Open Access. Powered by Scholars. Published by Universities.®
- Discipline
-
- Business (1)
- Computer Law (1)
- Computer Sciences (1)
- Corporate Finance (1)
- Data Storage Systems (1)
-
- Digital Communications and Networking (1)
- Electronic Devices and Semiconductor Manufacturing (1)
- Forensic Science and Technology (1)
- Hardware Systems (1)
- Information Security (1)
- Law (1)
- Legal Studies (1)
- Other Computer Engineering (1)
- Physical Sciences and Mathematics (1)
- Social and Behavioral Sciences (1)
Articles 1 - 2 of 2
Full-Text Articles in Computer Engineering
Cyber Black Box/Event Data Recorder: Legal And Ethical Perspectives And Challenges With Digital Forensics, Michael Losavio, Pavel Pastukov, Svetlana Polyakova
Cyber Black Box/Event Data Recorder: Legal And Ethical Perspectives And Challenges With Digital Forensics, Michael Losavio, Pavel Pastukov, Svetlana Polyakova
Journal of Digital Forensics, Security and Law
With ubiquitous computing and the growth of the Internet of Things, there is vast expansion in the deployment and use of event data recording systems in a variety of environments. From the ships’ logs of antiquity through the evolution of personal devices for recording personal and environmental activities, these devices offer rich forensic and evidentiary opportunities that smash against rights of privacy and personality. The technical configurations of these devices provide for greater scope of sensing, interconnection options for local, near, and cloud storage of data, and the possibility of powerful analytics. This creates the unique situation of near-total data …
Is Tech M&A Value-Additive?, Ani Deshmukh
Is Tech M&A Value-Additive?, Ani Deshmukh
Undergraduate Economic Review
Given rising M&A deal volume across all high-tech subsectors, the ability to measure post-acquisition performance becomes critical. Despite this growth, the relevant academic literature is severely lacking (Kohers and Kohers 2000). Using an event-study approach, I find that acquirers and targets both realize statistically significant day-0 abnormal returns (1.23% [p<0.1] and 8.1% [p<0.01], respectively). As positive stock returns signal positive growth prospects in a semi-strong efficient market, AR regressions found that firms' technological relatedness, deal financing, purchase price premiums, and the relative book to market ratio, explained most variance. Overall, high-tech transactions are value-additive for both targets and acquirers.