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A Study on Group Buying of O2O Mode using Generalized Stochastic Petri Nets

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영어

This paper proposes a Group Buying model (paid in advance) of online-to-offline mode using Generalized Stochastic Petri Nets. As the time cost of consumers is getting higher and higher, time efficiency is getting much more important in all aspects of life, especially in catering industry, and one way that can lead to direct communication between store owners and consumers is Group Buying of online-to-offline mode, the center of which is the brand building and service efficiency. Although researches based on both users’ and sellers’ perspective about online buying are very rich, these findings are not entirely applicable for this new e-commerce model, and most of current research on online-to-offline mode use qualitative methods. More importantly, few researchers have concerned about the efficiency of Group Buying process and come up with related solutions to improve it. By constructing a business model of GB and conducting time efficiency and performance analysis on it, we find that the key transitions of the system only take up less than half of the time before the whole process has been completed. And when we shorten the feedback process, the percentage of finishing consumption in physical store in the whole Group Buying model can be improved by 14.5%. Thus, we suggest that suppliers and sellers should be more focused and efficient in encouraging customers review timely as well as giving consumers feedback as soon as possible, since consumer comments are proved to be significantly important for the retailers. Besides, site operators and store sellers can also use other ways like WeChat and microblogging to promote their site linkages and gain more market share.

목차

Abstract
 1. Introduction
  1.1 Literature Review
  1.2 GSPN
  1.3 Using GSPN in GB Model
 2. Modeling and Calculation
  2.1 Constructing the Business Model
  2.2 Simplification and Calculation
  2.3 The Steady-state Probability
 3. Time Efficiency Analysis
  3.1 Subsystem
  3.2 Tokens in PN’
  3.3 Tokens in PN
  3.4 Average Execution Time
 4. Operational Performance Analysis
 5. Discussion
 6. Conclusion and Future Direction
 Acknowledgments
 References

저자정보

  • Fangfang Hou School of Information, Central University of Finance and Economics,Beijing, China
  • Shuyun Zhang School of Information, Central University of Finance and Economics,Beijing, China
  • Yue Wang School of Information, Central University of Finance and Economics,Beijing, China

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