Abstract
In the context of industry 4.0, personalized customization of products will be an important part of intelligent manufacturing. In a market competition, improving customer satisfaction is important to enhance the competitiveness of enterprises. Acquired demand information scientifically is significant to improve customer satisfaction. In this paper, we choose Tobii eye-tracking glasses as a research tool, the key chain and the customizable pictures as research objects. We selected 30 college students as subjects to repeat the experiment. The experiment collect the eye-tracking data of the subjects in and extract the fixation time of the subjects as a reference feature. We combine the relevant knowledge of statistical analysis to study the possibility of the rapid extraction of customer demand information by the eye tracking technology.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Wang K (2015) Intelligent Predictive Maintenance (IPdM) system—Industry 4.0 scenario, www.witpress.com, ISSN 1743-3533 (online) https://doi.org/10.2495/IWAMA150301
Wang J, Fan G, Yan F et al (2016) Research on initiative scheduling mode for a physical internet-based manufacturing system. Int J Adv Manuf Technol 84:47–58
Bogers M, Hadar R, Bilberg A (2016) Additive manufacturing for consumer-centric business models. Technol Forecast Soc Chang 102:225–239
Viviani M, Bennani N, Egyed-Zsigmond E (2016) G-Profile: a hybrid solution for extended identity management in the field of personalized service provision. Inf Resour Manage J 25(3):61–77
Gong DH, Wang ZJ (2014) Evaluation of enterprise leader’s qualities that affect the survival and development of enterprises. Appl Mech Mater 687–691:4622–4630
Zhang Y, Li Y, Wang L, Wang C et al (2016) The analysis and optimization of personalized customization model of crowdsourcing based on GSPN. Int J Multimedia Ubiquitous Eng 11(6):411–426
Mathesoulek K, Slevitch L, Dallinger I (2015) Applying mixed methods to identify what drives quick service restaurant’s customer satisfaction at the unit-level. Int J Hospitality Manage 50:46–54
Pierantonelli M, Perna A, Gregori GL (2015) Interaction between firms in new product development. Behav Brain Res 282(144):125–132
Kulikova NN, Smolentsev VM, Tikhonov AI et al (2016) Planning of technological development of new products and its impact on the economic performance of the enterprise. Int J Econ Financ Issues 6(S8):213–219
Kountouriotis G (2012) Gaze direction and visual information when steering. University of Leeds, http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.581790
Harris JM, Wiggins MW (2008) Evaluating cognitive competence: does eye movement behavior represent the missing piece of the puzzle? Human Factors Ergon Soc Meet 52(26):2077–2081
Lemonnier S, Brémond R, Baccino T (2010) Discriminating cognitive processes with eye movements in a decision-making driving task. J Eye Mov Res 7(4):1–14
Boraston Z, Blakemore SJ (2007) The application of eye-tracking technology in the study of autism. J Physiol 581(3):893–898
Lai ML, Tsai MJ, Yang FY et al (2013) A review of using eye-tracking technology in exploring learning from 2000 to 2012. Educ Res Rev 10(4):90–115
Kuo FY, Hsu CW, Day RF (2010) An exploratory study of cognitive effort involved in decision under framing—an application of the eye-tracking technology. Decis Support Syst 48(1):81–91
Liu HC, Lai ML, Chuang HH (2011) Using eye-tracking technology to investigate the redundant effect of multimedia web pages on viewers’ cognitive processes. Comput Hum Behav 27(6):2410–2417
Baptista PM, Mercadante MT, Macedo EC et al (2006) Cognitive performance in Rett syndrome girls: a pilot study using eyetracking technology. J Intellect Disabil Res 50(9):662–666
Wang Y (2015) Introduction of neural operations management—a product design perspective, www.witpress.com, ISSN 1743-3533 (online) https://doi.org/10.2495/IWAMA150491
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Li, B., Wang, Y., Wang, K., Yang, J., Liu, L. (2018). A Study on a Novel Application of Eye Tracking Technology in Product Customization. In: Wang, K., Wang, Y., Strandhagen, J., Yu, T. (eds) Advanced Manufacturing and Automation VII. IWAMA 2017. Lecture Notes in Electrical Engineering, vol 451. Springer, Singapore. https://doi.org/10.1007/978-981-10-5768-7_65
Download citation
DOI: https://doi.org/10.1007/978-981-10-5768-7_65
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-10-5767-0
Online ISBN: 978-981-10-5768-7
eBook Packages: EngineeringEngineering (R0)