Search for Articles: for Articles : Journal of Theoretical and Applied Electronic Commerce Research (JTAER) All Article Types Search All Sections All Special Issues Logical Operator Operator ► ▼ Hyunchul Ahn /ajax/scifeed/subscribe Article Views 7221 Citations 2 Altmetric Altmetric Share Help Cite Discuss in SciProfiles Arial Georgia Verdana Aa Aa Aa       Open Access Article Ovidiu-Iulian BuneaOvidiu-Iulian Bunea SciProfiles Scilit Preprints.org Google Scholar 1, Ovidiu-Iulian Bunea Răzvan-Andrei CorboșRăzvan-Andrei Corboș SciProfiles Scilit Preprints.org Google Scholar 1, Răzvan-Andrei Corboș Sorina Ioana MișuSorina Ioana Mișu SciProfiles Scilit Preprints.org Google Scholar 1,*, Sorina Ioana Mișu Monica TriculescuMonica Triculescu SciProfiles Scilit Preprints.org Google Scholar 1 and Monica Triculescu Andreea TrifuAndreea Trifu SciProfiles Scilit Preprints.org Google Scholar 2 Andreea Trifu Submission received: 21 August 2024 Revised: 25 September 2024 Accepted: 26 September 2024 Published: 30 September 2024 . The level of exposure to AI is expected to have a significant positive impact on Gen Z consumers’ perceived usefulness of AI in the context of AI-powered online shopping. The level of exposure to AI is expected to have a significant positive impact on Gen Z consumers’ perceived ease-of-use of AI in the context of AI-powered online shopping. The level of exposure to AI is expected to have a significant positive impact on Gen Z consumers’ purchase intentions in the context of AI-powered online shopping. The level of use of AI in Gen Z consumers’ daily lives is expected to positively impact their purchase intentions in the context of AI-powered online shopping. The level of use of AI in Gen Z consumers’ daily lives is expected to positively impact their perceived usefulness of AI in the context of AI-powered online shopping. The level of use of AI in Gen Z consumers’ daily lives is expected to positively impact their perceived ease-of-use of AI in the context of AI-powered online shopping. The perceived usefulness of AI is expected to have a positive impact on Gen Z consumers’ purchase intentions in the context of AI-powered online shopping. The perceived ease-of-use of AI is expected to have a positive impact on Gen Z consumers’ purchase intentions in the context of AI-powered online shopping. The level of AI knowledge is expected to have a positive impact on Gen Z consumers’ purchase intention in the context of AI-powered online shopping. The level of AI knowledge is expected to have a positive impact on Gen Z consumers’ perceived usefulness of AI in the context of AI-powered online shopping. The level of AI knowledge is expected to have a positive impact on Gen Z consumers’ perceived ease-of-use of AI in the context of AI-powered online shopping. The relationships between the (a) level of use of AI, (b) level of AI knowledge, and (c) level of AI exposure and the purchase intention are mediated by Gen Z consumers’ perceived usefulness of AI in the context of AI-powered online shopping. The relationships between the (a) level of use of AI, (b) level of AI knowledge, and (c) level of AI exposure and the purchase intention are mediated by Gen Z consumers’ perceived ease-of-use of AI in the context of AI-powered online shopping. , p p p p p p J. Retail. Consum. Serv. 60 J. Bus. Res. 144 Retail E-Commerce Sales Worldwide from 2014 to 2027 Technol. Soc. 70 Comput. Human. Behav. 114 Technol. Forecast. Soc. Chang. 190 Comput. Human. Behav. 128 Electron. Commer. Res. Appl. 61 J. Retail. 97 Psychol. Mark. 40 Guide to Gen Z: What Matters to This Generation and What It Means for Marketers J. Retail. Consum. Serv. 73 Meet Generation Z: Shaping the Future of Shopping MIS Q. 13 Handbook of Open, Distance and Digital Education Sustainability 17 J. Theor. Appl. Electron. Commer. Res. 17 J. Bus. Ind. Mark. 34 Electron. Mark. 32 Technology Acceptance Model: A Review AI-Powered Marketing and Sales Reach New Heights with Generative AI Comput. Human. Behav. 77 J. Consum. Behav. 20 J. Retail. Consum. Serv. 61 J. Retail. Consum. Serv. 75 Glob. Bus. Rev. 23 What Do Gen Z Shoppers Really Want What Is Gen Z? Comput. Human. Behav. 153 Technol. Forecast. Soc. Chang. 186 Technol. Forecast. Soc. Chang. 166 Young Consum. 22 J. Interact. Mark. 51 Procedia Econ. Financ. 