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THE INFLUENCE OF PERSONALIZED MARKETING AND DATA PRIVACY CONCERNS ON CONSUMER BEHAVIOR: THE MEDIATING ROLE OF PERCEIVED VALUE

Yıl 2025, Cilt: 26 Sayı: 2, 315 - 337, 22.07.2025

Altuğ Ocak

Öz

This study examines the complex interplay between personalized marketing (PM), data privacy concerns (DPC), perceived value (PV) and purchase intention (PI) in a sample of online consumers. The main aim of the research is to investigate the dual influence of PM and DPC on PV and PI, focusing on the mediating role of PV. To achieve this, all the data was collected through a constructed questionnaire involving 386 online consumers who have encountered PM. The questionnaire used established scales to measure PM, DPC, PV and PI. Analytical tools such as Confirmatory Factor Analysis (CFA) and Structural Equation Modeling (SEM) were used to validate the measurement model and test the hypotheses. The outcomes show PM positively influences both PV and PI, while DPC negatively influences PV and has a weaker effect on PI. PV was found to mediate the link between PM and PI and the relationship between DPC and PI. These results suggest that marketers need to strike a better balance between personalization and sound data privacy practices to increase PV and drive consumer behavior.

Anahtar Kelimeler

Personalized marketing data privacy concerns perceived value purchase intention consumer behavior.

Etik Beyan

Ethical approval for this research was granted by the Scientific Research and Publication Ethics Committee for Social Sciences and Humanities at Istanbul Beykent University, under approval number 163111, dated October 7, 2024.

