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USER ACCEPTANCE OF VIRTUAL COMMERCE ON METAVERSE INSIGHTS FROM INNOVATION DIFFUSION THEORY (IDT) AND TECHNOLOGY ACCEPTANCE MODEL

Year 2024, Volume: 11 Issue: 24, 23 - 42, 27.04.2024

Ayben Ceyhan Günay Yavuz Toraman

https://doi.org/10.58884/akademik-hassasiyetler.1345212

Abstract

In recent years, technological advancements have also influenced consumer behavior. One of the most significant developments in this regard is the metaverse. The metaverse, which has frequently captured the interest of experts, is a technological system that forms the basis of the current research. In this context, the present study examines the factors that affect the intention to use and acceptance of the metaverse system. The study constructs a research model using the Innovation Diffusion Theory (IDT) and the Technology Acceptance Model (TAM) to investigate user acceptance of conducting e-commerce activities within the metaverse system. Within this framework, structural equation modeling has been utilized to explain the acceptance of usage by potential metaverse users. The proposed research model has been analyzed using the Smart PLS 3 software package.
Among the independent variables of the research, a positive and significant relationship has been found between relative advantage as a mediator and the main variables of TAM. However, no significant relationship has been identified between complexity, another independent variable, and the main variables of TAM. Additionally, a significant relationship has been established between perceived compatibility and perceived ease of use. In this context, from a consumer perspective, when evaluated experientially (effort expended), the shopping experience in the metaverse system shows similarities with physical shopping, while no relationship has been found in terms of performance. The most significant contribution of the research to the literature is that attitude and intention, which are the most important antecedents of active usage of metaverse systems, exhibit a positive and significant relationship with all the variables in the relationship.

Keywords

Metaverse Innovation Diffusion Theory Technology Acceptance Model E-commerce Digital Marketing

