AN INVESTIGATION OF THE KEY DETERMINANTS OF INTENTION TO USE PAYMENT WITH CRYPTOCURRENCY: THE CASE OF RESTAURANT BUSINESSES

Year 2023, , 461 - 479, 31.10.2023

Duran Cankül , Kevser Çınar , Mustafa Çağatay Kızıltaş , Işıl Cankül

https://doi.org/10.32958/gastoria.1297334

Abstract

With the developments in technology, it has started to be used as an additional payment method in businesses due to the emergence and increasing popularity of cryptocurrencies. This study was aimed to measure the factors that affect the customers' intention to use cryptocurrency technology as a payment method in restaurants, by examining the four dimensions of mindfulness and the positive valences and the negative valences of the valence theory. In this context, an online survey was applied to 405 cryptocurrency users to collect data. Confirmatory factor analysis (CFA) was used to verify the measurement model, and the structural equation model (SEM) was used to test the model. The findings of the study reveal that the participants think that the convenience of using this method has no effect on the intention to use it, that using this method is beneficial, not risky, and that they will not have any privacy concerns if they use this method. This study offers valuable practical implications for restaurant operators in the context of cryptocurrency payment systems. This study successfully extended valence theory by adding awareness to valence theory.

Keywords

cryptocurrency, blockchain customer intentions, restaurant business

An Investigation Of The Key Determinants Of Intention To Use Payment With Cryptocurrency: The Case Of Restaurant Businesses

Abstract

With the developments in technology, it has started to be used as an additional payment method in businesses due to the emergence and increasing popularity of cryptocurrencies. This study was aimed to measure the factors that affect the customers' intention to use cryptocurrency technology as a payment method in restaurants, by examining the four dimensions of mindfulness and the positive valences and the negative valences of the valence theory. In this context, an online survey was applied to 405 cryptocurrency users to collect data. Confirmatory factor analysis (CFA) was used to verify the measurement model, and the structural equation model (SEM) was used to test the model. The findings of the study reveal that the participants think that the convenience of using this method has no effect on the intention to use it, that using this method is beneficial, not risky, and that they will not have any privacy concerns if they use this method. This study offers valuable practical implications for restaurant operators in the context of cryptocurrency payment systems. This study successfully extended valence theory by adding awareness to valence theory.

