MOBİL ALIŞVERİŞ UYGULAMALARININ KULLANIMINI ETKİLEYEN FAKTÖRLER VE BU FAKTÖRLERİN MEMNUNİYET VE KULLANMA NİYETİ ÜZERİNDEKİ ETKİSİ

Abstract

Araştırmanın amacı, tüketicilerin mobil alışveriş uygulamaları kullanımında algıladıkları risk, kullanışlılık, kullanım kolaylığı ve keyfin, memnuniyet ve kullanma niyeti üzerindeki etkisini belirlemektir. Bu temel amaç yanında araştırmanın diğer amaçları şunlardır; araştırmaya konu olan bireylerin demografik özelliklerini tespit etmek, mobil alışveriş uygulamalarına karşı algılarını belirlemek, memnuniyet ve kullanma niyetlerini ölçmektir. Veri toplama metodu olarak anket yöntemi seçilmiştir. Anket çalışması kolayda örnekleme yöntemi kullanılarak yapılmıştır. Araştırmanın ana kütlesini Erzurum il sınırlarında yaşayan 18 yaş ve üzeri katılımcılar oluşturmaktadır. 412 kişiye uygulanan anketin hatalı ve eksik cevapları elendikten sonra 389 adet anket formu değerlendirmeye tabi tutulmuştur. Yapılan çoklu regresyon analizi sonucunda, algılanan kullanışlılık, algılanan kullanım kolaylığı ve algılanan keyfin kullanma niyeti ve memnuniyet üzerinde etkili olduğu görülmüştür. Ayrıca algılanan riskin memnuniyet üzerinde etkisi olmasına rağmen kullanma niyeti üzerinde etkisinin olmadığı sonucuna ulaşılmıştır. Araştırma için belirlenen 8 hipotezden 7’si kabul 1’i red edilmiştir. Katılımcıların mobil alışveriş uygulamalarını kullanırken algıladıkları riskin yüksek olduğu tespit edilmiştir. Riskin azaltılmasıyla birlikte, uygulamaların kullanımı artacaktır. Uygulamaların geliştirilmesinde tasarım, sadelik, kullanım kolaylığı, hız, kullanıcı dostu gibi kriterlere önem verilerek müşteri memnuniyetinin artırılabileceğine dair öneriler geliştirilmiştir.

Keywords

• Teknoloji Kabul Modeli,Algılanan Risk,Algılanan Keyif,Memnuniyet,Mobil

References

1. Acılar, A., & Turan, A. H. Üniversite Öğrencileri Ve Mobil Ticaret: Bilecik Şeyh Edebali Üniversitesi Örneği. PressAcademia Procedia, 2(1), 515-523.
2. Agrebi, S., & Jallais, J. (2015). Explain the intention to use smartphones for mobile shopping. Journal of Retailing and Consumer Services, 22, 16-23.
3. Aldás-Manzano, J., Ruiz-Mafé, C., & Sanz-Blas, S. (2009). Exploring individual personality factors as drivers of M-shopping acceptance. Industrial Management & Data Systems, 109(6), 739-757.
4. Altunışık, R., Özdemir, Ş., & Torlak, Ö. (2002). Modern pazarlama. Değişim Yayınları.
5. Anderson, E. W., & Sullivan, M. W. (1993). The antecedents and consequences of customer satisfaction for firms. Marketing science, 12(2), 125-143.
6. Arning, K., & Ziefle, M. (2007). Understanding age differences in PDA acceptance and performance. Computers in Human Behavior, 23(6), 2904-2927.
7. Babin, B. J., Lee, Y. K., Kim, E. J., & Griffin, M. (2005). Modeling consumer satisfaction and word-of-mouth: restaurant patronage in Korea. Journal of Services Marketing, 19(3), 133-139.
8. Bhattacherjee, A. (2001). An empirical analysis of the antecedents of electronic commerce service continuance. Decision support systems, 32(2), 201-214.