References

  • Al-Jabri, I. M. & Sohail, M. S. (2012). Mobile banking adoption: Application of diffusion of innovation theory. Journal of Electronic Commerce Research, 13(4), 379-391.
  • Barrera, K. G. & Shah, D. (2023). Marketing in the Metaverse: Conceptual understanding, framework, and research agenda. Journal of Business Research, 155,1-19. https://doi.org/10.1016/j.jbusres.2022.113420.
  • Chang, S. C. & Tung, F. C. (2008). An empirical investigation of students' behavioral intentions to use online learning course websites. British Journal of Educational Technology, 39(1), 71-83. https://doi.org/10.1111/j.1467-8535.2007.00742.x.
  • Dawson, A. (2022). Data-driven consumer engagement, virtual ımmersive shopping experiences, and blockchain-based digital assets in the retail Metaverse. Journal of Self-Governance & Management Economics, 10(2). https://doi.org/10.22381/jsme10220224.
  • Dionisio, J. D., Burns III, W. G. & Gilbert, R. (2013). 3d virtual worlds and the Metaverse: current status and future possibilities. ACM Computing Surveys, 45(3), 33-38. http://dx.doi.org/10.1145/2480741.2480751.
  • Duman, O. (2022, February 10). Metaverse: the future of e-commerce. AR/VR Journey. Retrieved on 2023, May 21 from https://arvrjourney.com/metaverse-the-future-of-the-ecommerce-65d5581e0790.
  • Dwivedi, Y. K., Hughes, L., Wang, Y., Alalwan, A. A., Ahn, S. J., Balakrishnan, J. & Wirtz, J. (2023). Metaverse marketing: How the metaverse will shape the future of consumer research and practice. Psychology & Marketing, 40(4), 750-776. https://doi.org/10.1002/mar.21767.
  • Esmaeilpour, M. & Mohseni, Z. (2019). Effect of customer experiences on consumer purchase intention. Romanian Economic Journal, (73), 19-38.
  • García‐Avilés, J. A. (2020). Diffusion of innovation. The International Encyclopedia of Media Psychology, 1-8. https://doi.org/10.1002/9781119011071.iemp0137.
  • Hacialioğlu, A. & Sağlam, M. (2021). COVID-19 pandemi sürecinde tüketici davranışları ve e-ticaretteki değişimler. Medya ve Kültürel Çalışmalar Dergisi, 3(1), 16-29. https://doi.org/10.29228/mekcad.2.
  • Hair, J. F., Hult, G. T., Ringle, C. M. & Sarstedt, M. (2017). A primer on partial least squares structural equation modeling (Pls-Sem) (2. nd Ed.) Los Angeles: Sage Publication.
  • Hair, J. F., William C. B., Barry J. B. & Rolph E. A (2010). "Multivariate Data Analysis", 7th ed., Pearson Education. (2010).
  • Hardgrave, B. C., Davis, F. D. & Riemenschneider, C. K. (2003). Investigating determinants of software developers' intentions to follow methodologies. Journal of Management Information Systems, 20(1), 123-151. https://doi.org/10.1080/07421222.2003.11045751.
  • Hassouneh, D. & Brengman, M. (2015). Retailing in social virtual worlds: developing a typology of virtual store atmospherics. Journal of Electronic Commerce Research, 16(3), 218-241.
  • Hollensen, S., Kotler, P. & Opresnik, M. O. (2022). Metaverse–the new marketing universe. Journal of Business Strategy. https://doi.org/10.1108/JBS-01-2022-0014.
  • Khatri, M. (2022). Revamping the marketing world with metaverse–The future of marketing. International Journal of Computer Applications, 975(29), 8887. https://doi.org/10.5120/ijca2022922361.
  • 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 Behaviour and Research. https://doi.org/10.1108/IJEBR-12-2021-0984.
  • Kuntze, R., Crudele, T. R., Reynolds, D. & Matulich, E. (2013). The rise and fall of virtual reality retailing in second life: an avatar’s perspective. Journal of Management and Marketing Research, 1-13.
  • Lee, L. H., Lin, Z., Hu, R., Gong, Z., Kumar, A., Li, T., & Hui, P. (2021). When creators meet the metaverse: A survey on computational arts. ACM Computing Surveys, 37(4), 111-137, https://doi.org/10.1145/1122445.1122456
  • Laudon, K. & Traver, C. (2016). E-commerce: Business, technology, society. London: Pearson.
  • Lee, Y. H. (2007). Exploring key factors that affect consumers to adopt e-reading services. [master thesis]. Huafan University.
  • Linden Lab. (2018, June 20). Infographic: 10 Years of Second Life, Retrieved on 2023, September 4 from https://lindenlab.com/press-release/infographic-10-years-of-second-life
  • Ning, H., Wang, H., Lin, Y., Wang, W., Dhelim, S., Farha, F., ... & Daneshmand, M. (2023). A Survey on the Metaverse: The State-of-the-Art, Technologies, Applications, and Challenges. IEEE Internet of Things Journal. https://doi.org/10.48550/arXiv.2111.09673.
  • Oxford Analytica. (2022). Metaverse holds unknowable societal risks. Emerald Expert Briefings, (oxen-db).
