Araştırma Makalesi
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TÜRK KULLANICILARIN ONLİNE ALIŞVERİŞLERİNE DEVAM ETME NİYETLERİNİN İNCELENMESİ: AMPİRİK BİR DEĞERLENDİRME

Yıl 2022, Sayı: 50, 144 - 160, 20.04.2022
https://doi.org/10.30794/pausbed.1003073

Öz

Online alışveriş, son birkaç on yıldır hem kurumsal hem de bireysel hayatımızda en önemli faaliyetlerden biri haline gelmiştir. Web sitelerini benimsemenin, daha da önemlisi sürekli kullanmanın sosyo-psikolojik, teknik ve bireysel öncüllerinin daha iyi anlaşılması, online alışveriş faaliyetlerinin finansal, organizasyonel, ekonomik ve teknik başarısı için kritik öneme sahiptir Bu çalışmada, bilişim sistemleri (BS) başarı modeli, BS devam modeli ve teknoloji kabul teorileri entegre edilerek Türk kullanıcıların online alışverişe ilişkin memnuniyetleri ve online alışverişi kullanmaya devam etme niyetlerini etkileyen faktörler araştırılmıştır. Online alışveriş kullanım devamlılığı, Türkiye'de gerçekleştirilen e-ticaret çalışmalarında geniş çapta araştırılmamıştır. Bu çalışma, yukarıda bahsedilen BS araştırma modellerini entegre bir şekilde ampirik olarak test ederek BS araştırma alanına katkıda bulunmaktadır. Çalışmanın ampirik modeli kısmi en küçük kareler yapısal eşitlik modellemesi tekniği kullanılarak test edilmiştir. Veriler, 313 online alışveriş kullanıcısından kolayda örnekleme tekniği kullanarak toplanmıştır. Araştırma sonuçları, algılanan kullanışlılık ve bilgi kalitesi değişkenlerinin kullanıcıların online alışveriş sitelerini kullanmaya devam etmeleri üzeri anlamlı ve güçlü etkileri olduğunu ortaya çıkarmıştır.

