An exploratory study on computer-aided affective product design based on crowdsourcing

This research investigates the possibility of incorporating affective factors in 3D model creation using handbags as an exemplary product. We demonstrate a crowd-based experimental approach that establishes the correlations between human emotional responses described by bi-polar adjectives and design factors of a bag. A factorial experiment is conducted to understand which design factors independently and/or interactively influence the responses by systematically varying 3D bag models. In-depth statistical analysis of the experimental results indicates that increasing the bag height makes it look more casual; a black bag tends to look luxurious and formal; a bag made of linen feels more classic and sophisticated. Those insights provide a basis for implementing a prototyping design tool that enables users to create 3D bag models with certain affective features using free-form deformation. The proposed approach demonstrates the preliminary feasibility of improving Kansei Engineering applications with big data obtained from crowdsourcing.

[1]  J. Stevens.  Applied Multivariate Statistics for the Social Sciences , 1986 .

[2]  Franca Giannini,et al.  Incorporating free-form features in aesthetic and engineering product design: State-of-the-art report , 2008, Comput. Ind..

[3]  H BarrAlan.  Global and local deformations of solid primitives , 1984 .

[4]  Siddharth Suri,et al.  Conducting behavioral research on Amazon’s Mechanical Turk , 2010, Behavior research methods.

[5]  Markus Hartono,et al.  Applying Kansei Engineering, the Kano model and QFD to services , 2013 .

[6]  George Q. Huang,et al.  Dynamic mapping of design elements and affective responses: a machine learning based method for affective design , 2018 .

[7]  Kazjon Grace,et al.  Data-intensive evaluation of design creativity using novelty, value, and surprise , 2015 .

[8]  Chih-Hsing Chu,et al.  An Investigation of the Social‐Affective Effects Resulting from Appearance‐Related Product Models , 2014 .

[9]  Indika Perera,et al.  Multimodal user interaction framework for e-commerce , 2019, 2019 International Research Conference on Smart Computing and Systems Engineering (SCSE).

[10]  Indika Perera,et al.  Effect of 3D product presentation on consumer preference in e-commerce , 2017, 2017 Moratuwa Engineering Research Conference (MERCon).

[11]  Conrad S. Tucker,et al.  Quantifying Product Favorability and Extracting Notable Product Features Using Large Scale Social Media Data , 2015, J. Comput. Inf. Sci. Eng..

[12]  Barbara Reggiani,et al.  Innovative method for rapid development of shoes and footwear , 2020 .

[13]  Mitsuo Nagamachi,et al.  Kansei Engineering: A new ergonomic consumer-oriented technology for product development , 1995 .

[14]  Yu Wang,et al.  Design automation for customized apparel products , 2005, Comput. Aided Des..

[15]  Bianca Falcidieno,et al.  AESTHETIC DESIGN OF SHAPES USING FULLY FREE-FORM DEFORMATION FEATURES , 2005 .

[16]  Kevin Crowston,et al.  Amazon Mechanical Turk: A Research Tool for Organizations and Information Systems Scholars , 2012, Shaping the Future of ICT Research.

[17]  Yi-Hsuan Yang,et al.  Guest Editorial: Challenges and Perspectives for Affective Analysis in Multimedia , 2015, IEEE Trans. Affect. Comput..

[18]  Yi Ren,et al.  When Crowdsourcing Fails: A Study of Expertise on Crowdsourced Design Evaluation , 2015 .

[19]  Chih-Hsing Chu,et al.  Affective Modelling: Profiling Geometrical Models with Human Emotional Responses , 2009, Comput. Graph. Forum.

[20]  Shengfeng Qin,et al.  Exploring barriers and opportunities in adopting crowdsourcing based new product development in manufacturing SMEs , 2016, Chinese Journal of Mechanical Engineering.

[21]  Suthep Butdee,et al.  A methodology for leather goods design through the emotional design approach , 2017 .

[22]  Chih-Hsing Chu,et al.  Editorial: advances in mass customization , 2013, J. Intell. Manuf..

[23]  C. Osgood,et al.  The Measurement of Meaning , 1958 .

[24]  Adam J. Berinsky,et al.  Evaluating Online Labor Markets for Experimental Research: Amazon.com's Mechanical Turk , 2012, Political Analysis.

[25]  Tomio Jindo,et al.  Application studies to car interior of Kansei engineering , 1997 .

[26]  Hao Wu,et al.  An evaluation methodology for crowdsourced design , 2015, Adv. Eng. Informatics.

[27]  Danni Chang,et al.  A product affective properties identification approach based on web mining in a crowdsourcing environment , 2018 .

[28]  Anol Bhattacherjee,et al.  IFIP Advances in Information and Communication Technology , 2007 .

[29]  Shaofei Wu.  E-commerce decision support system based on internet of things , 2018 .

[30]  Meng-Dar Shieh,et al.  Eliciting design knowledge from affective responses using rough sets and Kansei engineering system , 2015, Journal of Ambient Intelligence and Humanized Computing.

[31]  Jp Tom Djajadiningrat,et al.  Changing your Hammer: The Implications of Paradigmatic Innovation for Design Practice , 2014 .

[32]  Raymond Scupin.  The KJ Method: A Technique for Analyzing Data Derived from Japanese Ethnology , 1997 .

[33]  David Wallace,et al.  Assessing the quality of ideas from prolific, early-stage product ideation , 2013 .

[34]  Lei Ren,et al.  A review on topological architecture and design methods of cable-driven mechanism , 2018 .

[35]  Alan H. Barr,et al.  Global and local deformations of solid primitives , 1984, SIGGRAPH.

[36]  Martin Schreier,et al.  The Value of Crowdsourcing: Can Users Really Compete with Professionals in Generating New Product Ideas? , 2009 .

[37]  Jonathan Corney,et al.  The generation of problem-focussed patent clusters: a comparative analysis of crowd intelligence with algorithmic and expert approaches , 2017, Design Science.

[38]  Kun-Chieh Wang,et al.  Affective product form design using fuzzy Kansei engineering and creativity , 2016, J. Ambient Intell. Humaniz. Comput..

[39]  Lingyun Sun,et al.  Collaborative sketching in crowdsourcing design: a new method for idea generation , 2015 .

[40]  Carlo H. Séquin,et al.  CAD tools for aesthetic engineering , 2005, Comput. Aided Des..

[41]  K. Hsiao,et al.  Fundamental dimensions of affective responses to product shapes , 2006 .

[42]  Theo Gevers,et al.  Texture affects color emotion , 2011 .

[43]  Shengfeng Qin,et al.  Exploring product design quality control and assurance under both traditional and crowdsourcing-based design environments , 2018, Advances in Mechanical Engineering.