Derleme
BibTex RIS Kaynak Göster

PUPİLLOMETRİ KULLANILARAK BİLİNÇLİ VE BİLİNÇDIŞI TÜKETİCİ TEPKİLERİNİN PAZARLAMA AÇISINDAN DEĞERLENDİRİLMESİ: SİSTEMATİK BİR DERLEME

Yıl 2025, Cilt: 26 Sayı: 2, 412 - 436, 31.12.2025
https://doi.org/10.24889/ifede.1725774

Öz

Nöropazarlama araştırmaları, geleneksel öz-bildirim ve davranışsal ölçümlerin sınırlılıklarını aşmak amacıyla giderek daha fazla bilinçdışı tüketici süreçlerini yakalayabilen fizyolojik teknikleri içermeye yönelmiştir. Bu teknikler arasında, göz bebeği büyüklüğü (pupil dilation), duygusal uyarılma, bilişsel çaba ve motivasyonel katılımı değerlendirmek için değerli ancak yeterince kullanılmayan bir ölçüt olarak öne çıkmaktadır. Kuramsal vaatlerine rağmen, göz bebeği büyüklüğü, ana akım tüketici davranışı araştırmalarında halen odaklanma temelli göz takibi metriklerinin gölgesinde kalmaktadır. Belirtilen önceliklerle bu çalışma, pazarlama ve tüketici davranışı bağlamlarında göz bebeği büyüklüğü kullanan 30 ampirik çalışmayı sistematik olarak incelemektedir. TCCM çerçevesi kullanılarak, göz bebeği temelli metriklerin nasıl kuramsallaştırıldığı, uygulandığı ve yorumlandığı çeşitli pazarlama perspektiflerinden analiz edilmektedir. Bulgular, göz bebeği büyüklüğünün ağırlıklı olarak görsel dikkat, duygusal uyarılma,
bilişsel yük ve tercih oluşumuyla ilişkili olduğunu ortaya koymakta; tüketicilerin bilinçdışı tepkilerine dair sözel olmayan, gerçek zamanlı bir pencere sunduğunu göstermektedir. Ancak literatürde, ışık hassasiyeti, duygusal değer belirsizliği ve standartlaşma eksikliği gibi metodolojik sınırlılıklar devam etmektedir. Özetle, bu derleme, göz bebeği büyümesinin tüketici sinirbiliminde tanılayıcı bir araç olarak henüz tam olarak değerlendirilmemiş potansiyeline dikkat çekmekte ve gelecekteki araştırmalar için daha fazla çok modlu entegrasyon, ekolojik geçerlik ve kültürler arası incelemenin önemini ortaya koymaktadır. Odaklanma temelli metriklerin ötesine geçilmesinin, araştırmacılar ve uygulayıcılar için tüketici davranışının gizli bilişsel ve duygusal etkenlerini daha yakından inceleyebilmesine olanak tanıyacağı düşünülmektedir.

Etik Beyan

İkincil verilerle çalışılmış olup etik kurul onayı aranmamıştır.

