Araştırma Makalesi
Yıl 2022,
Cilt: 6 Sayı: 1, 313 - 334, 29.08.2022
Öz
This study aimed to examine the consumers’ intentions of to use cryptocurrencies within the framework of the technology acceptance model. The study used a convenience sampling method to reach 228 participants who had previous experience with cryptocurrency through an online survey. The collected data were statistically analyzed using the SPSS 18 and LISREL 8.70 package programs. The research model and hypothesis developed for the study were tested using structural equation modelling. The research model consists of the following of variables such as perceived ease of use, perceived utility, attitude towards usage, and intention to use. As a result of the study, while the perceived ease of use of cryptocurrencies has a positive effect on the perceived usefulness, it has not been found to have an effect on the attitude towards use. In another result, it has been concluded that the perceived usefulness of cryptocurrencies affects the attitude and intention to use them. Finally, it has been observed that the attitude towards the use of cryptocurrencies affects the intention to use. The study was finished with a discussion of the findings and suggestions for future researchers and practitioners in the field.
Anahtar Kelimeler
Cryptocurrency technology acceptance model perceived usefulness ıntention to use
Kaynakça
- Alaklabi, S., & Kang, K. (2021). Perceptions towards cryptocurrency adoption: a case of Saudi Arabian citizens. IBIMA Business Review, Article ID 110411.
- Bhatiasevi, V., & Yoopetch, C. (2015). The determinants of intention to use electronic booking among young users in Thailand. Journal of Hospitality and Tourism Management, 23, 1–11.
- Binance Capital (2022, Ocak). https://coinmarketcap.com/[Erişim tarihi: 20 Ocak 2022].
- Carrick, J. (2016). Bitcoin as a complement to emerging market currencies. Emerging Markets Finance and Trade, 52(10), 2321–2334
- Chuttur, M. (2009). Overview of the technology acceptance model: Origins, developments and future directions. Indiana University, USA. Sprouts: Working Papers on Information Systems, 9(37). http://sprouts.aisnet.org/9-37.
- Çelik, Z., & Erdem, Ş. (2018). Web sitesi içeriğinin e-perakendeciliğin kullanıcı kabulüne etkisi. Turkish Journal of Marketing, 3(2), 108-126.
- Çelik, Z., Aydın, İ. (2021). Tüketicilerin fiziksel mağaza alışverişlerinde artırılmış gerçeklik uygulaması olarak akıllı ayna kullanmasının davranışsal niyete etkisi, İşletme Araştırmaları Dergisi, 13 (4), 3573-3585.
- Çetinkaya, Ş. (2018). Kripto paraların gelişimi ve para piyasalarındaki yerinin swot analizi ile incelenmesi. Uluslararası Ekonomi ve Siyaset Bilimleri Akademik Araştırmalar Dergisi, 2(5), 11-21.
- Davis, F.D. (1989). Perceived usefulness, perceived ease of use and user acceptance of information technology. MIS Quarterly, 13(3), 319-339.
- Davis, F.D., Bagozzi, R.P. & Warshaw, P.R. (1989). User acceptance of computer technology: a comparison of two theoretical models. Management Science, Vol. 35 No. 8, pp. 982-1003.
- Deniz, E.A. & Teker, D. (2020). Crypto currency applications in financial markets: factors affecting crypto currency prices. Pressacademia Procedia, 11(1), 34-37.
- Fettahoğlu, S. & Sayan, Ö. (2021). Attitudes of individuals about using cryptocurrencies: evidence from Turkey. İstanbul Ticaret Üniversitesi Sosyal Bilimler Dergisi, 20(42), 1122-1146.
- Folkinshteyn, D., & Lennon, M. (2016). Braving bitcoin: a technology acceptance model (TAM) analysis. Journal of Information Technology Case and Application Research, 18(4), 220-249.
- Fornell, C. & Larcker, D.F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1): 39-50
- Gilbert, S. & Loi, H. (2018). Digital currency risk. International Journal of Economics and Finance, 10(2), 108.
