An Optimal Design Search with Conjoint Analysis Using Genetic Algorithm

Jeng-Jong Lin

doi:10.6180/jase.2008.11.1.10

An Optimal Design Search with Conjoint Analysis Using Genetic Algorithm

Computer Science and Information Engineering

Jeng-Jong Lin This email address is being protected from spambots. You need JavaScript enabled to view it.¹

¹Department of Information Management, Vanung University, Tao-Yuan, Taiwan 320, R.O.C.

Received: June 3, 2006
Accepted: May 9, 2007
Publication Date: March 1, 2008

Download Citation: ||https://doi.org/10.6180/jase.2008.11.1.10

ABSTRACT

It is important for the R&D division to develop a product, which satisfies both the designer and the consumer. An integrated design model based on conjoint analysis can find several feasible solutions to combinations of design parameters in product designing. In this study, a relationship matrix is used to keep the characteristics of designer and the attributes of consumer related with one another. Along with the increasing number of the characteristics and attributes, there are more solutions to combination sets of product design with conjoint analysis. It becomes increasingly difficult using obtained conjoint data to evaluate product design that involve many characteristics, attributes and levels based on a discipline of “satisfy the most under the least sacrifice”. The applicability of conjoint analysis is improved by using a genetic algorithm (GA) to help search the possible combination sets between levels of characteristics and those of attributes. The experiment results show it is promising for us to use GA in searching the solutions to complex design problem.

Keywords: Conjoint Analysis, Integrated Design Model, Genetic Algorithm, Design Characteristics, Design Attributes

REFERENCES

[1] Carr, H. and Pomeroy, J., Fashion Design and Product Development, Chinese Language edition, Blackwell Publishers, Taipei, R.O.C. (1999).
[2] Hauser, J. R. and Clausing, D., “The House of Quality,” Harvard Business Review, Vol. 66, pp. 6373 (1998).
[3] Green, P. E. and Rao, V. R., “Conjoint Measurement for Quantifying Judgmental Data,” J. Marketing Res., Vol. 8, pp. 353363 (1971).
[4] Zong, T. S., Applying EXCEL to Expertizing in Marketing Research, Wu Naing Publishers, Taipei, R.O.C. (2004).
[5] Wittink, D. R. and Cattin, P., “Commercial Use of Conjoint Analysis: An Update,” J. Marketing, Vol. 53, pp. 9196 (1989).
[6] Wittink, D. R., Vriens, M. and Burhenne, W., “Commercial Use of Conjoint Analysis in Europe: Results and Critical Reflections,” Int. J. Res. Marketing, Vol. 11, pp. 4152 (1994).
[7] Zufryden, F. S., “A Conjoint Measurement-Based Approach for Optimal New Product Design And Market Segmentation,” in Analytic Approaches to Product and Market Planning, Alan D. Shocker (Ed.), Marketing Science Institute, Cambridge, MA, pp. 100114 (1977).
[8] Kohli, R. and Krishnamurti, R., “A Heuristic Approach to Product Design,” Vol. 33, pp. 15231533 (1987).
[9] Wind, J., Green, P. E., Shifflet, D. and Scarbrough, M., “Courtyard by Marriott: Designing a Hotel Facility with Customer-Based Marketing Models,” INTERFACES, Vol. 19, pp. 2547 (1989).
[10] Tscheulin, D. K. and Helmig, B., “The Optimal Design of Hospital Advertising by Means of Conjoint Measurement,” Journal of Advertising Research, Vol. 38, pp. 3546 (1998).
[11] Balakrishnan, P. V. and Jacob, V. S., “Triangulation in Decision Support Systems: Algorithms for Product Design,” Decision Support System, Vol. 14, pp. 313 327 (1995).
[12] Balakrishnan, P. V. and Jacob, V. S., “Genetic Algorithms for Product Design,” Management Science, Vol. 42, pp. 11051117 (1996).
[13] Srinivasan, V., Lovejoy, W. S. and Beach, D., “Integrated Product Design for Marketability and Manufacturing,” Journal of Marketing Research, Vol. 34, pp. 154163 (1997).
[14] Addelman, S., “Orthogonal Main-Effect Plans for Asymmetrical Factorial Experiments,” Technometrics, Vol. 4, pp. 2146 (1962a).
[15] Addelman, S., “Symmetrical and Asymmetrical Factorial Plans,” Technometrics, Vol. 4, pp. 4758 (1962b).
[16] Takashi, S., Premier to Questionnaire Design for Market Research and Statistic Analysis, DrMaster Press Co., Ltd., Taipei, R.O.C. (2004).
[17] Cosgrave, B., Costume and Fashion: A Complete History., Hamlyn, London, pp. 214250 (2003).
[18] Goldberg, D. E., Genetic Algorithms in Search, Optimization & Machine Learning, Addision-Wesley, NY (1989).