{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,14]],"date-time":"2026-01-14T23:59:08Z","timestamp":1768435148903,"version":"3.49.0"},"reference-count":66,"publisher":"Emerald","issue":"2","license":[{"start":{"date-parts":[[2017,6,12]],"date-time":"2017-06-12T00:00:00Z","timestamp":1497225600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.emerald.com\/insight\/site-policies"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["ICS"],"published-print":{"date-parts":[[2017,6,12]]},"abstract":"<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Purpose<\/jats:title>\n<jats:p>The purpose of this paper is to compare three social cognitive models in their ability to explain intentions of precautionary online behaviour. The models are: protection motivation theory (PMT), the reasoned action approach (RAA) and an integrated model comprising variables of these models.<\/jats:p>\n<\/jats:sec>\n<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Design\/methodology\/approach<\/jats:title>\n<jats:p>Data were collected from 1,200 Dutch users of online banking by means of an online survey and analysed using partial least squares path modelling method.<\/jats:p>\n<\/jats:sec>\n<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Findings<\/jats:title>\n<jats:p>The two models equally explain about much of the variance in precautionary online behaviour; in the integrated model, the significant predictors of the two models remained significant. Precautionary online behaviour is largely driven by response efficacy, attitude towards behaviour and self-efficacy.<\/jats:p>\n<\/jats:sec>\n<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Research limitations\/implications<\/jats:title>\n<jats:p>One limitation is that the predictor variables \u2013 \u201cself-efficacy\u201d and \u201cattitude\u201d \u2013 are represented by one item only in the path-analysis because of high cross-loadings of the other items with the dependent variable.<\/jats:p>\n<\/jats:sec>\n<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Practical implications<\/jats:title>\n<jats:p>The results give practitioners a potentially wider range of options to design preventative measures.<\/jats:p>\n<\/jats:sec>\n<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Originality\/value<\/jats:title>\n<jats:p>The three models are successfully applied to online banking. This paper concludes that both PMT and RAA make a unique contribution in explaining variance for precautionary online behaviour. 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