Document Type : Scientific - Research
Authors
1 Assistant
2 Graduated from the University of Tehran
Abstract
Even though 4G technology is still under development, many investors are currently working to advance the following type of internet networks identified as 5G. This research was to investigate the factors affecting the acceptance of 5G technology in Iran among university students in Tehran Province. About 238 students were randomly selected in this study from universities in Tehran. The main method for data collection and analysis is to provide an electronic questionnaire related to the model. Data analysis was performed using structural equation modeling method and PLS software. The results showed that the quality of technology has a positive influence on perceived ease of use, perceived usefulness, trust and perceived enjoyment. Quality has a positive influence on perceived ease of use, perceived usefulness and trust, while there is no direct relationship between perceived enjoyment and acceptance to use 5G technology.
Keywords
References
Ahn, T., Ryu, S., & Han, I. (2007). The impact of Web quality and playfulness on user acceptance of online retailing. Information & Management, 44(3), 263-275. doi:https://doi.org/10.1016/j.im.2006.12.008.
Ajzen, Icek ; Fishbein, Martin. (1980). Understanding attitudes and predicting social behavior. prentice Hall PTR, 1980. Retrieved from https://books.google.com/books/about/Understanding_Attitudes_and_Predicting_S.html?id=CbVmQgAACAAJ.
Ajzen, Icek. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179-211. doi:https://doi.org/10.1016/0749-5978(91)90020-T.
Akbari, M., Rezvani, A., Shahriari, E., Pouladian, H., & Zúñiga, M. (2020). Acceptance of 5G technology: mediation role of trust and concentration. Journal of Engineering and Technology Management, 57. doi:https://doi.org/10.1016/j.jengtecman.2020.101585.
Alalwan, A., Baabdullahb, A., Rana, N., Tamilmani, K., & Dwivedi, Y. (2018). Examining adoption of mobile internet in Saudi Arabia: Extending TAM with perceived enjoyment, innovativeness and trust. Technology in Society, 55, 100-110. doi:https://doi.org/10.1016/j.techsoc.2018.06.007.
Alshurideh, M., Salloum, S., Kurdi, B., Monem, A., & Shaalan, K. (2019). Understanding the quality determinants that influence the intention to use the mobile learning platforms: A practical study. International Journal of Interactive Mobile Technologies, 157-183. doi:10.3991/ijim.v13i11.10300.
Bagozzi, R., Youjae, Y., & Phillips, L. (1991). Assessing construct validity in organization research. Administrative Science Quarterly, 36, 421-458.
Balog, A., & Pribeanu, C. (2010). The role of perceived enjoyment in the students’ acceptance of an augmented reality teaching platform: a structural equation modelling approach. 319-330. doi:DOI: 10.24846/v19i3y201011.
Bao, Y., Hoque, R., & Wang, S. (2017). Investigating the determinants of Chinese adult children’s intention to use online health information for their aged parents. International Journal of Medical Informatics, 102, 12-20. doi:https://doi.org/10.1016/j.ijmedinf.2017.01.003.
Barclay, D., Thompson, R., & Higgins, C. (1995). The partial least squares (PLS) approach to casual modeling: personal computer adoption and use as an illustration. Technology Studies, 2(2), 285-309.
Barnes, S., & Mattsson, J. (2017). Understanding collaborative consumption: Test of a theoretical model. Technological Forecasting & Social Change, 118, 281-292. doi:https://doi.org/10.1016/j.techfore.2017.02.029.
Chang, C., Li, C., Hung, F., & Hwang, G. (2005). An empirical study on the impact of quality antecedents on tax payers’ acceptance of Internet tax-filing systems. 22(3), 389-410. doi:https://doi.org/10.1016/j.giq.2005.05.002.
Chang, C., Li, Y., Hung, W., & Hwang, H. (2005). An empirical study on the impact of quality antecedents on tax payers’ acceptance of Internet tax-filing systems. Government Information Quarterly, 22(3), 389-410. doi:https://doi.org/10.1016/j.giq.2005.05.002.
Chang, C., Yan, C., & Tseng, J. (2012). Perceived convenience in an extended technology acceptance model: Mobile technology and English learning for college students. Australasian Journal of Educational Technology, 28(5), 809-826. doi:DOI: 10.14742/ajet.818.
Chen, C., & Tsai, J. (2019). Determinants of behavioral intention to use the personalized Location-based Mobile Tourism Application: An empirical study by integrating TAM with ISSM. Future Generation Computer Systems, 96, 628-638. doi:https://doi.org/10.1016/j.future.2017.02.028.
