The Impact of Trust-Building Mechanisms on Purchase Intention towards Metaverse Shopping: The Moderating Role of Age

References

• Armstrong, J. S., & Overton, T. S. (1977). Estimating nonresponse bias in mail surveys. Journal of Marketing Research, 14(3), 396–402. https://doi.org/10.2307/3150783
   Web of Science ®Google Scholar
• Bao, Y., Cheng, X., De Vreede, T., & De Vreede, G.-J. (2021). Investigating the relationship between AI and trust in human-AI collaboration [Paper presentation]. Proceedings of the Hawaii International Conference on System Sciences, 54th (pp. 607–616). https://doi.org/10.24251/HICSS.2021.074
   Google Scholar
• Benitez, J., Arenas, A., Castillo, A., & Esteves, J. (2022). Impact of digital leadership capability on innovation performance: The role of platform digitization capability. Information & Management, 59(2), 103590. https://doi.org/10.1016/j.im.2022.103590
   Web of Science ®Google Scholar
• Benitez, J., Henseler, J., Castillo, A., & Schuberth, F. (2020). How to perform and report an impactful analysis using partial least squares: Guidelines for confirmatory and explanatory IS research. Information & Management, 57(2), 103168. https://doi.org/10.1016/j.im.2019.05.003
   Web of Science ®Google Scholar
• Benitez, J., Ruiz, L., & Popovic, A. (2022). Impact of mobile technology-enabled HR gamification on employee performance: An empirical investigation. Information & Management, 59(4), 103647. https://doi.org/10.1016/j.im.2022.103647
   Web of Science ®Google Scholar
• Berthiaume, D. (2022). Survey: Are consumers ready for metaverse shopping? Chain Store Age. https://chainstoreage.com/survey-are-consumers-ready-metaverse-shopping
   Google Scholar
• Boughzala, I., de Vreede, G.-J., & Limayem, M. (2012). Team collaboration in virtual worlds: Editorial to the special issue. Journal of the Association for Information Systems, 13(10), 714–734. https://doi.org/10.17705/1jais.00313
   Web of Science ®Google Scholar
• Braojos, J., Benitez, J., & Llorens, J. (2019). How do social commerce-IT capabilities influence firm performance? Theory and empirical evidence. Information & Management, 56(2), 155–171. https://doi.org/10.1016/j.im.2018.04.006
   Web of Science ®Google Scholar
• Castillo, A., Benitez, J., Llorens, J., & Luo, X. (. (2021). Social media-driven customer engagement and movie performance: Theory and empirical evidence. Decision Support Systems, 145(June), 113516. https://doi.org/10.1016/j.dss.2021.113516
   Google Scholar
• Chan, T. K. H., Cheung, C. M. K., & Lee, Z. W. Y. (2017). The state of online impulse-buying research: A literature analysis. Information & Management, 54(2), 204–217. https://doi.org/10.1016/j.im.2016.06.001
   Web of Science ®Google Scholar
• Chang, H. H., Rizal, H., & Amin, H. (2013). The determinants of consumer behavior towards email advertisement. Internet Research, 23(3), 316–337. https://doi.org/10.1108/10662241311331754
   Web of Science ®Google Scholar
• Chen, Y., Lu, Y., Wang, B., & Pan, Z. (2019). How do product recommendations affect impulse buying? An empirical study on WeChat social commerce. Information & Management, 56(2), 236–248. https://doi.org/10.1016/j.im.2018.09.002
   Web of Science ®Google Scholar
• Cheng, X., Fu, S., & de Vreede, G.-J. (2017). Understanding trust influencing factors in social media communication: A qualitative study. International Journal of Information Management, 37(2), 25–35. https://doi.org/10.1016/j.ijinfomgt.2016.11.009
   Web of Science ®Google Scholar
• Cheng, X., Fu, S., & de Vreede, G.-J. (2021). Determinants of trust in computer-mediated offshore software-outsourcing collaboration. International Journal of Information Management, 57(April), 102301. https://doi.org/10.1016/j.ijinfomgt.2020.102301
   Google Scholar
