Consumer Behaviour to Be Considered in Advertising: A Systematic Analysis and Future Agenda
Abstract
:1. Introduction
- Provides a profound evaluation of the current advertising research that has been used to investigate unconscious and subconscious consumer behaviour, such as emotional dimensions, perceptions, reward processes, and approach/withdrawal motivation toward advertising.
- Provides an overview of the current neurophysiological and physiological tools that were used in advertising within the neuromarketing context between 2009 and 2020.
2. Materials and Methods
- Methods: neuroimaging and physiological tools;
- Publication year: January 2009 to December 2020;
- Language: English;
- Document type: original articles (chapters of books, articles from conferences, reviews, and proceedings books were excluded).
3. Results
3.1. Growth of the Publication
3.2. Topics of Interest and Thematic Analysis
3.2.1. Neuroimaging and Physiological Tools Used in Advertising
3.2.2. Brain Processes to Be Considered in Advertising
Emotion and Feelings
Motivation
Reward Processing
Attention
Perception
Memory
4. Discussion
5. Conclusions and Implications
6. Limitations and Future Directions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
- Carrington, M.J.; Neville, B.A.; Whitwell, G.J. Lost in translation: Exploring the ethical consumer intention–behavior gap. J. Bus. Res. 2014, 67, 2759–2767. [Google Scholar] [CrossRef]
- Alsharif, A.H.; Salleh, N.Z.M.; Baharun, R.; Effandi, Y.M. Consumer behaviour through neuromarketing approach. J. Contemp. Issues Bus. Gov. 2021, 22, 344–354. [Google Scholar] [CrossRef]
- Harris, J.; Ciorciari, J.; Gountas, J. Consumer neuroscience for marketing researchers. J. Consum. Behav. 2018, 17, 239–252. [Google Scholar] [CrossRef]
- Alsharif, A.H.; Salleh, N.Z.M.; Baharun, R. Research trends of neuromarketing: A bibliometric analysis. J. Theor. Appl. Inf. Technol. 2020, 98, 2948–2962. [Google Scholar]
- Smidts, A. Kijken in Het Brein: Over de Mogelijkheden van Neuromarketing; Erasmus Research Institute of Management: Rotterdam, The Netherlands, 2002. [Google Scholar]
- Javor, A.; Koller, M.; Lee, N.; Chamberlain, L.; Ransmayr, G. Neuromarketing and consumer neuroscience: Contributions to neurology. BMC Neurol. 2013, 13, 13. [Google Scholar] [CrossRef] [Green Version]
- Fortunato, V.C.R.; Giraldi, J.D.M.E.; Oliveira, J.H.C.D. A review of studies on neuromarketing: Practical results, techniques, contributions and limitations. J. Manag. Res. 2014, 6, 201–221. [Google Scholar] [CrossRef] [Green Version]
- Levallois, C.; Clithero, J.A.; Wouters, P.; Smidts, A.; Huettel, S.A. Translating upwards: Linking the neural and social sciences via neuroeconomics. Nat. Rev. Neurosci. 2012, 13, 789–797. [Google Scholar] [CrossRef]
- Bočková, K.; Škrabánková, J.; Hanák, M. Theory and practice of neuromarketing: Analyzing human behavior in relation to markets. Emerg. Sci. J. 2021, 5, 44–56. [Google Scholar] [CrossRef]
- Alsharif, A.H.; Salleh, N.Z.M.; Baharun, R.; Alharthi, R.H.E. Neuromarketing research in the last five years: A bibliometric analysis. Cogent Bus. Manag. 2021, 8, 1978620. [Google Scholar] [CrossRef]
- Alsharif, A.H.; Salleh, N.Z.M.; Baharun, R.; Abuhassna, H.; Alharthi, R.H.E. A global research trends of neuromarketing: 2015–2020. Rev. Comun. 2022, 21, 15–32. [Google Scholar] [CrossRef]
- To, A.T.; Tran, T.S.; Nguyen, K.O.; Thai, K.P. Applying Conflict Management Styles to Resolve Task Conflict and Enhance Team Innovation. Emerg. Sci. J. 2021, 5, 667–677. [Google Scholar] [CrossRef]
- Ramsoy, T.Z. Introduction to Neuromarketing & Consumer Neuroscience; Neurons Inc.: Rørvig, Denmark, 2015. [Google Scholar]
- Izhikevich, E.M. Simple model of spiking neurons. IEEE Trans. Neural Netw. 2003, 14, 1569–1572. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Alsharif, A.H.; Salleh, N.Z.M.; Baharun, R. Neuromarketing: The popularity of the brain-imaging and physiological tools. Neurosci. Res. Notes 2021, 3, 13–22. [Google Scholar] [CrossRef]
- Dimpfel, W. Neuromarketing: Neurocode-tracking in combination with eye-tracking for quantitative objective assessment of TV commercials. J. Behav. Brain Sci. 2015, 5, 137. [Google Scholar] [CrossRef] [Green Version]
- Alsharif, A.H.; Salleh, N.Z.M.; Baharun, R. Neuromarketing: Marketing research in the new millennium. Neurosci. Res. Notes 2021, 4, 27–35. [Google Scholar] [CrossRef]
- Alsharif, A.H.; Salleh, N.Z.M.; Ahmad, W.A.b.W.; Khraiwish, A. Biomedical Technology in Studying Consumers’ Subconscious Behavior. Int. J. Online Biomed. Eng. 2022, 18, 98–114. [Google Scholar] [CrossRef]
