TÜKETİCİLERİN ALIŞVERİŞ İÇİN DİJİTAL PARA BİRİMİNİ KULLANMA NİYETLERİNİN İNCELENMESİ

Öz

Bu çalışma, tüketicilerin alışveriş için dijital para birimini kullanma niyetlerini incelemeyi amaçlamaktadır. Bu amaçla online anket yöntemi kullanılarak 230 kişiden veri toplanmıştır. Hipotezlerin analizi için istatistiksel analizler yapılmıştır. Tek örneklem t-testi sonucuna göre; dijital para birimi, tüketicilerin alışveriş için dijital para birimini kullanma niyeti üzerinde önemli olumlu bir etkiye sahiptir. Bağımsız örneklem t-testi sonuçlarına göre; cinsiyetler arasında dijital para birimi kullanma niyetinde anlamlı bir farklılık vardır. Erkekler, dijital para birimini kullanarak satın alma yapma konusunda daha isteklidir. Ancak ANOVA sonuçlarına göre; jenerasyonlar arasında dijital para birimi kullanma niyetinde anlamlı bir farklılık yoktur. Basit doğrusal regresyon analizi sonuçlarına göre, algılanan yenilikçilik, zevk, kullanım kolaylığı, fayda, erişim hızı ve güven, dijital para birimi kullanma niyeti üzerinde anlamlı olumlu bir etkiye sahiptir. Algılanan risk, dijital para birimi kullanma niyeti üzerinde anlamlı olumsuz bir etkiye sahiptir. Ancak, algılanan finansal maliyetin dijital para birimi kullanma niyeti üzerindeki etkisi anlamlı değildir. Öneriler çalışmanın sonunda verilmiştir.

Anahtar Kelimeler

• Dijital Para Birimi
• Online Alışveriş
• Kullanma Niyeti

INVESTIGATION OF CONSUMERS' INTENTIONS TO USE DIGITAL CURRENCY FOR SHOPPING

Öz

This study aims to examine the intentions of consumers to use digital currency for shopping. For this aim, data were collected from 230 people using the online survey method. Statistical analyzes were performed for the analysis of the hypotheses. According to the one-sample t-test result; digital currency has a significant positive effect on consumers' intention to use digital currency for shopping. According to the independent samples t-test results; there is a significant difference in the intention to use digital currency between genders. Male are more intent on making purchases using digital currency. However, according to the results of ANOVA; there is no significant difference in the intention to use digital currency between generations. According to the results of simple linear regression analysis, perceived innovativeness, enjoyment, ease of use, usefulness, speed of access, and trust have a significant positive effect on the intention to use digital currency. Perceived risk has a significant negative effect on the intention to use digital currency. However, the effect of perceived financial cost on the intention to use a digital currency is not significant. Recommendations are provided at the end of the study.

Anahtar Kelimeler

• Digital Currency
• Online Shopping
• Intention to Use

Kaynakça

1. Abramova, S., & Böhme, R. (2016). Perceived benefit and risk as multidimensional determinants of Bitcoin use: A quantitative exploratory study. In thirty seventh international conference on information systems, Dublin, 1-20.
2. Alaklabı S., & Kang K. (2021). Perceptions towards cryptocurrency adoption: A case of Saudi Arabian citizens. Journal of electronic banking systems, 2021 (2021), 1-17
3. Alharbi, A., & Sohaib, O. (2021). Technology readiness and cryptocurrency adoption: PLS-SEM and deep learning neural network analysis. IEEE access, 9, 21388-21394.
4. Alqaryouti, O., Siyam, N., Alkashri, Z., & Shaalan, K. (2019). Cryptocurrency usage impact on perceived benefits and users’ behaviour. In European, mediterranean, and middle eastern conference on ınformation systems (pp. 123-136). Springer, Cham.
5. Arias-Oliva, M., Pelegrín-Borondo, J., & Matías-Clavero, G. (2019). Variables influencing cryptocurrency use: A technology acceptance model in Spain. Frontiers in psychology, 10, 475.
6. Anser, M. K., Zaigham, G. H. K., Imran Rasheed, M., Pitafi, A. H., Iqbal, J., & Luqman, A. (2020). Social media usage and individuals' intentions toward adopting Bitcoin: The role of the theory of planned behavior and perceived risk. International journal of communication systems, 33(17), e4590.
7. Ariff, M. S. M., Sylvester, M., Zakuan, N., Ismail, K., & Ali, K. M. (2014). Consumer perceived risk, attitude and online shopping behaviour; empirical evidence from Malaysia. In IOP conference series: Materials science and engineering (58/1, 012007). IOP Publishing.
8. Atlantic Council (2021). Central bank digital currency (CBDC) tracker https://www.atlanticcouncil.org/cbdctracker/. (Access Date, 06.09.2021).

