More Web Proxy on the site http://driver.im/

research-article

UNISON framework of data-driven innovation for extracting user experience of product design of wearable devices

Authors:

Rhoann KerhAuthors Info & Claims

Computers and Industrial Engineering, Volume 99, Issue C

Pages 487 - 502

https://doi.org/10.1016/j.cie.2016.05.023

Published: 01 September 2016 Publication History

Abstract

A data mining and data-driven framework is constructed to extract user preferences effectively.An empirical study was conducted to derive useful rules for product form of wearable devices.Specific rules are employed to support product design based on user experience.The proposed approach was validated and implemented in real settings. For consumer products, the time-to-market pressure and market share competition are intensive due to the shortening product life cycles. Product form design that contributes to the user experience (UX) is critical to distinguish the product from others. However, few studies have been done for exploring the relationship between UX and the design of product form. To fill the gaps, this study aims to propose a UNISON framework for data-driven innovation to capture the user experience and preference among the factors of product form designs to derive useful rules. An empirical study was conducted for the product design of wearable devices of a world leading Electronics Manufacturing Service (EMS) company with experimental designs of the subjects with different backgrounds to extract their UX to derive design rules. The results have shown practical viability of the proposed approach to assist the designers to develop product design strategies based on the consumer characteristics and the product UX to launch the preferred products to the corresponding customers to enhance customer satisfaction.

References

[1]

B. Agard, A. Kusiak, Data-mining-based methodology for the design of product families, International Journal of Production Research, 42 (2004) 2955-2969.

[2]

C. Ardito, P. Buono, D. Caivano, M.F. Costabile, R. Lanzilotti, Investigating and promoting UX practice in industry: An experimental study, International Journal of Human-Computer Studies, 72 (2014) 542-551.

[3]

J.K. Bae, J. Kim, Product development with data mining techniques: A case on design of digital camera, Expert Systems with Applications, 38 (2011) 9274-9280.

Digital Library

[4]

P. Bate, G. Robert, Experience-based design: from redesigning the system around the patient to co-designing services with the patient, Quality & Safety in Health Care, 15 (2006) 307-310.

[5]

M. Billinghurst, T. Starner, Wearable devices: New ways to manage information, Computer, 32 (1999) 57-64.

Digital Library

[6]

P.H. Bloch, Seeking the ideal form: Product design and consumer response, Journal of Marketing, 59 (1995) 16-29.

[7]

P.H. Bloch, Product design and marketing: Reflections after fifteen years, Journal of Product Innovation Management, 28 (2011) 378-380.

[8]

P.H. Bloch, Frédéric F. Brunel, Todd J. Arnold, Individual differences in the centrality of visual product aesthetics: Concept and measurement, Journal of Consumer Research, 29 (2003) 551-565.

[9]

D. Braha, Data mining for design and manufacturing: Methods and applications, Kluwer Academic Publishers, Dordrecht, The Netherlands, 2001.

Digital Library

[10]

C.-F. Chien, Decision analysis and management: A UNISON framework for total decision quality enhancement, Yeh-Yeh Book Gallery, Taipei, Taiwan, 2005.

[11]

C.-F. Chien, C.-Y. Hsu, UNISON analysis to model and reduce step-and-scan overlay errors for semiconductor manufacturing, Journal of Intelligent Manufacturing, 22 (2011) 399-412.

Digital Library

[12]

C.-F. Chien, C.-Y. Hsu, Data mining for optimizing IC feature designs to enhance overall wafer effectiveness, IEEE Transactions on Semiconductor Manufacturing, 27 (2014) 71-82.

[13]

C.-F. Chien, K.-Y. Lin, A.P.-I. Yu, User-experience of tablet operating system: An experimental investigation of Windows 8, iOS 6, and Android 4.2, Computers & Industrial Engineering, 73 (2014) 75-84.

[14]

C.-F. Chien, H.-J. Wang, M. Wang, A UNISON framework for analyzing alternative strategies of IC final testing for enhancing overall operational effectiveness, International Journal of Production Economics, 107 (2007) 20-30.

[15]

A.K. Choudhary, J.A. Harding, M.K. Tiwari, Data mining in manufacturing: A review based on the kind of knowledge, Journal of Intelligent Manufacturing, 20 (2009) 501-521.

