In the introduction of the article “Integrated framework for information security investment and cyber insurance,” the author, Shaun S. Wang, assumes that every reader knows or must know the United States’ share of the world’s GDP, proceeding to present calculations based on the percentage. Seeing that the author argues with facts and data, it is critical to remain factual, clear, and accurate as much as possible. However, the author uses the U.S.’s percentage share of the global GDP without expressly mentioning it in the paper, leaving the reader to search and verify the data. Most critical readers know that authors can manipulate data or present nonfactual information to support their preferred argument. Therefore, every author should ensure that the data and statistics they use do not raise suspicions.
The author leaves essential data and information without proper referencing. On page three, he states that the world spends $60 billion annually on cybercrime without acknowledging the source or mentioning that the figure is estimated. Again on page five, the author describes a regulation that imposes fines on firms for data breaches but does not cite any sources. On page six, he states that “it was reported that JP Morgan has an annual cybersecurity budget of $250 million” and continues with more statistics without citing any sources. An article that involves data, statistics, and facts requires high-level referencing to ensure validity.
The article proposes an analytical model aimed at optimizing firms’ cybersecurity investments but fails to analyze the model’s limitations. Instead of discussing the factors that businesses should consider before implementing the model, the author uses the limitations section to explore future research areas. Since the author presents a new model, he should provide as much detail as possible to the readers who might want to implement it.
Reference
Wang, S. S. (2019). Integrated framework for information security investment and cyber insurance. Pacific-Basin Finance Journal, 57, 101173. Web.