You need to Know How Things are Going in order to ensure that Quality is Baked in. This article outlines three research methods that will help you get new data-backed insight into a user's experience with your technology.
Quality is multi-dimensional and is baked into many widely used research methods and assessments. Three popular research models, TAM, UTAUT, and SUS, take different approaches to evaluate how users interact with their information systems and their perspective of those interactions. We'll delve into each of these models' unique ways to determine the quality factors that affect a user's experience with technology.
A technology acceptance model is a popular research model that predicts the use and acceptance of information systems and technology by individual users. It gauges the value of the investment in new technology by analyzing a user's experience. Its purpose is to help understand and explain user behavior in an information system, and researchers typically put it to use for research studies. It has two constructs: Perceived Usefulness (U) and Perceived Ease of Use (E) that help measure the quality of the technology experience. However, the TAM isn't uniformly applicable to all situations.
Some researchers argue that the TAM model is more appropriate for individual use and acceptance than a corporate or institutional application that requires integrating other technology. It also doesn't fully live up to its full potential in many sectors. For example, healthcare IT critics claim that only measures created for healthcare fully capture the unique contextual features in healthcare tech. There are also no benchmarks for TAM total scores nor the usefulness and ease of use constructs. This lack of criteria proves challenging to communicate results without a standard threshold. Nevertheless, it still has a strong track record in other industries.
Many researchers consider TAM a valid and reliable measure that explains and predicts usage for information systems. It's a relatively easy model to replicate, and it's a model that can evolve. For example, response scales can change, and external variables like social influence added to the model. In essence, the TAM will continue to be a significant step in understanding user behavior with technology.
One specific kind of TAM is the Uniform Theory of Acceptance and Use of Technology (UTAUT). Its goal is to explain user intentions to use an information system and resulting user behavior. It claims four key constructs are direct determinants of usage intention and behavior: performance expectancy, effort expectancy, social influence, and facilitating conditions. Variables you can measure from those constructs are gender, age, experience, and voluntariness of use. These measures enhance the understanding of what drives a user to use a particular technology and how their experience was perceived.
One of the main advantages of the UTAUT is its capability to inform the understanding of factors that determine new technology acceptance. Research claims that the UTAUT model explains over 70 percent of all the technology acceptance behavior, unlike similar models that explain 40 percent of acceptance behavior. Thus, it exposes more factors that influence user intentions, and therefore, considered more encompassing. However, like the TAM, the UTAUT has been criticized for being overly simplistic and more viable for individual behavior than corporate use. Still, researchers say that the benefits of the model are far more significant than its shortcomings.
A System Usability Scale (SUS) is a tool to measure usability. The SUS evaluates a wide variety of products and services, including hardware, software, mobile devices, websites, and applications. Unlike TAM and UTAUT, SUS seems to be considered acceptable in corporate situations. Employees often use it in user interviews, focus group discussions, usability testing, and other UX programs. The SUS usually consists of ten items with questions like: "I found the system very cumbersome to use" or "I found the various functions in this system were well-integrated" with Likert-scale response options ranging from 'strongly agree' to 'strongly disagree.'
SUS has become an industry standard in the user experience community. It is praised for the ease of administration to participants, its ability to be used on small samples, and how it can differentiate between usable and unusable systems. It's also highly accessible.
Like any research model, SUS has its limitations. For example, the scoring system is more complicated than others. The participant's scores for each question are converted to a new number, added together, and then multiplied by 2.5 to convert the original scores of 0-40 to 0-100. Even though the scores are 0-100, they aren't percentages but rather measured as percentile rankings. A SUS also doesn't provide accurate information on a product's weakness.
It's best not to rely on just one of these models for a well-rounded, astute analysis. Take context into consideration when you pick the models to perform your research and extract understandings. Regardless of the model you choose, you will get new data-backed insight into a user's experience with your technology.
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