شناسایی مؤلفه‌ها و ارائه مدل تبلیغات شخصی سازی شده

نوع مقاله : مقاله پژوهشی

نویسندگان

1 دانشجوی دکتری مدیریت; مدیریت رسانه ای، دانشکده مدیریت، دانشگاه آزاد اسلامی، واحد اصفهان (خوراسگان)، اصفهان، ایران

2 استادیار، دانشکده مدیریت، دانشگاه آزاد اسلامی، واحد اصفهان (خوراسگان)، اصفهان، ایران

چکیده

پژوهش حاضر با هدف شناسایی مؤلفه‌ها و ارائه مدل تبلیغات شخصی‌سازی شده به روش آمیخته انجام گرفت. در فاز کیفی، با استفاده از روش فراترکیب مبتنی بر مدل هفت مرحله‌ای سندلوسکی و باروسو ، منابع مرتبط، بین سال‌های 1399-1380 خورشیدی و 2000-2021 میلادی مورد مطالعه قرار گرفت و 42 منبع انتخاب شد .داده‌ها با استفاده از مدل استراوس و کوربین در سه مرحله کدگذاری باز، محوری و انتخابی مورد تجزیه و تحلیل قرار گرفت. نتیجه خروجی فاز کیفی کشف 137 مفهوم، 29 مقوله فرعی و 9 مقوله اصلی بود که در قالب مدل مفهومی ارائه شد. روش پژوهش در فاز کمی توصیفی - همبستگی مبتنی بر معادلات ساختاری و جامعه آماری شامل کلیه مشتریان دیجی‌کالا در سال 1398 بود که با استفاده از فرمول کوکران برای جامعه نامحدود، 348 نفر به روش نمونه گیری هدفمند وابسته به معیار انتخاب شدند. ابزار جمع‌آوری داده‌ها در فاز کمی، پرسشنامه محقق ساخته برگرفته از فاز کیفی با 137 گویه بود که پس از تأیید روایی (صوری، محتوایی و سازه) و تأیید پایایی آن (با استفاده از روش آلفای کرونباخ)، به روش معادلات ساختاری مورد تجزیه و تحلیل قرارگرفت. یافته‌های پژوهش نشان داد که اثرات عوامل زمینه‌ای معنادار نبوده و اثر عوامل مداخله‌گر بر پیامدهای تبلیغات شخصی‌سازی شده نیز معنادار نمی‌باشد. سودمندی ادراک‌ شده با ضریب تاثیر(0/601) و هزینه‌های ادراک شده با ضریب تاثیر(0/521) به ترتیب بیشترین تاثیر را بر راهبرد مدیریت بازار داشته و ضمن اینکه راهبرد مدیریت بازار با ضریب تاثیر(0/691) بیشترین تاثیر را بر پیامد نگرشی دارد.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Determining factors and representing a model for personalized advertising

نویسندگان [English]

  • Maryam Azizinia 1
  • Reza Ebrahimzadeh 2
  • Mehrdad Sadeghi 2
1 Ph.D. Student, Faculty of Management, Department of Management- Media Management, Isfahan (Khorasgan) Branch, Islamic Azad University, Isfahan, Iran.
2 Assistant Professor, Faculty of Management, Department of Cultural Management, Isfahan (Khorasgan) Branch, Islamic Azad University, Isfahan, Iran.
چکیده [English]

The present study was aimed at determining factors and representing a model for personalized advertising by the mixed method. In the qualitative phase, using the Meta-Synthesis method based on the seven-stage model of Sandelowski and Barroso, related sources between the years 1399-1399 AH and 2021-2000 AD were studied, and 42 references were selected. The data were analyzed using Strauss and Corbin model during three stages of open, axial, and selective coding. The Conclusion The output of the qualitative phase was the discovery of 137 concepts, 29 sub-categories, and 9 main categories presented in the conceptual model. The research method was descriptive-correlative based on structured equation modeling and the statistical population consisted of all of the customers of Digikala in the Year 1398 which used the Cochran formula for an unlimited community, 348 members were selected for criterion- targeted Sampling method. The data collection tool in the quantitative phase was a researcher-made questionnaire taken from the qualitative phase with 137 items. After confirming its validity (face, content, and construct) and reliability (Using Cronbach's alpha method), the structural equation method was analyzed. Findings showed that Perceived usefulness and perceived costs had the most significant impact on market management strategy, respectively. At the same time, a market management strategy has the most significant impact on attitude outcomes.

