Araştırma Makalesi
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Mobil Ödeme Uygulamasının Risklerini Almaya Hazır mısınız? Erken Benimseyen ve Son Benimseyen Tüketicilerin Karşılaştırması

Yıl 2017, Cilt: 19 Sayı: 3, 952 - 974, 29.12.2017

Öz




Mobil
ödeme uygulamaları oldukça yeni, ancak hızla gelişen bir teknoloji olarak
akademisyenlerin ve uygulayıcıların yeni yeni dikkatini çekmektedir. Kitleler
tarafından kabul edilebilmesi için öncelikle mobil ödeme uygulama
teknolojisinin kullanımı ile ilgili risklerin anlaşılması gerekmektedir. Bu
çalışma, mobil ödeme uygulamalarıyla ilgili tüketicilerin algıladığı riskleri
anlamaya çalışırken, aynı zamanda yeniliklerin adaptasyonu eğrisindeki erken
benimseyenler ve son benimseyenler arasındaki farkları da araştırmaya yönelik
bir girişimdir. Bu amaçlara ulaşmak için, teknoloji kabul modeli (TAM) üzerinde
üç risk faktörünü, yani finansal risk, gizlilik riski ve güvenlik riski,
yansıtan bir araştırma modeli geliştirilmiştir. Oluşturulan model yapısal
eşitlik modellemesi kullanılarak, 133 erken benimseyen ve 105 geç benimseyen
tüketicilerden oluşan bir veri kümesiyle ampirik olarak test edilmiştir.
Sonuçlar, mobil ödeme uygulamalarını kullanmak konusunda erken benimseyen
tüketicilerin ve geç benimseyen tüketicilerin farklı risk algılamaları olduğunu
ortaya koymaktadır. Bu sonuca ek olarak, mobil ödeme uygulamalarını kullanımına
yönelik tutumları ve kullanma niyetleri, erken benimseyen tüketiciler ve geç
benimseyen tüketiciler için farklı faktörlerden etkilenmektedir.



