A time delay model for the diffusion of a new technology

Technological Advancement and the Evolving Gender Identities: A Focus on the Level of Female Economic Participation in Sub-Saharan Africa

“…It is important to state that the lag component of these variables was used in the econometric estimation because of the time lag that technology requires to diffuse (see Wang et al, 2006;Fanelli & Maddalena, 2012) To strengthen the causal interpretations of the result and to reduce biases that may arise from variable omissions, the study controls for trade liberalization, per capita income, foreign direct investment and extent of democracy. Following arguments from the literature, the degree of trade liberalization and the remaining three control variables are expected to have a significant impact on female economic participation (Pampel & Tanaka, 1986;Gaddis &Peters, 2012;Abe et al, 2016).…”

How the Innovation Diffusion Models from the Past can Help us to Explain Marketing in the New Media Era

“…Starting from several empirical studies, Rogers detects features and mechanisms typical of the diffusion process and points out different steps through which the innovation decision process develops: knowledge, persuasion, decision, implementation and confirmation. The gap between awareness and adoption persists in recent papers, such as in Fanelli and Maddalena (2012), who use a delayed equation to analyze at the aggregate level, without addressing the decision rationale behind it. In this process the features of the decision maker (socio-economic characteristics, personality variables and communication behavior) are important and affect the choice between adoption or rejection.…”

Hopf bifurcation analysis in a multiple delayed innovation diffusion model with Holling II functional response

“…[29][30][31][32][33] A time delay model for the diffusion of new technology has also been proposed by Fanelli and Maddalena. 34 Wang et al 32 have developed the model with the time delay to consider the evaluation stage. They have reviewed the aspect of delay in their studies to describe the process of evaluation and decision making, but Shukla et al explained that the innovation diffusion process is affected by variable external influences such as advertisements as well as change of density of nonadopters population due to intrinsic growth rate, emigration or death rate, etc.…”