The Pseudo-Flow Experience in Online Shopping

References

• Akar, E. (2021). Customers’ online purchase intentions and customer segmentation during the period of COVID-19 pandemic. Journal of Internet Commerce, 20(3), 371–401. https://doi.org/10.1080/15332861.2021.1927435
   Web of Science ®Google Scholar
• Bagozzi, R. P., Gopinath, M., & Nyer, P. U. (1999). The role of emotions in marketing. Journal of the Academy of Marketing Science, 27(2), 184–206. https://doi.org/10.1177/0092070399272005
   Web of Science ®Google Scholar
• Bai, X., & Luo, M. (2011). How much is trust worth? Evidence from the international online textbook market. Journal of Internet Commerce, 10(4), 245–260. https://doi.org/10.1080/15332861.2011.622692
   Google Scholar
• Barta, S., Gurrea, R., & Flavián, C. (2022). The role of flow consciousness in consumer regret. Internet Research, 32(3), 875–896. https://doi.org/10.1108/INTR-08-2020-0482
   Web of Science ®Google Scholar
• Çebi Karaaslan, K. (2023). Determinants of online shopping attitudes of households in Turkey. Journal of Modelling in Management, 17(1), 119–133. https://doi.org/10.1108/JM2-04-2021-0101
   Web of Science ®Google Scholar
• Chattaraman, V., Kwon, W. S., Gilbert, J. E., & Li, Y. (2014). Virtual shopping agents. Journal of Research in Interactive Marketing, 8(2), 144–162. https://doi.org/10.1108/JRIM-08-2013-0054
   Google Scholar
• Chen, Y.-T., & Chou, T.-Y. (2012). Exploring the continuance intentions of consumers for B2C online shopping: Perspectives of fairness and trust. Online Information Review, 36(1), 104–125. https://doi.org/10.1108/14684521211209572
   Web of Science ®Google Scholar
• Csikszentmihályi, M. (1975). Beyond boredom and anxiety. Jossey-Bass.
   Google Scholar
• Csikszentmihályi, M. (1990). Flow: The psychology of optimal experience. Harper and Row.
   Google Scholar
• De Almeida, S. O., Scaraboto, D., Santos Fleck, J. P., & Dalmoro, M. (2018). Seriously engaged consumers: Navigating between work and play in online brand communities. Journal of Interactive Marketing, 44, 29–42. https://doi.org/10.1016/j.intmar.2018.05.006
   Web of Science ®Google Scholar
• Diamantopoulos, A., Sarstedt, M., Fuchs, C., Wilczynski, P., & Kaiser, S. (2012). Guidelines for choosing between multi-item and single-item scales for construct measurement: A predictive validity perspective. Journal of the Academy of Marketing Science, 40(3), 434–449. https://doi.org/10.1007/s11747-011-0300-3
   Web of Science ®Google Scholar
• Dijkstra, T. K., & Henseler, J. (2015). Consistent partial least squares path modeling. MIS Quarterly, 39(2), 297–316. https://doi.org/10.25300/MISQ/2015/39.2.02
   Web of Science ®Google Scholar
• Fang, J., George, B., Shao, Y., & Wen, C. (2016). Affective and cognitive factors influencing repeat buying in e-commerce. Electronic Commerce Research and Applications, 19, 44–55. https://doi.org/10.1016/j.elerap.2016.08.001
   Web of Science ®Google Scholar
• Gentile, C., Spiller, N., & Noci, G. (2007). How to sustain the customer experience: An overview of experience components that cocreate value with the customer. European Management Journal, 25(5), 395–410. https://doi.org/10.1016/j.emj.2007.08.005
   Google Scholar
• Gunness, A., & Oppewal, H. (2020). How mindset and store familiarity impact online stockout responses. International Journal of Retail & Distribution Management, 48(4), 326–347. https://doi.org/10.1108/IJRDM-02-2018-0034
   Web of Science ®Google Scholar
• Hair, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2017). A Primer on Partial Least Squares Structural Equation Modelling (PLS-SEM). 2nd Edition. SAGE.
