DOI QR코드

DOI QR Code

Product Recommendation Service in Online Mass Customization: Consumers' Cognitive and Affective Responses

의류상품의 온라인 대량고객화 제품추천 서비스에 대한 소비자의 감정적, 인지적 반응

  • Moon, Heekang (Dept. of Home Economics Education, Pai Chai University) ;
  • Lee, Hyun-Hwa (Dept. of Fashion Design & Textiles, Inha University)
  • 문희강 (배재대학교 가정교육과) ;
  • 이현화 (인하대학교 의류디자인학 전공)
  • Received : 2012.10.11
  • Accepted : 2012.11.10
  • Published : 2012.11.30

Abstract

This study examined the effects of product recommendation services as an atmosphere for online mass customization shopping sites on consumers' cognitive and affective responses. We conducted a between-subject experimental study using a convenience sample of college students. A total of 196 participants provided usable responses for structural equation modeling analysis. The findings of the study support the S-O-R model for a product recommendation system as an element of the shopping environment with an influence on OMC product evaluations and arousal. The results showed that OMC product recommendation service positively affected cognitive and affective responses. The findings of the study suggest that OMC retailers might pay attention to the affective and cognitive responses of consumers through product recommendation services that can enhance product evaluations and OMC usage intentions.

Keywords

References

  1. Ansari, A., & Mela, C. F. (2003). E-customization. Journal of Marketing Research, 40(2), 131-145. https://doi.org/10.1509/jmkr.40.2.131.19224
  2. Avery, C., & Zeckhauser, R. (1997). Recommender systems for evaluating computer message. Communications of the ACM, 40(3), 88-89. https://doi.org/10.1145/245108.245127
  3. Babin, B. J., & Darden, W. R. (1995). Consumer self-regulation in a retail environment. Journal of Retailing, 71(1), 47-70. https://doi.org/10.1016/0022-4359(95)90012-8
  4. Bagozzi, R. P., & Yi, Y. (1988). On the evaluation of structural equation models. Journal of the Academy of Marketing Science, 16(1), 74-94. https://doi.org/10.1007/BF02723327
  5. Baker, J., Levy, M., & Grewal, D. (1992). An experimental approach to making retail store environmental decisions. Journal of Retailing, 68(4), 445-460.
  6. Bardakci, A., & Whitelock, J. (2004). How "Ready" are customers for mass customization? An exploratory investigation. European Journal of Marketing, 38(11/12), 1396-1416. https://doi.org/10.1108/03090560410560164
  7. Basu, C., Hirsh, H., & Cohen, W. (1998). Recommendation as classification: Using social and content-based information in recommendation. Proceedings of the 1998 Workshop on Recommendation System, U.S.A., 11-15.
  8. Bloch, P. H., & Bruce. G. D. (1984). Product involvement as leisure behavior. In T. C. Kinnear (Ed.), Advances in consumer Research, Vol. 11 (pp. 197-202). Ann arbor, MI: Association for Consumer Research.
  9. Brunato, M., & Battiti, R. (2003). PILGRIM: A location broker and mobility-aware recommendation system. Proceedings of the First IEEE International Conference on Pervasive Computing and Communication, U.S.A., 265-272.
  10. Byrne, B. M. (1998). Structural equation modeling with LISREL, PRELIS, and SIMPLIS: Basic concepts, appications, and programming. Mahwah, NJ: Lawrence Erlbaum Associates, Inc.
  11. Chebat, J. C., & Michon, R. (2003). Impact of ambient odors on mall shoppers' emotions, cognition, and spending: A test of competitive causal theories. Journal of Business Research, 56(7), 529-539. https://doi.org/10.1016/S0148-2963(01)00247-8
  12. Cho, Y. B., Cho, Y. H., & Kim, S. H. (2005). Mining changes in customer buying behavior for collaborative recommendations. Expert Systems with Applications, 28(2), 359-369. https://doi.org/10.1016/j.eswa.2004.10.015
  13. Chung, I. H., & Rhee, E. Y. (1992). A study on clothing images: Their constructing factors and evaluative dimensions. Journal of the Korean Society of Clothing and Textiles, 16(4), 379-391.
  14. Churchill, G. A., Jr. (1979). A paradigm for developing better measures of marketing constructs. Journal of Marketing Research, 16(1), 64-73. https://doi.org/10.2307/3150876
  15. Dailey, L. (2004). Navigational web atmospherics: Explaining the influence of restrictive navigation cues. Journal of Business Research, 57(7), 795-803. https://doi.org/10.1016/S0148-2963(02)00364-8
