The Bass Model and Its Implications on Adoption Models in Industry

This report delves into the Bass Diffusion Model, a framework for understanding how new products are adopted by a population. Developed by Frank Bass, the model describes the interaction between potential users and is widely used for forecasting. The report explores the model's core principles, including the coefficients of external and internal influence, and its applications in product and technological forecasting. It further examines the limitations of the Bass Model, such as success bias, and how the model has influenced the development of other adoption models, like the Technology Adoption Model and the Theory of Reasoned Action. The report highlights the model's usefulness in various industries, including retail and manufacturing, and its role in predicting user behavior and facilitating innovation. The conclusion emphasizes the model's contribution to long-term forecasting and its value to businesses introducing new products or related offerings.

Development and adoption
models and their uses in
industry

TABLE OF CONTENTS
INTRODUCTION...........................................................................................................................3
MAIN BODY...................................................................................................................................3
Introduction to the Bass Model....................................................................................................3
Implication of the diffusion model on the other models and their usage.....................................4
CONCLUSION................................................................................................................................5
REFERENCES................................................................................................................................7

INTRODUCTION
The Bass Model which is also known as the Bass Diffusion Model mainly describes the
process pertaining to how the new products are being adopted in the population. And this mainly
involves the differential equation. This model is useful in determining or presenting the rationale
in regard to how the current and the potential adopters interact. This research report is
emphasized on grabbing an understanding on the development of the adoption model and their
usefulness in respect to after the proposition of the Bass Model 1960s.
MAIN BODY
Introduction to the Bass Model
This model was developed by the Frank Bass and defines a procedure in terms of
describing how the new products are being adopted in respect to the interaction between the
potential users. This is the most famous generalization in the field of marketing and the Dirichlet
model which is in respect to the repeat buying and the choice of brand. Frank proposed this in
the paper named “A new product growth model for consumer durables" in the year 1969. Bass
made some contribution in the field of describing the various stages of the product adoption
which has resulted into contributing some mathematical concepts to the idea (Ntwoku, Negash
and Meso, 2017). This model is being widely used by the businesses in terms of forecasting and
mostly importantly in relation to the product and technological forecasting. This model is has
been having a greater impact over the marketing and the management science.
As per this model, the probability of the adopters of the new product in respect to the
time, t, it has been given that the new product has not been adopted and this mainly depends
upon the two forces (Fan, Che, and Chen, 2017). The first force, represents the coefficient p,
which depicts the adoption because of the mass media called as the coefficient of the external
influence. The second force is the presented as the q, which highlights that it is positively
influenced by the earlier adopter's. This is now terms as the coefficient of internal influence.
In terms of the application of the Bass model and the other model based upon this model,
especially in the context of the forecasting, it is important to effectively take into account certain
limitation (Lobitaña, 2020). The first and foremost limitation of such model is that it stats how
the successful innovation have diffused the population but fails to account for their chances of
success. Therefore, it will result into gathering such data which will result into predicting the
favourable or desirable forecasts in regard to the innovation or the new product (Abu, Khaidi and

Muhammad, 2020). This causes success bias in the final outcome of the forecasting. In order to
overcome this limitation, the organizations can consider the probability of the failure. Another
drawback is that the Bass model can estimate its parameters from the data by making certain
observation pertaining to the actual sales. But, till this time, the organization has already made
investment related decisions.
Implication of the diffusion model on the other models and their usage
This model has resulted into making modification in the other models in terms of
variables and assumption along with the usefulness. There has been a rapid growth in the online
social networks or any other virtual communities which has resulted into increase in the need for
the usage of the Bass Diffusion model. This is used for estimating the size and growth rate
pertaining to these social networks (Bertotti, Brunner and Modanese, 2016).
Illustration 1: Representation of the Bass Diffusion Model

The technical adoption model which was proposed by Fred D Davis in the 1989 is widely
useful in the field of technology adoption. The major strength and usage of this model is that its
simplicity as it has only two components which are perceived usefulness and the perceived ease
of use. This two is useful in predicting the extent of adoption of the new technology or the
innovation at the individual level. This model is a well-established, powerful model which is
used for predicting the user acceptance.
Another adoption model is theory of Reasoned Action developed in the year 1975, which
is build on the 3 general constructs which is behavioural intention, subjective norms and attitude.
This model is useful in determining how the individuals will behave based on the existing
attitude and behaviour. The core purpose of this is to gain an understanding about the
individual's behaviour through the way of analysing the basic motivation behind their actions.
This model is useful in all the industry in respect to brining innovation to the market. It is based
on certain assumptions which cannot be ignored. It is useful in industries like, retail,
manufacturing sector, service industries and so forth, which are willing to bring new product into
the market or bringing in innovation. This model provides assistance to the organizations in
respect to undergoing forecasting in terms of whether product will be adopted by the users based
on their attitude and behaviour.

Therefore, in this way, after the proposition of the Bass Diffusion Model has
resulted into bringing new models and theories which are there has been a complete change in
the way innovative product or the technology is being studied in terms of its impact over the
potential users in adopting the same. There has been greater development and modification in the
previous models on the basis of the Bass Model in order to effectively meet with the business
requirement.
CONCLUSION
It can be inferred from the above that the Bass model offers a conceptually attractive and
the mathematically elegant framework which will help in explaining how the product diffusion
to the target population. This is mainly useful in regard to the long term forecasting along with
the adoption of the innovation. These forecasts are not only crucial for the business entities
which are introducing the innovation, like, Apple's introduction of iPod, but also for the entities
who are willing to introduce the similar or the related products into the market like speaker
makers etc. Over the past few years changes have been made on the assumptions of the original
Bass model which has resulted into getting a rich framework for new product adoption. But the
most important advantage of the model is pertaining to the forecasting the diffusion of the focal
products through the way of utilizing the parameters of the diffusion procedure in respect to the
analogous products. Thus, there has been great and valuable changes in the models of adoption
after the proposition of Bass Model 1960s which has resulted into getting more valuable
outcome.

REFERENCES
Books and Journals
Abu, N., Khaidi, S. M. and Muhammad, N., 2020. New tourism product forecasting–application
of Bass Diffusion Model and Grey Forecasting Model. Data Analytics and Applied
Mathematics (DAAM). 1(01). pp.37-43.
Bertotti, M. L., Brunner, J. and Modanese, G., 2016. The Bass diffusion model on networks with
correlations and inhomogeneous advertising. Chaos, Solitons & Fractals. 90. pp.55-63.
Fan, Z. P., Che, Y. J. and Chen, Z. Y., 2017. Product sales forecasting using online reviews and
historical sales data: A method combining the Bass model and sentiment
analysis. Journal of Business Research. 74. pp.90-100.
Lobitaña, J. M., 2020. Characterization of Mining Behaviour of Selected Metals in the
Philippines Through a Bass Diffusion Model. Journal of Higher Education Research
Disciplines. 5(1).
Ntwoku, H., Negash, S. and Meso, P., 2017. ICT adoption in Cameroon SME: application of
Bass diffusion model. Information Technology for Development. 23(2). pp.296-317.