Chapter 3 outline

profileabhilash tati
chapter3outline_v10.pdf

Chapter III Outline: Methodology

Ransomware has emerged as one of the most severe dangers to enterprises' routine

commercial operations. Healthcare institutions are particularly vulnerable to ransomware attacks

due to the limits imposed by time constraints and limited resources. This chapter summarizes the

study's research methodologies. It describes the individuals, their characteristics, and how they

were selected. This chapter is organized into different sections: section 1 is the introduction,

section two the research design, section 3 population and sample, section 4 materials and

instrumentation, section 5 variables and operational definitions, section 6 data collection and

statistical analyses, section 7 Limitations, section 8 delimitations, and section 9 ethical assurances.

Research Design

This study seeks to understand the impact of ransomware in healthcare by conducting

surveys using Survey Monkey. This study used a quantitative research paradigm, including online

surveys, as detailed later in the chapter. Leedy (1993) refers to quantitative research as the

experience of others and offers the most significant evidence. It aims to understand people's worlds

from their perspective. The primary data collection method used in this research is surveys

obtained from Survey Monkey having conducted the study. Through the surveys, the researcher

can appropriate the usefulness of the information in analyzing the impact of ransomware attacks on

healthcare. Survey as a means of data collection was more appropriate than other methods such as

probability sampling because it had more precision according to the research paradigm.

Steps followed in the research design include:

1. Theory. This signified the deductive approach that the research would take

2. Hypothesis. This step involved outlining the hypotheses and testing them

Mary Lind
Sentence not clear.
Mary Lind
appropriate not correct word to use.

3. Research design. This step involved selecting an appropriate research design

4. Operationalizing concepts. This step involved devising the research concepts

5. Selecting a research site. This step involved choosing the setting for the research

6. Selecting respondents. Identifying the population and the respondents in the study.

7. Data collection

8. Process of data. Identifying variables and classifying them.

9. Analysis

Construct Item Hypothesis Habit (1) Habit2(Complying with

information security policies is something I do automatically) Habit3(Complying with information security policies is something I do without having to remember to do so consciously.) Habit4(Complying with information security policies is something that makes me feel weird if I do not do it) Habit7(Complying with information security policies is something that belongs to my (daily, weekly, monthly) routine) Habit8(complying with information security policies is something I start doing before I realize I'm doing it)

Habit positively influences perceived severity.

Intention (2) Int1(What is the chance that you would do what [the scenario character] did in the described Scenario?) Int2(I would act the same way as [the scenario character] did if I were in the same situation.)

Vulnerability positively affects employees' intention to comply with IS security policies.

Perceived severity (3) PerceivedSev1(An information security breach in my organization would be a severe

Perceived severity positively affects employees' intention to comply with IS security

Mary Lind
No measure for your dependent variable?
Mary Lind
Put he reference to the article where you got these items at the top of the table.

problem for me) PerceivedSev3(If I did what [the scenario character] did, there would be severe information security problems for my organization)

policies.

Response efficacy (4) ResponseEfficacy1(Complying with information security policies in our organization keep IS security breaches down) ResponseEfficacy2(If I comply with information security policies, IS security breaches are scarce.) ResponseEfficacy3(Careful compliance with IS security policies helps avoid security problems.)

Response efficacy positively affects employees' intention to comply with IS security policies.

Response cost (5) ResponseCost4(Complying with information security policies inconveniences my work) ResponseCost5((There are too many overheads associated with complying with information security policies) ResponseCost6(Complying with information security policies would require a considerable investment of effort other than time)

Response cost negatively affects employees' intention to comply with IS security policies.

Rewards (6) Reward1(If I did what [the scenario character] did, I would save time.) Reward2(If I did what [the scenario character] did, I would save work time) Reward3(Non-compliance with the information security policies saves work time)

Rewards negatively affect employees' intention (dependent variable) to comply with IS security policies

Self-efficacy (7) Self Efficay1(I can comply with information security policies by myself.) Self Efficay2(Doing the opposite of what the [scenario

Self-efficacy positively affects employees' intention to comply with IS security policies.

Mary Lind
Must show the scenario

character] did would be difficult for me to do) Self Efficay3(Doing the opposite of what the [scenario character] did would be easy for me to do.)

Perceived vulnerability (8) PerceivedVuln2(My organization could be subjected to an information security threat if I did what [the scenario character] did) PerceivedVuln3(An information security problem could occur if I did what [the scenario character] did.)

Vulnerability positively affects employees' intention to comply with IS security policies.

Population and Sample

The participants consisted of healthcare facilities, government entities, and healthcare

professionals. The population will be sampled randomly from a pool of 1000 individuals and

entities out of the possible 329.5 million (United states population) because of their specialization

and training on healthcare ransomware. The characteristics of the sample included both medium

and small enterprises with a total number of 118 people working for the organizations, including

nurses, doctors, and IT staff. The population was deemed relevant because of the day-to-day

interactions of healthcare professionals with medical devices. The characteristics of the

respondents include age, level of education, economic status, and gender.

Materials and Instrumentation

When feasible, all items were altered from previously validated instruments to meet the

needs of the participants. All the survey responses were rated on a Likert scale ranging from 0 to

10. The composite measures for deterrence constructs were calculated to create a sanction measure

that reflected both the risk and the cost of perceived punishment. This was accomplished by

multiplying each severity measure by the certainty measure associated with the deterrence

Mary Lind
if 118 is your sample size you need to use gpower to determine sample size.
Mary Lind
where did you get 1000?

construct. It also utilized observations of healthcare facilities as participants reported their

experiences. All the studies and surveys were conducted using SurveyMonkey as a tool. The

survey was adapted using Likert scale to show only the most relevant responses from the IT

manages and the medical professionals. The IT manages will have to implement two factor

authentication system in medical gadgets to combat the issue of ransomware. The survey is also

adapted to show the level of awareness on healthcare ransomware and the available strategies used

to combat the issue.

