Decision-based design: Integrating consumer preferences into engineering design

Decision-Based Design: Integrating Consumer Preferences into Engineering Design

Volumn , Issue , 2013, Pages 1-357

  Chen, Wei ^a,b   Hoyle, Christopher ^c   Wassenaar, Henk Jan ^d  

^a Northwestern University   (United States)

^b Segal Design Institute   (United States)

^c OREGON STATE UNIVERSITY   (United States)

^d Zilliant Inc   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

DECISION MAKING; DECISION THEORY; ECONOMIC ANALYSIS; ECONOMICS; MACHINE DESIGN; STATISTICS;

ANALYTICAL APPROACH; CONSUMER PREFERENCE MODELING; CONSUMER PREFERENCES; DECISION BASED DESIGN; DESIGN CASE STUDIES; ENGINEERING DECISIONS; FUNDAMENTAL PRINCIPLES; MULTI-DISCIPLINARY DESIGNS;

PRODUCT DESIGN;

EID: 84954599469     PISSN: None     EISSN: None     Source Type: Book    
DOI: 10.1007/978-1-4471-4036-8     Document Type: Book

References (407)

1. Allen B (2000) A toolkit for decision-based design theory. Eng valuat and Cost Anal 3(2/3):85—106 (special edition on Decision based Design Status Promise)
2. Besharati B, Azarm S, Kannan P (2006) A decision support system for product design selection: a generalized purchase modeling approach. Decis Support Syst 42(1):333-350
3. Chen W, Lewis KE, Schmidt L (2000) Decision-based design: an emerging design perspective. Eng valuat and Cost Anal 3(2/3):57-66 (special edition on Decision based Design Status Promise)
4. Clausing D, Hauser J (1988) The house of quality. Harv Bus Rev 66(3):63-73
5. Fowlkes WY, Creveling CM (1995) Engineering methods for robust product design. Addison-Wesley Publishing Company, Reading
6. Georgiopoulos P, Jonsson M, Papalambros PY (2005) Linking optimal design decisions to the theory of the firm: the case of resource allocation. J Mech Des 127:358
7. Hazelrigg GA (1996) The implications of arrow’s impossibility theorem on approaches to optimal engineering design. J Mech Des 118(2):161-164
8. Hazelrigg GA (1998) A framework for decision-based engineering design. J Mech Des 120(4):653-658
9. Jin Y, Lu SCY (2004) Agent based negotiation for collaborative design decision making. CIRP Annals-manuf Technol 53(1):121-124
10. Keeney RL (1973) A decision analysis with multiple objectives: The Mexico City Airport. Bell J Econ Manag Sci 4:101-117
11. Krishnan V, Ulrich KT (2001) Product development decisions: A review of the literature. Manag Sci 47(1):1-21
12. Lewis K, Chen W, Schmidt L (eds) (2006) Decision making in engineering design. ASME Press, New York
13. Li H, Azarm S (2000) Product design selection under uncertainty and with competitive advantage. Trans ASME: J Mech Des 122(4):411-418
14. Marston M, Allen J, Mistree F (2000) The decision support problem technique: integrating descriptive and normative approaches in decision based design. Eng valuat and Cost Anal 3(2/3):107-130 (special edition on Decision based Design Status Promise)
15. Messac A (1996) Physical programming: effective optimization for computational design. AIAA J 34(1):149-158
16. Olewnik A, Lewis K (2006) A decision support framework for flexible system design. J Eng Des 17(1):75-97
17. Phadke MS (1989) Quality engineering using robust design. Prentice Hall, Englewood Cliffs
18. Phillips RL (2005) Pricing and revenue optimization. Stanford University Press, Stanford
19. Roser C, Kazmer D, Rinderle J (2003) An economic design change method. J Mech Des 125:233
20. Scott MJ, Antonsson EK (1999) Arrow’s theorem and engineering design decision making. Res Eng Des 11(4):218-228
21. Shiau C, Michalek J (2009) Optimal product design under price competition. J Mech Des 131(7):1-10
22. Talluri KT, Van Ryzin G (2005) The theory and practice of revenue management, vol 68. Kluwer Academic Publishers, New York
23. Tang X, Krishnamurty S (2000) On decision model development in engineering design. Eng valuat and Cost Anal 3(2/3):131-150 (special edition on Decision based Design Status Promise)
24. Tappeta RV, Renaud JE (2001) Interactive multiobjective optimization design strategy for decision based design. J Mech Des 123:205
25. Thurston DL (2001) Real and misconceived limitations to decision based design with utility analysis. J Mech Des 123:176
26. Ullman DG (2009) The mechanical design process. McGraw-Hill, Boston
27. Wassenaar HJ, Chen W (2003) An approach to decision-based design with discrete choice analysis for demand modeling. Trans ASME: J Mech Des 125(3):490-497
28. Wood WH (2004) Decision-based design: a vehicle for curriculum integration. Int J Eng Educ 20(3):433-439
29. Zhao Z, Shah JJ (2005) Domain independent shell for dfm and its application to sheet metal forming and injection molding. Comput Aided Des 37(9):881-898
30. Arrow KJ (1963) Social choice and individual values. Wiley, New York
31. Arrow KJ, Raynaud H (1986) Social choice and multicriterion decision-making. MIT Press Books, Cambridge
32. Aungst S, Barton R, Wilson D (2003) The virtual integrated design method. Qual Eng 15(4):565-579
33. Barzilai J (2005) Measurement and preference function modelling. Int Trans Oper Res 12(2):173—183
34. Black D (1948) On the rationale of group decision making. J Political Econ 56:23-34
35. Brackin P, Colton J (2002) Using genetic algorithms to set target values for engineering characteristics in the house of quality. J Comput Inf Sci Eng (Transactions of the ASME) 2 (2):106-114
36. Browning TR (2001) Applying the design structure matrix to system decomposition and integration problems: a review and new directions. IEEE Trans Eng Manage 48(3):292-306
37. Chan LK, Kao HP, Wu ML (1999) Rating the importance of customer needs in quality function deployment by fuzzy and entropy methods. Int J Prod Res 37(11):2499-2518
38. Chan LK, Wu ML (2002) Quality function deployment: a literature review. Eur J Oper Res 143(3):463-497
39. Clausing D, Hauser J (1988) The house of quality. Harv Bus Rev 66(3):63-73
40. Condorcet M (1785) Essai sur l’application de l’analysea la probabilité des décisions renduesa la pluralité des voix. Imprimerie Royale, Paris
41. Cozzolino JM (1979) A new method for risk analysis. Sloan Manag Rev 20(3):53-66
42. Dym CL, Wood WH, Scott MJ (2002) Rank ordering engineering designs: pairwise comparison charts and borda counts. Res Eng Design 13(4):236-242
43. Gershenson JK, Stauffer LA (1999) A taxonomy for design requirements from corporate customers. Res Eng Design 11(2):103-115
44. Harry MJ, Schroeder RR (2000) Six sigma: the breakthrough management strategy revolutionizing the world’s top corporations. Broadway Business, New York
45. Hazelrigg GA (1996) The implications of arrow’s impossibility theorem on approaches to optimal engineering design. J Mech Des 118(2):161-164
46. Hazelrigg GA (1996) Systems engineering: an approach to information-based design. Prentice Hall, Upper Saddle River
47. Hazelrigg GA (2003) Validation of engineering design alternative selection methods. Eng Optim 35(2):103-120
48. Holt CA, Laury SK (2002) Risk aversion and incentive effects. Am Econ Rev 92(5): 1644-1655
49. Howard R (ed) (1992) In praise of the old time religion. Utility theories, measurements and applications. Kluwer Academic Publishers, Boston
50. Howard RA (1968) The foundations of decision analysis. IEEE Trans Syst Sci Cybern 4(3):211-219
51. Kahraman C, Ertay T, Büyükozkan G (2006) A fuzzy optimization model for QFD planning process using analytic network approach. Eur J Oper Res 171(2):390-411
52. Keeney RL, Raiffa H (1993) Decisions with multiple objectives: preferences and value tradeoffs. Cambridge University Press, New York
