ABSTRACT
The rapid digital transformations across every industry sector, accelerated partly due to the COVID-19 pandemic, have increased organizations’ use of information systems for operational and strategic purposes. These organizational responses have led to a confluence of digital, biological, and physical technologies that are revolutionizing business practices and workflows. But accompanying the pervasive use of digital technologies and the evolutionary nature of digital assets, is a shifting world of cyberattacks and information security (ISec) cybercrimes. Dynamic cybercrimes make it increasingly difficult for managers and researchers to anticipate the types, magnitude, and severity of future information security (ISec) breaches. Thus, we perform a systematic literature review (SLR) that explores, gathers, and categorizes event studies to examine the influence of favorable and unfavorable ISec events on stock markets. We extend the research conducted by Spanos and Angelis (2016) and provide a comprehensive understanding of the market's efficiency to process public information released about ISec events, ISec contingency factors, and the influence of ISec events on stock prices and factors other than price. Our systematic search reveals 58 relevant papers that include 80 studies. We find that in 75% of the studies ISec events can significantly affect a company's stock market performance, and that such effects are primarily exhibited within two days before and after the event day. Further, the magnitude of abnormal returns is higher in studies examining unfavorable ISec events, such as ISec breaches, compared to abnormal returns from favorable events, such as ISec investments and ISec certifications. In the end, our SLR serves as a foundation for ISec and management communities to build upon to keep industry and academia apprised of continually developing trends, new attack vectors and types of data breaches, protective ISec behaviors and programs, and their subsequent influences on stock market values and returns. © 2021 Elsevier Ltd
ABSTRACT
The year 2020 will be written in the history as the year that has caused catastrophic impact on health, human lives, and most importantly the economy that has been rumbled in some countries to the levels of World War I and II. This pandemic also exposed the loopholes in the systems for few 'Developed Nations', 'Established Public Health Systems', and 'Billion Dollar Forex Reserves' that most of the countries relied upon in general. All these were challenged to the core once the COVID-19 pandemic started growing exponentially from March 2020 forcing the countries to go under lockdown which has curved down their economic charts. Malaysia too has suffered with a months-long lockdown, growing unemployment and shrinking economy. The SMEs in Malaysia are among the worst affected. In May 2020, almost 50% of the SMEs reached a position where their very existence was at stake. A potential second or third wave of COVID-19 or some other pandemic in future is not any surprise for Malaysia. But, how far the country and its SMEs are prepared to face such situation again is the question. A quick and accurate data analytics on historical pandemics, hospital data, infection rates, tracking, testing and treatments offered may help in predicting the primary signs that can protect from disasters to a great extent. This study applies 'technology acceptance model' to Malaysian SMEs to explore the possibility of Data Science in launching accurate forecasts that could keep them in a better position rather than getting caught in surprise lockdowns. Since the acceleration in the spread of infectious diseases lately around the globe is due to the growth in the human population and globalisation, Data Analytics can be used to predict where the potential outbreaks may unfold next and thereby to flag the early alert. © 2020 IEEE.