Chennai, A., & India, T. (2013). 5G – Introduction & future of mobile broadband communication redefined. International Journal of Electronics, Communication & Instrumentation Engineering Research and Development, 3(4). Retrieved from file:///C:/Users/paytakht-pc/Downloads/5G_Introduction_and_Future_of_Mobile_Bro.pdf.
Chi, T. (2018). Understanding Chinese consumer adoption of apparel mobile commerce: An extended TAM approach. Journal of Retailing and Consumer Services, 44, 274-284. doi:https://doi.org/10.1016/j.jretconser.2018.07.019.
Chong, A., Chan, F., & Ooi, K. (2012). Predicting consumer decisions to adopt mobile commerce: Cross country empirical examination between China and Malaysia. Decision Support Systems, 53(1), 34-43. doi:https://doi.org/10.1016/j.dss.2011.12.001.
Chuchuen, C. (2016). The perception of mobile banking adoption: The study of behavioral, security, and trust in Thailand. doi:DOI: 10.7763/IJSSH.2016.V6.708.
Csikszentmihalyi, M., & Csikszentmihalyi, I. (1977). Beyond boredom and anxiety. San Francisco: San Francisco, Calif.: Jossey-Bass Publ., 1977. Retrieved from https://www.worldcat.org/title/beyond-boredom-and-anxiety/oclc/253539000.
Dağhan, G., & Akkoyunlu, B. (2016). Modeling the continuance usage intention of online learning environments. Computers in Human Behavior, 60, 198-211. doi:https://doi.org/10.1016/j.chb.2016.02.066.
Davis, F., Bagozzi, R., & Warshaw, P. (1989). User acceptance of computer technology: A comparison of two theoretical models. Management Science, 35(8), 903-1028. doi:https://doi.org/10.1287/mnsc.35.8.982.
Davis, Fred D. ; Bagozzi, Richard P.; Warshaw, Paul R. (1992). Extrinsic and intrinsic motivation to use computers in the workplace. Journal Of Applied Social Psychology, 22(14). doi:https://doi.org/10.1111/j.1559-1816.1992.tb00945.x.
Davis, Fred; Bagozzi, Richard; Warshaw, Paul. (1989). User acceptance of computer technology: a comparison of two theoretical models. Management Science. doi:https://doi.org/10.1287/mnsc.35.8.982.
DeLone, W., & McLean, E. (1992). Information systems success: The quest for the dependent variable. Journal of Management Information Systems, 60-95. doi:DOI: 10.1287/isre.3.1.60.
Fornell , C., & Larcker , D. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39-50.
Gefen, D., Karahanna, E., & Straub, D. (2003). Trust and TAM in online shopping: An integrated model. MIS Quarterly, 27(2). Retrieved from http://mail.im.tku.edu.tw/~myday/teaching/992/SMS/S/992SMS_T4_Paper_20110521_Trust%20and%20TAM%20in%20Online%20Shopping-An%20Integrated%20Model.pdf.
Giao, H., Vuong, B., & Quan, T. (2020). The influence of website quality on consumer’s e-loyalty through the mediating role of e-trust and e-satisfaction: An evidence from online shopping in Vietnam. 351-370. doi:DOI: 10.5267/j.uscm.2019.11.004.Gu, C., Lee, C., & Suh, Y. (2009). Determinants of behavioral intention to mobile banking. Gu, L. S. (2009). Determinants of behavioral intention to mobile banking. 36(9), 11605-11616. doi:https://doi.org/10.1016/j.eswa.2009.03.024.
Ha, S., & Stoel, L. (2009). Consumer e-shopping acceptance: Antecedents in a technology acceptance model. Journal of Business Research, 62(5), 565-571. doi:https://doi.org/10.1016/j.jbusres.2008.06.016.
Henseler, J., Ringle, C., & Sinkovics, R. (2009). The use of partial least squares path modeling in international marketing. Advances in International Marketing, 277-319.
Hulland, J. (1999). Use of partial least squares (PLS) in strategic management research: a review of four recent studies. Strategic Management, 20(2), 195-204.
Hwang, Y., & Kim, D. (2007). Customer self-service systems: The effects of perceived Web quality with service contents on enjoyment, anxiety, and e-trust. Decision Support Systems, 43(3), 746-760. doi:https://doi.org/10.1016/j.dss.2006.12.008.
Islam, M., Nahid Hasan, K., & Arefin, A. (2013). Universal mobile telecommunication system. doi:10.13140/2.1.2961.9523.
