Part of a series on Innovation Essentials
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change management adoption decision diffusion social-network early adopters knowledge-step perceived-attributes early majority adoption rate rejection resistance relative-advantage step laggards

The Big Picture…

Adoption occurs when an individual decides to use your innovation. And Rogers’ identified it as a five-step process: knowledge, persuasion, decision, implementation, and confirmation.

Can we influence the rate of adoption? Yes. Rogers’ identified five key parameters that do so. The perceived attributes of innovation, the adoption decision, network factors, such as the communication channels and the nature of the social system. Finally, we can impact the rate of adoption through the extent of the change agent’s efforts.

In this article, I update Rogers’ decision step to address the oft-forgotten innovation resistance. And include minimising resistance as a core approach to increase the rate of adoption.

In more authoritarian innovation decisions then, a practical approach to change management, such as Kotter’s eight steps, is an effective way.

What is adoption?

Innovation adoption is the act of individuals or organisations deciding to, and starting to, use an innovation.

getting a new idea adopted, even when is has obvious advantages, is difficult

Rogers (2003) Diffusion of Innovation

In this article, I explore two main topics. First, what does adoption mean for individuals and organisations? And secondly, can we speed up adoption; if so, how?

I look at adoption from the classic product view, as well as for platforms. Where platforms need two or more sides to adopt to be useful. Along the way, we’ll look at Rogers’ adoption curve and Rogers’ Innovation Adoption Decision Process. I’ll also enhance the adoption decision process to show where innovation resistance gets addressed.

Let’s get adopting!


In a moment we’ll watch a video that shows Rogers’ adoption curve in action. But first, I’ll introduce his curve – take a look at Figure 1.

Figure 1: Rogers’ Adoption Curve

So what does this curve tell us? It shows how many of your target market have adopted your innovation at any particular time. And it usefully breaks down adopters into 5 adopter types – innovators, early adopters, early and late majority, and laggards. You can see in Figure 1 that Rogers’ see 2.5% of your target market will be innovators – the first to adopt. Next, there are 13.5% who will be early adopters, 34% are in the early majority; and so on.

We can see this concept in action in the following video – where a dancing person is gradually joined by others.

Video 1: Adoption in action

At 40 seconds in the entrepreneur is starting to get some interest – being an innovator is lonely! But it’s not until 1 min 20-ish that he entices some innovator types to adopt. By 1 min 43, the entrepreneur has attracted his early adopters. 2 mins in the early majority are adopting. And it takes until 2 mins 50 for the late majority to start turning up. However, even at 3 mins 15 in, there are still some laggards not yet joining in.

Relationship with diffusion

There is a relationship between adoption and innovation diffusion. Diffusion is about spreading knowledge and adoption about using that knowledge:

Diffusion – is the process by which an innovation is communicated through certain channels over time among the members of a social system.

Adoption – getting a new idea adopted, even when is has obvious advantages, is difficult

Rogers (2003) – Diffusion of Innovation

Without diffusion, people will not know about an innovation, and so can not adopt. Without adoption, the efficiency of diffusion decreases – if people are not using, there is less incentive to tell other people about a particular innovation. However, not adopting does not necessarily stop diffusion. But resisting the innovation might.

It turns out that adopting an innovation is a five-step decision process.

Innovation Adoption Decision Process

As Rogers’ investigated diffusion and adoption, he built a model on how someone decides to adopt an innovation. He identified it as the 5-step process I show in Figure 2 (from “Diffusion of Innovation“).

Rogers' classic adoption decision process - adoption or rejection.
Figure 2: Rogers’ description of the Innovation Adoption Decision Process

I feel that innovation resistance should be reflected in this model, and shortly I’ll give my enhancement. But for now, let’s look at each of these five steps, in turn, starting with Knowledge.

1 – Knowledge

The first step kicks off after diffusion. That’s to say you’ve become aware of an innovation. Rogers would say you now have awareness knowledge. And perhaps you actively seek it out to solve a problem you have. Or you became passively aware of a magazine article, trade-fair, or observing someone in your social network using the innovation, etc.

knowledge occurs when an individual is exposed to an innovation’s existence and gains an understanding of how it functions

Rogers (2003) – Diffusion of Innovation

If the innovation is interesting enough to you then you want to find out more. Now you are seeking what Rogers’ calls know-how knowledge. You want to know how to use the innovation correctly. If you’re still interested, then you tend to enhance this know-how knowledge into know-why knowledge.