کلیدواژه‌ها [English]

  • Advertising
  • personalized
  • personalized advertising
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.‏ Doi:10.1016/j.jretai.2014.09.00
Ahmadi, M., sohrabi, S., tahzibi, S. (2020). The impact of advertising personalization and interaction on the advertising value and purchase intention at DJ Kala Company. Journal of Business Management, 12(47), 1-24. (in Persian) dor:20.1001.1.22520104.1399.12.47.1.0
Aiolfi, S., Bellini, S., & Pellegrini, D. (2021). Data-driven digital advertising: benefits and risks of online behavioral advertising. International Journal of Retail & Distribution Management, 49(7), 1089-1110. Doi: 10.1108/IJRDM-10-2020-0410
Al-Heali, A. N. (2021) The Impact of using celebrities in advertising on the purchasing behavior of consumers/Analytical Study about consumers opinions. Sample from Baghdad. Journal of University of Shanghai for Science and Technology. Volume 23(3). 333-351. DOI: 10.51201/Jusst12686
Ardiansyah, Y., Harrigan, P., Soutar, G. N., & Daly, T. M. (2018). Antecedents to consumer peer communication through social advertising: a self-disclosure theory perspective. Journal of Interactive Advertising, 18(1), 55-71. doi:10.1080/15252019.2018.1437854
Bang, H., & Wojdynski, B. W. (2016). Tracking users' visual attention and responses to personalized advertising based on task cognitive demand. Computers in Human Behavior, 55(Part B), 867–876. Doi:10.1016/j.chb.2015.10.025
Bang, H., Choi, D., Wojdynski, B. W., & Lee, Y. I. (2019). How the level of personalization affects the effectiveness of personalized ad messages: the moderating role of narcissism. International Journal of Advertising, 38(8), 1116-1138. Doi:10.1080/02650487.2019.1590069
Bleier, A., & Eisenbeiss, M. (2015). The importance of trust for personalized online advertising. Journal of Retailing, 91(3), 390-409. Doi:10.1016/j.jretai.2015.04.001
Brinson, N. H., & Eastin, M. S. (2016). Juxtaposing the persuasion knowledge model and privacy paradox: An experimental look at advertising personalization, public policy and public understanding. Cyberpsychology: Journal of Psychosocial Research on Cyberspace, 10(1), Article 7. Doi: 10.5817/CP2016-1-7
Campbell, C., Plangger, K., Sands, S., & Kietzmann, J. (2021). Preparing for an era of deepfakes and AI-generated ads: A framework for understanding responses to manipulated advertising. Journal of Advertising, 1-17. doi:10.1080/00913367.2021.1909515
Chandra, S., Verma, S., Lim, W. M., Kumar, S., & Donthu, N. (2022). Personalization in personalized marketing: Trends and ways forward. Psychology & Marketing. 39 (8), 1529-1562.doi: 10.1002/mar.21670
Chen, Q., Feng, Y., Liu, L., & Tian, X. (2019). Understanding consumers’ reactance of online personalized advertising: A new scheme of rational choice from a perspective of negative effects. International Journal of Information Management, 44, 53-64.‏ doi:10.1016/j.ijinfomgt.2018.09.001
Chkoniya, V. (2021). Challenges in decoding consumer behavior with data science. European Journal of Economics and Business Studies. Vol. 6 (3) doi: 10.26417/897ovg79t
Christian, J., Karissa, F., Handoyo, B., & Antonio, F. (2021). The Effect of Perceived Ads Personalization toward Online Impulse Buying Tendency with Mediating and Moderating Variables, Evidence from Indonesian Millennial E-Commerce Customers. KINERJA. Vol 25)1). Doi: 10.24002/kinerja.v25i1.4357
Cinar, N., & Ateş, S. (2022). Data Privacy in Digital Advertising: Towards a Post Third-Party Cookie Era. Çınar, N., & Ateş, S. (2022)." Data Privacy in Digital Advertising: Towards a Post Third-Party Cookie Era", in Filimowicz, M.(Ed.) Privacy: Algorithms and Society, Routledge. Doi:10.2139/ssrn.4041963
Daems, K., De Keyzer, F., De Pelsmacker, P., & Moons, I. (2019). Personalized and cued advertising aimed at children. International Journal of Advertising and Marketing to Children, 20(2), 138-151. https://doi.org/10.1108/YC-10-2018-0864.
Dahlgren, S., & Tabell, B. (2018). Personalized Advertising Online and its Difficulties with Customer Privacy. Master’s Thesis, Karlstad business school. Karlstad University.
De Keyzer, F., Dens, N., & De Pelsmacker, P. (2015). Is this for me? How consumers respond to personalized advertising on social network sites. Journal of Interactive Advertising, 15(2), 124-134. Doi:10.1080/15252019.2015.1082450