  • Pamucar, D., Deveci, M., Gokasar, I., Tavana, M. & Köppen, M. (2022). A Metaverse assessment model for sustainable transportation using ordinal priority approach and Aczel-Alsina norms. Technological Forecasting and Social Change, 182, 1-18. https://doi.org/10.1016/j.techfore.2022.121778.
  • Ramadan, Z. (2023). Marketing in the metaverse era: toward an integrative channel approach. Virtual Reality, 1-14. https://doi.org/10.1007/s10055-023-00783-2
  • Rogers, E. M. (2002). Diffusion of preventive innovations. Addictive behaviors, 27(6), 989-993. https://doi.org/10.1016/S0306-4603(02)00300-3
  • Rogers, E. M. (2003). Diffusion of innovations (5th ed.). New York, NY: Free Press.
  • Rogers, E. M., Singhal, A. & Quinlan, M. M. (2014). Diffusion of innovations. In An integrated approach to communication theory and research (pp. 432-448). Routledge.
  • Rathore, B. (2018). Metaverse marketing: novel challenges, opportunities, and strategic approaches. Eduzone: International Peer Reviewed/Refereed Multidisciplinary Journal, 7(2), 72-82.
  • Shah, D. & Murthi, B. P. S. (2021). Marketing in a data-driven digital world: Implications for the role and scope of marketing. J. Bus. Res., 125(March), 772–779. https://doi.org/10.1016/j.jbusres.2020.06.062
  • Shen, B., Tan, W., Guo, J., Zhao, L. & Qin, P. (2021). How to promote user purchase in Metaverse? A systematic literature review on consumer behavior research and virtual commerce application design. Applied Sciences, 11(23), 11087. https://doi.org/10.3390/app112311087
  • Shih, C. H. (2007). Integrating Innovation Diffusion Theory and UTAUT to explore the influencing factors on teacher adopt e-learning system–with MOODLE as an example. Unpublished Master Thesis, Dayeh University.
  • Surry, D. W. & Farquhar, J. D. (1997). Diffusion theory and instructional technology. Journal of Instructional Science and Technology, 2(1), 24-36.
  • Tabachnick, B. G. & Fidell, L. S. (2007). Using Multivariate Statistics (5th ed). Boston: Pearson Education Inc.
  • Toraman, Y. (2022). User acceptance of metaverse: Insights from technology acceptance model (TAM) and planned behavior theory (PBT). EMAJ: Emerging Markets Journal, 12(1), 67-75. https://doi.org/10.5195/emaj.2022.258
  • Toraman, Y., Merdivenci, F. & Tekin, M. (2023). Son kilometre (adım) teslimatta blokzincir teknolojisinin kullanımı. Cumhuriyet Üniversitesi İktisadi ve İdari Bilimler Dergisi, 24(1), 159-169. https://doi.org/10.37880/cumuiibf.1195981
  • Toraman, Y. & Geçit, B. B. (2023). User acceptance of metaverse: an analysis for e-commerce in the framework of technology acceptance model (TAM). Sosyoekonomi, 31(55), 85-104. https://doi.org/10.17233/sosyoekonomi.2023.01.05
  • Toraman, Y. & Yüksel, C. (2022). COVID-19 Salgını Sürecinde Tüketicilerin Yeni Teknolojileri Benimsemelerinin Teknoloji Kabul Modeli (TKM) Çerçevesinde Temassız Teslimat Özelinde İncelenmesi: Mobil Uygulamalar Üzerine Bir Araştırma. Doğuş Üniversitesi Dergisi, 23 (Covid-19 özel sayısı), 17-34. https://doi.org/10.31671/doujournal.928518
  • Tornatzky, L. G. & Klein, K. J. (1982). Innovation characteristics and innovation adoption-implementation: A meta-analysis of findings. IEEE Transactions on Engineering Management, (1), 28-45. https://doi.org/10.1109/TEM.1982.6447463
  • Usas, A., Jasinskas, E., Antoniuk, V. Z., Savitskyi, V. & Fuhelo, P. (2021). COVID-19 Impact on E. Commerce usage. Independent Journal of Management & Production, 12(6), 445-462. https://doi.org/10.14807/ijmp.v12i6.1750
  • Venkatesh, V. & Davis, F. D. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management Science, 46(2), 186-204.
  • Venkatesh, V. & Morris, M. G. (2000). Why don't men ever stop to ask for directions? Gender, social influence, and their role in technology acceptance and usage behavior. MIS Quarterly, 115-139.
  • Wang, Y., Su, Z., Zhang, N., Xing, R., Liu, D., Luan, T. H. & Shen, X. (2022). A Survey on Metaverse: Fundamentals, Security, and Privacy. IEEE Communications Surveys & Tutorials. https://doi: 10.1109/COMST.2022.320204.
  • Wani, T. A. & Ali, S. W. (2015). Innovation diffusion theory. Journal of General Management Research, 3(2), 101-118.
  • Yang, Q., Zhao, Y., Huang, H., Xiong, Z., Kang, J. & Zheng, Z. (2022). Fusing blockchain and AI with metaverse: A survey. IEEE Open Journal of the Computer Society, 3, 122-136. https://doi.org/10.1109/OJCS.2022.3188249
  • Ying, L. & Mengqing, S. (2011). Literature analysis of innovation diffusion. Technology and Investment, 2011. https://doi.org/10.4236/ti.2011.23016
  • Yuen, K. F., Cai, L., Qi, G. & Wang, X. (2021). Factors influencing autonomous vehicle adoption: An application of the technology acceptance model and innovation diffusion theory. Technology Analysis & Strategic Management, 33(5), 505-519. https://doi.org/10.1080/09537325.2020.1826423

