| Title |
Survival of the Fittest: The Long-run Productivity Analysis of the Listed Information Technology Companies in the US Stock Market |
| ID_Doc |
76598 |
| Authors |
Qiao, GS |
| Title |
Survival of the Fittest: The Long-run Productivity Analysis of the Listed Information Technology Companies in the US Stock Market |
| Year |
2023 |
| Published |
Economics-The Open Access Open-Assessment E-Journal, 17, 1 |
| DOI |
10.1515/econ-2022-0035 |
| Abstract |
This article tries to estimate the operating efficiency among 30 years (1989-2018) in the information technology (IT) industry, where technologies are everchanging. The balanced panel data model of Kneip et al. is extended to an unbalanced panel data model for more generic applications. The estimation results based on listed IT firms in the US stock market provide evidence that the law of the jungle is applicable to the IT industry. The industry survivors, which often obtain and maintain market power through merger and acquisition, create economic moats by setting high barriers to entry to defend against risk and uncertainty and dominate the capital-intensive and technology-intensive IT industry. At the same time, the estimation results also demonstrate that the global IT industry is highly sensitive to technological waves and business cycles. Though thriving start-ups and spin-offs stimulate innovation and generate a richer diversity, economies of scale are still essential for sustainable development in the IT industry. |
| Author Keywords |
information technology industry; economies of scale; total factor productivity; factor model |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Social Science Citation Index (SSCI) |
| EID |
WOS:000922910100001 |
| WoS Category |
Economics |
| Research Area |
Business & Economics |
| PDF |
https://www.degruyter.com/document/doi/10.1515/econ-2022-0035/pdf
|