53. Kim KJ, Moskowitz H, Dhingra A, Evans G (2000) Fuzzy multicriteria models for quality function deployment. Eur J Oper Res 121(3):504-518
54. Krishnamurty S (2006) Normative decision analysis in engineering design. In: Lewis K, Chen W, Schmidt L (eds) Decision making in engineering design. ASME Press, New York, pp 21-35
55. Locascio A, Thurston DL (1998) Transforming the house of quality to a multiobjective optimization formulation. Struct Multidiscip Optim 16(2):136-146
56. Nicholson W (2000) Intermediate microeconomics and its application, 8th edn. Hartcourt Inc, Orlando
57. Olewnik AT, Lewis K (2005) On validating engineering design decision support tools. Concurr Eng 13(2):111-122
58. Pennings JME, Smidts A (2000) Assessing the construct validity of risk attitude. Manage Sci 46(10):1337-1348
59. Podeswa H (2009) The business analyst’s handbook. Course Technology PTR, Boston
60. Prasad B (2000) A concurrent function deployment technique for a workgroup-based engineering design process. J Eng Des 11(2):103-119
61. Raffia H (1970) Decision analysis: introductory lectures on choices under uncertainty. Addison-Wesley Reading, Massachusetts
62. Saari D (2000) Mathematical structure of voting paradoxes. I; pairwise vote II; positional voting. Econ Theory 15:1-103
63. Saari D (2006) Fundamentals and implications of decision-making. In: Lewis K, Chen W, Schmidt L (eds) Decision making in engineering design. ASME Press, New York, pp 35-42
64. Saaty T (1980) Analytic hierarchy process: planning, priority setting, resource allocation. McGraw Hill, New York
65. Scott MJ, Antonsson EK (1999) Arrow’s theorem and engineering design decision making. Res Eng Design 11(4):218-228
66. Suh NP (1990) The principles of design. Oxford University Press, New York
67. Taguchi G (1988) Introduction to quality engineering: designing quality into products and processes. Asian Productivity Organization, Tokyo
68. Terninko J (1997) Step-by-step QFD: customer-driven product design. CRC Press, Boca Raton
69. Thurston DL (2001) Real and misconceived limitations to decision based design with utility analysis. J Mech Des 123:176
70. Thurston DL (2006) Utility function fundamentals. In: Lewis K, Chen W, Schmidt L (eds) Decision making in engineering design. ASME Press, New York, pp 5-14
71. Ullman DG (2009) The mechanical design process. McGraw-Hill, Boston
72. Van de Poel I (2007) Methodological problems in QFD and directions for future development. Res Eng Design 18(1):21-36
73. Von Neumann J, Morgenstern O, Rubinstein A, Kuhn HW (2007) Theory of games and economic behavior. Princeton Univ Press, Princeton
74. Bass FM (2004) A new product growth for model consumer durables. Manage Sci 50(13):1825-1832
75. Ben-Akiva M, Lerman SR (1985) Discrete choice analysis: theory and application to travel demand. MIT Press, Cambridge
76. Ben-Akiva M, Morikawa T, Shiroishi F (1992) Analysis of the reliability of preference ranking data. J Bus Res 24(2):149-164
77. Ben-Akiva ME (1973) Structure of passenger travel demand models. Massachusetts Institute of Technology, Cambridge
78. Bradley M, Daly A (1994) Use of the logit scaling approach to test for rank-order and fatigue effects in stated preference data. Transportation 21(2):167-184
79. Breiman L, Spector P (1992) Submodel selection and evaluation in regression. The x-random case. International statistical review/revue internationale de Statistique 60 (3):291-319
80. Brownstone D, Train K (1998) Forecasting new product penetration with flexible substitution patterns. J Econ 89(1-2):109-129
81. Clarkson P, Coleman R, Keates S, Lebbon C (2003) Inclusive design: design for the whole population. Springer, Cambridge
82. Cook HE (1997) Product management: value, quality, cost, price, profit and organization. Chapman & Hall, London
83. Daganzo C (1979) Multinomial probit, the theory and its application to demand forecasting. Academic Press Inc, New York
84. de Weck O, de Neufville R, Chaize M (2004) Staged deployment of communications satellite constellations in low earth orbit. J Aerosp Comput Inf Commun 1(3):119-136
85. Erdem T, Keane MP (1996) Decision-making under uncertainty: capturing dynamic brand choice processes in turbulent consumer goods markets. Mark Sci 15(1):1-20
86. Forinash CV, Koppelman FS (1993) Application and interpretation of nested logit models of intercity mode choice. Transp Res Rec 1413:98-106
87. Frischknecht BD, Whitefoot K, Papalambros PY (2010) On the suitability of econometric demand models in design for market systems. J Mech Des 132:1210071-1210011
88. Garrow L, Koppelman F (2004) Multinomial and nested logit models of airline passengers’ no-show and standby behaviour. J Rev Pricing Manag 3:237-253
89. Gelman A, Carlin JB, Stern HS, Rubin DB (2004) Bayesian data analysis, vol 25. Texts in statistical science. Chapman & Hall/CRC, Boca Raton
90. Georgiopoulos P, Jonsson M, Papalambros PY (2005) Linking optimal design decisions to the theory of the firm: the case of resource allocation. J Mech Des 127:358
91. Gorsuch RL (1983) Factor analysis. Lawrence Erlbaum Associates, Hillsdale
92. Green PE, Carmone FJ (1970) Multidimensional scaling and related techniques in marketing analysis. Allyn and Bacon, Boston
93. Green PE, Krieger AM (1991) Product design strategies for target-market positioning. J Prod Innov Manag 8(3):189-202
94. Green PE, Krieger AM (1991) Segmenting markets with conjoint analysis. J Mark 55(4): 20-31
95. Green PE, Srinivasan V (1978) Conjoint analysis in consumer research: issues and outlook. J Consumer Res 5(2):103-123
96. Green PE, Srinivasan V (1990) Conjoint analysis in marketing: new developments with implications for research and practice. J Mark 54(4):3-19
97. Green PE, Tull DS (1978) Research for marketing decisions. Prentice-Hall, Englewood Cliffs
98. Green PE, Wind Y (1975) New ways to measure consumer judgments. Harvard Business Review 53(4):107-117
99. Greene WH (2003) Econometric analysis, 5th edn. Macmillan Publishing Company, New York
100. Haaijer R, Wedel M, Vriens M, Wansbeek T (1998) Utility covariances and context effects in conjoint mnp models. Mark Sci 17(3):236-252
101. Hair JF, Anderson RE, Tatham RL, Black WC (eds) (1998) Multivariate data analysis, 5th edn. Prentice Hall College Division, Upper Saddle River
102. Hausman J, McFadden D (1984) Specification tests for the multinomial logit model. Econometrica. J Econ Soc 52(5):1219-1240
103. Hedeker D, Gibbons RD (1994) A random-effects ordinal regression model for multilevel analysis. Biometrics 50(4):933-944
104. Hensher DA, Johnson LW (1981) Applied discrete choice modeling. Halsted Press, New York
105. Hoyle C, Chen W, Wang N, Gomez-Levi G (2011) Understanding and modelling heterogeneity of human preferences for engineering design. J Eng Des 22(8):583-601
106. Ihaka R, Gentleman R (1996) A language for data analysis and graphics. J Comput Gr Stat 5:299-314
107. Johnson RM (2011) Multiple discriminant analysis: marketing research application. In: Seth J (ed) Multivariate methods for market and survey research. Marketing Classics Press, Inc., Decatur, pp 65-82
108. Kim JG, Menzefricke U, Feinberg FM (2005) Modeling parametric evolution in a random utility framework. J Bus Econ Stat 23(3):282-295
109. Kim WJ, Lee JD, Kim TY (2005) Demand forecasting for multigenerational product combining discrete choice and dynamics of diffusion under technological trajectories. Technol Forecast Soc Chang 72(7):825-849
110. Koppelman F, Bhat C, Sethi V, Williams B (2006) A self instructing course in mode choice modeling: multinomial and nested logit models. U.S. Department of Transportation, Federal Transit Administration.
