Firm performance and information security technology intellectual property

Martin Kang, Andrew Miller, Kyungmyung Jang and Horim Kim

Technological Forecasting and Social Change, 2022, vol. 181, issue C

Abstract: The appropriate valuation of information security (InfoSec) intellectual property (IP) is of interest to both business scholars and investors. This topic is important because InfoSec IP is a complementary knowledge resource that can complement a firm's existing and new products, services, business models, and operations. This paper attempts to understand the marginal effects of having additional InfoSec IP on a firm's performance in terms of return on investment and market capitalization. We collected objective InfoSec IP data from the United States Patent Office, the United States Copyright Office, and Compustat. Specifically, our data includes various types of IP, including patents, copyrights, and patent portfolios. We exclude IT-security firms in this study because we are interested in the effect of InfoSec IP on non-IT security firms. We include panel regression models using fixed effects that test the interplays between the various types of InfoSec IP and a firm's performance. In addition, we conduct generalized moment method and Heckman correction model analyses to alleviate potential endogeneity and sampling biases. Our results suggest that InfoSec IP is positively related to both return on investment and market capitalization. Further, we find that diverse InfoSec IP portfolios strengthen the effects of a firm's InfoSec patents and copyrights on market capitalization.

Keywords: Information security; Intellectual property; Copyrights; Patents; Research & development; Firm Performance; Market Capitalization; ROI; GMM; Heckman Correction Model (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:tefoso:v:181:y:2022:i:c:s004016252200261x

DOI: 10.1016/j.techfore.2022.121735

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