- McClure, S.M.; Li, J.; Tomlin, D.; Cypert, K.S.; Montague, L.M.; Montague, P.R. Neural correlates of behavioral preference for culturally familiar drinks. Neuron 2004, 44, 379–387. [Google Scholar] [CrossRef] [Green Version]
- Strozzi, F.; Colicchia, C.; Creazza, A.; Noè, C. Literature review on the ‘Smart Factory’concept using bibliometric tools. Int. J. Prod. Res. 2017, 55, 6572–6591. [Google Scholar] [CrossRef]
- Moher, D.; Shamseer, L.; Clarke, M.; Ghersi, D.; Liberati, A.; Petticrew, M.; Shekelle, P.; Stewart, L.A. Preferred reporting items for systematic review and meta-analysis protocols (PRISMA-P) 2015 statement. Syst. Rev. 2015, 4, 1. [Google Scholar] [CrossRef] [Green Version]
- Abuhassna, H.; Awae, F.; Bayoumi, K.; Alzitawi, D.U.; Alsharif, A.H.; Yahaya, N. Understanding Online Learning Readiness among University Students: A Bibliometric Analysis. iJIM 2022, 16, 81. [Google Scholar] [CrossRef]
- Alsharif, A.H.; Salleh, N.Z.M.; Linares, P.; Abbas, A.F.; Ali, J. Current Trends in the Application of EEG in Neuromarketing: A Bibliometric Analysis. Sci. Ann. Econ. Bus. 2022, 69, 393–415. [Google Scholar] [CrossRef]
- Ali, J.; Jusoh, A.; Idris, N.; Abbas, A.F.; Alsharif, A.H. Everything is Going Electronic, so do Services and Service Quality: Bibliometric Analysis of E-Services and E-Service Quality. Int. J. Interact. Mob. Technol. 2021, 15, 148–166. [Google Scholar] [CrossRef]
- Ali, J.; Jusoh, A.; Idris, N.; Abbas, A.F.; Alsharif, A.H. Nine Years of Mobile Healthcare Research: A Bibliometric Analysis. Int. J. Online Biomed. Eng. 2021, 17, 144–159. [Google Scholar] [CrossRef]
- Saha, V.; Mani, V.; Goyal, P. Emerging trends in the literature of value co-creation: A bibliometric analysis. Benchmarking Int. J. 2020, 27, 981–1002. [Google Scholar] [CrossRef]
- Morris, J.D.; Klahr, N.J.; Shen, F.; Villegas, J.; Wright, P.; He, G.J.; Li, Y.J. Mapping a multidimensional emotion in response to television commercials. Hum. Brain Mapp. 2009, 30, 789–796. [Google Scholar] [CrossRef]
- Venkatraman, V.; Dimoka, A.; Pavlou, P.A.; Vo, K.; Hampton, W.; Bollinger, B.; Hershfield, H.E.; Ishihara, M.; Winer, R.S. Predicting advertising success beyond traditional measures: New insights from neurophysiological methods and market response modeling. J. Mark. Res. 2015, 52, 436–452. [Google Scholar] [CrossRef] [Green Version]
- Cherubino, P.; Martinez-Levy, A.C.; Caratu, M.; Cartocci, G.; Di Flumeri, G.; Modica, E.; Rossi, D.; Mancini, M.; Trettel, A. Consumer behaviour through the eyes of neurophysiological measures: State of the art and future trends. Comput. Intell. Neurosci. 2019, 2019, 1976847. [Google Scholar] [CrossRef] [Green Version]
- García-Madariaga, J.; Moya, I.; Recuero, N.; Blasco, M.-F. Revealing unconscious consumer reactions to advertisements that include visual metaphors: A neurophysiological experiment. Front. Psychol. 2020, 11, 760–776. [Google Scholar] [CrossRef]
- Eijlers, E.; Boksem, M.A.S.; Smidts, A. Measuring neural arousal for advertisements and its relationship with advertising success. Front. Neurosci. 2020, 14, 736–748. [Google Scholar] [CrossRef]
- Wei, Z.; Wu, C.; Wang, X.Y.; Supratak, A.; Wang, P.; Guo, Y.K. Using Support Vector Machine on EEG for Advertisement Impact Assessment. Front. Neurosci. 2018, 12, 12. [Google Scholar] [CrossRef] [Green Version]
- Silverman, D. The anterior temporal electrode and the ten-twenty system. Am. J. EEG Technol. 1965, 5, 11–14. [Google Scholar] [CrossRef]
- Rawnaque, F.; Rahman, M.; Anwar, S.M.; Vaidyanathan, R.; Chau, T.; Sarker, F.; Al Mamun, A. Technological advancements and opportunities in Neuromarketing: A systematic review. Brain Inform. 2020, 7, 10. [Google Scholar] [CrossRef] [PubMed]
- Aditya, D.; Sarno, R. Neuromarketing: State of the arts. Adv. Sci. Lett. 2018, 24, 9307–9310. [Google Scholar] [CrossRef]
- Burle, B.; Spieser, L.; Roger, C.; Casini, L.; Hasbroucq, T.; Vidal, F. Spatial and temporal resolutions of EEG: Is it really black and white? A scalp current density view. Int. J. Psychophysiol. 2015, 97, 210–220. [Google Scholar] [CrossRef] [PubMed]
- Bazzani, A.; Ravaioli, S.; Trieste, L.; Faraguna, U.; Turchetti, G. Is EEG Suitable for Marketing Research? A Systematic Review. Front. Neurosci. 2020, 14, 594566. [Google Scholar] [CrossRef] [PubMed]
- Morin, C. Neuromarketing: The new science of consumer behavior. Society 2011, 48, 131–135. [Google Scholar] [CrossRef] [Green Version]
- Ernst, L.H.; Plichta, M.M.; Lutz, E.; Zesewitz, A.K.; Tupak, S.V.; Dresler, T.; Ehlis, A.-C.; Fallgatter, A.J. Prefrontal activation patterns of automatic and regulated approach–avoidance reactions–A functional near-infrared spectroscopy (fNIRS) study. Cortex 2013, 49, 131–142. [Google Scholar] [CrossRef]
