Business Research: QMB 3602

Summary: There’s standards and methods to getting from getting data to getting conclusions.

Exam 1: Scientific Concept of Research

1. Management Science & Analytics

• Management Science: Scientific approach to aid decision-making with quantitative analysis.
• Business Analytics: Extracts insight from data, applied in fields like marketing, finance, and health.
• DMAIC: Define, Measure, Analyze, Improve, and Control

2. Types of Analytics

• Descriptive Analytics: Summarize past data.
• Predictive Analytics: Uses historical data to forecast future trends.
• Prescriptive Analytics: Suggest optimal actions using optimization and simulation.

3. Big Data & Characteristics

• Big Data: Large, complex datasets that are difficult to process traditionally.

Volume	Velocity	Variety	Veracity	Values
Lots of data	Generation speed	Different types	Data reliability	Data insights

4. Data Measurement Scales (Categorize and describe data)

• Nominal: Categories (groups) with no ranking (e.g., marital status).
• Ordinal: Ranked categories without precise differences (e.g., star ratings).
• Interval: Numerical, meaningful differences, but no true zero (e.g., temperature).
• Ratio: Numerical with a true zero (e.g., profits, weight).

5. Decision-Making Traps

• Anchoring: Relying too much on initial information.
• Status Quo Bias: Preferring things to remain unchanged.
• Sunk Cost Fallacy: Sticking with a decision due to past investments.
• Confirmation Bias: Seeking data that supports pre-existing beliefs.
• Framing Effect: The way information is presented influences decisions.
• Overconfidence: Overestimating one’s knowledge or predictions.

6. Research Process

• Stages of Research: Clarify the problem (Ask Question) -> Design research (Form hypothesis) -> Collect data (Make observation) -> Analyze data (Analyze data haha) -> Report findings (Conclusion)
• Common Pitfalls: Poorly defined problems, hidden agendas, researcher bias.
• Types of Data Sources:
  • Primary: Directly collected (e.g., interviews, surveys).
  • Secondary: Previously gathered (e.g., textbooks, reports).
  • Tertiary: Indexes, search engines.

7. Root Cause Analysis Tools

• 5 Whys: Asking “why” repeatedly to find the root cause of effect
• Fishbone Diagram: Head is problem, rest is contributing factors to problem

8. Ethical Considerations in Research

• Privacy, deception, bias, data security.
• Right to nondisclosure all stages
• Right to safety in stage 3 (data collection)
• Ethical research practices: Proper sampling, transparency, avoiding conflicts of interest.

9. Key Performance Indicators (KPIs)

• Dashboards visualize KPIs for decision-making.
• Management Dilemmas: Symptoms leading to business problems.

10. Research Design & Question Hierarchy

• Management-Research Question Hierarchy:
  • Dilemma → Management Question → Research Question → Investigative Questions → Measurement Questions
    • Basically we have a problem what’s the best choice for best outcome 🙂
• Types of Research Questions:
  • Management question: Identifies key issues.
  • Research question: Guides study direction.
  • Measurement question: Collects quantifiable data.

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Exam 2:

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