  16. Dellaert, B. G. C., & Stremersch, S. (2005). Marketing mass-customized products: Striking a balance between utility and complexity. Journal of Marketing Research, 42(2), 219-227. https://doi.org/10.1509/jmkr.42.2.219.62293
  17. Delong, M. R. (1987). The way we look: A framework for visual analysis of dress. Ames, IA: Iowa State University Press.
  18. Donovan, R. J., & Rossiter, J. R. (1982). Store atmosphere: An environmental psychology approach. Journal of Retailing, 58(1), 34-57.
  19. Eroglu, S. A., Machleit, K. A., & Davis, L. M. (2001). Atmospheric qualities of online retailing: A conceptual model and implications. Journal of Business Research, 54(2), 177-184. https://doi.org/10.1016/S0148-2963(99)00087-9
  20. Eroglu, S. A., Machleit, K. A., & Davis, L. M. (2003). Empirical testing of a model of online store atmospherics and shopper responses. Psychology & Marketing, 20(2), 139-150. https://doi.org/10.1002/mar.10064
  21. Fiore, A. M., Lee, S. E., & Kunz, G. (2004). Individual differences, motivations, and willingness to use a mass customization option for fashion products. European Journal of Marketing, 38(7), 835-849. https://doi.org/10.1108/03090560410539276
  22. Fiore, A. M., Lee, S. E., Kunz, G., & Campbell, J. R. (2001). Relationships between optimum stimulation level and willingness to use mass customization options. Journal of Fashion Marketing and Management, 5(2), 99-107. https://doi.org/10.1108/EUM0000000007281
  23. Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39-50. https://doi.org/10.2307/3151312
  24. Franke, N., Keinz, P., & Steger, C. J. (2009). Testing the value of customization: When do customers really prefer products tailored to their preferences? Journal of Marketing, 73(5), 103-121. https://doi.org/10.1509/jmkg.73.5.103
  25. Frijda, N. H. (1993). The place of appraisal in emotion. Cognition & Emotion, 7(3/4), 357-387. https://doi.org/10.1080/02699939308409193
  26. Garland, R. (1991). The mid-point on a rating scale: Is it desirable? Marketing Bulletin, 2, 66-70.
  27. Gilmore, J. H., & Pine II, B. J. (1997). The four faces of mass customization. Harvard Business Review, 75(1), 91-101.
  28. Goff, B. G., Boles, J. S., Bellinger, D. N., & Stojack, C. (1997). The influence of salesperson selling behaviors on customer satisfaction with products. Journal of Retailing, 73(2), 171-183. https://doi.org/10.1016/S0022-4359(97)90002-6
  29. Hair, J. F., Tatham, R. L., Anderson, R. E., & Black, W. (1998). Multivariate data analysis (5th ed.). Upper Saddle River, NJ: Prentice Hall.
  30. Hill, W., Stead, L., Rosenstein, M., & Furnas, G. (1995). Recommending and evaluating choices in a virtual community of use. Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, USA, 194-201.
  31. Hirshman, E. C., & Holbrook, M. B. (1982). Hedonic consumption emerging concepts, methods and propositions. Journal of Marketing, 46(3), 92-101. https://doi.org/10.2307/1251707
  32. Huffman, C., & Khan, B. E. (1998). Variety for sale: Mass customization or mass confusion? Journal of Retailing, 74(4), 491-513. https://doi.org/10.1016/S0022-4359(99)80105-5
  33. Hui, M. K., & Bateson, J. E. G. (1991). Perceived control and the effects of crowding and consumer choices on the service experience. Journal of Consumer Research, 18(2), 174-184. https://doi.org/10.1086/209250
  34. Kahn, B. E. (1995). Consumer variety seeking among goods and services: An integrative review. Journal of Retailing and Consumer Services, 2(3), 139-148. https://doi.org/10.1016/0969-6989(95)00038-0
  35. Kaltcheva, V. D., & Weitz, B. A. (2006). When should a retailer create an exciting store environment? Journal of Marketing, 70(1), 107-118. https://doi.org/10.1509/jmkg.2006.70.1.107
  36. Kamis, A., Koufaris, M., & Stern, T. (2008). Using an attribute-based decision support system for user-customized products online: An experimental investigation. MIS Quarterly, 32(1), 159-177. https://doi.org/10.2307/25148832
  37. Kim, J., & Forsythe, S. (2007). Hedonic usage of product virtualization technologies in online apparel shopping. International Journal of Retail & Distribution Management, 35(6), 502-514. https://doi.org/10.1108/09590550710750368
  38. Kim, J., Fiore, A. M., & Lee, H. H. (2007). Influences of online store perception, shopping enjoyment, and shopping involvement on consumer patronage behavior towards an online retailer. Journal of Retailing and Consumer Services, 14(2), 95-107. https://doi.org/10.1016/j.jretconser.2006.05.001