Keywords

cryptocurrency, blockchain customer intentions, restaurant business

References

• Alaeddin, O., & Altounjy, R. (2018). Trust, Technology Awareness and Satisfaction Effect into the Intention to Use Cryptocurrency among Generation Z in Malaysia. International Journal of Engineering & Technology, 7(4), 8-10.
• Albayati, H., Kim, S., & Rho, J. (2020). Accepting financial transactions using blockchain technology and cryptocurrency: A customer perspective approach. Technology in Society, 62, 1-14.
• Alqaryouti, O., Siyam, N., Alkashri, Z., & Shaalan, K. (2020). Cryptocurrency Usage Impact on Perceived Benefits and Users’ Behaviour. M. Themistocleous, & M. Papadaki içinde, Lecture Notes in Business Information Processing (s. 123-136). Springer, Cham.
• Anastasiou, D., Ballis, A., & Drakos, K. (2021). Cryptocurrencies’ Price Crash Risk and Crisis Sentiment. Finance Research Letters, 1-5.
• Antonopoulos, A. (2010). Mastering Bitcoin. O’Reilly Media.
• Atlam, H., & Wills, G. (2018). Technical aspects of blockchain and IoT. Advances in Computers, 115.
• Arias-Oliva, M., Pelegrín-Borondo, J. and Matías-Clavero, G. (2019). Variables influencing cryptocurrency use: a technology acceptance model in Spain, Frontiers in Psychology, 10(475), 1-13.
• Ayedh, A., Echchabi, A., Battour, M., Omar, M. (2020). Malaysian Muslim investors’ behaviour towards the blockchain-based Bitcoin cryptocurrency market, Journal of Islamic Marketing, 12(4), 690–704. https://doi. org/10.1108/JIMA-04-2019-0081.
• Bandara, R., Fernando, M., & Akter , S. (2019). Privacy concerns in E-commerce: A taxonomy and a future research agenda. Electronic Markets, 30, 629-647.
• Bhattacherjee, A., & Premkumar, G. (2004). Understanding changes in belief and attitude toward information technology usage: a theoretical model and longitudinal test. MIS Quarterly, 28(2), 229-254.
• Bishop, S., Lau, M., Shapiro, S., Carlson, L., Anderson, N., Carmody, J., . . . Devins, G. (2004). Mindfulness: A Proposed Operational Definition. Clinical Psychology Science and Practice, 11(3), 230-241.
• Blau, B. (2018). Price dynamics and speculative trading in Bitcoin. Research in International Business and Finance, 43, 15-21.
• Boireau, O. (2018). Securing the blockchain against hackers. Network Security, 2018(1), 8-11.
• Boison, D., & Antwi-Boampong, A. (2020). Blockchain Ready Port Supply Chain Using Distributed Ledger. Nordic and Baltic Journal of Information and Communications Technologies, 1, 1-32.
• Bziker, Z. (2021). The status of cryptocurrency in Morocco. Research in Globalization, 3, 1-8.
• Caporale, G., Kang, W.-Y., Spagnolo, F., & Spagnolo, N. (2021). Cyber-attacks, spillovers and contagion in the cryptocurrency markets. Journal of International Financial Markets, Institutions and Money, 1-19.
• Caro, M., Ali, M., Vecchio, M., & Giaffreda, R. (2018). Blockchain-based Traceability in Agri-Food Supply Chain Management: A Practical Implementation. 2018 IoT Vertical and Topical Summit on Agriculture (s. 1-4). Tuscany: IEEE.
• Chen, X., & Li, S. (2017). Understanding continuance intention of mobile payment services: an empirical study. Journal of Computer Information Systems, 57(4), 287-298.
• Chin, A., Harris, M., & Brookshire, R. (2020). An empirical investigation of intent to adopt mobile payment systems using a trust-based extended valence framework. Information Systems Frontiers, 1-19.
• De Kerviler, G., Demoulin, N., & Zidda, P. (2016). Adoption of in-store mobile payment: are perceived risk and convenience the only drivers? Journal of Retailing and Consumer Services, 31, 334-344.
• Deery, H. (2000). Hazard and risk perception among young novice drivers. Journal of Safety Research, 30(4), 225-236.
• Dinev, T., & Hart, P. (2006). An Extended Privacy Calculus Model for E-Commerce Transactions. Information Systems Research, 17(1), 61-80.
• Douglas, A., Holloway, R., Lohr, J., Morgan, E., & Harfoush, K. (2020). Blockchains for constrained edge devices. Blockchain: Research and Applications, 1(1-2), 1-7.
• Efanov, D., & Roschin, P. (2018). The All-Pervasiveness of the Blockchain Technology. Procedia Computer Science, 123, 116-121.
• Feather, N. (1988). Values, Valences, and Course Enrollment: Testing the Role of Personal Values Within an Expectancy-Valence Framework. Journal of Educational Psychology, 80(3), 381-391.
• Featherman, M., & Pavlou, P. (2003). Predicting e-services adoption: a perceived risk facets perspective. International Journal of Human-Computer Studies, 59(4), 451-474.
• Fiol, M., & O’Connor, E. (2003). Waking up! Mindfulness in the face of bandwagons. Academy of Management Review, 28(1), 54-70.
• Flavian, C., Guinaliu, M., & Lu, Y. (2020). Mobile payments adoption – introducing mindfulness to better understand consumer behavior. International Journal of Bank Marketing, 38(7), 1575-1599.
• Folkinshteyn, D., & Lennon, M. (2016). Braving Bitcoin: A technology acceptance model (TAM) analysis. Journal of Information Technology Case and Application Research, 220-249.
