Explicit and Implicit Factors That Determine Private Labels' Possible Purchase: Eyetracking and EEG Research

• Autorzy: Urszula Garczarek-Bąk
• Języki publikacji: EN

Abstrakty

EN

Objective: This paper investigates the explicit and implicit factors affecting private-label (PL) products' possible purchase decision for different retailers. Design: The study uses eyetracking and electroencephalography (EEG) to explore the differences in eye movement and brain activity for PL products. This article examines how approach motivation, measured by total fixation duration and by EEG asymmetry over the frontal hemisphere of the brain, predicts PL purchase decision. Findings: This study investigates implicit variables that can influence consumers' willingness to PL purchase. The relatively greater left frontal activation (i.e., higher approach motivation) during the predecision period predicted an affirmative purchase decision in some cases. The eyetracking study did not reveal differences between women's and men's esthetics sensitivity toward the presented PL products. EEG research proved that consumers were not influenced by the PL product price. Originality/value: Literature lacks credible information on young buyers' behavior in the context of PL products. This paper elaborates on PL perception, revealing the neural origins of the associated psychological processes.(original abstract)

Słowa kluczowe

EN

Neuromarketing; Consumer behaviour; Private label

PL

Neuromarketing; Zachowania konsumenta; Marka handlowa

• Czasopismo: International Journal of Management and Economics
• Rocznik: 2018
• Tom: 54
• Numer: nr 1
• Strony: 36--49