Armed with your new awareness, know-how and know-why knowledge, you might enter the next step: persuasion.

2 – Persuasion

If you are now actively investigating an innovation beyond the knowledge step, Rogers says you are in the persuasion step. You are gathering more information and forming favourable, or unfavourable, attitudes towards the innovation.

persuasion occurs when an individual forms a favourable or unfavourable attitude towards the innovation

Rogers (2003) – Diffusion of Innovation

Compared to the logic-based knowledge step, this persuasion step is more feeling-based. But, “the formation of a favourable or unfavourable attitude toward an innovation does not always lead directly or indirectly to an adoption” decision.

3 – Decision

You’ve gained your knowledge and have formed an attitude towards the innovation. Now you are in the decision step.

Will you decide to adopt – that is to say you choose that “full use of an innovation as the best course of action available”? Or will you reject it? (known as passive rejection).

But of course, it is not as simple as this! You might choose to adopt and then decide to reject. Rogers calls this active rejection (also known as a discontinuance). And we typically actively reject for two reasons. Firstly, we realise after some time that we don’t get the benefit we expected. We call this disenchantment discontinuance. Secondly, we may discover another, better innovation – a replacement discontinuance.

Similarly, we might initially reject an innovation, but later decide to adopt. due to some change in circumstances. Figure 3 captures this.

Figure 3: A more detailed view of the Decision stage

Links with modern theories

Let’s take the view that there is an adoption decision each time an innovation is going to be used. Or better still, let’s say when the innovation gets hired. Now we can think in terms of job-to-be-done theory. Where there is a”big” hire initially followed by repeated “little” hires. Now discontinuance resonates nicely. At each hire point, i.e. when the consumer needs to get the same job done again (get to work, eat, hang a picture, etc.) there is a potential discontinuance. The implication being we have to think more of the lifetime use (hiring) than our current sell and be done approach.

And I think, without too much of an imagination stretch, that initial rejection followed by adoption fits the disruptive innovation model. Where an innovation is ignored by the main class of adopters initially before it moves upwards.

However, I do believe one important concept is missing from this view of the decision step. We need to deal with resistance to innovation.

Resistance to innovation

Too often we forget – or worse, don’t even know we have to address – innovation resistance (which I explore in this article). We tend to take the view that innovation is a good thing, and so we only have to persuade actors to adopt. But this misses that adopters can, and often do, resist innovation. Worryingly:

  • “innovation resistance seems to be a normal, instinctive response of consumers” (Sheth and Ram, 1989)
  • customer resistance is usually one of the most significant risks to innovation (Heidenreich & Kraemer, 2015).

Luckily, we know from Ram’s “A Model Of Innovation Resistance” article that “adoption begins only after the initial resistance offered by the consumers is overcome”. As such, we can update our view of the decision step to that shown in Figure 4.

Figure 4: Innovation Resistance in the Innovation Decision Process

If we do decide to adopt and have overcome resistance, then it is time to implement.

4 – Implementation

In the implementation step, the adopter is starting to use the innovation. But they may still require assistance from change agents to reduce any remaining uncertainty.

It is also at this stage that reinvention may occur. Where a user modifies, or changes, a particular innovation as they adopt and implement it.

reinvention – the degree to which an innovation is changed or modified by a user in the process of its adoption and implementation

Rogers (2013) – Diffusion of Innovation

Reinvention is common in the software tools industry. Where, for example, a generic tool is implemented and then customised for a particular client. Say to fit with the clients’ processes (rather than the client adopting the tools standard process flow).

5 – Confirmation

Finally, the last step of the adoption decision process is where the user seeks confirmation about their decision to adopt.

So that’s the process. Let’s now consider if we can increase the rate at which adoption occurs.