Destekleyen Kurum

Yok

Proje Numarası

Yok

Teşekkür

Yok

Kaynakça

  • Ab Hamid, M. R., Sami, W., & Mohmad Sidek, M. H. (2017). Discriminant Validity Assessment: Use of Fornell & Larcker criterion versus HTMT Criterion. Journal of Physics: Conference Series, 890(1), 0–5.
  • Adaji, I., & Vassileva, J. (2016). Perceived Effectiveness, Credibility and Continuance Intention in E-commerce: A Study of Amazon. 2016 Persuasive Technology conference (pp. 293–305).
  • Ajzen, I. (1988). Attitudes, Personality, and Behavior. Chicago, IL: Dorsey Press.
  • Ajzen, I. B., & Fishbein, M. (1980). Understanding Attitudes and Predicting Social Behavior. Englewood Cliffs: NJ: Prentice-Hal.
  • Ajzen, Icek. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179–211. Athmay, Al. A. A. AL, Fantazy, K., & Kumar, V. (2016). E-government adoption and user’s satisfaction: an empirical investigation. EuroMed Journal of Business, 11(1), 57–83.
  • Bagozzi, R. P. (2007). The legacy of the technology acceptance model and a proposal for a paradigm shift. Journal of the Association for Information Systems, 8(4), 244–254.
  • Beránek, L., Nýdl, V., & Remeš, R. (2015). Factors Influencing Customer Repeated Purchase Behavior in the E-commerce Contex. The International Scientific Conference INPROFORUM (pp. 123–128).
  • Bhattacherjee, A. (2001a). Understanding Information Systems Continuance: An Expectation-Confirmation Model. MIS Quarterly, 25(3), 351–370.
  • Bhattacherjee, A. (2001b). An empirical analysis of the antecedents of electronic commerce service continuance. Decision Support Systems, 32(2), 201–214.
  • Chen, J. V., Rungruengsamrit, D., Rajkumar, T. M., & Yen, D. C. (2013). Success of electronic commerce Web sites: A comparative study in two countries. Information and Management, 50(6), 344–355. Elsevier B.V. Retrieved from http://dx.doi.org/10.1016/j.im.2013.02.007
  • Chen, Y. T., & Chou, T. Y. (2012). Exploring the continuance intentions of consumers for B2C online shopping: Perspectives of fairness and trust. Online Information Review, 36(1), 104–125.
  • Cheung, C. M. K., Zheng, X., & Lee, M. K. O. (2015). How the Conscious and Automatic Information Processing Modes Influence Consumers ’ Continuance Decision in an e-Commerce Website. Pacific Asia Journal of the Association for Information Systems, 7(2), 25–40.
  • Chiu, C. M., Hsu, M. H., Lai, H., & Chang, C. M. (2012). Re-examining the influence of trust on online repeat purchase intention: The moderating role of habit and its antecedents. Decision Support Systems, 53(4), 835–845. Elsevier B.V. Retrieved from http://dx.doi.org/10.1016/j.dss.2012.05.021
  • Chopdar, P. K., & Sivakumar, V. J. (2019). Understanding continuance usage of mobile shopping applications in India: the role of espoused cultural values and perceived risk. Behaviour and Information Technology, 38(1), 42–64. Taylor & Francis.
  • Collazo, A. A. (2018). A Theory-Based Model for Understanding Faculty Intention to Use Students Ratings to Improve Teaching in a Health Sciences Institution in Puerto Rico. Journal of Hispanic Higher Education, 17(3), 229–248.
  • 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.
  • Delone, W. H., & E. McLean. (1992). Information Systems Success: The Quest for the Dependent Variable. Information Systems Research. The Institute of Management Sciences (now INFORMS), 3(1), 60–95.
  • DeLone, W. H., & McLean, E. R. (2002). Information Systems Success Revisited. Proceedings of the 35th Annual Hawaii International Conference on System Sciences (pp. 2966–2976). Big Island, HI.
  • DeLone, W. H., & McLean, E. R. (2003). The DeLone and McLean model of information systems success: A ten-year update. Journal of Management Information Systems, 19(4), 9–30.
  • DeLone, W. H., & McLean, E. R. (2004). Measuring e-Commerce Success: Applying the DeLone & McLean Information Systems Success Model. International Journal of Electronic Commerce, 9(1), 31–47. Retrieved from https://www.tandfonline.com/doi/full/10.1080/10864415.2004.11044317
  • Fornell, C., & Larcker, D. F. (1981). Evaluating Structural Equation Models with Unobservable Variables and Measurement Error. Journal of Marketing Research, 18(1), 39.
  • Gao, L., Waechter, K. A., & Bai, X. (2015). Understanding consumers’ continuance intention towards mobile purchase: A theoretical framework and empirical study - A case of China. Computers in Human Behavior, 53, 249–262. Elsevier Ltd. Retrieved from http://dx.doi.org/10.1016/j.chb.2015.07.014
  • Hair, J., Hult, G., Ringle, C., & Sarstedy, M. (2017). A primer on Partial Least Squares Structural Equation Modelling (PLS-SEM) (2nd ed.). Los Angeles: SAGE Publications, Inc.
  • Hair, Joe F., Ringle, C. M., & Sarstedt, M. (2011). PLS-SEM: Indeed a silver bullet. Journal of Marketing Theory and Practice, 19(2), 139–152.
  • Hair, Joseph F., Black, W. C., Babin, B. J., & Anderson, R. E. (2014). Multivariate Data Analysis. Exploratory Data Analysis in Business and Economics.
  • Halawi, L., & Mccarthy, R. (2008). Measuring Students Perceptions of Blackboard Using the Technology Acceptance Model: a Pls Approach. Issues in Information Systems, 9(2), 95–102.