Jackson, J., Yi, M., & Park, J. (2013). An empirical test of three mediation models for the relationship between personal innovativeness and user acceptance of technology. Information & Management, 50(4), 154-161. doi:https://doi.org/10.1016/j.im.2013.02.006.
K, P., & Thomas, S. (2014). Continuance Intention to Use Facebook: A Study of Perceived Enjoyment and TAM. Bonfring International Journal of Industrial Engineering and Management Science, 24-29. doi:DOI: 10.9756/BIJIEMS.4794.
Kaushik, A., Agrawal, A., & Rahman, Z. (2015). Tourist behaviour towards self-service hotel technology adoption: Trust and subjective norm as key antecedents. Tourism Management Perspectives, 16, 278-289. doi:https://doi.org/10.1016/j.tmp.2015.09.002.
Liawa, S., & Huang, H. (2003). An investigation of user attitudes toward search engines as an information retrieval tool. Computers in Human Behavior, 19(6), 751-765. doi:https://doi.org/10.1016/S0747-5632(03)00009-8.
Liu, S., Liao, H., & Pratt, J. (2009). Impact of media richness and flow on e-learning technology acceptance. Computers & Education, 52(3), 599-607. doi:https://doi.org/10.1016/j.compedu.2008.11.002.
Lu, Y., Zhou, T., & Wang, B. (2009). Exploring Chinese users’ acceptance of instant messaging using the theory of planned behavior, the technology acceptance model, and the flow theory. Computers in Human Behavior, 25(1), 29-39. doi:https://doi.org/10.1016/j.chb.2008.06.002.
Mayer, R., Davis, J., & Schoorman, D. (1995). An integrative model of organizational trust. Academy of Management Review, 20(3). doi:https://doi.org/10.5465/amr.1995.9508080335.
Mcknight, H., Carter, M., Thatcher, J., & Clay, P. (2011). Trust in a specific technology: An Investigation of its Components and Measures. ACM Transactions on Management Information Systems, 12-32. doi:DOI: 10.1145/1985347.1985353.
Montazemi, A., & Qahri-Saremi, H. (2015). Factors affecting adoption of online banking: A meta-analytic structural equation modeling study. Information & Management, 52(2), 210-226. doi:https://doi.org/10.1016/j.im.2014.11.002.
Nascimento, B., Oliveira, T., & Tam, C. (2018). Wearable technology: What explains continuance intention in smartwatches? Journal of Retailing and Consumer Services, 43, 157-169. doi:https://doi.org/10.1016/j.jretconser.2018.03.017.
Pai, F., & Huang, K. (2011). Applying the technology acceptance model to the introduction of healthcare information systems. Technological Forecasting and Social Change, 78(4), 650-660. doi:https://doi.org/10.1016/j.techfore.2010.11.007.
Park, Eunil ; Kim, Ki Joon. (2013). User acceptance of long-term evolution (LTE) services: An application of extended technology acceptance model. Program Electronic Library And Information Systems, 47(2). doi:DOI: 10.1108/00330331311313762.
Ramayah, T., & Ignatius, J. (2005). Impact of perceived usefulness, perceived ease of use and perceived enjoyment on intention to shop online. Journal of Systems Management. Retrieved from https://www.researchgate.net/publication/284417406_Impact_of_perceived_usefulness_perceived_ease_of_use_and_perceived_enjoyment_on_intention_to_shop_online.
Sarkar, S., Chauhan, S., & Khare, A. (2020). A meta-analysis of antecedents and consequences of trust in mobile commerce. International Journal of Information Management, 50, 286-301. doi:https://doi.org/10.1016/j.ijinfomgt.2019.08.008.
Sharma, P. (2013). Evolution of mobile wireless communication networks-1G to 5G as well as future prospective of next generation communication network. International Journal of Computer Science and mobile computing, 2(8), 47 – 53. Retrieved from http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.696.7061&rep=rep1&type=pdf.
Tenenhaus, M., Esposito Vinzi, V., & Amato, S. (2004). A global goodness-of-fit index for PLS structural equation modelling. 739-742.
Thong, J., Hong, S., & Tam, K. (2006). The effects of post-adoption beliefs on the expectation-confirmation model for information technology continuance. International Journal of Human-Computer Studies, 64(9), 799-810. doi:https://doi.org/10.1016/j.ijhcs.2006.05.001.
