×

A stochastic dominance based approach to consumer-oriented Kansei evaluation with multiple priorities. (English) Zbl 1415.91104

Summary: Nowadays, with the increasing of aesthetic products, it becomes more and more important and quite difficult for consumers to choose their preferred products, especially the ones whose artistic and aesthetic aspects play a crucial role in consumer purchase decisions. Taking Kansei as one quality aspect of products, consumer-oriented Kansei evaluation focuses on evaluation of existing commercial products based on consumers’ Kansei preferences. This paper proposes a stochastic dominance based approach to consumer-oriented Kansei evaluation with multiple priorities. Particularly, given a consumer’s preferences, the concept of stochastic dominance is used to build an evaluation function for each Kansei attribute. Then, the importance weights captured by a priority hierarchy of Kansei attributes, together with the fuzzy majority, are incorporated into the aggregation of individual stochastic dominance degrees into an overall one. An application to the hand-painted Kutani cups in Ishikawa, Japan, is conducted to illustrate the effectiveness and efficiency of the proposed approach. It is seen that the proposed approach outperforms the existing research in terms of easy of use and better decision-support to the consumers.

MSC:

91B06 Decision theory
90B10 Deterministic network models in operations research
60E15 Inequalities; stochastic orderings
PDFBibTeX XMLCite
Full Text: DOI

References:

[1] Adomavicius, G., & Tuzhilin, A. (2005). Toward the next generation of recommender systems: A survey of the state-of-the-art and possible extensions. IEEE Transactions on Knowledge and Data Engineering, 17(6), 734-749. · doi:10.1109/TKDE.2005.99
[2] Balters, S., & Steinert, M. (2015). Capturing emotion reactivity through physiology measurement as a foundation for affective engineering in engineering design science and engineering practices. Journal of Intelligent Manufacturing, pp. 1-23. doi:10.1007/s10845-015-1145-2. · Zbl 1320.91051
[3] Bordogna, G., Fedrizzi, M., & Pasi, G. (1997). A linguistic modeling of consensus in group decision making based on OWA operator. IEEE Transactions on Systems, Man and Cybernetics, Part A: Systems and Humans, 27(1), 126-132. · doi:10.1109/3468.553232
[4] Chang, H., Lai, H., & Chang, Y. (2006). Expression models used by consumers in conveying desire for product form: A case study of a car. International Journal of Industrial Ergonomics, 36(1), 3-10. · doi:10.1016/j.ergon.2005.06.004
[5] Chang, K. H. (2016). A novel reliability allocation approach using the owa tree and soft set. Annals of Operations Research. doi:10.1007/s10479-016-2178-4. · Zbl 1349.90246
[6] Chen, C. C., & Chuang, M. C. (2008). Integrating the kano model into a robust design approach to enhance customer satisfaction with product design. International Journal of Production Economics, 114(2), 667-681. · doi:10.1016/j.ijpe.2008.02.015
[7] Chen, H., & Chang, Y. (2009). Extraction of product form features critical to determining consumers’ perceptions of product image using a numerical definition-based systematic approach. International Journal of Industrial Ergonomics, 39(1), 133-145. · doi:10.1016/j.ergon.2008.04.007
[8] Chen, L., & Pu, P. (2012). Critiquing-based recommenders: Survey and emerging trends. User Modeling and User-Adapted Interaction, 22(1), 125-150. · doi:10.1007/s11257-011-9108-6
[9] Chen, M. C., Hsu, C. L., Chang, K. C., & Chou, M. C. (2015). Applying kansei engineering to design logistics services-a case of home delivery service. International Journal of Industrial Ergonomics, 48, 46-59. · doi:10.1016/j.ergon.2015.03.009
[10] Chuan, N. K., Sivaji, A., Shahimin, M. M., & Saad, N. (2013). Kansei engineering for e-commerce sunglasses selection in malaysia. Procedia-Social and Behavioral Sciences, 97, 707-714. · doi:10.1016/j.sbspro.2013.10.291
[11] Elokla, N., Hirai, Y., & Morita, Y. (2010). A proposal formeasuring user’s Kansei. In Lévy, P., Bouchard, C., Yamanaka,T., & Aoussat, A. (Eds.), The Kansei Engineering and EmotionResearch International Conference 2010-KEER 2010, Paris, France.
