Journal of the Korean Society of Clothing and Textiles (한국의류학회지)

The Korean Society of Clothing and Textiles (한국의류학회)
권호 표지
DOI QR코드

DOI QR Code

The Formation of Attitudes Toward Cross-Border Shopping Websites -Perceived Benefits, COVID-19 Anxiety, and Brand Familiarity-

  • Heesoon Yang (Fashion and Textiles Major, Sangmyung University) ;
  • Yun Jung Choi (Dept. of Fashion and Clothing, Mokpo National University) ;
  • Hye Jung Jung (Da Vinci College of General Education, Chung-Ang University) ;
  • Chorong Youn (Dept. of Clothing & Textiles, Pusan National University/Research Institute of Human Ecology, Pusan National University)
  • Received : 2023.02.08
  • Accepted : 2023.07.01
  • Published : 2023.08.31
Download PDF
⟨ Previous Next ⟩

Abstract

This study aimed to explore the effects of perceived benefits on consumers' attitudes towards cross-border online shopping websites. We also explore whether and how consumers' COVID-19 anxiety and brand familiarity weaken or strengthen the relationship between these perceived benefits and consumer attitudes. A total 319 items of data were used for the final analysis. The perceived benefits of a website were found to have only an indirect effect on purchase intentions by mediating consumers' attitudes toward the site. Competitive pricing of fashion products directly affected purchase intentions. COVID-19 anxiety was found to have a negative moderating influence on the relationship between perceived enjoyment and consumer attitudes, whereas brand familiarity had a positive moderating effect on both the relationships between perceived usefulness and consumers' attitudes toward the site and between perceived ease of use and their site attitude. This study provides useful insights for international e-tailers in developing marketing strategies that attract international consumers. Academically, we have contributed to the existing literature on the perceived benefits of global online shopping and the moderators of consumers' attitudes towards e-commerce sites.

Keywords

Acknowledgement

This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (No. NRF-2019R1G1A1010684).