Venkatesh, Viswanath ; Davis, Fred D. (2000). A theoretical extension of the technology acceptance model: four longitudinal field studies. Management Science, 46(2), 169-332. doi:https://doi.org/10.1287/mnsc.46.2.186.11926.
Verma, S., Bhattacharyya, S., & Kumar, S. (2018). An extension of the technology acceptance model in the big data analytics system implementation environment. Information Processing & Management, 54(5), 791-806. doi:https://doi.org/10.1016/j.ipm.2018.01.004.
Ahn, T., Ryu, S., & Han, I. (2007). The impact of Web quality and playfulness on user acceptance of online retailing. Information & Management, 44(3), 263-275. doi:https://doi.org/10.1016/j.im.2006.12.008.
Ajzen, Icek ; Fishbein, Martin. (1980). Understanding attitudes and predicting social behavior. prentice Hall PTR, 1980. Retrieved from https://books.google.com/books/about/Understanding_Attitudes_and_Predicting_S.html?id=CbVmQgAACAAJ.
Ajzen, Icek. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179-211. doi:https://doi.org/10.1016/0749-5978(91)90020-T.
Akbari, M., Rezvani, A., Shahriari, E., Pouladian, H., & Zúñiga, M. (2020). Acceptance of 5G technology: mediation role of trust and concentration. Journal of Engineering and Technology Management, 57. doi:https://doi.org/10.1016/j.jengtecman.2020.101585.
Alalwan, A., Baabdullahb, A., Rana, N., Tamilmani, K., & Dwivedi, Y. (2018). Examining adoption of mobile internet in Saudi Arabia: Extending TAM with perceived enjoyment, innovativeness and trust. Technology in Society, 55, 100-110. doi:https://doi.org/10.1016/j.techsoc.2018.06.007.
Alshurideh, M., Salloum, S., Kurdi, B., Monem, A., & Shaalan, K. (2019). Understanding the quality determinants that influence the intention to use the mobile learning platforms: A practical study. International Journal of Interactive Mobile Technologies, 157-183. doi:10.3991/ijim.v13i11.10300.
Bagozzi, R., Youjae, Y., & Phillips, L. (1991). Assessing construct validity in organization research. Administrative Science Quarterly, 36, 421-458.
Balog, A., & Pribeanu, C. (2010). The role of perceived enjoyment in the students’ acceptance of an augmented reality teaching platform: a structural equation modelling approach. 319-330. doi:DOI: 10.24846/v19i3y201011.
Bao, Y., Hoque, R., & Wang, S. (2017). Investigating the determinants of Chinese adult children’s intention to use online health information for their aged parents. International Journal of Medical Informatics, 102, 12-20. doi:https://doi.org/10.1016/j.ijmedinf.2017.01.003.
Barclay, D., Thompson, R., & Higgins, C. (1995). The partial least squares (PLS) approach to casual modeling: personal computer adoption and use as an illustration. Technology Studies, 2(2), 285-309.
Barnes, S., & Mattsson, J. (2017). Understanding collaborative consumption: Test of a theoretical model. Technological Forecasting & Social Change, 118, 281-292. doi:https://doi.org/10.1016/j.techfore.2017.02.029.
Chang, C., Li, C., Hung, F., & Hwang, G. (2005). An empirical study on the impact of quality antecedents on tax payers’ acceptance of Internet tax-filing systems. 22(3), 389-410. doi:https://doi.org/10.1016/j.giq.2005.05.002.
Chang, C., Li, Y., Hung, W., & Hwang, H. (2005). An empirical study on the impact of quality antecedents on tax payers’ acceptance of Internet tax-filing systems. Government Information Quarterly, 22(3), 389-410. doi:https://doi.org/10.1016/j.giq.2005.05.002.
Chang, C., Yan, C., & Tseng, J. (2012). Perceived convenience in an extended technology acceptance model: Mobile technology and English learning for college students. Australasian Journal of Educational Technology, 28(5), 809-826. doi:DOI: 10.14742/ajet.818.
Chen, C., & Tsai, J. (2019). Determinants of behavioral intention to use the personalized Location-based Mobile Tourism Application: An empirical study by integrating TAM with ISSM. Future Generation Computer Systems, 96, 628-638. doi:https://doi.org/10.1016/j.future.2017.02.028.
Chennai, A., & India, T. (2013). 5G – Introduction & future of mobile broadband communication redefined. International Journal of Electronics, Communication & Instrumentation Engineering Research and Development, 3(4). Retrieved from file:///C:/Users/paytakht-pc/Downloads/5G_Introduction_and_Future_of_Mobile_Bro.pdf.