111. Koppelman FS, Sethi V (2000) Closed form discrete choice models. Handbook of Transport Modelling 1:211-222
112. Krueger RA (1994) Focus groups: a practical guide for applied research, 2nd edn. Thousand Oaks Sage Publications, California
113. Lave CA (1969) A behavioral approach to modal split forecasting. Trans Research 3:463-480
114. Lee B (1999) Calling patterns and usage of residential toll service under self selecting tariffs. J Regul Econ 16(1):45-82
115. Lee T, Bradlow E (2011) Automated marketing research using online customer reviews. J Mark Res 48 (Oct.):881-894
116. Li H, Azarm S (2000) Product design selection under uncertainty and with competitive advantage Transactions of ASME. J Mech Des 122(4):411-418
117. Lin H, Hoyle C, Chen W, Yannou B (2012) Choice Modeling for Usage Context-Based Design, J Mech Des 134(3)
118. Louviere JJ (1994) Conjoint analysis. In: Bagozzi R (ed) Handbook of marketing research. Blackwell Publishers, Oxford
119. Louviere JJ (1996) Combining revealed and stated preference data: the rescaling revolution. Paper presented at the association of environmental and resource economists, Lake Tahoe
120. Louviere JJ, Fox MF, Moore WL (1993) Cross-task validity comparisons of stated preference choice models. Mark Lett 4(3):205-213
121. Louviere JJ, Hensher DA, Swait JD (2000) Stated choice methods: analysis and application. Cambridge University Press, New York
122. Lu M (1999) Determinants of residential satisfaction: ordered logit vs. Regression models. Growth and Change 30(2):264-287
123. Luce RD (1959) Individual choice behavior: a theoretical analysis. Wiley, New York
124. MacDonald EF, Gonzalez R, Papalambros PY (2009) Preference inconsistency in multidisciplinary design decision making. J Mech Des 131(3):1-13
125. Marschak J (ed) (1960) Binary choice constraints on random utility indicators Stanford symposium on mathematical methods in the social sciences. Stanford University Press, Stanford
126. McCullagh P (1980) Regression models for ordinal data. J Roy Stat Soc: Ser B (Methodol) 42(2):109-142
127. McCutcheon AL (1987) Latent class analysis. Sage Publications, Beverly Hills
128. McFadden D (1974) Conditional logit analysis of qualitative choice behavior. In: Zarembka P (ed) Frontiers in econometrics. Academic Press, New York, pp 105-142
129. McKelvey RD, Zavoina W (1975) A statistical model for the analysis of ordinal level dependent variables. J Math Sociol 4(1):103-120
130. Michalek JJ, Ceryan O, Papalambros PY (2006) Balancing marketing and manufacturing objectives in product line design. J Mech Des 128:1196
131. Neelamegham R, Chintagunta P (1999) A bayesian model to forecast new product performance in domestic and international markets. Mark Sci 18(2):115-136
132. Norman DA (2002) The design of everyday things. Basic Books, New York
133. Norman DA (2004) Emotional design: why we love (or hate) everyday things. Basic Civitas Books, New York
134. Norton JA, Bass FM (1987) A diffusion theory model of adoption and substitution for successive generations of high-technology products. Manag Sci 33(9):1069-1086
135. Orsborn S, Cagan J, Boatwright P (2009) Quantifying aesthetic form preference in a utility function. J Mech Des 131(6):1-10
136. Otto KN, Wood K (2001) Product design: techniques in reverse engineering and new product development. Prentice Hall, Upper Saddle River
137. Raftery A (1995) Bayesian model selection in social research. Social Methodology 25:111-163
138. Rossi PE, Allenby GM (2003) Bayesian statistics and marketing. Mark Sci 22(3):304-328
139. Rossi PE, Allenby GM, McCulloch R (2005) Bayesian statistics and marketing. Wiley, Hoboken
140. Shiau C, Michalek J (2009) Optimal product design under price competition. J Mech Des 131(7):1-10
141. Small KA, Winston C (eds) (1999) The demand for transportation: models and applications. Chapter 2 of transportation policy and economics: a handbook in honor of john r. Meyer. Brookings Institution, Washington
142. Spiegelhalter DJ, Thomas A, Best NG, Lunn D (2003) Winbugs version 1.4. MRC Biostatistics Unit, Cambridge
143. Sullivan E, Ferguson S, Donndelinger JA (2011) Exploring differences in preference heterogeneity representation and their influence in product family design. Paper presented at the Proceedings of the 2011 ASME design engineering technical conferences and computers in engineering conference, Washington, 28-31
144. Tamhane AC, Ankenman BE, Yang Y (2002) The beta distribution as a latent response model for ordinal data (i): estimation of location and dispersion parameters. J Stat Comput Simul 72(6):473-494
145. Thurstone L (1927) A law of comparative judgment. Psychol Rev 34:273-286
146. Train K (1986) Qualitative choice analysis, theory, econometrics, and an application to automobile demand. MIT Press, Cambridge
147. Train K, McFadden D (2000) Mixed mnl models for discrete response. J Appl Econ 15(5):447-470
148. Train KE (2003) Discrete choice methods with simulation. Cambridge University Press, Cambridge
149. Train KE, McFadden DL, Ben-Akiva M (1987) The demand for local telephone service: a fully discrete model of residential calling patterns and service choices. Rand J Econ 18(1):109-123
150. Tversky A (1972) Elimination by aspects: a theory of choice. Psychol Rev 79:281-299
151. Walker J, Ben-Akiva M (2002) Generalized random utility model. Math Soc Sci 43(3): 303-343
152. Wang L, Youn BD, Azarm S, Kannan PK (2011) Customer-driven product design selection using web based user-generated content. Paper presented at the ASME 2011 international design engineering technical conferences, Washington 29-31
153. Warner SL (1962) Stochastic choice of mode in urban travel: a study in binary choice. Northwestern University Press, Evanston
154. Wassenaar HJ, Chen W (2003) An approach to decision-based design with discrete choice analysis for demand modeling Transactions of the ASME. J Mech Des 125(3):490-497
155. Wassenaar HJ, Chen W, Cheng J, Sudjianto A (2004) An integrated latent variable choice modeling approach to enhancing product demand modeling. In: Proceedings of the 2004 ASME DETC/CIE, Salt Lake City, Utah, 2004. ASME, New York
156. Wassenaar HJ, Chen W, Cheng J, Sudjianto A (2005) Enhancing discrete choice demand modeling for decision-based design. J Mech Des 127(4):514-523
157. Wassenaar HJ, Kumar D, Chen W (2006) Discrete choice demand modeling for decision- based design. In: Lewis K, Chen W, Schmidt L (eds) Decision making in engineering design. ASME Press, New York, pp 89-108
158. Wedel M, Kamakura WA (2000) Market segmentation: conceptual and methodological foundations. Kluwer Academic Publishers, Norwell
159. Williams H (1977) On the formation of travel demand models and econometric evaluation measures. Environ Plan 9:285-344
160. Arrow KJ (1963) Social choice and individual values. Wiley, New York
