Mixed Methods Research the Nature

Mixed Methods Research

The nature of the world today is such that everything is in a continuous state of flux. Life, thought, research, study, and practically anything a person can conceptualize goes through a process of evolution according to its history, present analysis of situations, and potential future needs. The world of investigation and research is no exception to this. Increasingly, researchers are acknowledging the value of mixed-methods research.

The differentiation between qualitative and quantitative research has basically been a focus on two basic approaches. Qualitative analysis, for example, has tended to consider open-ended data derived from methods such as interviews and questionnaires. The results are generally non-numerical, where analysis focuses on deriving a certain amount of patterns and response types.

Quantitative research, on the other hand, derives consistency patterns for numerical data such as the amount of times a similar occurrence is recorded, the amount of income over a certain period of time, or the amount of revenue loss as a result of a certain occurrence.

In today's business and technologically advanced world, there are many differentiated factors that have an impact not only on revenue but also on human resources, the way business is conducted, leadership, and a variety of factors that all impact the success or failure rate of a business. Cloud computing lends itself particularly well to mixed-methods research precisely because of this integration of both quantitative and qualitative factors.

If a researcher were to investigate the impact of insider threat on businesses making use of cloud computing, for example, a mixed methods research method would be particularly useful in not only computing the likelihood of such a threat, but also the impact of this likelihood upon quantitative factors such as revenue loss. There are various approaches and starting points that can be considered, depending upon the kind of data and ultimate research aim.

Where the ultimate research aim is, for example, the likelihood of insider threat to a company using cloud computing for data storage and financial information, qualitative data can be obtained by means of interviews and questionnaires to both managers and employees. Variables that could increase the likelihood of insider threat can be certain personality traits or satisfaction levels revealed by employee questionnaires. If an employee, for example, believes that he or she is not receiving the full benefits merited by his or her service level or skill set within the company, it can be determined as more likely for this type of employee to act less ethically than those with a higher satisfaction level regarding their work and skill set match. These data can then be compared to historic quantitative data from companies that have suffered from cloud computing insider crimes. This comparison can then finally lead to a somewhat accurate determination of potential threat within the company being investigated, and appropriate steps for its mitigation recommended.