A systematic new product development methodology for creating affective products

  • Authors

    • Sa'Ed M. Salhieh Ph. D. The University of Jordan
    2018-10-14
    https://doi.org/10.14419/ijet.v7i4.19617
  • Affective Design, Kansei Engineering, Marketing, New Product Development, Perceptual Mapping.
  • The success of new product development (NPD) relies on the effective integration of marketing and engineering especially when the development is targeted at creating new products capable of satisfying customer needs generated by feelings, attitudes, and emotions. Such products can be called affective products. This paper introduces a systematic new product development methodology that integrates the processes needed to elicit both tangible/objective and intangible/affective customer needs and translates those needs into product parameters to be used in the development of new products that meet both the customer functional and affective needs. The methodology begins by identifying customer tangible and intangibles needs, then translates those needs into metrics. Next, perceptual mapping is used to determine initial specification and select a new position for the new product. After that, new product concepts are generated and tested. The methodology is illustrated using a case-study application of new pen development.

     

     

     

  • References

    1. [1] M. Nagamachi, Kansei engineering: a new ergonomic consumer-oriented technology for product development, International Journal of Industrial Ergonomics 15, 1 (1995) 3–11. https://doi.org/10.1016/0169-8141(94)00052-5

      [2] J. F. Petiota, B. Yannoub, Measuring consumer perceptions for a better comprehension, specification and assessment of product semantics. International Journal of Industrial Ergonomics, 33,6 (2004) 507-525. https://doi.org/10.1016/j.ergon.2003.12.004

      [3] J. Park, S. H. Han, A fuzzy rule-based approach to modeling affective user satisfaction towards office chair design, International Journal of Industrial Ergonomics 34, 1 (2004): 31–47. https://doi.org/10.1016/j.ergon.2004.01.006

      [4] S. Schütte, Engineering emotional values in product design: Kansei engineering in development. Ph.D. Thesis. In: Department of Mechanical Engineering. Linköping Universitet, Linköping., 2005.

      [5] H. H. Lai, Y. C. Lin, C. H. Yeh, Form design of product image using grey relational analysis and neural network models, Computers & Operations Research 32, 10 (2005) 2689–2711. https://doi.org/10.1016/j.cor.2004.03.021

      [6] S. W. Hsiao, H. C. Tsai, applying a hybrid approach based on fuzzy neural network and genetic algorithm to product from design, International Journal of Industrial Ergonomics 35, 5 (2005), 411–428. https://doi.org/10.1016/j.ergon.2004.10.007

      [7] T.W. Lau, P. C. L. Hui, F. S. F. Ng, K.C.C. Chan, A new fuzzy approach to improve fashion product development. Computers in Industry, 57,1, (2006) 82 – 92. https://doi.org/10.1016/j.compind.2005.04.003

      [8] J. R. Jiao, Y. Zhang, M. Helander, A Kansei mining system for affective design, Expert Systems with Applications 30, 4 (2006) 658–673. https://doi.org/10.1016/j.eswa.2005.07.020

      [9] S. Barone, A. Lombardo, P. Tarantino, A weighted logistic regression for conjoint analysis and Kansei engineering, Quality and Reliability Engineering International 23, 6 (2007) 689–706. https://doi.org/10.1002/qre.866

      [10] C. C. Chang, Factors influencing visual comfort appreciation of the product form of digital cameras, International Journal of Industrial Ergonomics 38, 11–12 (2008) 1007–1016. https://doi.org/10.1016/j.ergon.2008.04.002

      [11] H. B. Yan, V. N. Huynh, T. Murai, Y. Nakamori, Kansei evaluation based on prioritized multi-attribute fuzzy target-oriented decision analysis, Information Science, 178, 21 (2008) 4080-4093. https://doi.org/10.1016/j.ins.2008.06.023

      [12] S. W. Hong, S. H. Han, K. J. Kim, Optimal balancing of multiple affective satisfaction dimensions: A case study on mobile phones, International Journal of Industrial Ergonomics 38, 3–4, (2008) 272–279. https://doi.org/10.1016/j.ergon.2007.09.002

      [13] S. Orsborn, J. Cagan, P. Boatwright, Quantifying aesthetic form preference in a utility function.†Journal of Mechanical Design 131, 6 (2009) 061001-1–061001-10.