- Grover, P., Kar, A. K., Janssen, M., & Ilavarasan, P. V. (2019). Perceived usefulness, ease of use and user acceptance of blockchain technology for digital transactions–insights from user-generated content on Twitter. Enterprise Information Systems, 13(6), 771-800.
- Guych, N., Anastasia, S., Simon, Y., & Jennet, A. (2018). Factors influencing the intention to use cryptocurrency payments: An examination of blockchain economy. 303-310.
- Heijden, H. V. (2003). Factors influencing the usage of websites: the case of a generic portal in The Netherlands. Information & management, 40(6), 541-549.
- Hooper, D., Coughlan, J. & Mullen, M. R. (2008). Structural equation modelling: guidelines for determining model fit. The Electronic Journal of Business Research Methods, 6(1), 53-60.
- Iglesias D. U. (2015). Bitcoin: A new way to understand payment systems. Cambridge, MA: Massachusetts Institute of Technology.
- Kabak, A., & Çelik, Z. (2020). “Tüketicilerin Kripto Para Kullanım Niyeti İle İlişkili Faktörlerin Belirlenmesine Yönelik Uygulamalı Bir Araştırma”, 6th Internatıonal Gap Socıal Scıences Congress December 4-6, 2020, Şanlıurfa-Turkey
- Kalyoncuoğlu, S. (2018). Tüketicilerin online alışverişlerindeki sanal kart kullanımlarının teknoloji kabul modeli ile incelenmesi. Afyon Kocatepe Üniversitesi Sosyal Bilimler Dergisi, 20(2), 193-213.
- Kumpajaya, A., & Dhewanto, W. (2015). The acceptance of Bitcoin in Indonesia: extending TAM with IDT. Journal of Business and Management, 4(1), 28-38.
- Lee, M. C. (2009). Factors influencing the adoption of internet banking: An integration of TAM and TPB with perceived risk and perceived benefit. Electronic Commerce Research and Applications, 8(3), 130-141.
- Lee, W. J. (2018). Understanding counsumer acceptance of fintech service: an extension of the tam model to understand bitcoin. IOSR Journal of Business and Management, 20(7), 34-37.
- Liao, S., Hong, J. C., Wen, M. H., & Pan, Y. C. (2018). Applying technology acceptance model (TAM) to explore users’ behavioral intention to adopt a performance assessment system for E-book production. EURASIA Journal of Mathematics, Science and Technology Education, 14(10), em1601.
- Lu, D., Lai, I. K. W., & Liu, Y. (2019). The consumer acceptance of smart product-service systems in sharing economy: the effects of perceived interactivity and particularity. Sustainability, 11(3), 928.
- Nadeem, M. A., Liu, Z., Pitafi, A. H., Younis, A., & Xu, Y. (2021). Investigating the adoption factors of cryptocurrencies—a case of bitcoin: empirical evidence from China. SAGE Open, 11(1), 2158244021998704.
- Nakamoto, S. (2008). Bitcoin: A peer-to-peer electronic cash system. Decentralized Business Review, 21260.
- Nuryyev, G., Spyridou, A., Yeh, S., & Lo, C. C. (2021). Factors of digital payment adoption in hospitality businesses: A conceptual approach. European Journal of Tourism Research, 29, 2905-2905.
- Nysveen, H., Pedersen, P.E. & Thorbjørnsen, H. (2005). Intentions to use mobile services: antecedents and cross-service comparisons. Journal of the Academy of Marketing Science, Vol. 33 No. 3, pp. 330-46.
- Pikkarainen, T., Pikkarainen, K., Karjaluto H. & Pahnila, S. (2004). Consumer acceptance of online banking: an extension of the technology acceptance model, Internet Research, 14(3):224-235.
- Porter, C.E. & Donthu, N. (2006). Using the technology acceptance model to explain how attitudes determine internet usage: the role of perceived access barriers and demographics. Journal of Business Research, Vol. 59 No. 9, pp. 999-1007.