[12] Fan, Z. P., Liu, Y., & Feng, B. (2010). A method for stochastic multiple criteria decision making based on pairwise comparisons of alternatives with random evaluations. European Journal of Operational Research, 207, 906-915. · Zbl 1206.90057 · doi:10.1016/j.ejor.2010.05.032
[13] Grabisch, M., & Labreuche, C. (2010). A decade of application of the choquet and sugeno integrals in multi-criteria decision aid. Annals of Operations Research, 175, 247-286. · Zbl 1185.90118 · doi:10.1007/s10479-009-0655-8
[14] Grimsæth, K. (2005). Kansei Engineering: Linking emotionsand product features. Tech. rep., Norwegian University of Scienceand Technology, Norwegian.
[15] Herrera, F., & Martínez, L. (2000). A 2-tuple fuzzy linguistic representation model for computing with words. IEEE Transactions on Fuzzy Systems, 8(6), 746-752. · doi:10.1109/91.890332
[16] Huang, M. S., Tsai, H. C., & Huang, T. H. (2011). Applying kansei engineering to industrial machinery trade show booth design. International Journal of Industrial Ergonomics, 41(1), 72-78. · doi:10.1016/j.ergon.2010.10.002
[17] Huynh, V. N., Nakamori, Y., & Lawry, J. (2008). A probability-based approach to comparison of fuzzy numbers and applications to target-oriented decision making. IEEE Transactions on Fuzzy Systems, 16(2), 371-387. · doi:10.1109/TFUZZ.2007.896315
[18] Huynh, V. N., Yan, H. B., & Nakamori, Y. (2010). A target-based decision making approach to consumer-oriented evaluation model for Japanese traditional crafts. IEEE Transactions on Engineering Management, 57(4), 575-588. · doi:10.1109/TEM.2009.2025494
[19] Imai, M., Imai, Y., & Hattori, T. (2013). Collaborative design and its evaluation through kansei engineering approach. Artificial Life and Robotics, 18(3), 233-240. · doi:10.1007/s10015-013-0123-z
[20] Ishihara, S. (2014). Psychophysiological measurements in kansei engineering based product developments: Sanyo shaver case. International Journal of Psychophysiology, 94(2), 128. · doi:10.1016/j.ijpsycho.2014.08.609
[21] Kacprzyk, J., Zadrozny, S., Fedrizzi, M., & Nurmi, H. (2008). Fuzzy sets and their extensions: Representation, aggregation and models, Heidelberg: Physica-Verlag, chap On group decision making, consensus reaching, voting and voting paradoxes under fuzzy preferences and a fuzzy majority: A survey and some perspectives, pp. 263-295. · Zbl 1140.91343
[22] Kang, D. S. S., Baer, R., & Ladjahasan, N. (2008). Food as experience a design and evaluation methodology. In Proceedings of the Design Research Society Conference 2008, Sheffield Hallam University, Design Research Society, Sheffield, UK.
