Knowledge Management Research (지식경영연구)

The Knowledge Management Society of Korea (한국지식경영학회)
권호 표지
DOI QR코드

DOI QR Code

How User-Generated Content Characteristics Influence the Impulsive Consumption: Moderating Effect of Tie Strength

사용자 제작 콘텐츠 특성이 충동구매에 미치는 영향: 유대강도의 조절효과를 중심으로

  • 라위의 (중국 호남인문과학기술대학교 경영대학) ;
  • 이영찬 (동국대학교 WISE캠퍼스 상경대학 경영학부)
  • Received : 2022.10.16
  • Accepted : 2022.11.08
  • Published : 2022.12.31
Download PDF
⟨ Previous Next ⟩

Abstract

In recent years, with the continuous integrative development of e-commerce and social media, social commerce, as a trust-centered social transaction mode, has become an important performance form of e-commerce. The good experience of online community and abundant user-generated content (UGC) attract more and more users and businesses to participate in the community contribution. In this context, the cost of accessing information is continuously decreasing, which not only makes the purchase process more concise and efficient, but also greatly increases the possibility of consumers' impulsive consumption. However, there are very few empirical studies on the internal influencing mechanism of consumers' impulsive consumption based on the characteristics of UGC for social commerce. In view of this, based on S-O-R model, this study constructs a model of consumers' impulsive consumption in the context of social commerce from the characteristics of UGC, with perceived risk as the mediating variable and tie strength as the moderating variable. The results show that content authenticity, content usefulness, and content valence of UGC have significant negative impacts on consumers' risk perception in the process of purchase decision-making, and consumers' perceived risk has a significant negative impact on consumers' impulsive consumption. Meanwhile, the tie strength between UGC producer and UGC receiver plays a moderating role between content usefulness and perceived risk, as well as between perceived risk and impulsive consumption. Finally, combined with the above findings, this study provides effective suggestions for relevant participants in social commerce in terms of business management.

최근 몇 년 동안 전자상거래와 소셜미디어의 지속적인 통합 발전과 함께 소셜커머스는 신뢰 중심의 사회적 거래 방식으로서 전자상거래의 중요한 형태로 자리를 잡았다. 온라인 커뮤니티의 긍정적인 측면과 풍부한 사용자 제작 콘텐츠 (UGC)로 인해 커뮤니티에 참여하는 사용자와 기업이 점점 더 증가하고 있는 추세이다. 이러한 상황에서 정보접근 비용은 지속적으로 감소하고 있고 구매 프로세스는 보다 간결하고 효율적으로 개선되고 있는 반면에 소비자의 충동구매 가능성을 크게 높이는 결과를 가져오게 된다. 그럼에도 불구하고 아직까지 소셜커머스에서 UGC의 특성을 기반으로 한 소비자 충동구매의 메커니즘에 대한 실증적 연구는 거의 없다. 본 연구는 자극-유기체-반응 (S-O-R) 모델을 이용하여 소셜커머스에서 UGC 특성이 소비자 충동구매에 미치는 영향을 분석하는 연구모형을 구축하였고, 이 과정에서 지각된 위험을 매개변수로, 유대강도를 조절변수로 각각 설정하였다. 실증분석 결과 콘텐츠 진정성, 콘텐츠 유용성, 그리고 콘텐츠 가치는 구매의사결정 과정에서 소비자의 지각된 위험에 유의한 영향을 미치고, 소비자의 지각된 위험은 충동구매에 유의한 영향을 미치는 것으로 나타났다. 한편, UGC 생산자와 이용자 간의 유대강도는 콘텐츠 유용성과 지각된 위험의 관계 및 지각된 위험과 충동구매 관계를 조절하는 것으로 나타났다. 이러한 연구결과는 소셜커머스 사업자들로 하여금 고객의 소비행동에 대한 심층적인 이해를 도울 뿐만 아니라 소비자 충동구매가 왜 일어나는지에 대한 메커니즘을 학술적 관점에서 분석할 수 있는 이론적 틀을 제공하였다는 점에서 의의가 있다.

Keywords

Acknowledgement

This study was supported by the Outstanding Youth Project of Education Bureau of Hunan Province, China (18B451) and the Construct Program of the Applied Characteristic Discipline - Applied Economics in Hunan Province (2018469).