- Robinson, L. Jr., Marshall, G.W. & Stamps, M.B. (2005). Sales force use of technology: antecedents to technology acceptance. Journal of Business Research, Vol. 58 No. 12, pp. 1623-31
- Roussou, I., & Stiakakis, E. (2016). “Adoption of Digital Currencies by Companies in the European Union: A Research Model combining DOI and TAM”, In 4 th International Conference on Contemporary Marketing Issues ICCMI June 22-24, 2016 Heraklion, Greece (p. 163).
- Sanchez, P., Saura, J. R., & Ayestaran, R. (2021). An exploratory approach to the adoption process of bitcoin by business executives. Mathematics, 9(4), 355.
- Schermelleh-Engel, K., Moosbrugger, H. & Müller, H. (2003). Evaluating the fit of structural equation models: Tests of significance and descriptive goodness-of-fit measures. Methods of Psychological Research Online, 8(2), 23-74.
- Shrestha, A. K., & Vassileva, J. (2019). “User Acceptance of Usable Blockchain-Based Research Data Sharing System: an Extended TAM-Based Study”, In 2019 First IEEE International Conference on Trust, Privacy and Security in Intelligent Systems and Applications (TPS-ISA) (pp. 203-208). IEEE.
- Silva, P. M., & Dias, G. A. (2007). Theories about technology accepentace: why the users accept or reject the information technology? Brazilian Journal of Information Science: Research Trends, 1(2), 69-91.
- Siyam, N. (2019). Factors impacting special education teachers’ acceptance and actual use of technology. Education and Information Technologies, 24(3), 2035-2057.
- Stevens, J. (1996). Applied Multivariate Statistics for the Social Sciences, (3rd edition), Mahwah, Lawrence Erlbaum: New Jersey.
- Teo, A. C., Tan, G. W. H., Cheah, C. M., Ooi, K. B., & Yew, K. T. (2012). Can the demographic and subjective norms influence the adoption of mobile banking? International Journal of Mobile Communications, 10(6), 578-597.
- Toraman, Y. (2021). Blokzincir teknolojisinin benimsenmesinin teknoloji kabul modeli çerçevesinde incelenmesi: kripto (dijital) paralar üzerine bir araştırma. Journal Of Social, Humanities and Administrative Sciences, 7(45), 1841-1856.
- Türker, A., & Türker, Ö. G. (2013). Turistik ürün satın alma davranışının teknoloji kabul modeli ile incelenmesi. Dokuz Eylül Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 15(2), 281-312.
- Venkatesh, V. & Davis, F.D. (2000). A theoretical extension of the technology acceptance model: four longitudinal field studies, Management Science, 46(2), 186-204.
- Wang, Y., Wang, S., Wang, J., Wei, J., & Wang, C. (2020). An empirical study of consumers’ intention to use ride-sharing services: Using an extended tecnology acceptance model. Transportation, 47(1), 397-415.
- Yılmaz, C., & Tümtürk, A. (2015). Internet üzerinden alisveris niyetini etkileyen faktörlerin genisletilmis teknoloji kabul modeli kullanarak ıncelenmesi ve bir model önerisi. Yonetim ve Ekonomi, 22(2), 355-384.