161. Arrow KJ, Raynaud H (1986) Social choice and multicriterion decision-making. MIT Press Books, Cambridge
162. Ben-Akiva M, Lerman SR (1985) Discrete choice analysis. The MIT Press, Cambridge
163. Breiman L, Spector P (1992) Sub-model selection and evaluation in regression: the x-random case. Int Stat Rev 60:291-319
164. Gossen HH (1854) The development of the laws of exchange among men and of the consequent rules of human action. MIT Press, Cambridge
165. Hazelrigg GA (1998) A framework for decision-based engineering design. J Mech Des 120(4):653-658
166. Kamrani AK, Nasr EA (2010) Engineering design and rapid prototyping. Springer, New York
167. Kurtoglu T, Campbell MI (2009) Automated synthesis of electromechanical design configurations from empirical analysis of function to form mapping. J Eng Des 20(1):83-104
168. Marder E (1997) The laws of choice, predicting customer behavior. The Free Press, New York
169. Marshall A (1920) Principles of economics: an introductory volume, 8th edn. Macmillan, London
170. Matthews LM (1983) Estimating manufacturing costs: a practical guide for managers and estimators. McGraw-Hill, New York
171. Mileham AR, Currie GC, Miles AW, Bradford DT (1993) A parametric approach to cost estimating at the conceptual stage of design. J Eng Des 4(2):117-125
172. Nicholson W (2000) Intermediate microeconomics and its application, 8th edn. Hartcourt, Orlando
173. Ricardo D (1815) An essay on the influence of a low price of corn on the profits of stock. John Murray, London
174. Shiba S, Graham A, Walden D (1993) New American TQM: Four practical revolutions in management. Productivity Press, Cambridge
175. Simpson TW, Maier JRA, Mistree F (2001) Product platform design: method and application. Res Eng Des 13(1):2-22
176. Stewart RD (1982) Cost estimating. Wiley, New York
177. Stone RB, Wood KL (2000) Development of a functional basis for design. J Mech Des 122(4):359-370
178. Thurston DL, Liu T (1991) Design evaluation of multiple attributes under uncertainty. Int J Syst Autom Res Appl 1(2):143-159
179. Ullman DG (2009) The mechanical design process. McGraw-Hill, Boston
180. Wassenaar HJ, Chen W (2003) An approach to decision-based design with discrete choice analysis for demand modeling. Trans ASME J Mech Des 125(3):490-497
181. Wassenaar HJ, Chen W, Cheng J, Sudjianto A (2005) Enhancing discrete choice demand modeling for decision-based design. J Mech Des 127(4):514-523
182. Altshuller GS, Williams A (1984) Creativity as an exact science: the theory of the solution of inventive problems. Gordon and Breach Science Publishers, New York
183. Bradley SR, Agogino AM (1994) Intelligent real time design methodology for component selection: An approach to managing uncertainty. J Mech Des 116(4):980-988
184. Chen W, Jin R, Sudjianto A (2005) Analytical variance-based global sensitivity analysisglobal sensitivity analysis in simulation-based design under uncertainty. J Mech Des 127(5):875-886
185. Clausing D, Hauser J (1988) The house of quality. Harv Bus Rev 66(3):63-73
186. Gershenson JK, Stauffer LA (1999) A taxonomy for design requirements from corporate customers. Res Eng Des 11(2):103—115
187. Goldberg DE (2002) The design of innovation: Lessons from and for competent genetic algorithms. Kluwer Academic Publishers, Berlin
188. Hauptmann P (1993) Sensors: principles and applications. Prentice Hall, Upper Saddle River
189. Hazelrigg GA (1996) The implications of arrow’s impossibility theorem on approaches to optimal engineering design. J Mech Des 118(2):161—164
190. Hoyle C, Chen W (2009) Product attribute function deployment (PAFD) for decision-based conceptual design. IEEE Trans Eng Manag 56(2):271-284
191. Louviere JJ, Hensher DA, Swait JD (2000) Stated choice methods: analysis and application. Cambridge University Press, New York
192. McAdams DA, Stone RB, Wood KL (1999) Functional interdependence and product similarity based on customer needs. Res Eng Des 11(1):1-19
193. Stone RB, Wood KL (2000) Development of a functional basis for design. J Mech Des 122(4):359-370
194. Suh NP (1990) The principles of design. Oxford University Press, New York
195. Tamhane AC, Dunlop DD (2000) Statistics and data analysis: From elementary to intermediate. Prentice Hall, Upper Saddle River
196. Atkinson AC, Donev AN (1992) Optimum experimental designs. Oxford University Press, Oxford
197. Box G, Bisgaard S, Fung C (1988) An explanation and critique of taguchi” contributions to quality engineering. Qual Reliab Eng Intern 4(2):123-131
198. Box GEP, Hunter JS, Hunter WG (2005) Statistics for experimenters: design, innovation, and discovery. Wiley, New York
199. Cox EP III (1980) The optimal number of response alternatives for a scale: a review. J. Mark. Res. 17(4):407-422
200. Fisher RA (1935) The design of experiments, 1st edn. Oliver & Boyd, Oxford
201. Goos P (2002) The optimal design of blocked and split-plot experiments. Springer-Verlag, New York
202. Goos P, Vandebroek M (2004) Outperforming completely randomized designs. J Qual Technol 36(1):12-26
203. Green PE, Krieger AM, Agarwal MK (1991) Adaptive conjoint analysis: some caveats and suggestions. J. Mark. Res. 28(2):215-222
204. Green PE, Rao VR (1970) Rating scales and information recovery. How many scales and response categories to use? J Mark 34(3):33-39
205. Hensher DA, Rose JM, Greene WH (2005) Applied choice analysis: a primer. Cambridge Univ Press, Cambridge
206. Hines R (1997) Analysis of clustered polytomous data using generalized estimating equations and working covariance structures. Biometrics 53(4):1552-1556
207. Hines R (1998) Comparison of two covariance structures in the analysis of clustered polytomous data using generalized estimating equations. Biometrics 54(1):312-316
208. Hoyle C, Chen W, Ankenman B, Wang N (2009) Optimal experimental design of human appraisals for modeling consumer preferences in engineering design. J. Mech. Des. 131(7):98-107
209. Johnson VE, Albert JH (1999) Ordinal data modeling. Springer, New York
210. Kessels R, Goos P, Vandebroek M (2006) A comparison of criteria to design efficient choice experiments. J. Mark. Res. 43(3):409-419
211. Kessels R, Goos P, Vandebroek M (2008) Optimal designs for rating-based conjoint experiments. Comput. Stat. Data Anal. 52(5):2369-2387
212. Kessels R, Jones B, Goos P, Vandebroek M (2009) An efficient algorithm for constructing Bayesian optimal choice designs. J Bus Econ Stat 27(2):279-291
213. Kuhfeld WF, Tobias RD, Garratt M (1994) Efficient experimental design with marketing research applications. J. Mark. Res. 31(4):545-557
214. Liang K, Zeger SL (1986) Longitudinal data analysis using generalized linear models. Biometrika 73(1):13-22