  39. Kim, S. H. (2011). Consumers' emotional pleasure and cognitive pleasure: Dynamic relationship between cognition and emotion. Korean Management Review, 40(2), 255-295.
  40. Kim, Y. S., Yum, B. J., Song, J., & Kim, S. M. (2005). Development of a recommender system based on navigational and behavioral patterns of customers in e-commerce sites. Expert Systems with Applications, 28(2), 381-393. https://doi.org/10.1016/j.eswa.2004.10.017
  41. Koering, S. K., & Page, A. L. (2002). What if your dentist looked like tom cruise? Applying the match-up hypothesis to a service encounter. Psychology & Marketing, 19(1), 91-110. https://doi.org/10.1002/mar.1003
  42. Koo, D. M., & Ju, S. H. (2010). The interactional effects of atmospherics and perceptual curiosity on emotions and online shopping intention. Computers in Human Behavior, 26(3), 377-388. https://doi.org/10.1016/j.chb.2009.11.009
  43. Kotler, P. (1973). Atmospherics as a marketing tool. Journal of Retailing, 49(4), 48-64.
  44. Kramer, T. (2007). The effect of measurement task transparency on preference construction and evaluations of personalized recommendations. Journal of Marketing Research, 44(2), 224-233. https://doi.org/10.1509/jmkr.44.2.224
  45. Kuppens, P. (2008). Individual differences in the relationship between pleasure and arousal. Journal of Research in Personality, 42(4), 1053-1059. https://doi.org/10.1016/j.jrp.2007.10.007
  46. Lazarus, R. S. (1984). On the primacy of cognition. American Psychologist, 39(2), 124-129. https://doi.org/10.1037/0003-066X.39.2.124
  47. Lazarus. R. S. (1991). Emotion and adaptation. New York, NY: Oxford University Press.
  48. Lee, E. J., Kim, H., & Noh, M. (2011). Psychological benefits of one-to-one marketing in apparel E-commerce: An approach with perceived usefulness, pleasure, arousal, and attitude toward the E-store. Journal of Korean Society of Clothing and Textiles, 35(6), 646-658. https://doi.org/10.5850/JKSCT.2011.35.6.646
  49. Lee, H. H., & Chang, E. (2011). Consumer attitudes toward online mass customization: An application of extended technology acceptance model. Journal of Computer-Mediated Communications, 16(2), 171-200. https://doi.org/10.1111/j.1083-6101.2010.01530.x
  50. Lee, H. H., Damhorst, M. L., Campbell, J. R., Loker, S., & Parsons, J. L. (2011). Consumer satisfaction with a mass customized Internet apparel shopping site. International Journal of Consumer Studies 35(3), 316-329. https://doi.org/10.1111/j.1470-6431.2010.00932.x
  51. Lee, H. H., & Moon, H. (2012). Consumer responses to retailer's location-based mobile shopping service: Focusing on PAD emotional state model and information relevance. Journal of Channel and Retailing, 17(2), 63-92.
  52. Lee, J., Lee, Y., & Lee, Y. J. (2012). Do customization programs of e-commerce companies lead to better relationship with consumers? Electronic Commerce Research and Applications, 11(3), 262-274. https://doi.org/10.1016/j.elerap.2011.10.004
  53. Lee, J. H., Koo, D. M., Lee, M. J., & Kim, S. H. (2011). Causal relationships among dominance, arousal and pleasure as well as the effect of these emotional factors on behavior intention-Focusing on the difference between off-line and online shopping malls-. Journal of Marketing Management, 16(1), 89-123.
  54. Lee, J. H., Ok, J. W., & Park, H. H. (2008). The study on relationship of arousal, pleasure, and behavior intention from a store environment: Focused on moderating role of shopping value. Journal of Channel and Retailing, 13(4), 21-46.
  55. Lee, K. S., & Lee, H. R. (2011). The influence of travelers' perception of smart phone services on their attitude and intention to use: An application of TAM and PDA theory. International Journal of Tourism Science, 35(2), 271-292.
  56. Lunardo, R., & Ababacar, M. (2009). Perceived control and shopping behavior: The moderating role of the level of utilitarian motivational orientation. Journal of Retailing and Consumer Services, 16(6), 434-441. https://doi.org/10.1016/j.jretconser.2009.06.004
  57. Ma, H., Zhou, D., Liu, C., Lyu, M. R., & King, I. (2011). Recommender systems with social regularization. Proceedings of the fourth ACM international conference on Web search and data mining, Hong Kong, China, 287-296.
  58. Massara, F., Liu, S. S., & Melara, R. D. (2010). Adapting to a retail environment: Modeling consumer-environment interactions. Journal of Business Research, 63(7), 673-681. https://doi.org/10.1016/j.jbusres.2009.05.004