Twórcy

autor

Urszula Garczarek-Bąk

• Uniwersytet Ekonomiczny w Poznaniu

Bibliografia

• Abril, C., Rodriguez-Canovas, B. (2016), Marketing mix effects on private labels brand equity, "European Journal of Management and Business Economics", Vol. 25, No. 3, pp. 168-175.
• Acharya, J.N., Hani, A., Cheek, J., Partha Thirumala, P., Tsuchidak, T.N. (2013), American Clinical Neurophysiology Society Guideline 2: Guidelines for Standard Electrode Position Nomenclature, Available at: www.acns.org/UserFiles/file/ Guideline2-GuidelinesforStandardElectrodePositionNomenclature_v1.pdf (accessed 10 January 2017).
• Agarwal, S. (2015), Introduction to neuromarketing and consumer neuroscience, "Journal of Consumer Marketing", Vol. 32, No. 4, pp. 302-303.
• Agarwal, S., Xavier, M.J. (2015), Innovations in Consumer Science: Applications of Neuro-Scientific Research Tools, in: A. Brem, E. Viardot, (Eds), Adoption of innovation: balancing internal and external stakeholders in the marketing of innovation, Springer International Publishing, Switzerland, pp. 25-42.
• Ailawadi, K.L., Pauwels, K., Steenkamp, J.B.E. (2008), Private-label use and store loyalty, "Journal of Marketing", Vol. 72, No. 6, pp. 19-30.
• Allen, J.J.B., Coan, J.A., Nazarian, M. (2004), Issues and assumptions on the road from raw signals to metrics of frontal EEG asymmetry in emotion, "Biological Psychology", Vol. 67, pp. 183-218.
• Aprilianty, F., Purwanegara, M.S. (2016), Using Electroencephalogram (EEG) to understand the effect of price perception on consumer preference, "The Asian Journal of Technology Management", Vol. 9, No. 1, pp. 58-65.
• Ariely, D., Berns, G. (2010), Neuromarketing: the hope and hype of neuroimaging in business, "Nature Reviews Neuroscience", Vol. 11, No. 4, pp. 284-292.
• Azevedo, R., Aleven, V. (2013), International Handbook of Metacognition and Learning Technologies, Springer Science &Business Media, New York.
• Baisya, R.K., Das, G.G. (2008), Aesthetics in Marketing, SAGE Publications, Thousand Oaks.
• Berka, C., Levendowski, D.J., Lumicao, M.N., Yau, A., Davis, G., Zivkovic, V.T. (2007), EEG correlates of task engagement and mental workload in vigilance, learning, and memory tasks, Aviation, Space, and Environmental Medicine, 78, Suppl. 1, B231-B244.
• Bertola, M.A., Balk, S.A. (2011), Eyes on the Road: A Methodology for Analyzing Complex Eye Tracking Data, http://analytics.ncsu.edu/sesug/2011/ST12.Bertola.pdf (accessed 20 February 2018).
• Billeci, L., Sicca, F., Maharatna, K., Apicella, F., Narzisi, A., Campatelli, G., Calderoni, S., Pioggia, G., Muratori, F., 2013, On the application of quantitative EEG for characterizing autistic brain: a systematic review, "Frontiers in Human Neuroscienc"e, Vol. 7, No. 442, pp. 1-15. Bojko, A., Adamczyk, K.A. (2010), More than just eye candy, "User Experience", Vol. 9, No. 3, pp. 4-8.
• Bridger, K., 2015, Decoding the irrational consumer: how to commission, run and generate insights from neuromarketing research, Kogan Page Publishers, London.
• Brown, C., Randolph, A.B., Burkhalter, J.N. (2012), The story of taste: using EEGs and self-reports to understand consumer choice, "The Kennesaw Journal of Undergraduate Research", Vol. 2, No. 1, pp. 1-11.
• Bulley, C.A., Adu-Brobbey, V., Duodu, E.O. (2016), Neuromarketing and the potential applications of scientific methods in measuring consumer behaviour, in: A. Gbadmosi, (Ed), Handbook of research on consumerism and buying behavior in developing nations, IGI Global, Hershey, pp. 263-282.
• Calvert, G.A., Brammer, M.J. (2012), Predicting consumer behavior: using novel mind-reading approaches, "IEEE Pulse", Vol. 3, No. 3, pp. 38-41.
• Cant, M.C., Strydom, J.W., Jooste, C.J., Plessis, P.J. (2009), Marketing management, Juta and Company, Wetton.
• Creusen, M.E.H. (2010), The importance of product aspects in choice: the influence of demographic characteristics, "Journal of Consumer Marketing", Vol. 27, No. 1, pp. 26-34.
• Cuneo, A., Lopez, P., Jesus Yague, M. (2012), Measuring private labels brand equity: a consumer perspective, "European Journal of Marketing", Vol. 46, No. 7/8, pp. 952-964.
• Cuneo, A., Milberg, S.J., Benavente, J.M., Palacios-Fenech, J. (2015), The growth of private label brands: a worldwide phenomenon?, "Journal of International Marketing", Vol. 23, No. 1, pp. 72-90.
• Davidson, R.J. (1993), Cerebral asymmetry and emotion: conceptual and methodological conundrums, "Cognition and Emotion", Vol. 7, pp. 115-138.
• Dawes, J., Nenycz-Thiel, M. (2013), Analyzing the intensity of private label competition across retailers, "Journal of Business Research", Vol. 66, No. 1, pp. 60-66.
• Doyle, L. (2013), Keen for the innovation: standing apart in private label. Global Cosmetic Industry Magazine, available at: http://www.gcimagazine.com/marketstrends/segments/skincare/Keen-for-Innovation-Standing-Apart-in-Private-Label-204909911.html (accessed 30 March 2017).
• Duchowski, A. (2007), Eyetracking methodology: theory and practice, Springer Science & Business Media, London.
