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Original Articles

Can Stablecoins Foster Cryptocurrencies Adoption?

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References

  • Mattke J, Maier C, Reis L, Weitzel T. Bitcoin investment: a mixed methods study of investment motivations. Eur J Inf Syst. 2021;30(3):261–85. doi:10.1080/0960085X.2020.1787109.
  • Zohar A. Bitcoin: under the hood. Commun ACM. 2015;58(9):104–13. doi:10.1145/2701411.
  • Abramova S, Böhme R. Perceived benefit and risk as multidimensional determinants of Bitcoin use: a quantitative exploratory study [Internet]. 2016. https://aisel.aisnet.org/icis2016/Crowdsourcing/Presentations/19/
  • Li X, Whinston AB. Analyzing cryptocurrencies. Inform Syst Front. 2020;22(1):17–22. doi:10.1007/s10796-019-09966-2.
  • Carvalho A, Sambhara C, Young P. What the history of Linux says about the future of cryptocurrencies. Commun Assoc Inf Syst. 2020;46(1):2. doi:10.17705/1CAIS.04602.
  • Hsu WS, Au CH, Shieh P-H. Can stablecoins foster cryptocurrencies adoption? a preliminary study from the push-pull-mooring model perspective [Internet]. 2022. https://acis.aaisnet.org/wp-content/uploads/2022/11/ACIS_2022_paper_71.pdf.
  • Ciaian P, Rajcaniova M, d’Artis K. The economics of BitCoin price formation. Appl Econ. 2016;48(19):1799–815. doi:10.1080/00036846.2015.1109038.
  • Qureshi S, Xiong J. Global financial inclusion and human development: the Bitcoin effect [Internet]. 2018. https://aisel.aisnet.org/cgi/viewcontent.cgi?article=1007&context=globdev2018.
  • Hoang LT, Baur DG. How stable are stablecoins? Eur J Financ. 2021;1–17. doi:10.1080/1351847X.2021.1949369.
  • Lee DKC, Teo EGS. Emergence of FinTech and the LASIC principles. J Financ Perspect. 2015;3(3). doi:10.2139/ssrn.2668049.
  • Nakamoto S. Bitcoin: a peer-to-peer electronic cash system [Internet]. 2008. https://bitcoin.org/bitcoin.pdf .
  • Dumitrescu GC. Bitcoin–a brief analysis of the advantages and disadvantages. Global Econ Obs. 2017;5:63–71.
  • Biryukov A, Tikhomirov S. Security and privacy of mobile wallet users in Bitcoin, Dash, Monero, and Zcash. Pervasive Mob Comput. 2019;59:101030. doi:10.1016/j.pmcj.2019.101030.
  • Zhu F, Chen W, Wang Y, Lin P, Li T, Cao X, Yuan L. Trust your wallet: a new online wallet architecture for Bitcoin [Internet]. 2017. https://ieeexplore.ieee.org/abstract/document/8359562.
  • Kazan E, Tan C-W, Lim ETK. Value creation in cryptocurrency networks: towards a taxonomy of digital business models for Bitcoin companies [Internet]. 2015. https://aisel.aisnet.org/pacis2015/34/.
  • Fröhlich M, Wagenhaus M, Schmidt A, Alt F. Don’t stop me now! exploring challenges of first-time cryptocurrency users. The 2021 ACM Designing Interactive Systems Conference; 2021; New York, NY, United States.
  • Voskobojnikov A, Wiese O, Mehrabi Koushki M, Roth V, Beznosov K. The U in crypto stands for usable: an empirical study of user experience with mobile cryptocurrency wallets. Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems; 2021. p. 1–14; Yokohama, Japan.
  • Wei WC. The impact of Tether grants on Bitcoin. Econ Lett. 2018;171:19–22. doi:10.1016/j.econlet.2018.07.001.
  • Thanh BN, Hong TNV, Pham H, Cong TN, Anh TPT. Are the stabilities of stablecoins connected? J Ind Bus Econ. 2022. doi:10.1007/s40812-022-00207-3.
  • Moin A, Sirer EG, Sekniqi K. SoK: a classification framework for stablecoin designs. International Conference on Financial Cryptography and Data Security; 2020; Kota Kinabalu, Malaysia.