METAVERSE’TE SANAL TİCARETİN KULLANICI KABULÜ: YENİLİKLERİN YAYILMASI TEORİSİ (YYT) VE TEKNOLOJİ KABUL MODELİ (TKM) ÇERÇEVESİNDE İNCELENMESİ

Year 2024, Volume: 11 Issue: 24, 23 - 42, 27.04.2024

Ayben Ceyhan Günay Yavuz Toraman

https://doi.org/10.58884/akademik-hassasiyetler.1345212

Abstract

Son yıllarda teknolojideki gelişmeler tüketici davranışını da etkilemektedir. Söz konusu teknolojik gelişmelerden en önemlilerinden biri de metaverse’tür. Uzmanlar tarafından sıklıkla merak konusu olan metaverse, mevcut araştırmanın temelini oluşturan teknolojik sistemdir. Bu bağlamda mevcut çalışma, metaverse sistemini kullanma niyetini ve kabulünü etkileyen faktörleri incelemektedir. Çalışmada, yeniliklerin yayılması teorisi (YYT) ve teknoloji kabul modeli (TKM) kullanılarak bir araştırma modeli oluşturulmuş ve metaverse sisteminde e-ticaret faaliyetlerinin gerçekleştirilmesinin kullanıcı kabulü incelenmiştir. Bu bağlamda yapısal eşitlik modellemesi ile potansiyel metaverse kullanıcıları tarafından kullanımın kabulü açıklanmaya çalışılmıştır. Önerilen araştırma modeli Smart PLS 3 paket programı ile analiz edilmiştir.
Araştırmanın bağımsız değişkenlerinden göreceli avantajın aracı TKM’nin ana değişkenleriyle arasında pozitif ve anlamlı bir ilişki bulunmuştur. Fakat diğer bir bağımsız değişken olan karmaşıklık ile TKM’nin ana değişkenleriyle arasında anlamlı bir ilişki bulunamamıştır. Ayrıca algılanan uyumluluk ile algılanan kullanım kolaylığı arasında anlamlı bir ilişki bulunmuştur. Bu kapsamda tüketici açısından deneyimsel olarak (harcanan çaba) değerlendirildiğinde fiziksel alışverişle metaverse sistemindeki alışveriş deneyimi benzerlik gösterirken, performans açısından bir ilişki bulunamamıştır. Metaverse sistemlerinin aktif kullanımının en önemli öncülleri olan tutum ve niyetin, ilişkide olduğu değişkenlerin tamamıyla pozitif ve anlamlı bir ilişki içinde olması ise araştırmanın literatüre en önemli katkısıdır.

Keywords

Metaverse Yeniliklerin Yayılması Teorisi Teknoloji Kabul Modeli E-Ticaret Dijital Pazarlama