215. Louviere JJ (2006) What you don’t know might hurt you: some unresolved issues in the design and analysis of discrete choice experiments. Environ Resour Econ 34(1):173-188
216. Louviere JJ, Hensher DA, Swait JD (2000) Stated choice methods: analysis and application. Cambridge University Press, New York
217. Louviere JJ, Islam T, Wasi N, Street D, Burgess L (2008) Designing discrete choice experiments: do optimal designs come at a price? J Consum Res: An Interdiscip Q 35(2):360- 375
218. Mason RL, Gunst RF, Hess JL (2003) Statistical design and analysis of experiments: with applications to engineering and science. Wiley Series in Probability and Statistics, New York
219. McCullagh P (1980) Regression models for ordinal data. J. Roy. Stat. Soc.: Ser. B (Methodol.) 42(2):109-142
220. McKelvey RD, Zavoina W (1975) A statistical model for the analysis of ordinal level dependent variables. J Math Sociol 4(1):103-120
221. Montgomery DC (2005) Design and analysis of experiments. John Wiley and Sons, Inc., New York
222. Myers RH, Montgomery DC (2002) Response surface methodology: process and product in optimization using designed experiments. John Wiley & Sons, Inc., New York, NY
223. Phadke MS (1995) Quality engineering using robust design. Prentice Hall, Upper Saddle River
224. Sandor Z, Wedel M (2001) Designing conjoint choice experiments using managers prior beliefs. J. Mark. Res. 38(4):430-444
225. Society of Automotive Engineers Society of Automotive Engineers (2002) Surface vehicle recommended practice-motor vehicle dimensions. SAE J1100. Warrendale, Pennsylvania
226. Steckel JH, DeSarbo WS, Mahajan V (1991) On the creation of acceptable conjoint analysis experimental designs. Decis Sci 22(2):435-442
227. Stevens SS (1986) Psychophysics: introduction to its perceptual, neural, and social prospects. Transaction Publishers, New Brunswick
228. Street DJ, Burgess L (2007) The construction of optimal stated choice experiments: theory and methods. Wiley-Interscience, Hoboken
229. Taguchi G (1988) Introduction to quality engineering: designing quality into products and processes. Asian Productivity Organization, Tokyo
230. Tamhane AC, Dunlop DD (2000) Statistics and data analysis: from elementary to intermediate. Prentice Hall, Upper Saddle River
231. Train KE (2003) Discrete choice methods with simulation. Cambridge University Press, Cambridge
232. Wang N, Kiridena V, Gomez-Levi G, Wan J (2006) Design and verification of a new computer controlled seating buck. Paper presented at the Proceedings of the 2006 ASME IDETC/CIE, Philadelphia, Pennsylvania, September 10-13
233. Williamson JM, Kim K, Lipsitz SR (1995) Analyzing bivariate ordinal data using a global odds ratio. J Am Stat Assoc 90(432):1432-1437
234. Yu J, Goos P, Vandebroek M (2009) Efficient conjoint choice designs in the presence of respondent heterogeneity. Marke Sci 28(1):122-135
235. Zorn CJW (2001) Generalized estimating equation models for correlated data: a review with applications. Am J Political Sci 45(2):470-490
236. Hunter JS, Hunter WG (2005) Statistics for experimenters: design, innovation, and discovery. Wiley, New York
237. Breiman L, Friedman JH, Olshen RA, Stone CJ (1984) Classification and regression trees. Wadsworth and Brooks, Monterey
238. Cortina JM (1993) What is coefficient alpha? An examination of theory and applications. J Appl Psychol 78(1):98-104
239. Fisher RA (1925) Statistical methods for research workers. Oliver and Boyd, Edinburgh
240. Greenleaf EA (1992) Improving rating scale measures by detecting and correcting bias components in some response styles. J Mark Res 29(2):176-188
241. Hoyle C, Chen W, Wang N, Gomez-Levi G (2011) Understanding and modelling heterogeneity of human preferences for engineering design. J Eng Des 22(8):583-601
242. Johnson RA, Wichern DW (2007) Applied multivariate statistical analysis, 6th edn. Prentice Hall, Upper Saddle River
243. Keeney RL, Raiffa H (1993) Decisions with multiple objectives: preferences and value tradeoffs. Cambridge University Press, New York
244. McCutcheon AL (1987) Latent class analysis. Sage Publications, Beverly Hills
245. Montgomery DC (2005) Design and analysis of experiments. Wiley, New York
246. Pearl J (1988) Probabilistic reasoning in intelligent systems: networks of plausible inference. Morgan Kaufmann, San Francisco
247. Rossi PE, Gilula Z, Allenby GM (2001) Overcoming scale usage heterogeneity: a bayesian hierarchical approach. J Am Stat Assoc 96(453):20-31
248. Stevens SS (1986) Psychophysics: introduction to its perceptual, neural, and social prospects. Transaction Publishers, New Brunswick
249. Train KE (2003) Discrete choice methods with simulation. Cambridge University Press, Cambridge
250. Wang N, Wan J, Gomez-Levi G, Kiridena V, Sieczka S (2007) An integrated design and appraisal system for vehicle interior packaging. In: Body engineering and design, glass applications, corrosion prevention and design tools. SAE International, Detroit, pp 100-109
251. Witten IH, Frank E (2005) Data mining: practical machine learning tools and techniques. Morgan Kaufmann, San Francisco
252. Wood SN (2004) Mgcv: gams with gcv smoothness estimation and gamms by reml/pql. R Foundation for Statistical Computing, Vienna
253. Allenby G, Fennell G, Huber J, Eagle T, Gilbride T, Horsky D, Kim J, Lenk P, Johnson R, Ofek E (2005) Adjusting choice models to better predict market behavior. Mark Lett 16(3):197-208
254. Ben-Akiva M, Lerman SR (1985) Discrete choice analysis. MIT Press, Cambridge
255. Brooks SP, Roberts GO (1998) Assessing convergence of markov chain monte carlo algorithms. Stat Comput 8(4):319-335
256. Brownstone D, Bunch DS, Train K (2000) Joint mixed logit models of stated and revealed preferences for alternative-fuel vehicles. Transp Res Part B 34(5):315-338
257. Edmunds Inc (1995-2007) www.Edmunds.Com. Accessed Sept 21 2007
258. Erdem T, Keane MP (1996) Decision-making under uncertainty: capturing dynamic brand choice processes in turbulent consumer goods markets. Mark Sci 15(1):1-20
259. Gelman A, Carlin JB, Stern HS, Rubin DB (2004) Bayesian data analysis, vol 25. Texts in statistical science. Chapman and Hall, Boca Raton
260. Hamza K, Hossoy I, Reyes-Luna JF, Papalambros PY (2004) Combined maximisation of interior comfort and frontal crashworthiness in preliminary vehicle design. Int J Veh Des 35(3):167-185
261. Hedeker D, Gibbons RD (1994) A random-effects ordinal regression model for multilevel analysis. Biometrics 50(4):933-944
262. Hoyle C, Chen W, Ankenman B, Wang N (2009) Optimal experimental design of human appraisals for modeling consumer preferences in engineering design. J Mech Des 131(7):98-107
263. Hoyle C, Chen W, Wang N, Koppelman FS (2010) Integrated bayesian hierarchical choice modeling to capture heterogeneous consumer preferences in engineering design. J Mech Des 132(12):1-11