Destekleyen Kurum

Istanbul Beykent University

Kaynakça

  • Aguirre, E., Mahr, D., Grewal, D., de Ruyter, K., & Wetzels, M. (2015). Unraveling the personalization paradox: The effect of information collection and trust-building strategies on online advertisement effectiveness. Journal of Retailing, 91(1), 34–49. https://doi.org/10.1016/j.jretai.2014.09.005
  • Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179–211. https://doi.org/10.1016/0749-5978(91)90020-T
  • Alkadrie, S. A. (2024). Exploring the Impact of Digital Marketing Strategies on Consumer Purchase Behavior in the E-commerce Sector. The Journal of Academic Science, 1(4), 273-282. https://doi.org/10.59613/5p6gp784
  • Alkadrie, S. A. (2024). Exploring the Impact of Digital Marketing Strategies on Consumer Purchase Behavior in the E-commerce Sector. The Journal of Academic Science, 1(4), 273-282.
  • Arora, N., Drèze, X., Ghose, A., Hess, J. D., Iyengar, R., Jing, B., & Zhang, Y. (2008). Putting one-to-one marketing to work: Personalization, customization and choice. Marketing Letters, 19(3–4), 305–321. https://doi.org/10.1007/s11002-008-9056-z
  • Baek, T. H., & Morimoto, M. (2012). Stay away from me: Examining the determinants of consumer avoidance of personalized advertising. Journal of Advertising, 41(1), 59–76. https://doi.org/10.2753/JOA0091-3367410105
  • Bentler, P. M. (1990). Comparative fit indexes in structural models. Psychological Bulletin, 107(2), 238–246. https://doi.org/10.1037/0033-2909.107.2.238
  • Bentler, P. M., & Bonett, D. G. (1980). Significance tests and goodness of fit in the analysis of covariance structures. Psychological Bulletin, 88(3), 588–606. https://doi.org/10.1037/0033-2909.88.3.588
  • Bhattacharya, S., Sharma, R. P., & Gupta, A. (2023). Does e-retailer's country of origin influence consumer privacy, trust and purchase intention? Journal of Consumer Marketing, 40(2), 248–259. http://dx.doi.org/10.1108/JCM-04-2021-4611
  • Bleier, A., & Eisenbeiss, M. (2015). Personalized online advertising effectiveness: The interplay of what, when and where. Marketing Science, 34(5), 669–688. https://doi.org/10.1287/mksc.2015.0930
  • Bleier, A., & Eisenbeiss, M. (2015). The importance of trust for personalized online advertising. Journal of Retailing, 91(3), 390–409. https://doi.org/10.1016/j.jretai.2015.04.001
  • Bryman, A., & Bell, E. (2015). Business research methods (4th ed.). Oxford University Press.
  • Chellappa, R. K., & Shivendu, S. (2005). Managing piracy: Pricing and sampling strategies for digital experience goods in vertically segmented markets. Information Systems Research, 16(4), 400–417. https://doi.org/10.1287/isre.1050.0069
  • Culnan, M. J., & Armstrong, P. K. (1999). Information privacy concerns, procedural fairness and impersonal trust: An empirical investigation. Organization Science, 10(1), 104–115. https://doi.org/10.1287/orsc.10.1.104
  • Dinev, T., & Hart, P. (2006). An extended privacy calculus model for e-commerce transactions. Information Systems Research, 17(1), 61–80. https://doi.org/10.1287/isre.1060.0080
  • Ding, Y., & Keh, H. T. (2016). A reexamination of service standardization versus customization from the consumer perspective. Journal of Services Marketing, 30(1), 16–28. https://doi.org/10.1108/JSM-02-2015-0088
  • Dodds, W. B., Monroe, K. B., & Grewal, D. (1991). Effects of price, brand and store information on buyers' product evaluations. Journal of Marketing Research, 28(3), 307–319. https://doi.org/10.1177/002224379102800305
  • Etikan, I., Musa, S. A., & Alkassim, R. S. (2016). Comparison of convenience sampling and purposive sampling. American Journal of Theoretical and Applied Statistics, 5(1), 1–4. https://doi.org/10.11648/j.ajtas.20160501.11
  • Fan, W., Shao, B., & Dong, X. (2022). Effect of e-service quality on customer engagement behavior in community e-commerce. Frontiers in Psychology, 13, 965998. https://doi.org/10.3389/fpsyg.2022.965998
  • Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39–50. https://doi.org/10.1177/002224378101800104
