Managers and scholars alike are keen to understand the factors that affect individual acceptance and use of new technology. A lot of research has been done in this field and, while the many ideas have been unified into a single theory that can fairly reliably predict people’s behaviour towards new technology, it has mostly focused on employees at work. But what about consumers?

Viswanath Venkatesh, James Y.L Thong and Xin Xu provide an answer by adapting and extending the existing theory so that it can take into account issues likely to be of concern to consumers but not employees, such as price. They apply their model to 1,512 consumers and the use of mobile IT applications (apps), and show how it can predict differences between men and women, old and young, and inexperienced and experienced users when it comes to adopting new technology.

They start with the original employee-based model, which has four components: expectations of the performance of the technology, expectations about its ease of use, the social influence in terms of whether friends or employers expect the person to use the technology, and the facilitating conditions in terms of resources and support to use the technology.

To this, the authors add three factors that are particular to consumers: hedonic motivation (how much fun or pleasure they can get from the technology), price value, and experience and habit (how long they have used a technology and the extent to which the usage behavior is automatic).

Combining all of these together and throwing age and gender into the mix, the authors find distinct differences among certain groups in terms of when and how they respond to new technology.

First, they show that facilitating conditions are most important to older women, who tend to focus on the magnitude of effort required to adopt a new technology. This suggests that ongoing facilitations designed for older women should be provided by vendors of IT applications.

Second, younger men are more motivated by the hedonic benefits of using a new technology in the early stages. Managers therefore could bundle hedonic apps with special promos to attract their business.

Third, on price, older women were the most sensitive to this factor because of their social role as gatekeepers of family expenditure. The authors suggested managers could promote special discounts to them while applying premium prices to the hedonic apps targeted at younger men.

“The current cost structure of mobile internet applications is mainly based on the network traffic generated by each type of app, with multimedia contents priced at the highest level. But this pricing pattern may not reflect the relative value attached to different apps by consumers,” they said.

Fourth, habit also affected take-up of new technology. Older men who were experienced with technology were less likely to change their habits, while younger women were more fickle. Managers therefore needed to consider how to change these men’s habits, and how to get younger women to maintain habitual use, if they wanted their business.

“In sum, our study suggests the consumer technology industry should better design and market technologies to consumers in various demographic groups at various stages of the use curve,” the authors said.

Importantly, the results were also proof that their model could be useful in predicting consumer intention and use of technology. It explained 74 per cent of the variance in behavioural intention and 52 per cent of the variance in use. This was a substantial improvement on the original unified theory which predicted 56 per cent and 40 per cent, respectively, when applied to consumers.