IDEAS home Printed from https://ideas.repec.org/a/spr/fininn/v10y2024i1d10.1186_s40854-023-00509-y.html
   My bibliography  Save this article

Net valence analysis of iris recognition technology-based FinTech

Author

Listed:
  • Mutaz M. Al-Debei

    (Al-Ahliyya Amman University
    The University of Jordan)

  • Omar Hujran

    (United Arab Emirates University)

  • Ahmad Samed Al-Adwan

    (Al-Ahliyya Amman University)

Abstract

Iris recognition technology (IRT)-based authentication is a biometric financial technology (FinTech) application used to automate user recognition and verification. In addition to being a controversial technology with various facilitators and inhibitors, the adoption of IRT-based FinTech is driven by contextual factors, such as customer perceptions, deployed biometric technology, and financial transaction settings. Due to its controversial and contextual properties, analyzing IRT-based FinTech acceptance is challenging. This study uses a net valence framework to investigate the salient positive and negative factors influencing the intention to use IRT-based FinTech in automated teller machines (ATMs) in Jordan. This study is pertinent because there is a dearth of research on IRT-based FinTech in the relevant literature; most previous research has taken purely engineering and technical approaches. Furthermore, despite considerable investments by banks and other financial institutions in this FinTech, target user adoption is minimal, and only 6% of Jordan’s ATM transactions are currently IRT-enabled. This study employs mixed methods. In the first qualitative study, 17 Jordanian customers were interviewed regarding the benefits and risks of IRT-based FinTech in ATMs. Content analyses determined the most important concepts or themes. The advantages include financial security, convenience, and FinTech-enabled hygiene, whereas the concerns include performance, financial, privacy, and physical risks. The research model is constructed based on the qualitative study and theoretical underpinnings, wherein 631 Jordanian bank customers with active ATM accounts were surveyed to validate the research model. The findings indicate that IRT-based FinTech usage in ATMs is proportional to its perceived value. In descending order of effect, financial security, FinTech-enabled hygiene, and convenience benefits positively impact perceived value. Privacy, financial, and physical risks have negative impacts on perceived value, whereas performance risk has no effect. This study contributes to the relatively untapped domain of biometric technology in information systems, with important theoretical and practical implications.