• Fornell, C., & Larcker, D. (1981). Structural equation models with unobservable variables and measurement error: algebra and statistics. Journal of Marketing Research (JMR), 18(3), 382-388.
• Francisco, K., & Swanson, D. (2018). The Supply Chain Has No Clothes: Technology Adoption of Blockchain for Supply Chain Transparency. Digital Logistics, 2(1), 1-13.
• Frauman, E., & Norman, W. C. (2004). Mindfulness as a tool for managing visitors to tourism destinations. Journal of Travel Research, 42, 381–389.
• Gao, L., & Waechter, K. (2017). Examining the role of initial trust in user adoption of mobile payment services: an empirical investigation. Information Systems Frontiers, 19, 525-548.
• Gupta, S., Gupta, S., Mathew, M., & Sama , H. (2020). Prioritizing intentions behind investment in cryptocurrency: a fuzzy analytical framework. Journal of Economic Studies, 1-18.
• Hamrick, J., Rouhi, F., Mukherjee, A., Feder, A., Gandal, N., Moore, T., & Vasek, M. (2021). An examination of the cryptocurrency pump-and-dump ecosystem. Information Processing & Management, 58(4), 1-16.
• Hasso, T., Pelster, M., & Breitmayer, B. (2019). Who trades cryptocurrencies, how do they trade it, and how do they perform? Evidence from brokerage accounts. Journal of Behavioral and Experimental Finance, 23, 64-74.
• He, Q., Xu, Y., Liu, Z., He, J., Sun, Y., & Zhang, R. (2018). rivacy-preserving Internet of Things device management scheme based on blockchain. International Journal of Distributed Sensor Networks, 14(11), 1-12.
• Henderson, J. C. (1997). Singapore’s wartime heritage attractions. Journal of Tourism Studies, 8(2), 39–49.
• Iansati, M., & Lakhani, K. (2017). The Truth About Blockchain. Harvard Business Review. Harvard Business Review, 95(1), 4-11.
• Ikeda, K. (2018). Security and Privacy of Blockchain and Quantum Computation. Advances in Computers, 111, 199-228.
• Jayawardhena, C., & Foley, P. (2000). Changes in the banking sector – the case of Internet banking in the UK. Internet Research, 10(1), 19-31.
• Jeung-tai, E., & Chihui, C. (2009). Perceived Innovativeness, Perceived Convenience and TAM: Effects on Mobile Knowledge Management. 2009 Third International Conference on Multimedia and Ubiquitous Engineering (s. 413-420). Qingdao, China: IEEE.
• Ji-Xi, J., Salamzadeh, Y., & Teoh, A. (2021). Behavioral intention to use cryptocurrency in Malaysia: an empirical study. The Bottom Line, 34(2), 170-197.
• Joo, M., Nishikawa, Y., & Dandapani, K. (2019). Cryptocurrency, a successful application of blockchain technology. Managerial Finance, 46(6), 715-733.
• Kahn, C., & Rivadeneyra, F. (2020). Security and convenience of a central bank digital currency. Ottawa: Bank of Canada.
• Kamilaris, A., Fonts, A., & Prenafeta-Boldύ, F. (2019). The rise of blockchain technology in agriculture and food supply chains. Trends in Food Science & Technology, 91, 640-652.
• Kim, D., Ferrin, D., & Rao, H. (2009). Trust and Satisfaction, Two Stepping Stones for Successful E-Commerce Relationships: A Longitudinal Exploration. Information Systems Research, 20(2), 237-257.
• Kim, S. (2018). Blockchain for a Trust Network Among Intelligent Vehicles. Advances in Computers, 111, 43-68.
• Li, C., Zhang, J., Yang, X., & Youlong, L. (2021). Lightweight blockchain consensus mechanism and storage optimization for resource-constrained IoT devices. Information Processing & Management, 58(4), 1-24.
• Lin, W.-B. (2008). Investigation on the model of consumers’ perceived risk—integrated viewpoint. Expert Systems with Applications, 34(2), 977-988.
• Liu, C., Marchewka, J., Lu, J., & Yu, C.-S. (2005). Beyond concern—a privacy-trust-behavioral intention model of electronic commerce. Information & Management, 42(2), 289-304.
• López-Nicolás, C., Molina-Castillo, F., & Bouwman, H. (2008). An assessment of advanced mobile services acceptance: Contributions from TAM and diffusion theory models. Information & Management, 45(6), 359-364.
• Marthinsen, J., & Gordon, S. (2020). Hyperinflation, Optimal Currency Scopes, and a Cryptocurrency Alternative to Dollarization. The Quarterly Review of Economics and Finance, 1-13.
• McGovern, T. (2022, March 22). Cryptocurrency Statics 2022: How Many People Use Crypto? Earthweb: https://earthweb.com/cryptocurrency-statistics/
• Miraz, M., Hasan, M., Rekabder, M., & Akhter, R. (2022). Trust, Transaction, Transparency, Volatility, Facilitating Condition, Performance Expectancy Towards Cryptocurrency Adoption Through Intention To Use. Journal of Management Information and Decision Sciences, 25(1), 1-20.
• Moscardo, G. (2009). Understanding tourist experience through mindfulness theory. In M. Kozak & A. Decrop (Eds.), Handbook of tourist behaviour: Theory & practice (pp. 102–115). New York, NY: Routledge.
• Mou, J., Cohen, J., Dou, Y., & Zhang, B. (2017). Predıctıng Buyers’ Repurchase Intentıons In Cross-Border E-Commerce: A Valence Framework Perspectıve. In Proceedings of the 25th European Conference on Information Systems (s. 2382-2394). Guimarães, Portugal: Research Papers.