Chi, T. (2018). Understanding Chinese consumer adoption of apparel mobile commerce: An extended TAM approach. Journal of Retailing and Consumer Services, 44, 274-284. doi:https://doi.org/10.1016/j.jretconser.2018.07.019.
Chong, A., Chan, F., & Ooi, K. (2012). Predicting consumer decisions to adopt mobile commerce: Cross country empirical examination between China and Malaysia. Decision Support Systems, 53(1), 34-43. doi:https://doi.org/10.1016/j.dss.2011.12.001.
Chuchuen, C. (2016). The perception of mobile banking adoption: The study of behavioral, security, and trust in Thailand. doi:DOI: 10.7763/IJSSH.2016.V6.708.
Csikszentmihalyi, M., & Csikszentmihalyi, I. (1977). Beyond boredom and anxiety. San Francisco: San Francisco, Calif.: Jossey-Bass Publ., 1977. Retrieved from https://www.worldcat.org/title/beyond-boredom-and-anxiety/oclc/253539000.
Dağhan, G., & Akkoyunlu, B. (2016). Modeling the continuance usage intention of online learning environments. Computers in Human Behavior, 60, 198-211. doi:https://doi.org/10.1016/j.chb.2016.02.066.
Davis, F., Bagozzi, R., & Warshaw, P. (1989). User acceptance of computer technology: A comparison of two theoretical models. Management Science, 35(8), 903-1028. doi:https://doi.org/10.1287/mnsc.35.8.982.
Davis, Fred D. ; Bagozzi, Richard P.; Warshaw, Paul R. (1992). Extrinsic and intrinsic motivation to use computers in the workplace. Journal Of Applied Social Psychology, 22(14). doi:https://doi.org/10.1111/j.1559-1816.1992.tb00945.x.
Davis, Fred; Bagozzi, Richard; Warshaw, Paul. (1989). User acceptance of computer technology: a comparison of two theoretical models. Management Science. doi:https://doi.org/10.1287/mnsc.35.8.982.
DeLone, W., & McLean, E. (1992). Information systems success: The quest for the dependent variable. Journal of Management Information Systems, 60-95. doi:DOI: 10.1287/isre.3.1.60.
Fornell , C., & Larcker , D. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39-50.
Gefen, D., Karahanna, E., & Straub, D. (2003). Trust and TAM in online shopping: An integrated model. MIS Quarterly, 27(2). Retrieved from http://mail.im.tku.edu.tw/~myday/teaching/992/SMS/S/992SMS_T4_Paper_20110521_Trust%20and%20TAM%20in%20Online%20Shopping-An%20Integrated%20Model.pdf.
Giao, H., Vuong, B., & Quan, T. (2020). The influence of website quality on consumer’s e-loyalty through the mediating role of e-trust and e-satisfaction: An evidence from online shopping in Vietnam. 351-370. doi:DOI: 10.5267/j.uscm.2019.11.004.Gu, C., Lee, C., & Suh, Y. (2009). Determinants of behavioral intention to mobile banking. Gu, L. S. (2009). Determinants of behavioral intention to mobile banking. 36(9), 11605-11616. doi:https://doi.org/10.1016/j.eswa.2009.03.024.
Ha, S., & Stoel, L. (2009). Consumer e-shopping acceptance: Antecedents in a technology acceptance model. Journal of Business Research, 62(5), 565-571. doi:https://doi.org/10.1016/j.jbusres.2008.06.016.
Henseler, J., Ringle, C., & Sinkovics, R. (2009). The use of partial least squares path modeling in international marketing. Advances in International Marketing, 277-319.
Hulland, J. (1999). Use of partial least squares (PLS) in strategic management research: a review of four recent studies. Strategic Management, 20(2), 195-204.
Hwang, Y., & Kim, D. (2007). Customer self-service systems: The effects of perceived Web quality with service contents on enjoyment, anxiety, and e-trust. Decision Support Systems, 43(3), 746-760. doi:https://doi.org/10.1016/j.dss.2006.12.008.
Islam, M., Nahid Hasan, K., & Arefin, A. (2013). Universal mobile telecommunication system. doi:10.13140/2.1.2961.9523.
Jackson, J., Yi, M., & Park, J. (2013). An empirical test of three mediation models for the relationship between personal innovativeness and user acceptance of technology. Information & Management, 50(4), 154-161. doi:https://doi.org/10.1016/j.im.2013.02.006.