[16]

A. Cooper, The inmates are running the asylum, Macmillan Publishing Co., Inc., 1999.

Digital Library

[17]

M.E.H. Creusen, Research opportunities related to consumer response to product design¿, Journal of Product Innovation Management, 28 (2011) 405-408.

[18]

M.E.H. Creusen, J.P.L. Schoormans, The different roles of product appearance in consumer choice, Journal of Product Innovation Management, 22 (2005) 63-81.

[19]

N. Crilly, J. Moultrie, P.J. Clarkson, Shaping things: Intended consumer response and the other determinants of product form, Design Studies, 30 (2009) 224-254.

[20]

L. Damodaran, User involvement in the systems design process - A practical guide for users, Behaviour & Information Technology, 15 (1996) 363-377.

[21]

P. Desmet, P. Hekkert, Framework of product experience, International Journal of Design, 1 (2007) 57-66.

[22]

R. Dou, C. Zong, Application of Interactive Genetic Algorithm based on hesitancy degree in product configuration for customer requirement, International Journal of Computational Intelligence Systems, 7 (2014) 74-84.

[23]

J.J. Garrett, Elements of user experience: User-centered design for the web, New Riders Press, 2002.

Digital Library

[24]

M. Hassenzahl, M. Schöbel, T. Trautmann, How motivational orientation influences the evaluation and choice of hedonic and pragmatic interactive products: The role of regulatory focus, Interacting with Computers, 20 (2008) 473-479.

Digital Library

[25]

M. Hassenzahl, N. Tractinsky, User experience - A research agenda, Behaviour & Information Technology, 25 (2006) 91-97.

[26]

J. Hoegg, J.W. Alba, Seeing Is Believing (Too Much): The influence of product form on perceptions of functional performance, Journal of Product Innovation Management, 28 (2011) 346-359.

[27]

D. Horn, G. Salvendy, Measuring consumer perception of product creativity: Impact on satisfaction and purchasability, Human Factors and Ergonomics in Manufacturing & Service Industries, 19 (2009) 223-240.

Digital Library

[28]

W. Hoyer, N. Stokburger-Sauer, The role of aesthetic taste in consumer behavior, Journal of the Academy of Marketing Science, 40 (2012) 167-180.

[29]

S.H. Hsu, M.C. Chuang, C.C. Chang, A semantic differential study of designers' and users' product form perception, International Journal of Industrial Ergonomics, 25 (2000) 375-391.

[30]

K. Hornbæk, Current practice in measuring usability: Challenges to usability studies and research, International Journal of Human-Computer Studies, 64 (2006) 79-102.

Digital Library

[31]

W.-K. Hung, L.-L. Chen, Effects of novelty and its dimensions on aesthetic preference in product design, International Journal of Design, 6 (2012) 81-90.

[32]

K. Kang, C. Kang, Y.S. Hong, Data-driven optimized vehicle-level engineering specifications, Industrial Management & Data Systems, 114 (2014) 338-364.

[33]

V. Kaptelinin, L.J. Bannon, Interaction design beyond the product: Creating technology-enhanced activity spaces, Human-Computer Interaction, 27 (2011) 277-309.

[34]

R.L. Keeney, H. Raiffa, Decisions with multiple objectives: Preferences and value tradeoffs, Cambridge University Press, New York, 1993.

[35]

R. Kerh, C.-F. Chien, K.-Y. Lin, Data mining to capture user-experience: A case study in notebook product appearance design, International Journal of Mechanical, Aerospace, Industrial and Mechatronics Engineering, 8 (2014) 661-666.

[36]

P. Kim, Y. Ding, Optimal engineering system design guided by data-mining methods, Technometrics, 47 (2005) 336-348.

[37]

S.J. Kim, S. Kara, B. Kayis, Analysis of the impact of technology changes on the economic and environmental influence of product life-cycle design, International Journal of Computer Integrated Manufacturing, 27 (2014) 422-433.

Digital Library

[38]

M. Kouprie, F.S. Visser, A framework for empathy in design: Stepping into and out of the user's life, Journal of Engineering Design, 20 (2009) 437-448.

[39]

R. Kreuzbauer, A.J. Malter, Embodied cognition and new product design: Changing product form to influence brand categorization¿, Journal of Product Innovation Management, 22 (2005) 165-176.

[40]

S. Kujala, Effective user involvement in product development by improving the analysis of user needs, Behaviour & Information Technology, 27 (2008) 457-473.

