DOI QR코드

DOI QR Code

A Study on US Consumers' Loyalty to Online Shopping Mall : Focused on Group Buying Social Commerce

미국 소비자의 온라인 쇼핑몰 충성도 연구 : 공동구매형 소셜커머스를 중심으로

  • Cho, Yun-Jin (Dept of Textile Design, Gyeongnam National University of Science and Technology)
  • 조윤진 (경남과학기술대학교 텍스타일디자인학과)
  • Received : 2018.12.07
  • Accepted : 2019.02.20
  • Published : 2019.02.28

Abstract

The purpose of this paper is to examine the factors influencing on loyalty in US online shopping malls. The study proposed a model to investigate the relationship among quality of sites, satisfaction, attitude, and loyalty. The hypotheses were examined by analyzing a structural equation model. 280 US samples were used for the final analysis. The results show that this model demonstrates good fit for the samples. The ease of use was found to be a significant variable in their satisfaction, while it did not have the direct effect on attitude toward the sites. The information quality was found to be a crucial variable in consumers' satisfaction and attitude toward the site. Satisfaction directly affected attitude as well as loyalty, and attitude also directly affected loyalty. Thus, the structural relationship among the variables of customers' loyalty was verified. This research provides practical insights into US consumer behaviors that would be beneficial to marketers when they make decisions for the US e-commerce market.

연구의 목적은 미국 온라인 쇼핑몰에서의 고객 충성도에 영향을 미치는 변인들을 분석해보는 것이다. 이를 위해 본 연구는 사이트 품질, 사이트에 대한 만족, 태도 그리고 충성도의 관계를 살펴보기 위한 모형을 제안하고, 구조모형방정식을 통해 이를 검증하였다. 미국 소비자 280명의 샘플을 분석에 사용하였으며, AMOS 20.0을 이용하여 확인적 요인분석과 구조방정식 모형 분석을 실시하였다. 제안된 연구 모형은 비교적 양호한 적합도를 보였다. 사이트 품질 중 이용 용이성과 정보 품질은 만족에 긍정적인 영향을 미쳤다. 특히 정보 품질은 태도에도 긍정적인 영향을 미쳐 만족과 태도에 중요한 변수임을 확인하였다. 만족은 태도와 충성도에 유의한 영향을 미쳤으며, 태도 역시 충성도에 유의한 영향을 미쳤다. 즉 사이트에 대한 고객 만족과 호의적인 태도 형성이 결국 사이트의 충성으로 이끌 것이라는 점을 확인하였다. 본 연구는 미국 소비자들의 e-충성도에 대한 이론적 시사점을 제시하였으며, 이를 토대로 실천적인 마케팅 전략이 제안될 수 있다는 점에서 의의가 있다.

