As a web or app designer, have you ever designed a software application that looks well thought-out with super cool features, and that works very well, but you noticed that the website or app is not being used to its full potential by your intended users? A common reason for this could be that you did not conduct adequate research to understand the technology use behavior of your intended users, prior to the development of the software program.
Also very often, organizations invest huge amount of resources into developing an information system to support their business operations, without considering the technology usage behavior and attitude of their prospective users. Information system (IS) research has provided very useful theories and models that predict and explain the factors that affect an individual’s acceptance and use of an information system. The information system could be a proprietary application such as MS Word or Excel, or a customized or designed application such as a Transaction Processing System. One of the most popular theories for explaining technology usage is the Technology Acceptance Model (TAM) developed by Fred Davis in 1989.
Basically, TAM considers two factors relevant in computer or technology use behaviors. They are perceived usefulness and perceived ease of use. Davis, in his thesis proposal, defined perceived usefulness as whether the prospective user thinks that using a particular application or program will enhance his or her work or life performance. So, if a user has a positive attitude towards a software application, then he or she is very likely to use it and vice versa. Also, Davis defined perceived ease of use as the degree to which the intended user expects the application or program to be effortless. I can’t imagine anybody enjoys using an application or system that is too complex and difficult to use, no matter how effective it might be.
Researchers worldwide have applied TAM in various studies such as in
- healthcare to explain physician’s intention to use telemedicine technology
- the financial sector to understand the adoption of internet banking, and to predict the acceptance of e-commerce
- the education sector to understand the acceptance of eLearning by teachers
- the services sector to study online shopping behavior, and to understand e-service adoption
- the telecommunication sector to understand mobile service adoption
- the security sector to understand the acceptance of Radio Frequency Identification (RFID)
- human resources to understand the acceptance of e-recruitment
and so many more.
TAM has been tested and found to be reliable by numerous studies conducted worldwide. Hence, as a startup or organization, before devoting valuable resources into developing an information system, I suggest you take TAM into consideration to predict if your system will be accepted and used by your intended users.