Araştırma Makalesi
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Müşterilerin Mobil Alışveriş Davranışının Utaut2 Modeli ile İncelenmesi

Yıl 2020, Cilt: 11 Sayı: 3, 870 - 887, 25.10.2020

Öz

Bu çalışmanın amacı mobil alışveriş yapan kullanıcıların kullanım niyeti ve davranışının incelenmesidir. Bireylerin mobil alışverişi benimsemelerini etkileyen faktörleri araştırmak için Genişletilmiş bütünleşik teknoloji kullanımı ve davranışı modeli (UTAUT2) modeli kullanılmıştır. Müşterilerin yeni alışveriş kanallarından biri olan mobil alışveriş yeteneklerine ilişkin algılarını anlamalarına dayanarak işletmelere mobil alışveriş hizmetlerini tasarlamadaki öncülleri sunulacaktır. Araştırma bir anket tasarımı içermekte ve 301 örnekten anket soru formu aracılığıyla veriler toplanmıştır. LISREL programı, veri analizi için kullanılmıştır. Müşterilerin mobil alışveriş hizmetlerini benimsemede en etkili faktörün performans beklentisi, en az etkili faktörün ise sosyal etki olduğu ve algılanan risk faktörünün anlamsız bir etkiye sahip olduğu sonucu ortaya çıkmıştır.