  59. Mehrabian, A., & Russell, J. A. (1974). An approach to environmental psychology. Cambridge, MA: MIT Press.
  60. Milliman, R. E., & Fugate, D. L. (1993). Atmospherics as an emerging influence in the design of exchange environments. Journal of Marketing, 3(1), 66-74.
  61. Park, W. I., & Kim, Y. K. (2012). A weight based recommendation technique using customers' psychological patterns. Journal of Computing Science and Engineering, 39(2), 129-137.
  62. Parson, J., Ralph, P., & Gallagher, K. (2004). Using viewing time to infer user preference in recommender system. AAAI Workshop in Semantic Web Personalization. Retrieved January 10, 2012, from http://eprints.lancs.ac.uk/id/eprint/47394
  63. Piller, F. T. (2004). Mass customization: Reflections on the state of the concept. The International Journal of Flexible Manufacturing Systems, 16(4), 313-334. https://doi.org/10.1007/s10696-005-5170-x
  64. Pine II, B. J., Perppers, D., & Rogers, M. (1995). Do you want to keep your customers forever. Harvard Business Review, 73(2), 103-115.
  65. Pine II, B. J., Victor, B., & Boyton, A. C. (1993). Making mass customization work. Harvard Business Review, 71(5), 108-117.
  66. Rafaeli, E., & Revelle, W. (2006). A premature consensus: Are happiness and sadness truly opposite affects. Motivation and Emotion, 30(1), 1-12. https://doi.org/10.1007/s11031-006-9004-2
  67. Russell, J. A., & Pratt, G. (1980). A description of the affective quality attributed to environments. Journal of Personality and Social Psychology, 38(2), 311-322. https://doi.org/10.1037/0022-3514.38.2.311
  68. Salvador, F., de Holan, P. M., & Piller, F. (2009). Cracking the code of mass customization. MIT Sloan Management Review, 50(3), 70-79.
  69. Senecal, S. & Nantel, J. (2004). The influence of online product recommendations on consumers' online choices. Journal of Retailing, 80(2), 159-169. https://doi.org/10.1016/j.jretai.2004.04.001
  70. Sherman, E., Mathur, A., & Smith, R. B. (1997). Store environment and consumer purchase behavior: Mediating role of consumer emotions. Psychology & Marketing, 14(4), 361-378. https://doi.org/10.1002/(SICI)1520-6793(199707)14:4<361::AID-MAR4>3.0.CO;2-7
  71. Sherry, J. F., McGrath, M. A., & Levy, S. J. (1993). The dark side of the gift. Journal of Business Research, 28(3), 225-244. https://doi.org/10.1016/0148-2963(93)90049-U
  72. Suh, M. S., & Kim, S. H. (2002). A study on the relationship of internet shopping mall characteristics and emotional responses. Korean Marketing Review, 17(2), 113-145.
  73. Suh, Y. W., & Son, Y. H. (2004). A study on the development of Korean consumption emotion items. Korean Journal of Consumer and Advertising Psychology, 5(1), 69-92.
  74. Syam, N. B., Ruan, R., & Hess, J. D. (2005). Customized products: A competitive analysis. Marketing Science, 24(4), 569-584. https://doi.org/10.1287/mksc.1050.0128
  75. Ulrich, P. V., Anderson-Connell, L. J., & Wu, W. (2003). Consumer co-design of apparel for mass customization. Journal of Fashion Marketing and Management, 7(4), 398-412. https://doi.org/10.1108/13612020310496985
  76. Ward, J. C., & Barnes, J. W. (2001). Control and affect: The influence of feeling in control of the retail environment on affect, involvement, attitude and behavior. Journal of Business Research, 54(2), 139-144. https://doi.org/10.1016/S0148-2963(99)00083-1
  77. Xiao, B., & Benbasat, I. (2007). E-commerce product recommendation agents: Use, characteristics, and impact. MIS Quarterly, 31(1), 137-209. https://doi.org/10.2307/25148784
  78. Yoon, S. J., & Lee, D. H. (2008). An experiential approach to the determinants of impulse buying based on store type. Journal of Channel and Retailing, 13(3), 1-25.
  79. Zhang, Y., & Jiao, J. R. (2007). An associative classification-based recommendation system for personalization in B2C e-commerce applications. Expert Systems with Applications, 33(2), 357-367. https://doi.org/10.1016/j.eswa.2006.05.005

Cited by

  1. Effects of Contemporary Cultural Apparel Attributes on Consumer Response towards Consumer Behavior vol.66, pp.5, 2016, https://doi.org/10.7233/jksc.2016.66.5.001
  2. Consumers’ preference fit and ability to express preferences in the use of online mass customization vol.8, pp.2, 2014, https://doi.org/10.1108/JRIM-07-2013-0043