Kaynakça

  • Ahmi, A., Elbardan, H., and Ali, R. H. R. M. (2019, January). Bibliometric analysis of published literature on industry 4.0. In 2019 International Conference on Electronics, Information, and Communication (ICEIC), 1-6. IEEE.
  • Alós-Ferrer, C., Jaudas, A., and Ritschel, A. (2021). Attentional shifts and preference reversals: An eye-tracking study. Judgment and Decision Making, 16(1), 57-93. https://doi.org/10.5167/uzh-198757
  • Beatty, J. (1982). Task-evoked pupillary responses, processing load, and the structure of processing resources. Psychological Bulletin, 91(2), 276–292. https://doi.org/10.1037/0033-2909.91.2.276
  • Biswas, P., Dutt, V., and Langdon, P. (2016). Comparing ocular parameters for cognitive load measurement in eye-gaze-controlled interfaces for automotive and desktop computing environments. International Journal of Human-Computer Interaction, 32(1), 23-38. https://doi.org/10.1080/10447318.2015.1084112
  • Bradley, M. M., Miccoli, L., Escrig, M. A., and Lang, P. J. (2008). The pupil as a measure of emotional arousal and autonomic activation. Psychophysiology, 45(4), 602–607. https://doi.org/10.1111/j.1469-8986.2008.00654.x
  • Cao, Y., Ding, Y., Proctor, R. W., Duffy, V. G., Liu, Y., and Zhang, X. (2021). Detecting users’ usage intentions for websites employing deep learning on eye-tracking data. Information Technology and Management, 22(4), 281-292. https://doi.org/10.1007/s10799-021-00336-6
  • Cardamone, E., Miceli, G. N., and Raimondo, M. A. (2025). Color inside and outside the lines: Evidence from eye‐tracking studies on conformity to and differentiation from category color codes. Psychology and Marketing, 42(1), 25–39. https://doi.org/10.1002/mar.22180
  • Cash, D. K., Pazos, L. A., and Russell, T. D. (2024). Interpersonal pupillometry: The pupil as an indicator of emotion and its utility as a social cue. In Modern pupillometry: cognition, neuroscience, and practical applications, 327-347. Cham: Springer International Publishing.
  • Chang, Y. H., Yep, R., and Wang, C. A. (2025). Pupil size correlates with heart rate, skin conductance, pulse wave amplitude, and respiration responses during emotional conflict and valence processing. Psychophysiology, 62(1), 1-22. https://doi.org/10.1111/psyp.14726
  • Colombatto, C., and Scholl, B. J. (2022). Unconscious pupillometry: An effect of “attentional contagion” in the absence of visual awareness. Journal of Experimental Psychology: General, 151(2), 302- 308. https://doi.org/10.1037/xge0000927
  • D'Ambrogio, S., Werksman, N., Platt, M. L., and Johnson, E. N. (2023). How celebrity status and gaze direction in ads drive visual attention to shape consumer decisions. Psychology and Marketing, 40(4), 723-734. https://doi.org/10.1002/mar.21772
  • De Bellis, N. (2009). Bibliometrics and citation analysis: From the Science Citation Index to cybermetrics. Scarecrow Press.
  • Desrochers, C., Léger, P. M., Fredette, M., Mirhoseini, S., and Sénécal, S. (2019). The arithmetic complexity of online grocery shopping: The moderating role of product pictures. Industrial Management and Data Systems, 119(6), 1206-1222. https://doi.org/10.1108/IMDS-04-2018-0151
  • Dobovšek, T., Bernik, Š., and Strle, G. (2022, June). Pupil dilation and heart rate as responses to ad exposure. In Proceedings of the MEi: CogSci Conference (Vol. 16, No. 1).
  • European Commission. (2016). Regulation (EU) 2016/679 (General Data Protection Regulation). Official Journal of the European Union.
  • Franzen, L., Cabugao, A., Grohmann, B., Elalouf, K., and Johnson, A. P. (2022). Individual pupil size changes as a robust indicator of cognitive familiarity differences. PloS one, 17(1), 1-22. https://doi.org/10.1371/journal.pone.0262753
  • García-Carrión, B., Del Barrio-García, S., Muñoz-Leiva, F., and Porcu, L. (2025). Exploring destination positioning and message congruence in tourism management: An eye-tracking and fMRI study. Tourism Management, 108-129. https://doi.org/10.1016/j.tourman.2024.105111
  • García-Carrión, B., Muñoz-Leiva, F., Del Barrio-García, S., and Porcu, L. (2024). The effect of online message congruence, destination-positioning, and emojis on users’ cognitive effort and affective evaluation. Journal of Destination Marketing and Management, 31, 101334. https://doi.org/10.1016/j.jdmm.2023.100842
  • Garfield, E. (2006). The history and meaning of the journal impact factor. JAMA, 295(1), 90–93. https://doi.org/10.1001/jama.295.1.90
  • Grujic, N., Polania, R., and Burdakov, D. (2024). Neurobehavioral meaning of pupil size. Neuron, 112(20), 3381-3395. https://doi.org/10.1016/j.neuron.2024.05.029
  • Guo, F., Ding, Y., Liu, W., Liu, C., and Zhang, X. (2016). Can eye-tracking data be measured to assess product design?: Visual attention mechanism should be considered. International Journal of Industrial Ergonomics, 53, 229-235. https://doi.org/10.1016/j.ergon.2015.12.001
  • Hershman, R., Milshtein, D., and Henik, A. (2023). The contribution of temporal analysis of pupillometry measurements to cognitive research. Psychological Research, 87(1), 28-42. https://doi.org/10.1007/s00426-022-01656-0.
  • Hess, E. H., and Polt, J. M. (1960). Pupil size as related to interest value of visual stimuli. Science, 132(3423), 349–350. https://doi.org/10.1126/science.132.3423.349
  • Hoeks, B., and Levelt, W. J. M. (1993). Pupillary dilation as a measure of attention: A quantitative system analysis. Behavior Research Methods, Instruments, and Computers, 25(1), 16–26. https://doi.org/10.3758/BF03204445
  • Holmqvist, K., Nyström, M., Andersson, R., Dewhurst, R., Jarodzka, H., and van de Weijer, J. (2011). Eye tracking: A comprehensive guide to methods and measures. Oxford University Press.
  • Hopstaken, J. F., van der Linden, D., Bakker, A. B., and Kompier, M. A. J. (2015). The window of my eyes: Task disengagement and mental fatigue covary with pupil dynamics. Biological Psychology, 110, 100–106. https://doi.org/10.1016/j.biopsycho.2015.06.013
  • Huseynov, F., Kassym, J., and Öztürk, L. (2019). Incorporating biometric data in models of consumer choice. Applied Economics, 51(57), 6076–6091. https://doi.org/10.1080/00036846.2018.1527460
  • Kahneman, D. (1973). Attention and effort. Prentice-Hall.
  • Kahneman, D., and Beatty, J. (1966). Pupil diameter and load on memory. Science, 154(3756), 1583–1585. https://doi.org/10.1126/science.154.3756.1583
  • King, A. S. (1972). Pupil size, eye direction, and message appeal: Some preliminary findings. Journal of Marketing, 36(3), 55–58. https://doi.org/10.1177/002224297203600310
  • Ko, E. S., Kim, J. N., Na, H. J., and Kim, S. T. (2024). Changes in pupil size according to the color of cosmetic packaging: Using eye-tracking techniques. Applied Sciences, 15(1), 73. 1-18. https://doi.org/10. 3390/app15010073
  • Kret, M. E., and Sjak-Shie, E. E. (2019). Preprocessing pupil size data: Guidelines and code. Behavior Research Methods, 51(3), 1336–1342. https://doi.org/10.3758/s13428-018-1075-y
  • Laeng, B., and Mathôt, S. (2024). Methodological Aspects of Pupillometry. In Modern pupillometry: Cognition, neuroscience, and practical applications, 375-400. Cham: Springer International Publishing.
  • Laeng, B., Sirois, S., and Gredebäck, G. (2012). Pupillometry: A window to the preconscious?. Perspectives on Psychological Science, 7(1), 18-27. https://doi.org/10.1177/1745691611427305
  • Laeng, B., Suegami, T., and Aminihajibashi, S. (2016). Wine labels: An eye-tracking and pupillometry study. International Journal of Wine Business Research, 28(4), 327-348. https://doi.org/10.1108/IJWBR-03-2016-0009
  • Larsen, E. P., Kolman, J. M., Rao, A. H., Masud, F. N., and Sasangohar, F. (2020). Ethical considerations when using a mobile eye tracker in a patient-facing area: Case study of an intensive care unit observational protocol. Ethics and Human Research, 42(6), 28–35. https://doi.org/10.1002/eahr.500068
  • Larson, M. D., Berry, P. D., May, J., Bjorksten, A., and Sessler, D. I. (2004). Latency of pupillary reflex dilation during general anesthesia. Journal of Applied Physiology, 97(2), 725-730. https://doi.org/10.1152/japplphysiol.00098.2004
  • Logan, I. T. (2019). Window to the soul: Eye tracking as the impetus for federal surveillance oversight? Penn State Law Review, 124(3), 779–811.
  • Lohse, G. L. (1997). Consumer eye movement patterns on Yellow Pages advertising. Journal of Advertising, 26(1), 61–73. https://doi.org/10.1080/00913367.1997.10673518
  • Luan, J., Xiao, J., Tang, P., and Li, M. (2022). Positive effects of negative reviews: An eye-tracking perspective. Internet Research, 32(1), 197-218. https://doi.org/10.1108/INTR-12-2019-0517
  • Ludwig, J., Jaudas, A., and Achtziger, A. (2024). The Zero Effect: An Eye‐Tracking Study of Affect and Motivation in Risky Choices. Journal of Behavioral Decision Making, 37(3), 1-19. DOI: https://doi.org/10.1002/bdm.2400
  • Lukovics, M., Prónay, S., and Nagy, B. (2024). Segmented trust assessment in autonomous vehicles via eye-tracking. Journal of Intelligent and Connected Vehicles, 7(2), 151-161. https://doi.org/10.26599/JICV.2023.9210037
  • Mathôt, S., and Vilotijević, A. (2023). Methods in cognitive pupillometry: Design, preprocessing, and statistical analysis. Behavior Research Methods, 55(6), 3055-3077. https://doi.org/10.3758/s13428-022-01957-7
  • McInnes, A. N., and Sung, B. (2025). A neglected consumer neuroscience technique: Pupillometry and its practical application to consumer research. International Journal of Research in Marketing, 42, 827-843. https://doi.org/10.1016/j.ijresmar.2024.11.005
  • Meritt, S. L., Keegan, A. P., and Mercer, P. W. (1994). Artifact management in pupillometry. Nursing Research, 43(1), 56-59.