264. Ihaka R, Gentleman R (1996) R: a language for data analysis and graphics. J Comput Graph Stat 5:299-314
265. Johnson VE, Albert JH (1999) Ordinal data modeling. Springer, New York
266. Kumar D (2007) Demand modeling for enterprise-driven product design. Ph.D. Dissertation, Northwestern University, Evanston
267. Kumar D, Hoyle C, Chen W, Wang N, Gomez-Levi G, Koppelman F (2009) A hierarchical choice modelling approach for incorporating customer preferences in vehicle package design. Int J Prod Dev 8(3):228-251
268. Lancaster T (2004) An introduction to modern bayesian econometrics. Blackwell Publishing, Oxford
269. Louviere JJ, Hensher DA, Swait JD (2000) Stated choice methods: analysis and application. Cambridge University Press, New York
270. Neelamegham R, Chintagunta P (1999) A bayesian model to forecast new product performance in domestic and international markets. Mark Sci 18(2):115-136
271. Noui-Mehidi A (1997) Applying constraints to vehicle packaging. Customer Papers, ILOG Corporation
272. Parkinson MB, Reed MP, Kokkolaras M, Papalambros PY (2007) Optimizing truck cab layout for driver accommodation. J Mech Des 129(11):1-8
273. Rossi PE, Allenby GM (2003) Bayesian statistics and marketing. Mark Sci 22(3):304-328
274. Rossi PE, Allenby GM, McCulloch R (2005) Bayesian statistics and marketing. Wiley, Hoboken
275. Society of Automotive Engineers (2002) Surface vehicle recommended practice-motor vehicle dimensions. SAE J1100. Warrendale, Pennsylvania
276. Spiegelhalter DJ, Thomas A, Best NG, Lunn D (2003) Winbugs version 1.4. MRC Biostatistics Unit, Cambridge, UK
277. Suh ES, de Week OL, Chang D (2007) Flexible product platforms: framework and case study. Res Eng Des 18(2):67-89
278. Tamhane AC, Dunlop DD (2000) Statistics and data analysis: from elementary to intermediate. Prentice Hall, Upper Saddle River
279. Train KE (2003) Discrete choice methods with simulation. Cambridge University Press, Cambridge
280. Varian HR (1995) The information economy. Sci Am 273(3):200-202
281. Ben-Akiva M, Walker J, Bernardino AT, Gopinath DA, Morikawa T, Polydoropoulou A (2002) Integration of choice and latent variable models. In: Mahmassani E (ed) In perpetual motion: travel behaviour research opportunities and application challenges. Elsevier Science, Amsterdam, pp 431-470
282. Bentler PM (1980) Multivariate analysis with latent variables. Annu Rev Psychol 31:419-456
283. Congdon P (2003) Applied Bayesian modelling. Wiley, Chichester
284. Everitt BS (1984) An introduction to latent variable models (monographs on applied probability and statistics). Chapman & Hall, London
285. Gelman A, Carlin JB, Stern HS, Rubin DB (2004) Bayesian data analysis, vol 25. Texts in statistical science. Chapman & Hall, Boca Raton
286. Hair JF, Anderson RE, Tatham RL, Black WC (eds) (1998) Multivariate data analysis, 5th edn. Prentice Hall College Division, Upper Saddle River
287. Joreskog KG (ed) (1973) A general method for estimating a linear structural equation system. Structural models in the social sciences. Academic Press, New York
288. Keesling JW (1972) Maximum likelihood approaches to causal analysis. Dissertation, University of Chicago, Chicago
289. Koppelman F, Hauser J (1979) Destination choice for non-grocery-shopping trips. Transp Res Rec 673:157-165
290. Loehlin JC (1998) Latent variable models, an introduction to factor, path, and structural analysis, 3rd edn. L. Erlbaum Associates, Mahwah
291. McFadden D (1997) Rationality for economists. In: NSF symposium on eliciting preferences, Berkeley, July 1997
292. Prashker JA (1979) Mode choice models with perceived reliability measures. Transp Eng J 105(3):251-262
293. Wiley DE (1973) The identification problem for structural equation models with unmeasured variables. In: Goldberger AS, Duncan OD (eds) Structural models in the social sciences. Academic Press, New York
294. Axsen J, Burke A et al (2008) Batteries for plug-in hybrid electric vehicles (PHEVs): goals and the state of technology circa 2008. Institute of Transportation Studies, University of California Davis, Davis
295. Belk R (1974) An exploratory assessment of situational effects in buyer behavior. J Mark Res 11(2):156-163
296. Belk R (1975) Situational variable and consumer behavior. J Consum Res 2:157-164
297. Berkowitz E, Ginter J et al (1977) An investigation of the effects of specific usage situations on the prediction of consumer choice behavior. In: Educators’ Proceedings, American Marketing Association, Chicago
298. Christensen C, Cook S et al (2005) Marketing malpractice: the cause and the cure. Harv Bus Rev 83(12):74
299. De la Fuente J, Guillen M (2005) Identifying the influence of product design and usage situation on consumer choice. Int J Mark Res 47(6):667
300. Dickson P (1982) Person-situation: segmentation’s missing link. J Mark 46(4):56-64
301. Ehsani M, Gao Y et al (2009) Modern electric, hybrid electric, and fuel cell vehicles: fundamentals, theory, and design. CRC Press, Boca Raton
302. Engel J, Kollat D et al (1969) Personality measures and market segmentation: evidence favors interaction view. Bus Horiz 12(3):61-70
303. EPA UEPA (2008) Fuel economy guide 2008
304. Goldberg PK (1995) Product differentiation and oligopoly in international markets: the case of the US automobile industry. Econom J Econom Soc 63:891-951
305. Green MG, Linsey JS et al (2006) Frontier design: a product usage context method. 2006 ASME design engineering technical conference, Philadelphia
306. Green MG, Palani RPK et al (2004) Product usage context: improving customer needs gathering and design target setting. 2004 ASME design engineering technical conference, Salt Lake City
307. Green MG, Tan J et al (2005) Effects of product usage context on consumer product preferences. 2005 IDETC/CIE Conference, Long Beach
308. Hartigan JA, Wong MA (1979) Algorithm AS 136: a k-means clustering algorithm. J Royal Stat Soc Ser C (Appl Stat) 28(1):100-108
309. He L, Chen W (2011) Usage context-based choice modeling for hybrid electric vehicles. International conference on engineering design, Contribution 155, Copenhagen
310. He L, Hoyle C, Chen W, Yannou B (2012) Choice modeling for usage context-based Design, ASME J Mech Des 134(3)
311. He L, Hoyle C et al (2011) Examination of customer satisfaction surveys in choice modelling to support engineering design. J Eng Des 22(10):669-687
312. Hoyle C, Chen W et al (2009) Optimal experimental design of human appraisals for modeling consumer preferences in engineering design. J Mech Des 131(7):98-107
313. Hoyle C, Chen W et al (2011) Understanding and modeling heterogeneity of human preferences for engineering design. J Eng Des 22(8):583-601
314. Kroes EP, Sheldon RJ (1988) Stated preference methods: an introduction. J Transp Econ Policy 22(1):11-25