• Cheng, X., Su, L., Luo, X., Benitez, J., & Cai, S. (2022). The good, the bad, and the ugly: Impact of analytics and artificial intelligence-enabled personal information collection on privacy and participation in ridesharing. European Journal of Information Systems, 31(3), 339–363. https://doi.org/10.1080/0960085X.2020.1869508
   Web of Science ®Google Scholar
• Chi, O. H., Jia, S., Li, Y., & Gursoy, D. (2021). Developing a formative scale to measure consumers’ trust toward interaction with artificially intelligent (AI) social robots in service delivery. Computers in Human Behavior, 118(May), 106700. https://doi.org/10.1016/j.chb.2021.106700
   Google Scholar
• Chih, W.-H., Hsu, L.-C., & Liou, D.-K. (2017). Understanding virtual community members’ relationships from individual, group, and social influence perspectives. Industrial Management & Data Systems, 117(6), 990–1010. https://doi.org/10.1108/IMDS-03-2016-0119
   Web of Science ®Google Scholar
• Choung, H., David, P., & Ross, A. (2022). Trust in AI and its role in the acceptance of AI technologies. International Journal of Human–Computer Interaction. Advance online publication. https://doi.org/10.1080/10447318.2022.2050543
   Web of Science ®Google Scholar
• CNNIC. (2021). The 42nd China statistical report on internet development. http://www.cac.gov.cn/2021-02/03/c_1613923422728645.htm
   Google Scholar
• Cummings, L. L., & Bromiley, P. (1996). The organizational trust inventory (OTI). In R. M. Kramer & T. R. Tyler (Eds.), Trust in organizations: Frontiers of theory and research (pp. 302–330). Sage Publications, Inc. https://doi.org/10.4135/9781452243610.n15
   Google Scholar
• Daft, R. L., & Lengel, R. H. (1986). Organizational information requirements, media richness and structural design. Management Science, 32(5), 554–571. https://doi.org/10.1287/mnsc.32.5.554
   Web of Science ®Google Scholar
• Darbinyan, R. (2022). Virtual shopping in the metaverse: What is it and how will AI make it work. Forbes. https://www.forbes.com/sites/forbestechcouncil/2022/03/16/virtual-shopping-in-the-metaverse-what-is-it-and-how-will-ai-make-it-work/?sh=661defa85f27
   Google Scholar
• Dennis, A. R., & Kinney, S. T. (1998). Testing media richness theory in the new media: The effects of cues, feedback, and task equivocality. Information Systems Research, 9(3), 256–274. https://doi.org/10.1287/isre.9.3.256
   Web of Science ®Google Scholar
• Di Pietro, R., & Cresci, S. (2021). Metaverse: Security and Privacy Issues [Paper presentation]. 2021 Third IEEE International Conference on Trust, Privacy and Security in Intelligent Systems and Applications (TPS-ISA) (pp. 281–288). https://doi.org/10.1109/TPSISA52974.2021.00032
   Google Scholar
• Dwivedi, Y. K., Hughes, L., Baabdullah, A. M., Ribeiro-Navarrete, S., Giannakis, M., Al-Debei, M. M., Dennehy, D., Metri, B., Buhalis, D., Cheung, C. M., Conboy, K., Doyle, R., Dubey, R., Dutot, V., Felix, R., Goyal, D. P., Gustafsson, A., Hinsch, C., Jebabli, I., … Wamba, S. F. (2022). Metaverse beyond the hype: Multidisciplinary perspectives on emerging challenges, opportunities, and agenda for research, practice and policy. International Journal of Information Management, 66(October), 102542. https://doi.org/10.1016/j.ijinfomgt.2022.102542
   Google Scholar
• Faul, F., Erdfelder, E., Buchner, A., & Lang, A.-G. (2009). Statistical power analyses using G* Power 3.1: Tests for correlation and regression analyses. Behavior Research Methods, 41(4), 1149–1160. https://doi.org/10.3758/BRM.41.4.1149
   PubMed Web of Science ®Google Scholar
• Gefen, D. (2000). E-commerce: The role of familiarity and trust. Omega, 28(6), 725–737. https://doi.org/10.1016/S0305-0483(00)00021-9
   Web of Science ®Google Scholar
• Ghobadi, S., & Mathiassen, L. (2020). A generational perspective on the software workforce: Precocious users of social networking in software development. Journal of Management Information Systems, 37(1), 96–128. https://doi.org/10.1080/07421222.2019.1705508