  • Grewal, D., Monroe, K. B., & Krishnan, R. (1998). The effects of price-comparison advertising on buyers' perceptions of acquisition value, transaction value and behavioral intentions. Journal of Marketing, 62(2), 46–59. https://doi.org/10.1177/002224299806200204
  • Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2010). Multivariate data analysis (7th ed.). Pearson
  • Hair, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2017). A primer on partial least squares SEM (PLS-SEM) (2nd ed.). SAGE Publications.
  • Henseler, J., Hubona, G., & Ray, P. A. (2016). Using PLS path modeling in new technology research: Updated guidelines. Industrial Management & Data Systems, 116(1), 2–20. https://doi.org/10.1108/IMDS-09-2015-0382
  • Henseler, J., Ringle, C. M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based SEM. Journal of the Academy of Marketing Science, 43(1), 115–135. https://doi.org/10.1007/s11747-014-0403-8
  • Hoang, D. P. (2019). The central role of customer dialogue and trust in gaining bank loyalty: An extended SWICS model. International Journal of Bank Marketing, 37(3), 711–729. https://doi.org/10.1108/IJBM-03-2018-0069
  • Hu, L. T., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling: A Multidisciplinary Journal, 6(1), 1–55. https://doi.org/10.1080/10705519909540118
  • 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. https://doi.org/10.1016/j.dss.2007.07.001
  • Kim, J., Steinhoff, L., & Palmatier, R. W. (2021). An emerging theory of loyalty program dynamics. Journal of the Academy of Marketing Science, 49(1), 71–95. https://doi.org/10.1007/s11747-020-00719-1
  • Kline, R. B. (2015). Principles and practice of structural equation modeling (4th ed.). Guilford Publications.
  • Liao, C., Liu, C. C., & Chen, K. (2011). Examining the impact of privacy, trust and risk perceptions beyond monetary transactions: An integrated model. Electronic Commerce Research and Applications, 10(6), 702–715. https://doi.org/10.1016/j.elerap.2011.07.003
  • Liao, C., Liu, C. C., & Chen, K. (2023). Examining the impact of privacy, trust and risk perceptions beyond monetary transactions: An integrated model. Electronic Commerce Research and Applications, 10(6), 702–715. https://doi.org/10.1016/j.elerap.2023.07.003
  • Lin, M. Y. C., Do, B. R., Nguyen, T. T., & Cheng, J. M. S. (2022). Effects of personal innovativeness and perceived value of disclosure on data privacy concerns in proximity marketing: Self-control as a moderator. Journal of Research in Interactive Marketing, 16(2), 310–327. https://doi.org/10.1108/JRIM-04-2021-0112
  • Malhotra, N. K., Kim, S. S., & Agarwal, J. (2004). Internet users' information privacy concerns (IUIPC): The construct, the scale and a causal model. Information Systems Research, 15(4), 336–355. https://doi.org/10.1287/isre.1040.0032
  • Martin, K. D., & Murphy, P. E. (2017). The role of data privacy in marketing. Journal of the Academy of Marketing Science, 45, 135–155. https://doi.org/10.1007/s11747-016-0495-4
  • Muhammad, S. S., Dey, B. L., & Weerakkody, V. (2018). Analysis of factors that influence customers' willingness to leave big data digital footprints on social media: A systematic review of literature. Information Systems Frontiers, 20(3), 559–576. https://doi.org/10.1007/s10796-017-9802-y
  • Nunnally, J. C. (1978). Psychometric theory (2nd ed.). McGraw-Hill.
  • Pappas, N. (2016). Marketing strategies, perceived risks and consumer trust in online buying behaviour. Journal of Retailing and Consumer Services, 29, 92–103. https://doi.org/10.1016/j.jretconser.2015.11.007
  • Ponte, E. B., Carvajal-Trujillo, E., & Escobar-Rodríguez, T. (2015). Influence of trust and perceived value on the intention to purchase travel online: Integrating the effects of assurance on trust antecedents. Tourism Management, 47, 286–302. https://doi.org/10.1016/j.tourman.2014.10.009
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KİŞİSELLEŞTİRİLMİŞ PAZARLAMA VE VERİ GİZLİLİĞİ KAYGILARININ TÜKETİCİ DAVRANIŞI ÜZERİNDEKİ ETKİSİ: ALGILANAN DEĞERİN ARACILIK ROLÜ