  • Mishra, R. K., Gunasekaran, A., Papadopoulos, T., and Dubey, R. (2018). Supply chain performance measures and metrics: A bibliometric study. Benchmarking: An International Journal, 25(3), 932-963. https://doi.org/10.1108/BIJ-08-2017-0224
  • Modi, N., and Singh, J. (2023). Understanding online consumer behavior at e-commerce portals using eye-gaze tracking. International Journal of Human–Computer Interaction, 39(4), 721-742. https://doi.org/10.1080/10447318.2022.2047318
  • Mongeon, P., and Paul-Hus, A. (2016). The journal coverage of Web of Science and Scopus: A comparative analysis. Scientometrics, 106(1), 213–228. https://doi.org/10.1007/s11192-015-1765-5
  • Niknam, S., and Botev, J. (2024, January). Predicting cognitive failures in virtual reality using pupillometry. In 2024 IEEE International Conference on Artificial Intelligence and eXtended and Virtual Reality (AIxVR), 261-264. IEEE.
  • Onorati, F., Barbieri, R., Mauri, M., Russo, V., and Mainardi, L. (2013, July). Reconstruction and analysis of the pupil dilation signal: Application to a psychophysiological affective protocol. In 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 5-8. IEEE.
  • Orquin, J. L., and Loose, S. M. (2013). Attention and choice: A review on eye movements in decision making. Acta Psychologica, 144(1), 190–206. https://doi.org/10.1016/j.actpsy.2013.06.003
  • Paul, J. and Rosado-Serrano, A. (2019), “Gradual Internationalization vs Born-Global/International new venture models”, International Marketing Review, 830-858. https://doi.org/10.1108/IMR-10-2018-0280
  • Pengnate, S. (2019). Shocking secret you won’t believe! Emotional arousal in clickbait headlines: An eye-tracking analysis. Online Information Review, 43(7), 1136-1150. https://doi.org/10.1108/OIR-05-2018-0172
  • Pieters, R., and Wedel, M. (2004). Attention capture and transfer in advertising: Brand, pictorial, and text-size effects. Journal of Marketing, 68(2), 36-50. https://doi.org/10.1509/jmkg.68.2.36.27794
  • Plassmann, H., Venkatraman, V., Huettel, S., and Yoon, C. (2015). Consumer neuroscience: Applications, challenges, and possible solutions. Journal of Marketing Research, 52(4), 427–435. https://doi.org/10.1509/jmr.14.00
  • Preuschoff, K., ‘t Hart, B. M., and Einhäuser, W. (2011). Pupil dilation signals surprise: Evidence for noradrenaline’s role in decision making. Frontiers in Neuroscience, 5, 115. 1-12. https://doi.org/10.3389/fnins.2011.00115
  • Rahal, R. M., and Fiedler, S. (2019). Understanding cognitive and affective mechanisms in social psychology through eye-tracking. Journal of Experimental Social Psychology, 85. https://doi.org/10.1016/j.jesp.2019.103842
  • Ramsøy, T. Z., Jacobsen, C., Friis-Olivarius, M., Bagdziunaite, D., and Skov, M. (2017). Predictive value of body posture and pupil dilation in assessing consumer preference and choice. Journal of Neuroscience, Psychology, and Economics, 10(2-3), 95-110. https://doi.org/10.1037/npe0000073
  • Rosenfield, M. (2011). Computer vision syndrome: A review of ocular causes and potential treatments. Ophthalmic and Physiological Optics, 31(5), 502–515. https://doi.org/10.1111/j.1475-1313.2011.00834.x
  • Russell, C. A., Swasy, J. L., Russell, D. W., and Engel, L. (2017). Eye-tracking evidence that happy faces impair verbal message comprehension: The case of health warnings in direct-to-consumer pharmaceutical television commercials. International Journal of Advertising, 36(1), 82-106. https://doi.org/10.1080/02650487.2016.1196030
  • Segovia, M. S., Palma, M. A., and Nayga Jr, R. M. (2020). Can episodic future thinking affect food choices?. Journal of Economic Behavior and Organization, 177, 371-389. https://doi.org/10.1016/j.jebo.2020.06.019
  • Shaker, H., Sénécal, S., Grégoire, Y., and Taboubi, S. (2022). The effect of incidental prices in online display ads on consumer internal reference price. International Journal of Electronic Commerce, 26(3), 279-310. https://doi.org/10.1080/10864415.2022.2076195
  • Sheppard, A. L., and Wolffsohn, J. S. (2018). Digital eye strain: Prevalence, measurement and amelioration. BMJ Open Ophthalmology, 3(1), 1-10. https://doi.org/10.1136/bmjophth-2018-000146
  • Shi, S. W. (2022). Assortment levels, pupillary response, and product preference. Journal of Marketing Management, 38(17-18), 2035-2054. https://doi.org/10.1080/0267257X.2022.2078863
  • Siegle, G. J., Steinhauer, S. R., Stenger, V. A., Konecky, R., and Carter, C. S. (2003). Use of concurrent pupil dilation assessment to inform interpretation and analysis of fMRI data. NeuroImage, 20(1), 114-124. https://doi.org/10.1016/S1053-8119(03)00298-2
  • Singh, S., and Dhir, S. (2019). Structured review using TCCM: A study of international marketing research agenda. Journal of International Marketing, 27(3), 1-24. https://doi.org/10.1007/s12208-019-00233-3
  • Sirois, S., and Brisson, J. (2014). Pupillometry. Wiley interdisciplinary reviews: Cognitive Science, 5(6), 679-692. https://doi.org/10.1002/wcs.1323
  • Smidts, A., Hsu, M., Sanfey, A. G., Boksem, M. A. S., Ebstein, R. B., Huettel, S. A., and Yoon, C. (2014). Advancing consumer neuroscience. Marketing Letters, 25, 257-267. https://doi.org/10.1007/s11002-014-9306-1
  • Snyder, H. (2019). Literature reviews as a research strategy: An overview and guidelines. Journal of Business Research, 104, 333-339. https://doi.org/10.1016/j.jbusres.2019.07.039
  • Songa, G., Slabbinck, H., Vermeir, I., and Russo, V. (2019). How do implicit/explicit attitudes and emotional reactions to sustainable logo relate? A neurophysiological study. Food Quality and Preference, 71, 485-496. https://doi.org/10.1016/j.foodqual.2018.04.008
  • Souza, M. T. D., Oliveira, J. H. C. D., and Giraldi, J. D. M. E. (2020). Organic and sponsored ads: study on online purchase intent and visual behaviour. International Journal of Internet Marketing and Advertising, 14(3), 318-335. https://doi.org/10.1504/IJIMA.2020.108721
  • Steinhauer, S. R., Bradley, M. M., Siegle, G. J., Roecklein, K. A., and Dix, A. (2022). Publication guidelines and recommendations for pupillary measurement in psychophysiological studies. Psychophysiology, 59(4), 1-36. https://doi.org/10.1111/psyp.14035
  • Szymkowiak, A., Gaczek, P., and Padma, P. (2021). Impulse buying in hospitality: The role of content posted by social media influencers. Journal of Vacation Marketing, 27(4), 385-399. https://doi.org/10.1177/13567667211003216
  • Toma, F. M., Cepoi, C. O., Kubinschi, M. N., and Miyakoshi, M. (2023). Gazing through the bubble: An experimental investigation into financial risk-taking using eye-tracking. Financial Innovation, 9(1), 1- 28. https://doi.org/10.1186/s40854-022-00444-4
  • Tong, X., Chen, Y., Zhou, S., Yang, S., and Jiang, H. (2023). Do atmospheric cues matter in live streaming e-commerce? An eye-tracking investigation. Electronic Commerce Research and Applications, 62. https://doi.org/10.1016/j.elerap.2023.101334
  • Tranfield, D., Denyer, D., and Smart, P. (2003). Towards a methodology for developing evidence-informed management knowledge by means of systematic review. British Journal of Management, 14(3), 207-222. https://doi.org/10.1111/1467-8551.00375
  • Urai, A. E., Braun, A., and Donner, T. H. (2017). Pupil-linked arousal is driven by decision uncertainty and alters serial choice bias. Nature Communications, 8. 1-11. https://doi.org/10.1038/ncomms14637
  • Vallejo-De la Cueva, A., Aretxabala-Cortajarena, N., Quintano-Rodero, A., Rodriguez-Nuñez, C., Pelegrin-Gaspar, P. M., Gil-Garcia, Z. I., ... and Parraza-Diez, N. (2023). Pupillary dilation reflex and behavioural pain scale: Study of diagnostic test. Intensive and Critical Care Nursing, 74. 1-7. https://doi.org/10.1016/j.iccn.2022.103332
  • Valliappan, N., Dai, N., Steinberg, E., He, J., Rogers, K., Ramachandran, V., ... and Navalpakkam, V. (2020). Accelerating eye movement research via accurate and affordable smartphone eye tracking. Nature Communications, 11(1). 1-12. https://doi.org/10.1038/s41467-020-18360-5
  • van Eck, N. J., and Waltman, L. (2010). Software survey: VOSviewer, a computer program for bibliometric mapping. Scientometrics, 84(2), 523-538. https://doi.org/10.1007/s11192-009-0146-3
  • van Loon, A. M., Hermsen, R., and Naber, M. (2022). Predicting product preferences on retailers’ web shops through measurement of gaze and pupil size dynamics. Journal of Cognition, 5(1), 1-14. https://doi.org/10.5334/ joc.240
  • Wals, S. F., and Wichary, S. (2023). Under pressure: Cognitive effort during website-based task performance is associated with pupil size, visual exploration, and users’ intention to recommend. International Journal of Human–Computer Interaction, 39(18), 3504-3515. https://doi.org/10.1080/10447318.2022.2098576
  • Wedel, M., and Pieters, R. (2008). Eye tracking for visual marketing. Now Publishers Inc.
  • Winn, M. B., Wendt, D., Koelewijn, T., and Kuchinsky, S. E. (2018). Best practices and advice for using pupillometry to measure listening effort: An introduction for those who want to get started. Trends in Hearing, 22, 1-32. https://doi.org/10.1177/2331216518800869
  • Wook Chae, S., and Chang Lee, K. (2013). Exploring the effect of the human brand on consumers' decision quality in online shopping: An eye‐tracking approach. Online Information Review, 37(1), 83-100. https://doi.org/10.1108/14684521311311649
  • Zhou, C., Shi, Z., Huang, T., Zhao, H., and Kaner, J. (2023). Impact of swiping direction on the interaction performance of elderly-oriented smart home interface: EEG and eye-tracking evidence. Frontiers in Psychology, 14. 1-13. https://doi.org/10.3389/fpsyg.2023.1089769