- Qing, K.; Huang, R.; Hong, K.-S. Decoding three different preference levels of consumers using convolutional neural network: A functional near-infrared spectroscopy study. Front. Hum. Neurosci. 2021, 14, 597864. [Google Scholar] [CrossRef]
- Gier, N.R.; Strelow, E.; Krampe, C. Measuring dlPFC Signals to Predict the Success of Merchandising Elements at the Point-of-Sale—A fNIRS Approach. Front. Neurosci. 2020, 14, 575494. [Google Scholar] [CrossRef]
- Sitaram, R.; Caria, A.; Birbaumer, N. Hemodynamic brain–computer interfaces for communication and rehabilitation. Neural Netw. 2009, 22, 1320–1328. [Google Scholar] [CrossRef] [Green Version]
- Kopton, I.M.; Kenning, P. Near-infrared spectroscopy (NIRS) as a new tool for neuroeconomic research. Front. Hum. Neurosci. 2014, 8, 549–562. [Google Scholar] [CrossRef] [PubMed]
- Lloyd-Fox, S.; Blasi, A.; Elwell, C. Illuminating the developing brain: The past, present and future of functional near infrared spectroscopy. Neurosci. Biobehav. Rev. 2010, 34, 269–284. [Google Scholar] [CrossRef] [PubMed]
- Plichta, M.M.; Gerdes, A.B.; Alpers, G.W.; Harnisch, W.; Brill, S.; Wieser, M.J.; Fallgatter, A.J. Auditory cortex activation is modulated by emotion: A functional near-infrared spectroscopy (fNIRS) study. Neuroimage 2011, 55, 1200–1207. [Google Scholar] [CrossRef] [Green Version]
- Jackson, P.A.; Kennedy, D.O. The application of near infrared spectroscopy in nutritional intervention studies. Front. Hum. Neurosci. 2013, 7, 473–479. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Hoffman, J. Visual attention and eye movements. Attention 1998, 31, 119–153. [Google Scholar]
- Rayner, K. Eye movements and attention in reading, scene perception, and visual search. Q. J. Exp. Psychol. 2009, 62, 1457–1506. [Google Scholar] [CrossRef] [PubMed]
- Zurawicki, L. Neuromarketing: Exploring the Brain of the Consumer; Springer Science & Business Media: Boston, MA, USA, 2010. [Google Scholar] [CrossRef]
- Baraybar-Fernández, A.; Baños-González, M.; Barquero-Pérez, Ó.; Goya-Esteban, R.; De-la-Morena-Gómez, A. Evaluation of emotional responses to television advertising through neuromarketing. Comunicar 2017, 25, 19–28. [Google Scholar] [CrossRef]
- Guixeres, J.; Bigné, E.; Ausín Azofra, J.M.; Alcañiz Raya, M.; Colomer Granero, A.; Fuentes Hurtado, F.; Naranjo Ornedo, V. Consumer neuroscience-based metrics predict recall, liking and viewing rates in online advertising. Front. Psychol. 2017, 8, 1808. [Google Scholar] [CrossRef] [Green Version]
- Alsharif, A.H.; Salleh, N.Z.M.; Baharun, R.; Mehdi, S. Neuromarketing approach: An overview and future research directions. J. Theor. Appl. Inf. Technol. 2020, 98, 991–1001. [Google Scholar]
- Barquero-Pérez, Ó.; Cámara-Vázquez, M.A.; Vadillo-Valderrama, A.; Goya-Esteban, R. Autonomic Nervous System and Recall Modeling in Audiovisual Emotion-Mediated Advertising Using Partial Least Squares-Path Modeling. Front. Psychol. 2020, 11, 576771–576781. [Google Scholar] [CrossRef]
- Boucsein, W. Electrodermal Activity; Springer Science & Business Media: Boston, MA, USA, 2012. [Google Scholar]
- Salichs, M.A.; Barber, R.; Khamis, A.M.; Malfaz, M.; Gorostiza, J.F.; Pacheco, R.; Rivas, R.; Corrales, A.; Delgado, E.; García, D. Maggie: A robotic platform for human-robot social interaction. In Proceedings of the 2006 IEEE Conference on Robotics, Automation and Mechatronics, Luoyang, China, 25–28 June 2006; pp. 1–7. [Google Scholar]
- Dolcos, F.; Katsumi, Y.; Moore, M.; Berggren, N.; de Gelder, B.; Derakshan, N.; Hamm, A.O.; Koster, E.H.; Ladouceur, C.D.; Okon-Singer, H. Neural Correlates of Emotion-Attention Interactions: From Perception, Learning and Memory to Individual Differences and Training Interventions. Neurosci. Biobehav. Rev. 2019, 108, 559–601. [Google Scholar] [CrossRef] [PubMed]
- Siddharthan, A.; Cherbuin, N.; Eslinger, P.J.; Kozlowska, K.; Murphy, N.A.; Lowe, L. WordNet-feelings: A linguistic categorisation of human feelings. arXiv 2018, preprint. arXiv:1811.02435. [Google Scholar]
- Pham, M.T.; Geuens, M.; De Pelsmacker, P. The influence of ad-evoked feelings on brand evaluations: Empirical generalizations from consumer responses to more than 1000 TV commercials. Int. J. Res. Mark. 2013, 30, 383–394. [Google Scholar] [CrossRef]
- Ramsoy, T. An Introduction to Consumer Neuroscience & Neuromarketing. Available online: https://www.coursera.org/learn/neuromarketing/lecture/FTWBU/introduction-to-this-course (accessed on 29 March 2022).
