Application of the Bass diffusion model for estimating the lifecycle of a retail store

  • Jairo R Coronado Hernández
  • Alfonso R Romero-Conrado
  • Carlos Uribe-Martes
  • Ricardo R. Calderón-Pérez
Keywords: Diffusion model, business Lifecycle, Bass, estimation

Abstract

This article presents a practical application of Lifecycle estimation using the Bass Diffusion Model in the case of a retail store. The results from the application of the model show that the probability that a person will buy driven by advertising is 5%, whereas the probability of buying based on the recommendation of another customer is 23%. According to the sales Lifecycle results, the store’s monthly sales have stabilized and its market share is near its peak.

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References

J. Morrison, “Lyfe-Cycle Approach to new Product Forecasting,” J. Bus. Forecast. Methods Syst., vol. 14, no. 2, pp. 3–5, 1995.

N. Meade and T. Islam, “Modelling and forecasting the diffusion of innovation - A 25-year review,” International Journal of Forecasting Twenty five years of forecasting, vol. 22, no. 3. pp. 519–545, 2006.

R. Scitovski and M. Meler, “Solving parameter estimation problem in new product diffusion models,” Appl. Math. Comput., vol. 127, no. 1, pp. 45–63, 2002.https://doi.org/10.1016/S0096-3003(00)00164-8

J. R. Coronado-Hernández, J. P. García-Sabater, J. P. Maheut, and J. J. Garcia-Sabater, “Modelo de optimización estocástica para la planificación de cadenas de suministro para productos con ciclo de vida cortos,” in 4th International Conference On Industrial Engineering and Industrial Management, 2010.

J. R. Coronado-Hernández, “Análisis del efecto de algunos factores de complejidad e incertidumbre en el rendimiento de las Cadenas de Suministro. Propuesta de una herramienta de valoración basada en simulación.,” Universitat Politècnica de València, Valencia (Spain), 2016. https://doi.org/10.4995/Thesis/10251/61467

A. R. Romero-Conrado, “Algoritmo heurístico basado en listas tabú para la planificación de la producción en sistemas multinivel con listas de materiales alternativas y entornos de coproducción,” Universidad de la Costa, 2018.

Z. L. Chen, S. Li, and D. Tirupati, “A scenario-based stochastic programming approach for technology and capacity planning,” Comput. Oper. Res., vol. 29, no. 7, pp. 781–806, 2002. https://doi.org/10.1016/S0305-0548(00)00076-9

E. M. Rogers, “Social Structure and Social Change,” Am. Behav. Sci., vol. 14, no. 5, pp. 767–782, 1971.

https://doi.org/10.1177/000276427101400508

F. Bass, “A New Product Growth for Model Consumer Durables,” Manage. Sci., vol. 15, no. 5, pp. 215–227,

https://doi.org/10.1287/mnsc.15.5.215

V. Mahajan, E. Muller, and F. Bass, “Diffusion of New Products: Empirical Generalizations and Managerial Uses,” Mark. Sci., vol. 14, no. 3, pp. 79–88, 1995. https://doi.org/10.1287/mksc.14.3.G79

E. M. Rogers and T. F. Press, Diffusion of Innovations. New York, 1983.

C. V Trappey and H. Y. Wu, “An evaluation of the time-varying extended logistic, simple logistic, and Gompertz models for forecasting short product life cycles,” Adv. Eng. Informatics, vol. 22, no. 4, pp. 421–430, 2008.

https://doi.org/10.1016/j.aei.2008.05.007

M. Lawrence, P. Goodwin, M. O’Connor, and D. Ínkal, “Judgmental forecasting: A review of progress over

the last 25áyears,” International Journal of Forecasting Twenty five years of forecasting, vol. 22, no. 3. pp.

– 518, 2006.

V. Mahajan and S. Sharma, “A simple algebraic estimation procedure for innovation diffusion models

of new product acceptance,” Technol. Forecast. Soc. Change, vol. 30, no. 4, pp. 331–345, 1986. https://doi.org/10.1016/0040-1625(86)90031-4

V. Srinivasan and C. H. Mason, Nonlinear least squares estimation of the Bass diffusion model of new product

acceptance. Graduate School of Business, Stanford University, 1984.

Rd. C. Team, “R: A language and environment for statistical computing,” ISBN 3-900051-07-0. R Foundation

for Statistical Computing. Vienna, Austria, 2013. http://www.R-project.org

M. Valero-Herrero, J. P. Garcia-Sabater, J. R. Coronado-Hernandez, and J. P. Maheut, “Planteamiento dinámico del problema de secuenciación en líneas de montaje con mezcla de modelos,” in XV Congreso de Ingeniería de

Organización // 5th International Conference on Industrial Engineering and Industrial Management, 2011, pp. 288–296.

A. R. Romero-Conrado, L. J. Castro-Bolaño, J. R. Montoya-Torres, and M. Á. Jiménez Barros, “Operations research as a decision-making tool in the health sector: A state of the art,” DYNA, vol. 84, no. 201, p. 129, May 2017.

C. Saavedra Sueldo, S. Urrutia, D. Paravié, C. Rohvein, y G. Corres, Una propuesta metodológica para la determinación de capacidades estratégicas en pymes industriales, INGE CUC, vol. 10, n.º 2, pp. 43 - 50, dic. 2014.

C. Ayala, Desarrollo de Estrategias de Responsabilidad Social Universitaria, Módulo Arquitectura CUC, vol. 13, no. 1, pp. 67-86, jul. 2014.

Published
2018-12-13
How to Cite
Coronado Hernández, J., Romero-Conrado, A., Uribe-Martes, C., & Calderón-Pérez, R. (2018). Application of the Bass diffusion model for estimating the lifecycle of a retail store. IJMSOR: International Journal of Management Science & Operation Research, 3(1), 5-10. Retrieved from https://ijmsoridi.com/index.php/ijmsor/article/view/88