Kaynakça

  • Agrebi, S. ve Jallais, J. (2014). Explain the intention to use smartphones for mobile shopping. Journal of Retailing and Consumer Services, 22, 16–23.
  • Alalwana, A., A., Dwivedi, Y., K., & Rana, N., P.(2017). Factors influencing adoption of mobile banking by Jordanian bank customers: Extending UTAUT2 with trust. International Journal of Information Management, 37, 99–110.
  • Alan, A., K., Kabadayı, E., T. &Topaloğlu, A., K. (2018). Tüketicileri Mobil Alışverişe Yönlendiren Faktörlerin İncelenmesi. Doğuş Üniversitesi Dergisi, 19 (2), 75-94.
  • Alda´s-Manzano, J., Ruiz-Mafe´, C. & Sanz-Blas, S. (2009). Exploring individual personality factors as drivers of M-shopping acceptance. Industrial Management ve Data Systems, 109 /6, 739-757.
  • Alsamydai, M., J. (2014). Adaptation of the Technology Acceptance Model (TAM) to the Use of Mobile Banking Services. International Review of Management and Business Research, 3(4), 2031-2051.
  • Atılgan, K., Ö. ve Tanişman, H. (2019). Deneyimsel Ürünler ve Araştırma Ürünleri ile İlgili Çevrimiçi Tüketici Yorumları ve Referans Fiyat Bilgisinin Tüketicilerin Satın Alma Davranışları Üzerindeki Etkisi. İzmir İktisat Dergisi, 34 (4), 545-563.
  • Ateş, V. (2018). Online Alışveriş sitesi kullanıcı algılarının Müşteri Güven ve Sadakatine Etkilerinin İncelenmesi. Dokuz Eylül Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 20 (1), 109-132.
  • Baabdullah, A. M., Alalwanb, A., A., Ranac, N., P., Kizginc, H., & Patilc, P. (2019). Consumer use of mobile banking (M-Banking) in Saudi Arabia: Towards an integrated model. International Journal of Information Management, 44, 38–52.
  • Baptista, G. ve Oliveira, T. (2015). Understanding mobile banking: The unified theory of acceptanceand use of technology combined with cultural moderators. Computers in Human Behaviour, 50, 418-430.
  • Bentler, P., M. ve Yuan, K., H. (1999). Structural Equation Modeling with Small Samples: Test Statistics. Multivariate Behavioral Research, 34(2), 181-197.
  • Bölen, M., C., Özen, Ü., & Karaman, E. (2017). Mobil Alışveriş Bağlamında Sürekli Kullanım Niyetinin İncelenmesi: İki Kuramsal Modelin Karşılaştırılması. ACTA INFOLOGICA, 1 (2), 74-83.
  • Chen, Y., F., ve Lan, Y., C. (2014). An Empirical Study of the Factors Affecting Mobile Shopping in Taiwan. International Journal of Technology and Human Interaction, 10(1), 19-30.
  • Chen, Y., M., Hsu, T., H., & Lu, Y., J. (2018). Impact of flow on mobile shopping intention. Journal of Retailing and Consumer Services, 41, 281–287.
  • Chopdar, P., Korfiatis, N., Sivakumar, V. J. & Lytras, M. D. (2018). Mobile shopping apps adoption ve perceived risks: A cross-country perspective utilizing the Unified Theory of Acceptance ve Use of Technology. Computers in Human Behavior, 1-62.
  • Floyd, F., J. Ve Widaman, K. F. (1995). Factor analysis in the development and refinement of clinical assessment instruments. Psychological Assessment, 7(3), 286-299.
  • Fornell, C., ve Larcker, D. (1981). Evaluating Structural Equation Models with Unobservable Variables and Measurement Error. Journal of Marketing Research, 18(1), 39-50.
  • Gefen, D., Straub, D. & Boudreau, M. (2000). Structural Equation Modeling and Regression: Guidelines for Research Practice. Communications of the Association for Information Systems, 4 (7), 2-77.
  • 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.
  • Gupta, A., ve Arora, N. (2017). Understanding determinants and barriers of mobile shopping adoption using behavioral reasoning theory. Journal of Retailing and Consumer Services, 36, 1–7.
  • Hair, J., F., Sarstedt, M., Hopkins, L., & Kuppelwieser, V., G. (2014). Partial least squares structural equation modeling (PLS-SEM) An emerging tool in business research. European Business Review, 26 (2), 106-121.
  • Hew, J., J., Lee, V., H., Ooi, K., B., & Wei, J. (2015). What catalyses mobile apps usage intention: an empirical analysis. Industrial Management & Data Systems, 115(7), 1269-1291.
  • Holmes, A., Byrne, A., & Rowley, J. (2014). Mobile shopping behaviour: insights into attitudes, shopping process involvement and location. International Journal of Retail & Distribution Management, 42 (1), 25-3.
  • 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.
  • Hubert, M., Blut, M., Brock, C., Backhaus, C. & Eberhardt, T. (2017). Acceptance of Smartphone-Based Mobile Shopping: Mobile Benefits, Customer Characteristics, Perceived Risks, ve the Impact of Application Context. Psychology ve Marketing, 34/2, 175–194.
  • Kim, S., C., Yoon, D., & Han, E., K. (2016). Antecedents of mobile app usage among smartphone users. Journal of Marketing Communications, 22(6), 653-670.
  • Kline, P. (1994). An Easy Guide To Factor Analysis. New York: Routledge.
