Research on the Category Planning of Daily Necessities Merchants on Flash Sale Instant Retail Platforms

Xueqing Wang

doi:10.62051/ijgem.v7n2.01

Authors

Xueqing Wang

DOI:

https://doi.org/10.62051/ijgem.v7n2.01

Keywords:

Just-in-time retail, Daily necessities, Requirements life cycle, Category planning, Bass model

Abstract

Based on the background of instant consumption demand, this paper constructs a merchant category planning model of a flash sale instant retail platform. According to the development of the three stages of the emergence period, the accelerated growth period and the slow growth period, from the two aspects of the penetration of consumers' immediate demand and the degree of merchant participation, the category planning model of daily necessities in different stages of development of the instant retail market is constructed with the goal of maximizing the profit of daily necessities merchants, and the impact of the platform's subsidies to consumers, the platform's subsidies to merchants, and the commissions given by merchants to the platform on the development of daily necessities in the instant retail market are numerically analyzed. It has been inspired by the management that businesses should gradually broaden the application scenarios of daily necessities and meet the diversified needs of consumers.

Downloads

Download data is not yet available.

References

[1] Shichangbu.com. Demand Life Cycle Theory [EB/OL]. (2010-10-22) [2025-05-12]. Available at: https://www.shichangbu.com/know_info/103.html

[2] Cai Li. Research on the Diffusion Law of High Technology [J]. Science of Science and Management of S&T, 1994(8).

[3] Rogers E M. Diffusion of Innovations (5th ed.) [M]. New York: Free Press, 2003:11.

[4] Zhao Xiaoyu. Research on the Market Life Cycle of Autonomous Vehicle Products Based on Technology Diffusion Model [D]. Hunan University, 2014.

[5] Bass F M. A New Product Growth Model for Consumer Durables [J]. Management Science, 1969, 15(5):215-227.

[6] Kiesling E, Günther M, Stummer C, et al. Agent-based Simulation of Innovation Diffusion: A Review [J]. Central European Journal of Operations Research, 2012, 20(2):183-230.

[7] Yang Jinghui. Research on the Application of Bass Model and Its Two Extensions [D]. Dalian University of Technology, 2006.

[8] Massiani J, Gohs A. The Choice of Bass Model Coefficients to Forecast Diffusion for Innovative Products: An Empirical Investigation for New Automotive Technologies [J]. Research in Transportation Economics, 2015, 50:17-28.

[9] Guan Jiancheng, Zhang Xiwu. The Impact of Government Intermediaries and Subsidy Policies on the Diffusion Speed of Technological Innovation: A Study of Technology Policy [J]. Systems Engineering - Theory & Practice, 1995(8):6-12.

[10] Bottomley, P., & Fildes, R. The Role of Prices in Models of Innovation Diffusion [J]. Journal of Forecasting, 1998, 17:539-555.

[11] Tian Yihui. Research on Diffusion Model of Green Supply Chain Management [D]. Dalian University of Technology, 2014.

[12] Wang Li. Research on the Diffusion of Internet Information Disruptive Innovative Products [D]. Harbin Institute of Technology, 2022.