EVALUATING CONSCIOUS AND UNCONSCIOUS CONSUMER RESPONSES IN MARKETING THROUGH PUPILLOMETRY: A SYSTEMATIC REVIEW

Yıl 2025, Cilt: 26 Sayı: 2, 412 - 436, 31.12.2025
https://doi.org/10.24889/ifede.1725774

Öz

Neuromarketing research has increasingly sought to transcend the limitations of traditional self-report and behavioral measures by incorporating physiological techniques that capture nonconscious consumer processes. Among these, pupil dilation has emerged as a valuable yet underutilized metric for assessing emotional arousal, cognitive effort, and motivational engagement. Despite its theoretical promise, pupil dilation remains secondary to fixation-based eye-tracking metrics in mainstream consumer behavior research. This study systematically reviews 30 empirical studies employing pupil dilation within marketing and consumer behavior contexts. Using the TCCM framework, we analyze how pupil-based metrics have been theorized, applied, and interpreted across diverse marketing settings. A bibliometric analysis complements the review, mapping the intellectual structure and thematic evolution of pupillometric consumer research. Findings reveal that pupil dilation is predominantly associated with visual attention, emotional arousal, cognitive load, and preference formation, offering a nonverbal, real-time window into consumers’ subconscious responses. However, methodological limitations such as luminance sensitivity, emotional valence ambiguity, and lack of standardization persist across the literature. This review highlights the untapped potential of pupil dilation as a diagnostic tool in consumer neuroscience and calls for greater multimodal integration, ecological validity, cross-cultural exploration, and methodological rigor in future research. By moving beyond fixation-based metrics, scholars and practitioners can better capture the hidden cognitive and affective drivers of consumer behavior.