Digital Library

[41]

S. Kujala, V. Roto, K. Väänänen-Vainio-Mattila, E. Karapanos, A. Sinnelä, UX curve: A method for evaluating long-term user experience, Interacting with Computers, 23 (2011) 473-483.

Digital Library

[42]

S. Kujala, T. Walsh, P. Nurkka, M. Crisan, Sentence completion for understanding users and evaluating user experience, Interacting with Computers, 26 (2014) 238-255.

[43]

A. Kusiak, Innovation: A data-driven approach, International Journal of Production Economics, 122 (2009) 440-448.

[44]

A. Kusiak, M. Smith, Data mining in design of products and production systems, Annual Reviews in Control, 31 (2007) 147-156.

[45]

H.-H. Lai, Y.-C. Lin, C.-H. Yeh, C.-H. Wei, User-oriented design for the optimal combination on product design, International Journal of Production Economics, 100 (2006) 253-267.

[46]

E.L.-C. Law, V.P. Schaik, V. Roto, Attitudes towards user experience (UX) measurement, International Journal of Human-Computer Studies, 72 (2014) 526-541.

[47]

E.L.-C. Law, X. Sun, Evaluating user experience of adaptive digital educational games with Activity Theory, International Journal of Human-Computer Studies, 70 (2012) 478-497.

Digital Library

[48]

E.L.-C. Law, P. van Schaik, Modelling user experience - An agenda for research and practice, Interacting with Computers, 22 (2010) 313-322.

Digital Library

[49]

S. Li, K. Nahar, B.M. Fung, Product customization of tablet computers based on the information of online reviews by customers, Journal of Intelligent Manufacturing, 26 (2015) 97-110.

Digital Library

[50]

L. Lin, M.-Q. Yang, J. Li, Y. Wang, A systematic approach for deducing multi-dimensional modeling features design rules based on user-oriented experiments, International Journal of Industrial Ergonomics, 42 (2012) 347-358.

[51]

Y.-C. Lin, C.-H. Yeh, C.-C. Wei, How will the use of graphics affect visual aesthetics? A user-centered approach for web page design, International Journal of Human-Computer Studies, 71 (2013) 217-227.

Digital Library

[52]

Linoff, G. S., & Berry, M. J. A. (2011). Data mining techniques: For marketing, sales, and customer relationship management, 3rd ed.

Digital Library

[53]

G.S. Linoff, M.J.A. Berry, Data mining techniques: For marketing, sales, and customer relationship management, John Wiley and Sons, New York, 2004.

Digital Library

[54]

R. Mugge, P.C.M. Govers, J.P.L. Schoormans, The development and testing of a product personality scale, Design Studies, 30 (2009) 287-302.

[55]

D.A. Norman, A. Ortony, D.M. Russell, Affect and machine design: Lessons for the development of autonomous machines, IBM Systems Journal, 42 (2003) 38-44.

Digital Library

[56]

C. Page, P.M. Herr, An investigation of the processes by which product design and brand strength interact to determine initial affect and quality judgments, Journal of Consumer Psychology, 12 (2002) 133-147.

[57]

J. Park, S.H. Han, H.K. Kim, S. Oh, H. Moon, Modeling user experience: A case study on a mobile device, International Journal of Industrial Ergonomics, 43 (2013) 187-196.

[58]

J. Pruitt, T. Adlin, The persona lifecycle: Keeping people in mind throughout product design San Francisco, Morgan Kaufmann Publisher Inc., CA, 2006.

Digital Library

[59]

S.K. Radford, P.H. Bloch, Linking innovation to design: Consumer responses to visual product newness, Journal of Product Innovation Management, 28 (2011) 208-220.

[60]

J. Redström, Towards user design? On the shift from object to user as the subject of design, Design Studies, 27 (2006) 123-139.

[61]

V.P. Rindova, A.P. Petkova, When Is a New Thing a Good Thing? Technological Change, Product Form Design, and Perceptions of Value for Product Innovations, Organization Science, 18 (2007) 217-232.

Digital Library

[62]

S. Sangelkar, N. Cowen, D. McAdams, User activity-product function association based design rules for universal products, Design Studies, 33 (2012) 85-110.

[63]

J. Sauer, A. Sonderegger, The influence of product aesthetics and user state in usability testing, Behaviour & Information Technology, 30 (2011) 787-796.