• Eyetracking. (2018), The EyeTracking Blog http://www.eyetracking.com/News/EyeTracking-Blog/EntryId/58/We-re-Gonna- Need-a-Bigger-Sample (accessed 8 February 2018).
• Freeman, W., Quian Quiroga, R. (2013), Imaging brain function with EEG: advanced temporal and spatial analysis of electroencephalographic signals, Springer Science & Business Media, New York.
• Gaviglio, A., Demartini, E., Pirani, A., Marescotti, M.E., Bertocchi, M. (2015), National brands versus private labels versus niche products: a graphical representation of consumers' perception, in: 143rd Joint EAAE/AAEA Seminar, March 25-27, 2015, Naples, Italy (No. 202731). European Association of Agricultural Economists.
• Glaholt, M.G., Reingold, E.M. (2011), Eye movement monitoring as a process tracing methodology in decision making research, "Journal of Neuroscience, Psychology, and Economics", Vol. 4, No. 2, pp. 125-146.
• Goker, N., Dursun, M. (2016), A fuzzy MCDM approach for neuromarketing technology selection problem, in: Proceedings of IAC-MEBM in Vienna, International Academic Conference on Management, Economics, November 25-26, Business and Marketing, Vienna, 2016, pp. 157-161.
• Greenwald, A.G., Poehlman, A., Uhlmann, E., Banaji, M.R. (2009), Understanding and using the implicit association test: III. Meta-analysis of predictive validity, "Journal of Personality and Social Psychology", Vol. 97, No. 1, pp. 17-41.
• Gutberlet, I., Debener, S., Ping Jung, T., Makeig, S. (2009), Techniques of EEG recording and preprocessing, in: S. Tong, N.V. Thakor, (Eds.), Quantitative EEG analysis methods and clinical applications, Artech House, London, pp. 23-49.
• Harmon-Jones, E., Gable, P.A., Peterson, C.K. (2010), The role of asymmetric frontal cortical activity in emotion-related phenomena: a review and update, "Biological Psychology", Vol. 84, pp. 451-462.
• Hausel, H.G. (2007), Neuromarketing: Erkenntnisse der Hirnforschung fur Markenfuhrung, Werbung und Verkauf, Haufe Lexware, Planegg.
• Imotions. (2015), Frontal Asymmetry 101 - How to Get Insights on Motivation and Emotions from EEG, available at: https:// imotions.com/blog/frontal-asymmetry-101-get-insights-motivation-emotions-eeg/(accessed 15 February 2017).
• Indira, V., Vasanthakumari, R., Sugumaran, V. (2012), Sample size determination for classification of EEG signals using power analysis in machine learning approach, "International Journal of Advanced Research in Engineering and Technology", Vol. 3 No. 1, pp. 1-9.
• Jackson, D.J. Darrow, T.I.A. (2005), The influence of celebrity endorsements on young adults' political opinions, "Harvard International Journal of Press/Politics", Vol. 10, No. 3, pp. 80-98.
• John, E.R. (1977), Neurometrics: clinical applications of quantitative electrophysiology, in: E.R. John, R.W. Thatcher, (Eds), Functional neuroscience: vol. 2, Lawrence Erlbaum Associates, Hillsdale, NY, pp. 246-251.
• Karmarkar, U. (2011), Note on neuromarketing, Harvard Business School Marketing Unit Case (512-031).
• Khushaba, R.N., Wise, C., Kodagoda, S., Louviere, J., Kahn, B.E., Townsend, C. (2013), Consumer neuroscience: assessing the brain response to marketing stimuli using electroencephalogram (EEG) and eyetracking, Expert Systems with Applications, Vol. 40, No. 9, pp. 3803-3812.
• Koschate-Fischer, N., Cramer, J., Hoyer, W.D. (2014), Moderating effects of the relationship between private label share and store loyalty, "Journal of Marketing", Vol. 78, No. 2, pp. 69-82.
• Krishna, R. (2006), Gender differences in aesthetic preferences of product design, Mudra Institute of Communications, Ahmedabad.
• Kumar, N., Steenkamp, J.-B.E.M. (2007), Private label strategy: how to meet the store brand challenge, Harvard Business Press, Boston.
• Lamey, L., Deleersnyder, B., Steenkamp, J.B.E., Dekimpe, M.G. (2012), The effect of business-cycle fluctuations on privatelabel share: what has marketing conduct got to do with it?, "Journal of Marketing", Vol. 76, No. 1, pp 1-19.
• Lincoln, K., Thomassen, L. (2008), Private Label: Turning the Retail Brand Threat into Your Biggest Opportunity, Kogan Page Publishers, London.
• Martel, A., Dahne, S., Blankertz, B. (2014), EEG predictors of covert vigilant attention, "Journal of Neural Engineering", Vol. 11, No. 3, pp. 1-11.
• Marques dos Santos, J.P., Martins, M., Ferreira, H.A., Ramalho, J., Seixas, D. (2016), Neural imprints of national brands versus own-label brands, "Journal of Product & Brand Management", Vol. 25, No. 2, pp. 184-195.
• Martenson, R. (2007), Corporate brand image, satisfaction and store loyalty: a study of the store as a brand, store brands and manufacturer brands, "International Journal of Retail Distribution Management", Vol. 35, No. 7, pp. 544-555.
• Noormann, P., Tillmanns, S. (2017), Drivers of private-label purchase behavior across quality tiers and product categories, "Journal of Business Economics", Vol. 87, No. 3, pp. 359-395.
• Ohme, R., Matukin, M., Pacula-Lesniak, B. (2011), Biometric measures for interactive advertising research, "Journal of Interactive Advertising", Vol. 11, No. 2, pp. 60-72.
