SDE based Generalized Innovation Diffusion Modeling

Diffusion models are rigorously implemented in marketing research to predict the actual trend of innovations over time. These models can be classified in terms of deterministic and stochastic behavior. Deterministic models ignore the randomness in the adoption rate of an innovation that occurs due t...

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Main Authors: Shakshi Singhal, Adarsh Anand, Ompal Singh
Format: Article
Language:English
Published: International Journal of Mathematical, Engineering and Management Sciences 2019-06-01
Series:International Journal of Mathematical, Engineering and Management Sciences
Subjects:
Online Access:https://www.ijmems.in/assets/55-ijmems-ror13-vol.-4%2c-no.-3%2c-697%E2%80%93707%2c-2019.pdf
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spelling doaj-6a2bd8baad5b45d789ae608bb7a9bd182020-11-25T02:19:08ZengInternational Journal of Mathematical, Engineering and Management SciencesInternational Journal of Mathematical, Engineering and Management Sciences2455-77492455-77492019-06-014369770710.33889/IJMEMS.2019.4.3-055SDE based Generalized Innovation Diffusion ModelingShakshi Singhal0Adarsh Anand1Ompal Singh2Department of Operational Research, University of Delhi, Delhi-110007, IndiaDepartment of Operational Research, University of Delhi, Delhi-110007, IndiaDepartment of Operational Research, University of Delhi, Delhi-110007, IndiaDiffusion models are rigorously implemented in marketing research to predict the actual trend of innovations over time. These models can be classified in terms of deterministic and stochastic behavior. Deterministic models ignore the randomness in the adoption rate of an innovation that occurs due to environmental and internal system disturbances. Therefore, in the present research, a generalized stochastic diffusion model using Itô’s process is proposed that jointly study the product awareness and eventual adoption of an innovation. Convolution function is applied to integrate these two processes. In addition, different probability distributions are employed, which are relevant for describing the product awareness and adoption processes. Non-linear regression is further carried out to validate the proposed models and parameters are estimated based on the actual sales data from Smartphone and automobile industries. The forecasting results indicate that the proposed models perform empirically better than the already established diffusion models.https://www.ijmems.in/assets/55-ijmems-ror13-vol.-4%2c-no.-3%2c-697%E2%80%93707%2c-2019.pdfAwarenessConvolutionItô’s integralStochastic differential equationTechnology diffusion
collection DOAJ
language English
format Article
sources DOAJ
author Shakshi Singhal
Adarsh Anand
Ompal Singh
spellingShingle Shakshi Singhal
Adarsh Anand
Ompal Singh
SDE based Generalized Innovation Diffusion Modeling
International Journal of Mathematical, Engineering and Management Sciences
Awareness
Convolution
Itô’s integral
Stochastic differential equation
Technology diffusion
author_facet Shakshi Singhal
Adarsh Anand
Ompal Singh
author_sort Shakshi Singhal
title SDE based Generalized Innovation Diffusion Modeling
title_short SDE based Generalized Innovation Diffusion Modeling
title_full SDE based Generalized Innovation Diffusion Modeling
title_fullStr SDE based Generalized Innovation Diffusion Modeling
title_full_unstemmed SDE based Generalized Innovation Diffusion Modeling
title_sort sde based generalized innovation diffusion modeling
publisher International Journal of Mathematical, Engineering and Management Sciences
series International Journal of Mathematical, Engineering and Management Sciences
issn 2455-7749
2455-7749
publishDate 2019-06-01
description Diffusion models are rigorously implemented in marketing research to predict the actual trend of innovations over time. These models can be classified in terms of deterministic and stochastic behavior. Deterministic models ignore the randomness in the adoption rate of an innovation that occurs due to environmental and internal system disturbances. Therefore, in the present research, a generalized stochastic diffusion model using Itô’s process is proposed that jointly study the product awareness and eventual adoption of an innovation. Convolution function is applied to integrate these two processes. In addition, different probability distributions are employed, which are relevant for describing the product awareness and adoption processes. Non-linear regression is further carried out to validate the proposed models and parameters are estimated based on the actual sales data from Smartphone and automobile industries. The forecasting results indicate that the proposed models perform empirically better than the already established diffusion models.
topic Awareness
Convolution
Itô’s integral
Stochastic differential equation
Technology diffusion
url https://www.ijmems.in/assets/55-ijmems-ror13-vol.-4%2c-no.-3%2c-697%E2%80%93707%2c-2019.pdf
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AT ompalsingh sdebasedgeneralizedinnovationdiffusionmodeling
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