References

  1. Han, S., Jang, J., Choi, J., & Chang, S. R. (2021). The relationship between social media and consumer purchase decision: Findings from Seoul sharing bike. Knowledge Management Research, 22(4), 135-155.
  2. Kim, B., & Kim, D. (2020). The empirical study on the effects of repurchase intention on Airbnb: The role of emotions and key components of Airbnb. Knowledge Management Research, 21(4), 89-108.
  3. Tenzin, C., & Lee, Y. C. (2020). The effect of social media marketing activities on purchase intention with brand equity and social brand engagement: Empirical evidence from Korean cosmetic firms. Knowledge Management Research, 21(3), 141-160.
  4. Al-Debei, M., Akroush, M. N., & Ashouri, M. I. (2015). Consumer attitudes towards online shopping. Internet Research, 25(5), 707-733.
  5. Bauer, R. A. (1960). Consumer behavior as risk taking dynamic marketing for a changing world. In Proceedings of the 43rd Conference of the American Marketing Association, 389-398.
  6. Belk, R. W. (1975). Situational variables and consumer behavior. Journal of Consumer Research, 2(3), 157-164. https://doi.org/10.1086/208627
  7. Bone, F. P. (1992). Determinants of word-of-mouth communications during product consumption. Advanced in Consumer Research, 19(1), 579-583.
  8. Brown, J. J., & Reingen, P. H. (1987). Social ties and word-of-mouth referral behavior. Journal of Consumer Research, 14(3), 350-362.
  9. Bruyn, A. D., & Lilien, G. L. (2008). A multi-stage model of word-of-mouth influence through viral marketing. International Journal of Research in Marketing, 25(3), 151-163. https://doi.org/10.1016/j.ijresmar.2008.03.004
  10. Burgess, S., Sellitto, C., Cox, C., & Buultjens, J. (2009). Trust perceptions of online travel information by different content creators: Some social and legal implications. Information Systems Frontiers, 13(2), 221-235.
  11. Chen, P. Y., Dhanasobhon, S., & Smith, M. (2018). All reviews are not created equal: The disaggregate impact of reviews and reviewers at Amazon.com. Carnegie Mellon University. Journal Contribution. https://doi.org/10.1184/R1/6471002.v1
  12. Chen, Q., Rodgers, S., & He, Y. (2008). A critical review of the e-satisfaction literature. American Behavioral Scientist, 52(1), 38-59.
  13. Christodoulides, G., Jevons, C., & Bonhomme, J. (2012). Memo to marketers: Quantitative evidence for change. Journal of Advertising Research, 52(1), 53-64. https://doi.org/10.2501/JAR-52-1-053-064
  14. Clemons, E. K., Gao, G., & Hitt, L. M. (2006). When online review meet hyper differentiation: A study of the craft beer industry. Journal of Management Information Systems, 23(2), 149-171.
  15. Dodds, W. B., Monroe, K. B., & Grewal, D. (1991). Effects of price, brand, and store information on buyers' product evaluations. Journal of Marketing Research, 28(3), 307-319.
  16. 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
  17. Fang, Y. H. (2014). Beyond the credibility of electronic word of mouth: Exploring eWOM adoption on social networking sites from affective and curiosity perspectives. International Journal of Electronic Commerce, 18(3), 67-101. https://doi.org/10.2753/JEC1086-4415180303
  18. 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/10.1177/002224378101800104
  19. Gilly, M. C., Graham, J. L., & Wolfinbarger, M. F. (1998). A dyadic study of interpersonal information search. Journal of the Academy of Marketing Science, 26(2), 83-100. https://doi.org/10.1177/0092070398262001
  20. Granovetter, M. S. (1973). The strength of weak ties. American Journal of Sociology, 78(6), 1360-1380. https://doi.org/10.1086/225469
  21. Hair, J., Black, W., Babin, B., Anderson, R., & Tatham, R. (2006). Multivariate data analysis (6th ed.). Upper Saddle River, NJ: Pearson Prentice Hall.
  22. Ho-Dac, N. N., Carson, S. J., & Moore, W. L. (2013). The effects of positive and negative online customer reviews: Do brand strength and category maturity matter? Journal of Marketing, 77(6), 37-53.
  23. Hossain, L., & De Silva, A. (2009). Exploring user acceptance of technology using social networks. The Journal of High Technology Management Research, 20(1), 1-18. https://doi.org/10.1016/j.hitech.2009.02.005
  24. Hsu, C. L., & Lu, H. P. (2004). Why do people play online games? An extended TAM with social influences and flow experience. Information & Management, 41(7), 853-868. https://doi.org/10.1016/j.im.2003.08.014