  • Hofstede, G. (1980). Culture Consequences: International Differences in Work-related Values. Beverly Hills, CA.: Sage Publications.
  • Hofstede, G. (1991). Cultures and organizations: Software of the mind. New York: McGraw-Hill.
  • Hofstede, G. (2001). Culture’s Consequences: Comparing Values, Behaviors, Institutions, and Organizations Across Nations (2nd ed.). CA: Sage.
  • Hofstede Insights. (2020). Country Comparison. Retrieved March 10, 2020, from https://www.hofstede-insights.com/product/compare-countries/
  • Hsu, C.-L., Chang, K.-C., & Chen, M.-C. (2012). Flow Experience and Internet Shopping Behavior: Investigating the Moderating Effect of Consumer Characteristics. Systems Research and Behavioral Science, 29(3), 317–332.
  • Hsu, M. H., Yen, C. H., Chiu, C. M., & Chang, C. M. (2006). A longitudinal investigation of continued online shopping behavior: An extension of the theory of planned behavior. International Journal of Human Computer Studies, 64(9), 889–904.
  • Kang, Y. S., & Lee, H. (2010). Understanding the role of an IT artifact in online service continuance: An extended perspective of user satisfaction. Computers in Human Behavior, 26(3), 353–364. Elsevier Ltd. Retrieved from http://dx.doi.org/10.1016/j.chb.2009.11.006
  • Koppius, O., Speelman, W., Stulp, O., Verhoef, B., & van Heck, E. (2005). Why are customers coming back to buy their airline tickets online? theoretical explanations and empirical evidence. Proceedings of the 7th International Conference on Electronic Commerce (pp. 319–326).
  • Kueh, K., & Voon, B. H. (2007). Culture and service quality expectations: Evidence from Generation Y consumers in Malaysia. Managing Service Quality, 17(6), 656–680.
  • Lai, C., & Pires, G. (2010). Testing of a model evaluating e-government portal acceptance and satisfaction. The Electronic Journal Information Systems Evaluation, 13(1), 35–46.
  • Lee, K. C., & Chung, N. (2009). Understanding factors affecting trust in and satisfaction with mobile banking in Korea: A modified DeLone and McLean’s model perspective. Interacting with Computers, 21(5–6), 385–392. Elsevier B.V. Retrieved from http://dx.doi.org/10.1016/j.intcom.2009.06.004
  • Lee, M. K. O., Shi, N., Cheung, C. M. K., Lim, K. H., & Sia, C. L. (2011). Consumer’s decision to shop online: The moderating role of positive informational social influence. Information and Management, 48(6), 185–191. Elsevier B.V. Retrieved from http://dx.doi.org/10.1016/j.im.2010.08.005
  • Legris, P., Ingham, J., & Collerette, P. (2003). Why do people use information technology? A critical review of the technology acceptance model. Information and Management, 40(3), 191–204.
  • Lu, J., Wei, J., Yu, C. S., & Liu, C. (2017). How do post-usage factors and espoused cultural values impact mobile payment continuation? Behaviour and Information Technology, 36(2), 140–164.
  • Ma, Y., Ruangkanjanases, A., & Chen, S. C. (2019). Investigating the impact of critical factors on continuance intention towards cross-border shopping websites. Sustainability (Switzerland), 11(21).
  • Mason, R. O. (1978). Measuring information output: A communication systems approach. Information & Management, 1(4), 219–234.
  • Mohamed, N., Hussein, R., Zamzuri, N. H. A., & Haghshenas, H. (2014). Insights into individual’s online shopping continuance intention. Industrial Management & Data Systems, 114(9), 1453–1476.
  • Molla, A., & Licker, P. S. (2001). E-Commerce Systems Success : an Attempt To Extend and Respecify the Delone and Maclean Model of Is Success. Journal of Electronic Commerce Research, 2(4), 131–141.
  • Mouakket, S. (2018). The role of personality traits in motivating users’ continuance intention towards Facebook: Gender differences. Journal of High Technology Management Research, 29(1), 124–140. Elsevier Inc. Retrieved from https://doi.org/10.1016/j.hitech.2016.10.003
  • Nath, R., & Murthy, N. R. V. (2004). A study of the relationship between Internet diffusion and culture. Journal of International Technology and Information, 13(1994), 123–132.
  • Nunnally, J. C. (1978). Psychometric Theory (2nd ed.). New York: McGraw-Hill.
  • Nunnally, Jum C., & Bernstein, I. H. (1994). Psychometric Theory: 3rd (Third) edition. New York: McGraw-Hill.
  • Odusanya, K., Aluko, O., & Lal, B. (2020). Building Consumers’ Trust in Electronic Retail Platforms in the Sub-Saharan Context: an exploratory study on Drivers and Impact on Continuance Intention. Information Systems Frontiers, (2016). Information Systems Frontiers.
  • Oliver, R. L. (1977). Effect of Expectation and Disconfirmation on Postexposure Product Evaluations : An Alternative Interpretation. Journal of Applied Psychology, 62(4), 480–486.
  • Oliver, R. L. (1980). A Cognitive Model of the Antecedents and Consequences of Satisfaction Decisions. Journal of Marketing Research, 17(4), 460–469.
  • Rai, A., Lang, S. S., & Welker, R. B. (2002). Assessing the validity of IS success models: An empirical test and theoretical analysis. Information Systems Research, 13(1), 50–69.
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UNDERSTANDING ONLINE SHOPPING CONTINUANCE INTENTION OF TURKISH USERS: AN EMPIRICAL ASSESSMENT

