- -

Recognizing decision-making using eye movement: A case study with children

RiuNet: Repositorio Institucional de la Universidad Politécnica de Valencia

Compartir/Enviar a

Citas

Estadísticas

  • Estadisticas de Uso

Recognizing decision-making using eye movement: A case study with children

Mostrar el registro sencillo del ítem

Ficheros en el ítem

dc.contributor.author Rojas, Juan-Carlos es_ES
dc.contributor.author Marín-Morales, Javier es_ES
dc.contributor.author Ausin Azofra, Jose Manuel es_ES
dc.contributor.author Contero, Manuel es_ES
dc.date.accessioned 2021-05-28T03:33:47Z
dc.date.available 2021-05-28T03:33:47Z
dc.date.issued 2020-09-24 es_ES
dc.identifier.uri http://hdl.handle.net/10251/166907
dc.description.abstract [EN] The use of visual attention for evaluating consumer behavior has become a relevant field in recent years, allowing researchers to understand the decision-making processes beyond classical self-reports. In our research, we focused on using eye-tracking as a method to understand consumer preferences in children. Twenty-eight subjects with ages between 7 and 12 years participated in the experiment. Participants were involved in two consecutive phases. The initial phase consisted of the visualization of a set of stimuli for decision-making in an eight-position layout called Alternative Forced-choice. Then the subjects were asked to freely analyze the set of stimuli, they needed to choose the best in terms of preference. The sample was randomly divided into two groups balanced by gender. One group visualized a set of icons and the other a set of toys. The final phase was an independent assessment of each stimulus viewed in the initial phase in terms of liking/disliking using a 7-point Likert scale. Sixty-four stimuli were designed for each of the groups. The visual attention was measured using a non-obstructive eye-tracking device. The results revealed two novel insights. Firstly, the time of fixation during the last four visits to each stimulus before the decision-making instant allows us to recognize the icon or toy chosen from the eight alternatives with a 71.2 and 67.2% of accuracy, respectively. The result supports the use of visual attention measurements as an implicit tool to analyze decision-making and preferences in children. Secondly, eye movement and the choice of liking/disliking choice are influenced by stimuli design dimensions. The icon observation results revealed how gender samples have different fixation and different visit times which depend on stimuli design dimension. The toy observations results revealed how the materials determinate the largest amount fixations, also, the visit times were differentiated by gender. This research presents a relevant empirical data to understand the decision-making phenomenon by analyzing eye movement behavior. The presented method can be applied to recognize the choice likelihood between several alternatives. Finally, children's opinions represent an extra difficulty judgment to be determined, and the eye-tracking technique seen as an implicit measure to tackle it. es_ES
dc.description.sponsorship The authors thank Design Deparment of Tecnologico de Monterrey and I3B - Universitat Politecnica de Valencia for their support in the development of this work. es_ES
dc.language Inglés es_ES
dc.publisher Frontiers Media SA es_ES
dc.relation.ispartof Frontiers in Psychology es_ES
dc.rights Reconocimiento (by) es_ES
dc.subject Eye movements es_ES
dc.subject Decision-making es_ES
dc.subject Children es_ES
dc.subject Product es_ES
dc.subject.classification ESTADISTICA E INVESTIGACION OPERATIVA es_ES