  25. Hsu, M. H., Chang, C. M., & Yen, C. H. (2011). Exploring the antecedents of trust in virtual communities. Behaviour and Information Technology, 30(5), 587-601. https://doi.org/10.1080/0144929X.2010.549513
  26. Hussain, A., Mkpojiogu, E., & Kamal, F. M. (2016). Antecedents to user adoption of interactive mobile maps. Journal of Telecommunication, Electronic and Computer Engineering, 8(10), 41-45.
  27. Hussain, S., Ahmed, W., Jafar, R., Rabnawaz, A., & Yang, J. (2017). eWOM source credibility, perceived risk and food product customer's information adoption. Computers in Human Behavior, 66, 96-102. https://doi.org/10.1016/j.chb.2016.09.034
  28. Kim, J., & Lennon, S. J. (2013). Effects of reputation and website quality on online consumers' emotion perceived risk and purchase intention: Based on the stimulus-organism-response model. Journal of Research in Interactive Marketing, 7(1), 33-56. https://doi.org/10.1108/17505931311316734
  29. Koo, D. (2016). Impact of tie strength and experience on the effectiveness of online service recommendations. Electronic Commerce Research and Applications, 15(1), 38-51. https://doi.org/10.1016/j.elerap.2015.12.002
  30. Lawrence, B., Fournier, S., & Brunel, F. (2013). When companies don't make the ad: A multi-method inquiry into the differential effectiveness of consumer-generated advertising. Journal of Advertising, 42(4), 292-307. https://doi.org/10.1080/00913367.2013.795120
  31. Liao, Z., & Cheung, M. T. (2001). Internet-based e-shopping and consumer attitudes: An empirical study. Information & Management, 38(5), 299-306. https://doi.org/10.1016/S0378-7206(00)00072-0
  32. Luo, C., Luo, X. R., & Xu, Y. (2015). Examining the moderating role of sense of membership in online review evaluations. Information & Management, 52(3), 305-316. https://doi.org/10.1016/j.im.2014.12.008
  33. Paul, A. P., Liang, H., & Xue, Y. (2007). Understanding and mitigating uncertainty in online exchange relationships: A principal-agent perspective. MIS Quarterly, 31(1), 105-136.
  34. Peters, K., Chen, Y., Kaplan, A., & Ognibeni, B. (2013). Social media metrics: A framework and guidelines for managing social media. Journal of Interactive Marketing, 27(4), 281-298. https://doi.org/10.1016/j.intmar.2013.09.007
  35. Riegner, C. (2007). Word of Mouth on the web: The impact of web 2.0 on consumer purchase decisions. Journal of Advertising Research, 47(4), 436-447. https://doi.org/10.2501/S0021849907070456
  36. Rodgers, S., & Chen, Q. (2005). Internet community group participation psychosocial benefits for women with breast cancer. Journal of Computer-Mediated Communication, 10(4), 1-27.
  37. Rogers, E. M. (1995). Diffusion of innovations. New York: Free Press.
  38. Sautter, P. (2004). E-tail atmospherics: A critique of the literature and model extension. Journal of Electronic Commerce Research, 5(1), 14-24.
  39. Schulze, C., Scholer, L., & Skiera, B. (2014). Not all fun and games: Viral marketing for utilitarian products. Journal of Marketing, 78(1), 1-19. https://doi.org/10.1509/jm.11.0528
  40. 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
  41. Smith, D. N., & Sivakumar, K. (2004). Flow and Internet shopping behavior: A conceptual model and research propositions. Journal of Business Research, 57(10), 1199-1208. https://doi.org/10.1016/S0148-2963(02)00330-2
  42. Sweeney, J. C., Soutar, G. N., & Mazzarol, T. (2008). Factors influencing word of mouth effectiveness: Receiver perspectives. European Journal of Marketing, 42(3-4), 344-364. https://doi.org/10.1108/03090560810852977
  43. Sweeney, J., & Soutar, G. N. (2001). Consumer perceived value the development of a multiple item scale. Journal of Retailing, 77(2), 203-220. https://doi.org/10.1016/S0022-4359(01)00041-0
  44. Thompson, D. V., & Malaviya, P. (2013). Consumer-generated ads: Does awareness of advertising co-creation help or hurt persuasion. Journal of Marketing, 77(3), 33-47. https://doi.org/10.1509/jm.11.0403
  45. Vinzi, V. E., Chin, W. W., Henseler, J., & Wang, H. (2010). Handbook of partial least squares: Concepts, methods and applications in marketing and related fields. Springer Science & Business Media.
  46. Wood, C. M., & Scheer, L. K. (1996). Incorporating perceived risk into models of consumer deal assessment and purchase intent. Advances in Consumer Research, 23(1), 399-404.
  47. Yu, G., & Zou, D. (2015). Which user-generated content should be appreciated more?-A study on UGC features, consumers' behavioral intentions and social media engagement. ECIS 2015 Completed Research Papers, Paper 211.