Skip to main content

Eye-Tracking zur Kundenanforderungsvalidierung im Produktentwicklungsprozess

Auf dem Weg zur qualitätsoptimierten Customer-Co-Creation

  • 2807 Accesses

Zusammenfassung

Qualitativ hochwertige Produkte können durch die Entwicklung von Produktmerkmalen in Übereinstimmung mit den Kundenwünschen erreicht werden. Um die Konformität von Produkten mit den Anforderungen während des Produktentwicklungsprozesses zu validieren, werden zunehmend objektive biometrische Verfahren wie Eye-Tracking eingesetzt. Das vorliegende Papier gibt daher einen Überblick über den Einsatz von Eye-Tracking in der experimentellen Validierung von Produktdesigns. Darauf aufbauend wird ein Konzept zur Eye-Tracking-unterstützten Kundenanforderungsvalidierung vorgestellt und anhand einer ersten Machbarkeitsstudie überprüft. Anhand der Erkenntnisse wird dargelegt, wie die Präzision, Belastbarkeit und Reichhaltigkeit von Kundenanforderungsanalysen durch den Einsatz von Eye-Tracking erhöht werden können. Die Forschungsarbeiten legen damit einen Grundstein für objektivere und aufwandsärmere Kundenanforderungsanalysen. Sie ebnen so den Weg hin zu einer verstärkten Customer-Co-Creation und einer qualitätsorientierten Produktentwicklung auch für Konsumprodukte.

Schlüsselwörter

  • Kundenanforderungen
  • Eye-Tracking
  • Produktqualität

This is a preview of subscription content, access via your institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • DOI: 10.1007/978-3-662-63243-7_8
  • Chapter length: 20 pages
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
eBook
USD   109.00
Price excludes VAT (USA)
  • ISBN: 978-3-662-63243-7
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
Softcover Book
USD   139.99
Price excludes VAT (USA)
Abb. 1.
Abb. 2.
Abb. 3.
Abb. 4.
Abb. 5.
Abb. 6.

Notes

  1. 1.

    Vgl. https://github.com/solariz/german_stopwords/blob/master/german_stopwords_full.txt.

Literatur

  1. Abdipour, M., Lorentzen, L., Olin, H.: A design research lab—An insstegrated model to identify conscious and unconscious behavior in the design process. In: Di Bucchianico, G., Kercher, P. (Hrsg.) Advances in Design for Inclusion, Bd. 500, S. 553–563. Springer International Publishing, Cham (2016)

    CrossRef  Google Scholar 

  2. Balters, S., Steinert, M.: Capturing emotion reactivity through physiology measurement as a foundation for affective engineering in engineering design science and engineering practices. J. Intell. Manuf. 28, 1585–1607 (2017). https://doi.org/10.1007/s10845-015-1145-2

    CrossRef  Google Scholar 

  3. Blackert, L., Esser, C., Refflinghaus, R.: Development of an experimental design for QFD-guided requirement validations of virtual prototypes. In: Proceeding of the 25th International Symposium on QFD (ISQFD), S. 52–70 (2019)

    Google Scholar 

  4. Blake, C.: Eye Tracking: Grundlagen und Anwendungsfelder. In: Möhring W, Schlütz D (Hrsg.) Handbuch standardisierte Erhebungsverfahren in der Kommunikationswissenschaft. Springer Fachmedien, Wiesbaden (2013)

    Google Scholar 

  5. Blascheck, T., Kurzhals, K., Raschke, M., et al.: Visualization of eye tracking data: A taxonomy and survey. Comput. Graph. Forum 36, 260–284 (2017). https://doi.org/10.1111/cgf.13079

    CrossRef  Google Scholar 

  6. Borgianni, Y., Maccioni, L.: Review of the use of neurophysiological and biometric measures in experimental design research. Artif. Intell. Eng. Des. Anal. Manuf. 1–38 (2020) https://doi.org/10.1017/S0890060420000062

  7. Bucher, H.-J., Schumacher, P.: The relevance of attention for selecting news content. An eye-tracking study on attention patterns in the reception of print and online media. Communications 31, 347–368 (2006)

    CrossRef  Google Scholar 

  8. Campbell, F.W., Wurtz, R.H.: Saccadic omission: Why we do not see a grey-out during a saccadic eye movement. Vision. Res. 18, 1297–1303 (1978). https://doi.org/10.1016/0042-6989(78)90219-5

