Skip to main content

Advertisement

Log in

Supervising or assisting? The influence of virtual anchor driven by AI–human collaboration on customer engagement in live streaming e-commerce

  • Published:
Electronic Commerce Research Aims and scope Submit manuscript

Abstract

Digital technologies such as artificial intelligence (AI) are driving the growth of live-streaming e-commerce. As a result, a rising number of virtual anchors who are appearing in live-streaming e-commerce, generating customer engagement. However, whether the virtual anchor driven by different types of AI–human collaboration has different impacts on consumer engagement needs to be further investigated. By adopting the use and gratifications theory, this paper investigated the mechanism of the virtual anchor driven by AI–human collaboration on consumer engagement and the moderating effect of the humorous response. The results of two studies demonstrated that the virtual anchor driven by assisted AI–human collaboration contributed to higher levels of perceived playfulness than those driven by supervised AI–human collaboration, leading to increased customer engagement. Meanwhile, it was found that the differences between the supervised and assisted virtual anchor driven by AI–human collaboration on perceived playfulness decrease when the humorous response is present. This paper fills in the gap in virtual anchor research by providing insights into how to enhance the positive effect of customer engagement and giving suggestions for future research on virtual anchors.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

References

  1. Yun, J., Lee, D., Cottingham, M., & Hyun, H. (2023). New generation commerce: The rise of live commerce (L-commerce). Journal of Retailing and Consumer Services, 74, 103394.

    Article  Google Scholar 

  2. Guo, Y., Zhang, K., & Wang, C. (2022). Way to success: Understanding top streamer’s popularity and influence from the perspective of source characteristics. Journal of Retailing and Consumer Services, 64, 102786.

    Article  Google Scholar 

  3. Gao, W., Jiang, N., & Guo, Q. (2023). How do virtual streamers affect purchase intention in the live streaming context? A presence perspective. Journal of Retailing and Consumer Services, 73, 103356.

    Article  Google Scholar 

  4. Blut, M., Wang, C., Wünderlich, N. V., & Brock, C. (2021). Understanding anthropomorphism in service provision: A meta-analysis of physical robots, chatbots, and other AI. Journal of the Academy of Marketing Science, 49(4), 632–658.

    Article  Google Scholar 

  5. Liao, J., Chen, K., Qi, J., Li, J., & Yu, I. Y. (2023). Creating immersive and parasocial live shopping experience for viewers: The role of streamers’ interactional communication style. Journal of Research in Interactive Marketing, 17(1), 140–155.

    Article  Google Scholar 

  6. Hou, F., Guan, Z., Li, B., & Chong, A. Y. L. (2020). Factors influencing people’s continuous watching intention and consumption intention in live streaming. Internet Research, 30(1), 141–163.

    Article  Google Scholar 

  7. Niu, B., Yu, X., & Dong, J. (2023). Could AI livestream perform better than KOL in cross-border operations? Transportation Research Part E: Logistics and Transportation Review, 174, 103130.

    Article  Google Scholar 

  8. Xiao, L., & Kumar, V. (2019). Robotics for customer service: A useful complement or an ultimate substitute? Journal of Service Research, 24(1), 9–29.

    Article  Google Scholar 

  9. Dwivedi, Y. K., Hughes, L., Ismagilova, E., Aarts, G., Coombs, C., Crick, T., Duan, Y., Dwivedi, R., Edwards, J., & Eirug, A. (2021). Artificial Intelligence (AI): Multidisciplinary perspectives on emerging challenges, opportunities, and agenda for research, practice and policy. International Journal of Information Management, 57, 101994.

    Article  Google Scholar 

  10. Gervasi, R., Mastrogiacomo, L., & Franceschini, F. (2020). A conceptual framework to evaluate human–robot collaboration. The International Journal of Advanced Manufacturing Technology, 108(3), 841–865.

    Article  Google Scholar 

  11. Peng, C., van Doorn, J., Eggers, F., & Wieringa, J. E. (2022). The effect of required warmth on consumer acceptance of artificial intelligence in service: The moderating role of AI–human collaboration. International Journal of Information Management, 66, 102533.

    Article  Google Scholar 

  12. Luo, X., Qin, M. S., Fang, Z., & Qu, Z. (2020). Artificial intelligence coaches for sales agents: Caveats and solutions. Journal of Marketing, 85(2), 14–32.

    Article  Google Scholar 

  13. McLeay, F., Osburg, V. S., Yoganathan, V., & Patterson, A. (2020). Replaced by a robot: Service implications in the age of the machine. Journal of Service Research, 24(1), 104–121.

    Article  Google Scholar 

  14. Longoni, C., & Cian, L. (2020). Artificial intelligence in utilitarian vs. hedonic contexts: The “word-of-machine” effect. Journal of Marketing, 86(1), 91–108.