9. Bölen, M. C., Özen, Ü., & Karaman, E. Mobil Alışveriş Bağlamında Sürekli Kullanım Niyetinin İncelenmesi: İki Kuramsal Modelin Karşılaştırılması. Acta INFOLOGICA, 1(2), 74-83.
10. Bruner II, G. C., & Kumar, A. (2005). Explaining consumer acceptance of handheld Internet devices. Journal of business research, 58(5), 553-558.
11. Can, B. K., Yeşilyurt, H., Sancaktar, C. L., & Koçak, N. (2017). Mobil Çağda Mobil Uygulamalar: Türkiye’deki Yerli Otel Zincirleri Üzerine Bir Durum Tespiti. Journal of Yaşar University, 12(45), 48-59.
12. Chang, M. L., & Wu, W. Y. (2012). Revisiting perceived risk in the context of online shopping: An alternative perspective of decision‐making styles. Psychology & Marketing, 29(5), 378-400.
13. Childers, T. L., Carr, C. L., Peck, J., & Carson, S. (2002). Hedonic and utilitarian motivations for online retail shopping behavior. Journal of retailing, 77(4), 511-535.
14. Chong, A. Y. L. (2013). Mobile commerce usage activities: The roles of demographic and motivation variables. Technological Forecasting and Social Change, 80(7), 1350-1359.
15. Churchill Jr, G. A., & Surprenant, C. (1982). An investigation into the determinants of customer satisfaction. Journal of marketing research, 491-504.
16. Dai, H., & Palvi, P. C. (2009). Mobile commerce adoption in China and the United States: a cross-cultural study. ACM SIGMIS Database: the DATABASE for Advances in Information Systems, 40(4), 43-61.
17. Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS quarterly, 319-340.
18. Davis, F. D., & Venkatesh, V. (2004). Toward preprototype user acceptance testing of new information systems: implications for software project management. IEEE Transactions on Engineering management. 51 (1), 31-46.
19. Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989). User acceptance of computer technology: a comparison of two theoretical models. Management science, 35(8), 982-1003.
20. Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1992). Extrinsic and intrinsic motivation to use computers in the workplace. Journal of applied social psychology, 22(14), 1111-1132.
21. Dickinger, A., Arami, M., & Meyer, D. (2008). The role of perceived enjoyment and social norm in the adoption of technology with network externalities. European Journal of Information Systems, 17(1), 4-11.
22. Djamasbi, S., Strong, D. M., & Dishaw, M. (2010). Affect and acceptance: Examining the effects of positive mood on the technology acceptance model. Decision Support Systems, 48(2), 383-394.
23. Faqih, K. M., & Jaradat, M. I. R. M. (2015). Assessing the moderating effect of gender differences and individualism-collectivism at individual-level on the adoption of mobile commerce technology: TAM3 perspective. Journal of Retailing and Consumer Services, 22, 37-52.
24. Featherman, M. S., & Pavlou, P. A. (2003). Predicting e-services adoption: a perceived risk facets perspective. International journal of human-computer studies, 59(4), 451-474.
25. Fenech, T. (1998). Using perceived ease of use and perceived usefulness to predict acceptance of the World Wide Web. Computer Networks and ISDN Systems, 30(1-7), 629-630.
26. Fishbein, M., & Ajzen, I. (1975). Belief, Attitude, Intention, and Behavior: An Introduction to Theory and Researched. Reading: Addison-Wesley.
27. Forsythe, S. M., & Shi, B. (2003). Consumer patronage and risk perceptions in Internet shopping. journal of Business research, 56(11), 867-875.
28. Gefen, D., & Straub, D. W. (1997). Gender differences in the perception and use of e-mail: An extension to the technology acceptance model. MIS quarterly, 389-400.
29. Gefen, D., & Straub, D. W. (2003). Managing user trust in B2C e-services. E-service Journal, 2(2), 7-24.
30. Giovannini C. J., Ferreira J. B., Silva J. F., Ferreira D. B., (2015), “The effects of trust transference, mobile attributes and enjoyment on mobile trust” BAR, Rio de Janeiro, 12 (1/5), 88-108.