[23] Kanoh, M.; Nakamura, T.; Kato, S.; Itoh, H.; Dai, Y. (ed.); Chakraborty, B. (ed.); Shi, M. (ed.), Affective facial expressions using auto-associative neural network in kansei robot “Ifbot” (2011), Hershey, New York
[24] Kudo, Y., Amano, S., Seino, T., & Murai, T. (2006). A simple recommendation system based on rough set theory. Kansei Engineering International, 6(3), 19-24. · doi:10.5057/kei.6.3_19
[25] Llinares, C., & Page, A. F. (2011). Kano’s model in Kansei Engineering to evaluate subjective real estate consumer preferences. International Journal of Industrial Ergonomics, 41(3), 233-246. · doi:10.1016/j.ergon.2011.01.011
[26] Lu, W., & Petiot, J. F. (2014). Affective design of products using an audio-based protocol: Application to eyeglass frame. International Journal of Industrial Ergonomics, 44(3), 383-394. · doi:10.1016/j.ergon.2014.01.004
[27] Martínez, L. (2007). Sensory evaluation based on linguistic decision analysis. International Journal of Approximate Reasoning, 44(2), 148-164. · doi:10.1016/j.ijar.2006.07.006
[28] Miller, G. (1956). The magical number seven, plus or minus two: Some limits on our capacity for processing information. Psychological Review, 63(2), 81-97. · doi:10.1037/h0043158
[29] Nagamachi, M. (1995). Kansei engineering: A new ergonomic consumer oriented technology for product development. International Journal of Industrial Ergonomics, 15(1), 3-11. · doi:10.1016/0169-8141(94)00052-5
[30] Nagamachi, M. (2002). Kansei engineering as a powerful consumer-oriented technology for product development. Applied Ergonomics, 33(3), 289-294. · doi:10.1016/S0003-6870(02)00019-4
[31] Nakamori, Y., & Ryoke, M. (2006). Treating fuzziness in subjective evaluation data. Information Sciences, 176(24), 3610-3644. · Zbl 1101.62052 · doi:10.1016/j.ins.2006.02.015
[32] Nishizaki, I., Hayashida, T., & Ohmi, M. (2016). Multiattribute decision analysis using strict preference relations. Annals of Operations Research. doi:10.1007/s10479-014-1680-9. · Zbl 1406.90065
[33] Nureize, A., Watada, J., & Wang, S. (2014). Fuzzy random regression based multi-attribute evaluation and its application to oil palm fruit grading. Annals of Operations Research, 219(1), 299-315. · Zbl 1301.62131 · doi:10.1007/s10479-011-0979-z
[34] Okudan, G. E., Chiu, M. C., & Kim, T. H. (2013). Perceived feature utility-based product family design: A mobile phone case study. Journal of Intelligent Manufacturing, 24(5), 935-949. · doi:10.1007/s10845-012-0699-5
[35] Osgood, C., Suci, G., & Tannenbaum, P. (1957). The measurement of meaning. Urbana: University of Illinois Press.
[36] Oztekin, A., Iseri, A., Zaim, S., & Nikov, A. (2013). A taguchi-based kansei engineering study of mobile phones at product design stage. Production Planning & Control, 24(6), 465-474. · doi:10.1080/09537287.2011.633575
[37] Petiot, J. F., & Yannou, B. (2004). Measuring consumer perceptions for a better comprehension, specification and assessment of product semantics. International Journal of Industrial Ergonomics, 33(6), 507-525. · doi:10.1016/j.ergon.2003.12.004
[38] Schütte, S. T. W. (2005). Engineering emotional values in product design-Kansei engineering in development. Phd thesis, Linköping Studies in Science and Technology. · Zbl 1185.90118
[39] Schütte, S. T. W., Eklund, J., Axelsson, J. R. C., & Nagamachi, M. (2004). Concepts, methods and tools in Kansei engineering. Theoretical Issues in Ergonomics Science, 5(3), 214-231. · doi:10.1080/1463922021000049980
[40] Sotirov, G. R., & Krasteva, E. B. (1994). An approach to group decision making under uncertainty with application to project selection. Annals of Operations Research, 51, 115-126. · Zbl 0812.90085 · doi:10.1007/BF02032480
[41] Torra, V. (1997). The weighted OWA operator. International Journal of Intelligent Systems, 12, 153-166. · Zbl 0867.68089 · doi:10.1002/(SICI)1098-111X(199702)12:2<153::AID-INT3>3.0.CO;2-P
[42] Tversky, A., & Simonson, I. (1993). Context-dependent preferences. Management Science, 39(10), 1179-1189. · Zbl 0800.90037 · doi:10.1287/mnsc.39.10.1179
[43] Wu, Z., Xu, J., & Xu, Z. (2015). A multiple attribute group decision making framework for the evaluation of lean practices at logistics distribution centers. Annals of Operations Research, pp. 1-23. doi:10.1007/s10479-015-1788-6. · Zbl 1360.90149