Yıl 2022, Sayı: 50, 144 - 160, 20.04.2022
https://doi.org/10.30794/pausbed.1003073

Öz

Online shopping has become one of the most essential activities in our corporate as well as individual lives for the last couple of decades. Better understanding of socio-psychological, technical, and individual antecedents of adopting, more importantly continuously using websites have critical importance for the financial, organizational, economic, and technical success of online shopping activities. In this study, the factors affecting Turkish users’ satisfaction with online shopping and their intention to continue using online shopping have been investigated by integrating the information system success model (ISSM), information system continuance model (ISCM), and technology acceptance theories. Especially continuance intention of online shopping is not widely investigated construct among Turkish E-Commerce Studies. This study also contributes in Information Systems research domain by integrating and empirically testing variety of research frameworks mentioned above. The empirical model of this study has been tested by using the partial least squares structural equation modeling (PLS-SEM) technique. Data were collected using the convenience sampling technique from 313 online shopping users. The results revealed that perceived usefulness and information quality have significant and profound effects on users` continued use of online shopping websites.

Proje Numarası

Yok

Kaynakça

  • Ab Hamid, M. R., Sami, W., & Mohmad Sidek, M. H. (2017). Discriminant Validity Assessment: Use of Fornell & Larcker criterion versus HTMT Criterion. Journal of Physics: Conference Series, 890(1), 0–5.
  • Adaji, I., & Vassileva, J. (2016). Perceived Effectiveness, Credibility and Continuance Intention in E-commerce: A Study of Amazon. 2016 Persuasive Technology conference (pp. 293–305).
  • Ajzen, I. (1988). Attitudes, Personality, and Behavior. Chicago, IL: Dorsey Press.
  • Ajzen, I. B., & Fishbein, M. (1980). Understanding Attitudes and Predicting Social Behavior. Englewood Cliffs: NJ: Prentice-Hal.
  • Ajzen, Icek. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179–211. Athmay, Al. A. A. AL, Fantazy, K., & Kumar, V. (2016). E-government adoption and user’s satisfaction: an empirical investigation. EuroMed Journal of Business, 11(1), 57–83.
  • Bagozzi, R. P. (2007). The legacy of the technology acceptance model and a proposal for a paradigm shift. Journal of the Association for Information Systems, 8(4), 244–254.
  • Beránek, L., Nýdl, V., & Remeš, R. (2015). Factors Influencing Customer Repeated Purchase Behavior in the E-commerce Contex. The International Scientific Conference INPROFORUM (pp. 123–128).
  • Bhattacherjee, A. (2001a). Understanding Information Systems Continuance: An Expectation-Confirmation Model. MIS Quarterly, 25(3), 351–370.
  • Bhattacherjee, A. (2001b). An empirical analysis of the antecedents of electronic commerce service continuance. Decision Support Systems, 32(2), 201–214.
  • Chen, J. V., Rungruengsamrit, D., Rajkumar, T. M., & Yen, D. C. (2013). Success of electronic commerce Web sites: A comparative study in two countries. Information and Management, 50(6), 344–355. Elsevier B.V. Retrieved from http://dx.doi.org/10.1016/j.im.2013.02.007
  • Chen, Y. T., & Chou, T. Y. (2012). Exploring the continuance intentions of consumers for B2C online shopping: Perspectives of fairness and trust. Online Information Review, 36(1), 104–125.
  • Cheung, C. M. K., Zheng, X., & Lee, M. K. O. (2015). How the Conscious and Automatic Information Processing Modes Influence Consumers ’ Continuance Decision in an e-Commerce Website. Pacific Asia Journal of the Association for Information Systems, 7(2), 25–40.