9. Bhattacherjee, A. (2002). Individual trust in online firms: Scale development and initial test. Journal of management information systems, 19(1), 211-241.
10. Bordo, M. D., & Levin, A. T. (2017). Central bank digital currency and the future of monetary policy (No. w23711). National Bureau of Economic Research.
11. Brunnermeier, M. K., James, H., & Landau, J. P. (2019). The digitalization of money (No. w26300). National Bureau of Economic Research.
12. Childers, T. L., Carr, C. L., Peck, J., & Carson, S. (2001). Hedonic and utilitarian motivations for online retail shopping behavior. Journal of retailing, 77(4), 511-535.
13. Chong, A. Y. L., Ooi, K. B., Lin, B., & Tan, B. I. (2010). Online banking adoption: An empirical analysis. International journal of bank marketing, 28(4), 267-287.
14. Cruz, P., Neto, L.B.F., Muñoz-Gallego, P., Laukkanen, T. (2010), Mobile banking rollout in emerging Markets: Evidence From Brazil. International journal of bank marketing, 28(5), 342-371.
15. Çetinsöz, B. (2015). Yerli turistlerin e-satın alma eğilimlerinin teknoloji kabul modelinde analizi (TKM). Elektronik sosyal bilimler dergisi, 14(53), 242-258.
16. Dodgson, M., Gann, D., Wladawsky-Berger, I., Sultan, N., & George, G. (2015). Managing digital money. Academy of management journal, 58(2), 325–333.
17. Faqih, K. M. S. (2016). An empirical analysis of factors predicting the behavioral intention to adopt Internet shopping technology among non-shoppers in a developing country context: does gender matter? Journal of retailing and consumer services, 30, 140-164.
18. Field, A. (2000). Discovering statistics using SPSS for windows. London-Thousand Oaks-New Delhi: Sage Publications.
19. Goldsmith, R.E. (2000). Identifying wine innovators: a test of the domain specific innovativeness scale using known groups. International journal of wine marketing, 12(2), 37-46.
20. Hair, J. F., Jr., Black, W. C., Babin, B. J., & Anderson, R. E. (2009). Multivariate data analysis (7th ed.). Upper Saddle River, NJ: Pearson Prentice Hall.
21. Hoffman, D. L., Novak, T. P., & Peralta, M. (1999). Building consumer trust online. Communications of the ACM, 42(4), 80-85.
22. Jeong, B. K., & Yoon, T. E. (2013). An empirical investigation on consumer acceptance of mobile banking services. Business and management research, 2(1), 31-40.
23. Jonker, N. (2019). What drives the adoption of crypto-payments by online retailers?. Electronic commerce research and applications, 35, 100848.
24. Kabak, A., & Çelik, Z. (2020). Tüketicilerin kripto para kullanım niyeti ile ilişkili faktörlerin belirlenmesine yönelik uygulamalı bir araştırma. 6th international GAP social sciences congress, Şanlıurfa-Turkey, 239-252.
25. Kapser, S., & Abdelrahman, M. (2020). Acceptance of autonomous delivery vehicles for last-mile delivery in Germany–Extending UTAUT2 with risk perceptions. Transportation research part C: Emerging technologies, 111, 210-225.
26. Keong, O. C., Leong, T. K., Bio, C. J. (2020). Perceived risk factors affect intention to use FinTech. Journal of accounting and finance in emerging economies, 6(2),453-463.
27. Kim, C., Mirusmonov, M., & Lee, I. (2010). An empirical examination of factors influencing the intention to use mobile payment. Computers in human behavior, 26(3), 310-322.
28. Kim, J. J., Kim, I., & Hwang, J. (2021). A change of perceived innovativeness for contactless food delivery services using drones after the outbreak of COVID-19. International journal of hospitality management, 93, 102758.