• Pizzagalli, D. (2007), Electroencephalography and high-density electrophysiological source localization, in: J.T., Caccioppo,L.G., Tassinary, G. Berntson, (Eds), Handbook of psychophysiology, Cambridge University Press, Cambridge, UK, pp. 56-84.
• PLMA. (2017), PLMA's International Private Label Yearbook 2017.
• Quaedflieg, C.W.E.M., Smulders, F.T.Y., Meyer, T., Peeters, F., Merckelbach, H., Smeets, T. (2015), The validity of individual frontal alpha asymmetry EEG neurofeedback, Social Cognitive and Affective Neuroscience, p. 1-11.
• Rao, A., Monroe, K.B. (1989), The effect of price, brand name, and store name on buyers' perceptions of product quality: an integrative review, "Journal of Marketing Research", Vol. 26, pp. 351-357.
• Ravaja, N., Somervuori, O., Salminen, M. (2013), Predicting purchase decision: the role of hemispheric asymmetry over the frontal cortex, "Journal of Neuroscience, Psychology, and Economics", Vol. 6, No. 1, pp. 1-13.
• Regitz-Zagrosek, V. (2012), Sex and gender differences in health: science & society series on sex and science, EMBO Rep.
• Richardson, P.S., Jain, A.K., Dick, A. (1996), Household store brand proneness: a framework, "Journal of Retailing", Vol. 72, No. 2, pp. 159-185.
• Rodrigues, P., Rosa, P.J. (2017), Eye-tracking as a research methodology in educational context: a spanning framework, in: Ch., Was, F., Sanstosti, B. Morris, (Eds), Eye-tracking technology applications in educational research, IGI Global, Hershey, USA.
• Romano-Bergstom, J., Schall, A. (2014), Eyetracking in user experience design, Elsevier, MA, USA.
• Santos, J.P.M., Martins, M., Ferreira, H.A., Ramalho, J., Seixas, D., (2016), Neural imprints of national brands versus own-label brands, ^Journal of Product & Brand Management", Vol. 25, No. 2, pp. 184-195.
• Santos, R.O.J., Oliveira, J.H.C., Rocha, J.B., Giraldi, J.M.E. (2015), Eyetracking in neuromarketing: a research agenda for marketing studies, "International Journal of Psychological Studies", Vol. 7, No. 1, pp. 32-42.
• Schindler, R. (2012), Pricing strategies: a marketing approach, Sage, USA.
• Sebri, M., Zaccour, G. (2017), Cross-country differences in private-label success: an exploratory approach, "Journal of Business Research", Vol. 80, pp. 116-126.
• Sharma, J.K., Sings, D., Agarwal, D.P., Deepak, K.K. (2010), Neuromarketing: a peep into customers' minds, PHI Learning Pvt. Ltd, New Delhi.
• Sickmann, J., Le, N. (2016), Eye-tracking in behavioural economics and finance, available at: https://www.hochschule-rheinwaal. de/sites/default/files/documents/2016/10/19/discussion_papers_in_behavioural_sciences_and_economics_no1.pdf (accessed 24 February 2017).
• Smith, T.J. (2014), Price is not (always) the most important driver to customer purchasing behavior, The Wiglaf Journal, available at: http://www.wiglafjournal.com/pricing/2014/09/price-is-not-always-the-most-important-driver-tocustomer-purchasing-behavior/ (accessed 28 February 2017).
• Sohail, M.S. (2015), Gender differences in mall shopping: a study of shopping behaviour of an emerging nation, "Journal of Marketing and Consumer Behaviour in Emerging Market"s, Vol. 1, No. 1, pp. 36-46.
• Stern, J.M. (2013), Atlas of EEG patterns, Lippincott Williams & Wilkins, PA, USA.
• Telpaz, A., Webb, R., Levy, D.J. (2015), Using EEG to predict consumers' future choices, "Journal of Marketing Research", Vol. 52, No. 4, pp. 511-529.
• Thomas, A.R. (2017), Introduction, in: A.R. Thomas, N.A. Pop, A.M. Iorga, C. Ducu, Ethics and Neuromarketing: implications for market research and business practice, Springer, Switzerland, pp.1-4.
• Venkatraman, V., Clithero, J.A., Fitzsimons, G.J., Huettel, S.A. (2012), New scanner data for brand marketers: how neuroscience can help better understand differences in brand preferences, "Journal of Consumer Psychology", Vol. 22, pp. 143-153.
• Vicdan, H., Chapa, S., Los Santos, G. (2007), Understanding compulsive buyers' online shopping incidence: a closer look at the effects of sales promotions and bargains on Hispanic Americans, "Journal of Customer Behaviou"r, Vol. 6, No. 1, pp. 57-74.
• Vijayalakshmi, K., Sridhar, S., Khanwani, P. (2010), Estimation of effects of alpha music on EEG components by time and frequency domain analysis, Computer and Communication Engineering ICCCE 2010 International Conference, Kuala Lumpur, Malaysia.
• Weiβ, S. (2015), Determinants of private label attitude, Springer Fachmedien, Wiesbaden.
• Winkler, I., Jager, M., Mihajlovi, W., Tsoneva, T. (2010), Frontal EEG asymmetry based classification of emotional valence using common spatial patterns, "World Academy of Science, Engineering and Technology", Vol. 69, pp. 373-378.
• Wu, P.C.S., 2016. Determinants of consumer evaluations for private label brands, in: F.J., Martinez-Lopez, J., Carlos Gazquez-Abad, R. Sethuraman, (Eds), Advances in national brand and private label marketing, second international conference, Springer International Publishing, Switzerland, pp. 3-13.
• Zurawicki, L. (2010), Neuromarketing. Exploring the brain of the consumer, Springer Science & Business Media, Berlin.