Yıl 2025, Cilt: 26 Sayı: 2, 315 - 337, 22.07.2025

Altuğ Ocak

Öz

Bu çalışma, kişiselleştirilmiş pazarlama, veri gizliliği endişeleri, algılanan değer ve satın alma niyeti arasındaki karmaşık ilişkiyi çevrimiçi tüketiciler bağlamında incelemektedir. Çalışmanın temel amacı, algılanan değerin aracılık rolüne odaklanarak, kişiselleştirilmiş pazarlama ve veri gizliliği endişelerinin algılanan değer ve satın alma niyeti üzerindeki ikili etkisini araştırmaktır. Bunu başarmak için veriler, daha önce kişiselleştirilmiş pazarlama deneyimi olan 386 çevrimiçi tüketiciyi kapsayan yapılandırılm-ış bir anket aracılığıyla toplanmıştır. Ankette kişiselleştirilmiş pazarlama, veri gizliliği endişeleri, algılanan değer ve satın alma niyetini ölçmek için mevcut ölçekler kullanılmıştır. Ölçüm modelini doğrulamak ve hipotezleri test etmek için Doğrulayıcı Faktör Analizi (DFA) ve Yapısal Eşitlik Modellemesi (YEM) gibi analitik teknikler uygulanmıştır. Bulgular, kişiselleştirilmiş pazarlamanın hem algılanan değeri hem de satın alma niyetini olumlu yönde desteklediğini, veri gizliliği endişelerinin ise algılanan değeri olumsuz yönde etkilediğini ve satın alma niyeti üzerinde daha zayıf bir doğrudan etkisinin olduğunu ortaya koymaktadır. Algılanan değer, kişiselleştirilmiş pazarlama ile satın alma niyeti arasındaki ve veri gizliliği endişeleri ile satın alma niyeti arasındaki etkileşime aracılık etmektedir. Bu bulgular, pazarlamacıların algılanan değeri artırmak ve tüketici davranışını yönlendirmek için kişiselleştirme ile güçlü veri gizliliği uygulamaları arasında bir denge kurması gerektiğinin altını çizmektedir.

Anahtar Kelimeler

Kişiselleştirilmiş pazarlama veri gizliliği endişeleri algılanan değer satın alma niyeti tüketici davranışı.

Etik Beyan

Bu araştırma için etik onay, İstanbul Beykent Üniversitesi Sosyal ve Beşerî Bilimler İçin Bilimsel Araştırma ve Yayın Etiği Kurulu tarafından 7 Ekim 2024 tarih ve 163111 sayılı onay numarasıyla verilmiştir.