dc.subject.classification EXPRESION GRAFICA EN LA INGENIERIA es_ES
dc.title Recognizing decision-making using eye movement: A case study with children es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.3389/fpsyg.2020.570470 es_ES
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Ingeniería Gráfica - Departament d'Enginyeria Gràfica es_ES
dc.contributor.affiliation Universitat Politècnica de València. Instituto Interuniversitario de Investigación en Bioingeniería y Tecnología Orientada al Ser Humano - Institut Interuniversitari d'Investigació en Bioenginyeria i Tecnologia Orientada a l'Ésser Humà es_ES
dc.description.bibliographicCitation Rojas, J.; Marín-Morales, J.; Ausin Azofra, JM.; Contero, M. (2020). Recognizing decision-making using eye movement: A case study with children. Frontiers in Psychology. 11:1-11. https://doi.org/10.3389/fpsyg.2020.570470 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion https://doi.org/10.3389/fpsyg.2020.570470 es_ES
dc.description.upvformatpinicio 1 es_ES
dc.description.upvformatpfin 11 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 11 es_ES
dc.identifier.eissn 1664-1078 es_ES
dc.identifier.pmid 33071901 es_ES
dc.identifier.pmcid PMC7543050 es_ES
dc.relation.pasarela S\418415 es_ES
dc.contributor.funder Universitat Politècnica de València es_ES
dc.contributor.funder Instituto Tecnológico y de Estudios Superiores de Monterrey es_ES
dc.description.references Arkes, H. R., Gigerenzer, G., & Hertwig, R. (2016). How bad is incoherence? Decision, 3(1), 20-39. doi:10.1037/dec0000043 es_ES
dc.description.references Bell, L., Vogt, J., Willemse, C., Routledge, T., Butler, L. T., & Sakaki, M. (2018). Beyond Self-Report: A Review of Physiological and Neuroscientific Methods to Investigate Consumer Behavior. Frontiers in Psychology, 9. doi:10.3389/fpsyg.2018.01655 es_ES
dc.description.references Blanco, S., Dietmann, S., Flores, J. V., Hussain, S., Kutter, C., Humphreys, P., … Frye, M. (2014). Aberrant methylation of t RNA s links cellular stress to neuro‐developmental disorders. The EMBO Journal, 33(18), 2020-2039. doi:10.15252/embj.201489282 es_ES
dc.description.references Chambers, C. T. (2002). Developmental Differences in Children’s Use of Rating Scales. Journal of Pediatric Psychology, 27(1), 27-36. doi:10.1093/jpepsy/27.1.27 es_ES
dc.description.references Cowart, K. O., Fox, G. L., & Wilson, A. E. (2008). A structural look at consumer innovativeness and self-congruence in new product purchases. Psychology and Marketing, 25(12), 1111-1130. doi:10.1002/mar.20256 es_ES
dc.description.references Crone, E. A., & Richard Ridderinkhof, K. (2011). The developing brain: From theory to neuroimaging and back. Developmental Cognitive Neuroscience, 1(2), 101-109. doi:10.1016/j.dcn.2010.12.001 es_ES
dc.description.references Djamasbi, S., Siegel, M., & Tullis, T. (2010). Generation Y, web design, and eye tracking. International Journal of Human-Computer Studies, 68(5), 307-323. doi:10.1016/j.ijhcs.2009.12.006 es_ES
dc.description.references Fantz, R. L. (1963). Pattern Vision in Newborn Infants. Science, 140(3564), 296-297. doi:10.1126/science.140.3564.296 es_ES
dc.description.references Fantz, R. L. (1964). Visual Experience in Infants: Decreased Attention to Familiar Patterns Relative to Novel Ones. Science, 146(3644), 668-670. doi:10.1126/science.146.3644.668 es_ES
dc.description.references Festila, A., & Chrysochou, P. (2018). Implicit communication of food product healthfulness through package design: A content analysis. Journal of Consumer Behaviour, 17(5), 461-476. doi:10.1002/cb.1732 es_ES
