Mobil Cüzdan Kullanım Niyeti veKişisel Yenilikçiliğin Aracılık Etkisi

Öz

Bu araştırmanın amacı kullanımları dünya genelinde hızla yaygınlaşmakta olan mobil ödeme sistemlerini kullanma niyetleri üzerine etki eden faktörlerin belirlenmesi ve kişisel yenilikçiliğin bu ilişkiler üzerindeki aracılık etkisinin incelenmesidir. Araştırma Türkiye’de faaliyet gösteren telekomünikasyon operatörlerinden birinin mobil ödeme uygulaması olan mobil cüzdan özelinde yürütülmüştür. Mobil operatörün ilgili mobil cüzdan uygulamasını indiren kullanıcılar arasında tesadüfi örnekleme yoluyla seçilen kişiler üzerinde araştırma gerçekleştirilmiştir. Bilgisayar destekli telefon görüşmesi (CATI) yöntemiyle toplanan 667 cevaptan kullanılamayacak durumda olanlar elenerek 640 tanesi analize tabi tutulmuştur. Yüksek kişisel yenilikçilik ve düşük kişisel yenilikçiliğe sahip iki gruba ayrılan örneklem ve ilgili teorilerden türetilen model en küçük kareler yapısal eşitlik modellemesiyle analiz edilmiştir. İki grup için de algılanan faydanın mobil ödeme kullanma niyetine en fazla etkide bulunduğu görülmektedir. Ayrıca kullanım kolaylığının sağlanması ve güvenlik çekincelerini azaltabilecek iletişim faaliyetlerinin gerçekleştirilmesi kullanma niyetini iyileştirecektir. Kişisel yenilikçiliğe göre ayrılan iki grup içerisinde kullanma niyeti oluşumunun yapısal olarak birbirlerine oldukça benzer biçimde ortaya çıktığı görülmüştür. Diğer taraftan yüksek yenilikçiliğe sahip grubun düşük yenilikçiliğe sahip gruba göre mobil ödeme sistemi kullanma niyetinin ve niyete etki eden tüm algısal faktörlerin birbirlerinden anlamlı bir biçimde farklılaştığı görülmektedir.

Anahtar Kelimeler

• mobil ödeme, mobil cüzdan, mobil uygulamalar, yenilikçilik, mobil ticaret, PLS-SEM

Mobile Payment Use Intentions and the Impact of Personal Innovativeness as a Moderator

Öz

This study aims to understand the factors contributing to intention to use mobile payment systems and to test the moderating role of personal innovation between use intention and its antecedents. The research was carried out focusing on one of major mobile network operators’ mobile wallet applications in Turkey. Computer aided telephone interview (CATI) was used to collect data from the subscribers by stratified random sampling. A total of 667 questionnaires were collected from users of the mobile wallet application, which was filtered down to 640 after an initial screening. The data were grouped into two using personal innovativeness factor scores to arrive at a group with high personal innovativeness and another with low innovativeness. The data were then analyzed using partial least squares structural equation modeling. The findings indicate that the most important factor for both groups in affecting use intentions is perceived usefulness. In addition, establishing ease of use and improving the perceived security of the system helps in improving use intentions. The path models that appear as a result of the analysis were very similar to each other among the two sample groups. On the other hand, the use intentions and all the related antecedents were significantly different between the groups.

Anahtar Kelimeler

• mobile payment, mobile app, mobile wallet, mobile commerce, innovativeness, PLS-SEM

Kaynakça

1. AGARWAL, Ritu, and Jayesh PRASAD; (1998), “A Conceptual and Operational Definition of Personal Innovativeness in the Domain of Information Technology.” Information Systems Research 9 (2), pp. 204–15.
2. AJZEN, Icek; (1991), “The Theory of Planned Behavior.” Organizational Behavior and Human Decision Processes 50, pp.179–211.
3. AJZEN, Icek, and Martin FISHBEIN; (1980), Understanding Attitudes and Predicting Social Behaviour. Englewood Cliffs, NJ: Prentice Hall PTR.
4. APP ANNIE & MEF; (2014), “Emerging Markets and Growth in the Global App Economy.”
5. ARVIDSSON, Niklas; (2013), “Consumer Attitudes on Mobile Payment Services – Results from a Proof of Concept Test.” International Journal of Bank Marketing 32(2), pp.150–70.
6. BHATTACHERJEE, Anol; (2001), “An Empirical Analysis of the Antecedents of Electronic Commerce Service Continuance.” Decision Support Systems 32(2), pp.201–14.
7. BLAKE, Brian F., Kimberly a. NEUENDORF, and Colin M. VALDİSERRİ; (2003), “Innovativeness and Variety of Internet Shopping.” Internet Research 13(3), pp.156–69.
8. BURDGE, Brooke; (2014), “New Research Shows Mobile Dominates Desktops.” MovableInk. http://blog.movableink. com/new-research-shows-mobile-dominates-desktops-with65-of-total-email-opens-in-q4-2013/.

9. CARMINES, Edward G, and Richard A ZELLER; (1979), Reliability and Validity Assessment. Sage University Papers Series. Beverly Hills, California: Sage Publications.
10. CARRINGTON, Denée; (2014), “US Mobile Payments Will Reach $142B By 2019.” Forrester. http://blogs.forrester. com/denee_carrington/14-11-17- us_mobile_payments_will_ reach_142b_by_2019.
11. CHANG, Chiao-Chen, and Yang-Chieh CHIN; (2011), “Predicting the Usage Intention of Social Network Games: An IntrinsicExtrinsic Motivation Theory Perspective.” International Journal of Online Marketing 1 (3), pp.29–37.
12. CHANG, M.K., Waiman CHEUNG, and Vincent S. LAI;, (2005), “Literature Derived Reference Models for the Adoption of Online Shopping.” Information and Management 42 (4), pp.543– 59.
13. CHEN, Lei-da, and Ravi NATH; (2008), “Determinants of Mobile Payments: An Empirical Analysis.” Journal of International Technology and Information 17(1), pp.9–20.
14. VENKATESH, Viswanath, Michael G. MORRIS, Gordon B. DAVIS, and Fred D. DAVIS; (2003), “User Acceptance of Information Technology: Toward a Unified View.” MIS Quarterly 27 (3), pp.425–78.
15. VODAFONE; (2013), “Tokyo-Drift-How-Japan-Leads-theWay-on-M-Payments.” http://www.vodafone.com/business/ global-enterprise/tokyo-drift-how-japan-leads-the-way-on-mpayments-2013-08-13.
16. WANG, Yi-Shun, Yu-Min WANG, Hsin-Hui LİN, and Tzung-I TANG; (2003), “Determinants of User Acceptance of Internet Banking: An Empirical Study.” International Journal of Service Industry Management 14(5), pp.501–19.
17. WU, Jen H., and Shu Ching WANG; (2005), “What Drives Mobile Commerce? An Empirical Evaluation of the Revised Technology Acceptance Model.” Information and Management 42, pp.719–29.
18. YANG, Shuiqing, Yaobin LU, Sumeet GUPTA, Yuzhi CAO, and Rui ZHANG; (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). pp.129–42.
19. ZARMPOU, Theodora, Vaggelis SAPRIKIS, Angelos MARKOS, and Maro VLACHOPOULOU; (2012), “Modeling Users’ Acceptance of Mobile Services.” Electronic Commerce Research 12(2) pp.225-48.