Increasing the Rate of adoption

Rates of adoption are naturally increasing. Just look at Figure 5 (from this HBR article). And you see that while the telephone took 60 years to get to 80% adoption in US households, adoption of mobile/cell phone took a mere 14 years.

Figure 5: Increasing speed of adoption over the years

Rogers defines the rate of adoption as:

rate of adoption – the relative speed with which an innovation is adopted by members of a social system

Rogers (2003) – Diffusion of Innovation

And Rogers further identified five variables that affect the rate of innovation adoption. These are:

  1. Perceived attributes of innovation – relative advantage, compatibility, complexity, trialability, and observability
  2. Types of innovation-decision – optional, collective, authority
  3. Communication channels
  4. Nature of the social system
  5. The extent of change agent’s promotion efforts

In Figure 6 you can see how these are usually presented.

Figure 6: Classic view of the 5 variables affecting rate of innovation adoption

Again, though, this misses innovation resistance. So, let’s update Figure 6 with resistance, and re-arrange a little to get our enhanced view, to get Figure 7.

Figure 7: Variables that affect the rate of adoption of an innovation (including addressing innovation resistance)

Why have I re-arranged? For a couple of reasons. First, I feel the type of innovation-decision is more of a key driver than implied in the original. If the decision is authoritarian, for example, then change agents become key and other parameters less weight. And I like to bring minimising innovation resistance together with the perceived attributes of innovation.

Let’s look at each of these in turn, starting with the types of innovation decision.

Types of Innovation Decision

We tend to see the adoption decision as an individual choice – an optional innovation decision. Even if group dynamics play their part (peer pressure). But there are two other types of innovation-decision: collective and authority.

Figure 8: Types of Innovation Decision

A collective innovation-decision is where the social network together chooses to adopt an innovation. We can see such choices as consensus taking. Sometimes this consensus approach creates new social networks forming around an innovation (Linux operating system, for example).

And an authority decision is one where either an external influence or someone in the group takes and enforces a decision to adopt. Legislation or regulatory decisions can drive these type of decisions. Though most often, it is organisations internally deciding to adopt. For example, a CFO deciding to implement a new finance system, that impacts everyone in the organisation.

Authoritarian decisions place a high emphasis on the efforts of change agents.

Perceived Attributes of Innovation

Rogers identifies there are five, what he called, perceived attributes of innovation that affect the rate of adoption. These are:

  • Relative advantage
  • Compatibility
  • Complexity
  • Trialability
  • Observability
Figure 9: Perceived attributes of Innovation

Let’s take a look into each of them.

Relative Advantage

How is this innovation better than the existing solution?

the degree to which an innovation is perceived as being better than the idea it supersedes

Rogers (2003) – Diffusion of Innovation

My modern, service-dominant, definition of innovation talks about how it needs to help the “beneficiary make progress, better than they can currently”. And Vogt (2013) talks about what “better” might be. There it is defined as adding in at least one of several sub-dimensions: economic profitability, low initial cost, savings in time and effort, the immediacy of reward, status, etc.

But as well as having a relative advantage, the innovation benefits from being compatible with what the beneficiary currently uses.


We all come with baggage. Experiences, knowledge, familiarity with our ways of working. An innovation that is compatible with what we do now will be adopted quicker than one that does not.

the degree to which an innovation is perceived as consistent with the existing values, past experiences, and needs of potential adopters

Rogers (2003) – Diffusion of Innovation

The classic example is why we use the QWERTY keyboard on computers. On typewriters, such a keyboard layout acts to slow down typists to minimise the letter hammers jamming. We don’t have this problem on computers, so no need to use a QWERTY layout. However, it was a shrewd move to. It is familiar. And, on introducing computers to the market, we have an already-available pool of people that can use them.

I think we can broaden this concept nowadays to leverage what beneficiaries are used to in other markets/industries. So not just a computer keyboard replacing a typewriter. But, for example, the use of QR codes from travel industry into finance applications.


The perceived attribute of complexity is fairly obvious. The more complicated something is, the steeper the learning curve. And therefore the harder it is to get people to adopt. So it is advantageous to minimise the complexity.

the degree to which an innovation is perceived as relatively difficult to understand and use

Rogers (2003) – Diffusion of Innovation

Complexity feeds into resistance as it increases the perceived risks of the innovation to the beneficiary. One approach to address complexity, if you can’t take it away, is trialability.