   Web of Science ®Google Scholar
• Goles, T., Rao, S. V., Lee, S., & Warren, J. (2009). Trust violation in electronic commerce: Customer concerns and reactions. Journal of Computer Information Systems, 49(4), 1–9. https://doi.org/10.1080/08874417.2009.11645335
   Web of Science ®Google Scholar
• Grupac, M., Husakova, K., & Balica, R.-Ş. (2022). Virtual navigation and augmented reality shopping tools, immersive and cognitive technologies, and image processing computational and object tracking algorithms in the metaverse commerce. Analysis and Metaphysics, 2022(21), 210–226. https://doi.org/10.22381/am21202213
   Google Scholar
• Grupac, M., & Lăzăroiu, G. (2022). Image processing computational algorithms, sensory data mining techniques, and predictive customer analytics in the metaverse economy. Review of Contemporary Philosophy, 2022(21), 205–222. https://doi.org/10.22381/RCP21202213
   Google Scholar
• Gurtner, S., Reinhardt, R., & Soyez, K. (2014). Designing mobile business applications for different age groups. Technological Forecasting and Social Change, 88(October), 177–188. https://doi.org/10.1016/j.techfore.2014.06.020
   Google Scholar
• Hair, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2021). A primer on partial least squares structural equation modeling (PLS-SEM). Sage Publications.
   Google Scholar
• Hennig-Thurau, T., Aliman, D. N., Herting, A. M., Cziehso, G. P., Linder, M., & Kübler, R. V. (2022). Social interactions in the metaverse: Framework, initial evidence, and research roadmap. Journal of the Academy of Marketing Science. Advance online publication. https://doi.org/10.1007/s11747-022-00908-0
   Web of Science ®Google Scholar
• Henseler, J., Ringle, C. M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science, 43(1), 115–135. https://doi.org/10.1007/s11747-014-0403-8
   Web of Science ®Google Scholar
• Hong, S.-J., Lui, C. S. M., Hahn, J., Moon, J. Y., & Kim, T. G. (2013). How old are you really? Cognitive age in technology acceptance. Decision Support Systems, 56(December), 122–130. https://doi.org/10.1016/j.dss.2013.05.008
   Google Scholar
• Hua, J., Chen, Y., & Luo, X. R. (2018). Are we ready for cyberterrorist attacks?—Examining the role of individual resilience. Information & Management, 55(7), 928–938. https://doi.org/10.1016/j.im.2018.04.008
   Web of Science ®Google Scholar
• Hudson, J. (2022). Virtual immersive shopping experiences in metaverse environments: Predictive customer analytics, data visualization algorithms, and smart retailing technologies. Linguistic and Philosophical Investigations, 2022(21), 236–251. https://doi.org/10.22381/lpi21202215
   Google Scholar
• Hwang, R., & Lee, M. (2022). The influence of music content marketing on user satisfaction and intention to use in the metaverse: A focus on the SPICE model. Businesses, 2(2), 141–155. https://doi.org/10.3390/businesses2020010
   Google Scholar
• Jenkins, T. (2022). Immersive virtual shopping experiences in the retail metaverse: Consumer-driven E-commerce, blockchain-based digital assets, and data visualization tools. Linguistic and Philosophical Investigations, 2022(21), 154–169. https://doi.org/10.22381/lpi21202210
   Google Scholar
• Kesharwani, A. (2020). Do (how) digital natives adopt a new technology differently than digital immigrants? A longitudinal study. Information & Management, 57(2), 103170. https://doi.org/10.1016/j.im.2019.103170
   Web of Science ®Google Scholar
• Kim, J. (2021). Advertising in the metaverse: Research agenda. Journal of Interactive Advertising, 21(3), 141–144. https://doi.org/10.1080/15252019.2021.2001273
   Google Scholar
• Kimiagari, S., & Malafe, N. S. A. (2021). The role of cognitive and affective responses in the relationship between internal and external stimuli on online impulse buying behavior. Journal of Retailing and Consumer Services, 61(July), 102567. https://doi.org/10.1016/j.jretconser.2021.102567