  • Mita M, Ito K, Ohsawa S, Tanaka H. What is stablecoin?: a survey on price stabilization mechanisms for decentralized payment systems. 2019 8th International Congress on Advanced Applied Informatics (IIAI-AAI); 2019; [place unknown]: IEEE. p. 60–66; Toyama, Japan.
  • Liao GY, Caramichael J. Stablecoins: growth potential and impact on banking. Int Finance Discuss Pap. 2022;2022(1334):1–26. doi:10.17016/IFDP.2022.1334.
  • Sidorenko EL. Stablecoin as a new financial instrument. In: Ashmarina SI, Vochozka M, Mantulenko VV, editors. Digital age: chances, challenges and future. Berlin (Germany): Springer International Publishing; 2020. p. 630–38. doi:10.1007/978-3-030-27015-575.
  • Arner D, Auer R, Frost J. Stablecoins: risks, potential and regulation [Internet]. 2020 [accessed 2023 Feb 6]. https://www.bis.org/publ/work905.htm.
  • Li C, Shen Y. The potential impacts and risks of global stablecoins. China Econ J. 2021;14(1):39–51. doi:10.1080/17538963.2021.1872167.
  • Ante L, Fiedler I, Strehle E. The influence of stablecoin issuances on cryptocurrency markets. Financ Res Lett. [Internet]. 2021;41:101867. https://www.sciencedirect.com/science/article/abs/pii/S1544612320316810.
  • Lagna A, Ravishankar MN. Making the world a better place with fintech research. Inform Syst J. 2022;32(1):61–102. doi:10.1111/isj.12333.
  • Lee ES. A theory of migration. Demography. 1966;3(1):47–57. doi:10.2307/2060063.
  • Moon B. Paradigms in migration research: exploring “moorings” as a schema. Prog Hum Geogr. 1995;19(4):504–24. doi:10.1177/030913259501900404.
  • Bansal HS. “Migrating” to new service providers: toward a unifying framework of consumers’ switching behaviors. J Acad Mark Sci. 2005;33(1):96–115. doi:10.1177/0092070304267928.
  • Longino CF Jr. The forest and the trees: micro-level considerations in the study of geographic mobility in old age. In: Rogers A, Frey WH, editors. Elderly Migr Popul Redistribution. New York (USA): Wiley; 1992. p. 23–34.
  • Hou ACY, Chern C-C, Chen H-G, Chen Y-C. ‘Migrating to a new virtual world’: exploring MMORPG switching through human migration theory. Comput Human Behav. 2011;27(5):1892–903. doi:10.1016/j.chb.2011.04.013.
  • Lai J, Debbarma S, Ulhas KR. An empirical study of consumer switching behaviour towards mobile shopping: a push–pull–mooring model. Int J Mob Commun. 2012;10(4):386–404. doi:10.1504/IJMC.2012.048137.
  • Fang Y-H, Tang K. Involuntary migration in cyberspaces: the case of MSN messenger discontinuation. Telemat Inform. 2017;34(1):177–93. doi:10.1016/j.tele.2016.05.004.
  • Wu K, Vassileva J, Zhao Y. Understanding users’ intention to switch personal cloud storage services: evidence from the Chinese market. Comput Human Behav. 2017;68:300–14. doi:10.1016/j.chb.2016.11.039.
  • Cheng S, Lee S-J, Choi B. An empirical investigation of users’ voluntary switching intention for mobile personal cloud storage services based on the push-pull-mooring framework. Comput Human Behav. 2019;92:198–215. doi:10.1016/j.chb.2018.10.035.
  • Wang L, Luo XR, Yang X, Qiao Z. Easy come or easy go? empirical evidence on switching behaviors in mobile payment applications. Inf Manage. 2019;56(7):103150. doi:10.1016/j.im.2019.02.005.
  • Kuo R-Z. Why do people switch mobile payment service platforms? an empirical study in Taiwan. Technol Soc. 2020;62:101312. doi:10.1016/j.techsoc.2020.101312.
  • Lin C-L, Jin YQ, Zhao Q, Yu S-W, Su Y-S. Factors influence students’ switching behavior to online learning under COVID-19 pandemic: a Push-Pull-Mooring model perspective. Asia Pac Educ Res. 2021;30(3):229–45. doi:10.1007/s40299-021-00570-0.