31. Groß, M. (2015). Exploring the acceptance of technology for mobile shopping: an empirical investigation among Smartphone users. The International Review of Retail, Distribution and Consumer Research, 25(3), 215-235.
32. Guriting, P., & Oly Ndubisi, N. (2006). Borneo online banking: evaluating customer perceptions and behavioural intention. Management research news, 29(1/2), 6-15.
33. Hamid, A. A., Razak, F. Z. A., Bakar, A. A., & Abdullah, W. S. W. (2016). The effects of perceived usefulness and perceived ease of use on continuance intention to use e-government. Procedia Economics and Finance, 35, 644-649.
34. http://www.tdk.gov.tr/index.php?option=com_bts&arama=kelime&guid=TDK.GTS.5ac3de326f6953.06120384 erişim: 10/12/2017
35. https://medium.com/@fikirmedya/t%C3%BCrkiyede-mobil-al%C4%B1%C5%9Fveri%C5%9F-profili-157aa23626ce erişim: 26/12/2017
36. Hu, P. J. H., Clark, T. H., & Ma, W. W. (2003). Examining technology acceptance by school teachers: a longitudinal study. Information & management, 41(2), 227-241.
37. Hubert, M., Blut, M., Brock, C., Backhaus, C., & Eberhardt, T. (2017). Acceptance of smartphone‐based mobile shopping: Mobile benefits, customer characteristics, perceived risks, and the impact of application context. Psychology & Marketing, 34(2), 175-194.
38. Hung, M. C., Hwang, H. G., & Hsieh, T. C. (2007). An exploratory study on the continuance of mobile commerce: an extended expectation-confirmation model of information system use. International Journal of Mobile Communications, 5(4), 409-422.
39. Hur, Y. (2007). Determinants of sport website acceptance: an application and extension of the technology acceptance model(Doctoral dissertation, Washington State University).
40. Kang, H., Lee, M. J., & Lee, J. K. (2012). Are you still with us? A study of the post-adoption determinants of sustained use of mobile-banking services. Journal of Organizational Computing and Electronic Commerce, 22(2), 132-159.
41. Karabulut, A. N. (2013). Tüketicilerin Algılanan Risk Değişkeni Karşısında İnternetten Alışveriş Yapma Eğilimlerinin Ölçülmesi: Beklenen Fayda Teorisine Karşı Beklenti Teorisi. Journal of Yaşar University, 8(32), 5515-5536.
42. Karadeniz, M., & Çuhadaroğlu, Ö. (2016). Lojistik Yönetiminde E-Ticaret Mobil Uygulamalarında Sunulan Hizmet Kalitesinin Müşteri Memnuniyetine Etkisi Ve Bir Araştırma. Atatürk Üniversitesi İktisadi ve İdari Bilimler Dergisi, 30(1).
43. Kargin, B., & Basoglu, N. (2006, June). Adoption factors of mobile services. In Mobile Business, 2006. ICMB'06. International Conference on (pp. 41-41). IEEE.
44. Kim, C., Mirusmonov, M., & Lee, I. (2010). An empirical examination of factors influencing the intention to use mobile payment. Computers in Human Behavior, 26(3), 310-322.
45. Kim, D. J., Ferrin, D. L., & Rao, H. R. (2008). A trust-based consumer decision-making model in electronic commerce: The role of trust, perceived risk, and their antecedents. Decision support systems, 44(2), 544-564.
46. Kim, D., & Steinfield, C. (2004). Consumers mobile internet service satisfaction and their continuance intentions. AMCIS 2004 Proceedings, 332.
47. Kim, H. W., Chan, H. C., & Gupta, S. (2007). Value-based adoption of mobile internet: an empirical investigation. Decision support systems, 43(1), 111-126.