   Google Scholar
• Kishi, M. (2008). Perceptions and use of electronic media: Testing the relationship between organizational interpretation differences and media richness. Information & Management, 45(5), 281–287. https://doi.org/10.1016/j.im.2008.02.008
   Web of Science ®Google Scholar
• Kliestik, T., Novak, A., & Lăzăroiu, G. (2022). Live shopping in the metaverse: Visual and spatial analytics, cognitive artificial intelligence techniques and algorithms, and immersive digital simulations. Linguistic and Philosophical Investigations, 2022(21), 187–202. https://doi.org/10.22381/lpi21202212
   Google Scholar
• Komiak, S. Y. X., & Benbasat, I. (2006). The effects of personalization and familiarity on trust and adoption of recommendation agents. MIS Quarterly, 30(4), 941–960. https://doi.org/10.2307/25148760
   Web of Science ®Google Scholar
• Kraus, S., Kanbach, D. K., Krysta, P. M., Steinhoff, M. M., & Tomini, N. (2022). Facebook and the creation of the metaverse: Radical business model innovation or incremental transformation? International Journal of Entrepreneurial Behavior & Research, 28(9), 52–77. https://doi.org/10.1108/IJEBR-12-2021-0984
   Web of Science ®Google Scholar
• Kwak, D.-H., Lee, S., Ma, X., Lee, J., Lara, K., & Brandyberry, A. (2021). Announcement of formal controls as phase-shifting perceptions: Their determinants and moderating role in the context of mobile loafing. Internet Research, 31(5), 1874–1898. https://doi.org/10.1108/INTR-10-2020-0581
   Web of Science ®Google Scholar
• Lee, D. K. L., & Borah, P. (2020). Self-presentation on Instagram and friendship development among young adults: A moderated mediation model of media richness, perceived functionality, and openness. Computers in Human Behavior, 103(February), 57–66. https://doi.org/10.1016/j.chb.2019.09.017
   Google Scholar
• Lee, J., Lee, J.-N., & Tan, B. C. Y. (2015). Antecedents of cognitive trust and affective distrust and their mediating roles in building customer loyalty. Information Systems Frontiers, 17(1), 159–175. https://doi.org/10.1007/s10796-012-9392-7
   Web of Science ®Google Scholar
• Legood, A., van der Werff, L., Lee, A., den Hartog, D., & van Knippenberg, D. (2023). A critical review of the conceptualization, operationalization, and empirical literature on cognition‐based and affect‐based trust. Journal of Management Studies, 60(2), 495–537. https://doi.org/10.1111/joms.12811
   Web of Science ®Google Scholar
• Leong, L.-Y., Hew, T.-S., Ooi, K.-B., Chong, A. Y. L., & Lee, V.-H. (2021). Understanding trust in ms-commerce: The roles of reported experience, linguistic style, profile photo, emotional, and cognitive trust. Information & Management, 58(2), 103416. https://doi.org/10.1016/j.im.2020.103416
   Web of Science ®Google Scholar
• Li, K., Zhou, C., Luo, X. R., Benitez, J., & Liao, Q. (2022). Impact of information timeliness and richness on public engagement on social media during COVID-19 pandemic: An empirical investigation based on NLP and machine learning. Decision Support Systems, 162(November), 113752. https://doi.org/10.1016/j.dss.2022.113752
   PubMedGoogle Scholar
• Liang, J., Gao, Q., Li, W., Shi, Y., Shen, M., & Gao, Z. (2022). Personality Affects Dispositional Trust and History-Based Trust in Different Ways. International Journal of Human–Computer Interaction, 39(4), 949–960. https://doi.org/10.1080/10447318.2022.2055273
   Web of Science ®Google Scholar
• Liang, H., Xue, Y., Pinsonneault, A., & Wu, Y. A. (2019). What users do besides problem-focused coping when facing IT security threats: An emotion-focused coping perspective. MIS Quarterly, 43(2), 373–394. https://doi.org/10.25300/MISQ/2019/14360
   Web of Science ®Google Scholar
• McAllister, D. J. (1995). Affect-and cognition-based trust as foundations for interpersonal cooperation in organizations. Academy of Management Journal, 38(1), 24–59. https://doi.org/10.2307/256727
