SDE based Generalized Innovation Diffusion Modeling Article Swipe
Shakshi Singhal
,
Adarsh Anand
,
Ompal Singh
·
YOU?
·
· 2019
· Open Access
·
· DOI: https://doi.org/10.33889//ijmems.2019.4.3-055
YOU?
·
· 2019
· Open Access
·
· DOI: https://doi.org/10.33889//ijmems.2019.4.3-055
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.
Related Topics
Concepts
Randomness
Computer science
Innovation diffusion
Function (biology)
Diffusion
Product (mathematics)
Diffusion process
Process (computing)
Econometrics
Convolution (computer science)
Industrial engineering
Mathematics
Machine learning
Statistics
Engineering
Knowledge management
Thermodynamics
Artificial neural network
Operating system
Evolutionary biology
Biology
Geometry
Physics
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.33889//ijmems.2019.4.3-055
- https://doi.org/10.33889//ijmems.2019.4.3-055
- OA Status
- gold
- Cited By
- 11
- References
- 28
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W2938188832
All OpenAlex metadata
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https://openalex.org/W2938188832Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.33889//ijmems.2019.4.3-055Digital Object Identifier
- Title
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SDE based Generalized Innovation Diffusion ModelingWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2019Year of publication
- Publication date
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2019-04-16Full publication date if available
- Authors
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Shakshi Singhal, Adarsh Anand, Ompal SinghList of authors in order
- Landing page
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https://doi.org/10.33889//ijmems.2019.4.3-055Publisher landing page
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https://doi.org/10.33889//ijmems.2019.4.3-055Direct link to full text PDF
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YesWhether a free full text is available
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goldOpen access status per OpenAlex
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https://doi.org/10.33889//ijmems.2019.4.3-055Direct OA link when available
- Concepts
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Randomness, Computer science, Innovation diffusion, Function (biology), Diffusion, Product (mathematics), Diffusion process, Process (computing), Econometrics, Convolution (computer science), Industrial engineering, Mathematics, Machine learning, Statistics, Engineering, Knowledge management, Thermodynamics, Artificial neural network, Operating system, Evolutionary biology, Biology, Geometry, PhysicsTop concepts (fields/topics) attached by OpenAlex
- Cited by
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11Total citation count in OpenAlex
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2025: 2, 2023: 2, 2022: 2, 2020: 4, 2019: 1Per-year citation counts (last 5 years)
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28Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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| referenced_works | https://openalex.org/W2921430796, https://openalex.org/W2922364470, https://openalex.org/W1985342427, https://openalex.org/W2561627359, https://openalex.org/W2922339835, https://openalex.org/W2761713604, https://openalex.org/W2921643684, https://openalex.org/W4253543067, https://openalex.org/W2152725266, https://openalex.org/W2254222832, https://openalex.org/W2058858771, https://openalex.org/W2071691476, https://openalex.org/W2146066560, https://openalex.org/W2003748346, https://openalex.org/W2107140526, https://openalex.org/W2035393693, https://openalex.org/W2070349457, https://openalex.org/W2524088233, https://openalex.org/W1987802766, https://openalex.org/W1972542337, https://openalex.org/W2621199810, https://openalex.org/W2141436719, https://openalex.org/W2106718163, https://openalex.org/W2913149273, https://openalex.org/W2106616952, https://openalex.org/W2036338131, https://openalex.org/W2756726018, https://openalex.org/W2130067743 |
| referenced_works_count | 28 |
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| corresponding_author_ids | https://openalex.org/A5090148679 |
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| corresponding_institution_ids | https://openalex.org/I110166357 |
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