Research on Performance Commitment Agreement of Continuous M&A of Advertising Media Enterprises in China

A Case Study of Continuous M&A of Lianjian Optoelectronics

DOI

10.2991/aebmr.k.210803.033How to use a DOI?

Keywords

Advertising media, M&A, Performance Commitment agreement, Lianjian optoelectronics

Abstract

Due to the rapid development of advertising media industry, traditional media enterprises have to adopt M&A (mergers and acquisitions) to keep up with the speed of industry development. However, M&A, especially in a short period of time, is often accompanied by uncertain risks such as information asymmetry and difficult to predict future profits. Therefore, in order to avoid uncertainty risk, performance commitment agreement began to be widely used in media mergers and acquisitions. This paper takes the application case of Lianjian Optoelectronics to performance commitment agreement in continuous M&A, starting with short-term and short-term performance analysis, performance commitment standard and original country. The purpose of this paper is to study the long-term and short-term impact of M&A application performance commitment agreement on company performance. The case study found that different performance compensation methods will have different effects on M&A risk, and the performance commitment agreement will greatly improve the long-term operating risk of the company.

Copyright

© 2021, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Liangchen Zhang
AU  - Yu Wu
AU  - Chao Chen
PY  - 2021
DA  - 2021/08/04
TI  - Research on Performance Commitment Agreement of Continuous M&A of Advertising Media Enterprises in China
BT  - Proceedings of the  1st International Symposium on Innovative Management and Economics (ISIME 2021)
PB  - Atlantis Press
SP  - 237
EP  - 246
SN  - 2352-5428
UR  - https://doi.org/10.2991/aebmr.k.210803.033
DO  - 10.2991/aebmr.k.210803.033
ID  - Zhang2021
ER  -