  • Chiu, C. M., Hsu, M. H., Lai, H., & Chang, C. M. (2012). Re-examining the influence of trust on online repeat purchase intention: The moderating role of habit and its antecedents. Decision Support Systems, 53(4), 835–845. Elsevier B.V. Retrieved from http://dx.doi.org/10.1016/j.dss.2012.05.021
  • Chopdar, P. K., & Sivakumar, V. J. (2019). Understanding continuance usage of mobile shopping applications in India: the role of espoused cultural values and perceived risk. Behaviour and Information Technology, 38(1), 42–64. Taylor & Francis.
  • Collazo, A. A. (2018). A Theory-Based Model for Understanding Faculty Intention to Use Students Ratings to Improve Teaching in a Health Sciences Institution in Puerto Rico. Journal of Hispanic Higher Education, 17(3), 229–248.
  • 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.
  • Delone, W. H., & E. McLean. (1992). Information Systems Success: The Quest for the Dependent Variable. Information Systems Research. The Institute of Management Sciences (now INFORMS), 3(1), 60–95.
  • DeLone, W. H., & McLean, E. R. (2002). Information Systems Success Revisited. Proceedings of the 35th Annual Hawaii International Conference on System Sciences (pp. 2966–2976). Big Island, HI.
  • DeLone, W. H., & McLean, E. R. (2003). The DeLone and McLean model of information systems success: A ten-year update. Journal of Management Information Systems, 19(4), 9–30.
  • DeLone, W. H., & McLean, E. R. (2004). Measuring e-Commerce Success: Applying the DeLone & McLean Information Systems Success Model. International Journal of Electronic Commerce, 9(1), 31–47. Retrieved from https://www.tandfonline.com/doi/full/10.1080/10864415.2004.11044317
  • Fornell, C., & Larcker, D. F. (1981). Evaluating Structural Equation Models with Unobservable Variables and Measurement Error. Journal of Marketing Research, 18(1), 39.
  • Gao, L., Waechter, K. A., & Bai, X. (2015). Understanding consumers’ continuance intention towards mobile purchase: A theoretical framework and empirical study - A case of China. Computers in Human Behavior, 53, 249–262. Elsevier Ltd. Retrieved from http://dx.doi.org/10.1016/j.chb.2015.07.014
  • Hair, J., Hult, G., Ringle, C., & Sarstedy, M. (2017). A primer on Partial Least Squares Structural Equation Modelling (PLS-SEM) (2nd ed.). Los Angeles: SAGE Publications, Inc.
  • Hair, Joe F., Ringle, C. M., & Sarstedt, M. (2011). PLS-SEM: Indeed a silver bullet. Journal of Marketing Theory and Practice, 19(2), 139–152.
  • Hair, Joseph F., Black, W. C., Babin, B. J., & Anderson, R. E. (2014). Multivariate Data Analysis. Exploratory Data Analysis in Business and Economics.
  • Halawi, L., & Mccarthy, R. (2008). Measuring Students Perceptions of Blackboard Using the Technology Acceptance Model: a Pls Approach. Issues in Information Systems, 9(2), 95–102.
  • Hofstede, G. (1980). Culture Consequences: International Differences in Work-related Values. Beverly Hills, CA.: Sage Publications.
  • Hofstede, G. (1991). Cultures and organizations: Software of the mind. New York: McGraw-Hill.
  • Hofstede, G. (2001). Culture’s Consequences: Comparing Values, Behaviors, Institutions, and Organizations Across Nations (2nd ed.). CA: Sage.
  • Hofstede Insights. (2020). Country Comparison. Retrieved March 10, 2020, from https://www.hofstede-insights.com/product/compare-countries/
  • Hsu, C.-L., Chang, K.-C., & Chen, M.-C. (2012). Flow Experience and Internet Shopping Behavior: Investigating the Moderating Effect of Consumer Characteristics. Systems Research and Behavioral Science, 29(3), 317–332.