    Article  Google Scholar 

  15. Bansal, P., & Kockelman, K. M. (2018). Are we ready to embrace connected and self-driving vehicles? A case study of Texans. Transportation, 45, 641–675.

    Article  Google Scholar 

  16. Hossain, M. A., Kim, M., & Jahan, N. (2019). Can “liking” behavior lead to usage intention on Facebook? Uses and gratification theory perspective. Sustainability, 11(4), 1166.

    Article  Google Scholar 

  17. Jiang, Q., Gu, C., Feng, Y., Wei, W., & Tsai, W.-C. (2022). Study on the continuance intention in using virtual shoe-try-on function in mobile online shopping. Kybernetes, ahead-of-print.

  18. Kim, M., & Kim, H.-M. (2022). What online game spectators want from their twitch streamers: Flow and well-being perspectives. Journal of Retailing and Consumer Services, 66, 102951.

    Article  Google Scholar 

  19. Luo, H., Cheng, S., Zhou, W., Yu, S., & Lin, X. (2021). A study on the impact of linguistic persuasive styles on the sales volume of live streaming products in social E-Commerce environment. Mathematics, 9(13), 1576.

    Article  Google Scholar 

  20. Kaur, P., Dhir, A., Chen, S., Malibari, A., & Almotairi, M. (2020). Why do people purchase virtual goods? A uses and gratification (U&G) theory perspective. Telematics and Informatics, 53, 101376.

    Article  Google Scholar 

  21. Roux, T. (2020). Users’ experience of digital wayfinding screens: A uses and gratification perspective from South Africa. Advances in Human–Computer Interaction, 1, 1–11.

    Article  Google Scholar 

  22. Kujur, F., & Singh, S. (2020). Visual communication and consumer-brand relationship on social networking sites-uses & gratifications theory perspective. Journal of theoretical and applied electronic commerce research, 15(1), 30–47.

    Article  Google Scholar 

  23. Alhassan, M. D., Kolog, E. A., & Boateng, R. (2020). Effect of gratification on user attitude and continuance use of mobile payment services: A developing country context. Journal of Systems and Information Technology., 22(4), 351–378.

    Article  Google Scholar 

  24. Rese, A., Ganster, L., & Baier, D. (2020). Chatbots in retailers’ customer communication: How to measure their acceptance? Journal of Retailing and Consumer Services, 56, 102176.

    Article  Google Scholar 

  25. Murphy, J., Gretzel, U., & Pesonen, J. (2019). Marketing robot services in hospitality and tourism: The role of anthropomorphism. Journal of Travel & Tourism Marketing, 36(7), 784–795.

    Article  Google Scholar 

  26. Sheehan, B., Jin, H. S., & Gottlieb, U. (2020). Customer service chatbots: Anthropomorphism and adoption. Journal of Business Research, 115, 14–24.

    Article  Google Scholar 

  27. Siemon, D. (2022). Elaborating team roles for artificial intelligence-based teammates in human–AI collaboration. Group Decision and Negotiation, 31(5), 871–912.

    Article  Google Scholar 

  28. Vössing, M., Kühl, N., Lind, M., & Satzger, G. (2022). Designing transparency for effective human–AI collaboration. Information Systems Frontiers, 24(2), 1–19.

    Google Scholar 

  29. Jessup, S., Gibson, A., Capiola, A., Alarcon, G., & Borders, M. (2020). Investigating the effect of trust manipulations on affect over time in human–human versus human–robot interactions. In Hawaii international conference on system sciences (pp. 1–10).

  30. Tsai, C.-Y., Marshall, J. D., Choudhury, A., Serban, A., Tsung-Yu Hou, Y., Jung, M. F., Dionne, S. D., & Yammarino, F. J. (2022). Human–robot collaboration: A multilevel and integrated leadership framework. The Leadership Quarterly, 33(1), 101594.

    Article  Google Scholar 

  31. Koschmann, A., & Bowman, D. (2018). Evaluating marketplace synergies of ingredient brand alliances. International Journal of Research in Marketing, 35(4), 575–590.

    Article  Google Scholar 

  32. Pan, R., Feng, J., & Zhao, Z. (2022). Fly with the wings of live-stream selling: Channel strategies with/without switching demand. Production and Operations Management, 31(9), 3387–3399.

    Article  Google Scholar 

  33. Liu, C., Sun, K., & Liu, L. (2023). The formation and transformation mechanisms of deep consumer engagement and purchase behavior in E-Commerce live streaming. Sustainability, 15(7), 5754.