Kaynakça

  • Ahmi, A., Elbardan, H., and Ali, R. H. R. M. (2019, January). Bibliometric analysis of published literature on industry 4.0. In 2019 International Conference on Electronics, Information, and Communication (ICEIC), 1-6. IEEE.
  • Alós-Ferrer, C., Jaudas, A., and Ritschel, A. (2021). Attentional shifts and preference reversals: An eye-tracking study. Judgment and Decision Making, 16(1), 57-93. https://doi.org/10.5167/uzh-198757
  • Beatty, J. (1982). Task-evoked pupillary responses, processing load, and the structure of processing resources. Psychological Bulletin, 91(2), 276–292. https://doi.org/10.1037/0033-2909.91.2.276
  • Biswas, P., Dutt, V., and Langdon, P. (2016). Comparing ocular parameters for cognitive load measurement in eye-gaze-controlled interfaces for automotive and desktop computing environments. International Journal of Human-Computer Interaction, 32(1), 23-38. https://doi.org/10.1080/10447318.2015.1084112
  • Bradley, M. M., Miccoli, L., Escrig, M. A., and Lang, P. J. (2008). The pupil as a measure of emotional arousal and autonomic activation. Psychophysiology, 45(4), 602–607. https://doi.org/10.1111/j.1469-8986.2008.00654.x
  • Cao, Y., Ding, Y., Proctor, R. W., Duffy, V. G., Liu, Y., and Zhang, X. (2021). Detecting users’ usage intentions for websites employing deep learning on eye-tracking data. Information Technology and Management, 22(4), 281-292. https://doi.org/10.1007/s10799-021-00336-6
  • Cardamone, E., Miceli, G. N., and Raimondo, M. A. (2025). Color inside and outside the lines: Evidence from eye‐tracking studies on conformity to and differentiation from category color codes. Psychology and Marketing, 42(1), 25–39. https://doi.org/10.1002/mar.22180
  • Cash, D. K., Pazos, L. A., and Russell, T. D. (2024). Interpersonal pupillometry: The pupil as an indicator of emotion and its utility as a social cue. In Modern pupillometry: cognition, neuroscience, and practical applications, 327-347. Cham: Springer International Publishing.
  • Chang, Y. H., Yep, R., and Wang, C. A. (2025). Pupil size correlates with heart rate, skin conductance, pulse wave amplitude, and respiration responses during emotional conflict and valence processing. Psychophysiology, 62(1), 1-22. https://doi.org/10.1111/psyp.14726
  • Colombatto, C., and Scholl, B. J. (2022). Unconscious pupillometry: An effect of “attentional contagion” in the absence of visual awareness. Journal of Experimental Psychology: General, 151(2), 302- 308. https://doi.org/10.1037/xge0000927
  • D'Ambrogio, S., Werksman, N., Platt, M. L., and Johnson, E. N. (2023). How celebrity status and gaze direction in ads drive visual attention to shape consumer decisions. Psychology and Marketing, 40(4), 723-734. https://doi.org/10.1002/mar.21772
  • De Bellis, N. (2009). Bibliometrics and citation analysis: From the Science Citation Index to cybermetrics. Scarecrow Press.
  • Desrochers, C., Léger, P. M., Fredette, M., Mirhoseini, S., and Sénécal, S. (2019). The arithmetic complexity of online grocery shopping: The moderating role of product pictures. Industrial Management and Data Systems, 119(6), 1206-1222. https://doi.org/10.1108/IMDS-04-2018-0151
  • Dobovšek, T., Bernik, Š., and Strle, G. (2022, June). Pupil dilation and heart rate as responses to ad exposure. In Proceedings of the MEi: CogSci Conference (Vol. 16, No. 1).
  • European Commission. (2016). Regulation (EU) 2016/679 (General Data Protection Regulation). Official Journal of the European Union.
  • Franzen, L., Cabugao, A., Grohmann, B., Elalouf, K., and Johnson, A. P. (2022). Individual pupil size changes as a robust indicator of cognitive familiarity differences. PloS one, 17(1), 1-22. https://doi.org/10.1371/journal.pone.0262753
  • García-Carrión, B., Del Barrio-García, S., Muñoz-Leiva, F., and Porcu, L. (2025). Exploring destination positioning and message congruence in tourism management: An eye-tracking and fMRI study. Tourism Management, 108-129. https://doi.org/10.1016/j.tourman.2024.105111
  • García-Carrión, B., Muñoz-Leiva, F., Del Barrio-García, S., and Porcu, L. (2024). The effect of online message congruence, destination-positioning, and emojis on users’ cognitive effort and affective evaluation. Journal of Destination Marketing and Management, 31, 101334. https://doi.org/10.1016/j.jdmm.2023.100842
  • Garfield, E. (2006). The history and meaning of the journal impact factor. JAMA, 295(1), 90–93. https://doi.org/10.1001/jama.295.1.90
  • Grujic, N., Polania, R., and Burdakov, D. (2024). Neurobehavioral meaning of pupil size. Neuron, 112(20), 3381-3395. https://doi.org/10.1016/j.neuron.2024.05.029
  • Guo, F., Ding, Y., Liu, W., Liu, C., and Zhang, X. (2016). Can eye-tracking data be measured to assess product design?: Visual attention mechanism should be considered. International Journal of Industrial Ergonomics, 53, 229-235. https://doi.org/10.1016/j.ergon.2015.12.001
  • Hershman, R., Milshtein, D., and Henik, A. (2023). The contribution of temporal analysis of pupillometry measurements to cognitive research. Psychological Research, 87(1), 28-42. https://doi.org/10.1007/s00426-022-01656-0.
  • Hess, E. H., and Polt, J. M. (1960). Pupil size as related to interest value of visual stimuli. Science, 132(3423), 349–350. https://doi.org/10.1126/science.132.3423.349
  • Hoeks, B., and Levelt, W. J. M. (1993). Pupillary dilation as a measure of attention: A quantitative system analysis. Behavior Research Methods, Instruments, and Computers, 25(1), 16–26. https://doi.org/10.3758/BF03204445
  • Holmqvist, K., Nyström, M., Andersson, R., Dewhurst, R., Jarodzka, H., and van de Weijer, J. (2011). Eye tracking: A comprehensive guide to methods and measures. Oxford University Press.
  • Hopstaken, J. F., van der Linden, D., Bakker, A. B., and Kompier, M. A. J. (2015). The window of my eyes: Task disengagement and mental fatigue covary with pupil dynamics. Biological Psychology, 110, 100–106. https://doi.org/10.1016/j.biopsycho.2015.06.013
  • Huseynov, F., Kassym, J., and Öztürk, L. (2019). Incorporating biometric data in models of consumer choice. Applied Economics, 51(57), 6076–6091. https://doi.org/10.1080/00036846.2018.1527460
  • Kahneman, D. (1973). Attention and effort. Prentice-Hall.
  • Kahneman, D., and Beatty, J. (1966). Pupil diameter and load on memory. Science, 154(3756), 1583–1585. https://doi.org/10.1126/science.154.3756.1583
  • King, A. S. (1972). Pupil size, eye direction, and message appeal: Some preliminary findings. Journal of Marketing, 36(3), 55–58. https://doi.org/10.1177/002224297203600310