  • Hsu, M. H., Yen, C. H., Chiu, C. M., & Chang, C. M. (2006). A longitudinal investigation of continued online shopping behavior: An extension of the theory of planned behavior. International Journal of Human Computer Studies, 64(9), 889–904.
  • Kang, Y. S., & Lee, H. (2010). Understanding the role of an IT artifact in online service continuance: An extended perspective of user satisfaction. Computers in Human Behavior, 26(3), 353–364. Elsevier Ltd. Retrieved from http://dx.doi.org/10.1016/j.chb.2009.11.006
  • Koppius, O., Speelman, W., Stulp, O., Verhoef, B., & van Heck, E. (2005). Why are customers coming back to buy their airline tickets online? theoretical explanations and empirical evidence. Proceedings of the 7th International Conference on Electronic Commerce (pp. 319–326).
  • Kueh, K., & Voon, B. H. (2007). Culture and service quality expectations: Evidence from Generation Y consumers in Malaysia. Managing Service Quality, 17(6), 656–680.
  • Lai, C., & Pires, G. (2010). Testing of a model evaluating e-government portal acceptance and satisfaction. The Electronic Journal Information Systems Evaluation, 13(1), 35–46.
  • Lee, K. C., & Chung, N. (2009). Understanding factors affecting trust in and satisfaction with mobile banking in Korea: A modified DeLone and McLean’s model perspective. Interacting with Computers, 21(5–6), 385–392. Elsevier B.V. Retrieved from http://dx.doi.org/10.1016/j.intcom.2009.06.004
  • Lee, M. K. O., Shi, N., Cheung, C. M. K., Lim, K. H., & Sia, C. L. (2011). Consumer’s decision to shop online: The moderating role of positive informational social influence. Information and Management, 48(6), 185–191. Elsevier B.V. Retrieved from http://dx.doi.org/10.1016/j.im.2010.08.005
  • Legris, P., Ingham, J., & Collerette, P. (2003). Why do people use information technology? A critical review of the technology acceptance model. Information and Management, 40(3), 191–204.
  • Lu, J., Wei, J., Yu, C. S., & Liu, C. (2017). How do post-usage factors and espoused cultural values impact mobile payment continuation? Behaviour and Information Technology, 36(2), 140–164.
  • Ma, Y., Ruangkanjanases, A., & Chen, S. C. (2019). Investigating the impact of critical factors on continuance intention towards cross-border shopping websites. Sustainability (Switzerland), 11(21).
  • Mason, R. O. (1978). Measuring information output: A communication systems approach. Information & Management, 1(4), 219–234.
  • Mohamed, N., Hussein, R., Zamzuri, N. H. A., & Haghshenas, H. (2014). Insights into individual’s online shopping continuance intention. Industrial Management & Data Systems, 114(9), 1453–1476.
  • Molla, A., & Licker, P. S. (2001). E-Commerce Systems Success : an Attempt To Extend and Respecify the Delone and Maclean Model of Is Success. Journal of Electronic Commerce Research, 2(4), 131–141.
  • Mouakket, S. (2018). The role of personality traits in motivating users’ continuance intention towards Facebook: Gender differences. Journal of High Technology Management Research, 29(1), 124–140. Elsevier Inc. Retrieved from https://doi.org/10.1016/j.hitech.2016.10.003
  • Nath, R., & Murthy, N. R. V. (2004). A study of the relationship between Internet diffusion and culture. Journal of International Technology and Information, 13(1994), 123–132.
  • Nunnally, J. C. (1978). Psychometric Theory (2nd ed.). New York: McGraw-Hill.
  • Nunnally, Jum C., & Bernstein, I. H. (1994). Psychometric Theory: 3rd (Third) edition. New York: McGraw-Hill.
  • Odusanya, K., Aluko, O., & Lal, B. (2020). Building Consumers’ Trust in Electronic Retail Platforms in the Sub-Saharan Context: an exploratory study on Drivers and Impact on Continuance Intention. Information Systems Frontiers, (2016). Information Systems Frontiers.