Deng, S., Tan, C. W., Wang, W., & Pan, Y. (2019). Smart generation system of personalized advertising copy and its application to advertising practice and research. Journal of Advertising, 48(4), 356-365. doi:10.1080/00913367.2019.1652121
Dwivedi, Y. K., Ismagilova, E., Hughes, D. L., Carlson, J., Filieri, R., Jacobson, J., ... & Wang, Y. (2021). Setting the future of digital and social media marketing research: Perspectives and research propositions. International Journal of Information Management, 59, 102168. Doi:10.1016/j.ijinfomgt.2020.102168
Estrada Jiménez, J. A. (2020). Privacy in online advertising platforms. Doctoral dissertation, department of telematics engineering, Universitat Politècnica de Catalunya.
G Martín, A., Fernández-Isabel, A., Martín de Diego, I., & Beltrán, M. (2021). A survey for user behavior analysis based on machine learning techniques: current models and applications. Applied Intelligence, 51(8), 6029-6055. doi:10.1007/s10489-020-02160-x
Gioti, H., Ponis, S. T., & Panayiotou, N. (2018). Social business intelligence: Review and research directions. Journal of Intelligence Studies in Business, 8(2). DOI:10.37380/jisib.v8i2.320
Gironda, J. (2014). Tailored vs. invasive advertising: An empirical examination of antecedents and outcomes of consumers' attitudes toward personalized advertising. Doctoral Dissertation, College of Business, Florida Atlantic University.
Gironda, J. T., & Korgaonkar, P. K. (2018). iSpy? Tailored versus invasive ads and consumers’ perceptions of personalized advertising. Electronic Commerce Research and Applications, 29, 64-77. Doi:10.1016/j.elerap.2018.03.007
Hasanpour Delavar, M., Valipour, A. (2020). The effect of emotional factors on customers’ behavioral responses to personalized Internet advertising by Mediating role of rational choice theory components. Journal of New Research Approaches in Management and Accounting. 4(41), 134-156. (in Persian)
Ho, V. T. (2021). Advertising avoidance: a literature review. Independent Journal of Management & Production, 12(1), 185-200. DOI:10.14807/ijmp.v12i1.1264
Hoffman, B. (2019). The role of advertising in shaping children’s preferences of consumption. Trakia Journal of Sciences, 17(2), 115-124. doi:10.15547/tjs.2019.02.004
Huang, Y. T. (2018). The female gaze: Content composition and slot position in personalized banner ads, and how they influence visual attention in online shoppers. Computers in Human Behavior, 82, 1-15. /Doi.org/10.1016/j.chb.2017.12.038
Kerr, G., & Richards, J. (2021). Redefining advertising in research and practice. International Journal of Advertising, 40(2), 175-198. doi:10.1080/02650487.2020.1769407
Kishen, R., Upadhyay, S., Jaimon, F., Suresh, S., Kozlova, N., Bozhuk, S., & Matchinov, V. A. (2021). PROSPECTS FOR ARTIFICIAL INTELLIGENCE IMPLEMENTATION TO DESIGN PERSONALIZED CUSTOMER ENGAGEMENT STRATEGIES. Journal of Legal, Ethical and Regulatory Issues, 24, 1-18.
Ladig, E. A. (2019). An examination of personalization in digital advertising. Doctoral dissertation, the Faculty of the Graduate School, University of Missouri-Columbia.
Lai, Z. (2021). Research on advertising core business reformation driven by artificial intelligence. In Journal of Physics: Conference Series, 1757(1), p. 012018. IOP Publishing. DOI:10.1088/1742-6596/1757/1/012018
Li, C., Liu, J., & Hong, C. (2019). The Effect of Preference Stability and Extremity on Personalized Advertising. Journalism & Mass Communication Quarterly, 96(2), 406–427. Doi: 10.1177/1077699018782203
Liu-Thompkins, Y. (2019). A decade of online advertising research: What we learned and what we need to know. Journal of advertising, 48(1), 1-13. Doi:10.1080/00913367.2018.1556138
Mahnič, M. (2020). New Solutions for Digital Advertising: Gen Y Playing Roles of Personas. Mednarodno inovativno poslovanje. Journal of Innovative Business and Management, 12(2), 85-95. Doi:10.32015/JIBM.2020.12.2.9.85-95
Majhi, A., & Chirputka, A. (2020). The Role of Information Technology in Revolutionising Marketer’s approach towards personalized advertisement. PalArch's Journal of Archaeology of Egypt/Egyptology, 17(6), 4430-4451.
Mehanović, D., & Durmić, N. (2022). Case Study Application of Business Intelligence in Digital Advertising. International Journal of E-Business Research (IJEBR), 18(1), 1-16. http://doi.org/10.4018/IJEBR.293294