  • Ko, E., Kim, E., Y., & Lee, E., K. (2009). Modeling Consumer Adoption of Mobile Shopping for Fashion Products in Korea. Psychology & Marketing, 26(7), 669–687.
  • Lee, Y., K., Park, J., H., Chung, N., & Blakeney, A. (2012). A unified perspective on the factors influencing usage intention toward mobile financial services. Journal of Business Research, 65,1590–1599.
  • Lu, H., P., & Su, P., Y. (2009). Factors affecting purchase intention on mobile shopping web sites. Internet Research, 19 (4), 442-458.
  • 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.
  • Ney, B. (2013). Unraveling the adoption of mCRM smartphone applications among Dutch retailers .
  • Oliveira, T., Fariaa, M., Thomas, M., & Popovic, A. (2014). Extending the understanding of mobile banking adoption: When UTAUT meets TTF and ITM. International Journal of Information Management, 34, 689–703.
  • Osborne, J.W., & Costello, A.B.:(2009). Best practices in exploratory factor analysis: Four recommendations for getting the most from your analysis”. Pan-Pacific Management Review, 12 (2), 131-146.
  • Özgüner, M. ve Özgüner, Z. (2019). Tedarik Zinciri Riskleri’nin Lojistik Performans Üzerindeki Etkisinin Yapısal Eşitlik Modellemesi ile Belirlenmesi. Eskişehir Osmangazi Üniversitesi İİBF Dergisi, 14 (1), 67 – 82.
  • Rennie, K.M. (1997). Exploratory And Confirmatory Rotation Strategies in Exploratory Factor Analysis. Paper Presented At The Annual Meeting Of The Southwest Educational Research Association (Austin, January).
  • Palau-Saumell, R., Forgas-Coll, S., Sánchez-García, J., & Robres, E. (2019). User Acceptance of Mobile Apps for Restaurants: An Expanded and Extended UTAUT-2. Sustainability, 11, 1210-1234.
  • San-Martína, S., Jiménez, N., H., & López-Catalán, B. (2016).The firms benefits of mobile CRM from the relationship marketing approach and the TOE model. Spanısh Journal of Marketıng, 20, 18-29.
  • Soni, M., Jain, K., & Kumar, B. (2019). Factors affecting the adoption of fashion mobile shopping applications. Journal of Global Fashion Marketing, 10(4), 358-376.
  • Stapleton, C.D. (1997). Basic Concepts And Procedures Of Confirmatory Factor Analysis. Paper Presented At The Annual Meeting Of The Southwest Educational Research Association (Austin, January).
  • Tabachnick, B.G. ve Fidel, L.S. (2007). Using multivariate statistics. MA: Allyn& Bacon, Inc.
  • Thakur, R. ve Srivastaka, 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.
  • Trojanowski, M. ve Kułak, J. (2017). The Impact of Moderators and Trust on Consumer’s Intention to Use a Mobile Phone for Purchases. Journal of Management and Business Administration. Central Europe”, 25 (2), 91–116.
  • Uylaş, Z. ve Tıngöy, Ö. (2016). Türkiye’de Mobil Alışverişin Çevrimiçi Tüketici Davranışlarına Etkisi Üzerine Bir Araştırma. Online Academic Journal of Information Technology, 7 (25), 23-36.
  • Venkatesh, V., Morris, M.G., Davis, G.B. & Davis, F.D. (2003). User acceptance of information technology: toward a unified view. MIS Quarterly, 27/3, 425-78.
  • Venkatesh, V., Thong, J. Y. & Xu, T. (2012). Consumer acceptance ve use of information technology: Extending the Unified Theory of Acceptance ve Use of Technology. MIS Quarterly, 36(1) 157–178.
  • Verma, D. ve Verma, D., S. (2013). Managing Customer Relationships through Mobile CRM In Organized retail outlets. International Journal of Engineering Trends and Technology (IJETT), 4 (5), 1697-1701.
  • Yang, S. ve Kim, H., Y. (2012). Mobile shopping motivation: an application of multiple discriminant analysis. International Journal of Retail & Distribution Management, 40 (10), 778-789.
  • Yang, K. (2010). Determinants of US consumer mobile shopping services adoption: implications for designing mobile shopping services. Journal of Consumer Marketing, 27(3), 262–270.
  • Yang, S. (2013). Understanding Undergraduate Students’ Adoption of Mobile Learning Model: A Perspective of the Extended UTAUT2. Journal of Convergence Information Technology(JCIT), 8(10), 969-979.
  • Yang, K. ve Forney, J., C. (2013). The Moderatıng Role Of Consumer Technology Anxıety in Mobıle Shoppıng Adoptıon: Dıfferentıal Effects of Facılıtatıng Condıtıons and Socıal Influences. Journal of Electronic Commerce Research, 14(4), 334-347.
  • Yu, C., S. (2012). Factors Affectıng Indıvıduals To Adopt Mobıle Bankıng: Empırıcal Evıdence From The Utaut Model. Journal of Electronic Commerce Research, 13 (2),104-120.
  • Weston, R. ve Gore, P., A. (2006). A Brief Guide to Structural Equation Modeling. The Counselıng Psychologıst, 34 (5), 719-751.
  • Wong, C., H., Lee, H., S., Lim, Y., H.,Chua, B., H., Chai, B., H., & Tan, G., W., H. (2012). Predicting the Consumers' Intention to Adopt Mobile Shopping: An Emerging Market Perspective. International Journal of Network and Mobile Technologies , 3 (3), 24-39.