[64]

X.Y. Shao, Z.H. Wang, P.G. Li, C.X.J. Feng, Integrating data mining and rough set for customer group-based discovery of product configuration rules, International Journal of Production Research, 44 (2006) 2789-2811.

[65]

D. Snelders, R. Mugge, M. Huinink, Using social distinctions in taste for analysing design styles across product categories, International Journal of Design, 8 (2014) 23-34.

[66]

Z. Song, A. Kusiak, Optimising product configurations with a data-mining approach, International Journal of Production Research, 47 (2009) 1733-1751.

[67]

W.K. Tan, M.S. Sie, The impact of personal innovativeness on product aesthetics and self-connection with brand: a case study of mobile phone users, Behaviour & Information Technology, 34 (2014) 316-325.

Digital Library

[68]

M. Tilburg, T. Lieven, A. Herrmann, C. Townsend, Beyond "Pink It and Shrink It" perceived product gender, aesthetics, and product evaluation, Psychology & Marketing, 32 (2015) 422-427.

[69]

J.D. Townsend, W. Kang, M.M. Montoya, R.J. Calantone, Brand-Specific Design Effects: Form and Function, Journal of Product Innovation Management, 30 (2013) 994-1008.

[70]

Y. Truong, R.R. Klink, L. Fort-Rioche, G.A. Athaide, Consumer response to product form in technology-based industries, Journal of Product Innovation Management, 31 (2014) 867-876.

[71]

S. Tuarob, C. Tucker, Quantifying product favorability and extracting notable product features using large scale social media data, Journal of Computing and Information Science in Engineering, 15 (2015) 1-12.

[72]

C.S. Tucker, H.M. Kim, Data-driven decision tree classification for product portfolio design optimization, Journal of Computing and Information Science in Engineering, 9 (2009) 041004.

[73]

C.S. Tucker, H.M. Kim, Trend mining for predictive product design, Journal of Mechanical Design, 133 (2011) 111008.

[74]

T. Tullis, B. Albert, Measuring the user experience: Collecting, analyzing, and presenting usability metrics, Morgan Kaufmann, Amsterdam, 2013.

Digital Library

[75]

V. Venkatesh, M.G. Morris, B.D. Gordon, F.D. Davis, User acceptance of information technology: Toward a unified view, MIS Quarterly, 27 (2003) 425-478.

Digital Library

[76]

C.-C. Yang, Constructing a hybrid Kansei engineering system based on multiple affective responses: Application to product form design, Computers & Industrial Engineering, 60 (2011) 760-768.

Digital Library

[77]

G. Zaltman, Metaphorically speaking: New technique uses multidisciplinary ideas to improve qualitative research, Marketing Research, 8 (1996) 13-20.

[78]

T. Zhou, Examining mobile banking user adoption from the perspectives of trust and flow experience, Information Technology and Management, 13 (2012) 27-37.

Digital Library

Cited By

Lin K(2024)Circular supply chain for smart production in Industry 4.0Computers and Industrial Engineering10.1016/j.cie.2024.110682198:COnline publication date: 1-Dec-2024
https://dl.acm.org/doi/10.1016/j.cie.2024.110682
Lin KHu LZhang K(2024)UNISON framework of data-driven tripartite evolutionary game-based knowledge sharing decision for digital servitizationComputers and Industrial Engineering10.1016/j.cie.2024.109935189:COnline publication date: 1-Mar-2024
https://dl.acm.org/doi/10.1016/j.cie.2024.109935
Chien CKu CLu Y(2024)Ensemble learning for demand forecast of After-Market spare parts to empower data-driven value chain and an empirical studyComputers and Industrial Engineering10.1016/j.cie.2023.109670185:COnline publication date: 27-Feb-2024
https://dl.acm.org/doi/10.1016/j.cie.2023.109670
Show More Cited By

UNISON framework of data-driven innovation for extracting user experience of product design of wearable devices
1. Human-centered computing

Recommendations

Data-driven innovation to capture user-experience product design

A framework of data-driven product design is developed to capture user-experience effectively.An empirical study was conducted to derive useful rules for notebook visual aesthetics design.Specific rules are employed to support product design and ...
Study on big data framework for product design
DSIT '18: Proceedings of the 2018 International Conference on Data Science and Information Technology

With the arrival of the intelligent era, Big Data will play an increasingly important role in all aspects of product design. In the product design stage, comprehensive evaluations such as product quality assessment and social demand exploration are ...
From product concept to user experience: exploring UX potentials at early product stages
NordiCHI '10: Proceedings of the 6th Nordic Conference on Human-Computer Interaction: Extending Boundaries

The focus on users' needs and emotions while interacting with products is a key factor for product success. As the field of User Experience (UX) explores these needs and their fulfilment, it gains in importance against the background of the wish for ...