    Article  Google Scholar 

  34. Guo, L., Hu, X., Lu, J., & Ma, L. (2021). Effects of customer trust on engagement in live streaming commerce: Mediating role of swift guanxi. Internet Research, 31(5), 1718–1744.

    Article  Google Scholar 

  35. Gu, Y., Cheng, X., & Shen, J. (2023). Design shopping as an experience: Exploring the effect of the live-streaming shopping characteristics on consumers’ participation intention and memorable experience. Information & Management, 60, 103810.

    Article  Google Scholar 

  36. Ye, C., Zheng, R., & Li, L. (2022). The effect of visual and interactive features of tourism live streaming on tourism consumers’ willingness to participate. Asia Pacific Journal of Tourism Research, 27, 506–525.

    Article  Google Scholar 

  37. Chen, T., Tang, S., Shao, Z., He, J., Zhang, X., & Zhu, P. (2023). Doing well by doing good: The effect of purchasing poverty-alleviation products on consumers’ subsequent product preference in live streaming shopping. Computers in Human Behavior, 144, 107753.

    Article  Google Scholar 

  38. Wang, B., Xie, F., Kandampully, J., & Wang, J. (2022). Increase hedonic products purchase intention through livestreaming: The mediating effects of mental imagery quality and customer trust. Journal of Retailing and Consumer Services, 69, 103109.

    Article  Google Scholar 

  39. Zhou, Y., & Huang, W. (2023). The influence of network anchor traits on shopping intentions in a live streaming marketing context: The mediating role of value perception and the moderating role of consumer involvement. Economic Analysis and Policy, 78, 332–342.

    Article  Google Scholar 

  40. He, Y., Li, W., & Xue, J. (2022). What and how driving consumer engagement and purchase intention in officer live streaming? A two-factor theory perspective. Electronic Commerce Research and Applications, 56, 101223.

    Article  Google Scholar 

  41. Manser Payne, E. H., Dahl, A. J., & Peltier, J. (2021). Digital servitization value co-creation framework for AI services: A research agenda for digital transformation in financial service ecosystems. Journal of Research in Interactive Marketing, 15(2), 200–222.

    Article  Google Scholar 

  42. Nagel, D. M., Giunipero, L., Jung, H., Salas, J., & Hochstein, B. (2021). Purchaser perceptions of early phase supplier relationships: The role of similarity and likeability. Journal of Business Research, 128, 174–186.

    Article  Google Scholar 

  43. Zhang, M., Sun, L., Qin, F., & Wang, G. A. (2021). E-service quality on live streaming platforms: Swift guanxi perspective. Journal of Services Marketing, 35(3), 312–324.

    Article  Google Scholar 

  44. Longoni, C., Bonezzi, A., & Morewedge, C. K. (2019). Resistance to medical artificial intelligence. Journal of Consumer Research, 46(4), 629–650.

    Article  Google Scholar 

  45. Lv, J., Cao, C., Xu, Q., Ni, L., Shao, X., & Shi, Y. (2022). How live streaming interactions and their visual stimuli affect users’ sustained engagement behaviour: A comparative experiment using live and virtual live streaming. Sustainability, 14(14), 8907.

    Article  Google Scholar 

  46. Wu, Y., Jiang, Q., Ni, S., & Liang, H. (2021). Critical factors for predicting users’ acceptance of digital museums for experience-influenced environments. Information, 12(10), 426.

    Article  Google Scholar 

  47. Aw, E.C.-X., Tan, G.W.-H., Cham, T.-H., Raman, R., & Ooi, K.-B. (2022). Alexa, what’s on my shopping list? Transforming customer experience with digital voice assistants. Technological Forecasting and Social Change, 180, 121711.

    Article  Google Scholar 

  48. Chung, M., Ko, E., Joung, H., & Kim, S. J. (2020). Chatbot e-service and customer satisfaction regarding luxury brands. Journal of Business Research, 117, 587–595.

    Article  Google Scholar 

  49. Tan, T. M., Makkonen, H., Kaur, P., & Salo, J. (2022). How do ethical consumers utilize sharing economy platforms as part of their sustainable resale behavior? The role of consumers’ green consumption values. Technological Forecasting and Social Change, 176, 121432.

    Article  Google Scholar 

  50. Xiao, L., Li, X., & Zhang, Y. (2023). Exploring the factors influencing consumer engagement behavior regarding short-form video advertising: A big data perspective. Journal of Retailing and Consumer Services, 70, 103170.

    Article  Google Scholar 

  51. Zhang, M., Gursoy, D., Zhu, Z., & Shi, S. (2021). Impact of anthropomorphic features of artificially intelligent service robots on consumer acceptance: Moderating role of sense of humor. International Journal of Contemporary Hospitality Management, 33(11), 3883–3905.