Investigation of Customers Mobile Shopping Behavior with Utaut2 Model

Yıl 2020, Cilt: 11 Sayı: 3, 870 - 887, 25.10.2020

Öz

The purpose of this study is to examine the intent and behavior of the users who use mobile shopping. The Extended Integrated Technology Usage and Behavior Model (UTAUT2) model was used to investigate the factors that affect individuals' adoption of mobile shopping. Based on customers' understanding of their perceptions of mobile shopping capabilities, one of their new shopping channels, businesses will be presented with their premises in designing mobile shopping services. The research includes a questionnaire design and data were collected from a questionnaire form from 301 samples. LISREL program was used for data analysis. The performance expectation of the most effective factor in adopting customers' mobile shopping services is the result that the least effective factor is social impact and the perceived risk factor has a meaningless effect.

Kaynakça

  • Agrebi, S. ve Jallais, J. (2014). Explain the intention to use smartphones for mobile shopping. Journal of Retailing and Consumer Services, 22, 16–23.
  • Alalwana, A., A., Dwivedi, Y., K., & Rana, N., P.(2017). Factors influencing adoption of mobile banking by Jordanian bank customers: Extending UTAUT2 with trust. International Journal of Information Management, 37, 99–110.
  • Alan, A., K., Kabadayı, E., T. &Topaloğlu, A., K. (2018). Tüketicileri Mobil Alışverişe Yönlendiren Faktörlerin İncelenmesi. Doğuş Üniversitesi Dergisi, 19 (2), 75-94.
  • Alda´s-Manzano, J., Ruiz-Mafe´, C. & Sanz-Blas, S. (2009). Exploring individual personality factors as drivers of M-shopping acceptance. Industrial Management ve Data Systems, 109 /6, 739-757.
  • Alsamydai, M., J. (2014). Adaptation of the Technology Acceptance Model (TAM) to the Use of Mobile Banking Services. International Review of Management and Business Research, 3(4), 2031-2051.
  • Atılgan, K., Ö. ve Tanişman, H. (2019). Deneyimsel Ürünler ve Araştırma Ürünleri ile İlgili Çevrimiçi Tüketici Yorumları ve Referans Fiyat Bilgisinin Tüketicilerin Satın Alma Davranışları Üzerindeki Etkisi. İzmir İktisat Dergisi, 34 (4), 545-563.
  • Ateş, V. (2018). Online Alışveriş sitesi kullanıcı algılarının Müşteri Güven ve Sadakatine Etkilerinin İncelenmesi. Dokuz Eylül Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 20 (1), 109-132.
  • Baabdullah, A. M., Alalwanb, A., A., Ranac, N., P., Kizginc, H., & Patilc, P. (2019). Consumer use of mobile banking (M-Banking) in Saudi Arabia: Towards an integrated model. International Journal of Information Management, 44, 38–52.
  • Baptista, G. ve Oliveira, T. (2015). Understanding mobile banking: The unified theory of acceptanceand use of technology combined with cultural moderators. Computers in Human Behaviour, 50, 418-430.
  • Bentler, P., M. ve Yuan, K., H. (1999). Structural Equation Modeling with Small Samples: Test Statistics. Multivariate Behavioral Research, 34(2), 181-197.
  • Bölen, M., C., Özen, Ü., & Karaman, E. (2017). Mobil Alışveriş Bağlamında Sürekli Kullanım Niyetinin İncelenmesi: İki Kuramsal Modelin Karşılaştırılması. ACTA INFOLOGICA, 1 (2), 74-83.
  • Chen, Y., F., ve Lan, Y., C. (2014). An Empirical Study of the Factors Affecting Mobile Shopping in Taiwan. International Journal of Technology and Human Interaction, 10(1), 19-30.
  • Chen, Y., M., Hsu, T., H., & Lu, Y., J. (2018). Impact of flow on mobile shopping intention. Journal of Retailing and Consumer Services, 41, 281–287.
  • Chopdar, P., Korfiatis, N., Sivakumar, V. J. & Lytras, M. D. (2018). Mobile shopping apps adoption ve perceived risks: A cross-country perspective utilizing the Unified Theory of Acceptance ve Use of Technology. Computers in Human Behavior, 1-62.