K, P., & Thomas, S. (2014). Continuance Intention to Use Facebook: A Study of Perceived Enjoyment and TAM. Bonfring International Journal of Industrial Engineering and Management Science, 24-29. doi:DOI: 10.9756/BIJIEMS.4794.
Kaushik, A., Agrawal, A., & Rahman, Z. (2015). Tourist behaviour towards self-service hotel technology adoption: Trust and subjective norm as key antecedents. Tourism Management Perspectives, 16, 278-289. doi:https://doi.org/10.1016/j.tmp.2015.09.002.
Liawa, S., & Huang, H. (2003). An investigation of user attitudes toward search engines as an information retrieval tool. Computers in Human Behavior, 19(6), 751-765. doi:https://doi.org/10.1016/S0747-5632(03)00009-8.
Liu, S., Liao, H., & Pratt, J. (2009). Impact of media richness and flow on e-learning technology acceptance. Computers & Education, 52(3), 599-607. doi:https://doi.org/10.1016/j.compedu.2008.11.002.
Lu, Y., Zhou, T., & Wang, B. (2009). Exploring Chinese users’ acceptance of instant messaging using the theory of planned behavior, the technology acceptance model, and the flow theory. Computers in Human Behavior, 25(1), 29-39. doi:https://doi.org/10.1016/j.chb.2008.06.002.
Mayer, R., Davis, J., & Schoorman, D. (1995). An integrative model of organizational trust. Academy of Management Review, 20(3). doi:https://doi.org/10.5465/amr.1995.9508080335.
Mcknight, H., Carter, M., Thatcher, J., & Clay, P. (2011). Trust in a specific technology: An Investigation of its Components and Measures. ACM Transactions on Management Information Systems, 12-32. doi:DOI: 10.1145/1985347.1985353.
Montazemi, A., & Qahri-Saremi, H. (2015). Factors affecting adoption of online banking: A meta-analytic structural equation modeling study. Information & Management, 52(2), 210-226. doi:https://doi.org/10.1016/j.im.2014.11.002.
Nascimento, B., Oliveira, T., & Tam, C. (2018). Wearable technology: What explains continuance intention in smartwatches? Journal of Retailing and Consumer Services, 43, 157-169. doi:https://doi.org/10.1016/j.jretconser.2018.03.017.
Pai, F., & Huang, K. (2011). Applying the technology acceptance model to the introduction of healthcare information systems. Technological Forecasting and Social Change, 78(4), 650-660. doi:https://doi.org/10.1016/j.techfore.2010.11.007.
Park, Eunil ; Kim, Ki Joon. (2013). User acceptance of long-term evolution (LTE) services: An application of extended technology acceptance model. Program Electronic Library And Information Systems, 47(2). doi:DOI: 10.1108/00330331311313762.
Ramayah, T., & Ignatius, J. (2005). Impact of perceived usefulness, perceived ease of use and perceived enjoyment on intention to shop online. Journal of Systems Management. Retrieved from https://www.researchgate.net/publication/284417406_Impact_of_perceived_usefulness_perceived_ease_of_use_and_perceived_enjoyment_on_intention_to_shop_online.
Sarkar, S., Chauhan, S., & Khare, A. (2020). A meta-analysis of antecedents and consequences of trust in mobile commerce. International Journal of Information Management, 50, 286-301. doi:https://doi.org/10.1016/j.ijinfomgt.2019.08.008.
Sharma, P. (2013). Evolution of mobile wireless communication networks-1G to 5G as well as future prospective of next generation communication network. International Journal of Computer Science and mobile computing, 2(8), 47 – 53. Retrieved from http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.696.7061&rep=rep1&type=pdf.
Tenenhaus, M., Esposito Vinzi, V., & Amato, S. (2004). A global goodness-of-fit index for PLS structural equation modelling. 739-742.
Thong, J., Hong, S., & Tam, K. (2006). The effects of post-adoption beliefs on the expectation-confirmation model for information technology continuance. International Journal of Human-Computer Studies, 64(9), 799-810. doi:https://doi.org/10.1016/j.ijhcs.2006.05.001.
Venkatesh, Viswanath ; Davis, Fred D. (2000). A theoretical extension of the technology acceptance model: four longitudinal field studies. Management Science, 46(2), 169-332. doi:https://doi.org/10.1287/mnsc.46.2.186.11926.
Verma, S., Bhattacharyya, S., & Kumar, S. (2018). An extension of the technology acceptance model in the big data analytics system implementation environment. Information Processing & Management, 54(5), 791-806. doi:https://doi.org/10.1016/j.ipm.2018.01.004.
)