000121199 001__ 121199
000121199 005__ 20250722154012.0
000121199 0247_ $$2doi$$a10.1016/j.chb.2022.107564
000121199 0248_ $$2sideral$$a131766
000121199 037__ $$aART-2023-131766
000121199 041__ $$aeng
000121199 100__ $$0(orcid)0000-0001-8353-3870$$aBarta, S.$$uUniversidad de Zaragoza
000121199 245__ $$aUsing augmented reality to reduce cognitive dissonance and increase purchase intention
000121199 260__ $$c2023
000121199 5060_ $$aAccess copy available to the general public$$fUnrestricted
000121199 5203_ $$aAugmented reality (AR) has been shown to improve consumers' shopping decisions and experiences. Based on a theoretical stimulus-organism-response model and cognitive load theory, this research examines the effects that AR has on cognitive variables related to cognitive load, hitherto scarcely considered. Specifically, this research examines the impact of perceived similarity among options, confusion caused by overchoice and prepurchase cognitive dissonance on purchase-related behavioral intention variables such as purchase intention and willingness to pay for products. The study is based on consumers' AR web shopping experiences of an online cosmetics store which offers a wide assortment of products. The mixed-method research combines two focus groups and an experiment. This combination allows triangulation of the findings to provide corroboration. The results showed that AR reduces cognitive dissonance through its effects on perceived similarity and confusion caused by overchoice. Furthermore, lower cognitive load enhances purchase intentions, resulting in greater willingness to pay more for the product. The research extends knowledge of the benefits provided to consumers by AR in their decision-making through its impacts on perceived similarity, confusion by overchoice and prepurchase cognitive dissonance. The application of web AR in e-commerce shops is particularly useful when a wide assortment of similar products is offered. Online retailers can use AR to improve their economic performance both by increasing their sales’ volumes and their margins.
000121199 536__ $$9info:eu-repo/grantAgreement/ES/MICIU/PID2019-105468RB-I00$$9info:eu-repo/grantAgreement/ES/MCIU/FPU18-02037$$9info:eu-repo/grantAgreement/ES/DGA-FSE/S20-20R METODO Research Group$$9info:eu-repo/grantAgreement/ES/DGA-FSE/LMP51-21
000121199 540__ $$9info:eu-repo/semantics/openAccess$$aby-nc-nd$$uhttp://creativecommons.org/licenses/by-nc-nd/3.0/es/
000121199 590__ $$a9.0$$b2023
000121199 592__ $$a2.641$$b2023
000121199 591__ $$aPSYCHOLOGY, MULTIDISCIPLINARY$$b9 / 219 = 0.041$$c2023$$dQ1$$eT1
000121199 593__ $$aArts and Humanities (miscellaneous)$$c2023$$dQ1
000121199 591__ $$aPSYCHOLOGY, EXPERIMENTAL$$b3 / 99 = 0.03$$c2023$$dQ1$$eT1
000121199 593__ $$aPsychology (miscellaneous)$$c2023$$dQ1
000121199 593__ $$aHuman-Computer Interaction$$c2023$$dQ1
000121199 594__ $$a19.1$$b2023
000121199 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/publishedVersion
000121199 700__ $$0(orcid)0000-0002-5487-5203$$aGurrea, R.$$uUniversidad de Zaragoza
000121199 700__ $$0(orcid)0000-0001-7118-9013$$aFlavián, C.$$uUniversidad de Zaragoza
000121199 7102_ $$14011$$2095$$aUniversidad de Zaragoza$$bDpto. Direc.Mark.Inves.Mercad.$$cÁrea Comerci.Investig.Mercados
000121199 773__ $$g140 (2023), 107564 [13 pp.]$$pComput. hum. behav.$$tCOMPUTERS IN HUMAN BEHAVIOR$$x0747-5632
000121199 8564_ $$s2419025$$uhttps://zaguan.unizar.es/record/121199/files/texto_completo.pdf$$yVersión publicada
000121199 8564_ $$s2620542$$uhttps://zaguan.unizar.es/record/121199/files/texto_completo.jpg?subformat=icon$$xicon$$yVersión publicada
000121199 909CO $$ooai:zaguan.unizar.es:121199$$particulos$$pdriver
000121199 951__ $$a2025-07-22-15:35:45
000121199 980__ $$aARTICLE