  • Floyd, F., J. Ve Widaman, K. F. (1995). Factor analysis in the development and refinement of clinical assessment instruments. Psychological Assessment, 7(3), 286-299.
  • Fornell, C., ve Larcker, D. (1981). Evaluating Structural Equation Models with Unobservable Variables and Measurement Error. Journal of Marketing Research, 18(1), 39-50.
  • Gefen, D., Straub, D. & Boudreau, M. (2000). Structural Equation Modeling and Regression: Guidelines for Research Practice. Communications of the Association for Information Systems, 4 (7), 2-77.
  • 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.
  • Gupta, A., ve Arora, N. (2017). Understanding determinants and barriers of mobile shopping adoption using behavioral reasoning theory. Journal of Retailing and Consumer Services, 36, 1–7.
  • Hair, J., F., Sarstedt, M., Hopkins, L., & Kuppelwieser, V., G. (2014). Partial least squares structural equation modeling (PLS-SEM) An emerging tool in business research. European Business Review, 26 (2), 106-121.
  • Hew, J., J., Lee, V., H., Ooi, K., B., & Wei, J. (2015). What catalyses mobile apps usage intention: an empirical analysis. Industrial Management & Data Systems, 115(7), 1269-1291.
  • Holmes, A., Byrne, A., & Rowley, J. (2014). Mobile shopping behaviour: insights into attitudes, shopping process involvement and location. International Journal of Retail & Distribution Management, 42 (1), 25-3.
  • 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.
  • Hubert, M., Blut, M., Brock, C., Backhaus, C. & Eberhardt, T. (2017). Acceptance of Smartphone-Based Mobile Shopping: Mobile Benefits, Customer Characteristics, Perceived Risks, ve the Impact of Application Context. Psychology ve Marketing, 34/2, 175–194.
  • Kim, S., C., Yoon, D., & Han, E., K. (2016). Antecedents of mobile app usage among smartphone users. Journal of Marketing Communications, 22(6), 653-670.
  • Kline, P. (1994). An Easy Guide To Factor Analysis. New York: Routledge.
  • Ko, E., Kim, E., Y., & Lee, E., K. (2009). Modeling Consumer Adoption of Mobile Shopping for Fashion Products in Korea. Psychology & Marketing, 26(7), 669–687.
  • Lee, Y., K., Park, J., H., Chung, N., & Blakeney, A. (2012). A unified perspective on the factors influencing usage intention toward mobile financial services. Journal of Business Research, 65,1590–1599.
  • Lu, H., P., & Su, P., Y. (2009). Factors affecting purchase intention on mobile shopping web sites. Internet Research, 19 (4), 442-458.
  • 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.
  • Ney, B. (2013). Unraveling the adoption of mCRM smartphone applications among Dutch retailers .
  • Oliveira, T., Fariaa, M., Thomas, M., & Popovic, A. (2014). Extending the understanding of mobile banking adoption: When UTAUT meets TTF and ITM. International Journal of Information Management, 34, 689–703.
  • Osborne, J.W., & Costello, A.B.:(2009). Best practices in exploratory factor analysis: Four recommendations for getting the most from your analysis”. Pan-Pacific Management Review, 12 (2), 131-146.
  • Özgüner, M. ve Özgüner, Z. (2019). Tedarik Zinciri Riskleri’nin Lojistik Performans Üzerindeki Etkisinin Yapısal Eşitlik Modellemesi ile Belirlenmesi. Eskişehir Osmangazi Üniversitesi İİBF Dergisi, 14 (1), 67 – 82.
  • Rennie, K.M. (1997). Exploratory And Confirmatory Rotation Strategies in Exploratory Factor Analysis. Paper Presented At The Annual Meeting Of The Southwest Educational Research Association (Austin, January).