References

  • Al-Jabri, I. M. & Sohail, M. S. (2012). Mobile banking adoption: Application of diffusion of innovation theory. Journal of Electronic Commerce Research, 13(4), 379-391.
  • Barrera, K. G. & Shah, D. (2023). Marketing in the Metaverse: Conceptual understanding, framework, and research agenda. Journal of Business Research, 155,1-19. https://doi.org/10.1016/j.jbusres.2022.113420.
  • Chang, S. C. & Tung, F. C. (2008). An empirical investigation of students' behavioral intentions to use online learning course websites. British Journal of Educational Technology, 39(1), 71-83. https://doi.org/10.1111/j.1467-8535.2007.00742.x.
  • Dawson, A. (2022). Data-driven consumer engagement, virtual ımmersive shopping experiences, and blockchain-based digital assets in the retail Metaverse. Journal of Self-Governance & Management Economics, 10(2). https://doi.org/10.22381/jsme10220224.
  • Dionisio, J. D., Burns III, W. G. & Gilbert, R. (2013). 3d virtual worlds and the Metaverse: current status and future possibilities. ACM Computing Surveys, 45(3), 33-38. http://dx.doi.org/10.1145/2480741.2480751.
  • Duman, O. (2022, February 10). Metaverse: the future of e-commerce. AR/VR Journey. Retrieved on 2023, May 21 from https://arvrjourney.com/metaverse-the-future-of-the-ecommerce-65d5581e0790.
  • Dwivedi, Y. K., Hughes, L., Wang, Y., Alalwan, A. A., Ahn, S. J., Balakrishnan, J. & Wirtz, J. (2023). Metaverse marketing: How the metaverse will shape the future of consumer research and practice. Psychology & Marketing, 40(4), 750-776. https://doi.org/10.1002/mar.21767.
  • Esmaeilpour, M. & Mohseni, Z. (2019). Effect of customer experiences on consumer purchase intention. Romanian Economic Journal, (73), 19-38.
  • García‐Avilés, J. A. (2020). Diffusion of innovation. The International Encyclopedia of Media Psychology, 1-8. https://doi.org/10.1002/9781119011071.iemp0137.
  • Hacialioğlu, A. & Sağlam, M. (2021). COVID-19 pandemi sürecinde tüketici davranışları ve e-ticaretteki değişimler. Medya ve Kültürel Çalışmalar Dergisi, 3(1), 16-29. https://doi.org/10.29228/mekcad.2.
  • Hair, J. F., Hult, G. T., Ringle, C. M. & Sarstedt, M. (2017). A primer on partial least squares structural equation modeling (Pls-Sem) (2. nd Ed.) Los Angeles: Sage Publication.
  • Hair, J. F., William C. B., Barry J. B. & Rolph E. A (2010). "Multivariate Data Analysis", 7th ed., Pearson Education. (2010).
  • Hardgrave, B. C., Davis, F. D. & Riemenschneider, C. K. (2003). Investigating determinants of software developers' intentions to follow methodologies. Journal of Management Information Systems, 20(1), 123-151. https://doi.org/10.1080/07421222.2003.11045751.
  • Hassouneh, D. & Brengman, M. (2015). Retailing in social virtual worlds: developing a typology of virtual store atmospherics. Journal of Electronic Commerce Research, 16(3), 218-241.
  • Hollensen, S., Kotler, P. & Opresnik, M. O. (2022). Metaverse–the new marketing universe. Journal of Business Strategy. https://doi.org/10.1108/JBS-01-2022-0014.
  • Khatri, M. (2022). Revamping the marketing world with metaverse–The future of marketing. International Journal of Computer Applications, 975(29), 8887. https://doi.org/10.5120/ijca2022922361.
  • 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 Behaviour and Research. https://doi.org/10.1108/IJEBR-12-2021-0984.
  • Kuntze, R., Crudele, T. R., Reynolds, D. & Matulich, E. (2013). The rise and fall of virtual reality retailing in second life: an avatar’s perspective. Journal of Management and Marketing Research, 1-13.
  • Lee, L. H., Lin, Z., Hu, R., Gong, Z., Kumar, A., Li, T., & Hui, P. (2021). When creators meet the metaverse: A survey on computational arts. ACM Computing Surveys, 37(4), 111-137, https://doi.org/10.1145/1122445.1122456
  • Laudon, K. & Traver, C. (2016). E-commerce: Business, technology, society. London: Pearson.
  • Lee, Y. H. (2007). Exploring key factors that affect consumers to adopt e-reading services. [master thesis]. Huafan University.
  • Linden Lab. (2018, June 20). Infographic: 10 Years of Second Life, Retrieved on 2023, September 4 from https://lindenlab.com/press-release/infographic-10-years-of-second-life
  • Ning, H., Wang, H., Lin, Y., Wang, W., Dhelim, S., Farha, F., ... & Daneshmand, M. (2023). A Survey on the Metaverse: The State-of-the-Art, Technologies, Applications, and Challenges. IEEE Internet of Things Journal. https://doi.org/10.48550/arXiv.2111.09673.
  • Oxford Analytica. (2022). Metaverse holds unknowable societal risks. Emerald Expert Briefings, (oxen-db).
  • Pamucar, D., Deveci, M., Gokasar, I., Tavana, M. & Köppen, M. (2022). A Metaverse assessment model for sustainable transportation using ordinal priority approach and Aczel-Alsina norms. Technological Forecasting and Social Change, 182, 1-18. https://doi.org/10.1016/j.techfore.2022.121778.