   Web of Science ®Google Scholar
• McKnight, D. H., Choudhury, V., & Kacmar, C. (2002). The impact of initial consumer trust on intentions to transact with a web site: A trust building model. The Journal of Strategic Information Systems, 11(3–4), 297–323. https://doi.org/10.1016/S0963-8687(02)00020-3
   Web of Science ®Google Scholar
• Miller, B. K., & Simmering, M. J. (2022). Attitude toward the color blue: An ideal marker variable. Organizational Research Methods. Advance online publication. https://doi.org/10.1177/10944281221075361
   PubMed Web of Science ®Google Scholar
• Mirzaei, T., & Esmaeilzadeh, P. (2021). Engagement in online health communities: Channel expansion and social exchanges. Information & Management, 58(1), 103404. https://doi.org/10.1016/j.im.2020.103404
   Web of Science ®Google Scholar
• Nica, E., Poliak, M., Popescu, G. H., & Pârvu, I.-A. (2022). Decision intelligence and modeling, multisensory customer experiences, and socially interconnected virtual services across the metaverse ecosystem. Linguistic and Philosophical Investigations, 2022(21), 137–153. https://doi.org/10.22381/lpi2120229
   Google Scholar
• Niehaves, B., & Plattfaut, R. (2014). Internet adoption by the elderly: Employing IS technology acceptance theories for understanding the age-related digital divide. European Journal of Information Systems, 23(6), 708–726. https://doi.org/10.1057/ejis.2013.19
   Web of Science ®Google Scholar
• Nix, N. (2022). Facebook is opening a physical store to show off its virtual gadgets. The Washington Post. https://www.washingtonpost.com/technology/2022/04/25/facebook-meta-store/
   Google Scholar
• Oh, H. J., Kim, J., Chang, J. J. C., Park, N., & Lee, S. (2023). Social benefits of living in the metaverse: The relationships among social presence, supportive interaction, social self-efficacy, and feelings of loneliness. Computers in Human Behavior, 139(February), 107498. https://doi.org/10.1016/j.chb.2022.107498
   Google Scholar
• Ollier-Malaterre, A., & Foucreault, A. (2021). When are social network sites connections with coworkers beneficial? The roles of age difference and preferences for segmentation between work and life. Journal of the Association for Information Systems, 22(5), 1454–1471. https://doi.org/10.17705/1jais.00699
   Web of Science ®Google Scholar
• Otondo, R. F., Van Scotter, J. R., Allen, D. G., & Palvia, P. (2008). The complexity of richness: Media, message, and communication outcomes. Information & Management, 45(1), 21–30. https://doi.org/10.1016/j.im.2007.09.003
   Web of Science ®Google Scholar
• Patil, K., & Pramod, D. (2022). Can Metaverse Retail lead to purchase intentions among the youth? A Stimulus-Organism-Response theory perspective [Paper presentation]. 2022 ASU International Conference in Emerging Technologies for Sustainability and Intelligent Systems (ICETSIS) (pp. 314–320). https://doi.org/10.1109/ICETSIS55481.2022.9888929
   Google Scholar
• Pavlou, P. A. (2002). Institution-based trust in interorganizational exchange relationships: The role of online B2B marketplaces on trust formation. The Journal of Strategic Information Systems, 11(3–4), 215–243. https://doi.org/10.1016/S0963-8687(02)00017-3
   Web of Science ®Google Scholar
• Podsakoff, P. M., MacKenzie, S. B., Lee, J.-Y., & Podsakoff, N. P. (2003). Common method biases in behavioral research: A critical review of the literature and recommended remedies. The Journal of Applied Psychology, 88(5), 879–903. https://doi.org/10.1037/0021-9010.88.5.879
   PubMed Web of Science ®Google Scholar
• Ronkko, M., Ylitalo, J. (2011). PLS marker variable approach to diagnosing and controlling for method variance [Paper presentation]. Proceedings of the 32nd International Conference on Information Systems. https://aisel.aisnet.org/icis2011/proceedings/researchmethods/8.
