Advances in Economics, Management and Political Sciences
- The Open Access Proceedings Series for Conferences
Proceedings of the 3rd International Conference on Business and Policy Studies
Series Vol. 74 , 17 April 2024
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A Study of the Use of Mathematical Models in a Blind Box Economy
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Abstract
Since 2016, blind boxes have been loved by consumers, and the blind box economy has exploded. However, the blind box economy is closely linked with mathematical models. The mathematical models could be research predictions of profit and loss in blind boxes. Such functions as the loss function can assess the purchase probability of the blind box as well as how to avoid massive losses. Neural networks and Linear regression can predict the price changes of the blind box. Besides, we can predict and analyze the psychological and behavioral motivations of consumers. Therefore, the passage through literature reading and specific data analysis methods focuses on the mathematical models such as Loss function , Neural network and Linear regression that are applied in the blind box now. And the passage also describes the predictional model of profit and loss controdiction to avoid consumers consuming excessively ‘a pig in a poke’. At present, Linear regression can analysis and calculate investment with the blind box, but it should consider a lot of factors that can cause errors. Neural network can predict price changes, and it needs a large amount of data to support the model. Loss function can be used to predict the profit and loss of a blind box, but it also needs a large amount of data to prove its accuracy.
Keywords
Neural network, Loss function, Linear regression, blind box economy, behavioral motivation
References
1. Liu, F., Lyu, L., & Yang, K. (2021, December). Analysis of Success Factors and Developing Potential of Pop Mart. In 2021 3rd International Conference on Economic Management and Cultural Industry (ICEMCI 2021) (pp. 2901-2906). Atlantis Press.
2. Sun, X., Jin, Y., & Huang, X. (2023). POP Mart: How to Maximize IP Value in the Field of Art Toy?. In Innovation of Digital Economy: Cases from China (pp. 223-236). Singapore: Springer Nature Singapore.
3. Liu, S. W., Huang, W., Rao, H., & Fu, Y. K. (2023). Ternary economic analysis of blind-box marketing. Economic Research-Ekonomska Istraživanja, 36(3), 2183517.
4. Cohen, J., Cohen, P., West, S. G., & Aiken, L. S. (2013). Applied multiple regression/correlation analysis for the behavioral sciences. Routledge.
5. Hazewinkel, M. (Ed.). (2013). Encyclopaedia of mathematics: A-integral—coordinates (Vol. 1). Springer.
6. Zhang, L., & Phakdeephirot, N. (2023). The Influence of Blind Box Marketing on Consumers' Purchase Intention:--Taking" POPMART" as an Example. Highlights in Art and Design, 4(2), 154-160.
Data Availability
The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.
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- Volume Title
- Proceedings of the 3rd International Conference on Business and Policy Studies
- ISBN (Print)
- 978-1-83558-371-5
- ISBN (Online)
- 978-1-83558-372-2
- Published Date
- 17 April 2024
- Series
- Advances in Economics, Management and Political Sciences
- ISSN (Print)
- 2754-1169
- ISSN (Online)
- 2754-1177
- DOI
- 10.54254/2754-1169/74/20241460
- Copyright
- 17 April 2024
- Open Access
- This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited