DOI QR코드

DOI QR Code

Effect on user evaluation, purchase intention, and satisfaction of personalized recommendation services by purchase journey in mobile fashion commerce

모바일 패션커머스의 구매여정별 개인화 추천서비스 사용자 평가와 구매의도 및 만족도에 미치는 영향

  • kang, Sun-Young (Dept. of Smart Experience Design, Graduate School of Techno Design, Kookmin University) ;
  • Pan, Young-Hwan (Dept. of Smart Experience Design, Graduate School of Techno Design, Kookmin University)
  • 강선영 (국민대학교 테크노 디자인 전문대학원 인터랙션랩) ;
  • 반영환 (국민대학교 테크노 디자인 전문대학원 인터랙션랩)
  • Received : 2021.11.24
  • Accepted : 2022.01.20
  • Published : 2022.01.28

Abstract

Fashion is a field in which personal taste acts as the first criterion for purchase, and it is being refined as an important strategy to increase purchase conversion on mobile. Although related studies have been conducted, there are insufficient studies to confirm this according to the detailed purchasing journey of consumers. The purpose of this study is to examine whether the evaluation of user experience factors of personalized recommendation service differs by purchase journey, and to reveal whether it affects purchase intention and satisfaction. Variety, reliability, and convenience showed a significant difference at the level of 0.001% and usefulness at the level of 0.05%. Satisfaction levels were different for each stage, such as novelty and usefulness in the cognitive and interest stage, and high reliability and diversity in the search stage. It has theoretical significance in that it enhances the understanding of the purchase journey by revealing that there is a difference in user evaluation of the personalized recommendation service, and it has practical significance in that it suggests the direction of improvement of the personalized recommendation service strategy. If research on effectiveness is conducted in the future, it will be able to contribute to an advanced strategy.

패션은 개인 취향이 구매의 첫 번째 기준으로 작용하는 분야인 만큼 개인화된 추천 서비스가 일찍이 자리를 잡았다. 특히 모바일 패션 커머스에서 구매전환을 높이는 중요한 전략으로 꼽히며 더욱 정교화 되고있다. 이로 인해 개인화 추천서비스의 사용자 경험 관해 많은 연구들이 이루어졌지만, 세부적인 소비자의 구매여정에 따라 확인한 연구는 부족한 실정이다. 본 연구는 개인화 추천서비스의 사용자 평가가 구매여정별로 차이가 있는지 살펴보고, 구매의도와 만족도에는 어떠한 영향을 미치는지 밝히고자 하였다. 분석결과 다양성, 신뢰성, 편의성은 0.001%수준, 유용성은 0.05% 수준에서 구매여정 단계별로 유의한 차이를 보였다. 또한 만족도는 인지 및 흥미단계에서 새로움과 유용성이, 검색단계에서 신뢰성과 다양성이 높게 나타나는 등 각 단계별로 차이를 보였으며, 구매의도는 구매 후 단계를 제외하고 유용성과 신뢰성이 높은 결과를 보였다. 본 연구는 소비자의 개인화 추천 서비스에 대한 사용자 평가에 차이가 있음을 밝힘으로써 구매 여정에 따른 개인화 추천서비스 사용자 평가의 영향에 대한 이해를 높였다는 점에서 이론적 의의가 있으며, 모바일 패션커머스의 개인화 추천서비스 전략개선의 방향성을 제시했다는 실무적 의의를 지닌다. 추후 개선안의 효과성에 대한 연구가 진행된다면 더욱 고도화된 개인화 추천서비스 전략에 기여할 수 있을 것이다.

