Araştırma Makalesi
BibTex RIS Kaynak Göster

İnternet Bankacılığına İlişkin Tüketici Tutumlarını Etkileyen Faktörlerin Belirlenmesi: Bir Pilot Uygulama

Yıl 2016, Cilt: 16 Sayı: 3, 165 - 182, 19.10.2016
https://doi.org/10.18037/ausbd.390394

Öz



 Teknolojik gelişmeler işletmelere mevcut hizmetlerini self-servis araçlar vasıtasıyla sunma olanağı sağlamıştır. Self-servis bir araç olarak internet bankacılığı işlem maliyetlerinin azalmasına yardımcı olmaktadır. Bu çalışmada internet bankacılığı kullanıcılarının internet bankacılığına ilişkin tutumlarını etkileyen faktörleri ve internet bankacılığı kullanma niyetlerini etkileyen faktörleri belirlemek amaçlanmaktadır. Çalışma kapsamında teknoloji kabul modeli (TKM) temel alınarak bir internet bankacılığı kabul modeli geliştirilmiş ve test edilmiştir. Kolayda ve yargısal örnekleme ile seçilen 201 kişi ile araştırma gerçekleştirilmiştir. Sonuçlar göre internet bankacılığının algılanan faydası bu hizmete yönelik tutumu, tutum ise gelecekte hizmeti kullanma niyetini olumlu yönde etkilemektedir. Ayrıca etkileşim ihtiyacı arttıkça internet bankacılığına yönelik olumlu tutumun azaldığı görülmüştür. Elde edilen bulgular bankalara internet bankacılığı kullanımının yaygınlaştırılması konusunda yol gösterici olabilecektir. 

