Research Design

Research Design Question: 

“Are New York government administrative efforts in aiding the homeless more or less effective than nonprofit organizations?”

The Dependent Variable (DV) 

The dependent variable in this research study is the effectiveness of initiatives aimed at assisting individuals experiencing homelessness.

Part 1- (Case Study Research Design)

1) What is the purpose of a case study design?,

2)  When is this design used? ,

3) Why is this design the most appropriate choice based on the research question? ,

4) What are the potential weaknesses of the research design?,

Part 2- (Qualitative Research Method) 

1) What is the purpose of the qualitative research method?

2)  When is this method used?

3) Why is this method the most appropriate choice based on the research question?

4) What are the potential weaknesses of the research method?

Part 1: Case Study Research Design

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1) What is the purpose of a case study design?

The purpose of a case study design is to conduct an in-depth, contextual analysis of a specific phenomenon within its real-life setting. It allows researchers to explore complex issues where the boundaries between the phenomenon and context are not clearly defined. It often examines “how” and “why” questions.

2) When is this design used?

This design is used when:

• The researcher seeks a deep understanding of a real-world issue.

• The focus is on contemporary phenomena.

• Multiple sources of data (e.g., interviews, documents, observations) are needed.

• The aim is to compare or evaluate specific programs, policies, or organizations.

3) Why is this design the most appropriate choice based on the research question?

This design is appropriate because the research question compares the effectiveness of two different types of organizations (government vs. nonprofit) within the same issue area—homeless services. A case study allows the researcher to:

• Compare organizational strategies and outcomes.

• Examine the contextual factors influencing success.

• Collect rich, detailed data from multiple stakeholders (e.g., staff, clients, policymakers).

• Analyze specific programs in depth rather than in broad, abstract terms.

4) What are the potential weaknesses of the research design?

• Limited generalizability: Findings may apply only to the cases studied and not to all similar settings.

• Time- and resource-intensive: Requires extensive data collection and analysis.

• Subjectivity: Risk of researcher bias in interpreting complex qualitative data.

• Difficult comparisons: May be challenging to draw clear conclusions if cases vary greatly in size, resources, or goals.

Part 2: Qualitative Research Method

1) What is the purpose of the qualitative research method?

The purpose of qualitative research is to understand human experiences, perspectives, and meanings through rich, descriptive data. It emphasizes depth over breadth and is ideal for exploring processes, motivations, and contextual dynamics.

2) When is this method used?

This method is used when:

• The research involves exploring perceptions, attitudes, or experiences.

• The aim is to understand rather than quantify.

• There are open-ended questions with complex variables.

• The context or social setting plays a major role in shaping outcomes.

3) Why is this method the most appropriate choice based on the research question?

This method suits the research question because:

• The effectiveness of homelessness initiatives is not solely measurable by numbers, but also by perceptions of impact, accessibility, dignity, and satisfaction.

• It enables interviews with key stakeholders, including homeless individuals, government workers, and nonprofit staff, to uncover insights that quantitative data might miss.

• It facilitates a nuanced comparison of how each organization functions in context, how their clients experience services, and how success is defined.

4) What are the potential weaknesses of the research method?

• Subjectivity: Analysis relies heavily on researcher interpretation.

• Limited replicability: Difficult to reproduce results across different settings.

• Time-consuming: Requires detailed data collection and careful coding.

• Smaller sample sizes: Can lead to criticisms about generalizability.