Modelling and forecasting the diffusion of innovation – A 25-year review

By Nigel Meade, Towhidul Islam. 2006

833 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Management Science and Operations Research

View Paper: https://www.semanticscholar.org/paper/774fe3b6929782d99d4383ce79490c16f2fbb101

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In Management Science and Operations Research

Citations in the corpus

A bibliometric review of the innovation adoption literature (2018, background): “In their review Meade and Islam (2006) suggest that future research should focus on forecasting new product diffusion with little or no data, forecasting with multinational models, and forecasting with multi-generation models [135].”
Agent-based simulation of innovation diffusion: a review (2011, background): “…their applications have been reviewed extensively over the past 30years (Mahajan and Muller 1979; Mahajan et al. 1990; Sultan et al. 1990; Parker 1994; Mahajan et al. 1995, 2000; Meade and Islam 2006), far less attention has been paid to the fast growing literature on agent-based diffusion models.”
Manufacturing intelligence for semiconductor demand forecast based on technology diffusion and product life cycle (2010, background): “Technology diffusion models are applied primarily to consumer durables (Meade and Islam, 2006), while little research has been done for semiconductor product demand forecast.”
Cross-country diffusion of photovoltaic systems: Modelling choices and forecasts for national adoption patterns (2010, methodology): “Consistently with most of the literature on statistical implementation of the Bass model (for a review see for instance Meade and Islam, 2006), in this work we will use a nonlinear least squares, NLS, approach (e.g. Levenberg-Marquardt, see Seber and Wild, 1989)) to estimate the model parameters:…”
Forecasting and operational research: a review (2008, methodology): “Many univariate alternatives (summarized in Meade and Islam, 2006) have been proposed, including the Gompertz curve (which has the same S-shaped form as the logistic), as well as Harvey’s (1984) and Meade’s (1985) contributions in JORS, all of which have shown comparative empirical success.”
Innovation diffusion and new product growth models: A critical review and research directions (2010, background): “…models Individual-level models Fully connected networks Partially connected and small-world networks Products Services Forecasting Managerial diagnostics (2000); Meade and Islam (2006); Hauser, Tellis and Griffin (2006); Chandrasekaran and Tellis (2007); and Krishnan and Suman (2009)).”
Modeling The Diffusion Of Residential Photovoltaic Systems In Italy: An Agent-based Simulation (2013, background): “For an overview, see for instance Mahajan et al. (2000) and Meade and Islam (2006).”
The impact of free-floating carsharing on car ownership: Early-stage findings from London (2017, neutral): “There is a well-established body of literature which documents that early adopters of innovative products/services have distinctive characteristics from lateradopting groups, traditionally termed the ‘early majority’, ‘late majority’ and ‘laggards’, cf. Rogers 1962, Robinson 1967, Mahajan et al. 199”
Dynamic Pricing and Learning: Historical Origins, Current Research, and New Directions (2013, neutral): “[83], Baptista [84], and Meade and Islam [85].”