29. Kim, J., & Forsythe, S. (2008). Adoption of virtual try-on technology for online apparel shopping. Journal of interactive marketing, 22(2), 45-59.
30. Krishanan, D., Khin, A. A., Teng, K. L. L., & Chinna, K. (2016). Consumers' perceived interactivity & intention to use mobile banking in structural equation modeling. International review of management and marketing, 6(4), 883-890.
31. Koufaris, M. (2002). Applying the technology acceptance model and flow theory to online consumer behavior. Information systems research, 13(2), 205-223.
32. Köse, N., & Yengin, D. (2018). Dijital pazarlamadan fijital pazarlamaya geçişe örnek olarak artırılmış gerçeklik ve sanal gerçeklik uygulamalarının pazarlama üzerindeki katkılarının incelenmesi. İstanbul Aydın Üniversitesi Dergisi, 10(1), 77-111.
33. 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.
34. Löber, K., & Houben, A. (2018). Committee on payments and market ınfrastructures markets committee. Bank for international settlements march-2018.
35. Lu, H. P.., &Yu-Jen Su, P. (2009). Factors affecting purchase intention on mobile shopping web sites. Internet research, 19(4), 442-458.
36. Luarn, P., & Lin, H. H. (2005). Toward an understanding of the behavioral intention to use mobile banking. Computers in human behavior, 21(6), 873-891.
37. Masoud, E. Y. (2013). The effect of perceived risk on online shopping in Jordan. European Journal of business and management, 5(6), 76-87.
38. Maqableh, M., Masa’deh, R. M. T., Shannak, R.O., & Nahar, K. M. (2015). Perceived trust and payment methods: An empirical study of MarkaVIP company. International Journal of communications, network and system sciences, 8(11), 409.
39. Mathieson, K., Peacock, E., & Chin, W. W. (2001). Extending the technology acceptance model: The influence of perceived user resources. ACM SIGMIS database: The DATABASE for advances in information systems, 32(3), 86-112.
40. Nadeem, M. A., Liu, Z., Pitafi, A. H., Younis, A., & Xu, Y. (2020). Investigating the repurchase intention of Bitcoin: Empirical evidence from China. Data technologies and applications, 54(5), 625-642.
41. Nadeem, M. A., Liu, Z., Pitafi, A. H., Younis, A., & Xu, Y. (2021). Investigating the qdoption factors of cryptocurrencies—a cse of Bitcoin: Empirical evidence from China. SAGE open, 11(1), 2158244021998704.
42. Nunnally, J. C. (1978). Psychometric theory. New York: McGraw-Hill. PewInternet.
43. Paçan Özcan, H. P., Sabah Çelik, Ş., & Özer, A. (2019). Bireysel müşterilerin mobil bankacılık kullanım niyetini etkileyen faktörler. Çankırı Karatekin Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 9(2), 475-506.
44. Radner, R., & Rothschild, M. (1975). On the allocation of effort. Journal of economic theory, 10(3), 358-376.
45. Rahmiati, R., Engriani, Y., & Putri, R. R. E. (2019). The influence of trust, perceived usefulness, and perceived ease of using intensity of e-money with attitude toward using intervening variable in Padang City. In Third padang international conference on economics education, economics, business and management, accounting and entrepreneurship (PICEEBA 2019) (pp. 136-141). Atlantis Press.
46. Ramayah, T., Ignatius, J. (2005). Impact of perceived usefulness, perceived ease of use and perceived enjoyment on the ıntention to shop online. ICFAI Journal of systems management (IJSM), III (3): 36-51.
47. Roca, J. C., García, J. J., & De La Vega, J. J. (2009). The importance of perceived trust, security and privacy in online trading systems. Information management & computer security, 17(2), 96-113.