Variables and Operational Definitions

Hypotheses

H0: Habit influences perceived severity.

H1: Habit does not influence perceived severity

H0: Vulnerability does not affect employees' intention to comply with IS security policies.

H1: Vulnerability positively affects employees' intention to comply with IS security policies.

H0: Perceived severity does not affect employees' intention to comply with IS security policies.

H1: Perceived severity positively affects employees' intention to comply with IS security policies.

H0: Response efficacy does not affect employees' intention to comply with IS security policies.

H1: Response efficacy positively affects employees' intention to comply with IS security policies.

H0: Response cost does not affect employees' intention to comply with IS security policies.

H1: Response cost negatively affects employees' intention to comply with IS security policies.

H0: Rewards does not affect employees' intention to comply with IS security policies

H1: Rewards negatively affect employees' intention to comply with IS security policies

H0: Self-efficacy does not affect employees' intention to comply with IS security policies.

H1: Self-efficacy positively affects employees' intention to comply with IS security policies.

Mary Lind
This has nothing to do with design
Mary Lind
managers?

H0: Vulnerability does not affect employees' intention to comply with IS security policies.

Variables

H1: Vulnerability positively affects employees' intention to comply with IS security policies.

Variables

Two dependent variables were used is Scenario and intention. The inclusion of intention as

a dependent variable is congruent with PMT, as the behavioral intention has always been used to

assess protective motive in research. About this item, the answer scale went from 0 (no chance at

all) to 10 (100 percent chance). An additional single-item measure, which asked respondents to

judge the realism of a specific scenario, was included alongside questions evaluating latent

components. On a scale of 0 to 10, the credibility of this item ranged from 0 to 10.

Table 1

Summary of Variables

Variable Type LoM Values Data source

Intention Dependent Interval 0-50 units Survey

Scenario Independent-1 Interval 1-10 units Secondary data

Realism Independent-2 Nominal 0 = left

1 = right

Secondary data

Gender Independent 3 Nominal Secondary data

Note: LoM = level of measurement, DV = dependent variable, IV = independent variable.

Data Collection and Statistical Analysis

Mary Lind
what is this - you are NOT collecting secondary data?

This report was created using data from an American municipal organization. Because

realism is a fundamental concern with the scenarios approach, we chose a single organization to

guarantee that the events were realistic and contextually relevant for the people who answered. As

a result, the target audience comprised the whole organization's clerical and administrative staff.

This particular business was picked due to its compliance with information security standards

inside its IT architecture. Furthermore, the equipment was physically placed at a university to

ensure respondents' secrecy further. With the model in hand, we tested its performance against

three control variables: gender, scenario type, and the perceived realism of the Scenario. In this

section, we added the scenario type since we allocated different situations to participants in a

random manner.

Assumptions

Awareness of the impact of ransomware attacks on healthcare data and other facilities is

inadequate among healthcare professionals.

Limitations

Our study had typical limitations. First, the data was obtained from one organization,

including biases unique to the sample. Therefore, care should be taken in generalizing findings to

other organizations. Second, the administrative and clerical workers at the organization we

sampled were predominantly female. Although our tests did not find any difference in the

compliance based on gender, it is essential in other IT contexts. Third, our study was limited in its

use of intention as the dependent variable. Measures of intention are widely accepted as needed,

especially in criminological research; there is also strong evidence of a strong relationship

between intention and actual behavior Delimitations

Ethical Assurances

Mary Lind
What you are using medical facilites - what is municipal?

The goal of the study was outlined before issuing out the survey. Following that, subjects

received information outlining the study's objectives in further detail. They were assured of secrecy

and anonymity and advised that participation in the study was entirely voluntary and that they

might leave at any time without incurring any negative consequences. They were then asked to

sign a consent form indicating that they had read and comprehended the information presented to

them. Digital Consent was acquired to ensure that the survey was done willingly.

CONCLUSION

This chapter discusses the technique employed in this study. A description of qualitative research

as a data collecting and analysis technique. This chapter explained the procedures used to obtain

the data and offered information about the sample.

REFERENCES

Hewitt, B., Dolezel, D., & McLeod Jr, A. (2017). Mobile device security: Perspectives of future

healthcare workers. Perspectives in health information management, 14(Winter).

Janwadkar, S., & Dhavse, R. (2021). Qualitative and quantitative analysis of parallel-prefix adders.

In Advances in VLSI and Embedded Systems (pp. 71-88). Springer, Singapore.

Liu, Y., Yang, L., & Jiang, W. (2020). Qualitative and quantitative analysis of the relationship

between water pollution and economic growth: a case study in Nansi Lake catchment,

China. Environmental Science and Pollution Research, 27(4), 4008-4020.

Liang, H., & Xue, Y. L. (2010). Understanding security behaviors in personal computer usage: A

threat avoidance perspective. Journal of the association for information systems, 11(7), 1.

Vance, A., Siponen, M., & Pahnila, S. (2012). Motivating IS security compliance: Insights from

habit and protection motivation theory. Information & Management, 49(3-4), 190-198.