Where does IS continuance collide?

The intention to keep using an information system after adopting it, driven by how far the system confirmed what the user expected, by the perceived usefulness of continued use, and by satisfaction with use so far. Bhattacherjee introduced this expectation-confirmation model of IS continuance in 2001 and tested it on online banking users, showing that continuance intention was set by satisfaction and by post-acceptance perceived usefulness, while satisfaction was set by confirmation of prior expectations. The point of the model was that carrying on with a system is not the same decision as first accepting it, so the acceptance literature could not simply be reused. This is the referent for the map: the other names here either supplied its mechanism or grew out of it.[1]

Unit

A user's intention to keep using one specific system

Recovery means

Not applicable

Measured by

Continuance-intention items alongside confirmation, satisfaction, and post-acceptance usefulness scales

In marketing, satisfaction is modelled as a function of what a buyer expected before purchase and how far the product then confirmed or disconfirmed those expectations, with satisfaction in turn shaping attitude and the intention to buy again. Oliver set out this expectation-disconfirmation account in 1980 and tested it on people deciding whether to take a flu shot. Bhattacherjee borrowed the theory wholesale and re-pointed it from repurchase to continued system use, so the IS model's confirmation and satisfaction constructs are Oliver's, renamed for technology. The mechanism is the same comparison of expectation against experience, and only the object changed, from a bought product to an adopted system. The satisfaction construct itself is treated on its own page at satisfaction.[2]

Unit

A consumer's satisfaction and intention to repurchase

Recovery means

Not applicable

Measured by

Pre-purchase expectation, disconfirmation, satisfaction, and repurchase-intention items

The tendency to keep using a system automatically, out of learned routine rather than a fresh decision each time. Limayem, Hirt, and Cheung argued in 2007 that once use is frequent it becomes habitual, so intention explains less and less of what people actually do. In their model IS habit both feeds continued use directly and weakens the link from continuance intention to use, which is a different mechanism from the deliberate weighing that the continuance model assumes. This is the sharpest contrast on the map: the origin explains continued use as a considered intention, while habit explains it as behaviour that has stopped being considered at all. Habit as a construct has its own page at habit.[3]

Unit

How automatic a user's system use has become

Recovery means

Not applicable

Measured by

Self-reported automaticity or response-frequency habit measures, with continuance intention and use as criteria

How a user's beliefs and attitudes about a system shift as they gain first-hand experience, and how those revised beliefs then reset the intention to keep using it. Bhattacherjee and Premkumar extended the expectation-confirmation account in 2004 with two longitudinal studies, treating disconfirmation and satisfaction as the forces that change perceived usefulness and attitude over time rather than as one-off inputs measured once. This keeps the same confirmation-and-satisfaction machinery as the origin model but makes it dynamic, following the same users across successive points instead of asking after adoption alone. It names continued use through a moving target, the belief that experience keeps updating, rather than a fixed post-adoption judgement.[4]

Unit

The change in a user's beliefs and attitudes over repeated use

Recovery means

Not applicable

Measured by

Perceived usefulness, attitude, disconfirmation, and satisfaction measured at two or more time points