Miia, A., & Dong, K. (2019). Avoiding Personalized Ads on Social Media: Understanding how YouTube users experience personalized advertising and what leads to ad avoidance in the context of personalization. Master Thesis, Jonkoping International Business School, Jonkoping University.
Morimoto, M. (2020). Privacy concerns about personalized advertising across multiple social media platforms in Japan: the relationship with information control and persuasion knowledge. International Journal of Advertising, 40(3), 431–451. Doi:10.1080/02650487.2020.1796322
Munir, H., Rana, R., & Bhatti, U. T. (2017). Factors affecting advertisement avoidance through mediating role of customer perceived value. International Journal of Research, 4(9), 961-975.
Nyheim, P., Xu, S., Zhang, L., & Mattila, A. S. (2015). Predictors of avoidance towards personalization of restaurant smartphone advertising. Journal of Hospitality and Tourism Technology. 6(2), 145–159. Doi: 10.1108/JHTT-07-2014-0026
O'Donnell, K., & Cramer, H. (2015). People's perceptions of personalized ads. In Proceedings of the 24th International Conference on World Wide Web .1293-1298.‏ Doi:10.1145/2740908.2742003
Patapau, M. (2020). The main differences between responses to personalized advertising among generations. Bachelor thesis, LAB University of Applied Sciences.
Rhee, C. E., & Choi, J. (2020). Effects of personalization and social role in voice shopping: An experimental study on product recommendation by a conversational voice agent. Computers in Human Behavior, 109,106359. doi:10.1016/j.chb.2020.106359
Rodgers, W., & Nguyen, T. (2022). Advertising benefits from ethical artificial intelligence algorithmic purchase decision pathways. Journal of Business Ethics, 1-19. DOI: 10.1007/s10551-022-05048-7
Seckelmann, S., Bargas-Avila, J., & Opwis, K. (2011). The impact of user reach of personalized advertisements on the click-through rate. Master's Thesis, Department of Psychology, Center for Cognitive Psychology and Methodology, University of Basel.
Segijn, C. M., & van Ooijen, I. (2020). Differences in consumer knowledge and perceptions of personalized advertising: Comparing online behavioural advertising and synced advertising. Journal of Marketing Communications, 1-20. Doi:10.1080/13527266.2020.1857297
Segijn, C. M., Kim, E., Sifaoui, A., & Boerman, S. C. (2021). When you realize that big brother is watching: How informing consumers affects synced advertising effectiveness. Journal of Marketing Communications, 1-22. DOI: 10.1080/13527266.2021.2020149
Semerádová, T., & Weinlich, P. (2019). Computer estimation of customer similarity with Facebook lookalikes: Advantages and disadvantages of hyper-targeting. IEEE Access, 7, 153365-153377. DOI: 10.1109/ACCESS.2019.2948401
Shanahan, T., Tran, T. P., & Taylor, E. C. (2019). Getting to know you: Social media personalization as a means of enhancing brand loyalty and perceived quality. Journal of Retailing and Consumer Services, 47, 57–65. Doi:10.1016/j.jretconser.2018.10.007
Sharma, N. (2021). Digital marketing as an effective tool for advertising in India: A critical review. PalArch's Journal of Archaeology of Egypt/Egyptology, 18(09), 37-49.
Sifaoui, A. (2021). “We Know What You See, so Here’s an Ad!” Online Behavioral Advertising and Surveillance on Social Media in an Era of Privacy Erosion (Doctoral dissertation, University of Minnesota).
Song, H., & Jiang, Y. (2017). Online Personalized Advertising Avoidance by Chinese Consumers: The Effect of Consumer Good Types. Noble International Journal of Business and Management Research, 1(6), 107-117.
Stiglbauer, B., & Kovacs, C. (2019). Need for Uniqueness Determines Reactions to Web-Based Personalized Advertising. Psychological Reports, 122(1), 246–267. https://doi.org/10.1177/0033294118756353
Strycharz, J., van Noort, G., Smit, E., & Helberger, N. (2019). Consumer view on personalized advertising: Overview of self-reported benefits and concerns. In: Bigne E., Rosengren S. In Advances in Advertising Research X. 53-66. Springer Gabler, Wiesbaden. A.‏ Doi: 10.1007/978-3-658-24878 9_5
Strycharz, J., van Noort, G., Smit, E., & Helberger, N. (2019). Protective behavior against personalized ads: Motivation to turn personalization off. Cyberpsychology: Journal of Psychosocial Research on Cyberspace, 13(2), B. Doi: 10.5817/CP2019-2-1