dc.description.references Glaholt, M. G., & Reingold, E. M. (2009). The time course of gaze bias in visual decision tasks. Visual Cognition, 17(8), 1228-1243. doi:10.1080/13506280802362962 es_ES
dc.description.references Glaholt, M. G., & Reingold, E. M. (2012). Direct control of fixation times in scene viewing: Evidence from analysis of the distribution of first fixation duration. Visual Cognition, 20(6), 605-626. doi:10.1080/13506285.2012.666295 es_ES
dc.description.references Glaholt, M. G., & Reingold, E. M. (2007). Predicting Preference From Fixations. PsycEXTRA Dataset. doi:10.1037/e527342012-455 es_ES
dc.description.references Green-Armytage, P. (2006). The value of knowledge for colour design. Color Research & Application, 31(4), 253-269. doi:10.1002/col.20222 es_ES
dc.description.references Grunert, K. G., Bredahl, L., & Brunsø, K. (2004). Consumer perception of meat quality and implications for product development in the meat sector—a review. Meat Science, 66(2), 259-272. doi:10.1016/s0309-1740(03)00130-x es_ES
dc.description.references Helo, A., Pannasch, S., Sirri, L., & Rämä, P. (2014). The maturation of eye movement behavior: Scene viewing characteristics in children and adults. Vision Research, 103, 83-91. doi:10.1016/j.visres.2014.08.006 es_ES
dc.description.references Hertenstein, J. H., Platt, M. B., & Veryzer, R. W. (2013). What Is «Good Design»?: An Investigation of the Complexity and Structure of Design. Design Management Journal, 8(1), 8-21. doi:10.1111/dmj.12000 es_ES
dc.description.references Hsu, M. (2017). Neuromarketing: Inside the Mind of the Consumer. California Management Review, 59(4), 5-22. doi:10.1177/0008125617720208 es_ES
dc.description.references Hsu, M., & Yoon, C. (2015). The neuroscience of consumer choice. Current Opinion in Behavioral Sciences, 5, 116-121. doi:10.1016/j.cobeha.2015.09.005 es_ES
dc.description.references Hubert, M. (2010). Does neuroeconomics give new impetus to economic and consumer research? Journal of Economic Psychology, 31(5), 812-817. doi:10.1016/j.joep.2010.03.009 es_ES
dc.description.references Hubert, M., & Kenning, P. (2008). A current overview of consumer neuroscience. Journal of Consumer Behaviour, 7(4-5), 272-292. doi:10.1002/cb.251 es_ES
dc.description.references Hult, G. T. M., Sharma, P. N., Morgeson, F. V., & Zhang, Y. (2019). Antecedents and Consequences of Customer Satisfaction: Do They Differ Across Online and Offline Purchases? Journal of Retailing, 95(1), 10-23. doi:10.1016/j.jretai.2018.10.003 es_ES
dc.description.references Joško Brakus, J., Schmitt, B. H., & Zhang, S. (2014). Experiential product attributes and preferences for new products: The role of processing fluency. Journal of Business Research, 67(11), 2291-2298. doi:10.1016/j.jbusres.2014.06.017 es_ES
dc.description.references Kareklas, I., Brunel, F. F., & Coulter, R. A. (2014). Judgment is not color blind: The impact of automatic color preference on product and advertising preferences. Journal of Consumer Psychology, 24(1), 87-95. doi:10.1016/j.jcps.2013.09.005 es_ES
dc.description.references Karmarkar, U. R., & Plassmann, H. (2017). Consumer Neuroscience: Past, Present, and Future. Organizational Research Methods, 22(1), 174-195. doi:10.1177/1094428117730598 es_ES
dc.description.references Kuijpers, R. C. W. M., Otten, R., Vermulst, A. A., & Engels, R. C. M. E. (2014). Reliability and Construct Validity of a Child Self-Report Instrument. European Journal of Psychological Assessment, 30(1), 40-47. doi:10.1027/1015-5759/a000166 es_ES
dc.description.references Kwon, O. B., Kim, C.-R., & Lee, E. J. (2002). Impact of website information design factors on consumer ratings of web-based auction sites. Behaviour & Information Technology, 21(6), 387-402. doi:10.1080/0144929021000050256 es_ES