  • Oliver, R. L. (1977). Effect of Expectation and Disconfirmation on Postexposure Product Evaluations : An Alternative Interpretation. Journal of Applied Psychology, 62(4), 480–486.
  • Oliver, R. L. (1980). A Cognitive Model of the Antecedents and Consequences of Satisfaction Decisions. Journal of Marketing Research, 17(4), 460–469.
  • Rai, A., Lang, S. S., & Welker, R. B. (2002). Assessing the validity of IS success models: An empirical test and theoretical analysis. Information Systems Research, 13(1), 50–69.
  • Rosillo-Díaz, E., Blanco-Encomienda, F. J., & Crespo-Almendros, E. (2019). A cross-cultural analysis of perceived product quality, perceived risk and purchase intention in e-commerce platforms. Journal of Enterprise Information Management, 33(1), 139–160.
  • Schaupp, L. C. (2010). Web site success: Antecedents of web site satisfaction and re-use. Journal of Internet Commerce, 9(1), 42–64.
  • Seddon, P. (1997). A respecification and extension of the DeLone and McLean model of IS. Information Systems Research. Information Systems Research, 8(3), 240–253. Retrieved from https://pubsonline.informs.org/doi/abs/10.1287/isre.8.3.240
  • Shannon, C. E., & Weaver, W. (1949). The mathematical theory of communication. Urbana: University of Illinois Press.
  • Sia, C. L., Lim, K. H., Leung, K., Lee, M. K. O., Huang, W. W., & Benbasat, I. (2009). Web strategies to promote internet shopping: Is cultural-customization needed? MIS Quarterly: Management Information Systems, 33(3), 491–512.
  • T.R. Ministry of Family Labor and Social Services. (2020). Asgari Ücretin Net Hesabı ve İşverene Maliyeti (Yıllara Göre). Retrieved January 15, 2020, from https://www.ailevecalisma.gov.tr/tr-tr/asgari-ucret/asgari-ucret-2020/
  • To, P. L., Liao, C., & Lin, T. H. (2007). Shopping motivations on Internet: A study based on utilitarian and hedonic value. Technovation, 27(12), 774–787.
  • TUBISAD. (2019). Türkiye’de E-Ticaret, 2018 Pazar Büyüklüğü. Retrieved August 18, 2019, from http://www.tubisad.org.tr/tr/images/pdf/tubisad_2019_e-ticaret_sunum_tr.pdf
  • TURKSTAT. (2020a). Individuals using the computer and Internet in the last 3 months by age groups and sex, 2004-2019. Retrieved February 17, 2020, from http://www.turkstat.gov.tr/PreTablo.do?alt_id=1028
  • TURKSTAT. (2020b). Internet purchases by individuals in the last 12 months for the private use by type of goods and services by sex, 2011-2019. Retrieved January 12, 2020, from http://www.turkstat.gov.tr/PreTablo.do?alt_id=1028
  • TURKSTAT. (2020c). Information and Communication Technology (ICT) Usage in Households and by Individuals. Retrieved from https://data.tuik.gov.tr/Bulten/Index?p=Hanehalki-Bilisim-Teknolojileri-(BT)-Kullanim-Arastirmasi-2020-33679
  • Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User Acceptence of Information Technology: Toward a Unified View. MIS Quarterly, 27(3), 425–478.
  • Wen, C., Prybutok, V. R., & Chenyan, X. (2011). AN INTEGRATED MODEL FOR CUSTOMER ONLINE REPURCHASE INTENTION. Journal of Computer Information Systems, 52(1), 14–23.
  • Yassierli, Y., Vinsensius, V., & Mohamed, M. S. S. (2018). The Importance of Usability Aspect in M-Commerce Application for Satisfaction and Continuance Intention. Makara Journal of Technology, 22(3), 149.
  • Yaveroglu, I. S., & Donthu, N. (2002). Cultural Influences on the Diffusion of New Products. Journal of International Consumer Marketing, 14(4), 49–63.
Toplam 67 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Finans
Bölüm Makaleler
Yazarlar