Yıl 2022,
Cilt: 6 Sayı: 1, 313 - 334, 29.08.2022
Öz
Bu çalışma, teknoloji kabul modeli çerçevesinde tüketicilerin kripto para kullanım niyetlerinin incelenmesini amaçlamıştır. Çalışmada kolayda örnekleme yöntemi kullanılmış ve kripto para kullanımı deneyimine sahip 228 katılımcıya online anket yöntemi kullanılarak ulaşılmıştır. Elde edilen verilerin istatistiksel analizi SPSS 18 ve LISREL 8.70 paket programları ile incelenmiştir. Araştırma amacı doğrultusunda oluşturulan araştırma modeli ve kurulan hipotezler yapısal eşitlik modellemesi ile test edilmiştir. Araştırma modeli algılanan kullanım kolaylığı, algılanan fayda, kullanıma yönelik tutum ve kullanım niyeti değişkenlerinden oluşmaktadır. Çalışma sonucunda kripto paralara ilişkin algılanan kullanım kolaylığının algılanan fayda üzerinde olumlu yönde ve pozitif etkisi bulunmuştur. Algılanan kullanım kolaylığının kullanıma yönelik tutum üzerinde ise anlamlı bir etkisi bulunamamıştır. Bir başka sonuçta kripto paralara ilişkin algılanan faydanın kullanıma yönelik tutum ve kullanım niyeti üzerinde etkili olduğu sonucuna ulaşılmıştır. Son olarak kripto paralara ilişkin kullanıma yönelik tutumun kullanım niyeti üzerinde etkili olduğu da görülmüştür. Araştırma sonuçları tartışılarak hem alan yazındaki araştırmacılara hem de uygulayıcılara önerilerde bulunularak çalışma nihayete erdirilmiştir.
Anahtar Kelimeler
Kripto para Teknoloji kabul modeli Algılanan fayda Kullanım niyeti
Kaynakça
- Alaklabi, S., & Kang, K. (2021). Perceptions towards cryptocurrency adoption: a case of Saudi Arabian citizens. IBIMA Business Review, Article ID 110411.
- Bhatiasevi, V., & Yoopetch, C. (2015). The determinants of intention to use electronic booking among young users in Thailand. Journal of Hospitality and Tourism Management, 23, 1–11.
- Binance Capital (2022, Ocak). https://coinmarketcap.com/[Erişim tarihi: 20 Ocak 2022].
- Carrick, J. (2016). Bitcoin as a complement to emerging market currencies. Emerging Markets Finance and Trade, 52(10), 2321–2334
- Chuttur, M. (2009). Overview of the technology acceptance model: Origins, developments and future directions. Indiana University, USA. Sprouts: Working Papers on Information Systems, 9(37). http://sprouts.aisnet.org/9-37.
- Çelik, Z., & Erdem, Ş. (2018). Web sitesi içeriğinin e-perakendeciliğin kullanıcı kabulüne etkisi. Turkish Journal of Marketing, 3(2), 108-126.
- Çelik, Z., Aydın, İ. (2021). Tüketicilerin fiziksel mağaza alışverişlerinde artırılmış gerçeklik uygulaması olarak akıllı ayna kullanmasının davranışsal niyete etkisi, İşletme Araştırmaları Dergisi, 13 (4), 3573-3585.
- Çetinkaya, Ş. (2018). Kripto paraların gelişimi ve para piyasalarındaki yerinin swot analizi ile incelenmesi. Uluslararası Ekonomi ve Siyaset Bilimleri Akademik Araştırmalar Dergisi, 2(5), 11-21.
- Davis, F.D. (1989). Perceived usefulness, perceived ease of use and user acceptance of information technology. MIS Quarterly, 13(3), 319-339.
- Davis, F.D., Bagozzi, R.P. & Warshaw, P.R. (1989). User acceptance of computer technology: a comparison of two theoretical models. Management Science, Vol. 35 No. 8, pp. 982-1003.
- Deniz, E.A. & Teker, D. (2020). Crypto currency applications in financial markets: factors affecting crypto currency prices. Pressacademia Procedia, 11(1), 34-37.
- Fettahoğlu, S. & Sayan, Ö. (2021). Attitudes of individuals about using cryptocurrencies: evidence from Turkey. İstanbul Ticaret Üniversitesi Sosyal Bilimler Dergisi, 20(42), 1122-1146.
- Folkinshteyn, D., & Lennon, M. (2016). Braving bitcoin: a technology acceptance model (TAM) analysis. Journal of Information Technology Case and Application Research, 18(4), 220-249.