  • Loh X-M, Lee V-H, Tan G-H, Ooi K-B, Dwivedi YK. Switching from cash to mobile payment: what’s the hold-up? Internet Res. [Internet]. 2021;31(1):376–99. doi:10.1108/INTR-04-2020-0175.
  • Au CH, Law KMY, Chiu DKW, Ho KKW. Investigating mainstreaming strategies of hot cryptocurrencies-wallet [Internet]. 2022. https://aisel.aisnet.org/acis2022/1/.
  • Dierksmeier C, Seele P. Cryptocurrencies and business ethics. J Bus Ethics. 2018;152(1):1–14. doi:10.1007/s10551-016-3298-0.
  • Dimitrov DM, Rumrill PD Jr. Pretest-posttest designs and measurement of change. Work. 2003;20:159–65.
  • Isaac O, Aldholay A, Abdullah Z, Ramayah T. Online learning usage within Yemeni higher education: the role of compatibility and task-technology fit as mediating variables in the is success model. Comput Educ. 2019;136:113–29. doi:10.1016/j.compedu.2019.02.012.
  • Ndubisi NO, Nataraajan R, Lai R. Customer perception and response to ethical norms in legal services marketing. J Bus Res. 2014;67(3):369–77. doi:10.1016/j.jbusres.2013.01.001.
  • Evjemo B, Castejón-Martínez H, Akselsen S. Trust trumps concern: findings from a seven-country study on consumer consent to ‘digital native’vs.‘digital immigrant’service providers. Behav Inf Technol. 2019;38(5):503–18. doi:10.1080/0144929X.2018.1541254.
  • Chiu C, Chiu C, Chang H. Examining the integrated influence of fairness and quality on learners’ satisfaction and web‐based learning continuance intention. Inform Syst J. 2007;17(3):271–87. doi:10.1111/j.1365-2575.2007.00238.x.
  • Chen X, Li S. Understanding continuance intention of mobile payment services: an empirical study. J Comput Inf Syst. 2017;57(4):287–98. doi:10.1080/08874417.2016.1180649.
  • Maier C, Laumer S, Wirth J, Weitzel T. Technostress and the hierarchical levels of personality: a two-wave study with multiple data samples. Eur J Inf Syst. 2019;28(5):496–522. doi:10.1080/0960085X.2019.1614739.
  • Jia R, Steelman ZR, Reich BH. Using mechanical turk data in IS research: risks, rewards, and recommendations. Commun Assoc Inf Syst. 2017;41(1):301–18. doi:10.17705/1CAIS.04114.
  • Smith NA, Sabat IE, Martinez LR, Weaver K, Xu S. A convenient solution: using MTurk to sample from hard-to-reach populations. Ind Organ Psychol. 2015;8(2):220–28. doi:10.1017/iop.2015.29.
  • Mummolo J, Peterson E. Demand effects in survey experiments: an empirical assessment. Am Polit Sci Rev. 2019;113(2):517–29. doi:10.1017/S0003055418000837.
  • Cheung JH, Burns DK, Sinclair RR, Sliter M. Amazon mechanical turk in organizational psychology: an evaluation and practical recommendations. J Bus Psychol. 2017;32(4):347–61. doi:10.1007/s10869-016-9458-5.
  • Rogers EM. Diffusion of innovations. New York (USA): Simon and Schuster; 2010.
  • Davis FD. Perceived usefulness, perceived ease of use, and user acceptance of information technology. Mis Q. 1989;13(3):319–40. doi:10.2307/249008.
  • Sun S, Cegielski CG, Jia L, Hall DJ. Understanding the factors affecting the organizational adoption of big data. J Comput Inf Syst. 2018;58(3):193–203. doi:10.1080/08874417.2016.1222891.
  • Santos F, Pache A-C, Birkholz C. Making hybrids work: aligning business models and organizational design for social enterprises. Calif Manage Rev. 2015;57(3):36–58. doi:10.1525/cmr.2015.57.3.36.
  • Pecot F, Vasilopoulou S, Cavallaro M. How political ideology drives anti-consumption manifestations. J Bus Res. 2021;128:61–69. doi:10.1016/j.jbusres.2021.01.062.
  • Nurbaev V, Au CH, Chou C-Y. What drives neobanks business success? – a case study on tinkoff. DIGIT 2022 Proceedings; 2022; Copenhagen, Denmark.

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