References

  1. Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179-211. https://doi.org/10.1016/0749-5978(91)90020-T 
  2. Ajzen, I., & Fishbein, M. (1980). Understanding attitudes and predicting social behaviour. Prentice Hall.
  3. Alba, J. W., & Hutchinson, J. W. (1987). Dimensions of consumer expertise. Journal of Consumer Research, 13(4), 411-454. http://www.jstor.org/stable/2489367  https://doi.org/10.1086/209080
  4. Ali, B. J. (2020). Impact of COVID-19 on consumer buying behavior toward online shopping in Iraq. Economic Studies Journal, 18(42), 267-280. 
  5. An, S., Jung, J., & Lee, H.-H. (2016). A study on cross-border online shoppers for fashion products by benefit sought. International Journal of Costume and Fashion, 16(2), 25-50. http://dx.doi.org/10.7233/ijcf.2016.16.2.025 
  6. Aryani, D. N., Nair, R. K., Hoo, D. X. Y., Hung, D. K. M., Lim, D. H. R., Chew, W. P., & Desai, A. (2021). A study on consumer behaviour: Transition from traditional shopping to online shopping during the COVID-19 pandemic. International Journal of Applied Business and International Management (IJABIM), 6(2), 81-95. https://doi.org/10.32535/ijabim.v6i2.1170 
  7. Augusta, E. D., Mardhiyah, D., & Widiastuti, T. (2019). Effect of country of origin image, product knowledge, brand familiarity to purchase intention Korean cosmetics with information seeking as a mediator variable: Indonesian women's perspective. Dermatology Reports, 11(s1), 7-10. https://doi.org/10.4081/dr.2019.8014 
  8. Baek, E., Lee, H. K., & Choo, H. J. (2020). Cross-border online shopping experiences of Chinese shoppers. Asia Pacific Journal of Marketing and Logistics, 32(2), 366-385. https://doi.org/10.1108/APJML-03-2018-0117 
  9. Biucky, S. T., Abdolvand, N., & Harandi, S. R. (2017). The effects of perceived risk on social commerce adoption based on tam model. International Journal of Electronic Commerce Studies, 8(2), 173-196. http://dx.doi.org/10.7903/ijecs.1538 
  10. Castaneda, J. A., Munoz-Leiva, F., & Luque, T. (2007). Web acceptance model (WAM): Moderating effects of user experience. Information & Management, 44(4), 384-396. https://doi.org/10.1016/j.im.2007.02.003 
  11. Cebeci, U., Ince, O., & Turkcan, H. (2019). Understanding the intention to use Netflix: An extended technology acceptance model approach. International Review of Management and Marketing, 9(6), 152-157. https://doi.org/10.32479/irmm.8771 
  12. Chen, J., Xu, S., Zhao, C., & Chen, H. (2021). Cross-border e-commerce competitive strategy based on the survey of product differentiation. In H. Song, & D. Jiang (Eds.), Simulation Tools and Techniques (pp. 659-678). Springer. https://doi.org/10.1007/978-3-030-72795-6_53 
  13. Chen, N., & Yang, Y. (2021). The impact of customer experience on consumer purchase intention in cross-border E-commerce-taking network structural embeddedness as mediator variable. Journal of Retailing and Consumer Services, 59, 102344. https://doi.org/10.1016/j.jretconser.2020.102344 
  14. Chiang, K.-P., & Dholakia, R. R. (2003). Factors driving consumer intention to shop online: An empirical investigation. Journal of Consumer psychology, 13(1-2), 177-183. https://doi.org/10.1207/S15327663JCP13-1&2_16 
  15. Choi, H., Kim, Y., & Kim, J. (2010). An acceptance model for an internet protocol television service in Korea with prior experience as a moderator. The Service Industries Journal, 30(11), 1883-1901. https://doi.org/10.1080/02642060802627178 
  16. Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319-340. https://doi.org/10.2307/249008 
  17. Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1992). Extrinsic and intrinsic motivation to use computers in the workplace. Journal of Applied Social Psychology, 22(14), 1111-1132. https://doi.org/10.1111/j.1559-1816.1992.tb00945.x 
  18. Dmitrovic, T., & Vida, I. (2007). Saliency of product origin information in consumer choices. Management: Journal of Contemporary Management Issues, 12(2), 1-23. 
  19. Donmez-Turan, A., & Kir, M. (2019). User anxiety as an external variable of technology acceptance model: A meta-analytic study. Procedia Computer Science, 158, 715-724. https://doi.org/10.1016/j.procs.2019.09.107 
  20. Eger, L., Komarkova, L., Egerova, D., & Micik, M. (2021). The effect of COVID-19 on consumer shopping behaviour: Generational cohort perspective. Journal of Retailing and Consumer Services, 61, 102542. https://doi.org/10.1016/j.jretconser.2021.102542 
