000120940 001__ 120940
000120940 005__ 20241125101125.0
000120940 0247_ $$2doi$$a10.1002/mar.21765
000120940 0248_ $$2sideral$$a131429
000120940 037__ $$aART-2023-131429
000120940 041__ $$aeng
000120940 100__ $$0(orcid)0000-0001-7118-9013$$aFlavián, Carlos$$uUniversidad de Zaragoza
000120940 245__ $$aEffects of voice assistant recommendations on consumer behavior
000120940 260__ $$c2023
000120940 5060_ $$aAccess copy available to the general public$$fUnrestricted
000120940 5203_ $$aThe present study compares the influence of text-based recommendations; traditionally known as online consumer reviews, and the influence of voice-based recommendations provided by voice-driven virtual assistants on consumer behaviors. Based on media richness theory, the research model investigates how voice versus text modality influences consumers' perceptions of credibility and usefulness, as well as their behavioral intentions and actual behaviors. In addition, the study analyses if these relationships vary based on the type of product and compares the influence of masculine and feminine voices. Two studies were conducted using between-subjects experimental designs, partial least squares-structural equation modeling, and logistic regression. The core finding is that voice-based recommendations are more effective than online consumer reviews in altering consumer behaviors. In addition, the first study showed that the influence of recommendations on behavioral intentions is mediated by consumers' perceptions of their credibility and usefulness. The second study confirmed, in a realistic setting, that voice-based recommendations affect consumer choices to a greater extent. Recommendations for search products and provided by males are also found to be more effective. These results contribute to the voice assistant and e-WOM literature by highlighting the effectiveness of voice-based recommendations in predicting consumer behaviors, confirming that credibility and usefulness are key factors that determine the influence of recommendations, and showing that recommendations are more effective when they focus on search products.
000120940 536__ $$9info:eu-repo/grantAgreement/ES/DGA-FSE/S20-20R METODO Research Group$$9info:eu-repo/grantAgreement/ES/DGA-FSE/LMP51-21$$9info:eu-repo/grantAgreement/ES/MCIU/PID2019-105468RB-I00
000120940 540__ $$9info:eu-repo/semantics/openAccess$$aby-nc-nd$$uhttp://creativecommons.org/licenses/by-nc-nd/3.0/es/
000120940 590__ $$a8.9$$b2023
000120940 592__ $$a2.76$$b2023
000120940 591__ $$aPSYCHOLOGY, APPLIED$$b6 / 113 = 0.053$$c2023$$dQ1$$eT1
000120940 593__ $$aMarketing$$c2023$$dQ1
000120940 591__ $$aBUSINESS$$b19 / 304 = 0.062$$c2023$$dQ1$$eT1
000120940 593__ $$aApplied Psychology$$c2023$$dQ1
000120940 594__ $$a12.1$$b2023
000120940 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/publishedVersion
000120940 700__ $$aAkdim, Khaoula$$uUniversidad de Zaragoza
000120940 700__ $$0(orcid)0000-0002-9643-2814$$aCasaló, Luis V.$$uUniversidad de Zaragoza
000120940 7102_ $$14011$$2095$$aUniversidad de Zaragoza$$bDpto. Direc.Mark.Inves.Mercad.$$cÁrea Comerci.Investig.Mercados
000120940 773__ $$g40, 2 (2023), 328-346$$pPsychol. mark.$$tPSYCHOLOGY & MARKETING$$x0742-6046
000120940 8564_ $$s1174982$$uhttps://zaguan.unizar.es/record/120940/files/texto_completo.pdf$$yVersión publicada
000120940 8564_ $$s2059487$$uhttps://zaguan.unizar.es/record/120940/files/texto_completo.jpg?subformat=icon$$xicon$$yVersión publicada
000120940 909CO $$ooai:zaguan.unizar.es:120940$$particulos$$pdriver
000120940 951__ $$a2024-11-22-11:57:24
000120940 980__ $$aARTICLE