   Google Scholar
• Rospigliosi, P. (2022). Metaverse or Simulacra? Roblox, Minecraft, Meta and the turn to virtual reality for education, socialisation and work. Interactive Learning Environments, 30(1), 1–3. https://doi.org/10.1080/10494820.2022.2022899
   Web of Science ®Google Scholar
• Ryder, B. (2022). Taobao launches ‘Metaverse Mall’ in time for China’s 618 Shopping Festival. Jing Daily. https://jingdaily.com/taobao-launches-metaverse-mall-in-time-for-chinas-618-shopping-festival/
   Google Scholar
• Shao, Z., Benitez, J., Zhang, J., Zheng, H., & Ajamieh, A. (2022). Antecedents and performance outcomes of employees’ data analytics skills: An adaptation structuration theory-based empirical investigation. European Journal of Information Systems. Advance online publication. https://doi.org/10.1080/0960085X.2022.2078235
   PubMed Web of Science ®Google Scholar
• Shao, Z., & Yin, H. (2019). Building customers’ trust in the ridesharing platform with institutional mechanisms: An empirical study in China. Internet Research, 29(5), 1040–1063. https://doi.org/10.1108/INTR-02-2018-0086
   Web of Science ®Google Scholar
• Shao, Z., Zhang, L., Brown, S. A., & Zhao, T. (2022). Understanding users’ trust transfer mechanism in a blockchain-enabled platform: A mixed methods study. Decision Support Systems, 155(April), 113716. https://doi.org/10.1016/j.dss.2021.113716
   Google Scholar
• Shao, Z., Zhang, L., Li, X., & Guo, Y. (2019). Antecedents of trust and continuance intention in mobile payment platforms: The moderating effect of gender. Electronic Commerce Research and Applications, 33(January–February), 100823. https://doi.org/10.1016/j.elerap.2018.100823
   Google Scholar
• Shao, Z., Zhang, L., Li, X., & Zhang, R. (2022). Understanding the role of justice perceptions in promoting trust and behavioral intention towards ride-sharing. Electronic Commerce Research and Applications, 51(January–February), 101119. https://doi.org/10.1016/j.elerap.2022.101119
   Google Scholar
• Shen, X.-L., Li, Y.-J., Sun, Y., & Wang, F. (2021). Good for use, but better for choice: A relative model of competing social networking services. Information & Management, 58(3), 103448. https://doi.org/10.1016/j.im.2021.103448
   Web of Science ®Google Scholar
• Shin, D. (2022). The actualization of meta affordances: Conceptualizing affordance actualization in the metaverse games. Computers in Human Behavior, 133(August), 107292. https://doi.org/10.1016/j.chb.2022.107292
   Google Scholar
• Standish, J. (2022). Retailers, meet me in the metaverse. https://www.accenture.com/us-en/insights/retail/tech-vision
   Google Scholar
• Suh, K. S. (1999). Impact of communication medium on task performance and satisfaction: An examination of media-richness theory. Information & Management, 35(5), 295–312. https://doi.org/10.1016/S0378-7206(98)00097-4
   Web of Science ®Google Scholar
• Tams, S., Thatcher, J. B., & Grover, V. (2018). Concentration, competence, confidence, and capture: An experimental study of age, interruption-based technostress, and task performance. Journal of the Association for Information Systems, 19(9), 857–908. https://doi.org/10.17705/1jais.00511
   Web of Science ®Google Scholar
• Tan, T. M., & Saraniemi, S. (2022). Trust in blockchain-enabled exchanges: Future directions in blockchain marketing. Journal of the Academy of Marketing Science. Advance online publication. https://doi.org/10.1007/s11747-022-00889-0
   Web of Science ®Google Scholar
• Taylor, C. R. (2022). Research on advertising in the metaverse: A call to action. International Journal of Advertising, 41(3), 383–384. https://doi.org/10.1080/02650487.2022.2058786
   Web of Science ®Google Scholar
• Tong, Y., Wang, X., Tan, C.-H., & Teo, H.-H. (2013). An empirical study of information contribution to online feedback systems: A motivation perspective. Information & Management, 50(7), 562–570. https://doi.org/10.1016/j.im.2013.02.009
   Web of Science ®Google Scholar
• Trevino, L. K. (1992). Experimental approaches to studying ethical-unethical behavior in organizations. Business Ethics Quarterly, 2(2), 121–136. https://doi.org/10.2307/3857567
