Exploration into the Development Status and Popularization Reasons of Online Live Streaming of Niche Content: Blind Box Live Streaming as an Example

Zheyi Huang

doi:10.54097/dx4a2b62

Authors

Zheyi Huang

DOI:

https://doi.org/10.54097/dx4a2b62

Keywords:

Blind fast-moving products, live streaming shopping, random products, low unit price products, incendiary consumption.

Abstract

With the development of the internet, the retail industry has undergone earth shaking changes. Various new retail methods have emerged, as well as new best-selling products. Since 2022, blind box live streaming in the gaming industry has been thriving and gaining popularity among young people. This study aims to analyse the key factors for the success of the gaming blind box live streaming industry, with a focus on exploring how fast-moving consumer goods can achieve commercial success through live interaction, fun games, and utilizing consumer mentality. Firstly, the sales form of live streaming interaction enhances the connection between consumers and hosts, promotes consumer stickiness, and further forms a fan economy. In addition, blind box products take advantage of young people's pursuit of excitement and unknown psychology, further promoting consumption. Ultimately, this study suggests that the success of the gaming blind box live streaming industry depends not only on the popularity of social media, but also on its control and utilization of consumer psychology.

Downloads

Download data is not yet available.

References

[1] Nijssen, Edwin J. “Success Factors of Line Extensions of Fast‐Moving Consumer Goods.” European Journal of Marketing, vol. 33, no. 5/6, June 1999, pp. 450 – 74, https: //doi.org/10.1108/03090569910262044.

[2] Liu Pingsheng and Shi Yongdong “The impact mechanism of live streaming sales marketing model on consumer purchasing decisions.” China Circulation Economy 34.10 (2020): 10 Amjady N. Short-term hourly load forecasting using time series modeling with peak load estimation capability. IEEE Transactions on Power Systems, 2001, 16 (4): 798 - 805.

[3] Apasrawirote, Darlin, and Kritcha Yawised. “Factors Influencing the Behavioral and Purchase Intention on Live-Streaming Shopping.” Asian Journal of Business Research, vol. 12, no. 1, Apr. 2022, https: //doi.org/10.14707/ajbr.220119. Accessed 11 June 2022.SHI Biao, LI Yu Xia, YU Xhua, YAN Wang. Short-term load forecasting based on modified particle swarm optimizer and fuzzy neural network model. Systems Engineering-Theory and Practice, 2010, 30 (1): 158 - 160.

[4] Yan Xiuxia and others “Research on the Impact of Live Streaming Sales on Consumer Purchasing Behavior: Mediated by Perceived Value.” Price Theory and Practice 6 (2021): 137-140Amjady N. Short-term hourly load forecasting using time series modeling with peak load estimation capability. IEEE Transactions on Power Systems, 2001, 16 (4): 798 - 805.

[5] No15 UNCTAD Technical Notes on ICT for Development No18 ESTIMATES of GLOBAL E-COMMERCE 2019 and PRELIMINARY ASSESSMENT of COVID-19 IMPACT on ONLINE RETAIL 2020. unctad.org/system/files/official-document/tn_unctad_ict4d18_en.pdf.Ma Kunlong. Short term distributed load forecasting method based on big data. Changsha: Hunan University, 2014.

[6] Xu Ying and Guo Wenjun “The Dual Perspective of Uncertainty - A Discussion Based on Blind Box Sales.” Management Science 36.1 (2023): 119 - 131.

[7] Zhang, Ziwei. “Research on Blind Box and Its Marketing Strategy.” Proceedings of the 2021 International Conference on Economic Development and Business Culture (ICEDBC 2021), vol. 182, no. 2352 - 5428, 2021, https: //doi.org/10.2991/aebmr.k.210712.020.Fangfang. Research on power load forecasting based on Improved BP neural network. Harbin Institute of Technology, 2011.

[8] “Determinants of Consumer Purchase Decision Making for Fast Moving Consumer Goods.” Research on Humanities and Social Sciences, June 2019, https: //doi.org/10.7176/rhss/9 - 11 - 02.