    Article  Google Scholar 

  52. De Cicco, R., Silva, S. C. L., & Alparone, F. R. (2021). “It’s on its way”: Chatbots applied for online food delivery services, social or task-oriented interaction style? Journal of Foodservice Business Research, 24(2), 140–164.

    Article  Google Scholar 

  53. Shin, H., & Larson, L. R. (2020). The bright and dark sides of humorous response to online customer complaint. European Journal of Marketing, 54(8), 2013–2047.

    Article  Google Scholar 

  54. Vitezić, V., & Perić, M. (2021). Artificial intelligence acceptance in services: Connecting with Generation Z. The Service Industries Journal, 41(13–14), 926–946.

    Article  Google Scholar 

  55. Liu, J. (2022). Artificial intelligence humor in service recovery. Annals of Tourism Research, 95, 103439.

    Article  Google Scholar 

  56. Lv, X., Yang, Y., Qin, D., Cao, X., & Xu, H. (2022). Artificial intelligence service recovery: The role of empathic response in hospitality customers’ continuous usage intention. Computers in Human Behavior, 126, 106993.

    Article  Google Scholar 

  57. Go, E., & Sundar, S. S. (2019). Humanizing chatbots: The effects of visual, identity and conversational cues on humanness perceptions. Computers in Human Behavior, 97, 304–316.

    Article  Google Scholar 

  58. Oliveira, R., Arriaga, P., Axelsson, M., & Paiva, A. (2021). Humor–Robot interaction: A scoping review of the literature and future directions. International Journal of Social Robotics, 13(6), 1369–1383.

    Article  Google Scholar 

  59. Tan, S.-M., & Liew, T. W. (2020). Designing embodied virtual agents as product specialists in a multi-product category E-commerce: The roles of source credibility and social presence. International Journal of Human–Computer Interaction, 36(12), 1136–1149.

    Article  Google Scholar 

  60. Dhar, R., & Wertenbroch, K. (2000). Consumer choice between hedonic and utilitarian goods. Journal of Marketing Research, 37, 60–71.

    Article  Google Scholar 

  61. Bytedance, (2022, June 24). Report on Big Data analysis and trend research of China's live streaming e-commerce industry in 2022–2023. OR Commons. Retrieved July 29, 2023, from https://www.iimedia.cn/c400/86233.html

  62. Economist, (2021, June 5). Comparison of companies in China's live e-commerce industry in 2021. OR Commons. Retrieved July 29, 2023, from https://www.qianzhan.com/analyst/detail/220/210604-c60f5dda.html

  63. McShane, L., Pancer, E., Poole, M., & Deng, Q. (2021). Emoji, playfulness, and brand engagement on twitter. Journal of Interactive Marketing, 53, 96–110.

    Article  Google Scholar 

  64. Kull, A. J., Romero, M., & Monahan, L. (2021). How may I help you? Driving brand engagement through the warmth of an initial chatbot message. Journal of Business Research, 135, 840–850.

    Article  Google Scholar 

  65. Li, X., Guo, M., & Huang, D. (2023). The role of scarcity promotion and cause-related events in impulse purchase in the agricultural product live stream. Scientific Reports, 13(1), 3800.

    Article  Google Scholar 

  66. Hayes, A. F. (2015). An index and test of linear moderated mediation. Multivariate Behavioral Research, 50(1), 1–22.

    Article  Google Scholar 

  67. Kim, S., Jang, S., Choi, W., Youn, C., & Lee, Y. (2022). Contactless service encounters among Millennials and Generation Z: The effects of millennials and Gen Z characteristics on technology self-efficacy and preference for contactless service. Journal of Research in Interactive Marketing, 16(1), 82–100.

    Article  Google Scholar 

Download references

Funding

Funding was provided by Social Science Foundation of China (Grant No. 21BGL057).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to XueYing Wang.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Appendices

Appendix 1

1.1 Manipulation of virtual anchors driven by AI–human collaboration in Study 1

See Figs.

Fig. 4
figure 4

Virtual anchor driven by supervised AI–human collaboration

4 and

Fig. 5
figure 5

Virtual anchor driven by assisted AI–human collaboration

5.

Appendix 2

2.1 Manipulation of virtual anchors driven by AI–human collaboration in Study 2

See Figs.

Fig. 6
figure 6

Virtual anchor driven by supervised AI–human collaboration

6 and

Fig. 7
figure 7

Virtual anchor driven by assisted AI–human collaboration

7.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Zhang, Y., Wang, X. & Zhao, X. Supervising or assisting? The influence of virtual anchor driven by AI–human collaboration on customer engagement in live streaming e-commerce. Electron Commer Res (2023). https://doi.org/10.1007/s10660-023-09783-5

Download citation

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s10660-023-09783-5

Keywords

Navigation