A simulation-based product diffusion forecasting method using geometric Brownian motion and spline interpolation

This study addresses the problem of stochasticity in forecasting diffusion of a new product with scarce historical data. Demand uncertainties are calibrated using a geometric Brownian motion (GBM) process. The spline interpolation (SI) method and curve fitting process have been utilized to obtain pa...

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Autores principales:	Najmeh Madadi, Azanizawati Ma’aram, Kuan Yew Wong
Formato:	article
Lenguaje:	EN
Publicado:	Taylor & Francis Group 2017
Materias:	demand forecast stochastic differential equation simulation uncertainties gbm interpolation Business HF5001-6182 Management. Industrial management HD28-70
Acceso en línea:	https://doaj.org/article/aca087f279bf4789be4943cdbc09f782
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spelling	oai:doaj.org-article:aca087f279bf4789be4943cdbc09f7822021-12-02T14:35:46ZA simulation-based product diffusion forecasting method using geometric Brownian motion and spline interpolation2331-197510.1080/23311975.2017.1300992https://doaj.org/article/aca087f279bf4789be4943cdbc09f7822017-01-01T00:00:00Zhttp://dx.doi.org/10.1080/23311975.2017.1300992https://doaj.org/toc/2331-1975This study addresses the problem of stochasticity in forecasting diffusion of a new product with scarce historical data. Demand uncertainties are calibrated using a geometric Brownian motion (GBM) process. The spline interpolation (SI) method and curve fitting process have been utilized to obtain parameters of the constructed GBM-based differential equation over the product’s life cycle (PLC). The constructed stochastic differential equation is coded as the forecast model and is simulated using MATLAB. The results are several sample demand paths generated from simulation of the forecast model. To evaluate the forecasting performance of the proposed method it is compared with Holt’s model, using actual data from the semiconductor industry. The comparison results confirm the applicability of the proposed method in the semiconductor industry. The method can be helpful for policy-makers who require the prediction of uncertain demand over a time horizon, such as decisions associated with aggregate production planning, capacity planning, and supply chain network design. Especially for the semiconductor industry with intensive capital investment the proposed approach can be useful for making decisions associated with capacity allocation and expansion.Najmeh MadadiAzanizawati Ma’aramKuan Yew WongTaylor & Francis Grouparticledemand forecaststochastic differential equationsimulationuncertaintiesgbminterpolationBusinessHF5001-6182Management. Industrial managementHD28-70ENCogent Business & Management, Vol 4, Iss 1 (2017)
institution	DOAJ
collection	DOAJ
language	EN
topic	demand forecast stochastic differential equation simulation uncertainties gbm interpolation Business HF5001-6182 Management. Industrial management HD28-70
spellingShingle	demand forecast stochastic differential equation simulation uncertainties gbm interpolation Business HF5001-6182 Management. Industrial management HD28-70 Najmeh Madadi Azanizawati Ma’aram Kuan Yew Wong A simulation-based product diffusion forecasting method using geometric Brownian motion and spline interpolation
description	This study addresses the problem of stochasticity in forecasting diffusion of a new product with scarce historical data. Demand uncertainties are calibrated using a geometric Brownian motion (GBM) process. The spline interpolation (SI) method and curve fitting process have been utilized to obtain parameters of the constructed GBM-based differential equation over the product’s life cycle (PLC). The constructed stochastic differential equation is coded as the forecast model and is simulated using MATLAB. The results are several sample demand paths generated from simulation of the forecast model. To evaluate the forecasting performance of the proposed method it is compared with Holt’s model, using actual data from the semiconductor industry. The comparison results confirm the applicability of the proposed method in the semiconductor industry. The method can be helpful for policy-makers who require the prediction of uncertain demand over a time horizon, such as decisions associated with aggregate production planning, capacity planning, and supply chain network design. Especially for the semiconductor industry with intensive capital investment the proposed approach can be useful for making decisions associated with capacity allocation and expansion.
format	article
author	Najmeh Madadi Azanizawati Ma’aram Kuan Yew Wong
author_facet	Najmeh Madadi Azanizawati Ma’aram Kuan Yew Wong
author_sort	Najmeh Madadi
title	A simulation-based product diffusion forecasting method using geometric Brownian motion and spline interpolation
title_short	A simulation-based product diffusion forecasting method using geometric Brownian motion and spline interpolation
title_full	A simulation-based product diffusion forecasting method using geometric Brownian motion and spline interpolation
title_fullStr	A simulation-based product diffusion forecasting method using geometric Brownian motion and spline interpolation
title_full_unstemmed	A simulation-based product diffusion forecasting method using geometric Brownian motion and spline interpolation
title_sort	simulation-based product diffusion forecasting method using geometric brownian motion and spline interpolation
publisher	Taylor & Francis Group
publishDate	2017
url	https://doaj.org/article/aca087f279bf4789be4943cdbc09f782
work_keys_str_mv	AT najmehmadadi asimulationbasedproductdiffusionforecastingmethodusinggeometricbrownianmotionandsplineinterpolation AT azanizawatimaaram asimulationbasedproductdiffusionforecastingmethodusinggeometricbrownianmotionandsplineinterpolation AT kuanyewwong asimulationbasedproductdiffusionforecastingmethodusinggeometricbrownianmotionandsplineinterpolation AT najmehmadadi simulationbasedproductdiffusionforecastingmethodusinggeometricbrownianmotionandsplineinterpolation AT azanizawatimaaram simulationbasedproductdiffusionforecastingmethodusinggeometricbrownianmotionandsplineinterpolation AT kuanyewwong simulationbasedproductdiffusionforecastingmethodusinggeometricbrownianmotionandsplineinterpolation
_version_	1718391092015005696

A simulation-based product diffusion forecasting method using geometric Brownian motion and spline interpolation

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