48. Rogers, E. M. (1995). Diffusion of innovations (4th ed). New York: The Free Press.
49. Rosencrance, L. (2021). Compare NFTs vs. cryptocurrency vs. digital currency. https://whatis.techtarget.com/feature/Compare-NFTs-vs-cryptocurrency-vs-digital-currency (Access Date, 06.09.2021).
50. Salam, K. N., & Taufik, M. I. (2020). The Effect of perceived enjoyment on the decision of digital payment utilization in millennial generation. Hasanuddin economics and business review, 4(2), 50-52.
51. Seth, S. (2021). What is a central bank digital currency (CBDC)? https://www.investopedia.com/terms/c/central-bank-digital-currency-cbdc.asp#citation-2 (Access Date, 06.09.2021).
52. 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.
53. Sigar, J. F. (2016). The Influence of perceived usefulness, perceived ease of use and perceived enjoyment to intention to use electronic money in Manado. Jurnal EMBA: Jurnal riset ekonomi, manajemen, bisnis dan akuntansi, 4(2), 498-507.
54. Singh, N., & Sinha, N. (2020). How perceived trust mediates merchant's intention to use a mobile wallet technology. Journal of retailing and consumer services, 52, 101894.
55. Stevens, J. (1996). Applied multivariate statistics for the social sciences, (3rd edition). Mahwah, Lawrence Erlbaum: New Jersey.
56. Stocker, V., & Jason W. (2016). Speed isn't everything: a multicriteria analysis of broadband access speeds in the UK. 27th European regional conference of the international telecommunications society (ITS): "The evolution of the north-south telecommunications divide: The role for europe", Cambridge, United Kingdom, 7th-9th September.
57. Ulaan, R. V., Pangemanan, S. S., & Lambey, L. (2016). The effect of perceived enjoyment on intention to shop online. Jurnal EMBA: Jurnal riset ekonomi, manajemen, bisnis dan akuntansi, 4(1), 1137–1146.
58. 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.
59. Tobbin, P., & Kuwornu, J. (2011). Adoption of mobile money transfer technology: structural equation modeling approach. European journal of business and management, 3(7), 59–77.
60. Walton, A., & Johnston, K. (2018). Exploring perceptions of Bitcoin adoption: The South African virtual community perspective. Interdisciplinary journal of information, knowledge & management, 13, 165-182.
61. Wen, C., Prybutok, V. R., & Xu, C. (2011). An integrated model for customer online repurchase intention. Journal of computer information systems, 52(1), 14-23.
62. Wixom, B. H., & Todd, P. A. (2005). A theoretical integration of user satisfaction and technology acceptance. Information systems research, 16(1), 85-102.
63. Won-jun, L. (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.
64. Wu, S. (2003). The relationship between consumer characteristics and attitude toward online shopping. Marketing intelligence & planning, 21(1), 37-44.
65. Wu, L. Y., Chen, K. Y., Chen, P. Y., & Cheng, S. L. (2014). Perceived value, transaction cost, and repurchase-intention in online shopping: A relational exchange perspective. Journal of business research, 67(1), 2768-2776.
66. Vijayasarathy, L.R., & Jones, J.M. (2000). Print and internet catalog shopping: Assessing attitudes and intentions. Internet research, 10, 191-202.
67. Yu, T., & Wu, G, (2007). Determinants of internet shopping behavior: An application of reasoned behavior theory. International journal of management, 24(4), 744-762, 823.
68. Zhang, X., & Yu, X. (2020). The impact of perceived risk on consumers’ cross-platform buying behavior. Frontiers in psychology, 11, 2835.