48. Kim, L. H., Qu, H., & Kim, D. J. (2009). A study of perceived risk and risk reduction of purchasing air‐tickets online. Journal of Travel & Tourism Marketing, 26(3), 203-224.
49. Koçak Alan, A., Tümer Kabadayı, E., & Topaloğlu, A. K. (2018). Tüketicileri Mobil Alışverişe Yönlendiren Faktörlerin İncelenmesi. Dogus University Journal, 19(2).
50. Kurtuluş, K. (1998). Pazarlama Araştırmaları, İÜ İşletme Fakültesi Yayınları No 274, 6. Baskı İstanbul.
51. Lee, M. K., Cheung, C. M., & Chen, Z. (2005). Acceptance of Internet-based learning medium: the role of extrinsic and intrinsic motivation. Information & management, 42(8), 1095-1104.
52. Legris, P., Ingham, J., & Collerette, P. (2003). Why do people use information technology? A critical review of the technology acceptance model. Information & management, 40(3), 191-204.
53. Li, Z., & Bai, X. (2011). An Empirical Study of the Influencing Factors of User Adoption on Mobile Securities Services. JSW, 6(9), 1696-1704.
54. Liao, C., Palvia, P., & Chen, J. L. (2009). Information technology adoption behavior life cycle: Toward a Technology Continuance Theory (TCT). International Journal of Information Management, 29(4), 309-320.
55. Manzoor, A. (2010). E-commerce: an introduction. Amir Manzoor.
56. Mitchell, V. W. (1992). Understanding consumers’ behaviour: can perceived risk theory help?. Management Decision, 30(3).
57. Moore, G. C., & Benbasat, I. (1991). Development of an instrument to measure the perceptions of adopting an information technology innovation. Information systems research, 2(3), 192-222.
58. NART, S., & Okutan, S. (2015). Yeniliklere Uyum ve Mobil Ticaret: Tüketicilerin Mobil Alışverişe Yönlendirilmeleri Nasıl Sağlanabilir. Bartın Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 6(11), 163-180.
59. Natarajan, T., Balasubramanian, S. A., & Kasilingam, D. L. (2017). Understanding the intention to use mobile shopping applications and its influence on price sensitivity. Journal of Retailing and Consumer Services, 37, 8-22.
60. Novak, T. P., Hoffman, D. L., & Duhachek, A. (2003). The influence of goal-directed and experiential activities on online flow experiences. Journal of consumer psychology, 13(1-2), 3-16.
61. Nysveen, H., Pedersen, P. E., & Thorbjørnsen, H. (2005). Intentions to use mobile services: Antecedents and cross-service comparisons. Journal of the academy of marketing science, 33(3), 330.
62. O’Cass, A., & Fenech, T. (2003). Web retailing adoption: exploring the nature of internet users Web retailing behaviour. Journal of Retailing and Consumer services, 10(2), 81-94.
63. Oliver, R. L. (1981). Measurement and evaluation of satisfaction processes in retail settings. Journal of retailing.
64. Pai, F. Y., & Huang, K. I. (2011). Applying the technology acceptance model to the introduction of healthcare information systems. Technological Forecasting and Social Change, 78(4), 650-660.
65. Park, C., & Jun, J. K. (2003). A cross-cultural comparison of Internet buying behavior: Effects of Internet usage, perceived risks, and innovativeness. International Marketing Review, 20(5), 534-553.
66. Peter, J. P., & Ryan, M. J. (1976). An investigation of perceived risk at the brand level. Journal of marketing research, 184-188.
67. Ross, I. (1975). Perceived risk and consumer behavior: a critical review. ACR North American Advances.
68. Sheth, J. N., & Parvatiyar, A. (1995). The evolution of relationship marketing. International business review, 4(4), 397-418.
69. Shih, H. P. (2004). An empirical study on predicting user acceptance of e-shopping on the Web. Information & Management, 41(3), 351-368.