Destekleyen Kurum

İstanbul Beykent Üniversitesi

Kaynakça

  • Aguirre, E., Mahr, D., Grewal, D., de Ruyter, K., & Wetzels, M. (2015). Unraveling the personalization paradox: The effect of information collection and trust-building strategies on online advertisement effectiveness. Journal of Retailing, 91(1), 34–49. https://doi.org/10.1016/j.jretai.2014.09.005
  • Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179–211. https://doi.org/10.1016/0749-5978(91)90020-T
  • Alkadrie, S. A. (2024). Exploring the Impact of Digital Marketing Strategies on Consumer Purchase Behavior in the E-commerce Sector. The Journal of Academic Science, 1(4), 273-282. https://doi.org/10.59613/5p6gp784
  • Alkadrie, S. A. (2024). Exploring the Impact of Digital Marketing Strategies on Consumer Purchase Behavior in the E-commerce Sector. The Journal of Academic Science, 1(4), 273-282.
  • Arora, N., Drèze, X., Ghose, A., Hess, J. D., Iyengar, R., Jing, B., & Zhang, Y. (2008). Putting one-to-one marketing to work: Personalization, customization and choice. Marketing Letters, 19(3–4), 305–321. https://doi.org/10.1007/s11002-008-9056-z
  • Baek, T. H., & Morimoto, M. (2012). Stay away from me: Examining the determinants of consumer avoidance of personalized advertising. Journal of Advertising, 41(1), 59–76. https://doi.org/10.2753/JOA0091-3367410105
  • Bentler, P. M. (1990). Comparative fit indexes in structural models. Psychological Bulletin, 107(2), 238–246. https://doi.org/10.1037/0033-2909.107.2.238
  • Bentler, P. M., & Bonett, D. G. (1980). Significance tests and goodness of fit in the analysis of covariance structures. Psychological Bulletin, 88(3), 588–606. https://doi.org/10.1037/0033-2909.88.3.588
  • Bhattacharya, S., Sharma, R. P., & Gupta, A. (2023). Does e-retailer's country of origin influence consumer privacy, trust and purchase intention? Journal of Consumer Marketing, 40(2), 248–259. http://dx.doi.org/10.1108/JCM-04-2021-4611
  • Bleier, A., & Eisenbeiss, M. (2015). Personalized online advertising effectiveness: The interplay of what, when and where. Marketing Science, 34(5), 669–688. https://doi.org/10.1287/mksc.2015.0930
  • Bleier, A., & Eisenbeiss, M. (2015). The importance of trust for personalized online advertising. Journal of Retailing, 91(3), 390–409. https://doi.org/10.1016/j.jretai.2015.04.001
  • Bryman, A., & Bell, E. (2015). Business research methods (4th ed.). Oxford University Press.
  • Chellappa, R. K., & Shivendu, S. (2005). Managing piracy: Pricing and sampling strategies for digital experience goods in vertically segmented markets. Information Systems Research, 16(4), 400–417. https://doi.org/10.1287/isre.1050.0069
  • Culnan, M. J., & Armstrong, P. K. (1999). Information privacy concerns, procedural fairness and impersonal trust: An empirical investigation. Organization Science, 10(1), 104–115. https://doi.org/10.1287/orsc.10.1.104
  • Dinev, T., & Hart, P. (2006). An extended privacy calculus model for e-commerce transactions. Information Systems Research, 17(1), 61–80. https://doi.org/10.1287/isre.1060.0080
  • Ding, Y., & Keh, H. T. (2016). A reexamination of service standardization versus customization from the consumer perspective. Journal of Services Marketing, 30(1), 16–28. https://doi.org/10.1108/JSM-02-2015-0088
  • Dodds, W. B., Monroe, K. B., & Grewal, D. (1991). Effects of price, brand and store information on buyers' product evaluations. Journal of Marketing Research, 28(3), 307–319. https://doi.org/10.1177/002224379102800305
  • Etikan, I., Musa, S. A., & Alkassim, R. S. (2016). Comparison of convenience sampling and purposive sampling. American Journal of Theoretical and Applied Statistics, 5(1), 1–4. https://doi.org/10.11648/j.ajtas.20160501.11
  • Fan, W., Shao, B., & Dong, X. (2022). Effect of e-service quality on customer engagement behavior in community e-commerce. Frontiers in Psychology, 13, 965998. https://doi.org/10.3389/fpsyg.2022.965998
  • Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39–50. https://doi.org/10.1177/002224378101800104
  • Grewal, D., Monroe, K. B., & Krishnan, R. (1998). The effects of price-comparison advertising on buyers' perceptions of acquisition value, transaction value and behavioral intentions. Journal of Marketing, 62(2), 46–59. https://doi.org/10.1177/002224299806200204
  • Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2010). Multivariate data analysis (7th ed.). Pearson
  • Hair, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2017). A primer on partial least squares SEM (PLS-SEM) (2nd ed.). SAGE Publications.
  • Henseler, J., Hubona, G., & Ray, P. A. (2016). Using PLS path modeling in new technology research: Updated guidelines. Industrial Management & Data Systems, 116(1), 2–20. https://doi.org/10.1108/IMDS-09-2015-0382
  • Henseler, J., Ringle, C. M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based SEM. Journal of the Academy of Marketing Science, 43(1), 115–135. https://doi.org/10.1007/s11747-014-0403-8
  • Hoang, D. P. (2019). The central role of customer dialogue and trust in gaining bank loyalty: An extended SWICS model. International Journal of Bank Marketing, 37(3), 711–729. https://doi.org/10.1108/IJBM-03-2018-0069
  • Hu, L. T., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling: A Multidisciplinary Journal, 6(1), 1–55. https://doi.org/10.1080/10705519909540118
  • 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. https://doi.org/10.1016/j.dss.2007.07.001
  • Kim, J., Steinhoff, L., & Palmatier, R. W. (2021). An emerging theory of loyalty program dynamics. Journal of the Academy of Marketing Science, 49(1), 71–95. https://doi.org/10.1007/s11747-020-00719-1
  • Kline, R. B. (2015). Principles and practice of structural equation modeling (4th ed.). Guilford Publications.