Kadir Kurt 0000-0002-4857-2492

Bahadır Aktaş 0000-0002-3650-6471

Aykut Turan 0000-0002-8855-4643

Proje Numarası Yok
Erken Görünüm Tarihi 15 Mayıs 2022
Yayımlanma Tarihi 20 Nisan 2022
Kabul Tarihi 22 Kasım 2021
Yayımlandığı Sayı Yıl 2022 Sayı: 50

Kaynak Göster

APA Kurt, K., Aktaş, B., & Turan, A. (2022). UNDERSTANDING ONLINE SHOPPING CONTINUANCE INTENTION OF TURKISH USERS: AN EMPIRICAL ASSESSMENT. Pamukkale Üniversitesi Sosyal Bilimler Enstitüsü Dergisi(50), 144-160. https://doi.org/10.30794/pausbed.1003073
AMA Kurt K, Aktaş B, Turan A. UNDERSTANDING ONLINE SHOPPING CONTINUANCE INTENTION OF TURKISH USERS: AN EMPIRICAL ASSESSMENT. PAUSBED. Nisan 2022;(50):144-160. doi:10.30794/pausbed.1003073
Chicago Kurt, Kadir, Bahadır Aktaş, ve Aykut Turan. “UNDERSTANDING ONLINE SHOPPING CONTINUANCE INTENTION OF TURKISH USERS: AN EMPIRICAL ASSESSMENT”. Pamukkale Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, sy. 50 (Nisan 2022): 144-60. https://doi.org/10.30794/pausbed.1003073.
EndNote Kurt K, Aktaş B, Turan A (01 Nisan 2022) UNDERSTANDING ONLINE SHOPPING CONTINUANCE INTENTION OF TURKISH USERS: AN EMPIRICAL ASSESSMENT. Pamukkale Üniversitesi Sosyal Bilimler Enstitüsü Dergisi 50 144–160.
IEEE K. Kurt, B. Aktaş, ve A. Turan, “UNDERSTANDING ONLINE SHOPPING CONTINUANCE INTENTION OF TURKISH USERS: AN EMPIRICAL ASSESSMENT”, PAUSBED, sy. 50, ss. 144–160, Nisan 2022, doi: 10.30794/pausbed.1003073.
ISNAD Kurt, Kadir vd. “UNDERSTANDING ONLINE SHOPPING CONTINUANCE INTENTION OF TURKISH USERS: AN EMPIRICAL ASSESSMENT”. Pamukkale Üniversitesi Sosyal Bilimler Enstitüsü Dergisi 50 (Nisan 2022), 144-160. https://doi.org/10.30794/pausbed.1003073.
JAMA Kurt K, Aktaş B, Turan A. UNDERSTANDING ONLINE SHOPPING CONTINUANCE INTENTION OF TURKISH USERS: AN EMPIRICAL ASSESSMENT. PAUSBED. 2022;:144–160.
MLA Kurt, Kadir vd. “UNDERSTANDING ONLINE SHOPPING CONTINUANCE INTENTION OF TURKISH USERS: AN EMPIRICAL ASSESSMENT”. Pamukkale Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, sy. 50, 2022, ss. 144-60, doi:10.30794/pausbed.1003073.
Vancouver Kurt K, Aktaş B, Turan A. UNDERSTANDING ONLINE SHOPPING CONTINUANCE INTENTION OF TURKISH USERS: AN EMPIRICAL ASSESSMENT. PAUSBED. 2022(50):144-60.