Suggested Citation

  • Mutaz M. Al-Debei & Omar Hujran & Ahmad Samed Al-Adwan, 2024. "Net valence analysis of iris recognition technology-based FinTech," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 10(1), pages 1-47, December.
    • Handle: RePEc:spr:fininn:v:10:y:2024:i:1:d:10.1186_s40854-023-00509-y
    DOI: 10.1186/s40854-023-00509-y
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1186/s40854-023-00509-y
    File Function: Abstract
    Download Restriction: no
    File URL: https://libkey.io/10.1186/s40854-023-00509-y?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Shankar, Amit & Rishi, Bikramjit, 2020. "Convenience matter in mobile banking adoption intention?," Australasian marketing journal, Elsevier, vol. 28(4), pages 273-285.
    2. Francisco Liébana-Cabanillas & Francisco Muñoz-Leiva & Sebastián Molinillo & Elena Higueras-Castillo, 2022. "Do biometric payment systems work during the COVID-19 pandemic? Insights from the Spanish users' viewpoint," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-25, December.
    3. Ajzen, Icek, 1991. "The theory of planned behavior," Organizational Behavior and Human Decision Processes, Elsevier, vol. 50(2), pages 179-211, December.
    4. Hossain, Mohammad Alamgir & Dwivedi, Yogesh K., 2014. "What improves citizens’ privacy perceptions toward RFID technology? A cross-country investigation using mixed method approach," International Journal of Information Management, Elsevier, vol. 34(6), pages 711-719.
    5. Gianluca Elia & Valeria Stefanelli & Greta Benedetta Ferilli, 2022. "Investigating the role of Fintech in the banking industry: what do we know?," European Journal of Innovation Management, Emerald Group Publishing Limited, vol. 26(5), pages 1365-1393, March.
    6. Liu, Yu-li & Yan, Wenjia & Hu, Bo, 2021. "Resistance to facial recognition payment in China: The influence of privacy-related factors," Telecommunications Policy, Elsevier, vol. 45(5).
    7. Albanna, Hanaa & Alalwan, Ali Abdallah & Al-Emran, Mostafa, 2022. "An integrated model for using social media applications in non-profit organizations," International Journal of Information Management, Elsevier, vol. 63(C).
    8. Jan-Michael Becker & Christian Ringle & Marko Sarstedt & Franziska Völckner, 2015. "How collinearity affects mixture regression results," Marketing Letters, Springer, vol. 26(4), pages 643-659, December.
    9. Sookeun Byun & Sang-Eun Byun, 2013. "Exploring perceptions toward biometric technology in service encounters: a comparison of current users and potential adopters," Behaviour and Information Technology, Taylor & Francis Journals, vol. 32(3), pages 217-230.
    10. Peter, J Paul & Tarpey, Lawrence X, Sr, 1975. "A Comparative Analysis of Three Consumer Decision Strategies," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 2(1), pages 29-37, June.
    11. Roy, Sanjit Kumar & Shekhar, Vaibhav & Lassar, Walfried M. & Chen, Tom, 2018. "Customer engagement behaviors: The role of service convenience, fairness and quality," Journal of Retailing and Consumer Services, Elsevier, vol. 44(C), pages 293-304.
    12. Quoc Trung Pham & Xuan Phuc Tran & Sanjay Misra & Rytis Maskeliūnas & Robertas Damaševičius, 2018. "Relationship between Convenience, Perceived Value, and Repurchase Intention in Online Shopping in Vietnam," Sustainability, MDPI, vol. 10(1), pages 1-14, January.
    13. Eric J. Johnson & John W. Payne, 1985. "Effort and Accuracy in Choice," Management Science, INFORMS, vol. 31(4), pages 395-414, April.
    14. Michael Breward & Khaled Hassanein & Milena Head, 2017. "Understanding Consumers’ Attitudes Toward Controversial Information Technologies: A Contextualization Approach," Information Systems Research, INFORMS, vol. 28(4), pages 760-774, December.
    15. Anol Bhattacherjee & Neset Hikmet, 2007. "Physicians' resistance toward healthcare information technology: a theoretical model and empirical test," European Journal of Information Systems, Taylor & Francis Journals, vol. 16(6), pages 725-737, December.
    16. Alalwan, Ali Abdallah & Dwivedi, Yogesh K. & Rana, Nripendra P. & Algharabat, Raed, 2018. "Examining factors influencing Jordanian customers’ intentions and adoption of internet banking: Extending UTAUT2 with risk," Journal of Retailing and Consumer Services, Elsevier, vol. 40(C), pages 125-138.
    17. Tsai, Juin-Ming & Cheng, Min-Jhih & Tsai, Her-Her & Hung, Shiu-Wan & Chen, Ya-Ling, 2019. "Acceptance and resistance of telehealth: The perspective of dual-factor concepts in technology adoption," International Journal of Information Management, Elsevier, vol. 49(C), pages 34-44.
    18. Edward Shih-Tse Wang & Ruenn-Lien Lin, 2017. "Perceived quality factors of location-based apps on trust, perceived privacy risk, and continuous usage intention," Behaviour and Information Technology, Taylor & Francis Journals, vol. 36(1), pages 2-10, January.
    19. Grewal, Dhruv & Gotlieb, Jerry & Marmorstein, Howard, 1994. "The Moderating Effects of Message Framing and," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 21(1), pages 145-153, June.
    20. Deepa Mangala & Lalita Soni, 2022. "A systematic literature review on frauds in banking sector," Journal of Financial Crime, Emerald Group Publishing Limited, vol. 30(1), pages 285-301, January.
    21. Jen Sheng Wang, 2021. "Exploring biometric identification in FinTech applications based on the modified TAM," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-24, December.