Keywords

References

  1. H. S. Ahn, S. H. Kwon & M. J. Park. (2019). A case study of personalized fashion style recommendation service by artificial intelligence. Journal of the Korean Society of Clothing and Textiles, 43(3), 349-360. https://doi.org/10.5850/JKSCT.2019.43.3.349
  2. Y. L. Kim. (2019). Negative emotions and rumination on mobile fashion shopping service failure experience. Doctoral dissertation. Seoul National University, Seoul.
  3. Groobee. (2021. 9. 4). In the era of hyper-personalization, securing various recommendation strategies is a competitive advantage. [online]. https://groobee.net/groobeeaireco/?gclid=CjwKCAjw2vOLBhBPEiwAjEeK9gMBT0EG-BP6b9ILKQo3H9Mwe_ib-JlIcfC5iV8JybOBOnTWu3ICKhoCl6YQAvD_BwE.
  4. J. Gupta & J. Gadge. (2015, January). Performance analysis of recommendation system based on collaborative filtering and demographics. 2015 International Conference on Communication. Information & Computing Technology (ICCICT). (pp. 1-6). Mumbai : IEEE.
  5. H. J. Joo & K. W. Lee. (2021). The impact of AI-enabled recommendation systems on the success of small and medium-sized online stores. 2021 Korea Management Information Society Spring Integration Conference. (pp. 243-247). Seoul : KMIS.
  6. J. E. Kim. (2021). Size recommendation service based on data convergence of online shopping: The role of service quality, information trust, and purchase intention of customer satisfaction. Journal of the Korean Convergence Society, 12(7), 7-17.
  7. Y. N. Park & C. S. Kim. (2017). A study on the influence of fashion interest and personal taste on their attitude of fashion curation service (FCS) and purchase intention of fashion products-focused on people aged 20s to 30s who experienced FCS-. Journal of Basic Design & Art, 18(1), 173-188.
  8. S. Lee. (2016). The effects of fashion curation service quality attribute on satisfaction. trust and purchase intention. Unpublished master's dissertation. Yonsei University, Seoul.
  9. K. N. Lemon & P. C. Verhoef. (2016). Understanding customer experience throughout the customer journey. Journal of Marketing: AMA/MSI Special Issue, 80(6), 69-96. https://doi.org/10.1509/jm.15.0420
  10. S. K. Kang, E. Yoo & J. M. Jeong. (2019). The digital customer experience of consumer electronics purchases: an analysis of the online purchase journey process. Information Systems Review, 21(1), 61-90. https://doi.org/10.14329/isr.2019.21.1.061
  11. H. Han. (2019). A study on changes in consumer sentiment in the online clothing purchase process. Doctoral dissertation. Seoul National University, Seoul.
  12. M. R. Kim & S. S. Kim. (2019). Intention to continue purchasing through online open market platform: Focusing on the multidimensional approach of perceived value in the purchasing process and transaction satisfaction. Internet E-Commerce Research, 19(3), 149-172.
  13. J. E. Park. (2016). Recommend products that are relevant to customers' personal experiences and tastes. Master's dissertation. Yonsei University, Seoul.
  14. S. Y. Shim. (2012). Whose hearts do SNS reviews move?: A study on marketing strategies using social network services. Journal of the Korean IT Service Society, 11(3), 103-127. https://doi.org/10.9716/KITS.2012.11.3.103
  15. J. W. Choi & H. J. Lee. (2012). Integrated approach to user evaluation of personalized recommendation system. Journal of the Korean Electronic Transactions Association, 17(3), 85-103.
  16. B. J. Park & S. H. Choi. (2018). User evaluation and intention to use and purchase intention by type of recommended service in online fashion shopping malls. Korea Design Forum, 23(4), 139-149. https://doi.org/10.21326/ksdt.2018.23.4.012
  17. Y. G. Park, K. H. Yeon & C. H. Jeon. (2010). Research on the effect of IPTV features on consumers' viewing satisfaction and sustainable utilizationIntention. Journal of Internet Electronic Commerce Research, 10(2), 191-205. https://doi.org/10.1007/s10660-010-9051-3
  18. R. L. Oliver. (1980). A cognitive model of the antecedents and on sequences of satisfaction decisions. Journal of Marketing Research, 17(4), 460-469. https://doi.org/10.2307/3150499
  19. J. F. Engel & R. D. Blackwell. (1982). Consumer behavior. New York : Dryden press.
  20. B. J. Kim & U. R. Hwang. (2007). A study on the effect of online product evaluation information on consumer purchasing decision making. Convergence Conference of the Korean Business Association, 1-27.
  21. J. W. Hwang & J. H. Lee. (2019). A study on consumer product purchase intention and purchasing behavior factors in mobile shopping malls. Journal of the Korean Society for Design Culture, 25(3), 547-559. https://doi.org/10.18208/ksdc.2019.25.3.547
  22. H. Y. Lim, H. K. Hong &, K. S. Han. (2020). A study on the effect of image search-related characteristics and user characteristics on purchase intention of a mobile shopping mall. Information Technology Architecture Study, 17(1), 41-50.
  23. J. W. Hwang & J. H. Lee. (2019). A study on consumer product purchase intention and purchase behavior factors in mobile shopping malls. Journal of the Korean Society for Design Culture, 25(3), 547-559. https://doi.org/10.18208/ksdc.2019.25.3.547
  24. T. Y. Shim & S. J. Yoon. (2020). Effect of online shopping mall characteristics on emotional response, perceived value, and reuse intention: Focusing on the extended technology adoption model (TAM2). Journal of the Korean Society for Industrial-Academic Technology, 21(4), 374-383.
  25. S. E. Choi & H. S. Lim. (2019). A study on the product recommendation system based on user search keyword characteristics. Journal of the Korea Digital Content Society, 20(2), 315-320. https://doi.org/10.9728/dcs.2019.20.2.315
  26. S. Y. Shim. (2012). A large number of consumer recommendations? or a small number of friend recommendations?: Purchasing decision making based on SNS. The Journal of Society for E-Business Studies, 17(3), 15-41. https://doi.org/10.7838/JSEBS.2012.17.3.015
  27. O. J. Lee. & Y. T. Baek. (2014). Hybrid preference prediction technique using weighting based data reliability for collaborative filtering recommendation system. Journal of the Korea Society of Computer and Information, 19(5), 61-69. https://doi.org/10.9708/JKSCI.2014.19.5.061