Kaynakça

  • Ajzen, I. & Fishbein, M. (1980). Understanding Attitudes and Predicting Social Behavior. Englewood Cliffs, NJ: Prentice-Hall.
  • Aladwani, A. M. (2001). Online banking: a field study of drivers, development challenges, and expectations, International Journal of Information Management, 21, 213-225
  • Alsajjan, B., Dennis, C. (2010). Internet banking acceptance model: cross-market examination, Journal of Business Research, 63, 957-963.
  • Anderson J.C., Gerbing, D. W. (1988). Structural equation modeling in practice: a review and recommended two-step approach, Psychological Bulletin, 103, 411–423.
  • Bagozzi, R. P., Davis, F. D., Warshaw, R. P. (1992). Development and test of a theory of technological learning and usage, Human Relations, 45, 7, 659-86.
  • Black, N. J., Lockett, A., Ennew, C., Winklhofer, H., McKechnie, S. (2002). Modeling consumer choice of distribution channels: an illustration from financial services, International Journal of Marketing, 20, 4, 161-173.
  • Bollen, K. A. (1989). Structural Equations with Latent Variables, John Wileyand Sons, Inc. USA.
  • Byrne, B. M. (1998). Structural Equation Modeling With Lisrel, Prelis And Simplis, Lawrance Erlbaum Associates, Inc. USA.
  • Cheng, E. T. C., Lam, D. Y. C., Yeung, A. C. L. (2006). Adoption of internet banking: an empirical study in Hong Kong, Decision Support Systems, 42, 1558-1572.
  • Chen, S., Chen, H., Chen, M. (2009). Determinants of satisfaction and continuance intention towards self-service Technologies, Industrial Management & Data Systems, 109 (9), 1248-1263.
  • Chou, C. P. & Bentler, P. M. (1995). Estimates and Tests in Structural Equation Modeling, Structural Equation Modeling, Concepts, Issues and Applications (Ed: Hoyle, R.H.). Sage Publications. USA.
  • Cox, M., Preston, C., Cox, K. (1999). What Factors Support or Prevent Teachers from Using ICT in their Classrooms?. British Educational Research Association Annual Conference, University of Sussex, Brighton, UK, September 2-5, 1999.
  • Curran, J. M., Meuter, M. L. (2005). Self-service technology adoption: comparing three Technologies, Journal of Services Marketing, 19 (2), 103-113
  • Dabholkar, P. A. (1994). Incorporating choice into an attitudinal framework: analyzing models of mental comparison processes. Journal of Consumer Research 21 (June), 100-118.
  • Dabholkar, P. A. (1996). Consumer evaluations of new technology-based self-service options: an investigation of alternative models of service quality, International Journal of Research in Marketing, 13 (1), 29-51.
  • Dabholkar, P. A., Bagozzi, R. P. (2002). An attitudinal model of technology-based self-service: moderating effects of consumer traits and situational factors, Journal of the Academy of Marketing Science, 30 (3), 184-201.
  • Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance in information technology, MIS Quarterly, 13 (3), 319-340.
  • Devlin, J. F., Yeung, M. (2003). Insights into customer motivations for switching to Internet banking, International Review of Retail, Distribution and Consumer Research, 14 (4), October, 375-392.
  • Durkin, M., Deirdre, J., Mulholland, G., Worthington, S. (2007). Key influencers and inhibitors on adoption of the internet for banking, Journal of Retailing and Consumer Services, doi:10.1016/j.jretconser. 2007.08.002
  • Fishbein, M. & Ajzen, I. (1975). Belief, Attitude, Intention, and Behavior: An Introduction to Theory and Research Reading, MA: Addison-Wesley.
  • Geldhof, G. J., Selig, J. P., Mcconnell, E. K. (2008). Special Issues In Lisrel: Important Issues In SEM Including Non-Normal Data, Bootstrapping, Multiple Imputation, the Rp Command and the Use of Custom Parameters. http://www.Quant.Ku.Edu, Guide No. Kuant 006.1, (29.02.2008).
  • Golob, T. F. (2001). Structural Equation Modeling For Travel Behavior Research. Institute of Transportation Studies, Center for Activity System Analysis, Paper, November 11. http://www.Repositories. Cdlib.Org/Itsirvine/Casa/Uci-Its-As-Wp-01-2 (11.07.2007).
  • Gülmez, M., Kitapçı, O. (2006). İnternet Bankacılığı ve Müşteri Davranışları: Cumhuriyet Üniversitesi Akademik ve İdari Personeline Yönelik Bir Uygulama, C.Ü. İktisadi ve İdari Bilimler Dergisi, 7 (2), 83-100.
  • Hair, J. F., Black, B., Babin, B., Anderson, R. E., Tatham, R. L. (2006). Multivariate Data Analysis, Prentice Hall., USA.
  • Hair, J. F., Anderson, R. E., Tatham, R. L., Black, W.C. (1998). Multivariate Data Analysis, International Fifth Edition, Prentice-Hall International, Inc., USA.
  • Hooper, D., Coughlan, J., Mullen, M. R. (2008) Structural Equation Modelling: Guidelines for Determining Model Fit The Electronic Journal of Business Research Methods, 6 (1), 53 – 60
  • Hu, L. & Bentler, P. (1995). Evaluating Model Fit. Structural Equation Modeling, Concepts, Issues and Applications (Ed: Hoyle, R.H.). Sage Publications. USA.
  • Jones, A. B., Hubona, G. S. (2006). The mediation of external variables in the technology acceptance model, Information & Management, 43, 706-717.
  • Lages, C., Lages, C. R., Lages, L. F. (2005). The RELQUAL scale: a measure of relationship quality in export market ventures, Journal of Business Research, 58 (8), 1040-1048.
  • Lee, K., Tsai, M., Lanting, M. C. L. (2011). From marketplace to marketspace: Investigating the consumer switch to online banking, Electronic Commerce Research and Applications, 10, 115-125.