- Gordon, W. What do consumers do emotionally with advertising? J. Advert. Res. 2006, 46, 2–10. [Google Scholar] [CrossRef] [Green Version]
- Winkielman, P.; Berntson, G.G.; Cacioppo, J.T. The Psychophysiological Perspective on the Social Mind; Blackwell: Hoboken, NJ, USA, 2008; pp. 89–108. [Google Scholar]
- Barrett, L.F.; Satpute, A.B. Large-scale brain networks in affective and social neuroscience: Towards an integrative functional architecture of the brain. Curr. Opin. Neurobiol. 2013, 23, 361–372. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Damasio, A.R. The Feeling of What Happens: Body and Emotion in the Making of Consciousness; Houghton Mifflin Harcourt: Boston, MA, USA, 1999. [Google Scholar]
- Damasio, A.; Carvalho, G.B. The nature of feelings: Evolutionary and neurobiological origins. Nat. Rev. Neurosci. 2013, 14, 143–152. [Google Scholar] [CrossRef]
- LeDoux, J.E.; Brown, R. A higher-order theory of emotional consciousness. Proc. Natl. Acad. Sci. USA 2017, 114. [Google Scholar] [CrossRef] [Green Version]
- Reimann, M.; Bechara, A. The somatic marker framework as a neurological theory of decision-making: Review, conceptual comparisons, and future neuroeconomics research. J. Econ. Psychol. 2010, 31, 767–776. [Google Scholar] [CrossRef]
- Damasio, A.R. Self Comes to Mind: Constructing the Conscious Brain; Pantheon-Random House: New York, NY, USA, 2012. [Google Scholar]
- Posner, J.; Russell, J.A.; Peterson, B.S. The circumplex model of affect: An integrative approach to affective neuroscience, cognitive development, and psychopathology. Dev. Psychopathol. 2005, 17, 715–734. [Google Scholar] [CrossRef]
- Alsharif, A.H.; Salleh, N.Z.M.; Baharun, R.; Alharthi, R.H.E.; Mansor, A.A.; Ali, J.; Abbas, A.F. Neuroimaging Techniques in Advertising Research: Main Applications, Development, and Brain Regions and Processes. Sustainability 2021, 13, 6488. [Google Scholar] [CrossRef]
- Lang, P.J.; Bradley, M.M.; Cuthbert, B.N. Motivated attention: Affect, activation, and action. Atten. Orienting Sens. Motiv. Process. 1997, 97, 135. [Google Scholar]
- Russell, J.A.; Barrett, L.F. Core affect, prototypical emotional episodes, and other things called emotion: Dissecting the elephant. J. Personal. Soc. Psychol. 1999, 76, 805. [Google Scholar] [CrossRef] [PubMed]
- Sundar, S.S.; Kalyanaraman, S. Arousal, memory, and impression-formation effects of animation speed in web advertising. J. Advert. 2004, 33, 7–17. [Google Scholar] [CrossRef]
- Lajante, M.; Droulers, O.; Derbaix, C.; Poncin, I. Looking at aesthetic emotions in advertising research through a psychophysiological perspective. Front. Psychol. 2020, 11, 2544. [Google Scholar] [CrossRef] [PubMed]
- Herrador, J.L.M.; Núñez-Cansado, M.; Cárion, M.I.V. Neuromarketing methodology: Sociograph measurement applied to the analysis of the erotic audiovisual narrative and its applications to the marketing strategy. Vivat Acad. 2020, 23, 131–154. [Google Scholar]
- Grigaliunaite, V.; Pileliene, L. Emotional or rational? The determination of the influence of advertising appeal on advertising effectiveness. Sci. Ann. Econ. Bus. 2016, 63, 391–414. [Google Scholar] [CrossRef] [Green Version]
- Pileliene, L.; Grigaliunaite, V. Relationship between spokesperson’s gender and advertising color temperature in a framework of advertising effectiveness. Sci. Ann. Econ. Bus. 2017, 64, 1–13. [Google Scholar] [CrossRef]
- Grigaliunaite, V.; Pileliene, L. Attitude toward smoking: The effect of negative smoking-related pictures. Oecon. Copernic. 2017, 8, 317–328. [Google Scholar] [CrossRef] [Green Version]
- Pileliene, L.; Grigaliunaite, V. The effect of female celebrity spokesperson in FMCG advertising: Neuromarketing approach. J. Consum. Mark. 2017, 34, 202–213. [Google Scholar] [CrossRef]
- Crespo-Pereira, V.; Martínez-Fernández, V.-A.; Campos-Freire, F. Neuroscience for Content Innovation on European Public Service Broadcasters. Comun. Media Educ. Res. J. 2017, 25, 9–18. [Google Scholar] [CrossRef] [Green Version]
- Banos-González, M.; Baraybar-Fernández, A.; Rajas-Fernández, M. The Application of Neuromarketing Techniques in the Spanish Advertising Industry: Weaknesses and Opportunities for Development. Front. Psychol. 2020, 11, 2175. [Google Scholar] [CrossRef] [PubMed]
- Boscolo, J.C.; Oliveira, J.H.C.; Maheshwari, V.; Giraldi, J.D.E. Gender differences: Visual attention and attitude toward advertisements. Mark. Intell. Plan. 2020, 39, 300–314. [Google Scholar] [CrossRef]
- Silberstein, R.B.; Nield, G.E. Measuring emotion in advertising research: Prefrontal brain activity. IEEE Pulse 2012, 3, 24–27. [Google Scholar] [CrossRef] [PubMed]
- Vecchiato, G.; Astolfi, L.; Fallani, F.D.V.; Cincotti, F.; Mattia, D.; Salinari, S.; Soranzo, R.; Babiloni, F. Changes in brain activity during the observation of TV commercials by using EEG, GSR and HR measurements. Brain Topogr. 2010, 23, 165–179. [Google Scholar] [CrossRef]
- Vecchiato, G.; Kong, W.; Giulio Maglione, A.; Wei, D. Understanding the impact of TV commercials. IEEE Pulse 2012, 3, 42–49. [Google Scholar] [CrossRef] [PubMed]
- Vecchiato, G.; Maglione, A.G.; Cherubino, P.; Wasikowska, B.; Wawrzyniak, A.; Latuszynska, A.; Latuszynska, M.; Nermend, K.; Graziani, I.; Leucci, M.R. Neurophysiological tools to investigate consumer’s gender differences during the observation of TV commercials. Comput. Math. Methods Med. 2014, 2014, 912981. [Google Scholar] [CrossRef] [Green Version]