- Fornell, C. & Larcker, D.F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1): 39-50
- Gilbert, S. & Loi, H. (2018). Digital currency risk. International Journal of Economics and Finance, 10(2), 108.
- Grover, P., Kar, A. K., Janssen, M., & Ilavarasan, P. V. (2019). Perceived usefulness, ease of use and user acceptance of blockchain technology for digital transactions–insights from user-generated content on Twitter. Enterprise Information Systems, 13(6), 771-800.
- Guych, N., Anastasia, S., Simon, Y., & Jennet, A. (2018). Factors influencing the intention to use cryptocurrency payments: An examination of blockchain economy. 303-310.
- Heijden, H. V. (2003). Factors influencing the usage of websites: the case of a generic portal in The Netherlands. Information & management, 40(6), 541-549.
- Hooper, D., Coughlan, J. & Mullen, M. R. (2008). Structural equation modelling: guidelines for determining model fit. The Electronic Journal of Business Research Methods, 6(1), 53-60.
- Iglesias D. U. (2015). Bitcoin: A new way to understand payment systems. Cambridge, MA: Massachusetts Institute of Technology.
- Kabak, A., & Çelik, Z. (2020). “Tüketicilerin Kripto Para Kullanım Niyeti İle İlişkili Faktörlerin Belirlenmesine Yönelik Uygulamalı Bir Araştırma”, 6th Internatıonal Gap Socıal Scıences Congress December 4-6, 2020, Şanlıurfa-Turkey
- Kalyoncuoğlu, S. (2018). Tüketicilerin online alışverişlerindeki sanal kart kullanımlarının teknoloji kabul modeli ile incelenmesi. Afyon Kocatepe Üniversitesi Sosyal Bilimler Dergisi, 20(2), 193-213.
- Kumpajaya, A., & Dhewanto, W. (2015). The acceptance of Bitcoin in Indonesia: extending TAM with IDT. Journal of Business and Management, 4(1), 28-38.
- Lee, M. C. (2009). Factors influencing the adoption of internet banking: An integration of TAM and TPB with perceived risk and perceived benefit. Electronic Commerce Research and Applications, 8(3), 130-141.
- Lee, W. J. (2018). Understanding counsumer acceptance of fintech service: an extension of the tam model to understand bitcoin. IOSR Journal of Business and Management, 20(7), 34-37.
- Liao, S., Hong, J. C., Wen, M. H., & Pan, Y. C. (2018). Applying technology acceptance model (TAM) to explore users’ behavioral intention to adopt a performance assessment system for E-book production. EURASIA Journal of Mathematics, Science and Technology Education, 14(10), em1601.
- Lu, D., Lai, I. K. W., & Liu, Y. (2019). The consumer acceptance of smart product-service systems in sharing economy: the effects of perceived interactivity and particularity. Sustainability, 11(3), 928.
- Nadeem, M. A., Liu, Z., Pitafi, A. H., Younis, A., & Xu, Y. (2021). Investigating the adoption factors of cryptocurrencies—a case of bitcoin: empirical evidence from China. SAGE Open, 11(1), 2158244021998704.
- Nakamoto, S. (2008). Bitcoin: A peer-to-peer electronic cash system. Decentralized Business Review, 21260.
- Nuryyev, G., Spyridou, A., Yeh, S., & Lo, C. C. (2021). Factors of digital payment adoption in hospitality businesses: A conceptual approach. European Journal of Tourism Research, 29, 2905-2905.
- Nysveen, H., Pedersen, P.E. & Thorbjørnsen, H. (2005). Intentions to use mobile services: antecedents and cross-service comparisons. Journal of the Academy of Marketing Science, Vol. 33 No. 3, pp. 330-46.
- Pikkarainen, T., Pikkarainen, K., Karjaluto H. & Pahnila, S. (2004). Consumer acceptance of online banking: an extension of the technology acceptance model, Internet Research, 14(3):224-235.
