32. Minhi Hahn & Sehoon Park & Lakshman Krishnamurthi & Andris A. Zoltners, 1994. "Analysis of New Product Diffusion Using a Four-Segment Trial-Repeat Model," Marketing Science, INFORMS, vol. 13(3), pages 224-247.
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    Cited by:

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    3. Duan, Hongbo & Zhang, Gupeng & Wang, Shouyang & Fan, Ying, 2018. "Peer interaction and learning: Cross-country diffusion of solar photovoltaic technology," Journal of Business Research, Elsevier, vol. 89(C), pages 57-66.
    4. Li, Xishu & Yin, Ying & Manrique, David Vergara & Bäck, Thomas, 2021. "Lifecycle forecast for consumer technology products with limited sales data," International Journal of Production Economics, Elsevier, vol. 239(C).
    5. Xiaoyu Li & Jiahong Yuan & Yan Shi & Tianteng Wang & Xiangpei Hu & Felix Tung Sun Chan & Junhu Ruan, 2020. "An extended Bass Model on consumer quantity of B2C commerce platforms," Electronic Commerce Research, Springer, vol. 20(3), pages 609-628, September.
    6. Chumnumpan, Pattarin & Shi, Xiaohui, 2019. "Understanding new products’ market performance using Google Trends," Australasian marketing journal, Elsevier, vol. 27(2), pages 91-103.
    7. Fan, Zhi-Ping & Che, Yu-Jie & Chen, Zhen-Yu, 2017. "Product sales forecasting using online reviews and historical sales data: A method combining the Bass model and sentiment analysis," Journal of Business Research, Elsevier, vol. 74(C), pages 90-100.
    8. Lee, Youseok & Kim, Sang-Hoon & Cha, Kyoung Cheon, 2021. "Impact of online information on the diffusion of movies: Focusing on cultural differences," Journal of Business Research, Elsevier, vol. 130(C), pages 603-609.
    9. Carlos Pablo Sigüenza & Bernhard Steubing & Arnold Tukker & Glenn A. Aguilar‐Hernández, 2021. "The environmental and material implications of circular transitions: A diffusion and product‐life‐cycle‐based modeling framework," Journal of Industrial Ecology, Yale University, vol. 25(3), pages 563-579, June.
    10. Dong, Ming & Mao, Shunjie & Li, Shan, 2023. "Supplier's technology upgrading investment strategy considering product life cycle," International Journal of Production Economics, Elsevier, vol. 263(C).

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