- Harris, J.; Ciorciari, J.; Gountas, J. Consumer neuroscience and digital/social media health/social cause advertisement effectiveness. Behav. Sci. 2019, 9, 25. [Google Scholar] [CrossRef] [Green Version]
- Chen, Y.; Fowler, C.H.; Papa, V.B.; Lepping, R.J.; Brucks, M.G.; Fox, A.T.; Martin, L.E. Adolescents’ behavioral and neural responses to e-cigarette advertising. Addict. Biol. 2018, 23, 761–771. [Google Scholar] [CrossRef]
- Wang, R.W.; Chang, Y.-C.; Chuang, S.-W. EEG spectral dynamics of video commercials: Impact of the narrative on the branding product preference. Sci. Rep. 2016, 6, 36487–36498. [Google Scholar] [CrossRef] [Green Version]
- Royo González, M.; Chulvi, V.; Mulet, E. Users’ Reactions Captured by Means of an EEG Headset on Viewing the Presentation of Sustainable Designs Using Verbal Narrative. Eur. J. Mark. 2018, 52, 159–181. [Google Scholar] [CrossRef]
- Shen, F.; Morris, J.D. Decoding neural responses to emotion in television commercials. J. Advert. Res. 2016, 56, 11–28. [Google Scholar] [CrossRef]
- Leanza, F. Consumer neuroscience: The traditional and VR TV commercial. Neuropsychol. Trends 2017, 21, 81–90. [Google Scholar] [CrossRef]
- Ramsoy, T.Z.; Michael, N.; Michael, I. A consumer neuroscience study of conscious and subconscious destination preference. Sci. Rep. 2019, 9, 15102. [Google Scholar] [CrossRef] [Green Version]
- Shestyuk, A.Y.; Kasinathan, K.; Karapoondinott, V.; Knight, R.T.; Gurumoorthy, R. Individual EEG measures of attention, memory, and motivation predict population level TV viewership and Twitter engagement. PLoS ONE 2019, 14, e0214507. [Google Scholar] [CrossRef] [PubMed]
- Wang, P.; Wang, S.; Peng, D.; Chen, L.; Wu, C.; Wei, Z.; Childs, P.; Guo, Y.; Li, L. Neurocognition-inspired design with machine learning. Des. Sci. 2020, 6, e33–e52. [Google Scholar] [CrossRef]
- Kim, Y.; Park, K.; Kim, Y.; Yang, W.; Han, D.-u.; Kim, W.-S. The Impact of Visual Art and High Affective Arousal on Heuristic Decision-Making in Consumers. Front. Psychol. 2020, 11, 2994. [Google Scholar] [CrossRef]
- Mengual-Recuerda, A.; Tur-Viñes, V.; Juárez Varón, D. Neuromarketing in haute cuisine gastronomic experiences. Front. Psychol. 2020, 11, 1772. [Google Scholar] [CrossRef]
- Lang, P.J.; Bradley, M.M. Cortex-reflex connections appetitive and defensive motivation is the substrate of emotion. In Handbook of Approach and Avoidance Motivation; Psychology Press: London, UK, 2008; pp. 51–65. [Google Scholar]
- Chiew, K.S.; Braver, T.S. Positive affect versus reward: Emotional and motivational influences on cognitive control. Front. Psychol. 2011, 2, 279. [Google Scholar] [CrossRef] [Green Version]
- Pessoa, L. The Cognitive-Emotional Brain: From Interactions to Integration; MIT press: London, UK, 2013. [Google Scholar]
- Chiew, K.S.; Braver, T.S. Reward favors the prepared: Incentive and task-informative cues interact to enhance attentional control. J. Exp. Psychol. Hum. Percept. Perform. 2016, 42, 52. [Google Scholar] [CrossRef]
- Anderson, B.A.; Laurent, P.A.; Yantis, S. Reward predictions bias attentional selection. Front. Hum. Neurosci. 2013, 7, 262. [Google Scholar] [CrossRef] [Green Version]
- Pessoa, L. Attention, Motivation, and Emotion; Oxford: London, UK, 2014. [Google Scholar]
- Raymond, J. Interactions of attention, emotion and motivation. Prog. Brain Res. 2009, 176, 293–308. [Google Scholar] [PubMed]
- Higgins, E.T. Promotion and prevention: Regulatory focus as a motivational principle. In Advances in Experimental Social Psychology; Elsevier: Amsterdam, The Netherlands, 1998; Volume 30, pp. 1–46. [Google Scholar]
- Cherubino, P.; Maglione, A.G.; Graziani, I.; Trettel, A.; Vecchiato, G.; Babiloni, F. Measuring cognitive and emotional processes in retail: A neuroscience perspective. In Successful Technological Integration for Competitive Advantage in Retail Settings; IGI Global: Hershey, PA, USA, 2015; pp. 76–92. [Google Scholar]
- Pozharliev, R.; Verbeke, W.J.; van Strien, J.W.; Bagozzi, R.P. Merely being with you increases my attention to luxury products: Using EEG to understand consumers’ emotional experience with luxury branded products. J. Mark. Res. 2015, 52, 546–558. [Google Scholar] [CrossRef]
- Zhang, W.; Jin, J.; Wang, A.; Ma, Q.; Yu, H. Consumers’ Implicit Motivation of Purchasing Luxury Brands: An EEG Study. Psychol. Res. Behav. Manag. 2019, 12, 913–929. [Google Scholar] [CrossRef] [Green Version]
- Bosshard, S.S.; Bourke, J.D.; Kunaharan, S.; Koller, M.; Walla, P. Established liked versus disliked brands: Brain activity, implicit associations and explicit responses. Cogent Psychol. 2016, 3, 1–16. [Google Scholar] [CrossRef]
- Davidson, R.J.; Ekman, P.; Saron, C.D.; Senulis, J.A.; Friesen, W.V. Approach-withdrawal and cerebral asymmetry: Emotional expression and brain physiology: I. J. Personal. Soc. Psychol. 1990, 58, 330. [Google Scholar] [CrossRef]
- Bahrabad, M.R.; Farrokhian, S. The Effect of Personality on Purchase Decisions Based on New Freud’s Theories and Behavioral Theory in Mashhad. Int. J. Manag. Account. Econ. 2017, 4, 226–237. [Google Scholar]
- Di Flumeri, G.; Herrero, M.T.; Trettel, A.; Cherubino, P.; Maglione, A.G.; Colosimo, A.; Moneta, E.; Peparaio, M.; Babiloni, F. EEG frontal asymmetry related to pleasantness of olfactory stimuli in young subjects. In Selected Issues in Experimental Economics; Springer: Berlin/Heidelberg, Germany, 2016; pp. 373–381. [Google Scholar] [CrossRef]