    CrossRef  Google Scholar 

  9. Carbon, C.-C., Hutzler, F., Minge, M.: Innovativness in design investigated by eye movments and pupillometry. Psychol. Sci. 48, 173–186 (2006)

    Google Scholar 

  10. Cooper, R.M.: The control of eye fixation by the meaning of spoken language. Cogn. Psychol. 6, 84–107 (1974). https://doi.org/10.1016/0010-0285(74)90005-X

    CrossRef  Google Scholar 

  11. Deutsches Institut für Normung e. V. DIN EN ISO 9000:2015-11, Qualitätsmanagementsysteme – Grundlagen und Begriffe (ISO_9000:2015); Deutsche und Englische Fassung EN_ISO_9000:2015

    Google Scholar 

  12. Dogan, K.M., Suzuki, H., Gunpinar, E.: Eye tracking for screening design parameters in adjective-based design of yacht hull. Ocean Eng. 166, 262–277 (2018). https://doi.org/10.1016/j.oceaneng.2018.08.026

    CrossRef  Google Scholar 

  13. Duchowski, A.: Eye Tracking Methodology. Theory and Practice. Springer, London (2007)

    Google Scholar 

  14. Esser, C., Refflinghaus, R.: Requirements validation using virtual prototypes to optimize product quality. In: Proceedings of the 19th International QMOD Conference on Quality and Service Science, S. 332–341 (2016)

    Google Scholar 

  15. Fels, A., Falk, B., Schmitt, R.: Eye-Tracking – Jagd nach dem Augenblick. Qualität und Zuverlässigkeit: QZ 60, 22–25 (2015)

    Google Scholar 

  16. Georgiev, G.V., Yamada, K., Taura, T.: Dynamics of shifting viewpoints: An investigation into users’ attitudes towards products. JDR 15, 62 (2017). https://doi.org/10.1504/JDR.2017.084505

    CrossRef  Google Scholar 

  17. Guo, F., Ding, Y., Liu, W., et al.: Can eye-tracking data be measured to assess product design? Visual attention mechanism should be considered. Int. J. Ind. Ergon. 53, 229–235 (2016). https://doi.org/10.1016/j.ergon.2015.12.001

    CrossRef  Google Scholar 

  18. Hill, A.P., Bohil, C.J.: Applications of optical neuroimaging in usability research. Ergon Des 24, 4–9 (2016). https://doi.org/10.1177/1064804616629309

    CrossRef  Google Scholar 

  19. Ho, C.-H., Lu, Y.-N.: Can pupil size be measured to assess design products? Int. J. Ind. Ergon. 44, 436–441 (2014). https://doi.org/10.1016/j.ergon.2014.01.009

    CrossRef  Google Scholar 

  20. Holmqvist, K., Nyström, M., Andersson, R., et al.: Eye tracking. A Comprehensive Guide to Methods and Measures, 1. Aufl. Oxford Uni-versity Press, Oxford (2011)

    Google Scholar 

  21. Hsu, C.-C., Fann, S.-C., Chuang, M.-C.: Relationship between eye fixation patterns and Kansei evaluation of 3D chair forms. Displays 50, 21–34 (2017). https://doi.org/10.1016/j.displa.2017.09.002

    CrossRef  Google Scholar 

  22. Huettig, F., Rommers, J., Meyer, A.S.: Using the visual world paradigm to study language processing: A review and critical evaluation. Acta Physiol. (Oxf) 137, 151–171 (2011). https://doi.org/10.1016/j.actpsy.2010.11.003

    CrossRef  Google Scholar 

  23. Jiao, R.J., Zhou, F., Chu, C.-H.: Decision theoretic modeling of affective and cognitive needs for product experience engineering: Key issues and a conceptual framework. J. Intell. Manuf. 28, 1755–1767 (2017). https://doi.org/10.1007/s10845-016-1240-z

    CrossRef  Google Scholar 

  24. Khalighy, S., Green, G., Scheepers, C., et al.: Quantifying the qualities of aesthetics in product design using eye-tracking technology. Int. J. Ind. Ergon. 49, 31–43 (2015). https://doi.org/10.1016/j.ergon.2015.05.011