  • Ko, E. S., Kim, J. N., Na, H. J., and Kim, S. T. (2024). Changes in pupil size according to the color of cosmetic packaging: Using eye-tracking techniques. Applied Sciences, 15(1), 73. 1-18. https://doi.org/10. 3390/app15010073
  • Kret, M. E., and Sjak-Shie, E. E. (2019). Preprocessing pupil size data: Guidelines and code. Behavior Research Methods, 51(3), 1336–1342. https://doi.org/10.3758/s13428-018-1075-y
  • Laeng, B., and Mathôt, S. (2024). Methodological Aspects of Pupillometry. In Modern pupillometry: Cognition, neuroscience, and practical applications, 375-400. Cham: Springer International Publishing.
  • Laeng, B., Sirois, S., and Gredebäck, G. (2012). Pupillometry: A window to the preconscious?. Perspectives on Psychological Science, 7(1), 18-27. https://doi.org/10.1177/1745691611427305
  • Laeng, B., Suegami, T., and Aminihajibashi, S. (2016). Wine labels: An eye-tracking and pupillometry study. International Journal of Wine Business Research, 28(4), 327-348. https://doi.org/10.1108/IJWBR-03-2016-0009
  • Larsen, E. P., Kolman, J. M., Rao, A. H., Masud, F. N., and Sasangohar, F. (2020). Ethical considerations when using a mobile eye tracker in a patient-facing area: Case study of an intensive care unit observational protocol. Ethics and Human Research, 42(6), 28–35. https://doi.org/10.1002/eahr.500068
  • Larson, M. D., Berry, P. D., May, J., Bjorksten, A., and Sessler, D. I. (2004). Latency of pupillary reflex dilation during general anesthesia. Journal of Applied Physiology, 97(2), 725-730. https://doi.org/10.1152/japplphysiol.00098.2004
  • Logan, I. T. (2019). Window to the soul: Eye tracking as the impetus for federal surveillance oversight? Penn State Law Review, 124(3), 779–811.
  • Lohse, G. L. (1997). Consumer eye movement patterns on Yellow Pages advertising. Journal of Advertising, 26(1), 61–73. https://doi.org/10.1080/00913367.1997.10673518
  • Luan, J., Xiao, J., Tang, P., and Li, M. (2022). Positive effects of negative reviews: An eye-tracking perspective. Internet Research, 32(1), 197-218. https://doi.org/10.1108/INTR-12-2019-0517
  • Ludwig, J., Jaudas, A., and Achtziger, A. (2024). The Zero Effect: An Eye‐Tracking Study of Affect and Motivation in Risky Choices. Journal of Behavioral Decision Making, 37(3), 1-19. DOI: https://doi.org/10.1002/bdm.2400
  • Lukovics, M., Prónay, S., and Nagy, B. (2024). Segmented trust assessment in autonomous vehicles via eye-tracking. Journal of Intelligent and Connected Vehicles, 7(2), 151-161. https://doi.org/10.26599/JICV.2023.9210037
  • Mathôt, S., and Vilotijević, A. (2023). Methods in cognitive pupillometry: Design, preprocessing, and statistical analysis. Behavior Research Methods, 55(6), 3055-3077. https://doi.org/10.3758/s13428-022-01957-7
  • McInnes, A. N., and Sung, B. (2025). A neglected consumer neuroscience technique: Pupillometry and its practical application to consumer research. International Journal of Research in Marketing, 42, 827-843. https://doi.org/10.1016/j.ijresmar.2024.11.005
  • Meritt, S. L., Keegan, A. P., and Mercer, P. W. (1994). Artifact management in pupillometry. Nursing Research, 43(1), 56-59.
  • Mishra, R. K., Gunasekaran, A., Papadopoulos, T., and Dubey, R. (2018). Supply chain performance measures and metrics: A bibliometric study. Benchmarking: An International Journal, 25(3), 932-963. https://doi.org/10.1108/BIJ-08-2017-0224
  • Modi, N., and Singh, J. (2023). Understanding online consumer behavior at e-commerce portals using eye-gaze tracking. International Journal of Human–Computer Interaction, 39(4), 721-742. https://doi.org/10.1080/10447318.2022.2047318
  • Mongeon, P., and Paul-Hus, A. (2016). The journal coverage of Web of Science and Scopus: A comparative analysis. Scientometrics, 106(1), 213–228. https://doi.org/10.1007/s11192-015-1765-5
  • Niknam, S., and Botev, J. (2024, January). Predicting cognitive failures in virtual reality using pupillometry. In 2024 IEEE International Conference on Artificial Intelligence and eXtended and Virtual Reality (AIxVR), 261-264. IEEE.
  • Onorati, F., Barbieri, R., Mauri, M., Russo, V., and Mainardi, L. (2013, July). Reconstruction and analysis of the pupil dilation signal: Application to a psychophysiological affective protocol. In 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 5-8. IEEE.
  • Orquin, J. L., and Loose, S. M. (2013). Attention and choice: A review on eye movements in decision making. Acta Psychologica, 144(1), 190–206. https://doi.org/10.1016/j.actpsy.2013.06.003
  • Paul, J. and Rosado-Serrano, A. (2019), “Gradual Internationalization vs Born-Global/International new venture models”, International Marketing Review, 830-858. https://doi.org/10.1108/IMR-10-2018-0280
  • Pengnate, S. (2019). Shocking secret you won’t believe! Emotional arousal in clickbait headlines: An eye-tracking analysis. Online Information Review, 43(7), 1136-1150. https://doi.org/10.1108/OIR-05-2018-0172
  • Pieters, R., and Wedel, M. (2004). Attention capture and transfer in advertising: Brand, pictorial, and text-size effects. Journal of Marketing, 68(2), 36-50. https://doi.org/10.1509/jmkg.68.2.36.27794
  • Plassmann, H., Venkatraman, V., Huettel, S., and Yoon, C. (2015). Consumer neuroscience: Applications, challenges, and possible solutions. Journal of Marketing Research, 52(4), 427–435. https://doi.org/10.1509/jmr.14.00
  • Preuschoff, K., ‘t Hart, B. M., and Einhäuser, W. (2011). Pupil dilation signals surprise: Evidence for noradrenaline’s role in decision making. Frontiers in Neuroscience, 5, 115. 1-12. https://doi.org/10.3389/fnins.2011.00115
  • Rahal, R. M., and Fiedler, S. (2019). Understanding cognitive and affective mechanisms in social psychology through eye-tracking. Journal of Experimental Social Psychology, 85. https://doi.org/10.1016/j.jesp.2019.103842
  • Ramsøy, T. Z., Jacobsen, C., Friis-Olivarius, M., Bagdziunaite, D., and Skov, M. (2017). Predictive value of body posture and pupil dilation in assessing consumer preference and choice. Journal of Neuroscience, Psychology, and Economics, 10(2-3), 95-110. https://doi.org/10.1037/npe0000073
  • Rosenfield, M. (2011). Computer vision syndrome: A review of ocular causes and potential treatments. Ophthalmic and Physiological Optics, 31(5), 502–515. https://doi.org/10.1111/j.1475-1313.2011.00834.x