  • Palau-Saumell, R., Forgas-Coll, S., Sánchez-García, J., & Robres, E. (2019). User Acceptance of Mobile Apps for Restaurants: An Expanded and Extended UTAUT-2. Sustainability, 11, 1210-1234.
  • San-Martína, S., Jiménez, N., H., & López-Catalán, B. (2016).The firms benefits of mobile CRM from the relationship marketing approach and the TOE model. Spanısh Journal of Marketıng, 20, 18-29.
  • Soni, M., Jain, K., & Kumar, B. (2019). Factors affecting the adoption of fashion mobile shopping applications. Journal of Global Fashion Marketing, 10(4), 358-376.
  • Stapleton, C.D. (1997). Basic Concepts And Procedures Of Confirmatory Factor Analysis. Paper Presented At The Annual Meeting Of The Southwest Educational Research Association (Austin, January).
  • Tabachnick, B.G. ve Fidel, L.S. (2007). Using multivariate statistics. MA: Allyn& Bacon, Inc.
  • Thakur, R. ve Srivastaka, 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.
  • Trojanowski, M. ve Kułak, J. (2017). The Impact of Moderators and Trust on Consumer’s Intention to Use a Mobile Phone for Purchases. Journal of Management and Business Administration. Central Europe”, 25 (2), 91–116.
  • Uylaş, Z. ve Tıngöy, Ö. (2016). Türkiye’de Mobil Alışverişin Çevrimiçi Tüketici Davranışlarına Etkisi Üzerine Bir Araştırma. Online Academic Journal of Information Technology, 7 (25), 23-36.
  • Venkatesh, V., Morris, M.G., Davis, G.B. & Davis, F.D. (2003). User acceptance of information technology: toward a unified view. MIS Quarterly, 27/3, 425-78.
  • Venkatesh, V., Thong, J. Y. & Xu, T. (2012). Consumer acceptance ve use of information technology: Extending the Unified Theory of Acceptance ve Use of Technology. MIS Quarterly, 36(1) 157–178.
  • Verma, D. ve Verma, D., S. (2013). Managing Customer Relationships through Mobile CRM In Organized retail outlets. International Journal of Engineering Trends and Technology (IJETT), 4 (5), 1697-1701.
  • Yang, S. ve Kim, H., Y. (2012). Mobile shopping motivation: an application of multiple discriminant analysis. International Journal of Retail & Distribution Management, 40 (10), 778-789.
  • Yang, K. (2010). Determinants of US consumer mobile shopping services adoption: implications for designing mobile shopping services. Journal of Consumer Marketing, 27(3), 262–270.
  • Yang, S. (2013). Understanding Undergraduate Students’ Adoption of Mobile Learning Model: A Perspective of the Extended UTAUT2. Journal of Convergence Information Technology(JCIT), 8(10), 969-979.
  • Yang, K. ve Forney, J., C. (2013). The Moderatıng Role Of Consumer Technology Anxıety in Mobıle Shoppıng Adoptıon: Dıfferentıal Effects of Facılıtatıng Condıtıons and Socıal Influences. Journal of Electronic Commerce Research, 14(4), 334-347.
  • Yu, C., S. (2012). Factors Affectıng Indıvıduals To Adopt Mobıle Bankıng: Empırıcal Evıdence From The Utaut Model. Journal of Electronic Commerce Research, 13 (2),104-120.
  • Weston, R. ve Gore, P., A. (2006). A Brief Guide to Structural Equation Modeling. The Counselıng Psychologıst, 34 (5), 719-751.
  • Wong, C., H., Lee, H., S., Lim, Y., H.,Chua, B., H., Chai, B., H., & Tan, G., W., H. (2012). Predicting the Consumers' Intention to Adopt Mobile Shopping: An Emerging Market Perspective. International Journal of Network and Mobile Technologies , 3 (3), 24-39.
Toplam 53 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Bölüm Makaleler
Yazarlar

Esma Durukal 0000-0001-8684-6311

Yayımlanma Tarihi 25 Ekim 2020
Gönderilme Tarihi 21 Mart 2020
Yayımlandığı Sayı Yıl 2020 Cilt: 11 Sayı: 3

Kaynak Göster

APA Durukal, E. (2020). Müşterilerin Mobil Alışveriş Davranışının Utaut2 Modeli ile İncelenmesi. Gümüşhane Üniversitesi Sosyal Bilimler Dergisi, 11(3), 870-887. https://doi.org/10.36362/gumus.707182