Kaynakça

  • Akturan, U., and Tezcan, N. (2012). Mobile banking adoption of the youth market: Perceptions and intentions. Marketing Intelligence and Planning, 30(4), 444-459.
  • Anderson, J. C., and Gerbing, D. W. (1988). Structural equation modeling in practice: A review and recommended two-step approach. Psychological bulletin, 103(3), 411.
  • Alsajjan, B., and Dennis, C. (2010). Internet banking acceptance model: Cross-market examination. Journal of Business Research, 63(9), 957-963.
  • Bagozzi, R. P., and Yi, Y. (1988). On the evaluation of structural equation model. Journal of Academy of Marketing Science, 16(1), 74–94.
  • Bauer, R.A. (1960). Consumer behaviour as risk taking. In Cox, D.F. (Ed.). Risk taking and information handling in consumer behavior (pp.23-33). Harvard University Press, Cambridge, MA.
  • Bauer, H. H., Reichardt, T., Barnes, S. J., and Neumann, M. M. (2005). Driving consumer acceptance of mobile marketing: A theoretical framework and empirical study. Journal of Electronic Commerce Research, 6(3), 181.
  • Cases, A. S. (2002). Perceived risk and risk-reduction strategies in Internet shopping. The International Review of Retail, Distribution and Consumer Research, 12(4), 375-394.
  • Cheung, C. M. K., and Lee, M. K. O. (2006). Understanding consumer trust in Internet shopping: A multidisciplinary approach. Journal of the American Society for Information Science and Technology, 57(4), 479–492.
  • Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340.
  • Davis, F. D., Bagozzi, R. P., and Warshaw, P.R. (1989). User acceptance of computer technology: A comparison of two theoretical model., Management Science, 35(4), 982-1003.
  • Dewan, S. G., and Chen, L. D. (2005). Mobile payment adoption in the US: A cross-industry, crossplatform solution. Journal of Information Privacy and Security, 1(2), 4-28.
  • Dhaigude, A. S., Kapoor, R., and Ambekar, S. (2016). A conceptual model for adoption of information communication technology in the travel and tourism industry. Tourism Recreation Research, 41(1), 49-59.
  • Flynn, L. R., Goldsmith, R. E., and Eastman, J. K. (1996). Opinion leaders and opinion seekers: Two new measurement scales. Journal of the Academy of Marketing Science, 24(2), 137-147.
  • Gao, T. T., Rohm, A. J., Sultan, F., and Pagani, M. (2013). Consumers un-tethered: A three-market empirical study of consumers' mobile marketing acceptance. Journal of Business Research, 66(12), 2536-2544.
  • Gefen, D., Straub, D.W., and Boudreau, M.C. (2000). Structural equation modeling and regression: Guidelines for research practice. Communications of the Association for Information Systems, 4(7), 1–79.
  • Ghezzi, A., Renga, F., Balocco, R., and Pescetto, P. (2010). Mobile payment applications: Offer state of the art in the Italian market. Info, 12(5), 3–22.
  • Goldsmith, R. E., Flynn, L. R., and Goldsmith, E. B. (2003). Innovative consumers and market mavens. Journal of Marketing Theory and Practice, 11(4), 54-65.
  • Hair, Jr. J. F., Black, W. C., Babin, B. J., and Anderson, R.E. (2010). Multivariate data analysis: A global perspective (7th ed.). Upper Saddle River, NJ: Prentice Hall.
  • Hampshire, C. (2017). A mixed methods empirical exploration of UK consumer perceptions of trust, risk and usefulness of mobile payments. International Journal of Bank Marketing, 35(3), 354-369.
  • Hanafizadeh, P., Behboudi, M., Koshksaray, A. A., and Tabar, M. J. S. (2014). Mobile-banking adoption by Iranian bank clients. Telematics and Informatics, 31(1), 62-78.
  • Jacoby, J., and Kaplan, L. B. (1972). The components of perceived risk. In SV-Proceedings of the third annual conference of the association for consumer research.
  • Jack, W., and Suri, T. (2011, January). Mobile money: The economics of M-PESA (Working paper 16721). National Bureau of Economic Research. Retrieved May, 21, 2017, from http://www.nber.org/papers/w16721.pdf
  • Kim, C., Mirusmonov, M., and Lee, I. (2010). An empirical examination of factors influencing the intention to use mobile payment. Computers in Human Behavior, 26(3), 310-322.
  • Khalilzadeh, J., Ozturk, A. B., and Bilgihan, A. (2017). Security-related factors in extended UTAUT model for NFC based Mobile Payment in the Restaurant Industry. Computers in Human Behavior. 70, 460-474, http://doi.org/10.1016/j.chb.2017.01.001
  • Koenig-Lewis, N., Palmer, A., and Moll, A. (2010). Predicting young consumers' take up of mobile banking services. International Journal of Bank Marketing, 28(5), 410-432.