- Case, J.A.; Olino, T.M. Approach and avoidance patterns in reward learning across domains: An initial examination of the Social Iowa Gambling Task. Behav. Res. Ther. 2020, 125, 103547. [Google Scholar] [CrossRef]
- Knutson, B.; Adams, C.M.; Fong, G.W.; Hommer, D. Anticipation of increasing monetary reward selectively recruits nucleus accumbens. J. Neurosci. 2001, 21, RC159. [Google Scholar] [CrossRef]
- Berridge, K.C. Food reward: Brain substrates of wanting and liking. Neurosci. Biobehav. Rev. 1996, 20, 1–25. [Google Scholar] [CrossRef]
- Lehner, R.; Balsters, J.H.; Herger, A.; Hare, T.A.; Wenderoth, N. Monetary, food, and social rewards induce similar Pavlovian-to-instrumental transfer effects. Front. Behav. Neurosci. 2017, 10, 247. [Google Scholar] [CrossRef] [Green Version]
- Gilbert, A.M.; Fiez, J.A. Integrating rewards and cognition in the frontal cortex. Cogn. Affect. Behav. Neurosci. 2004, 4, 540–552. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Anderson, B.A. The attention habit: How reward learning shapes attentional selection. Ann. N. Y. Acad. Sci. 2016, 1369, 24–39. [Google Scholar] [CrossRef] [PubMed]
- Krawczyk, D.C.; Gazzaley, A.; D’Esposito, M. Reward modulation of prefrontal and visual association cortex during an incentive working memory task. Brain Res. 2007, 1141, 168–177. [Google Scholar] [CrossRef] [PubMed]
- Bechara, A.; Damasio, A.R.; Damasio, H.; Anderson, S.W. Insensitivity to future consequences following damage to human prefrontal cortex. Cognition 1994, 50, 7–15. [Google Scholar] [CrossRef] [PubMed]
- Maia, T.V.; McClelland, J.L. A reexamination of the evidence for the somatic marker hypothesis: What participants really know in the Iowa gambling task. Proc. Natl. Acad. Sci. USA 2004, 101, 16075–16080. [Google Scholar] [CrossRef]
- Bechara, A.; Damasio, A.R. The somatic marker hypothesis: A neural theory of economic decision. Games Econ. Behav. 2005, 52, 336–372. [Google Scholar] [CrossRef]
- Knutson, B.; Wimmer, G.E. Splitting the difference: How does the brain code reward episodes? Ann. N. Y. Acad. Sci. 2007, 1104, 54–69. [Google Scholar] [CrossRef]
- Padmala, S.; Pessoa, L. Reward reduces conflict by enhancing attentional control and biasing visual cortical processing. J. Cogn. Neurosci. 2011, 23, 3419–3432. [Google Scholar] [CrossRef] [Green Version]
- Galvan, A. Adolescent development of the reward system. Front. Hum. Neurosci. 2010, 4, 6. [Google Scholar] [CrossRef] [Green Version]
- Geier, C.; Terwilliger, R.; Teslovich, T.; Velanova, K.; Luna, B. Immaturities in reward processing and its influence on inhibitory control in adolescence. Cereb. Cortex 2010, 20, 1613–1629. [Google Scholar] [CrossRef] [Green Version]
- Jung, Y.S.; Kim, Y.-T.; Baeck, J.-S.; Lee, J.; Kim, J.G.; Chang, Y. The Neural Correlates of Celebrity Power on Product Favorableness: An fMRI Study. NeuroQuantology 2018, 16, 50–58. [Google Scholar] [CrossRef] [Green Version]
- Padmanabhan, A.; Geier, C.F.; Ordaz, S.J.; Teslovich, T.; Luna, B. Developmental changes in brain function underlying the influence of reward processing on inhibitory control. Dev. Cogn. Neurosci. 2011, 1, 517–529. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Lieberman, M.D. Social: Why Our Brains Are Wired to Connect; OUP: Oxford, UK, 2013. [Google Scholar]
- Izuma, K.; Saito, D.N.; Sadato, N. Processing of social and monetary rewards in the human striatum. Neuron 2008, 58, 284–294. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Davey, C.G.; Allen, N.B.; Harrison, B.J.; Dwyer, D.B.; Yücel, M. Being liked activates primary reward and midline self-related brain regions. Hum. Brain Mapp. 2010, 31, 660–668. [Google Scholar] [CrossRef] [PubMed]
- Fliessbach, K.; Weber, B.; Trautner, P.; Dohmen, T.; Sunde, U.; Elger, C.E.; Falk, A. Social comparison affects reward-related brain activity in the human ventral striatum. Science 2007, 318, 1305–1308. [Google Scholar] [CrossRef]
- Hovland, C.I.; Lumsdaine, A.A.; Sheffield, F.D. Experiments on Mass Communication.(Studies in Social Psychology in World War II); Princeton University Press: Princeton, NJ, USA, 1949; Volume 3. [Google Scholar]
- Wu, C.; Kao, S.-C.; Chiu, H.-Y. Determinants of discontinuous intention of attention to mobile instant message services. J. Retail. Consum. Serv. 2019, 49, 219–230. [Google Scholar] [CrossRef]
- Dayan, P.; Kakade, S.; Montague, P.R. Learning and selective attention. Nat. Neurosci. 2000, 3, 1218–1223. [Google Scholar] [CrossRef]
- Scheier, C.; Held, D. Wie Werbung Wirkt: Erkenntnisse des Neuromarketing. Planegg; Rudolf Haufe Verlag: Munich, Germany, 2006. [Google Scholar]
- Matthews, G.; Wells, A. The Cognitive Science of Attention and Emotion; Dalgleish, T., Power, M.J., Eds.; John Wiley & Sons, Ltd.: New York, NY, USA, 1999; pp. 171–192. [Google Scholar] [CrossRef]
- Genco, S.; Pohlmann, A.; Steidl, P. Neuromarketing for Dummies; John Wiley & Sons: New York, NY, USA, 2013. [Google Scholar]
- Hamelin, N.; Al-Shihabi, S.; Quach, S.; Thaichon, P. Forecasting Advertisement Effectiveness: Neuroscience and Data Envelopment Analysis. Australas. Mark. J. 2021, 30, 313–330. [Google Scholar] [CrossRef]
- Kandel, E.R. Em busca da Memória: O Nascimento de Uma Nova Ciência da Mente; Companhia das Letras: Sao Paulo, Brazil, 2009. [Google Scholar]
