Technology Acceptance Model (TAM)
The Technology Acceptance Model (TAM) is a 12-question survey useful for predicting technology product adoption and usage frequency. Slightly modified, it can also be used to predict Likelihood-to-Recommend scores.
- Predicting Usage from Perceived Usefulness and Perceived Ease-of-Use
- Modified TAM (mTAM): Predicting Likelihood-to-Recommend from Usage Experience
- Applicability and limitations
Predicting Usage from Perceived Usefulness and Perceived Ease-of-Use
The original TAM model was developed by Fred D Davis, and described in the 1989 paper Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology. Researching acceptance of new technology by users, Davis looked for robust measures predicting and explaining usage levels. His research was focused on two potential factors that can lead to usage:
- Perceived usefulness (“the degree to which a person believes that using a particular system would enhance his or her job performance.”)
- Perceived ease of use (“the degree to which a person believes that using a particular system would be free of effort.”)
People tend to use or not use an application to the extent they believe it will help them perform their job better…. Even if potential users believe that a given application is useful, they may, at the same time, believe that the system is too hard to use and that the performance benefits of usage are outweighed by the effort of using the application.
– Fred D Davis
In the paper, Davis proposed measuring those factors with a two part survey, with a 7-point scale from Extremely likely to Extremely unlikely, such as the one below:
Perceived Usefulness
1. Using [Product] in my job would enable me to accomplish tasks more quickly.
2. Using [Product] would improve my job performance.
3. Using [Product] in my job would increase my productivity.
4. Using [Product] would enhance my effectiveness on the job.
5. Using [Product] would make it easier to do my job.
6. I would find [Product] useful in my job.
Perceived Ease of Use
7. Learning to operate [Product] would be easy for me.
8. I would find it easy to get [Product] to do what I want it to do.
9. My interaction with [Product] would be clear and understandable.
10. I would find [Product] to be flexible to interact with.
11. It would be easy for me to become skillful at using [Product].
12. I would find [Product] easy to use.
This 12-question survey was tested on two software programs, and concluded that usage was significantly correlated with both perceived usefulness and perceived ease of use. (Although, taken separately, usefulness had a significantly greater correlation with usage behavior than did ease of use. Davis even questioned whether ease-of-use is just a predictor of usefulness, and not a separate parallel factor).
Modified TAM (mTAM): Predicting Likelihood-to-Recommend from Usage Experience
Urška Lah, James R. Lewis and Boštjan Šumak modified the TAM questionnaire to be applicable outside enterprise applications, and also rephrased it to measure experienced ease of use and usefulness, rather than what users perceived before actually trying the products. They found that the modified TAM (mTAM) can be used to predict Likelihood-to-Recommend scores. The results of their research are published in the paper Perceived Usability and the Modified Technology Acceptance Model.
1. Using [Product] enabled me to accomplish tasks more quickly than the previous alternative product.
2. Using [Product] improved my job performance.
3. Using [Product] increased my productivity.
4. Using [Product] enhanced my effectiveness.
5. Using [Product] made it easier to do the things I needed to do with it.
6. I found [Product] useful.
7. It was easy to learn to operate [Product].
8. I found it easy to get [Product] to do what I wanted it to do.
9. My interaction with [Product] was clear and understandable.
10. I found [Product] to be flexible to interact with.
11. It was easy for me to become skillful at using [Product].
12. I found [Product] easy to use.
Lah, Lewis and Šumak conducted a survey with the modified TAM questionnaire and a 7-point Likert scale on 3 products, and concluded that the modified TAM survey is highly reliable, and correlates with Likelihood to Recommend scores (0.80 in one study, 0.65 in the second study, 0.90 in the third study). In all three studies, the modified TAM survey correlated higher with likelihood-to-recommend scores than the System Usability Scale and UMUX-LITE.
Applicability and limitations
Although the TAM survey originated at a time when regular business users were just adopting computers, it’s still relevant and applicable, and an active topic in the academic UX research community (with relatively recent research proving it’s usefulness every few years). It is particularly useful for internal and enterprise applications, assisting with adoption and retention.
Both TAM and mTAM surveys use a 7-point Likert Scale, so you can use the standard methods for scoring and interpreting Likert Scale data to track changes over time, and for relative comparisons between different product proposals, versions or designs.
The TAM model provides a statistical research backing for the importance of the Performance Path Map, and similar skill-based user segmentations, and it can be used to track if the product manager assumptions about key stages in the map reflect increased user engagement, retention and referrals.
The modified TAM version focused on experienced instead of perceived usefulness is also relevant as more granular way to investigate likelihood to recommend compared to single-question surveys such as the Net Promoter Score, and providing some direction what could be improved to increase those ratings and get more referrals.
In general, both the original and modified TAM are more applicable to professional use and adopting new products to assist with people’s work tasks, where effectiveness and job performance are critical for users, so they mostly apply to B2B and B2P applications and may not work as well for B2C products.
Learn more about the Technology Acceptance Model
- Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology, MIS Quarterly, Vol. 13, No. 3 by Fred D Davis (1989)
- Perceived Usability and the Modified Technology Acceptance Model, International Journal of Human-Computer Interaction Issue 13, Vol. 36 by Urška Lah, James R. Lewis, Boštjan Šumak (2020)