  • Kotler, P. (1994), Marketing Management – Analysis, Planning, Implementation and Control, 8th ed., Prentice-Hall, Englewood Cliffs, NJ.
  • Lassar, W. M., Manolis, C., and Lassar, S. S. (2005). The relationship between consumer innovativeness, personal characteristics, and online banking adoption. International Journal of Bank Marketing, 23(2), 176-199.
  • 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.
  • Legris, P., Ingham, J., and Collerette, P. (2003). Why do people use information technology? A critical review of the technology acceptance model. Information and Management, 40(3), 191–204.
  • Leong, L.Y., Hew, T.S., Tan, G.W.H., and Ooi, K.B. (2013). Predicting the determinants of the NFC-enabled mobile credit card acceptance: A neural networks approach. Expert Systems with Applications, 40(14), 5604-5620.
  • Mallat, N. (2007). Exploring consumer adoption of mobile payments – A qualitative study. Journal of Strategic Information Systems, 16(4), 413–432.
  • Moore, G.A. Crossing the Chasm: Marketing and Selling High-Tech Products to Mainstream Customers. New York, NY: Harper Business, 1999.
  • Nunnally, J. C., and Bernstein, I.H. (1994). Psychometric Theory. New York: McGraw-Hill.
  • Nyshadham, E. A. (2000). Consumer perceptions of online transaction security-A cognitive explanation of the origins of perception. AMCIS 2000 Proceedings, 111.
  • Ong, J. W., Poong, Y. S., and Ng, T.H. (2008). 3G services adoption among university students:Diffusion of innovation theory, Communications of the IBIMA, 3(16),114–121.
  • Pikkarainen, T., Pikkarainen, K., Karjaluoto, H. and Pahnila, S. (2004), “Consumer acceptance of online banking: an extension of the technology acceptance model”, Internet Research, 14(3), 224-235.
  • Risselada, H., Verhoef, P. C., and Bijmolt, T. H. (2014). Dynamic effects of social influence and direct marketing on the adoption of high-technology products. Journal of Marketing, 78(2), 52-68.
  • Rogers, E. M., and Cartano, D. G. (1962). Methods of measuring opinion leadership. Public Opinion Quarterly, 435-441.
  • Sheng, H., Nah, F. F. H., and Siau, K. (2008). An experimental study on ubiquitous commerce adoption: Impact of personalization and privacy concerns. Journal of the Association for Information Systems, 9(6), 344.
  • Shin, D.H. (2009). Towards an understanding of the consumer acceptance of mobile wallet. Computers in Human Behavior, 25(6), 1343-1354.
  • Shin, D. H. (2010). Modeling the interaction of users and mobile payment system: Conceptual framework. International Journal of Human-Computer Interaction, 26(10), 917-940.
  • Stone, R. N., and Grønhaug, K. (1993). Perceived risk: Further considerations for the marketing discipline. European Journal of Marketing, 27(3), 39-50.
  • Son, J. Y., and Kim, S. S. (2008). Internet users' information privacy-protective responses: a taxonomy and a nomological model. MIS Quarterly, 32(3), 503-529.
  • Tan, G. W. H., Ooi, K. B., Chong, S. C., and Hew, T. S. (2014). NFC mobile credit card: the next frontier of mobile payment?. Telematics and Informatics, 31(2), 292-307.
  • Thakur, R., and Srivastava, M. (2014). Adoption readiness, personal innovativeness, perceived risk and usage intention across customer groups for mobile payment services in India. Internet Research, 24(3), 369-392.
  • Tsai, J. Y., Kelley, P. G., Cranor, L. F., and Sadeh, N. (2010). Location-sharing technologies: Privacy risks and controls. ISJLP, 6, 119.
  • Van Eck, P. S.,Jager, W.,andLeeflang,P S.(2011). Opinion leaders' role in innovation diffusion: A simulation study. Journal of Product Innovation Management, 28(2),187-203.
  • Vessel, L., and Drennan, J. (2010). An investigation of consumer acceptance of m-banking. International Journal of Bank Marketing, 28(7), 547-568.
  • Wang, E. S. T., and Lin, R. L. (2017). Perceived quality factors of location-based apps on trust, perceived privacy risk, and continuous usage intention. Behaviour and Information Technology, 36(1), 2-10.
  • Wu, J. H.,and Wang,S.C. (2005).What drives mobile commerce? An empirical evaluation of the revised technology acceptance model. Information and Management, 42(5), 719–729.
  • Yang, S., Lu, Y., Gupta, S., Cao, Y., and 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.
  • Zhang, J., and Mao, E. (2008). Understanding the acceptance of mobile SMS advertising among young Chinese consumers. Psychology and Marketing, 25(8), 787–805.