315. Lavidge R (1966) The cotton candy concept: intra-individual variability. In: Adler L, Crespi I (eds) Attitude research at sea. American Marketing Association, Chicago, pp 39-50
316. Louviere JJ, Hensher DA et al (2000) Stated choice methods: analysis and application. Cambridge University Press, New York
317. McCullagh P (1980) Regression models for ordinal data. J Royal Stat Soc Ser B (Methodol) 42(2):109-142
318. Ratneshwar S, Shocker A (1991) Substitution in use and the role of usage context in product category structures. J Mark Res 28(3):281-295
319. Robertson T, Ward S (1973) Consumer behavior research: promise and prospects. In: Robertson T, Ward S (eds) Consumer behavior: theoretical sources. Englewood Cliffs, Prentice-Hall, pp 3-42
320. Samuelson PA (1948) Consumption theory in terms of revealed preference. Economica 15(60):243-253
321. Shiau C, Samaras C et al (2009) Impact of battery weight and charging patterns on the economic and environmental benefits of plug-in hybrid vehicles. Energy Policy 37(7):2653- 2663
322. Simonson I, Tversky A (1992) Choice in context: tradeoff contrast and extremeness aversion. J Mark Res 29(3):281-295
323. Stefflre V (1971) New products and new enterprises: a report of an experiment in applied social science. University of California, Irvine
324. Ulrich K, Eppinger S (2003) Product design and development. McGraw-Hill, New York
325. Yannou B, Wang J et al (2009) Usage coverage model for choice modeling: principles and taxonomy. 2009 ASME design engineering technical conferences, San Diego
326. Yannou B, Wang J et al (2010) Computation of the usage contexts coverage of a jigsaw with CSP techniques. 2010 ASME design engineering technical conferences, Montreal
327. Aboulafia R (2000) Airbus pulls closer to Boeing. Aerosp Am (0740-722 X) 38(4):16-18
328. Bremmer R (1999) Cutting-edge platforms. Financial Times Automotive World, pp 30-38
329. Chapman SJ (1991) Electric machinery fundamentals. McGraw Hill, New York
330. Chen KD, Hausman WH (2000) Technical note: mathematical properties of the optimal product line selection problem using choice-based conjoint analysis. Manag Sci 46(2):327-332
331. Choi SC, DeSarbo WS (1994) A conjoint-based product designing procedure incorporating price competition. J Prod Innov Manag 11(5):451-459
332. Coleman T, Branch MA, Grace A (1999) Optimization toolbox for use with matlab: user’s guide, version 2. The Math Works, Natick
333. Dai Z, Scott MJ (2006) Effective product family design using preference aggregation. J Mech Des 128(4):659-667
334. Dai Z, Scott MJ (2007) Product platform design through sensitivity analysis and cluster analysis. J Intell Manuf 18(1):97-113
335. Dobson G, Kalish S (1993) Heuristics for pricing and positioning a product-line using conjoint and cost data. Manag Sci 39(2):160-175
336. Farrell RS, Simpson TW (2003) Product platform design to improve commonality in custom products. J Intell Manuf 14(6):541-556
337. Fellini R, Kokkolaras M, Papalambros P, Perez-Duarte A (2005) Platform selection under performance bounds in optimal design of product families. J Mech Des 127(4):524-535
338. Fruchter GE, Fligler A, Winer RS (2006) Optimal product line design: genetic algorithm approach to mitigate cannibalization. J Optim Theory Appl 131(2):227-244
339. Green PE, Krieger AM (1991) Segmenting markets with conjoint analysis. J Mark 55(4):20-31
340. Halman JIM, Hofer AP, van Vuuren W (2003) Platform-driven development of product families: linking theory with practice. J Prod Innov Manag 20(2):149-162
341. Jiao J, Zhang Y, Wang Y (2007) A generic genetic algorithm for product family design. J Intell Manuf 18(2):233-247
342. Kim K, Chhajed D (2000) Commonality in product design: cost saving, valuation change and cannibalization. Eur J Oper Res 125(3):602-621
343. Kima K, Chhajed D (2001) An experimental investigation of valuation change due to commonality in vertical product line extension. J Prod Innov Manag 18(4):219-230
344. Kumar D, Chen W, Simpson TW (2009) A market-driven approach to the design of platform- based product families. Int J Prod Res 47(1):71-104
345. Lehnerd AP (1987) Revitalizing the manufacture and design of mature global products. In: Guile BR, Brooks H (eds) Technology and global industry: companies and nations in the world economy. National Academies Press, Washington DC, pp 49-64
346. Li H, Azarm S (2002) An approach for product line design selection under uncertainty and competition. J Mech Des (Trans ASME) 124(3):385-392
347. Lilien GL, Rangaswamy A (2004) Marketing engineering: computer-assisted marketing analysis and planning. Trafford Publishing, Victoria
348. Marion TJ, Simpson TW (2006) Platform leveraging strategies and market segmentation. In: Simpson TW, Siddique Z, Jiao RJ (eds) Product platform and product family design: methods and applications. Springer, New York, pp 73-90
349. Mazanec JA (1984) How to detect travel market segments: a clustering approach. J Travel Res 23(1):17-21
350. Messac A, Martinez MP, Simpson TW (2002) Effective product family design using physical programming. Eng Optim 34(3):245-261
351. Messac A, Martinez MP, Simpson TW (2002) A penalty function for product family design using physical programming. ASME J Mech Des 124(2):164-172
352. Meyer MH, Lehnerd AP (1997) The power of product platforms: building value and cost leadership. Free Press, New York
353. Michalek JJ, Ceryan O, Papalambros PY, Koren Y (2006) Balancing marketing and manufacturing objectives in product line design. Trans ASME J Mech Des 128(6):1196-1204
354. Michalek JJ, Feinberg FM, Papalambros PY (2005) Linking marketing and engineering product design decisions via analytical target cascading. J Prod Innov Manag 22(1):42-62
355. Miller S (1999) Vw sows confusion with common pattern for models—investors worry profits may suffer as lines compete, vol A.25. Wall Street Journal, New York
356. Miller S (2002) Volkswagen to overhaul audi brand—effort is first step by european car maker to shed conservative image, vol D.8. Wall Street Journal, New York
357. Moore WL, Louviere JJ, Verma R (1999) Using conjoint analysis to help design product platforms. J Prod Innov Manag 16(1):27-39
358. Nair SK, Thakur LS, Wen KW (1995) Near optimal solutions for product line design and selection: beam search heuristics. Manag Sci 41(5):767-785
359. Nayak RU, Chen W, Simpson TW (2002) A variation-based method for product family design. Eng Optim 34(1):65-81
360. Pine BJ (1993) Mass customization: The new frontier in business competition. Harvard Business School Press, Boston, MA
361. Robertson D, Ulrich K (1998) Planning for product platforms. Sloan Manag Rev 39(4):19-31
362. Simpson T (2006) Methods for optimizing product platforms and product families. In: Simpson TW, Siddique Z, Jiao RJ (eds) Product platform and product family design: methods and applications. Springer, New York, pp 133-156