  • Russell, C. A., Swasy, J. L., Russell, D. W., and Engel, L. (2017). Eye-tracking evidence that happy faces impair verbal message comprehension: The case of health warnings in direct-to-consumer pharmaceutical television commercials. International Journal of Advertising, 36(1), 82-106. https://doi.org/10.1080/02650487.2016.1196030
  • Segovia, M. S., Palma, M. A., and Nayga Jr, R. M. (2020). Can episodic future thinking affect food choices?. Journal of Economic Behavior and Organization, 177, 371-389. https://doi.org/10.1016/j.jebo.2020.06.019
  • Shaker, H., Sénécal, S., Grégoire, Y., and Taboubi, S. (2022). The effect of incidental prices in online display ads on consumer internal reference price. International Journal of Electronic Commerce, 26(3), 279-310. https://doi.org/10.1080/10864415.2022.2076195
  • Sheppard, A. L., and Wolffsohn, J. S. (2018). Digital eye strain: Prevalence, measurement and amelioration. BMJ Open Ophthalmology, 3(1), 1-10. https://doi.org/10.1136/bmjophth-2018-000146
  • Shi, S. W. (2022). Assortment levels, pupillary response, and product preference. Journal of Marketing Management, 38(17-18), 2035-2054. https://doi.org/10.1080/0267257X.2022.2078863
  • Siegle, G. J., Steinhauer, S. R., Stenger, V. A., Konecky, R., and Carter, C. S. (2003). Use of concurrent pupil dilation assessment to inform interpretation and analysis of fMRI data. NeuroImage, 20(1), 114-124. https://doi.org/10.1016/S1053-8119(03)00298-2
  • Singh, S., and Dhir, S. (2019). Structured review using TCCM: A study of international marketing research agenda. Journal of International Marketing, 27(3), 1-24. https://doi.org/10.1007/s12208-019-00233-3
  • Sirois, S., and Brisson, J. (2014). Pupillometry. Wiley interdisciplinary reviews: Cognitive Science, 5(6), 679-692. https://doi.org/10.1002/wcs.1323
  • Smidts, A., Hsu, M., Sanfey, A. G., Boksem, M. A. S., Ebstein, R. B., Huettel, S. A., and Yoon, C. (2014). Advancing consumer neuroscience. Marketing Letters, 25, 257-267. https://doi.org/10.1007/s11002-014-9306-1
  • Snyder, H. (2019). Literature reviews as a research strategy: An overview and guidelines. Journal of Business Research, 104, 333-339. https://doi.org/10.1016/j.jbusres.2019.07.039
  • Songa, G., Slabbinck, H., Vermeir, I., and Russo, V. (2019). How do implicit/explicit attitudes and emotional reactions to sustainable logo relate? A neurophysiological study. Food Quality and Preference, 71, 485-496. https://doi.org/10.1016/j.foodqual.2018.04.008
  • Souza, M. T. D., Oliveira, J. H. C. D., and Giraldi, J. D. M. E. (2020). Organic and sponsored ads: study on online purchase intent and visual behaviour. International Journal of Internet Marketing and Advertising, 14(3), 318-335. https://doi.org/10.1504/IJIMA.2020.108721
  • Steinhauer, S. R., Bradley, M. M., Siegle, G. J., Roecklein, K. A., and Dix, A. (2022). Publication guidelines and recommendations for pupillary measurement in psychophysiological studies. Psychophysiology, 59(4), 1-36. https://doi.org/10.1111/psyp.14035
  • Szymkowiak, A., Gaczek, P., and Padma, P. (2021). Impulse buying in hospitality: The role of content posted by social media influencers. Journal of Vacation Marketing, 27(4), 385-399. https://doi.org/10.1177/13567667211003216
  • Toma, F. M., Cepoi, C. O., Kubinschi, M. N., and Miyakoshi, M. (2023). Gazing through the bubble: An experimental investigation into financial risk-taking using eye-tracking. Financial Innovation, 9(1), 1- 28. https://doi.org/10.1186/s40854-022-00444-4
  • Tong, X., Chen, Y., Zhou, S., Yang, S., and Jiang, H. (2023). Do atmospheric cues matter in live streaming e-commerce? An eye-tracking investigation. Electronic Commerce Research and Applications, 62. https://doi.org/10.1016/j.elerap.2023.101334
  • Tranfield, D., Denyer, D., and Smart, P. (2003). Towards a methodology for developing evidence-informed management knowledge by means of systematic review. British Journal of Management, 14(3), 207-222. https://doi.org/10.1111/1467-8551.00375
  • Urai, A. E., Braun, A., and Donner, T. H. (2017). Pupil-linked arousal is driven by decision uncertainty and alters serial choice bias. Nature Communications, 8. 1-11. https://doi.org/10.1038/ncomms14637
  • Vallejo-De la Cueva, A., Aretxabala-Cortajarena, N., Quintano-Rodero, A., Rodriguez-Nuñez, C., Pelegrin-Gaspar, P. M., Gil-Garcia, Z. I., ... and Parraza-Diez, N. (2023). Pupillary dilation reflex and behavioural pain scale: Study of diagnostic test. Intensive and Critical Care Nursing, 74. 1-7. https://doi.org/10.1016/j.iccn.2022.103332
  • Valliappan, N., Dai, N., Steinberg, E., He, J., Rogers, K., Ramachandran, V., ... and Navalpakkam, V. (2020). Accelerating eye movement research via accurate and affordable smartphone eye tracking. Nature Communications, 11(1). 1-12. https://doi.org/10.1038/s41467-020-18360-5
  • van Eck, N. J., and Waltman, L. (2010). Software survey: VOSviewer, a computer program for bibliometric mapping. Scientometrics, 84(2), 523-538. https://doi.org/10.1007/s11192-009-0146-3
  • van Loon, A. M., Hermsen, R., and Naber, M. (2022). Predicting product preferences on retailers’ web shops through measurement of gaze and pupil size dynamics. Journal of Cognition, 5(1), 1-14. https://doi.org/10.5334/ joc.240
  • Wals, S. F., and Wichary, S. (2023). Under pressure: Cognitive effort during website-based task performance is associated with pupil size, visual exploration, and users’ intention to recommend. International Journal of Human–Computer Interaction, 39(18), 3504-3515. https://doi.org/10.1080/10447318.2022.2098576
  • Wedel, M., and Pieters, R. (2008). Eye tracking for visual marketing. Now Publishers Inc.
  • Winn, M. B., Wendt, D., Koelewijn, T., and Kuchinsky, S. E. (2018). Best practices and advice for using pupillometry to measure listening effort: An introduction for those who want to get started. Trends in Hearing, 22, 1-32. https://doi.org/10.1177/2331216518800869
  • Wook Chae, S., and Chang Lee, K. (2013). Exploring the effect of the human brand on consumers' decision quality in online shopping: An eye‐tracking approach. Online Information Review, 37(1), 83-100. https://doi.org/10.1108/14684521311311649
  • Zhou, C., Shi, Z., Huang, T., Zhao, H., and Kaner, J. (2023). Impact of swiping direction on the interaction performance of elderly-oriented smart home interface: EEG and eye-tracking evidence. Frontiers in Psychology, 14. 1-13. https://doi.org/10.3389/fpsyg.2023.1089769
Toplam 86 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Pazarlama Araştırma Metodolojisi
Bölüm Derleme
Yazarlar