  21. Evanschitzky, H., Iyer, G. R., Pillai, K. G., Kenning, P., & Schutte, R. (2015). Consumer trial, continuous use, and economic benefits of a retail service innovation: The case of the personal shopping assistant. Journal of Product Innovation Management, 32(3), 459-475. https://doi.org/10.1111/jpim.12241 
  22. Eysenck, M. W., Derakshan, N., Santos, R., & Calvo, M. G. (2007). Anxiety and cognitive performance: Attentional control theory. Emotion, 7(2), 336-353. https://doi.org/10.1037/1528-3542.7.2.336 
  23. Featherman, M. S., & Pavlou, P. A. (2003). Predicting e-services adoption: A perceived risk facets perspective. International Journal of Human-Computer Studies, 59(4), 451-474. https://doi.org/10.1016/S1071-5819(03)00111-3 
  24. Gefen, D., Karahanna, E., & Straub, D. W. (2003). Trust and TAM in online shopping: An integrated model. MIS Quarterly, 27(1), 51-90. https://doi.org/10.2307/30036519 
  25. Gielens, K., & Steenkamp, J.-B. E. (2007). Drivers of consumer acceptance of new packaged goods: An investigation across products and countries. International Journal of Research in Marketing, 24(2), 97-111. https://doi.org/10.1016/j.ijresmar.2006.12.003 
  26. Grable, J. E., Archuleta, K. L., Ford, M. R., Kruger, M., Gale, J., & Goetz, J. (2020). The moderating effect of generalized anxiety and financial knowledge on financial management behavior. Contemporary Family Therapy, 42(1), 15-24. https://doi.org/10.1007/s10591-019-09520-x 
  27. Ha, S., & Stoel, L. (2009). Consumer e-shopping acceptance: Antecedents in a technology acceptance model. Journal of Business Research, 62(5), 565-571. https://doi.org/10.1016/j.jbusres.2008.06.016 
  28. Hair Jr, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2021). A primer on partial least squares structural equation modeling (PLS-SEM). Sage publications. 
  29. Han, B., Kim, M., & Lee, J. (2018). Exploring consumer attitudes and purchasing intentions of cross-border online shopping in Korea. Journal of Korea Trade, 22(2), 86-104. https://doi.org/10.1108/JKT-10-2017-0093 
  30. Huang, S.-L., & Chang, Y.-C. (2019). Cross-border e-commerce: Consumers' intention to shop on foreign websites. Internet Research, 29(6), 1256-1279. https://doi.org/10.1108/INTR-11-2017-0428 
  31. Jensen, K. L., Yenerall, J., Chen, X., & Yu, T. E. (2021). US consumers' online shopping behaviors and intentions during and after the COVID-19 pandemic. Journal of Agricultural and Applied Economics, 53(3), 416-434. https://doi.org/10.1017/aae.2021.15 
  32. Kazancoglu, I., & Yarimoglu, E. K. (2018). How food retailing changed in Turkey: Spread of self-service technologies. British Food Journal, 120(2), 290-308. https://doi.org/10.1108/BFJ-03-2017-0189 
  33. Kim, C., Hwang, J. S., & Cho, J. (2015). Relationships among mobile fashion shopping characteristics, perceived usefulness, perceived enjoyment, and purchase intention: Mediating effect of ease of use. Journal of the Korean Society of Clothing and Textiles, 39(2), 161-174. http://dx.doi.org/10.5850/JKSCT.2015.39.2.161 
  34. Kim, T. Y., Dekker, R., & Heij, C. (2017). Cross-border electronic commerce: Distance effects and express delivery in European Union markets. International Journal of Electronic Commerce, 21(2), 184-218. https://doi.org/10.1080/10864415.2016.1234283 
  35. Kimiagari, S., & Malafe, N. S. A. (2021). The role of cognitive and affective responses in the relationship between internal and external stimuli on online impulse buying behavior. Journal of Retailing and Consumer Services, 61, 102567. https://doi.org/10.1016/j.jretconser.2021.102567 
  36. Klopping, I. M., & McKinney, E. J. (2006). Practice makes a difference: Experience and e-commerce. Information Technology, Learning, and Performance Journal, 24(1), 25-37. 
  37. KOSIS. (2022, May 2). Overseas direct purchase amount of online shopping by country. https://kostat.go.kr/portal/korea/kor_nw/1/1/index.board?bmode=read&aSeq=41803. 
  38. Laato, S., Islam, A. N., Farooq, A., & Dhir, A. (2020). Unusual purchasing behavior during the early stages of the COVID-19 pandemic: The stimulus-organism-response approach. Journal of Retailing and Consumer Services, 57, 102224. https://doi.org/10.1016/j.jretconser.2020.102224 
  39. Laroche, M., Kim, C., & Zhou, L. (1996). Brand familiarity and confidence as determinants of purchase intention: An empirical test in a multiple brand context. Journal of Business Research, 37(2), 115-120. https://doi.org/10.1016/0148-2963(96)00056-2 
  40. Lazarus, R. S. (1991). Emotion and adaptation. Oxford University Press.