    CrossRef  Google Scholar 

  25. Köhler, M.: Kansei Engineering zur Strukturierung objektiv erfasster Informationen über die visuelle Wahrnehmung für die kundenorientierte Produktgestaltung. Dissertation, RWTH Aachen (2017)

    Google Scholar 

  26. Köhler, M., Falk, B., Schmitt, R.: Applying eye-tracking in Kansei engineering method for design evaluations in product development. Int. J. Affect. Eng. 14, 241–251 (2015). https://doi.org/10.5057/ijae.IJAE-D-15-00016

    CrossRef  Google Scholar 

  27. Kukkonen, S.: Exploring eye tracking in design evaluation. In: Proceedings of Joining Forces – International Conference on Design Research, Helsinki, 119–126 (2005)

    Google Scholar 

  28. Laohakangvalvit, T., Ohkura, M.: Relationship between physical attributes of spoon designs and eye movements caused by Kawaii feelings. In: Chung, W., Shin, C.S. (Hrsg.) Advances in Affective and Pleasurable Design, Bd. 585, S. 245–257. Springer International Publishing, Cham (2018)

    CrossRef  Google Scholar 

  29. Li, B., Fu, H., Wen, D., et al.: Etracker: A mobile Gaze-Tracking system with near-eye display based on a combined Gaze-Tracking algorithm. Sensors (Basel) 18 (2018). https://doi.org/10.3390/s18051626

  30. Lieb, H., Quattelbaum, B., Schmitt, R.: (2008) Perceived quality as a key factor for strategic change in product development. In: IEEE International Engineering Management Conference. IEMC-Europe 2008; 28–30 June 2008, Estoril, Portugal. IEEE, Piscataway, NJ, S. 1–5 (2008)

    Google Scholar 

  31. Mitev, N., Renner, P., Pfeiffer, T., et al.: Towards efficient human-machine collaboration: Effects of gaze-driven feedback and engagement on performance. Cogn Res Princ Implic 3, 51 (2018). https://doi.org/10.1186/s41235-018-0148-x

    CrossRef  Google Scholar 

  32. Mougenot, C., Wtanabe, K., Bouchard, C., et al.: Visual materials and designers’ cognitive activity: Towards in-depth investigations of design cognition. In: International Association of Societies of Design Research, South Korea (2009)

    Google Scholar 

  33. Mussgnug, M., Lohmeyer, Q., Meboldt, M.: Raising designers’ awareness of user experience by mobile eye tracking records. In: Bohemia, E., Eger, A., Eggink, W., et al. (Hrsg.) Proceedings of the 16th International Conference on Engineering and Product Design Education (E&PDE14) (2014)

    Google Scholar 

  34. Mussgnug, M., Singer, D., Lohmeyer, Q., et al.: Automated interpretation of eye–hand coordination in mobile eye tracking recordings. KI – Künstliche Intelligenz 31, 331–337 (2017) https://doi.org/10.1007/s13218-017-0503-y

  35. Nagai, Y., Fukami, T., Kadomatsu, S., et al.: A study on product display using eye-tracking systems. In: Chakrabarti, A., Chakrabarti, D. (Hrsg.) Research Into Design for Communities. Bd. 65, 1. Aufl, S. 547–555. Springer Singapore, Singapore (2017)

    CrossRef  Google Scholar 

  36. Nagamachi, M.: Kansei engineering: A new ergonomic consumer-oriented technology for product development. Int. J. Ind. Ergon. 15, 3–11 (1995). https://doi.org/10.1016/0169-8141(94)00052-5

    CrossRef  Google Scholar 

  37. Pelka, A.: Die Ermittlung von Kundenanforderungen und ihre Transformation in technologische Produktinnovationen in der frühen Phase der automobilen Produktentstehung. Dissertation (2018)

    Google Scholar 

  38. Pfeiffer, T., Renner, P.: EyeSee3D: A low-cost approach for analyzing mobile 3D eye tracking data using computer vision and augmented reality technology. In: Proceedings of the Symposium on Eye Tracking Research and Applications. ACM, S. 195–202 (2014)

    Google Scholar 

  39. Preim, B., Dachselt, R.: Interaktive Systeme. User Interface Engineering, 3D-Interaktion, Natural User Interaces, 2. Aufl., Bd. 2. Springer, Berlin (2015)

