The Impact of Stock Compensation on the Financial Performance: From the Perspective of IT Listed Companies in China
2020 (English)Independent thesis Advanced level (degree of Master (One Year)), 10 credits / 15 HE credits
Student thesis
Abstract [en]
Stock compensation is an essential topic of corporate governance. It is a method for companies to use part of the company's stock to motivate corporate managers or key employees. Financial performance is the most common indicator of a company’s operating conditions. Previous studies have drawn many opposite conclusions on the relationship between stock compensation and financial performance. It is because different countries, industries and enterprises have different reactions to stock compensation. The IT industry, as a technology and research-oriented sector, has a higher dependence on human resources than other sectors. So, for the emerging Chinese market, will the stock compensation plan affect the financial performance of IT listed companies?
The purpose of this study is to investigate whether there is a significant relationship between the stock compensation plan and the financial performance of IT listed companies in China and whether different elements of the stock compensation plan have different effects. This study takes 115 listed IT companies in China as research objects, the Pooled regression model, fixed effect regression model, and random effect regression model will be used as analysis models. Our conclusions show that the stock compensation plan has a significant role in promoting the financial performance of IT listed companies in China, and the impact of each essential element of the stock compensation plan varies.
IT listed companies in China can use these conclusions as a reference for stock compensation decisions. These findings also provide some new ideas for investors' investment decisions and risk avoidance.
Place, publisher, year, edition, pages
2020. , p. 77
Keywords [en]
Stock Compensation, Financial Performance, Employee Incentive, Principal–agent Problem, Panel Data, IT Industry
National Category
Business Administration
Identifiers
URN: urn:nbn:se:hj:diva-48715ISRN: JU-IHH-FÖA-2-20201119OAI: oai:DiVA.org:hj-48715DiVA, id: diva2:1434187
Subject / course
JIBS, Business Administration
Supervisors
Examiners
2020-06-242020-06-022020-06-24Bibliographically approved