Are You Ready To Take The Risks Of Mobile Payment App? Early Adopters Vs Laggards

Yıl 2017, Cilt: 19 Sayı: 3, 952 - 974, 29.12.2017

Öz











Mobile payment apps are rather a new, but a quickly
developing technology which newly takes attention of the academicians and
practitioners. In order for them to be accepted by the masses, first of all, risks that are related to the use of technology should be understood.
This study is an attempt to understand the related risks with the mobile
payment apps while differentiating between early adopters and laggards. To do this, a research model that reflects
the three risk factors, namely
financial,
privacy and security risk, are developed on the technology acceptance model
(TAM). The model is empirically tested by structural equation modeling with a
dataset of 133 early adopters and 105 laggards. The results imply that there
are different perceptions of risks of early adopters and laggards in m-payment
app use. Additionally, their attitude toward the app use and their intention to
use the mobile payment apps are dependent
on different factors for early adopters and laggards.

Kaynakça

  • Akturan, U., and Tezcan, N. (2012). Mobile banking adoption of the youth market: Perceptions and intentions. Marketing Intelligence and Planning, 30(4), 444-459.
  • Anderson, J. C., and Gerbing, D. W. (1988). Structural equation modeling in practice: A review and recommended two-step approach. Psychological bulletin, 103(3), 411.
  • Alsajjan, B., and Dennis, C. (2010). Internet banking acceptance model: Cross-market examination. Journal of Business Research, 63(9), 957-963.
  • Bagozzi, R. P., and Yi, Y. (1988). On the evaluation of structural equation model. Journal of Academy of Marketing Science, 16(1), 74–94.
  • Bauer, R.A. (1960). Consumer behaviour as risk taking. In Cox, D.F. (Ed.). Risk taking and information handling in consumer behavior (pp.23-33). Harvard University Press, Cambridge, MA.
  • Bauer, H. H., Reichardt, T., Barnes, S. J., and Neumann, M. M. (2005). Driving consumer acceptance of mobile marketing: A theoretical framework and empirical study. Journal of Electronic Commerce Research, 6(3), 181.
  • Cases, A. S. (2002). Perceived risk and risk-reduction strategies in Internet shopping. The International Review of Retail, Distribution and Consumer Research, 12(4), 375-394.
  • Cheung, C. M. K., and Lee, M. K. O. (2006). Understanding consumer trust in Internet shopping: A multidisciplinary approach. Journal of the American Society for Information Science and Technology, 57(4), 479–492.
  • Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340.
  • Davis, F. D., Bagozzi, R. P., and Warshaw, P.R. (1989). User acceptance of computer technology: A comparison of two theoretical model., Management Science, 35(4), 982-1003.
  • Dewan, S. G., and Chen, L. D. (2005). Mobile payment adoption in the US: A cross-industry, crossplatform solution. Journal of Information Privacy and Security, 1(2), 4-28.
  • Dhaigude, A. S., Kapoor, R., and Ambekar, S. (2016). A conceptual model for adoption of information communication technology in the travel and tourism industry. Tourism Recreation Research, 41(1), 49-59.
  • Flynn, L. R., Goldsmith, R. E., and Eastman, J. K. (1996). Opinion leaders and opinion seekers: Two new measurement scales. Journal of the Academy of Marketing Science, 24(2), 137-147.
  • Gao, T. T., Rohm, A. J., Sultan, F., and Pagani, M. (2013). Consumers un-tethered: A three-market empirical study of consumers' mobile marketing acceptance. Journal of Business Research, 66(12), 2536-2544.
  • Gefen, D., Straub, D.W., and Boudreau, M.C. (2000). Structural equation modeling and regression: Guidelines for research practice. Communications of the Association for Information Systems, 4(7), 1–79.
  • Ghezzi, A., Renga, F., Balocco, R., and Pescetto, P. (2010). Mobile payment applications: Offer state of the art in the Italian market. Info, 12(5), 3–22.
  • Goldsmith, R. E., Flynn, L. R., and Goldsmith, E. B. (2003). Innovative consumers and market mavens. Journal of Marketing Theory and Practice, 11(4), 54-65.
  • Hair, Jr. J. F., Black, W. C., Babin, B. J., and Anderson, R.E. (2010). Multivariate data analysis: A global perspective (7th ed.). Upper Saddle River, NJ: Prentice Hall.
  • Hampshire, C. (2017). A mixed methods empirical exploration of UK consumer perceptions of trust, risk and usefulness of mobile payments. International Journal of Bank Marketing, 35(3), 354-369.
  • Hanafizadeh, P., Behboudi, M., Koshksaray, A. A., and Tabar, M. J. S. (2014). Mobile-banking adoption by Iranian bank clients. Telematics and Informatics, 31(1), 62-78.
  • Jacoby, J., and Kaplan, L. B. (1972). The components of perceived risk. In SV-Proceedings of the third annual conference of the association for consumer research.
  • Jack, W., and Suri, T. (2011, January). Mobile money: The economics of M-PESA (Working paper 16721). National Bureau of Economic Research. Retrieved May, 21, 2017, from http://www.nber.org/papers/w16721.pdf