- Porter, C.E. & Donthu, N. (2006). Using the technology acceptance model to explain how attitudes determine internet usage: the role of perceived access barriers and demographics. Journal of Business Research, Vol. 59 No. 9, pp. 999-1007.
- Robinson, L. Jr., Marshall, G.W. & Stamps, M.B. (2005). Sales force use of technology: antecedents to technology acceptance. Journal of Business Research, Vol. 58 No. 12, pp. 1623-31
- Roussou, I., & Stiakakis, E. (2016). “Adoption of Digital Currencies by Companies in the European Union: A Research Model combining DOI and TAM”, In 4 th International Conference on Contemporary Marketing Issues ICCMI June 22-24, 2016 Heraklion, Greece (p. 163).
- Sanchez, P., Saura, J. R., & Ayestaran, R. (2021). An exploratory approach to the adoption process of bitcoin by business executives. Mathematics, 9(4), 355.
- Schermelleh-Engel, K., Moosbrugger, H. & Müller, H. (2003). Evaluating the fit of structural equation models: Tests of significance and descriptive goodness-of-fit measures. Methods of Psychological Research Online, 8(2), 23-74.
- Shrestha, A. K., & Vassileva, J. (2019). “User Acceptance of Usable Blockchain-Based Research Data Sharing System: an Extended TAM-Based Study”, In 2019 First IEEE International Conference on Trust, Privacy and Security in Intelligent Systems and Applications (TPS-ISA) (pp. 203-208). IEEE.
- Silva, P. M., & Dias, G. A. (2007). Theories about technology accepentace: why the users accept or reject the information technology? Brazilian Journal of Information Science: Research Trends, 1(2), 69-91.
- Siyam, N. (2019). Factors impacting special education teachers’ acceptance and actual use of technology. Education and Information Technologies, 24(3), 2035-2057.
- Stevens, J. (1996). Applied Multivariate Statistics for the Social Sciences, (3rd edition), Mahwah, Lawrence Erlbaum: New Jersey.
- Teo, A. C., Tan, G. W. H., Cheah, C. M., Ooi, K. B., & Yew, K. T. (2012). Can the demographic and subjective norms influence the adoption of mobile banking? International Journal of Mobile Communications, 10(6), 578-597.
- Toraman, Y. (2021). Blokzincir teknolojisinin benimsenmesinin teknoloji kabul modeli çerçevesinde incelenmesi: kripto (dijital) paralar üzerine bir araştırma. Journal Of Social, Humanities and Administrative Sciences, 7(45), 1841-1856.
- Türker, A., & Türker, Ö. G. (2013). Turistik ürün satın alma davranışının teknoloji kabul modeli ile incelenmesi. Dokuz Eylül Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 15(2), 281-312.
- Venkatesh, V. & Davis, F.D. (2000). A theoretical extension of the technology acceptance model: four longitudinal field studies, Management Science, 46(2), 186-204.
- Wang, Y., Wang, S., Wang, J., Wei, J., & Wang, C. (2020). An empirical study of consumers’ intention to use ride-sharing services: Using an extended tecnology acceptance model. Transportation, 47(1), 397-415.
- Yılmaz, C., & Tümtürk, A. (2015). Internet üzerinden alisveris niyetini etkileyen faktörlerin genisletilmis teknoloji kabul modeli kullanarak ıncelenmesi ve bir model önerisi. Yonetim ve Ekonomi, 22(2), 355-384.
Toplam 47 adet kaynakça vardır.
Ayrıntılar
| Birincil Dil | Türkçe |
|---|---|
| Konular | İşletme |
| Bölüm | Makaleler |
| Yazarlar | |
| Erken Görünüm Tarihi | 29 Ağustos 2022 |
| Yayımlanma Tarihi | 29 Ağustos 2022 |
| Gönderilme Tarihi | 21 Şubat 2022 |
| Yayımlandığı Sayı | Yıl 2022 Cilt: 6 Sayı: 1 |