Keywords

JKOHBZ_2019_v9n2_75_f0001.png 이미지

Fig. 1. Research Model

Table 1. Demographic Information about the Respondents

JKOHBZ_2019_v9n2_75_t0001.png 이미지

Table 2. Measurement model

JKOHBZ_2019_v9n2_75_t0002.png 이미지

Table 3. The Squared Correlations and AVE of Variables

JKOHBZ_2019_v9n2_75_t0003.png 이미지

Table 4. Results of Hypotheses Testing

JKOHBZ_2019_v9n2_75_t0004.png 이미지

References

  1. M. K. Kim. (2016. 5. 8). Global e-commerce scale in 2 018...10% annual growth forecast. Chosun Biz. http://biz.chosun.com/site/data/html_dir/2016/05/08/2016050800561.html
  2. J. W. Choi. (2017. 2. 1). US Online Retail Market Gro wth. Kotra News. https://news.kotra.or.kr/user/globalAllBbs/kotranews/album/2/globalBbsDataAllView.do?dataIdx=156983&searchNationCd=101001
  3. D. Kim. (2018. 1. 24). US retail trend forecast for 2018. Kotra News. https://news.kotra.or.kr/user/globalBbs/kotranews/4/globalBbsDataView.do?setIdx=243&dataIdx=164492
  4. V. Todri & P. Adamopoulos. (2014). Social commerce: An empirical examination of the antecedents and consequences of commerce in social network platform. Thirty Fifth International Conference on Information Systems. Association for Information Systems. Auckland, New Zealand, 1-18.
  5. Y. J. Cho. (2017). A Customer Satisfaction Model for Social Commerce in China : Integration of EDT and TAM. Korea Science & Art Forum, 32. 293-304. DOI : 10.17548/ksaf.2018.01.30.293
  6. Sina. (2011. 9. 13). The revenue of online group-buyin g in USA will reach US$42 billion in 2015, http://finance.sina.com/bg/tech/sinacn/20110913/1751359523.html
  7. S. Cheng, K. R. Lee & S. J. Lee. (2017). Study on Chinese Repurchase Intention of Group-buying Social Commerce : The Moderating Role of Shopping Habit. Journal of the Korea Convergence Society, 8(2), 169-181. DOI : 10.15207/JKCS.2017.8.2.169
  8. J. N. Lee. (2015). A Study on the effects of Informatio n Quality on Customer Satisfaction to use in Chinese Social Commerce. Journal of Digital Convergence, 13 (9), 161-167. DOI : 10.14400/JDC.2015.13.9.161
  9. F. F. Reichheld & P. Schefter. (2000). E-Loyalty : Your Secret Weapon on the Web. Harvard Business Review, 78(4), 105-113.
  10. O. J. Lee & D. W. Yang. (2017). A Study on the Eff ect of O2O Service Quality on User Satisfaction and I ntention of Reuse. Journal of Digital Convergence, 15 (6), 165-178. DOI : 10.14400/JDC.2017.15.6.165
  11. A. K. Jaiswal, R. Niraj & P. Venugopal. (2010). Context-general and Context-specific Determinants of Online Satisfaction and Loyalty for Commerce and Content Sites. Journal of Interactive Marketing, 24, 222-238. DOI : 10.1016/j.intmar.2010.04.003
  12. C. H. Lee, U. C. Eze & N. O. Ndubisi. (2011). Analyzi ng key determinants of online repurchase intentions. A sia Pacific Journal of Marketing and Logistics, 23(2), 200-221. DOI : 10.1108/13555851111120498
  13. Y. J. Moon. (2008). E-loyalty in the B2C context: the effects of website factors via e-satisfaction/trust and the moderating role of switching costs. Korea Journal of Business Administration, 21(2), 587-614.
  14. H. J. Lee, E. Lee & K. Lee. (2017). The Impact of University Students' Perceived Service Quality of Mobile Social Commerce on Their Satisfaction and Continued Usage Intentions. Journal of Consumption Culture, 20(2), 235-254.
  15. C. H. Jung & D. H. Jung. (2015). The Effects of Social Commerce Characteristics on Satisfaction and Reuse Intention. Journal of Knowledge Information Technology and Systems, 10(2), 221-229.
  16. S. H. Kim & H. S. Park. (2013). An Empirical Study on Individual and Social Commerce Factors Impacting Shopping Value and Intention to Repurchase in Social Commerce and Moderating Effects of Perceived Security. Journal of Information Technology Services, 12(2), 31-53. DOI : 10.5859/KAIS.2013.22.2.1
  17. S. O. Olsen. (2002). Comparative Evaluation and the Relationship between Quality, Satisfaction, and Repurchase Loyalty. Journal of the Academy of Marketing Science, 30(3), 240-249. DOI : 10.1177/0092070302303005
  18. F. D. Davis. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319-339. DOI : 10.2307/249008
  19. P. Kotler & G. Armstrong. (2004). Principles of Marketing. New Jersey: Pearson/Prentice Hall.
  20. A. Bhattacherjee. (2001). An empirical analysis of the antecedents of electronic commerce service continuance. Decision Support Systems, 32(2), 201-214. DOI : 10.1016/S0167-9236(01)00111-7
  21. J. S. Chou & C. Kim. (2009). A structural equation analysis of the QSL relationship with passenger riding experience on high speed rail: An empirical study of Taiwan and Korea. Expert Systems with Applications, An International Journal archive, 36(3), 6945-6955. https://doi.org/10.1016/j.eswa.2008.08.056