  • Kim, C., Mirusmonov, M., and Lee, I. (2010). An empirical examination of factors influencing the intention to use mobile payment. Computers in Human Behavior, 26(3), 310-322.
  • Khalilzadeh, J., Ozturk, A. B., and Bilgihan, A. (2017). Security-related factors in extended UTAUT model for NFC based Mobile Payment in the Restaurant Industry. Computers in Human Behavior. 70, 460-474, http://doi.org/10.1016/j.chb.2017.01.001
  • Koenig-Lewis, N., Palmer, A., and Moll, A. (2010). Predicting young consumers' take up of mobile banking services. International Journal of Bank Marketing, 28(5), 410-432.
  • Kotler, P. (1994), Marketing Management – Analysis, Planning, Implementation and Control, 8th ed., Prentice-Hall, Englewood Cliffs, NJ.
  • Lassar, W. M., Manolis, C., and Lassar, S. S. (2005). The relationship between consumer innovativeness, personal characteristics, and online banking adoption. International Journal of Bank Marketing, 23(2), 176-199.
  • 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.
  • Legris, P., Ingham, J., and Collerette, P. (2003). Why do people use information technology? A critical review of the technology acceptance model. Information and Management, 40(3), 191–204.
  • Leong, L.Y., Hew, T.S., Tan, G.W.H., and Ooi, K.B. (2013). Predicting the determinants of the NFC-enabled mobile credit card acceptance: A neural networks approach. Expert Systems with Applications, 40(14), 5604-5620.
  • Mallat, N. (2007). Exploring consumer adoption of mobile payments – A qualitative study. Journal of Strategic Information Systems, 16(4), 413–432.
  • Moore, G.A. Crossing the Chasm: Marketing and Selling High-Tech Products to Mainstream Customers. New York, NY: Harper Business, 1999.
  • Nunnally, J. C., and Bernstein, I.H. (1994). Psychometric Theory. New York: McGraw-Hill.
  • Nyshadham, E. A. (2000). Consumer perceptions of online transaction security-A cognitive explanation of the origins of perception. AMCIS 2000 Proceedings, 111.
  • Ong, J. W., Poong, Y. S., and Ng, T.H. (2008). 3G services adoption among university students:Diffusion of innovation theory, Communications of the IBIMA, 3(16),114–121.
  • Pikkarainen, T., Pikkarainen, K., Karjaluoto, H. and Pahnila, S. (2004), “Consumer acceptance of online banking: an extension of the technology acceptance model”, Internet Research, 14(3), 224-235.
  • Risselada, H., Verhoef, P. C., and Bijmolt, T. H. (2014). Dynamic effects of social influence and direct marketing on the adoption of high-technology products. Journal of Marketing, 78(2), 52-68.
  • Rogers, E. M., and Cartano, D. G. (1962). Methods of measuring opinion leadership. Public Opinion Quarterly, 435-441.
  • Sheng, H., Nah, F. F. H., and Siau, K. (2008). An experimental study on ubiquitous commerce adoption: Impact of personalization and privacy concerns. Journal of the Association for Information Systems, 9(6), 344.
  • Shin, D.H. (2009). Towards an understanding of the consumer acceptance of mobile wallet. Computers in Human Behavior, 25(6), 1343-1354.
  • Shin, D. H. (2010). Modeling the interaction of users and mobile payment system: Conceptual framework. International Journal of Human-Computer Interaction, 26(10), 917-940.
  • Stone, R. N., and Grønhaug, K. (1993). Perceived risk: Further considerations for the marketing discipline. European Journal of Marketing, 27(3), 39-50.
  • Son, J. Y., and Kim, S. S. (2008). Internet users' information privacy-protective responses: a taxonomy and a nomological model. MIS Quarterly, 32(3), 503-529.
  • Tan, G. W. H., Ooi, K. B., Chong, S. C., and Hew, T. S. (2014). NFC mobile credit card: the next frontier of mobile payment?. Telematics and Informatics, 31(2), 292-307.
  • Thakur, R., and Srivastava, M. (2014). Adoption readiness, personal innovativeness, perceived risk and usage intention across customer groups for mobile payment services in India. Internet Research, 24(3), 369-392.
  • Tsai, J. Y., Kelley, P. G., Cranor, L. F., and Sadeh, N. (2010). Location-sharing technologies: Privacy risks and controls. ISJLP, 6, 119.
  • Van Eck, P. S.,Jager, W.,andLeeflang,P S.(2011). Opinion leaders' role in innovation diffusion: A simulation study. Journal of Product Innovation Management, 28(2),187-203.
  • Vessel, L., and Drennan, J. (2010). An investigation of consumer acceptance of m-banking. International Journal of Bank Marketing, 28(7), 547-568.
  • Wang, E. S. T., and Lin, R. L. (2017). Perceived quality factors of location-based apps on trust, perceived privacy risk, and continuous usage intention. Behaviour and Information Technology, 36(1), 2-10.
  • Wu, J. H.,and Wang,S.C. (2005).What drives mobile commerce? An empirical evaluation of the revised technology acceptance model. Information and Management, 42(5), 719–729.
  • Yang, S., Lu, Y., Gupta, S., Cao, Y., and 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.
  • Zhang, J., and Mao, E. (2008). Understanding the acceptance of mobile SMS advertising among young Chinese consumers. Psychology and Marketing, 25(8), 787–805.
Toplam 52 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Bölüm Makaleler
Yazarlar