   Google Scholar
• Tseng, C.-H., & Wei, L.-F. (2020). The efficiency of mobile media richness across different stages of online consumer behavior. International Journal of Information Management, 50(February), 353–364. https://doi.org/10.1016/j.ijinfomgt.2019.08.010
   Google Scholar
• Vance, A., Siponen, M., & Pahnila, S. (2012). Motivating IS security compliance: Insights from habit and protection motivation theory. Information & Management, 49(3–4), 190–198. https://doi.org/10.1016/j.im.2012.04.002
   Web of Science ®Google Scholar
• Wang, W., Qiu, L., Kim, D., & Benbasat, I. (2016). Effects of rational and social appeals of online recommendation agents on cognition-and affect-based trust. Decision Support Systems, 86(June), 48–60. https://doi.org/10.1016/j.dss.2016.03.007
   Google Scholar
• Wang, N., Shen, X.-L., & Sun, Y. (2013). Transition of electronic word-of-mouth services from web to mobile context: A trust transfer perspective. Decision Support Systems, 54(3), 1394–1403. https://doi.org/10.1016/j.dss.2012.12.015
   Web of Science ®Google Scholar
• Wang, X., Xu, Y. C., Lu, T., & Zhang, C. (2020). Why do borrowers default on online loans? An inquiry of their psychology mechanism. Internet Research, 30(4), 1203–1228. https://doi.org/10.1108/INTR-05-2019-0183
   Web of Science ®Google Scholar
• Wongkitrungrueng, A., & Suprawan, L. (2023). Metaverse Meets Branding: Examining Consumer Responses to Immersive Brand Experiences. International Journal of Human–Computer Interaction. Advance online publication. https://doi.org/10.1080/10447318.2023.2175162
   Web of Science ®Google Scholar
• Wu, W., Wang, S., Ding, G., & Mo, J. (2023). Elucidating trust-building sources in social shopping: A consumer cognitive and emotional trust perspective. Journal of Retailing and Consumer Services, 71(March), 103217. https://doi.org/10.1016/j.jretconser.2022.103217
   Google Scholar
• Xi, N., Chen, J., Gama, F., Riar, M., & Hamari, J. (2022). The challenges of entering the metaverse: An experiment on the effect of extended reality on workload. Information Systems Frontiers. Advance online publication. https://doi.org/10.1007/s10796-022-10244-x
   PubMed Web of Science ®Google Scholar
• Yoo, Y., & Alavi, M. (2001). Media and group cohesion: Relative influences on social presence, task participation, and group consensus. MIS Quarterly, 25(3), 371–390. https://doi.org/10.2307/3250922
   Web of Science ®Google Scholar
• Zhang, K. Z. K., Cheung, C. M. K., & Lee, M. K. O. (2014). Examining the moderating effect of inconsistent reviews and its gender differences on consumers’ online shopping decision. International Journal of Information Management, 34(2), 89–98. https://doi.org/10.1016/j.ijinfomgt.2013.12.001
   Web of Science ®Google Scholar
• Zhang, S., & Leidner, D. (2018). From improper to acceptable: How perpetrators neutralize workplace bullying behaviors in the cyber world. Information & Management, 55(7), 850–865. https://doi.org/10.1016/j.im.2018.03.012
   Web of Science ®Google Scholar
• Zhang, L., Shao, Z., Li, X., & Feng, Y. (2021). Gamification and online impulse buying: The moderating effect of gender and age. International Journal of Information Management, 61(December), 102267. https://doi.org/10.1016/j.ijinfomgt.2020.102267
   Google Scholar
• Zhang, L., Wang, Y., Anjum, M. A., & Mu, J. (2022). The impacts of point rewarding and exchanging on users’ loyalty toward mobile payment applications: A dual channeling perspective. Internet Research, 32(6), 1832–1861. https://doi.org/10.1108/INTR-06-2021-0414
   Web of Science ®Google Scholar
• Zhu, L., Benbasat, I., & Jiang, Z. (2010). Let’s shop online together: An empirical investigation of collaborative online shopping support. Information Systems Research, 21(4), 872–891. https://doi.org/10.1287/isre.1080.0218
   Web of Science ®Google Scholar
• Zvarikova, K., Machova, V., & Nica, E. (2022). Cognitive artificial intelligence algorithms, movement and behavior tracking tools, and customer identification technology in the metaverse commerce. Review of Contemporary Philosophy, 2022(21), 171–187. https://doi.org/10.22381/RCP21202211
   Google Scholar