Nihan Tomris Küçün 0000-0001-5548-6093

Gönderilme Tarihi 23 Haziran 2025
Kabul Tarihi 5 Eylül 2025
Yayımlanma Tarihi 31 Aralık 2025
Yayımlandığı Sayı Yıl 2025 Cilt: 26 Sayı: 2

Kaynak Göster

APA Tomris Küçün, N. (2025). EVALUATING CONSCIOUS AND UNCONSCIOUS CONSUMER RESPONSES IN MARKETING THROUGH PUPILLOMETRY: A SYSTEMATIC REVIEW. Dokuz Eylül Üniversitesi İşletme Fakültesi Dergisi, 26(2), 412-436. https://doi.org/10.24889/ifede.1725774
AMA Tomris Küçün N. EVALUATING CONSCIOUS AND UNCONSCIOUS CONSUMER RESPONSES IN MARKETING THROUGH PUPILLOMETRY: A SYSTEMATIC REVIEW. Dokuz Eylül Üniversitesi İşletme Fakültesi Dergisi. Aralık 2025;26(2):412-436. doi:10.24889/ifede.1725774
Chicago Tomris Küçün, Nihan. “EVALUATING CONSCIOUS AND UNCONSCIOUS CONSUMER RESPONSES IN MARKETING THROUGH PUPILLOMETRY: A SYSTEMATIC REVIEW”. Dokuz Eylül Üniversitesi İşletme Fakültesi Dergisi 26, sy. 2 (Aralık 2025): 412-36. https://doi.org/10.24889/ifede.1725774.
EndNote Tomris Küçün N (01 Aralık 2025) EVALUATING CONSCIOUS AND UNCONSCIOUS CONSUMER RESPONSES IN MARKETING THROUGH PUPILLOMETRY: A SYSTEMATIC REVIEW. Dokuz Eylül Üniversitesi İşletme Fakültesi Dergisi 26 2 412–436.
IEEE N. Tomris Küçün, “EVALUATING CONSCIOUS AND UNCONSCIOUS CONSUMER RESPONSES IN MARKETING THROUGH PUPILLOMETRY: A SYSTEMATIC REVIEW”, Dokuz Eylül Üniversitesi İşletme Fakültesi Dergisi, c. 26, sy. 2, ss. 412–436, 2025, doi: 10.24889/ifede.1725774.
ISNAD Tomris Küçün, Nihan. “EVALUATING CONSCIOUS AND UNCONSCIOUS CONSUMER RESPONSES IN MARKETING THROUGH PUPILLOMETRY: A SYSTEMATIC REVIEW”. Dokuz Eylül Üniversitesi İşletme Fakültesi Dergisi 26/2 (Aralık2025), 412-436. https://doi.org/10.24889/ifede.1725774.
JAMA Tomris Küçün N. EVALUATING CONSCIOUS AND UNCONSCIOUS CONSUMER RESPONSES IN MARKETING THROUGH PUPILLOMETRY: A SYSTEMATIC REVIEW. Dokuz Eylül Üniversitesi İşletme Fakültesi Dergisi. 2025;26:412–436.
MLA Tomris Küçün, Nihan. “EVALUATING CONSCIOUS AND UNCONSCIOUS CONSUMER RESPONSES IN MARKETING THROUGH PUPILLOMETRY: A SYSTEMATIC REVIEW”. Dokuz Eylül Üniversitesi İşletme Fakültesi Dergisi, c. 26, sy. 2, 2025, ss. 412-36, doi:10.24889/ifede.1725774.
Vancouver Tomris Küçün N. EVALUATING CONSCIOUS AND UNCONSCIOUS CONSUMER RESPONSES IN MARKETING THROUGH PUPILLOMETRY: A SYSTEMATIC REVIEW. Dokuz Eylül Üniversitesi İşletme Fakültesi Dergisi. 2025;26(2):412-36.
Dokuz Eylül Üniversitesi İşletme Fakültesi Dergisi
TR-DİZİN, EBSCO ve SOBIAD tarafından taranmaktadır.

Dokuz Eylül Üniversitesi Yayınevi Web Sitesi

Dergi İletişim Bilgileri Sayfası