dc.description.references Laforet, S. (2011). Brand names on packaging and their impact on purchase preference. Journal of Consumer Behaviour, 10(1), 18-30. doi:10.1002/cb.343 es_ES
dc.description.references Lăzăroiu, G., Pera, A., Ștefănescu-Mihăilă, R. O., Mircică, N., & Negurită, O. (2017). Can Neuroscience Assist Us in Constructing Better Patterns of Economic Decision-Making? Frontiers in Behavioral Neuroscience, 11. doi:10.3389/fnbeh.2017.00188 es_ES
dc.description.references Liao, H.-I., Shimojo, S., & Yeh, S.-L. (2013). Happy faces are preferred regardless of familiarity—sad faces are preferred only when familiar. Emotion, 13(3), 391-396. doi:10.1037/a0030861 es_ES
dc.description.references Liao, H.-I., Yeh, S.-L., & Shimojo, S. (2011). Novelty vs. Familiarity Principles in Preference Decisions: Task-Context of Past Experience Matters. Frontiers in Psychology, 2. doi:10.3389/fpsyg.2011.00043 es_ES
dc.description.references Lieberman, M. D. (2007). Social Cognitive Neuroscience: A Review of Core Processes. Annual Review of Psychology, 58(1), 259-289. doi:10.1146/annurev.psych.58.110405.085654 es_ES
dc.description.references Lin, L. (2010). The relationship of consumer personality trait, brand personality and brand loyalty: an empirical study of toys and video games buyers. Journal of Product & Brand Management, 19(1), 4-17. doi:10.1108/10610421011018347 es_ES
dc.description.references Luo, M. R. (2006). Applying colour science in colour design. Optics & Laser Technology, 38(4-6), 392-398. doi:10.1016/j.optlastec.2005.06.025 es_ES
dc.description.references Marewski, J. N., Gaissmaier, W., & Gigerenzer, G. (2009). Good judgments do not require complex cognition. Cognitive Processing, 11(2), 103-121. doi:10.1007/s10339-009-0337-0 es_ES
dc.description.references Mitsuda, T., & Glaholt, M. G. (2014). Gaze bias during visual preference judgements: Effects of stimulus category and decision instructions. Visual Cognition, 22(1), 11-29. doi:10.1080/13506285.2014.881447 es_ES
dc.description.references Morii, M., & Sakagami, T. (2015). The effect of gaze-contingent stimulus elimination on preference judgments. Frontiers in Psychology, 6. doi:10.3389/fpsyg.2015.01351 es_ES
dc.description.references OCHSNER, K., & GROSS, J. (2005). The cognitive control of emotion. Trends in Cognitive Sciences, 9(5), 242-249. doi:10.1016/j.tics.2005.03.010 es_ES
dc.description.references Pachur, T., Todd, P. M., Gigerenzer, G., Schooler, L. J., & Goldstein, D. G. (2011). The Recognition Heuristic: A Review of Theory and Tests. Frontiers in Psychology, 2. doi:10.3389/fpsyg.2011.00147 es_ES
dc.description.references Park, J., Shimojo, E., & Shimojo, S. (2010). Roles of familiarity and novelty in visual preference judgments are segregated across object categories. Proceedings of the National Academy of Sciences, 107(33), 14552-14555. doi:10.1073/pnas.1004374107 es_ES
dc.description.references Poels, K., & Dewitte, S. (2006). How to Capture the Heart? Reviewing 20 Years of Emotion Measurement in Advertising. Journal of Advertising Research, 46(1), 18-37. doi:10.2501/s0021849906060041 es_ES
dc.description.references Qu, Q.-X., & Guo, F. (2019). Can eye movements be effectively measured to assess product design?: Gender differences should be considered. International Journal of Industrial Ergonomics, 72, 281-289. doi:10.1016/j.ergon.2019.06.006 es_ES
dc.description.references Rojas, J.-C., Contero, M., Bartomeu, N., & Guixeres, J. (2015). Using Combined Bipolar Semantic Scales and Eye-Tracking Metrics to Compare Consumer Perception of Real and Virtual Bottles. Packaging Technology and Science, 28(12), 1047-1056. doi:10.1002/pts.2178 es_ES