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

cover image Computers and Industrial Engineering

Computers and Industrial Engineering Volume 99, Issue C

September 2016

518 pages

ISSN:0360-8352

Issue’s Table of Contents

Copyright © Elsevier Ltd.

Publisher

Pergamon Press, Inc.

United States

Publication History

Published: 01 September 2016

Author Tags

Qualifiers

Research-article

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

31
Total Citations
View Citations
0
Total Downloads

Downloads (Last 12 months)0
Downloads (Last 6 weeks)0

Reflects downloads up to 05 Mar 2025

Other Metrics

View Author Metrics

Citations

Cited By

Lin K(2024)Circular supply chain for smart production in Industry 4.0Computers and Industrial Engineering10.1016/j.cie.2024.110682198:COnline publication date: 1-Dec-2024
https://dl.acm.org/doi/10.1016/j.cie.2024.110682
Lin KHu LZhang K(2024)UNISON framework of data-driven tripartite evolutionary game-based knowledge sharing decision for digital servitizationComputers and Industrial Engineering10.1016/j.cie.2024.109935189:COnline publication date: 1-Mar-2024
https://dl.acm.org/doi/10.1016/j.cie.2024.109935
Chien CKu CLu Y(2024)Ensemble learning for demand forecast of After-Market spare parts to empower data-driven value chain and an empirical studyComputers and Industrial Engineering10.1016/j.cie.2023.109670185:COnline publication date: 27-Feb-2024
https://dl.acm.org/doi/10.1016/j.cie.2023.109670
Lu PHsiao STang JWu F(2024)A generative-AI-based design methodology for car frontal forms designAdvanced Engineering Informatics10.1016/j.aei.2024.10283562:PCOnline publication date: 1-Oct-2024
https://dl.acm.org/doi/10.1016/j.aei.2024.102835
Carrera-Rivera ALarrinaga FLasa GMartinez-Arellano GUnamuno G(2024)AdaptUI: A Framework for the development of Adaptive User Interfaces in Smart Product-Service SystemsUser Modeling and User-Adapted Interaction10.1007/s11257-024-09414-034:5(1929-1980)Online publication date: 1-Nov-2024
https://dl.acm.org/doi/10.1007/s11257-024-09414-0
Buis EAshby SKouwenberg K(2023)Increasing the UX maturity level of clientsInformation and Software Technology10.1016/j.infsof.2022.107086154:COnline publication date: 1-Feb-2023
https://dl.acm.org/doi/10.1016/j.infsof.2022.107086
Briard TJean CAoussat AVéron P(2023)Challenges for data-driven design in early physical product designComputers in Industry10.1016/j.compind.2022.103814145:COnline publication date: 1-Feb-2023
https://dl.acm.org/doi/10.1016/j.compind.2022.103814
Hong TChien CChen H(2023)UNISON framework of system dynamics-based technology acquisition decision for semiconductor manufacturing and an empirical studyComputers and Industrial Engineering10.1016/j.cie.2023.109012177:COnline publication date: 1-Mar-2023
https://dl.acm.org/doi/10.1016/j.cie.2023.109012
Zhang KLin KWang JMa YLi HZhang LLiu KFeng L(2023)UNISON framework for user requirement elicitation and classification of smart product-service systemAdvanced Engineering Informatics10.1016/j.aei.2023.10199657:COnline publication date: 1-Aug-2023
https://dl.acm.org/doi/10.1016/j.aei.2023.101996
Jang HHan S(2022)User experience framework for understanding user experience in blockchain servicesInternational Journal of Human-Computer Studies10.1016/j.ijhcs.2021.102733158:COnline publication date: 1-Feb-2022
https://dl.acm.org/doi/10.1016/j.ijhcs.2021.102733
Show More Cited By

View Options

View options

Figures

Tables

Media

View Issue’s Table of Contents