Influence of Venture Capital and Knowledge Transfer on Innovation Performance in the Big Data Environment

Chuanrong Wu, Xiaoming Yang, Veronika Lee and Mark E. McMurtrey
Additional contact information
Chuanrong Wu: School of Economy and Management, Changsha University of Science & Technology, Changsha 410114, China
Xiaoming Yang: College of Business Administration, University of Nebraska at Omaha, Omaha, NE 68182, USA
Veronika Lee: School of Economy and Management, Changsha University of Science & Technology, Changsha 410114, China
Mark E. McMurtrey: College of Business, University of Central Arkansas, Conway, AR 72035, USA

JRFM, 2019, vol. 12, issue 4, 1-13

Abstract: Technological innovation requires large investments. Venture capital (VC) is a prominent financial source for innovative start-ups. A venture capitalist will inevitably transfer knowledge to facilitate the innovation of a firm while monitoring and advising its portfolio companies. Only when a firm has its own valuable new knowledge and high growth potential would venture capitalists select it. At the same time, big data knowledge, such as customer demands and user preferences, is also important for the new product development of a firm in the big data environment. Therefore, private knowledge transferred from venture capitalists, new knowledge developed independently by a firm itself, and big data knowledge are the three main types of knowledge for venture-backed firms in the big data environment. To find the influences of VC and knowledge transfer on the innovative performance of venture-backed firms, a model of maximizing the present value of the expected profit of new product innovation performance of a venture-backed firm in the big data environment is presented. The model can help venture capitalists to determine the scale of investment and the optimal exit time and predict the internal rate of return (IRR). This model can also help innovative start-ups to illustrate the value and prospects of a project to attract investment in their business prospectus.

Keywords: venture capital; big data; knowledge transfer; venture capitalist; innovation performance (search for similar items in EconPapers)
JEL-codes: C E F2 F3 G (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://www.mdpi.com/1911-8074/12/4/188/pdf (application/pdf)
https://www.mdpi.com/1911-8074/12/4/188/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jjrfmx:v:12:y:2019:i:4:p:188-:d:297271

Access Statistics for this article

JRFM is currently edited by Ms. Chelthy Cheng

More articles in JRFM from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().