  22. G. Human & P. Naude. (2014). Heterogeneity in the quality-satisfaction-loyalty framework. Industrial Marketing Management, 43(6), 920-928. DOI : 10.1016/j.indmarman.2014.05.006
  23. K. H. Cho & H. S. Bae. (2017). Convergence study of the in-flight meal quality on customer satisfaction, brand image and brand loyalty in airlines. Journal of the Korea Convergence Society, 8(12), 317-327. DOI : 10.15207/JKCS.2017.8.12.317
  24. V. Venkatesh, M. G. Morris, G. B. Davis & F. D. Davis. (2003). User acceptance of information technology: toward a unified view. MIS Quarterly, 27(3), 425-478. DOI : 10.2307/30036540
  25. A. Haque, J. Sadeghzadah & A. Khatibi. (2006). Identifying potentiality online sales in Malaysia: a study on customer relationships online shopping. Journal of Applied Business Research, 22(4), 119-130. DOI : 10.19030/jabr.v22i4.1420
  26. S. S. Shin, M. Shin, Y. S. Jeong, & J. Lee. (2015). An investigation of Social Commerce Service Quality on Consumer's Satisfaction. Journal of Convergence for Information Technology, 5(2), 27-32. https://doi.org/10.22156/CS4SMB.2015.5.2.027
  27. C. M. Sabiote, D. M. Frias & J. A. Castaneda. (2012). E-service quality as antecedent to e-satisfaction: the moderating effect of culture. Online Information Review, 36(2), 157-174. DOI : 10.1108/14684521211229011
  28. T. P. Kian, G. H. Boonb, S. W. L. Fongc & Y. J. Aid. (2017). Factors That Influence the Consumer Purchase Intention in Social Media Websites. ICARBSS 2017 Langkawi, Malaysia, 112-120.
  29. M. M. Montoya-Weiss, G. B. Voss & D. Grewal. (2003). Determinants of Online Channel Use and Overall Satisfaction with a Relational Multichannel Service Provider. Journal of the Academy of Marketing Science, 31(4), 448-458. DOI : 10.1177/0092070303254408
  30. E. T. Loiacono, R. T. Watson & D. L. Goodhue. (2007). WebQual: An Instrument for Consumer Evaluation of Web Sites. International Journal of Electronic Commerce, 11(3), 51-87. DOI : 10.2753/JEC1086-4415110302
  31. C. Fornell. (1992). A National Customer Satisfaction B arometer: The Swedish Experience. Journal of Marketi ng, 56(1), 6-21. DOI : 10.1177/002224299205600103
  32. C. G. Kim. (2013). The Effects of Internet Shopping Mall Attributes on Shopping Value, Consumer Satisfaction and Customer Loyalty. Korea Corporation Management Review, 20(1), 63-86.
  33. R. L. Oliver. (1980). A cognitive model of the antecedents and consequences of satisfaction decisions. Journal of Marketing Research, 17(4), 460-469. DOI : 10.2307/3150499
  34. A. Bhattacherjee & G. Premkumar. (2004). Understanding changes in belief and attitude toward information technology usage: a theoretical model and longitudinal test. MIS Quarterly, 28(2), 351-370. DOI : 10.2307/25148634
  35. Y. Kim, I H. Bae. (2007). The Effects of Website Factor and Consumer Factor on Internet Shopping Consumer Behavior. Journal of Product Research, 25(3), 133-147. https://doi.org/10.36345/kacst.2007.25.3.012
  36. H. Y. Jang & S. Y. Jung. (2014). The Interactions among Social Commerce Properties, Satisfaction, and Reuse Intention according to the Consumer Propensity and Attitude. Academy of customer satisfaction management, 16(4), 167-192.
  37. N. K. Lankton, D. H. McKnight & J. B. Thatcher. (2012). The Moderating Effects of Privacy Restrictiveness and Experience on Trusting Beliefs and Habit: An Empirical Test of Intention to Continue Using a Social Networking Website. IEEE Transactions on Engineering Management, 59(4), 654-665. DOI : 10.1109/TEM.2011.2179048
  38. W. M. Lim & D. H. Ting. (2012). E-shopping: an Analysis of the Technology Acceptance Model. Modern Applied Science. 6(4), 49-62. DOI : 10.5539/mas.v6n4p49
  39. L. R. Vijayasarathy. (2004). Predicting consumer intentions to use online shopping: the case for an augmented technology acceptance model. Information & Management, 41(6), 747-762. DOI : 10.1016/j.im.2003.08.011
  40. M. H. Hsu, C. M. Chang, K. K. Chu & Y. J. Lee. (2014). Determinants of Repurchase Intention in Online Group-buying: The Perspectives of DeLone & McLean IS Success Model and Trust. Computers in Human Behavior, 36, 234-245. DOI : 10.1016/j.chb.2014.03.065
  41. F. D. Davis, R. P. Bagozzi & P. R. Warshaw. (1989). User acceptance of computer technology: a comparison of two theoretical models. Management Science, 35(8), 982-1003. DOI : 10.1287/mnsc.35.8.982
  42. K. S. Kim. (2010). AMOS 18.0 Structural Equation Model Analysis. Seoul.: Hannarae.
  43. R. P. Bagozzi & Y. Yi. (1988). On the evaluation of structural equation models. Journal of the Academy of Marketing Science, 16(1), 74-94. DOI : 10.1007/BF02723327
  44. C. Fornell & D. F. Larcker. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39-50. DOI : 10.2307/3151312