  41. Lee, H., Xu, Y., & Porterfield, A. (2022). Antecedents and moderators of consumer adoption toward AR-enhanced virtual try-on technology: A stimulus-organism-response approach. International Journal of Consumer Studies, 46(4), 1319-1338. https://doi.org/10.1111/ijcs.12760 
  42. Lee, Y., Kozar, K. A., & Larsen, K. R. (2003). The technology acceptance model: Past, present, and future. Communications of the Association for Information Systems, 12(50), 752-780. 
  43. Lin, A. J., Li, E. Y., & Lee, S.-Y. (2018). Dysfunctional customer behavior in cross-border e-commerce: A justiceaffect-behavior model. Journal of Electronic Commerce Research, 19(1), 36-54. 
  44. Macdonald, E. K., & Sharp, B. M. (2000). Brand awareness effects on consumer decision making for a common, repeat purchase product: A replication. Journal of Business Research, 48(1), 5-15. https://doi.org/10.1016/S0148-2963(98)00070-8 
  45. Plotkina, D., & Saurel, H. (2019). Me or just like me? The role of virtual try-on and physical appearance in apparel M-retailing. Journal of Retailing and Consumer Services, 51, 362-377. https://doi.org/10.1016/j.jretconser.2019.07.002 
  46. Rogers, E. (2003). Diffusion of Innovations (5th ed.). Free Press.
  47. Saleh, K. (2016). Cross-border shopping-statistics and trends. Invesp. https://www.invespcro.com/blog/cross-border-shopping 
  48. Shankar, A., & Jain, S. (2021). Factors affecting luxury consumers' webrooming intention: A moderated-mediation approach. Journal of Retailing and Consumer Services, 58, 102306. https://doi.org/10.1016/j.jretconser.2020.102306 
  49. Shao, B., Cheng, Z., Wan, L., & Yue, J. (2021). The impact of cross border E-tailer's return policy on consumer's purchase intention. Journal of Retailing and Consumer Services, 59, 102367. https://doi.org/10.1016/j.jretconser.2020.102367 
  50. Sharma, A., & Jhamb, D. (2020). Changing consumer behaviours towards online shopping-an impact of Covid 19. Academy of Marketing Studies Journal, 24(3), 1-10. 
  51. Srinivasan, R. (2015). Exploring the impact of social norms and online shopping anxiety in the adoption of online apparel shopping by Indian consumers. Journal of Internet Commerce, 14(2), 177-199. https://doi.org/10.1080/15332861.2015.1008891 
  52. Thapa, S., Guzman, F., & Paswan, A. K. (2022). How isolation leads to purchasing luxury brands: The moderating effects of COVID-19 anxiety and social capital. Journal of Product & Brand Management, 31(6), 984-1001. https://doi.org/10.1108/JPBM-05-2021-3500 
  53. Tian, T. K., & McKenzie, K. (2001). The long-term predictive validity of the consumers' need for uniqueness scale. Journal of Consumer Psychology, 10(3), 171-193. https://doi.org/10.1207/s15327663jcp1003_5 
  54. Van der Heijden, H., Verhagen, T., & Creemers, M. (2003). Understanding online purchase intentions: Contributions from technology and trust perspectives. European Journal of Information Systems, 12(1), 41-48. https://doi.org/10.1057/palgrave.ejis.3000445 
  55. Wagner, G., Schramm-Klein, H., & Schu, M. (2016). Determinants and moderators of consumers' cross-border online shopping intentions. Marketing: ZFP, 38(4), 214-227. https://doi.org/10.15358/0344-1369-2016-4-214 
  56. Xiao, L., Guo, F., Yu, F., & Liu, S. (2019). The effects of online shopping context cues on consumers' purchase intention for cross-border e-commerce sustainability. Sustainability, 11(10), 2777. https://doi.org/10.3390/su11102777 
  57. Ye, H. (2018, March 29-30). Research on the cross-border shopping behavior of consumers based on TAM model and perceived risk. [Paper presentation]. The 2nd International Conference on Economics and Management, Education, Humanities and Social Sciences (EMEHSS 2018), Wuhan, China. https://doi.org/10.2991/emehss-18.2018.1 
  58. Yeung, R. M. W., & Morris, J. (2001). Food safety risk: Consumer perception and purchase behaviour. British Food Journal, 103(3), 170-187. https://doi.org/10.1108/00070700110386728 
  59. yStats. (2021). Global cross-border B2C E-commerce 2021. https://www.researchandmarkets.com/ 
  60. Yuan, C., Zhang, C., & Wang, S. (2022). Social anxiety as a moderator in consumer willingness to accept AI assistants based on utilitarian and hedonic values. Journal of Retailing and Consumer Services, 65, 102878. https://doi.org/10.1016/j.jretconser.2021.102878 
  61. Zeithaml, V. A. (1982). Consumer response to in-store price information environments. Journal of Consumer Research, 8(4), 357-369. https://doi.org/10.1086/208876