363. Simpson TW (2005) Product platform design and customization: status and promise. AIEDAM 18(01):3-20
364. Simpson TW, D'Souza BS (2004) Assessing variable levels of platform commonality within a product family using a multiobjective genetic algorithm. Concurr Eng 12(2):119-129
365. Simpson TW, Maier JRA, Mistree F (2001) Product platform design: method and application. Res Eng Des 13(1):2-22
366. Suh ES, de Weck OL, Chang D (2007) Flexible product platforms: framework and case study. Res Eng Des 18(2):67-89
367. Veinott CG, Martin JE (1986) Fractional and subfractional horsepower electric motors: available types, basic operating principles, selection, and maintenance. McGraw-Hill, New York
368. Vellido A, Lisboa PJG, Meehan K (1999) Segmentation of the on-line shopping market using neural networks. Expert Syst Appl 17(4):303-314
369. Wedel M, Kamakura WA (2000) Market segmentation: conceptual and methodological foundations, 2nd edn. Kluwer Academic Publishers, Norwell
370. Wilhelm B (1997) Platform and modular concepts at volkswagen-their effects on the assembly process. In: Shimokawa K, Jürgens U, Fujimoto T (eds) Transforming automobile assembly: experience in automation and work organization. Springer, Berlin, pp 146-156
371. Williams HCWL (1977) On the formation of travel demand models and econometric evaluation measures. Environ Plan A 9(3):285-344
372. Zufryden F (1979) A conjoint-measurement-based approach to optimal new product design and market segmentation. In: Shocker A (ed) Analytical approaches to product and market planning. Marketing Science Institute, Cambridge, pp 100-114
373. Ben-Akiva M, Lerman SR (1985) Discrete choice analysis: theory and application to travel demand. MIT Press, Cambridge
374. Binder AK (ed) (2000) Ward’s automotive yearbook 2000. Wards Communications, Detroit, MI
375. Braun RD (1996) Collaborative optimization: an architecture for large-scale distributed design. PhD Thesis, Stanford University, Stanford, CA
376. Gu X, Renaud JE, Ashe LM, Batill SM, Budhiraja AS, Krajewski LJ (2002) Decision-based collaborative optimization. J Mech Des (Trans ASME) 124 (1):1-13
377. Hogland DK, Mousseau CW (2001) A parametric model to generate subsystem constitutive laws for a vehicle ride model. SAE Trans 110(7):69-77
378. Keeney RL, Raiffa H (1993) Decisions with multiple objectives: Preferences and value tradeoffs. Cambridge University Press, New York
379. Kim HM, Kokkolaras M, Louca LS, Delagrammatikas GJ, Michelena NF, Filipi ZS, Papalambros PY, Stein JL, Assanis DN (2002) Target cascading in vehicle redesign: a class VI truck study. Int J Veh Des 29(3):199-225
380. Kim HM, Kumar D, Chen W, Papalambros PY (2006) Target exploration for disconnected feasible regions in enterprise-driven hierarchical multilevel product design. AIAA J 44(1):67-77
381. Kim HM, Michelena NF, Papalambros PY, Jiang T (2003a) Target cascading in optimal system design. J Mech Des (Trans ASME) 125(3):474-480
382. Kim HM, Rideout DG, Papalambros PY, Stein JL (2003b) Analytical target cascading in automotive vehicle design. J Mech Des (Trans ASME) 125(3):481-489
383. Kroo I (1997) Multidisciplinary optimization applications in preliminary design: status and directions. Paper presented at the 38th AIAA/ASME/ASCE/AHS/ASC structures, structural dynamics, and materials conference and exhibit and AIAA/ASME/AHS adaptive structures forum, Kissimmee, FL, 7-10 April
384. Michalek JJ, Feinberg FM, Papalambros PY (2005) Linking marketing and engineering product design decisions via analytical target cascading. J Prod Innov Manag 22(1):42-62
385. Shi L, Olafsson S, Chen Q (2001) An optimization framework for product design. Manag Sci 47(12):1681-1692
386. Sobieszczanski-Sobieski J, Agte JS, Sandusky RR (2000) Bilevel integrated system synthesis. AIAA J 38(1):164-172
387. Sobieszczanski-Sobieski J, Altus TD, Phillips M, Sandusky R (2002) Bi-level integrated system synthesis (bliss) for concurrent and distributed processing. AIAA J 41(10):1996-2003
388. Stata Corporation (2003) Stata [statistical software]: Release 9. Stata Press, College Station, TX
389. Train KE (2003) Discrete choice methods with simulation. Cambridge University Press, Cambridge
390. Wujek BA, Renaud JE, Batill SM, Brockman JB (1996) Concurrent subspace optimization using design variable sharing in a distributed computing environment. Concurrent Eng 4(4):361-377
391. Bass FM (2004) A new product growth for model consumer durables. Manag Sci 50(13):1825-1832
392. Hurwicz L (1973) The design of mechanisms for resource allocation. Am Econ Rev 63(2): 1-30
393. Kano N, Seraku N, Takahashi F, Tsuji S (1984) Attractive quality and must-be quality. J Jpn Soc Qual Control 14(2):39-48
394. Kanter RM (2006) Innovation: the classic traps. Harv Bus Rev 84(11):72-83
395. Mariampolski H (2006) Ethnography for marketers: a guide to consumer immersion. Sage Publications, Inc., Thousand Oaks
396. Marshall A (1920) Principles of economics: an introductory volume, 8th edn. Macmillan and Co. Ltd., London
397. Maskin ES (2008) Mechanism design: how to implement social goals. Am Econ Rev 98(3):567-576
398. Monge PR, Contractor NS (2003) Theories of communication networks. Oxford University Press, New York
399. Morrow WR, Skerlos SJ (2011) Fixed-point approaches to computing bertrand-nash equilibrium prices under mixed logit demand. Oper Res 59(2):328-345
400. Myerson RB (2008) Perspectives on mechanism design in economic theory. Am Econ Rev 98(3):586-603
401. National Science Foundation (2010) Report on NSF engineering systems design workshop. February 22-24, at vddi.org/ESDW-report.pdf
402. North MJ, Macal CM (2007) Managing business complexity: discovering strategic solutions with agent-based modeling and simulation. Oxford University Press, New York
403. Ramani K, Ramanujan D, Bernstein WZ, Zhao F, Sutherland J, Handwerker C, Choi JK, Kim H, Thurston D (2010) Integrated sustainable life cycle design: a review. J Mech Des 132(9):1-15
404. Resende CB, Heckmann CG, Michalek JJ (2011) Robust design for profit maximization under uncertainty of consumer choice model parameters using the delta method. Paper presented at the Proceedings of the 2011 ASME Design Engineering Technical Conferences and Computers in Engineering Conference, Washington, August 28-31
405. Shah JJ, Finger S, Lu S, Leifer L, Cruz-Neira C, Wright P, Cagan J, Vandenbrande J (2004) ED2030: strategic plan for engineering design. In: Report on NSF Workshop, Arizona, March 26-29
406. Shiau CSN, Michalek JJ (2009) Should designers worry about market systems? J Mech Des 131(1):1-9
407. Simpson TW, Martins JRA (2010) The future of multidisciplinary design optimization (MDO): advancing the design of complex engineered systems. NSF Workshop September 15-16