dc.description.references Saegusa, C., Intoy, J., & Shimojo, S. (2015). Visual attractiveness is leaky: the asymmetrical relationship between face and hair. Frontiers in Psychology, 6. doi:10.3389/fpsyg.2015.00377 es_ES
dc.description.references Shimojo, S., Simion, C., Shimojo, E., & Scheier, C. (2003). Gaze bias both reflects and influences preference. Nature Neuroscience, 6(12), 1317-1322. doi:10.1038/nn1150 es_ES
dc.description.references Simion, C., & Shimojo, S. (2006). Early interactions between orienting, visual sampling and decision making in facial preference. Vision Research, 46(20), 3331-3335. doi:10.1016/j.visres.2006.04.019 es_ES
dc.description.references Simion, C., & Shimojo, S. (2007). Interrupting the cascade: Orienting contributes to decision making even in the absence of visual stimulation. Perception & Psychophysics, 69(4), 591-595. doi:10.3758/bf03193916 es_ES
dc.description.references Smidts, A., Hsu, M., Sanfey, A. G., Boksem, M. A. S., Ebstein, R. B., Huettel, S. A., … Yoon, C. (2014). Advancing consumer neuroscience. Marketing Letters, 25(3), 257-267. doi:10.1007/s11002-014-9306-1 es_ES
dc.description.references Solnais, C., Andreu-Perez, J., Sánchez-Fernández, J., & Andréu-Abela, J. (2013). The contribution of neuroscience to consumer research: A conceptual framework and empirical review. Journal of Economic Psychology, 36, 68-81. doi:10.1016/j.joep.2013.02.011 es_ES
dc.description.references Song, L., Singh, J., & Singer, M. (1994). The Youth Self-Report inventory: A study of its measurements fidelity. Psychological Assessment, 6(3), 236-245. doi:10.1037/1040-3590.6.3.236 es_ES
dc.description.references Stanton, S. J., Sinnott-Armstrong, W., & Huettel, S. A. (2016). Neuromarketing: Ethical Implications of its Use and Potential Misuse. Journal of Business Ethics, 144(4), 799-811. doi:10.1007/s10551-016-3059-0 es_ES
dc.description.references Steinhauser, J., Janssen, M., & Hamm, U. (2019). Consumers’ purchase decisions for products with nutrition and health claims: What role do product category and gaze duration on claims play? Appetite, 141, 104337. doi:10.1016/j.appet.2019.104337 es_ES
dc.description.references Sturgess, J., Rodger, S., & Ozanne, A. (2002). A Review of the Use of Self-Report Assessment with Young Children. British Journal of Occupational Therapy, 65(3), 108-116. doi:10.1177/030802260206500302 es_ES
dc.description.references Tanaka, J., Weiskopf, D., & Williams, P. (2001). The role of color in high-level vision. Trends in Cognitive Sciences, 5(5), 211-215. doi:10.1016/s1364-6613(00)01626-0 es_ES
dc.description.references Van der Laan, L. N., Hooge, I. T. C., de Ridder, D. T. D., Viergever, M. A., & Smeets, P. A. M. (2015). Do you like what you see? The role of first fixation and total fixation duration in consumer choice. Food Quality and Preference, 39, 46-55. doi:10.1016/j.foodqual.2014.06.015 es_ES
dc.description.references Wang, Y. J., & Minor, M. S. (2008). Validity, reliability, and applicability of psychophysiological techniques in marketing research. Psychology and Marketing, 25(2), 197-232. doi:10.1002/mar.20206 es_ES
dc.description.references Wedel, M., & Pieters, R. (2006). Eye Tracking for Visual Marketing. Foundations and Trends® in Marketing, 1(4), 231-320. doi:10.1561/1700000011 es_ES
dc.description.references Yaramothu, C., Santos, E. M., & Alvarez, T. L. (2018). Effects of visual distractors on vergence eye movements. Journal of Vision, 18(6), 2. doi:10.1167/18.6.2 es_ES


Este ítem aparece en la(s) siguiente(s) colección(ones)

Mostrar el registro sencillo del ítem