  • Ramadan, Z. (2023). Marketing in the metaverse era: toward an integrative channel approach. Virtual Reality, 1-14. https://doi.org/10.1007/s10055-023-00783-2
  • Rogers, E. M. (2002). Diffusion of preventive innovations. Addictive behaviors, 27(6), 989-993. https://doi.org/10.1016/S0306-4603(02)00300-3
  • Rogers, E. M. (2003). Diffusion of innovations (5th ed.). New York, NY: Free Press.
  • Rogers, E. M., Singhal, A. & Quinlan, M. M. (2014). Diffusion of innovations. In An integrated approach to communication theory and research (pp. 432-448). Routledge.
  • Rathore, B. (2018). Metaverse marketing: novel challenges, opportunities, and strategic approaches. Eduzone: International Peer Reviewed/Refereed Multidisciplinary Journal, 7(2), 72-82.
  • Shah, D. & Murthi, B. P. S. (2021). Marketing in a data-driven digital world: Implications for the role and scope of marketing. J. Bus. Res., 125(March), 772–779. https://doi.org/10.1016/j.jbusres.2020.06.062
  • Shen, B., Tan, W., Guo, J., Zhao, L. & Qin, P. (2021). How to promote user purchase in Metaverse? A systematic literature review on consumer behavior research and virtual commerce application design. Applied Sciences, 11(23), 11087. https://doi.org/10.3390/app112311087
  • Shih, C. H. (2007). Integrating Innovation Diffusion Theory and UTAUT to explore the influencing factors on teacher adopt e-learning system–with MOODLE as an example. Unpublished Master Thesis, Dayeh University.
  • Surry, D. W. & Farquhar, J. D. (1997). Diffusion theory and instructional technology. Journal of Instructional Science and Technology, 2(1), 24-36.
  • Tabachnick, B. G. & Fidell, L. S. (2007). Using Multivariate Statistics (5th ed). Boston: Pearson Education Inc.
  • Toraman, Y. (2022). User acceptance of metaverse: Insights from technology acceptance model (TAM) and planned behavior theory (PBT). EMAJ: Emerging Markets Journal, 12(1), 67-75. https://doi.org/10.5195/emaj.2022.258
  • Toraman, Y., Merdivenci, F. & Tekin, M. (2023). Son kilometre (adım) teslimatta blokzincir teknolojisinin kullanımı. Cumhuriyet Üniversitesi İktisadi ve İdari Bilimler Dergisi, 24(1), 159-169. https://doi.org/10.37880/cumuiibf.1195981
  • Toraman, Y. & Geçit, B. B. (2023). User acceptance of metaverse: an analysis for e-commerce in the framework of technology acceptance model (TAM). Sosyoekonomi, 31(55), 85-104. https://doi.org/10.17233/sosyoekonomi.2023.01.05
  • Toraman, Y. & Yüksel, C. (2022). COVID-19 Salgını Sürecinde Tüketicilerin Yeni Teknolojileri Benimsemelerinin Teknoloji Kabul Modeli (TKM) Çerçevesinde Temassız Teslimat Özelinde İncelenmesi: Mobil Uygulamalar Üzerine Bir Araştırma. Doğuş Üniversitesi Dergisi, 23 (Covid-19 özel sayısı), 17-34. https://doi.org/10.31671/doujournal.928518
  • Tornatzky, L. G. & Klein, K. J. (1982). Innovation characteristics and innovation adoption-implementation: A meta-analysis of findings. IEEE Transactions on Engineering Management, (1), 28-45. https://doi.org/10.1109/TEM.1982.6447463
  • Usas, A., Jasinskas, E., Antoniuk, V. Z., Savitskyi, V. & Fuhelo, P. (2021). COVID-19 Impact on E. Commerce usage. Independent Journal of Management & Production, 12(6), 445-462. https://doi.org/10.14807/ijmp.v12i6.1750
  • Venkatesh, V. & Davis, F. D. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management Science, 46(2), 186-204.
  • Venkatesh, V. & Morris, M. G. (2000). Why don't men ever stop to ask for directions? Gender, social influence, and their role in technology acceptance and usage behavior. MIS Quarterly, 115-139.
  • Wang, Y., Su, Z., Zhang, N., Xing, R., Liu, D., Luan, T. H. & Shen, X. (2022). A Survey on Metaverse: Fundamentals, Security, and Privacy. IEEE Communications Surveys & Tutorials. https://doi: 10.1109/COMST.2022.320204.
  • Wani, T. A. & Ali, S. W. (2015). Innovation diffusion theory. Journal of General Management Research, 3(2), 101-118.
  • Yang, Q., Zhao, Y., Huang, H., Xiong, Z., Kang, J. & Zheng, Z. (2022). Fusing blockchain and AI with metaverse: A survey. IEEE Open Journal of the Computer Society, 3, 122-136. https://doi.org/10.1109/OJCS.2022.3188249
  • Ying, L. & Mengqing, S. (2011). Literature analysis of innovation diffusion. Technology and Investment, 2011. https://doi.org/10.4236/ti.2011.23016
  • Yuen, K. F., Cai, L., Qi, G. & Wang, X. (2021). Factors influencing autonomous vehicle adoption: An application of the technology acceptance model and innovation diffusion theory. Technology Analysis & Strategic Management, 33(5), 505-519. https://doi.org/10.1080/09537325.2020.1826423
There are 48 citations in total.

