Research in Engineering Design

, Volume 25, Issue 1, pp 75–92 | Cite as

A linguistic approach to assess the dynamics of design team preference in concept selection

  • Andy Dong
  • Somwrita Sarkar
  • Maria C. Yang
  • Tomonori Honda
Original Paper

Abstract

This paper addresses the problem of describing the decision-making process of a committee of engineers based upon their verbalized linguistic appraisals of alternatives. First, we show a way to model an individual’s evaluation of an alternative through natural language based on the Systemic-Functional Linguistics system of APPRAISAL. The linguistic model accounts for both the degree of intensity and the uncertainty of expressed evaluations. Second, this multi-dimensional linguistic model is converted into a scalar to represent the degree of intensity and a probability distribution function for the stated evaluation. Finally, we present a Markovian model to calculate the time-varying change in preferential probability, the probability that an alternative is the most preferred alternative. We further demonstrate how preferential probability toward attributes of alternatives correspond to preferential probability toward alternatives. We illustrate the method on two case studies to highlight the time-variant dynamics of preferences toward alternatives and attributes. This research contributes to process tracing in descriptive decision science to understand how engineers actually take decisions.

Keywords

Decision-based design Ranking alternatives Social choice 

References

  1. Dong A (2009) The language of design: theory and computation. Springer, LondonGoogle Scholar
  2. Dong A, Kleinsmann M, Valkenburg R (2009) Affect-in-cognition through the language of appraisals. Des Stud 30(2):138–153CrossRefGoogle Scholar
  3. Dym CL, Wood WH, Scott MJ (2002) Rank ordering engineering designs: pairwise comparison charts and Borda counts. Res Eng Design 13(4):236–242Google Scholar
  4. Frey D, Herder P, Wijnia Y, Subrahmanian E, Katsikopoulos K, Clausing D (2009) The pugh controlled convergence method: model-based evaluation and implications for design theory. Res Eng Design 20(1):41–58CrossRefGoogle Scholar
  5. Frishammar J, Floren H, Wincent J (2011) Beyond managing uncertainty: Insights from studying equivocality in the fuzzy front end of product and process innovation projects. IEEE Trans Eng Manag 58(3):551–563CrossRefGoogle Scholar
  6. Garbuio M, Lovallo D (2011) The under-appreciated role of quality conversations in strategic decision-making. In: 71st annual meeting of the academy of management AoM 2011. Academy of ManagementGoogle Scholar
  7. Gigone D, Hastie R (1997) The impact of information on small group choice. J Pers Soc Psychol 72(1):132–140CrossRefGoogle Scholar
  8. Hayes AF, Krippendorff K (2007) Answering the call for a standard reliability measure for coding data. Commun Methods Meas 1(1):77–89CrossRefGoogle Scholar
  9. Ji H, Yang M, Honda T (2012) An approach to the extraction of preference-related information from design team language. Res Eng Design 23(2):85–103CrossRefGoogle Scholar
  10. Kahneman D, Lovallo D, Sibony O (2011) Before you make that big decision. Harv Bus Rev 89(6):50–60Google Scholar
  11. Kim J, Wilemon D (2002) Focusing the fuzzy frontend in new product development. R&D Manag 32(4):269–279CrossRefGoogle Scholar
  12. Le Dantec CA, Do EYL (2009) The mechanisms of value transfer in design meetings. Design Stud 30(2):119–137CrossRefGoogle Scholar
  13. Martin JR, White PRR (2005) The language of evaluation: appraisal in English. Palgrave Macmillan, New YorkGoogle Scholar
  14. Paolacci G, Chandler J, Ipeirotis PG (2010) Running experiments on amazon mechanical turk. Judgm Decis Mak 5(5):411–419Google Scholar
  15. Pugh S (1991) Total design: integrated methods for successful product engineering. Addison-Wesley, ReadingGoogle Scholar
  16. Reich Y (2010) My method is better! Res Eng Design 21(3):137–142CrossRefGoogle Scholar
  17. Scott MJ, Antonsson EK (1998) Aggregation functions for engineering design trade-offs. Fuzzy Sets Syst 99(3):253–264CrossRefGoogle Scholar
  18. Sorokin A, Forsyth D (2008) Utility data annotation with amazon mechanical turk. In: IEEE computer society conference on computer vision and pattern recognition workshops, 2008. CVPRW’08, pp 1–8. doi:10.1109/CVPRW.2008.4562953
  19. Subasic P, Huettner A (2001) Affect analysis of text using fuzzy semantic typing. IEEE Trans Fuzzy Syst 9(4):483–496CrossRefGoogle Scholar
  20. Thurston DL (1991) A formal method for subjective design evaluation with multiple attributes. Res Eng Design 3:105–122CrossRefGoogle Scholar
  21. Thurston DL (2001) Real and misconceived limitations to decision based design with utility analysis. J Mech Design 123(2):176–182CrossRefMathSciNetGoogle Scholar
  22. Ulrich KT, Eppinger SD (2004) Product design and development, 3rd edn. McGraw-Hill/Irwin, New YorkGoogle Scholar
  23. Wasiak J, Hicks BJ, Newnes L, Dong A (2010) Understanding engineering email: the development of a taxonomy for identifying and classifying engineering work. Res Eng Design 21(1):43–64CrossRefGoogle Scholar
  24. Wasiak J, Hicks BJ, Newnes L, Loftus C, Dong A, Burrow L (2011) Managing by e-mail: what e-mail can do for engineering project management. IEEE Trans Eng Manag 58(3):445–456CrossRefGoogle Scholar
  25. Weick KE (1995) Sensemaking in organizations. Sage Publications, Thousand OaksGoogle Scholar
  26. Whitelaw C, Garg N, Argamon S (2005) Using appraisal groups for sentiment analysis. In: Proceedings of the 14th ACM international conference on information and knowledge management, CIKM’05, pp. 625–631. ACM, New York, NY, USA. doi:10.1145/1099554.1099714

Copyright information

© Springer-Verlag London 2013

Authors and Affiliations

  • Andy Dong
    • 1
  • Somwrita Sarkar
    • 2
  • Maria C. Yang
    • 3
  • Tomonori Honda
    • 4
  1. 1.Faculty of Engineering and Information TechnologiesUniversity of SydneySydneyAustralia
  2. 2.Design Lab, Faculty of Architecture, Design, and PlanningUniversity of SydneySydneyAustralia
  3. 3.Department of Mechanical Engineering and Engineering Systems DivisionMassachusetts Institute of TechnologyCambridgeUSA
  4. 4.Department of Mechanical EngineeringMassachusetts Institute of TechnologyCambridgeUSA

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