• Muzammal, M., Qu, Q., & Nasrulin, B. (2019). Renovating Blockchain With Distributed Databases: An open source system. Future Generation Computer Systems, 90, 105-117.
• Nabilou, H. (2019). The dark side of licensing cryptocurrency exchanges as payment institutions. Law and Financial Markets Review, 14(1), 39-47.
• Nuryyev, G., Spyridou, A., Yeh, S., & Achyldurdyyeva, J. (2018). Factors influencing the intention to use cryptocurrency payments: an examination of blockchain economy. Tourman 2018 Conference Proceedings (s. 303-310). Rhodes: Greece: Munich Personal RePEc Archive.
• Oredo, J.O., & Njihia, J.M. (2015). Mindfulness and quality of innovation in cloud computing adoption, International Journal of Business and Management, 10 (1), 144.
• Ozturk, A., Bilgihan, A., Salehi-Esfahani, S., & Hua, N. (2017). Understanding the mobile payment technology acceptance based on valence theory: A case of restaurant transactions. International Journal of Contemporary Hospitality Management, 29(8), 2027-2049.
• Peter, J., & Tarpey, L. (1975). A Comparative Analysis of Three Consumer Decision Strategies. Journal of Consumer Research, 2(1), 29-37.
• Ramachandran, T., & Stella, M. (2022). Behavioural Intention Towards Cryptocurrency Adoption Among Students: A Fintech Innovation. Journal of Positive School Psychology, 5046 – 5053-5046 – 5053.
• Roberts, N. H., Thatcher, J. B., & Klein, R. (2007). Using information technology mindfulness. In Proceedings of the Southern Association for Information Systems.
• Rosenberg, E. (2004). Mindfulness and consumerism. T. Kasser, & A. Kanner içinde, Psychology and consumer culture: The struggle for a good life in a materialistic world (s. 107-125). American Psychological Association. Shahzad, F., Xiu, G., Wang, J., & Shahbaz, M. (2018). An empirical investigation on the adoption of cryptocurrencies among the people of mainland China. Technology in Society, 55, 33-40.
• Sheng, H., Nah, F.-H., & Siau, K. (2008). An Experimental Study on U-commerce Adoption: Impact of Personalization and Privacy Concerns. Journal of the AIS, 9(6), 344-376.
• Sullivan, Y., & Kim, D. (2018). Assessing the effects of consumers' product evaluations and trust on repurchase intention in e-commerce environment. International Journal of Information Management, 39, 199-219.
• Sun, H., & Fang, Y. (2010). Toward a Model of Mindfulness in Technology Acceptance. ICIS 2010 Proceedings, 121.
• Sun, H., Fang, Y., & Zou, H. (2016). Choosing a Fit Technology: Understanding Mindfulness in Technology Adoption and Continuance. Journal of the Association for Information Systems, 17(6), 377-412.
• Swan, M. (2018). Blockchain for Business: Next-Generation Enterprise Artificial Intelligence Systems. Advances in Computers, 111, 121-162.
• Tamphakdiphanit, J., & Laokulrach, M. (2020). Regulations and Behavioral Intention for Use Cryptocurrency in Thailand. Journal of Applied Economic Sciences, 15, 523-531.
• Titov , V., Uandykova , M., Litvishko , O., Kalmykova , T., Prosekov, S., & Senjyu, T. (2021). Cryptocurrency Open Innovation Payment System: Comparative Analysis of Existing Cryptocurrencies. Journal of Open Innovation: Technology, Market, and Complexity, 7(1), 1-13.
• Underwood, S. (2016). Blockchain beyond bitcoin. Communications of the ACM, 15-17.
• Van Eerde, W., & Thierry, H. (1996). Vroom’s expectancy models and work-related criteria: a metaanalysis, Journal of Applied Psychology, 81(5), 575-586
• Wang, K. (2021). Measuring Global Crypto Users A Study to Measure Market Size Using On-Chain Metrics. Crypto.com.
• Wang, Q., & Su, M. (2020). Integrating blockchain technology into the energy sector — from theory of blockchain to research and application of energy blockchain. Computer Science Review, 1-25.
• Yahanpath, N., & Wilton, Z. (2014). Virtual Money Betting On Bitcoin. University of Auckland Business Review, 17(1), 37-43.
• Yang, S., Chen, Y., & Wei, J. (2015). Understanding consumers' web-mobile shopping extension behavior: a trust transfer perspective. Journal of Computer Information Systems, 55(2), 78-87.
• Yang, S., Lu, Y., Gupta, S., Cao, Y., & Zhang, R. (2012). Mobile payment services adoption across time: an empirical study of the effects of behavioral beliefs, social influences, and personal traits. Computers in Human Behavior, 28(1), 129-142.
• Yeong, Y.-C., Kalid, K., Savita, K., Ahmad, M., & Zaffar, M. (2022). Sustainable cryptocurrency adoption assessment among IT enthusiasts and cryptocurrency social communities. Sustainable Energy Technologies and Assessments, 52, 1-15.
• Yoon, C., & Kim, S. (2007). Convenience and TAM in a ubiquitous computing environment: The case of wireless LAN. Electronic Commerce Research and Applications, 6(1), 102-112.
• Zhong, H., Zhang, F., & Gu, Y. (2021). A Stackelberg game based two-stage framework to make decisions of freight rate for container shipping lines in the emerging blockchain-based market. Transportation Research Part E: Logistics and Transportation Review, 149, 1-24.