Which Decision Model Should I Use When Choosing to Adopt a New Technology?

This post outlines 8 models (or frameworks) that have helped people decide whether or not to adopt new technologies. (Note: most of these frameworks were developed by academics in the fields of information technology and marketing.)

You will be happy you read this post if you:

• need to choose a technology for your business to adopt.
• you are a teacher and you are trying to figure out which teaching method (technology) to use.
• you are a tech nerd and read blogposts for fun.

Personally, I don’t believe that there will ever be a perfect model to predict human behavior.   So I tried to pick more-simple models to share here.  The more simple the model, the more generalizable it is.  The more complex the model, the more potential it has for not being useful (if it doesn’t exactly describe your situation).

My advice: First, know your audience. Then, pick a model that works for you.

 

1. Social-Cognitive Theory

This is perhaps the most basic model.  The process of  technology adoption looks something like this:  “Wow! A new thing! I’d better watch others model how to use it…okay, I get it.  I will now do that thing.”  (Also see: Social Learning Theory.)

Bandura, A (1977). “Self-efficacy: Toward a Unifying Theory of Behavioral Change” (PDF). Psychological Review. 84 (2): 191–215.

 

2. The Technology Acceptance Model (TAM)

Simply put, if you want someone to do something, they need to believe two things: 1) they need to believe that it’s actually useful, and 2) that it won’t be a major pain to use.  Designers should keep the following questions in mind whenever they require adopting new technology:

1. Perceived usefulness—Is the new behavior (facilitated by the new technology) genuinely useful? If it is useful, how will the learner know that?
2. Ease of use—Is the new behavior easy to use? If it’s not easy to use, is there anything that can be done to help that?

Davis, F.D. 1989. “Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology.” MIS Quarterly 13(3): 319-340.

 

3. Task-Technology Fit

If the characteristics of a given task is aligned with the given technology, we will perform better at the task and we will use the technology more frequently.

Goodhue,Dale L.; Thompson,Ronald L., “Task-technology fit and individual performance”, MIS Quarterly, 1995, 19, 2, 213-236.

 

4. Theory of Reasoned Action (TRA)

People adopt new technology based on two basic factors: personal interests (attitudes toward behavior) and social influence (subjective norm).

http://edutechwiki.unige.ch/en/Theory_of_reasoned_action
Ajzen, I., Fishbein, M., 1980. Understanding attitudes and predicting social behavior. Prentice-Hall, Englewood Cliffs, NJ.

 

5. Theory of Planned Behavior

Essentially, 1) if you think adopting a certain technology is a good idea, and 2) others around you think it’s a good idea, and 3) you feel comfortable using it, you will adopt that technology.

Ajzen, Icek (1991). “The theory of planned behavior”. Organizational Behavior and Human Decision Processes. 50 (2): 179–211.

 

6. Disruptive Innovation

This isn’t an adoption model per se.  Rather, it is a theory, which states that if a company invests solely in retaining current customers, without keeping an eye on emerging markets and growing needs, they will be disrupted by up-and-coming competitors (and become obsolete).

I include this one as a caution when choosing to invest in a technology—before investing, make sure the vendors demonstrate that they are flexible and forward thinking.  E.g., they have a significant R&D budget, they send their people to conferences, it’s part of their culture business statements, etc.

Christensen, Clayton M. (15 December 2015). “The Innovator’s Dilemma: When New Technologies Cause Great Firms to Fail”. Harvard Business Review Press. Retrieved 19 January 2018 – via Google Books.

 

7. Diffusions of Innovation Theory

There are 5 perceived attributes that affect whether a user adopts or rejects an innovation:

1. Relative advantage —The degree to which an innovation is perceived as being better than the idea it supersedes.
2. Compatibility—The degree to which an innovation is perceived to be consistent with the existing values, past experiences, and needs of the potential adopters.
3. Complexity—The degree to which an innovation is perceived as difficult to use.
4. Observability—The degree to which the results of an innovation are visible to others.
5. Trailability—The opportunity to experiment with the innovation on a limited basis. (Rogers, 2003)

Rogers, Everett M. 2003. Diffusion of Innovations (5th edition). Glencoe: Free Press.
Additionally, here’s a 3rd edition PDF for your reading pleasure.

 

8. Technology Readiness Index (Tri)

This model takes many of the previous theories and mashes it up into one, complex, multiple-item algorithm to measure readiness to embrace new technologies.  Only look into this one if you are super serious about understanding all the factors that go into technology adoption.

Parasuraman, A.: Technology readiness index (TRI): a multiple-item scale to measure readiness to embrace new technologies. Journal of Service Research 2(4), 307–320 (2000)

PDF