    Google Scholar 

  40. Refflinghaus, R., Esser, C.: Structured eyetracking-based requirements validation with the help of virtual prototypes. In: Gomes, J.F.S., Meguid, S.A. (Hrsg.) Proceedings of the 7th International Conference on Mechanics and Materials in Design, S. 1695–1708. INEGI-Instituto de Ciência e Inovação em Engenharia Mecânica e Gestão Industrial Rua Dr Roberto Frias (2017) ISBN: 978-989-98832-7-7

    Google Scholar 

  41. Richter, M., Flückiger, M.D.: Usability Engineering Kompakt. Benutzbare Produkte gezielt entwickeln, 3. Aufl. Springer, Berlin (2013)

    Google Scholar 

  42. Rojas, J.-C., Contero, M., Camba, J.D., et al.: Design perception: Combining semantic priming with eye tracking and event-related potential (ERP) techniques to identify salient product visual attributes. Bd. 11, Systems, Design, and Complexity. American Society of Mechanical Engineers (2015)

    Google Scholar 

  43. Schieber, A., Hilbert, A.: Entwicklung eines generischen Vorgehensmodells für Text Mining. Dresdner Beiträge zur Wirtschaftsinformatik, 69/14. TU Dresden, Dresden (2014)

    Google Scholar 

  44. Schmitt, R., Köhler, M., Durá, J.V., et al.: Objectifying user attention and emotion evoked by relevant perceived product components. J. Sens Sens Syst. 3, 315–324 (2014). https://doi.org/10.5194/jsss-3-315-2014

    CrossRef  Google Scholar 

  45. Triberti, S., Chirico, A., La Rocca, G., et al.: Developing emotional design: Emotions as cognitive processes and their role in the design of interactive Technologies. Front Psychol 8, 1773 (2017). https://doi.org/10.3389/fpsyg.2017.01773

    CrossRef  Google Scholar 

  46. Wang, G.G.: Definition and review of virtual prototyping. J. Comput. Inf. Sci. Eng. 2, 232 (2002). https://doi.org/10.1115/1.1526508

    CrossRef  Google Scholar 

  47. Wang, Z.Y., Liu, H.S., Shi, H.H., et al.: The research of automobile design evaluation method based on the eye tracking system Technology. AMR 230–232, 654–658 (2011). https://doi.org/10.4028/www.scientific.net/AMR.230-232.654

    CrossRef  Google Scholar 

  48. Yang, X., He, H., Wu, Y., et al.: User intent perception by gesture and eye tracking. Cogent Eng. 3 (2016). https://doi.org/10.1080/23311916.2016.1221570

  49. Zhang, J.N., Du, L., Xie, Y., et al.: A literature review of using eye tracking technology in fashion and product design. AMM 536–537, 1662–1665 (2014). https://doi.org/10.4028/www.scientific.net/AMM.536-537.1662

    CrossRef  Google Scholar 

  50. Zhao, M., Yang, D., Liu, S., et al.: Mental stress-performance model in emotional engineering. In: Fukuda, S. (Hrsg.) Emotional Engineering, Bd. 6, S. 119–139. Springer International Publishing, Cham (2018)

    CrossRef  Google Scholar 

Download references

Danksagung

Danke an unseren Kollegen Christian Esser für die Erlaubnis zur Nutzung der zugrundeliegenden experimentellen Daten der hier vorgestellten Versuche.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Lena Stubbemann .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and Permissions

Copyright information

© 2021 Der/die Autor(en), exklusiv lizenziert durch Springer-Verlag GmbH, DE, ein Teil von Springer Nature

About this paper

Verify currency and authenticity via CrossMark

Cite this paper

Stubbemann, L., Refflinghaus, R., Pfeiffer, T. (2021). Eye-Tracking zur Kundenanforderungsvalidierung im Produktentwicklungsprozess. In: Leyendecker, B. (eds) Qualitätsmanagement in den 20er Jahren - Trends und Perspektiven. Springer Vieweg, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-63243-7_8

Download citation

  • DOI: https://doi.org/10.1007/978-3-662-63243-7_8

  • Published:

  • Publisher Name: Springer Vieweg, Berlin, Heidelberg

  • Print ISBN: 978-3-662-63242-0

  • Online ISBN: 978-3-662-63243-7

  • eBook Packages: Computer Science and Engineering (German Language)