   Google Scholar
• Han, M. C., & Kim, J. (2017). Why consumers hesitate to shop online: perceived risk and product involvement on Taobao.com. Journal of Promotion Management, 23(1), 24–44. https://doi.org/10.1080/10496491.2016.1251530
   Google Scholar
• Hernandez, M. (2011). A model of flow experience as determinant of positive attitudes toward online advergames. Journal of Promotion Management, 17(3), 315–326. https://doi.org/10.1080/10496491.2011.596761
   Google Scholar
• Henseler, J., Hubona, G., & Ray, P. A. (2016). Using PLS path modeling in new technology research. Updated guidelines. Industrial Management & Data Systems, 116(1), 2–20. https://doi.org/10.1108/IMDS-09-2015-0382
   Web of Science ®Google Scholar
• Hoffman, D. L., & Novak, T. P. (2009). Flow online: Lessons learned and future prospects. Journal of Interactive Marketing, 23(1), 23–34. https://doi.org/10.1016/j.intmar.2008.10.003
   Web of Science ®Google Scholar
• Hsu, T.-H., Tang, J.-W., & Chen, C.-H. (2023). An SEM-ANP multi-criteria evaluation model for mobile advertising that affect purchase intentions: Perspectives on the values of context awareness and flow experience. Journal of Promotion Management, 29(3), 383–404. https://doi.org/10.1080/10496491.2022.2143984
   Google Scholar
• İçözü, T. (2020). Gemius Türkiye’den E-Ticarette Kasım Kampanyaları Verisi. Webrazzi. Retrieved March 19, 2023, from https://webrazzi.com/2020/12/14/gemius-turkiye-den-e-ticarette-kasim-kampanyalari-verisi/.
   Google Scholar
• Jiang, Y., & Katsamakas, E. (2010). Impact of e-book technology: Ownership and market asymmetries in digital transformation. Electronic Commerce Research and Applications, 9(5), 386–399. https://doi.org/10.1016/j.elerap.2010.06.003
   Web of Science ®Google Scholar
• Kaya, B., Behravesh, E., Abubakar, A. M., Kaya, O. S., & Orús, C. (2019). The moderating role of website familiarity in the relationships between e-service quality, e-satisfaction and e-loyalty. Journal of Internet Commerce, 18(4), 369–394. https://doi.org/10.1080/15332861.2019.1668658
   Web of Science ®Google Scholar
• Khalifa, M., & Liu, V. (2007). Online consumer retention: Contingent effects of online shopping habit and online shopping experience. European Journal of Information Systems, 16(6), 780–792. https://doi.org/10.1057/palgrave.ejis.3000711
   Web of Science ®Google Scholar
• Kim, C., Galliers, R. D., Shin, N., Ryoo, J. H., & Kim, J. (2012). Factors influencing Internet shopping value and customer repurchase intention. Electronic Commerce Research and Applications, 11(4), 374–387. https://doi.org/10.1016/j.elerap.2012.04.002
   Web of Science ®Google Scholar
• Koronaki, E., Vlachvei, A., & Panopoulos, A. (2023). Managing the online customer experience and subsequent consumer responses across the customer journey: A review and future research agenda. Electronic Commerce Research and Applications, 58, 101242. https://doi.org/10.1016/j.elerap.2023.101242
   Web of Science ®Google Scholar
• Larche, C. J., & Dixon, M. J. (2021). Winning isn’t everything: The impact of optimally challenging smartphone games on flow, game preference and individuals gaming to escape aversive bored states. Computers in Human Behavior, 123, 106857. https://doi.org/10.1016/j.chb.2021.106857
   Web of Science ®Google Scholar
• Mahfouz, A. Y., Joonas, K., & Opara, E. U. (2020). An overview of and factor analytic approach to flow theory in online contexts. Technology in Society, 61, 101228. https://doi.org/10.1016/j.techsoc.2020.101228