26 J. Bus. Res. 66 Educ. Inf. Technol. 28 Int. J. Contemp. Hosp. Manag. 34 Int. J. Contemp. Hosp. Manag. 36 Libr. Philos. Pract. 9 Marketing and Smart Technologies: Proceedings of ICMarkTech 2019, Maia, Portugal, 27–29 November 2019 Foresight 25 Amfiteatru Econ. 23 Cloth. Text. Res. J. 38 Sustainability 14 Int. J. Inf. Manag. 70 Int. J. Inf. Manag. 49 Internet Res. 32 Sustainability 13 Int. J. Retail Distrib. Manag. 51 J. Mark. Manag. 35 Electronics 11 Bus. Horiz. 63 Technol. Forecast. Soc. Chang. 177 J. Retail. Consum. Serv. 65 Manag. Mark. 13 J. Enterp. Inf. Manag. Qual. Mark. Res. An Int. J. 25 Behav. Inf. Technol. 40 Int. J. Man. Mach. Stud. 38 Psychol. Mark. 36 J. Retail. Consum. Serv. 74 Resour. Policy 67 Int. J. Hosp. Manag. 90 Ind. Manag. Data Syst. 116 Annu. Rev. Psychol. 63 J. Retail. 88 J. Bus. Res. 69 J. Appl. Psychol. 88 A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM) Handbook of Market Research Advanced Issues in Partial Least Squares Structural Equation Modeling (PLS-SEM) Eur. Bus. Rev. 31 J. Acad. Mark. Sci. 43 J. Mark. 85 J. Res. Interact. Mark. 17 Int. J. Hum. Comput. Interact. 39 Comput. Human. Behav. 128 J. Organ. Chang. Manag. 36 Transylv. Rev. Adm. Sci. 19 J. Consum. Mark. 41 Note: α = Cronbach’s alpha; AVE = average variance extracted; VIF = variance inflation factor. p Note: R-square—coefficient of determination; p-value—statistical significance; Q—SquareBlindfolding-based cross-validated redundancy measure. Unexplained variances indicate potential influences of other variables not included in this model. p Note: *** p < 0.001; ** p < 0.01. SD—standard deviation. p p Note: *** p < 0.001; ** p < 0.01; * p < 0.05. Abbreviations: de—direct effect; ie—indirect effect; SD—standard deviation; BCCI—bias-corrected confidence interval. p p p Note: The quadrants are delimited using the mean of performance (49.355) and mean of importance (0.055304) reported in the IPMA results table at the indicator level. Q1 and Q2 cells were colored in green and orange to emphasize the most important indicators. | | | | | | | J. Theor. Appl. Electron. Commer. 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Electron. Commer. Res. 2024, 19, 2605-2629. https://doi.org/10.3390/jtaer19040125 Bunea O-I, Corboș R-A, Mișu SI, Triculescu M, Trifu A. The Next-Generation Shopper: A Study of Generation-Z Perceptions of AI in Online Shopping. Journal of Theoretical and Applied Electronic Commerce Research. 2024; 19(4):2605-2629. https://doi.org/10.3390/jtaer19040125 Bunea, Ovidiu-Iulian, Răzvan-Andrei Corboș, Sorina Ioana Mișu, Monica Triculescu, and Andreea Trifu. 2024. "The Next-Generation Shopper: A Study of Generation-Z Perceptions of AI in Online Shopping" Journal of Theoretical and Applied Electronic Commerce Research 19, no. 4: 2605-2629. https://doi.org/10.3390/jtaer19040125 Bunea, O.-I., Corboș, R.-A., Mișu, S. I., Triculescu, M., & Trifu, A. (2024). The Next-Generation Shopper: A Study of Generation-Z Perceptions of AI in Online Shopping. Journal of Theoretical and Applied Electronic Commerce Research, 19(4), 2605-2629. https://doi.org/10.3390/jtaer19040125 Bunea, O.-I.; Corboș, R.-A.; Mișu, S.I.; Triculescu, M.; Trifu, A. The Next-Generation Shopper: A Study of Generation-Z Perceptions of AI in Online Shopping. J. Theor. Appl. Electron. Commer. Res. 2024, 19, 2605-2629. https://doi.org/10.3390/jtaer19040125 Bunea O-I, Corboș R-A, Mișu SI, Triculescu M, Trifu A. The Next-Generation Shopper: A Study of Generation-Z Perceptions of AI in Online Shopping. Journal of Theoretical and Applied Electronic Commerce Research. 2024; 19(4):2605-2629. https://doi.org/10.3390/jtaer19040125 Bunea, Ovidiu-Iulian, Răzvan-Andrei Corboș, Sorina Ioana Mișu, Monica Triculescu, and Andreea Trifu. 2024. "The Next-Generation Shopper: A Study of Generation-Z Perceptions of AI in Online Shopping" Journal of Theoretical and Applied Electronic Commerce Research 19, no. 4: 2605-2629. https://doi.org/10.3390/jtaer19040125 Bunea, O.-I., Corboș, R.-A., Mișu, S. I., Triculescu, M., & Trifu, A. (2024). The Next-Generation Shopper: A Study of Generation-Z Perceptions of AI in Online Shopping. Journal of Theoretical and Applied Electronic Commerce Research, 19(4), 2605-2629. https://doi.org/10.3390/jtaer19040125 Subscribe to receive issue release notifications and newsletters from MDPI journals