  • Liao, C., Liu, C. C., & Chen, K. (2011). Examining the impact of privacy, trust and risk perceptions beyond monetary transactions: An integrated model. Electronic Commerce Research and Applications, 10(6), 702–715. https://doi.org/10.1016/j.elerap.2011.07.003
  • Liao, C., Liu, C. C., & Chen, K. (2023). Examining the impact of privacy, trust and risk perceptions beyond monetary transactions: An integrated model. Electronic Commerce Research and Applications, 10(6), 702–715. https://doi.org/10.1016/j.elerap.2023.07.003
  • Lin, M. Y. C., Do, B. R., Nguyen, T. T., & Cheng, J. M. S. (2022). Effects of personal innovativeness and perceived value of disclosure on data privacy concerns in proximity marketing: Self-control as a moderator. Journal of Research in Interactive Marketing, 16(2), 310–327. https://doi.org/10.1108/JRIM-04-2021-0112
  • Malhotra, N. K., Kim, S. S., & Agarwal, J. (2004). Internet users' information privacy concerns (IUIPC): The construct, the scale and a causal model. Information Systems Research, 15(4), 336–355. https://doi.org/10.1287/isre.1040.0032
  • Martin, K. D., & Murphy, P. E. (2017). The role of data privacy in marketing. Journal of the Academy of Marketing Science, 45, 135–155. https://doi.org/10.1007/s11747-016-0495-4
  • Muhammad, S. S., Dey, B. L., & Weerakkody, V. (2018). Analysis of factors that influence customers' willingness to leave big data digital footprints on social media: A systematic review of literature. Information Systems Frontiers, 20(3), 559–576. https://doi.org/10.1007/s10796-017-9802-y
  • Nunnally, J. C. (1978). Psychometric theory (2nd ed.). McGraw-Hill.
  • Pappas, N. (2016). Marketing strategies, perceived risks and consumer trust in online buying behaviour. Journal of Retailing and Consumer Services, 29, 92–103. https://doi.org/10.1016/j.jretconser.2015.11.007
  • Ponte, E. B., Carvajal-Trujillo, E., & Escobar-Rodríguez, T. (2015). Influence of trust and perceived value on the intention to purchase travel online: Integrating the effects of assurance on trust antecedents. Tourism Management, 47, 286–302. https://doi.org/10.1016/j.tourman.2014.10.009
  • Ponte, S., Mondliwa, P., & Roberts, S. (2021). Competition and power in global value chains. Competition and Change, 25(3–4), 328–349. https://doi.org/10.1177/1024529420975154
  • Preacher, K. J., & Hayes, A. F. (2008). Asymptotic and resampling strategies for assessing and comparing indirect effects in multiple mediator models. Behavior Research Methods, 40(3), 879–891. https://doi.org/10.3758/BRM.40.3.879
  • Quach, S., Thaichon, P., Martin, K. D., Weaven, S., Palmatier, R. W., & Patterson, P. (2022). Digital technologies: Tensions in privacy and data. Journal of the Academy of Marketing Science, 50, 1299–1323. https://doi.org/10.1007/s11747-022-00845-y
  • Steiger, J. H. (1990). Structural model evaluation and modification: An interval estimation approach. Multivariate Behavioral Research, 25(2), 173–180. https://doi.org/10.1207/s15327906mbr2502_4
  • Sweeney, J. C., & Soutar, G. N. (2001). Consumer perceived value: The development of a multiple item scale. Journal of Retailing, 77(2), 203–220. https://doi.org/10.1016/S0022-4359(01)00041-0
  • Tam, K. Y., & Ho, S. Y. (2006). Understanding the impact of web personalization on user information processing and decision outcomes. MIS Quarterly, 30(4), 865–890. https://doi.org/10.2307/25148757
  • Tirtayani, I. G. A., Wardana, I., Setiawan, P. Y., Widagda, I. G. N. J. A., Kustina, K. T., & Arlita, I. G. A. D. (2024). The privacy paradox on social media: Balancing data privacy concerns, perceived value and purchase intentions with habit moderation. In B. Alareeni & A. Hamdan (Eds.), Technology and business model innovation: Challenges and opportunities (Vol. 923, pp. 429–441). Springer. https://doi.org/10.1007/978-3-031-55911-2_34
  • Tucker, C. E. (2014). Social networks, personalized advertising and privacy controls. Journal of Marketing Research, 51(5), 546–562. https://doi.org/10.1509/jmr.10.0355
  • Wright, K. B. (2005). Researching internet-based populations: Advantages and disadvantages of online survey research, online questionnaire authoring software packages and web survey services. Journal of Computer-Mediated Communication, 10(3), Article JCMC1034. https://doi.org/10.1111/j.1083-6101.2005.tb00259.x
  • Wu, Y., & Huang, H. (2023). Influence of perceived value on consumers’ continuous purchase intention in live-streaming e-commerce—Mediated by consumer trust. Sustainability, 15(5), 1–19. https://doi.org/10.3390/su15054432
  • Xu, H., Luo, X., Carroll, J. M., & Rosson, M. B. (2011). The personalization privacy paradox: An exploratory study of decision making process for location-aware marketing. Decision Support Systems, 51(1), 42–52. https://doi.org/10.1016/j.dss.2010.11.017
  • Zeithaml, V. A. (1988). Consumer perceptions of price, quality and value: A means-end model and synthesis of evidence. Journal of Marketing, 52(3), 2–22. https://doi.org/10.1016/S0022-4359(01)00041-0
  • Zhang, J., Agarwal, R., & Lucas Jr., H. C. (2017). The value of IT-enabled retailer learning: Personalized marketing and firm performance. MIS Quarterly, 41(2), 389–412. https://doi.org/10.2307/41409964
Toplam 52 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Uluslararası İktisat (Diğer)
Bölüm Araştırma Makalesi
Yazarlar

Altuğ Ocak 0000-0002-8018-4158

Yayımlanma Tarihi 22 Temmuz 2025
Gönderilme Tarihi 10 Ocak 2025
Kabul Tarihi 24 Mart 2025
Yayımlandığı Sayı Yıl 2025 Cilt: 26 Sayı: 2

Kaynak Göster

APA Ocak, A. (2025). THE INFLUENCE OF PERSONALIZED MARKETING AND DATA PRIVACY CONCERNS ON CONSUMER BEHAVIOR: THE MEDIATING ROLE OF PERCEIVED VALUE. Doğuş Üniversitesi Dergisi, 26(2), 315-337. https://doi.org/10.31671/doujournal.1617271
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