Details

Primary Language English
Subjects Business Administration
Journal Section Tüm Sayı
Authors

Ayben Ceyhan Günay 0000-0001-5191-9787

Yavuz Toraman 0000-0002-5196-1499

Publication Date April 27, 2024
Submission Date August 18, 2023
Published in Issue Year 2024 Volume: 11 Issue: 24

Cite

APA Ceyhan Günay, A., & Toraman, Y. (2024). USER ACCEPTANCE OF VIRTUAL COMMERCE ON METAVERSE INSIGHTS FROM INNOVATION DIFFUSION THEORY (IDT) AND TECHNOLOGY ACCEPTANCE MODEL. Akademik Hassasiyetler, 11(24), 23-42. https://doi.org/10.58884/akademik-hassasiyetler.1345212
AMA Ceyhan Günay A, Toraman Y. USER ACCEPTANCE OF VIRTUAL COMMERCE ON METAVERSE INSIGHTS FROM INNOVATION DIFFUSION THEORY (IDT) AND TECHNOLOGY ACCEPTANCE MODEL. Akademik Hassasiyetler. April 2024;11(24):23-42. doi:10.58884/akademik-hassasiyetler.1345212
Chicago Ceyhan Günay, Ayben, and Yavuz Toraman. “USER ACCEPTANCE OF VIRTUAL COMMERCE ON METAVERSE INSIGHTS FROM INNOVATION DIFFUSION THEORY (IDT) AND TECHNOLOGY ACCEPTANCE MODEL”. Akademik Hassasiyetler 11, no. 24 (April 2024): 23-42. https://doi.org/10.58884/akademik-hassasiyetler.1345212.
EndNote Ceyhan Günay A, Toraman Y (April 1, 2024) USER ACCEPTANCE OF VIRTUAL COMMERCE ON METAVERSE INSIGHTS FROM INNOVATION DIFFUSION THEORY (IDT) AND TECHNOLOGY ACCEPTANCE MODEL. Akademik Hassasiyetler 11 24 23–42.
IEEE A. Ceyhan Günay and Y. Toraman, “USER ACCEPTANCE OF VIRTUAL COMMERCE ON METAVERSE INSIGHTS FROM INNOVATION DIFFUSION THEORY (IDT) AND TECHNOLOGY ACCEPTANCE MODEL”, Akademik Hassasiyetler, vol. 11, no. 24, pp. 23–42, 2024, doi: 10.58884/akademik-hassasiyetler.1345212.
ISNAD Ceyhan Günay, Ayben - Toraman, Yavuz. “USER ACCEPTANCE OF VIRTUAL COMMERCE ON METAVERSE INSIGHTS FROM INNOVATION DIFFUSION THEORY (IDT) AND TECHNOLOGY ACCEPTANCE MODEL”. Akademik Hassasiyetler 11/24 (April 2024), 23-42. https://doi.org/10.58884/akademik-hassasiyetler.1345212.
JAMA Ceyhan Günay A, Toraman Y. USER ACCEPTANCE OF VIRTUAL COMMERCE ON METAVERSE INSIGHTS FROM INNOVATION DIFFUSION THEORY (IDT) AND TECHNOLOGY ACCEPTANCE MODEL. Akademik Hassasiyetler. 2024;11:23–42.
MLA Ceyhan Günay, Ayben and Yavuz Toraman. “USER ACCEPTANCE OF VIRTUAL COMMERCE ON METAVERSE INSIGHTS FROM INNOVATION DIFFUSION THEORY (IDT) AND TECHNOLOGY ACCEPTANCE MODEL”. Akademik Hassasiyetler, vol. 11, no. 24, 2024, pp. 23-42, doi:10.58884/akademik-hassasiyetler.1345212.
Vancouver Ceyhan Günay A, Toraman Y. USER ACCEPTANCE OF VIRTUAL COMMERCE ON METAVERSE INSIGHTS FROM INNOVATION DIFFUSION THEORY (IDT) AND TECHNOLOGY ACCEPTANCE MODEL. Akademik Hassasiyetler. 2024;11(24):23-42.
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MAKALE DEĞERLENDİRME SÜRECİ