   Web of Science ®Google Scholar
• Mauri, M., Cipresso, P., Balgera, A., Villamira, M., & Riva, G. (2011). Why is Facebook so successful? Psychophysiological measures describe a core flow state while using Facebook. Cyberpsychology, Behavior and Social Networking, 14(12), 723–731. https://doi.org/10.1089/cyber.2010.0377
   PubMed Web of Science ®Google Scholar
• Min, S., Zhou, M., Kim, D., & Kim, J. (2013). Assessing the e-service quality of sellers in an industrial e-marketplace. Journal of Promotion Management, 19(5), 556–582. https://doi.org/10.1080/10496491.2013.829156
   Google Scholar
• Nitzl, C., Roldan, J. L., & Cepeda, G. (2016). Mediation analysis in partial least squares path modeling: Helping researchers discuss more sophisticated models. Industrial Management & Data Systems, 116(9), 1849–1864. https://doi.org/10.1108/IMDS-07-2015-0302
   Web of Science ®Google Scholar
• Novak, T. P., Hoffman, D. L., & Yung, Y.-F. (2000). Measuring the customer experience in online environments: A structural modeling approach. Marketing Science, 19(1), 22–42. https://doi.org/10.1287/mksc.19.1.22.15184
   Web of Science ®Google Scholar
• Rasool, A., Shah, F. A., & Ul Islam, J. (2020). Customer engagement in the digital age: A review and research agenda. Current Opinion in Psychology, 36, 96–100. https://doi.org/10.1016/j.copsyc.2020.05.003
   PubMed Web of Science ®Google Scholar
• Rezaei, S. (2018). Dragging market mavens to promote apps repatronage intention: The forgotten market segment. Journal of Promotion Management, 24(4), 511–532. https://doi.org/10.1080/10496491.2017.1380106
   Google Scholar
• Rose, S., Clark, M., Samouel, P., & Hair, N. (2012). Online customer experience in e-retailing: An empirical model of antecedents and outcomes. Journal of Retailing, 88(2), 308–322. https://doi.org/10.1016/j.jretai.2012.03.001
   Web of Science ®Google Scholar
• Roy, S. K., Lassar, W. M., & Shekhar, V. (2016). Convenience and satisfaction: Mediation of fairness and quality. The Service Industries Journal, 36(5–6), 239–260. https://doi.org/10.1080/02642069.2016.1186657
   Web of Science ®Google Scholar
• Saha, S. K., Duarte, P., Silva, S. C., & Zhuang, G. (2023). The role of online experience in the relationship between service convenience and future purchase intentions. Journal of Internet Commerce, 22(2), 244–271. https://doi.org/10.1080/15332861.2022.2045767
   Web of Science ®Google Scholar
• Somosi, A., Stiassny, A., Kolos, K., & Warlop, L. (2021). Customer defection due to service elimination and post-elimination customer behavior: An empirical investigation in telecommunications. International Journal of Research in Marketing, 38(4), 915–934. https://doi.org/10.1016/j.ijresmar.2021.03.003
   Web of Science ®Google Scholar
• Statista. (2023a). E-commerce worldwide – statistics & facts. Retrieved October 14, 2023, from https://www.statista.com/topics/871/online-shopping/#topicOverview.
   Google Scholar
• Statista (2023b). Books: Market data and analysis. Market insight reports. Retrieved October 19, 2023, from https://www.statista.com/study/134751/media-report-books/.
   Google Scholar
• Tubisad. (2022). Türkiye’de E-Ticaret 2022 Pazar Büyüklüğü: 16. Tubisad. Retrieved March 20, 2023, from https://www.tubisad.org.tr/tr/images/pdf/dde-2022-raporu-final.pdf
   Google Scholar
• TurkStat (2019). Household budget statistics micro data set. Retrieved March 20, 2023, from www.tuik.gov.tr.
   Google Scholar