Investment Analysis on the Autonomous Vehicle Technology Company Under Covid-19 Pandemic
A Case Study on Pony.ai Company
Kaicheng Jiang1, †, Wanying Huang2, †, Yunran Liu3, †, Xinyi Wei4, *, †
1Kang Chiao International School, Suzhou City, Jiangsu Province, China
2School of Earth and Environment, University of Leeds, Leeds, LS2 9JT, United Kingdom
4Department of Business and Management Studies, Lancaster University Management School, Lancaster University, Lancaster, LA1 4YW, United Kingdom
3School of Social Sciences, University of Manchester, Manchester, M13 9PL, United Kingdom
These authors contributed equally.
*Corresponding author. Email: firstname.lastname@example.org
Available Online 15 December 2021.
- 10.2991/assehr.k.211209.120How to use a DOI?
- PEST analysis; POCD framework; Automated vehicle; Covid-19 pandemic
This paper studies the investment prospect of the autonomous vehicle technology company using the case of Pony.ai company. We apply the Political-Economic-Social-Technological (PEST) analysis to analyze the macroenvironment and the People-Context-Deal-Opportunity (PCDO) framework to evaluate the investment prospects of Pony.ai. We find that the autonomous vehicle industry has great prospects of development under the Covid-19 pandemic, and Pony.ai is a startup with great potential. Thus, Pony.ai is worthy of being invested by venture capital investors. Furthermore, our research enriches the PEST analysis and POCD framework application in investment analysis under the Covid-19 pandemic.
- © 2021 The Authors. Published by Atlantis Press International B.V.
- Open Access
- This is an open access article under the CC BY-NC license.
Cite this article
TY - CONF AU - Kaicheng Jiang AU - Wanying Huang AU - Yunran Liu AU - Xinyi Wei PY - 2021 DA - 2021/12/15 TI - Investment Analysis on the Autonomous Vehicle Technology Company Under Covid-19 Pandemic BT - Proceedings of the 2021 3rd International Conference on Economic Management and Cultural Industry (ICEMCI 2021) PB - Atlantis Press SP - 724 EP - 732 SN - 2352-5428 UR - https://doi.org/10.2991/assehr.k.211209.120 DO - 10.2991/assehr.k.211209.120 ID - Jiang2021 ER -