A crowdsourcing design framework for concept generation

CIRP Annals - Manufacturing Technology

Volumn 65, Issue 1, 2016, Pages 177-180

  Liu, Ang ^a   Lu, Stephen C Y ^b  

^a UNIVERSITY OF NEW SOUTH WALES   (Australia)

^b UNIVERSITY OF SOUTHERN CALIFORNIA   (United States)

Author keywords

Conceptual design; Crowdsourcing; Design method

Indexed keywords

CONCEPTUAL DESIGN; CROWDSOURCING; REVIEWS; SALES;

CONCEPT GENERATION; CONTROLLED EXPERIMENT; DESIGN FRAMEWORKS; DESIGN METHOD; INNOVATIVE DESIGN; ONLINE CUSTOMER REVIEWS; QUALITATIVE DATA ANALYSIS; SUPPORT CONCEPTS;

DESIGN;

EID: 84969135126     PISSN: 00078506     EISSN: 17260604     Source Type: Journal    
DOI: 10.1016/j.cirp.2016.04.021     Document Type: Article

References (19)

1. [1] Tseng, M.M., et al. Design in the New E-commerce Era. CIRP Annals – Manufacturing Technology 52:2 (2003), 509–519.
2. [2] Mudambi, S.M., Schuff, D., What Makes a Helpful Review? A Study of Customer Reviews on Amazon. MIS Quarterly 34:1 (2010), 185–200.
3. [3] Liu, A., Lu, S.C.Y., Alternation of Analysis and Synthesis for Concept Generation. CIRP Annals – Manufacturing Technology 63:1 (2014), 177–180.
4. [4] Liu, A., Lu, S.C.Y., A New Coevolution Process for Conceptual Design. CIRP Annals – Manufacturing Technology 64:1 (2015), 153–156.
5. [5] Evans, R.D., et al. A Review of Crowdsourcing Literature Related to the Manufacturing Industry. Journal of Advanced Management Science, 4(3), 2016.
6. [6] Kaulio, M.A., Customer, Consumer and User Involvement in Product Development: A Framework and a Review of Selected Methods. Total Quality Management 9:1 (1998), 141–149.
7. [7] Schuh, G., et al. Global Footprint Design based on Genetic Algorithms – An “Industry 4.0” Perspective. CIRP Annals – Manufacturing Technology 63:1 (2014), 433–436.
8. [8] Lee, J., et al. Service Innovation and Smart Analytics for Industry 4.0 and Big Data Environment. Procedia CIRP 16 (2014), 3–8.
9. [9] Yang, M.C., Design Information Retrieval: A Thesauri-based Approach for Reuse of Informal Design Information. Engineering with Computers 21:2 (2005), 177–192.
10. [10] Miles, M.B., Huberman, A.M., Qualitative Data Analysis: An Expanded Sourcebook. 1994, Sage.
11. [11] Richards, L., Handling Qualitative Data: A Practical Guide. 2014, Sage.
12. [12] Pajo Verhaegen, et al. Analysis of Automatic Online Lead User Identification. Smart Product Engineering. 2013, Springer, Berlin, Heidelberg.
13. [13] Suh, N.P., Axiomatic Design: Advances and Applications. 2001, Oxford University Press, New York.
14. [14] Gero, J.S., Kannengiesser, U., The Situated Function–Behaviour–Structure Framework. Design Studies 25:4 (2004), 373–391.
15. [15] Savransky, S.D., Engineering of Creativity: Introduction to TRIZ Methodology of Inventive Problem Solving. 2000, CRC Press.
16. [16] Chan, L.K., Wu, M.L., Quality Function Deployment: A Literature Review. European Journal of Operational Research 143:3 (2002), 463–497.
17. [17] Lu, S.C.Y., et al. A Scientific Foundation of Collaborative Engineering. CIRP Annals – Manufacturing Technology 56:2 (2007), 605–634.
18. [18] Sauder, J., et al. Collaborative Stimulation in Design: A Retrospective Protocol Analysis Approach. Design Creativity Workshop, 2012.
19. [19] Shah, J.J., et al. Metrics for Measuring Ideation Effectiveness. Design Studies 24:2 (2003), 111–134.