[44] Yadav, O. P., & Goel, P. S. (2008). Customer satisfaction driven quality improvement target planning for product development in automotive industry. International Journal of Production Economics, 113(2), 997-1011. · doi:10.1016/j.ijpe.2007.12.008
[45] Yager, R. R. (1988). On ordered weighted averaging operators in multi-criteria decision making. IEEE Transactions on Systems, Man and Cybernetics, 18(1), 183-190. · Zbl 0637.90057 · doi:10.1109/21.87068
[46] Yager, R. R. (1996). Quantifier guided aggregation using OWA operators. International Journal of Intelligent Systems, 11(1), 49-73. · doi:10.1002/(SICI)1098-111X(199601)11:1<49::AID-INT3>3.3.CO;2-L
[47] Yager, R. R. (2002). On the instantiation of possibility distributions. Fuzzy Sets and Systems, 128(2), 261-266. · Zbl 1003.68161 · doi:10.1016/S0165-0114(01)00206-8
[48] Yager, R. R. (2004). Modeling prioritized multicriteria decision making. IEEE Transactions on Systems, Man, and Cybernetics, Part B, 34(6), 2396-2404. · doi:10.1109/TSMCB.2004.837348
[49] Yager, R. R. (2008). Prioritized aggregation operators. International Journal of Approximate Reasoning, 48(1), 263-274. · Zbl 1184.68526 · doi:10.1016/j.ijar.2007.08.009
[50] Yan, H. B., & Ma, T. (2015). A group decision-making approach to uncertain quality function deployment based on fuzzy preference relation and fuzzy majority. European Journal of Operational Research, 241(3), 815-829. · Zbl 1339.91047 · doi:10.1016/j.ejor.2014.09.017
[51] Yan, H. B., Huynh, V. N., Murai, T., & Nakamori, Y. (2008). Kansei evaluation based on prioritized multi-attribute fuzzy target-oriented decision analysis. Information Sciences, 178(21), 4080-4093. · doi:10.1016/j.ins.2008.06.023
[52] Yan, H. B., Huynh, V. N., Nakamori, Y., & Murai, T. (2011). On prioritized weighted aggregation in multi-criteria decision making. Expert Systems with Applications, 38(1), 812-823. · doi:10.1016/j.eswa.2010.07.039
[53] Yan, H. B., Huynh, V. N., & Nakamori, Y. (2012). A group nonadditive multiattribute consumer-oriented kansei evaluation model with an application to traditional crafts. Annals of Operations Research, 195(1), 325-354. · Zbl 1259.91064 · doi:10.1007/s10479-010-0826-7
[54] Yan, H. B., Huynh, V. N., Ma, T., & Nakamori, Y. (2013a). Non-additive multi-attribute fuzzy target-oriented decision analysis. Information Sciences, 240, 21-44. · Zbl 1320.91051 · doi:10.1016/j.ins.2013.03.050
[55] Yan, H. B., Ma, T., & Li, Y. S. (2013b). A novel fuzzy linguistic model for prioritising engineering design requirements in quality function deployment under uncertainties. International Journal of Production Research, 51(21), 6336-6355. · doi:10.1080/00207543.2013.796423
[56] Yan, H. B., Ma, T., & Huynh, V. N. (2014). Coping with group behaviors in uncertain quality function deployment. Decision Sciences, 45(6), 1025-1052. · doi:10.1111/deci.12104
[57] Yang, C. C. (2011). Constructing a hybrid Kansei engineering system based on multiple affective responses: Application to product form design. Computers & Industrial Engineering, 60(4), 760-768. · doi:10.1016/j.cie.2011.01.011
[58] Zadeh, L. (1975). The concept of a linguistic variable and its applications to approximate reasoning—I. Information Sciences, 8(3), 199-249. · Zbl 0397.68071 · doi:10.1016/0020-0255(75)90036-5
[59] Zadeh, L. A. (1983). A computational approach to fuzzy quantifiers in natural languages. Computers and Mathematics with Applications, 9(1), 149-184. · Zbl 0517.94028 · doi:10.1016/0898-1221(83)90013-5
[60] Zeng, X., Ruan, D., & Koehl, L. (2008). Intelligent sensory evaluation: Concepts, implementations, and applications. Mathematics and Computers in Simulation, 77(5-6), 443-452. · Zbl 1137.62418 · doi:10.1016/j.matcom.2007.11.013
This reference list is based on information provided by the publisher or from digital mathematics libraries. Its items are heuristically matched to zbMATH identifiers and may contain data conversion errors. In some cases that data have been complemented/enhanced by data from zbMATH Open. This attempts to reflect the references listed in the original paper as accurately as possible without claiming completeness or a perfect matching.