- Knudsen, E.I. Fundamental components of attention. Annu. Rev. Neurosci. 2007, 30, 57–78. [Google Scholar] [CrossRef]
- Van Zoest, W.; Donk, M.; Theeuwes, J. The role of stimulus-driven and goal-driven control in saccadic visual selection. J. Exp. Psychol. Hum. Percept. Perform. 2004, 30, 746. [Google Scholar] [CrossRef]
- Meneguzzo, P.; Tsakiris, M.; Schioth, H.B.; Stein, D.J.; Brooks, S.J. Subliminal versus supraliminal stimuli activate neural responses in anterior cingulate cortex, fusiform gyrus and insula: A meta-analysis of fMRI studies. BMC Psychol. 2014, 2, 52. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Crottaz-Herbette, S.; Menon, V. Where and when the anterior cingulate cortex modulates attentional response: Combined fMRI and ERP evidence. J. Cogn. Neurosci. 2006, 18, 766–780. [Google Scholar] [CrossRef] [PubMed]
- Smith, M.E.; Gevins, A. Attention and brain activity while watching television: Components of viewer engagement. Media Psychol. 2004, 6, 285–305. [Google Scholar] [CrossRef]
- Kong, W.Z.; Zhao, X.X.; Hu, S.Q.; Vecchiato, G.; Babiloni, F. Electronic evaluation for video commercials by impression index. Cogn. Neurodynamics 2013, 7, 531–535. [Google Scholar] [CrossRef] [PubMed]
- Casado-Aranda, L.A.; van der Laan, L.N.; Sánchez-Fernández, J. Neural correlates of gender congruence in audiovisual commercials for gender-targeted products: An fMRI study. Hum. Brain Mapp. 2018, 39, 4360–4372. [Google Scholar] [CrossRef] [Green Version]
- Ananos, E. Eye tracker technology in elderly people: How integrated television content is paid attention to and processed. Comunicar 2015, 23, 75–83. [Google Scholar] [CrossRef] [Green Version]
- Cuesta-Cambra, U.; Niño-González, J.-I.; Rodríguez-Terceño, J. The cognitive processing of an educational app with EEG and eye tracking. Media Educ. Res. J. 2017, 25, 41–50. [Google Scholar] [CrossRef] [Green Version]
- Treleaven-Hassard, S.; Gold, J.; Bellman, S.; Schweda, A.; Ciorciari, J.; Critchley, C.; Varan, D. Using the P3a to gauge automatic attention to interactive television advertising. J. Econ. Psychol. 2010, 31, 777–784. [Google Scholar] [CrossRef] [Green Version]
- Simson, A.K. Neuromarketing, Emotions, and Campaigns. Yayımlanmamış Yüksek Lisans Tezi, Copenhagen Business School Master of Social Science. 2010. Available online: https://research.cbs.dk/en/studentProjects/096fa9c2-fc4d-490c-8e1b-2ef7de992528 (accessed on 15 August 2022).
- Thuermer, S. Consumers: Driven by unconscious forces! 2012. Available online: https://research.cbs.dk/en/studentProjects/e5a89c23-9a66-4171-a023-239ec736a16f (accessed on 15 August 2022).
- Hogg, M.; Askegaard, S.; Bamossy, G.; Solomon, M. Consumer Behaviour: A European Perspective; Prentice Hall: Hoboken, NJ, USA, 2006. [Google Scholar]
- Belch, G.E.; Belch, M.A. Advertising and Promotion: An Integrated Marketing Communications Perspective, 7th ed.; McGraw-Hill: New York, NY, USA, 2007. [Google Scholar]
- Cartocci, G.; Caratù, M.; Modica, E.; Maglione, A.G.; Rossi, D.; Cherubino, P.; Babiloni, F. Electroencephalographic, heart rate, and galvanic skin response assessment for an advertising perception study: Application to antismoking public service announcements. J. Vis. Exp. 2017, 3, 55872–55881. [Google Scholar] [CrossRef] [Green Version]
- Modica, E.; Rossi, D.; Cartocci, G.; Perrotta, D.; Di Feo, P.; Mancini, M.; Arico, P.; Inguscio, B.M.S.; Babiloni, F. Neurophysiological Profile of Antismoking Campaigns. Comput. Intell. Neurosci. 2018, 2018, 9721561. [Google Scholar] [CrossRef] [Green Version]
- Falk, E.B.; Berkman, E.T.; Lieberman, M.D. From neural responses to population behavior: Neural focus group predicts population-level media effects. Psychol. Sci. 2012, 23, 439–445. [Google Scholar] [CrossRef] [PubMed]
- Plassmann, H.; O’Doherty, J.; Shiv, B.; Rangel, A. Marketing actions can modulate neural representations of experienced pleasantness. Proc. Natl. Acad. Sci. USA 2008, 105, 1050–1054. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Daw, N.D.; Odoherty, J.P.; Dayan, P.; Seymour, B.; Dolan, R.J. Cortical substrates for exploratory decisions in humans. Nature 2006, 441, 876–879. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Nuñez-Gomez, P.; Alvarez-Ruiz, A.; Ortega-Mohedano, F.; Alvarez-Flores, E.P. Neuromarketing Highlights in How Asperger Syndrome Youth Perceive Advertising. Front. Psychol. 2020, 11, 2103–2116. [Google Scholar] [CrossRef] [PubMed]
- Gong, Y.; Hou, W.; Zhang, Q.; Tian, S. Discounts or gifts? Not just to save money: A study on neural mechanism from the perspective of fuzzy decision. J. Contemp. Mark. Sci. 2018, 1, 53–75. [Google Scholar] [CrossRef]
- Endo, A.C.B.; Roque, M.A.B. Atenção, memória e percepção: Uma análise conceitual da Neuropsicologia aplicada à propaganda e sua influência no comportamento do consumidor. Intercom Rev. Bras. Ciênc. Comun. 2017, 40, 77–96. [Google Scholar] [CrossRef] [Green Version]
- Myers, D.G.; DeWall, N.C. Psychology, 13th ed.; Worth Publishers: New York, NY, USA, 2021. [Google Scholar]
- Atkinson, R.C.; Shiffrin, R.M. Human memory: A proposed system and its control processes. In Psychology of Learning and Motivation; Elsevier: Amsterdam, The Netherlands, 1968; Volume 2, pp. 89–195. [Google Scholar]
- McLeod, S. Multi Store Model of Memory. Available online: https://www.simplypsychology.org/multi-store.html (accessed on 28 August 2022).