Yazar tarafından gönderilen bir makale, gönderim tarihinden itibaren 10 gün içinde dergi sekreteri tarafından makalenin, telif sözleşmesinin ve benzerlik raporunun (Turnitin programı) eksiksiz ve düzgün bir şekilde gönderilip gönderilmediği yönünden incelenir. İstenilen bu dosyalar eksiksiz ve düzgün bir şekilde gönderilmiş ise makale; ikinci aşamada derginin yayın çizgisine uygun olup olmadığı yönünden değerlendirilir. Bu süreçte makale yayın çizgisine uygun değilse yazara iade edilir. Makale yayın çizgisine uygun ise şablona uygun bir şekilde gönderilip gönderilmediği yönünden değerlendirilir. Şayet makale şablona uyarlanıp gönderilmemiş ise değerlendirme sürecine alınmaz. Bu süreçte yazarın derginin belirlediği şartlara uygun bir şekilde sisteme makale yüklemesi beklenir. Makale şablona uygun bir şekilde hazırlanıp gönderilmiş ise son aşamada makale derginin yayın ilkeleri, yazım kuralları, öz, abstract, extented abstract, kaynakça gösterimi vb. yönlerden incelenir. Bu ayrıntılarda makalede bir sorun varsa yazarın bu hususları tamamlaması istenir ve verilen süre içerisinde eksiksiz bir şekilde yeniden makaleyi göndermesi istenir.
Tüm bu aşamaları geçen makale, editör tarafından bilimsel yeterliliğinin denetlenmesi amacıyla ikinci 7 günlük süre içerisinde çalışmaya uygun iki hakeme değerlendirmeleri için gönderilir. Hakemlerin değerlendirme süreleri 15 gündür. Bu süre zarfında hakemlik görevini tamamlamayan bir hakem olursa ilgili hakeme değerlendirmeyi tamamlaması için 7 günlük ek süre verilebilir. Bu süre zarfında hakem görevini yerine getirmezse yerine yeni bir hakem ataması yapılır. En az iki hakemden gelen raporlar olumlu ise makale yayın aşamasına alınır. Hakem raporlarından birisi olumlu diğeri olumsuz ise makale üçüncü bir hakeme gönderilir. Üçüncü hakem raporu da olumsuz ise makale ret edilir. Üçüncü hakemin değerlendirmesi olumlu ise makaleyle ilgili hakem raporları dergi alan editörlerinden oluşan Editörler Kurulu tarafından incelenir. Makalenin yayınlanmasıyla ilgili nihai karar alan editörlerinden oluşan Editörler Kurulu tarafından verilir. Hakem raporlarının yetersiz ve tatmin etmekten uzak olması veya İngilizce editör tarafından abstract ve extented abstract’ın yetersiz görülmesi hallerinde de yine makaleyle ilgili son karar Editörler Kurulu tarafından verilir. Tüm bu aşamalardan geçen bir makale en yakın sayıya yayınlanmak üzere eklenir. İlgili sayıda yer kalmaması halinde makalenin yayımı bir sonraki sayıya kaydırılır. Bu durumda ve tüm değerlendirme sürecinde yazar isterse makalesini geri çekme hakkına sahiptir. Ancak bu durumu dergiye bildirmesi gerekir. Makale gönderim tarihinden makalenin yayına kabul tarihine kadar tüm bu işlemler için ortalama 3 aylık bir süre öngörülmektedir.