70. Solomon M, Bamossy G, Askegaard S, 2002. Consumer behavior. prentince hall. Upper Saddle River, 236-249.
71. Subramanian, G. H. (1994). A replication of perceived usefulness and perceived ease of use measurement. Decision sciences, 25(5‐6), 863-874.
72. Thakur, R., & Srivastava, M. (2013). Customer usage intention of mobile commerce in India: an empirical study. Journal of Indian Business Research, 5(1), 52-72.
73. Thakur, R., & 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.
74. Thong, J. Y., Hong, S. J., & Tam, K. Y. (2006). The effects of post-adoption beliefs on the expectation-confirmation model for information technology continuance. International Journal of Human-Computer Studies, 64(9), 799-810.
75. Tsu Wei, T., Marthandan, G., Yee-Loong Chong, A., Ooi, K. B., & Arumugam, S. (2009). What drives Malaysian m-commerce adoption? An empirical analysis. Industrial Management & Data Systems, 109(3), 370-388.
76. Uğur, N. G., & Turan, A. H. (2015). Üniversite Öğrencilerinin Mobil Uygulamaları Kabulü ve Kullanımı: Sakarya Üniversitesi Örneği. İnternet Uygulamaları ve Yönetimi Dergisi, (2), 63-79.
77. Uygun, M., Divanoğlu, S. U., & Özçifçi, V. (2012). Mobil pazarlama uygulamalarına yönelik tüketici kabulünü etkileyen faktörler. Organizasyon ve Yönetim Bilimleri Dergisi, 4(2).
78. Uylaş, Z., & Tıngöy, Ö. (2016). Türkiye'de Mobil Alışverişin Çevrimiçi Tüketici Davranışlarına Etkisi Üzerine Bir Araştırma. AJIT-e: Online Academic Journal of Information Technology, 7(25).
79. Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management science, 46(2), 186-204.
80. Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS quarterly, 425-478.
81. Wang, S., Wang, S., & Wang, M. T. (2006). Shopping online or not? Cognition and personality matters. Journal of Theoretical and Applied Electronic Commerce Research, 1(3).
82. Wang, Y. S., & Liao, Y. W. (2008). Understanding individual adoption of mobile booking service: An empirical investigation. Cyberpsychology & Behavior, 11(5), 603-605.
83. Wang, Y. S., Lin, H. H., & Luarn, P. (2006). Predicting consumer intention to use mobile service. Information systems journal, 16(2), 157-179.
84. Williams, A. (2002). Understanding the hospitality consumer. Routledge.
85. Wu, J. H., & Wang, S. C. (2005). What drives mobile commerce?: An empirical evaluation of the revised technology acceptance model. Information & management, 42(5), 719-729.
86. Yang, K. (2012). Consumer technology traits in determining mobile shopping adoption: An application of the extended theory of planned behavior. Journal of Retailing and Consumer Services, 19(5), 484-491.
87. Yang, K. C. (2005). Exploring factors affecting the adoption of mobile commerce in Singapore. Telematics and informatics, 22(3), 257-277.
88. Yilmaz, C. (2015). İnternet Üzerinden Alışveriş Niyetini Etkileyen Faktörlerin Genişletilmiş Teknoloji Kabul Modeli Kullanarak İncelenmesi Ve Bir Model Önerisi (An Investigation And A Model Suggestion For Factors Affecting Online Shopping Intention Using Extended Technology. Yönetim ve Ekonomi: Celal Bayar Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 22(2), 355-384.
89. Yuan, S., Liu, Y., Yao, R., & Liu, J. (2016). An investigation of users’ continuance intention towards mobile banking in China. Information Development, 32(1), 20-34.
90. Zhang, L., Zhu, J., & Liu, Q. (2012). A meta-analysis of mobile commerce adoption and the moderating effect of culture. Computers in human behavior, 28(5), 1902-1911.
91. Zhou, T. (2013). An empirical examination of continuance intention of mobile payment services. Decision Support Systems, 54(2), 1085-1091.