- McGaugh, J.L. Memory--a century of consolidation. Science 2000, 287, 248–251. [Google Scholar] [CrossRef] [Green Version]
- Plassmann, H.; Ramsøy, T.Z.; Milosavljevic, M. Branding the brain: A critical review and outlook. J. Consum. Psychol. 2012, 22, 18–36. [Google Scholar] [CrossRef]
- Bradley, M.M.; Greenwald, M.K.; Petry, M.C.; Lang, P.J. Remembering pictures: Pleasure and arousal in memory. J. Exp. Psychol. Learn. Mem. Cogn. 1992, 18, 379. [Google Scholar] [CrossRef]
- Murty, V.P.; Adcock, R.A. Enriched encoding: Reward motivation organizes cortical networks for hippocampal detection of unexpected events. Cereb. Cortex 2014, 24, 2160–2168. [Google Scholar] [CrossRef] [Green Version]
- Wittmann, B.C.; Schott, B.H.; Guderian, S.; Frey, J.U.; Heinze, H.-J.; Düzel, E. Reward-related FMRI activation of dopaminergic midbrain is associated with enhanced hippocampus-dependent long-term memory formation. Neuron 2005, 45, 459–467. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Rossiter, J.R.; Silberstein, R.B.; Harris, P.G.; Nield, G. Brain-imaging detection of visual scene encoding in long-term memory for TV commercials. J. Advert. Res. 2001, 41, 13–21. [Google Scholar] [CrossRef]
- Astolfi, L.; Fallani, F.D.V.; Cincotti, F.; Mattia, D.; Bianchi, L.; Marciani, M.G.; Salinari, S.; Gaudiano, I.; Scarano, G.; Soranzo, R. Brain activity during the memorization of visual scenes from TV commercials: An application of high resolution EEG and steady state somatosensory evoked potentials technologies. J. Physiol. 2009, 103, 333–341. [Google Scholar] [CrossRef] [PubMed]
- Morey, A.C. Memory for positive and negative political TV ads: The role of partisanship and gamma power. Political Commun. 2017, 34, 404–423. [Google Scholar] [CrossRef]
- Bakalash, T.; Riemer, H. Exploring ad-elicited emotional arousal and memory for the ad using fMRI. J. Advert. 2013, 42, 275–291. [Google Scholar] [CrossRef]
- Seelig, D.; Wang, A.-L.; Jaganathan, K.; Loughead, J.W.; Blady, S.J.; Childress, A.R.; Romer, D.; Langleben, D.D. Low message sensation health promotion videos are better remembered and activate areas of the brain associated with memory encoding. PLoS ONE 2014, 9, e113256. [Google Scholar] [CrossRef] [PubMed]
- Langleben, D.D.; Loughead, J.W.; Ruparel, K.; Hakun, J.G.; Busch-Winokur, S.; Holloway, M.B.; Strasser, A.A.; Cappella, J.N.; Lerman, C. Reduced prefrontal and temporal processing and recall of high “sensation value” ads. Neuroimage 2009, 46, 219–225. [Google Scholar] [CrossRef] [Green Version]
- Davidson, R.J. What does the prefrontal cortex “do” in affect: Perspectives on frontal EEG asymmetry research. Biol. Psychol. 2004, 67, 219–234. [Google Scholar] [CrossRef]
- Alsharif, A.H.; Salleh, N.Z.M.; Baharun, R.; Abuhassna, H.; Alsharif, Y.H. Neuromarketing in Malaysia: Challenges, limitations, and solutions. In Proceedings of the International Conference on Decision Aid Sciences and Applications (DASA), Chiangrai, Thailand, 23–25 March 2022; pp. 740–745. [Google Scholar]
Classifications | Tool | No. of Studies | Percentage (%) |
---|---|---|---|
Neuroimaging tools | EEG | 38 | 50% |
fMRI | 20 | 26.3% | |
fNIRS | 4 | 5.3% | |
Physiological tools | ET | 14 | 18.4% |
GSR | 12 | 15.8% | |
ECG/HR | 9 | 11.8% | |
IAT | 4 | 5.3% | |
EMG | 3 | 4% | |
Self-report | Surveys, interviews, observation | 7 | 9.2% |
Emotional Processes | Dimensions | Classification | Tools to Measure Emotions and Feelings |
---|---|---|---|
Emotions | Valence, Arousal | Neuroimaging tools | fMRI, PET, EEG, SST, EMG |
Physiological tools | SST, GSR/SC | ||
Feelings | Self-reports | Surveys, interviews, focus groups, and observation |
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. |
© 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
Alsharif, A.H.; Salleh, N.Z.M.; Al-Zahrani, S.A.; Khraiwish, A. Consumer Behaviour to Be Considered in Advertising: A Systematic Analysis and Future Agenda. Behav. Sci. 2022, 12, 472. https://doi.org/10.3390/bs12120472
Alsharif AH, Salleh NZM, Al-Zahrani SA, Khraiwish A. Consumer Behaviour to Be Considered in Advertising: A Systematic Analysis and Future Agenda. Behavioral Sciences. 2022; 12(12):472. https://doi.org/10.3390/bs12120472
Chicago/Turabian StyleAlsharif, Ahmed H., Nor Zafir Md Salleh, Shaymah Ahmed Al-Zahrani, and Ahmad Khraiwish. 2022. "Consumer Behaviour to Be Considered in Advertising: A Systematic Analysis and Future Agenda" Behavioral Sciences 12, no. 12: 472. https://doi.org/10.3390/bs12120472
APA StyleAlsharif, A. H., Salleh, N. Z. M., Al-Zahrani, S. A., & Khraiwish, A. (2022). Consumer Behaviour to Be Considered in Advertising: A Systematic Analysis and Future Agenda. Behavioral Sciences, 12(12), 472. https://doi.org/10.3390/bs12120472