Diffusion is a popular theory of communication used in marketing to model the first-purchase sales growth of a new product over time. As Mahajan et al (1990) put it diffusion theory suggests that a new product is first adapted by a few innovators who, in turn, influence others to adopt it. Taking this perspective on diffusion we can clearly see the pivotal role which interpersonal communication (word of mouth) between adopters and nonadopters plays in accounting for the rapid growth stage found in the diffusion process. It is important to remember that the value of diffusion modeling is not just restricted to historical data; rather leading academics in this field like Bass have made predictions based on early sales data which have resulted in successful predictions of diffusions before those products reached their peak. From a commercial perspective there are endless examples of diffusion processes, which will be elaborated on later, including: the diffusion of blockbuster movies; mobile phones and other analogous products. For the purposes of this assessment we will discuss the principal theories in this field playing particular attention to Bass and its variants, we will then apply these theories to the practical example of VCR diffusion.
[...] The hypothesis was tested by examining the relationship between the coefficient of imitation (the q effect) and the time of introduction of an innovation (the p effect). The findings confirm the hypothesis. This study suggests to us that that the product life cycles of consumer durable products like TV's and washing machines is becoming shorter in the market place because of the increasing change in the number of new technologies being developed. Takada and Jain (1988) in Mahajan et al (1986) wanted to test the hypothesis that cultural differences among countries will lead to different diffusion patterns. The diffusion model used was Bass. [...]
[...] A look at the Bass model: Report structure 1. What is new product diffusion 2. An overview of the Bass model 3. Using analogues products in diffusion modeling 4. The assumptions and limitations of the Bass model 5. The technical description of the Bass model 6. A look at the estimation procedures used 6.1 Ordinary least squared estimation 2. Non linear squared estimation 6. [...]
[...] The various estimation procedures For the Bass model, there are various estimation procedures available for use, all of which are designed to produce estimates for q and m. Considering the four that are available; NLS (Non Linear Least Squares Estimation) OLS (Ordinary Least Squares Estimation) MLE (Maximum Likelihood Estimation) AE (Algebraic Estimation) . It is useful to determine which is the best to use, both in terms of the Bass model and other diffusion models. Which to use? To determine this, it is important to identify how does the predictive performance of the estimation procedures vary across the various diffusion models. [...]
[...] It can be written as: DN / dt = q/m N Where n = N0 Its point of inflection occurs at = (Mahajan, Mason & Srinivsan 1990) 7.2 The Gompertz model Like the Mansfield model the Gompertz model also assumes that the diffusion of an innovative product occurs only by imitation. Again the innovative variable is ignored in the model. However unlike the Mansfield model the Gompertz model has a fixed point of inflection estimated at around 30% of total possible adopters. The model states that a decrease in the imitation effect slows down the overall diffusion process. [...]
[...] (Mahajan et al 1986) Benefits of the Gompertz model & the model itself It is asymmetric not symmetric like the bass model ~ a variety of shaped curves can be got from the model It is easier to use and manipulate then other diffusion models~ it can be easily fitted Like the Mansfield model it has only two parameters to solve ~ q and dN / dt = qN [ln m ln Its point of inflection occurs at 1/q ln (ln N0) (Mahajan, Mason & Srinivsan 1990) Note: It can be said that for both the Mansfield and the Gompertz model that the non linear estimation procedure generally provides better predictions than the other estimation techniques available Uses of Diffusion models When we think of diffusion models we usually hold close associations of the model with sales forecasting. In fact this approach is taken by our look at the bass model. Mahajan et al. (1986) acknowledge that many firms use diffusion models for forecasting the demand of a new product. They go on to say that if the firm is willing to share their experiences of the diffusion process, that industry users can learn from these experiences. However sales forecasting isn't the only use that companies can gain from using diffusion models. Mahajan et al. [...]
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