      [14] L. Y. Zhai, L. P. Khoo, Z. W. Zhong, A rough set-based decision support approach to improving consumer affective satisfaction in product design, International Journal of Industrial Ergonomics 39, 2 (2009) 295–302. https://doi.org/10.1016/j.ergon.2008.11.003

      [15] E. A. Demirtas, A. S. Anagun, G. Koksal, Determination of optimal product styles by ordinal logistic regression versus conjoint analysis for kitchen faucets, International Journal of Industrial Ergonomics 39, 5 (2009) 866–875. https://doi.org/10.1016/j.ergon.2009.06.007

      [16] C. C. Yang, M. D. Shieh, A support vector regression-based prediction model of affective responses for product form design, Computers & Industrial Engineering 59, 4 (2010) 682–689. https://doi.org/10.1016/j.cie.2010.07.019

      [17] K. Y. Chan, C. K. Kwong, T. C. Wong, Modelling customer satisfaction for product development using genetic programming, Journal of Engineering Design 22, 1 (2011) 55–68. https://doi.org/10.1080/09544820902911374

      [18] K. Y. Fung, C. K. Kwong, K. W. M. Siu, K. M. Yu, A multi-objective genetic algorithm approach to rule mining for affective product design, Expert Systems with Applications 39, 8 (2012) 7411–7419. https://doi.org/10.1016/j.eswa.2012.01.065

      [19] L. Luo, P. K. Kannan, B. Besharati, S. Azarm, Design of robust new products under variability: marketing meets design, Journal of Product Innovation Management, 22, 2 (2005) 177–192. https://doi.org/10.1111/j.0737-6782.2005.00113.x

      [20] J. J. Michalek, O. Ceryan, P. Y. Papalambros, Y. Koren, Balancing marketing and manufacturing objectives in product line design, Journal of Mechanical Design, 128, 6 (2006) 1196–1204.

      [21] B. Besharati, L. Luo, S. Azarm, P.K. Kanan, Multi-objective single product robust optimization: an integrated design and marketing approach. Journal of Mechanical Design. 128, 4 (2006) 884–892.

      [22] J. Jiao, Y. Zhang, Product portfolio planning with customer-engineering interaction, IIE Transactions 37, 9 (2007) 801–814. https://doi.org/10.1080/07408170590917011

      [23] D. Kumar, W. Chen, T.W. Simpson, A market-driven approach to product family design. International Journal of Production Research, 47, 1 (2009)71–104. https://doi.org/10.1080/00207540701393171

      [24] C. C. Chen, M.-C. Chuang, Integrating the Kano model into a robust design approach to enhance customer satisfaction with product design, International Journal of Production Economics, 114, 2 (2008) 667-681. https://doi.org/10.1016/j.ijpe.2008.02.015

      [25] K. H. Kano, H. H., Hinterhuber, F. Bailon, E. Sauerwein, how to delight your customers, Journal of Product and Brand Management 5, 2 (1984) 6–17.

      [26] K. Otto, K. Wood, Product Design: Techniques in Reverse Engineering and New Product Development, Pearson, 2000.

      [27] K. Ulrich, S. Eppinger, Product Design and Development, McGraw-Hill Education, 2015.

      [28] C. K. Kwong, Y. Chen, K. Y. Chan, A methodology of integrating marketing with engineering for defining design specifications of new products, Journal of Engineering Design, 22, 3 (2011) 201–213. https://doi.org/10.1080/09544820903173180

      [29] F. Kardes, Consumer Behavior, Cengage Learning, 2010.

      [30] M. Crawford, A. Benedetto, New Products Management, McGraw-Hill Irwin, NewYork, 2003

      [31] J. H. Hair, W. C. Black, B. J. Babin, and R. E. Anderson, Multivariate Data Analysis, Pearson Higher Educations, 2013.

      [32] N. K. Malhotra, Marketing Research: An Applied Orientation, Pearson Higher Education, 2015.

  • Downloads

  • How to Cite

    M. Salhieh Ph. D., S. (2018). A systematic new product development methodology for creating affective products. International Journal of Engineering & Technology, 7(4), 4743-4752. https://doi.org/10.14419/ijet.v7i4.19617