Rogers Innovation Adoption Model: Blockchain, IoT, Healthcare Report

This report examines the Rogers Innovation Adoption Model, a framework developed by Everett Rogers to understand how new ideas and products are accepted by users. The model outlines five stages: innovators, early adopters, early majority, late majority, and laggards. The report applies this model to various technological advancements, including blockchain, the Internet of Things (IoT), and healthcare innovations. It analyzes how each technology aligns with the different stages of the adoption cycle, highlighting the characteristics of users at each stage. For instance, blockchain is discussed in terms of its position in the cycle, with the report noting its evolution from innovators to early majority. The application of the model to IoT and healthcare innovations, such as e-appointment scheduling, is also explored, demonstrating how the model can be used to understand and predict user behavior. The report concludes by emphasizing the model's utility in providing insights into customer behavior and aiding in strategic decision-making for companies introducing new technologies. The report also includes a bibliography of relevant sources.

RUNNING HEAD: ROGERS INNOVATION ADOPTION MODEL 0
Rogers Innovation Adoption Model
Student’s Details-
SEPTEMBER 21, 2019

ROGERS INNOVATION ADOPTION MODEL 1
Rogers Innovation Adoption Model
Rogers Innovation model is regarded as the diffusion of innovation given by Everett Rogers to
determine the various stages in the process of acceptance of the innovation by the determined
users. The stages in the innovation cycle ultimately help in analyzing the success of the idea or
the product1. It can be said that this model is helpful in all kinds of technological advancements
whether it is blockchain, internet of things or advancements in healthcare. The evidences of the
application of innovation model on the types of technological advancement is discussed under
the following paths.
Rogers Innovation model suggest the five stages which identifies the five different types of users
of the product or the new idea. The first stage is the innovators which are considered as the group
of individuals or persons who will buy the product very first when the product is freshly
introduced in the market2. Further, there are early adopters who are similar to innovators. Early
adopters do not hesitate in investing the new products and they already have much knowledge of
the product due to the word of mouth strategy to be used by the organization. In the next stage of
Rogers Innovation theory suggest about the early majority people who are not willing to take risk
for sake of the new product3. Furthermore, Rogers model have described the late majority as the
people seek for a verifiable proof for the success of the innovative product before buying it. The
last stage in the innovation theory is the laggards. These people are the ones who do not accept
the innovation at all.
Further, it can be noted that the blockchain technology is the emerging technology which is in
the early majority stage when it entered in the innovation cycle in 2013. With respect to
acceptance of technology innovators are 2,5%, early adopters are 13,5%, early majority 34%,
late majority 34% and laggards 16%4. Thus, it can be said that the innovation model describes
the cycles of the technology acceptance. When the blockchain reaches the innovators stage, it
1 Mohammad Mehdi Mohammadi, Roghayeh Poursaberi and Mohammad Reza Salahshoor ‘Evaluating the
adoption of evidence-based practice using Rogers’s diffusion of innovation theory: a model testing study’ (2018)
8(1) Health Promotion Perspectives 25, 32
2 What Is Diffusion of Innovation and Why Is It Important in 2019, The Street ( 11 December 2018) <
https://www.thestreet.com/technology/what-is-diffusion-of-innovation-14804157>.
3 B. Desmarchelier & E.S. Fang ‘National culture and innovation diffusion. Exploratory insights from agent-based
modeling’ 2016 105 Technological Forecasting and Social Change 121,128