Taneo Zander, J. T. Z., & Mirkovic, A. M. (2019). Personalized Advertising: Examining the Consumer Attitudes of Generation Z towards Data Privacy and Personalization: A study of consumer attitudes towards the commercial usage of personal data. Bachelor thesis, Jonkoping International Business School, Jonkoping University.
Teeny, J. D., Siev, J. J., Briñol, P., & Petty, R. E. (2021). A review and conceptual framework for understanding personalized matching effects in persuasion. Journal of Consumer Psychology, 31(2), 382-414.
Tran, T. P. (2017). Personalized ads on Facebook: An effective marketing tool for online marketers. Journal of Retailing and Consumer Services, 39, 230-242. Doi: 10.1016/j.jretconser.2017.06.010
Tran, T. P., Lin, C. W., Baalbaki, S., & Guzmán, F. (2020). How personalized advertising affects equity of brands advertised on Facebook? A mediation mechanism. Journal of Business Research, 120, 1-15.A. Doi: 10.1016/j.jbusres.2020.06.027
Tran, T.P., van Solt, M. and Zemanek Jr, J.E. (2020), "How does personalization affect brand relationship in social commerce? A mediation perspective", Journal of Consumer Marketing, Vol. 37 No. 5, pp. 473-486.B. https://doi.org/10.1108/JCM-12-2017-2499
Tyrväinen, O., Karjaluoto, H., & Saarijärvi, H. (2020). Personalization and hedonic motivation in creating customer experiences and loyalty in omnichannel retail. Journal of Retailing and Consumer Services, 57, 102233. Doi: 10.1016/j.jretconser.2020.102233
Utami, T. R., & Agus, A. A. (201). The Role of Trust in Determining Consumers’ Intention to Click on Online Personalized Ads. In 2019 2nd International Conference of Computer and Informatics Engineering (IC2IE) (pp. 147-152). IEEE. doi:10.1109/ic2ie47452.2019.8940892
Van den Broeck, E., Poels, K., & Walrave, M. (2020). How do users evaluate personalized Facebook advertising? An analysis of consumer-and advertiser controlled factors. Qualitative Market Research: An International Journal. 23(2), 309–327. Doi: 10.1108/qmr-10-2018-0125
Walrave, M., Poels, K., Antheunis, M. L., Van den Broeck, E., & van Noort, G. (2018). Like or dislike? Adolescents’ responses to personalized social network site advertising. Journal of Marketing Communications, 24(6), 599-616. Doi:10.1080/13527266.2016.1182938
Wei, L., Kang, J., & Schmierbach, M. (2019). Memory at Play: Personalizing Online Advertisements Based on Consumers’ Autobiographical Memory. Journal of Promotion Management, 26(3), 322-349. Doi:10.1080/10496491.2019.1699632
Yarmohammadtooski, M. (2018). The influence of personalized ad relevance with the mediation role of privacy concerns on Telegram social network advertising (Case study: Malayer university students). Master Thesis, Department of Business Management, Malayer University. (in Persian)
Yu, J., & Cude, B. J. (2009). Possible disparities in consumers' perceptions toward personalized advertising caused by cultural differences: US and Korea. Journal of International Consumer Marketing, 21(4), 251-269. Doi: 10.1080/08961530802282166
Zafar, A. U., Shen, J., Shahzad, M., & Islam, T. (2021). Relation of impulsive urges and sustainable purchase decisions in the personalized environment of social media. Sustainable Production and Consumption, 25, 591-603.
Zeng, F., Ye, Q., Li, J., & Yang, Z. (2021). Does self-disclosure matter? A dynamic two-stage perspective for the personalization-privacy paradox. Journal of Business Research, 124, 667-675. Doi: 10.1016/j.jbusres.2020.02.006
Zhao, X., Gu, C., Zhang, H., Yang, X., Liu, X., Liu, H., & Tang, J. (2021). DEAR: Deep Reinforcement Learning for Online Advertising Impression in Recommender Systems. In Proceedings of the AAAI Conference on Artificial Intelligence 35 ( 1), 750-758.
Zhu, Y. Q., & Chang, J. H. (2016). The key role of relevance in personalized advertisement: Examining its impact on perceptions of privacy invasion, self-awareness, and continuous use intentions. Computers in Human Behavior, 65, 442-447. Doi: 10.1016/j.chb.2016.08.048
Zou, Y. Q., & Zhang, H. (2019). Consumers' and companies' attitudes to personalized advertising: a case study of Taobao. Bachelor thesis, Akademin för textil, teknik och ekonomi. University Borås. 
 
 
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