Ayşegül Sağkaya Güngör

Yayımlanma Tarihi 29 Aralık 2017
Yayımlandığı Sayı Yıl 2017 Cilt: 19 Sayı: 3

Kaynak Göster

APA Sağkaya Güngör, A. (2017). Are You Ready To Take The Risks Of Mobile Payment App? Early Adopters Vs Laggards. Gazi Üniversitesi İktisadi Ve İdari Bilimler Fakültesi Dergisi, 19(3), 952-974.
AMA Sağkaya Güngör A. Are You Ready To Take The Risks Of Mobile Payment App? Early Adopters Vs Laggards. Gazi Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi. Aralık 2017;19(3):952-974.
Chicago Sağkaya Güngör, Ayşegül. “Are You Ready To Take The Risks Of Mobile Payment App? Early Adopters Vs Laggards”. Gazi Üniversitesi İktisadi Ve İdari Bilimler Fakültesi Dergisi 19, sy. 3 (Aralık 2017): 952-74.
EndNote Sağkaya Güngör A (01 Aralık 2017) Are You Ready To Take The Risks Of Mobile Payment App? Early Adopters Vs Laggards. Gazi Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi 19 3 952–974.
IEEE A. Sağkaya Güngör, “Are You Ready To Take The Risks Of Mobile Payment App? Early Adopters Vs Laggards”, Gazi Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, c. 19, sy. 3, ss. 952–974, 2017.
ISNAD Sağkaya Güngör, Ayşegül. “Are You Ready To Take The Risks Of Mobile Payment App? Early Adopters Vs Laggards”. Gazi Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi 19/3 (Aralık 2017), 952-974.
JAMA Sağkaya Güngör A. Are You Ready To Take The Risks Of Mobile Payment App? Early Adopters Vs Laggards. Gazi Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi. 2017;19:952–974.
MLA Sağkaya Güngör, Ayşegül. “Are You Ready To Take The Risks Of Mobile Payment App? Early Adopters Vs Laggards”. Gazi Üniversitesi İktisadi Ve İdari Bilimler Fakültesi Dergisi, c. 19, sy. 3, 2017, ss. 952-74.
Vancouver Sağkaya Güngör A. Are You Ready To Take The Risks Of Mobile Payment App? Early Adopters Vs Laggards. Gazi Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi. 2017;19(3):952-74.