ROGERS INNOVATION ADOPTION MODEL 2
seeks to determine the triggering technology and when it reaches the early adopters, it leads to
trough of disillusionment. As the blockchain technology has reached the early majority stage it
has scope of enlightenment and it has a plateau of majority when it reaches the late majority
stage5. Thus, these were the evidences of the acceptance of the blockchain technology.
Apart from this, if the innovation model is applied in the Internet of Things which is the popular
technology in today’s world. This technology is expected to be in the early majority as almost
every person is aware about the technological development. This technology is prevalent in
every area and is in the mind of the people. But in some circumstances people who fall in the
category of laggards and late majority who may not accept the technology because of the
traditional lifestyle and they are highly hesitant to accept the technology6. Theses people wait for
the downfall in the prices of the technology that is to be brought up by Internet of Things. Thus,
it can be said that the innovation model is applicable to Internet of things technology.
Moreover, technological innovations in the healthcare sector such as the e-appointment
scheduling software and the e-health innovations are the technological developments in various
regions of Australia. The adoption rate of these kind of innovation increased from 1.5% to 4% in
29 months7. Late majority stage of Roger’s Innovation model is prevalent in the healthcare
technological advancement due to the lack of internet literacy or lack of computer education of
the patient and staff members in the healthcare clinics who hesitate of accepting the
technological advancement.
To conclude, it can be said that the Roger’s Innovation model gives the required information
about the nature and the type of the customer exist in the acceptance of the innovation being
introduced by the company. Thus, it is not wrong to say that Roger’s Innovation model is useful
for all types of technological advancements as it can be applied in every kind of situation and
4 Application of the diffusion of innovation theory to Blockchain technology, Tozex (21 August 2018) <
https://medium.com/tozex/application-of-the-diffusion-of-innovation-theory-to-blockchain-technology-
b4d9535507fa>.
5 S. Pashaeypoor, T. Ashtray, M. Rassouli, & H. Alavi-Majd ‘Predicting the adoption of evidence-based practice using
Rogers diffusion of innovation model’ (2016) 52(1) Contemporary nurse 85, 94
6 Abhimanyu Roy, Ali M.S. Zalzala and Alok Kumar ‘Disruption of Things: A Model to Facilitate Adoption of IoT-
based Innovations by the Urban Poor’ (2016) 159 Procedia Engineering 199, 209
7 Xiaojun, Zhang, Ping Yu, Jun Yan and Ir Ton Am Spil ‘Using diffusion of innovation theory to understand the factors
impacting patient acceptance and use of consumer e-health innovations: a case study in a primary care clinic’
(2015) 15(1) BMC Health Service Research 71

ROGERS INNOVATION ADOPTION MODEL 3
useful for getting the insights of the data. The model is prevalent and have due importance in the
technological developments that are being done in the form of blockchain, Internet of Things and
healthcare systems. Thus, the model gives an opportunity to deal with every kind of customer of
the introduced technology and taking the right action in every stage.

ROGERS INNOVATION ADOPTION MODEL 4
Bibliography
Mohammadi, Mohammad Mehdi, Roghayeh Poursaberi and Mohammad Reza Salahshoor
‘Evaluating the adoption of evidence-based practice using Rogers’s diffusion of innovation
theory: a model testing study’ (2018) 8(1) Health Promotion Perspectives 25, 32
What Is Diffusion of Innovation and Why Is It Important in 2019, The Street ( 11 December
2018) < https://www.thestreet.com/technology/what-is-diffusion-of-innovation-14804157>.
Desmarchelier B. & E.S. Fang ‘National culture and innovation diffusion. Exploratory insights
from agent-based modeling’ 2016 105 Technological Forecasting and Social Change 121,128
Application of the diffusion of innovation theory to Blockchain technology, Tozex (21 August
2018) < https://medium.com/tozex/application-of-the-diffusion-of-innovation-theory-to-
blockchain-technology-b4d9535507fa>.
Pashaeypoor, S, T. Ashtray, M. Rassouli, & H. Alavi-Majd ‘Predicting the adoption of evidence-
based practice using Rogers diffusion of innovation model’ (2016) 52(1) Contemporary nurse
85, 94
Roy, Abhimanyu Ali M.S. Zalzala and Alok Kumar ‘Disruption of Things: A Model to Facilitate
Adoption of IoT-based Innovations by the Urban Poor’ (2016) 159 Procedia Engineering 199,
209
Zhang, Xiaojun, Ping Yu, Jun Yan and Ir Ton Am Spil ‘Using diffusion of innovation theory to
understand the factors impacting patient acceptance and use of consumer e-health innovations: a
case study in a primary care clinic’ (2015) 15(1) BMC Health Service Research 71