    22. Murinde, Victor & Rizopoulos, Efthymios & Zachariadis, Markos, 2022. "The impact of the FinTech revolution on the future of banking: Opportunities and risks," International Review of Financial Analysis, Elsevier, vol. 81(C).
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Suhail Ahmad Bhat & Sheikh Basharul Islam & Mansoor Farooq Mir, 2024. "Consumers’ attitude toward biometric banking services: an empirical evaluation of determinants and outcomes," Journal of Financial Services Marketing, Palgrave Macmillan, vol. 29(4), pages 1572-1588, December.
    2. Osakwe, Christian Nedu & Ogunmokun, Oluwatobi A. & Elgammal, Islam & Kwarteng, Michael Adu, 2025. "Individuals' attitudes and their adoption intentions of central bank digital currency: Combining theories and analytics for deeper insights," Technological Forecasting and Social Change, Elsevier, vol. 210(C).
    3. Jebarajakirthy, Charles & Shankar, Amit, 2021. "Impact of online convenience on mobile banking adoption intention: A moderated mediation approach," Journal of Retailing and Consumer Services, Elsevier, vol. 58(C).
    4. Shankar, Amit & Rishi, Bikramjit, 2020. "Convenience matter in mobile banking adoption intention?," Australasian marketing journal, Elsevier, vol. 28(4), pages 273-285.
    5. Mashaal A. M. Saif & Nazimah Hussin & Maizaitulaidawati Md Husin & Ayed Alwadain & Ayon Chakraborty, 2022. "Determinants of the Intention to Adopt Digital-Only Banks in Malaysia: The Extension of Environmental Concern," Sustainability, MDPI, vol. 14(17), pages 1-32, September.
    6. Teng Yu & Ai Ping Teoh & Chengliang Wang & Qing Bian, 2024. "Convenient or risky? Investigating the behavioral intention to use facial recognition payment in smart hospitals," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-20, December.
    7. Shahid, Shadma & Islam, Jamid Ul & Malik, Shehla & Hasan, Uzma, 2022. "Examining consumer experience in using m-banking apps: A study of its antecedents and outcomes," Journal of Retailing and Consumer Services, Elsevier, vol. 65(C).
    8. Thomas Dobbelstein & Carina Lochner, 2023. "Factors influencing purchase intention for recycled products: A comparative analysis of Germany and South Africa," Sustainable Development, John Wiley & Sons, Ltd., vol. 31(4), pages 2256-2277, August.
    9. Nitin Walia & Mark Srite & Wendy Huddleston, 2016. "Eyeing the web interface: the influence of price, product, and personal involvement," Electronic Commerce Research, Springer, vol. 16(3), pages 297-333, September.
    10. Garima Malik & A. Sajeevan Rao, 2019. "Extended expectation-confirmation model to predict continued usage of ODR/ride hailing apps: role of perceived value and self-efficacy," Information Technology & Tourism, Springer, vol. 21(4), pages 461-482, December.
    11. repec:dgr:rugsom:04f04 is not listed on IDEAS
    12. Meents, S. & Verhagen, T. & Vlaar, P.W.L., 2011. "How sellers can stimulate purchasing in electronic marketplaces: Using information as a risk reduction signal," Serie Research Memoranda 0014, VU University Amsterdam, Faculty of Economics, Business Administration and Econometrics.
    13. Umara Noreen & Attayah Shafique & Zaheer Ahmed & Muhammad Ashfaq, 2023. "Banking 4.0: Artificial Intelligence (AI) in Banking Industry & Consumer’s Perspective," Sustainability, MDPI, vol. 15(4), pages 1-16, February.
    14. Lingling Gao & Kerem Aksel Waechter, 0. "Examining the role of initial trust in user adoption of mobile payment services: an empirical investigation," Information Systems Frontiers, Springer, vol. 0, pages 1-24.
    15. Khan Burhan Khan & Noor Ismawati Jaafar & Shamshul Bahri Zakaria, 2024. "The role of collectivist cultural practices in supporting a hybrid payment system among small and medium enterprises (SMEs) in Pakistan," Future Business Journal, Springer, vol. 10(1), pages 1-18, December.
    16. Gansser, Oliver Alexander & Reich, Christina Stefanie, 2021. "A new acceptance model for artificial intelligence with extensions to UTAUT2: An empirical study in three segments of application," Technology in Society, Elsevier, vol. 65(C).
    17. Tsai, Pei-Hsuan & Tang, Jia-Wei & Ou, Mei-Ling, 2024. "Applying the extended UTAUT-2 to assess the factors contributing to consumers’ usage intention towards over-the-top video streaming platforms," Journal of Retailing and Consumer Services, Elsevier, vol. 81(C).
    18. Leonie Kuen & Fiona Schürmann & Daniel Westmattelmann & Sophie Hartwig & Shay Tzafrir & Gerhard Schewe, 2023. "Trust transfer effects and associated risks in telemedicine adoption," Electronic Markets, Springer;IIM University of St. Gallen, vol. 33(1), pages 1-22, December.
    19. Yaprak, Ümit & Kılıç, Fatih & Okumuş, Abdullah, 2021. "Is the Covid-19 pandemic strong enough to change the online order delivery methods? Changes in the relationship between attitude and behavior towards order delivery by drone," Technological Forecasting and Social Change, Elsevier, vol. 169(C).
    20. Farzaneh Soleimani Zoghi, "undated". "An Empirical Study On The Impact Of Risk Perception On German Consumers Online Buying Intention," Review of Socio - Economic Perspectives 201935, Reviewsep.
    21. Hossain, Akram & Quaresma, Rui & Rahman, Habibur, 2019. "Investigating factors influencing the physicians’ adoption of electronic health record (EHR) in healthcare system of Bangladesh: An empirical study," International Journal of Information Management, Elsevier, vol. 44(C), pages 76-87.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:fininn:v:10:y:2024:i:1:d:10.1186_s40854-023-00509-y. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.