  • Lee, H., Fiore, A. M., Kim, J. (2006). The role of the technology acceptance model in explaining effects of image interactivity technology on consumer responses, International Journal of Retail & Distribution Management, 34 (8), 621-644.
  • Liao, C., Tsou, C., Huang, M. (2007). Factors influencing the usage of 3G mobile services in Taiwan, Online Information Review, 31 (6), 759-774.
  • Liljander, V., Gillberg, F., Gummerus, J., van Riel, A. (2006). Technology readiness and the evaluation and adoption of self-service technologies, Journal of Retailing and Consumer Services, 13, 177-191.
  • Meuter, M. L., Ostrom, A. L., Roundtree, R. I., Bitner, M. J. (2000). Self-service technologies: understanding customer satisfaction with technology-based service encounters, Journal of Marketing, 64 (July), 50-64.
  • Meuter, M. L., Ostrom, A.L., Bitner, M.J., Roundtree, R. (2003). The influence of technology anxiety on consumer use and experiences with self-service technologies, Journal of Business Research, 56, 899- 906
  • Meuter, M. L., Bitner, M.J., Ostrom, A. L., Brown, S.W. (2005). Choosing among alternative service delivery modes: an investigation of customer trial of self-service technologies, Journal of Marketing, 69 (April), 61-83.
  • Muhammed, L., Rana, G. (2012). Factors Distressing Internet Banking Adoption among Adult Students: Evidence from Kingdom of Saudi Arabia, Business and Management Review, 2 (1), March, 76 – 82
  • Ndubisi, N. O. (2007). Customers’ perceptions and intention to adopt Internet banking: the moderation effect of computer self-efficacy, Al&Soc, 21, 315-327.
  • Parasuraman, A. (2000). Technology Rediness Index (TRI): A multiple-item scale to measure readiness to embrace new technologies, Journal of Service Research, 2, 4, 307-320.
  • Pavlou, P. A. (2003). Consumer acceptance of electronic commerce – integrating trust and risk with the technology acceptance model, International Journal of Electronic Commerce, 7 (3), 69-103.
  • Rotchanakitumnuai, S., Speece, M. (2009). Modeling electronic service acceptance of an e-securities trading system, Industrial Management & Data Systems, 109 (8), 1069-1084.
  • Sathye, M. (1999). Adoption of Internet banking by Australian consumers: an empirical investigation, International Journal of Bank Marketing, 17 (7), 324-334.
  • Sharma, S., Mukherjeeb, S., Kumar, A., Dillond, W. R. (2005). A simulation study to investigate the use of cutoff values for assessing model fit in covariance structure models, Journal of Business Research, 58, 935– 943
  • Sheth, J. N., Parvatiyar, A. (1995). Relationship Marketing in Consumer Markets: Antecedents and Consequences, Journal of the Academy of Marketing Science, Fall, 255-271.
  • Seneler, C. O., Basoglu, N., Daim, T. U. (2010). An empirical analysis of the antecedents of adoption of online services A prototype-based framework, Journal of Enterprise Information Management, 23 (4), 417-438.
  • Spears, N. (2001). Time pressure and information in sales promotion strategy: conceptual framework and content analysis, Journal of Advertising, XXX (1), 67-76.
  • Stoel, L., Lee, K. H. (2003). Modeling the effect of experience on student acceptance of web-based courseware, Internet Research: Networking Applications and Policy, 13 (5), 364-374.
  • Şıker, P. (2011). Müşterilerin İnternet Bankaciliğini Benimsemelerine Yönelik Keşifsel Bir Araştirma, Niğde Üniversitesi IUYD, 2 (2), 35-50
  • Tan, M., Thompson T. S. H. (2000). Factors influencing the adoption of internet banking, Journal of the Association for Information Systems, 1 (5), 1-42.
  • Taylor, S., Todd, P. A. (1995). Understanding information technology usage: a test of competing models, Information Systems Research, 6 (2), 144-176.
  • Türkiye Bankalar Birliği (2014). İnternet ve Mobil Bankacılık Hizmetleri Eylül, 2014. http://www.tbb.org.tr/tr/banka-vesektorbilgileri/istatistikiraporlar/Internet_ve_Mobil_ Bankacilik_Istatistikleri/1375
  • Wessels, L., Drennan, J. (2010). An investigation of consumer acceptance of M-banking, International Journal of Bank Marketing, 28 (7), 547-568.
  • West, S. G., Finch, J. F., Curan, P. J. (1995). Structural Equation Models With Nonnormal Variables: Problems and Remedies, Structural Equation Modeling, Concepts, Issues and Applications (Ed: Hoyle, R.H.). Sage Publications. USA.
  • Wixom, B. H., Todd, P. A. (2005). A theoretical integration of user satisfaction and technology acceptance, Information Systems Research, 16 (1), 85-102.
  • Usta, R. (2005). Tüketicilerin İnternet Bankacılığını Kullanmama Nedenleri Üzerine Bir Araştırma, Doğuş Üniversitesi Dergisi, 6 (2), 279-290
  • Ustasüleyman, T., Eyüboğlu, K. (2010). Bireylerin İnternet Bankacılığını Benimsemesini Etkileyen Faktörlerin Yapısal Eşitlik Modeli ile Belirlenmesi, BDDK Bankacılık ve Finansal Piyasalar, 4 (2), 11-38.
Toplam 56 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Bölüm Makaleler
Yazarlar

Doç. Dr. Hilal İnan Bu kişi benim

Yrd. Doç. Dr. Burak Nakıboğlu

Öğr. Grv. Dr. Hatice Doğan Südaş Bu kişi benim

Yayımlanma Tarihi 19 Ekim 2016
Gönderilme Tarihi 18 Haziran 2014
Yayımlandığı Sayı Yıl 2016 Cilt: 16 Sayı: 3

Kaynak Göster

APA İnan, D. D. H., Nakıboğlu, Y. D. D. B., & Doğan Südaş, Ö. G. D. H. (2016). İnternet Bankacılığına İlişkin Tüketici Tutumlarını Etkileyen Faktörlerin Belirlenmesi: Bir Pilot Uygulama. Anadolu Üniversitesi Sosyal Bilimler Dergisi, 16(3), 165-182. https://doi.org/10.18037/ausbd.390394