Allowing adopters to trial an innovation is a way to increase the speed of adoption. It lowers uncertainty and allows for learning by doing.

the degree to which an innovation may be experimented with on a limited basis

Rogers (2003) – Diffusion of Innovation

We are all familiar with this in marketing approaches. Free samples of goods, for example. Or freemium software (use a limited version of a service for free, pay for full functionality). Or charging monthly fees for a service instead of large upfront costs.

A downside could be that the adopters identify undesirable aspects of the innovation that outweigh advantages. However, if the innovator can react to address those findings, there are benefits all round.

And finally, the last perceived attribute is observability.


The easier it is for others to see the innovation in action (or that others are using it), the quicker it is likely to be adopted by others.

the degree to which the results of an innovation are visible to others

Rogers (2003) – Diffusion of Innovation

Apple’s iPod is an oft-quoted example here. Since it spent most of its time living in people’s pockets, it was hard for others to observe it was being used. Apple’s solution was to provide white coloured headphones. These were very uncommon at the time. But, even today, if you see someone going past with white headphones in their ears, you knew they are using an Apple product.

As well as traditionally addressing the above 5 attributes, we need to minimise resistance to innovation.

Minimising Innovation Resistance

As we’ve already seen, removing innovation resistance is the path to an adoption decision. But what does resistance mean? Well, it is a scale of postponement, rejection and objection. And I summarise the seven main reasons for resistance, and typically what type of resistance they lead to in Figure 10.

You can find the details in my article “Innovation Resistance“.

Figure 10: what typically causes the types of resistance in the innovation resistance hierarchy

In short, we need to minimise physical, economic, functional and social risks. Am I going to be harmed using the innovation? Is there a chance I can be financially out of pocket – remember the Betamax vs VHS wars? Electric cars are fantastic, but if I mainly drive long distance, then I currently have a functional risk. And remember the social risks associated with the first edition of Google Glass?

Secondly, we live comfortably in a set of traditions and norms. Most innovations are going to challenge those. The greater the difference, the higher the likelihood of push-back. Similarly, any innovation that goes against existing usage patterns, or that cannot support existing usage patterns will likely face challenges.

Finally, we all have perceived images of how things are and should be. Could Japanese companies make top-quality motorcycles when they first established in the US? The perceived image initially was no.

Next we have the promotion efforts of any change agents.

The extent of Change Agent’s promotion Efforts

The efforts of change agent are, I believe, different depending on the innovation-decision. So are the types of change agent.

Change agents efforts in an optional innovation-decision

If we take an optional innovation-decision, then the change agent is initially the innovator’s messaging to each adopter type. As time progresses, the change comes from peers that are adopting. This reflects Bass’ view that there are initially innovators followed by imitators. We might see certain people in the social network as critical drivers of change through their actions – influencers, you might say. Targetting them could help with innovation adoption.

Change agents efforts in a collective innovation-decision

A collective innovation-decision starts to move towards more formal change management needs. The group needs to identify why they need to make a change (adopt something new). It might be an existing group looking for something new. Or it might be that a new group emerges, driven by the need to find something. Either way, they need to legitimise their search, make a decision and action the change. Rogers and Shoemaker (1971) identified the approach as stimulation, initiation, legitimation, decision and action.

Change agents efforts in an authority innovation-decision

In an authority innovation-decision – such as one taken due to legal/regulatory decision or by a senior manager in an organisation – we move to the realm of formal change management.

Kotter’s 8 accelerators of change (you may have previously seen called 8 steps of change) is my recommended approach.

Figure 11: Kotter’s 8 accelerators of change

Last but not least are the fourth and fifth aspects, the communication channels and nature of the social system.

Communication channels & Nature of Social System

The rate of adoption is, unsurprisingly, related to the rate that knowledge of the innovation spreads. And that in turn relates to

to be related to two factors that relate to diffusion. First there are the communication channels in place including network topology (here); type of messaging (16% rule)

Figure 12: Communication Channels and the Nature of Social Systems

Wrapping Up


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