casual research design

Page 1: Introduction to Research Designs

• School: W. P. Carey School of Business, Arizona State University

• Topic: Overview of Exploratory, Descriptive, and Causal Research Designs

Page 2: Review of Previous Class

• Focus on three basic types of research design:

  • Emphasis of each type

  • Key characteristics and techniques of "Exploratory" research

  • Differences between cross-sectional and longitudinal studies in "Descriptive" research

Page 3: Descriptive Research Example

• Example: Brand Switching Matrix from Sun Devils Panel

  • Sample Size: 100 students

  • Brand Loyalty for Brand B: 48.1% (13/27)

  • Market Share: Brand A (April: 19%, May: 15%)

  • Conditional Probability of buying Brand C in May after buying Brand B in April: 40.1% (11/27)

  • Data Presentation:

    • Matrix of brand shifts from April to May

Page 4: Competitive Analysis in Brand Switching

• Identifying competition: Brands B and C show significant rivalry

• Brand data analysis:

  • Brand A (April: 21.1%, May: 11.1%)

  • Brand B (April: 26.3%, May: 40.1%)

  • Brand C (April: 3.7%, May: 38.9%)

Page 5: Cross-sectional Study Limitations

• Explanation of cross-sectional study timeframes:

  • Two time points: April and May

  • Possibility to calculate Market share, not brand loyalty or conditional probability

Page 6: Learning Objectives

• Understanding of causality:

  • Distinction between laboratory experiments and field experiments

Page 7: Types of Research Design

• Categorization:

  • Exploratory Research

  • Descriptive Research

  • Causal Research

  • Conclusive Research

Page 8: Causal Research Focus

• Decision Problem (DP): Improving student satisfaction

• Research Problem (RP): Identifying factors affecting student satisfaction

• Factors from exploratory research:

  • Self-confidence, curriculum, quality of teaching, etc.

• Cross-sectional survey results: Correlation between mentorship and satisfaction

Page 9: Defining Causal Research

• Causal Research: Focuses on obtaining evidence for cause-and-effect relationships

• Applicability:

  • When stronger evidence is required for the outcomes of actions

  • Testing cause-and-effect relationships

• Methodology: Experimentation

Page 10: Correlation vs. Causation

• Definition of causation: Change in one variable results in change in another

Page 11: Misinterpretation of Correlation

• Correlation does not imply causation due to:

  1. Reverse causation (e.g., wind causing windmills to rotate)

  2. Third factor influence (e.g., drinking habits influencing both headache and shoe wearing)

Page 12: Coincidental Correlation

• Third point of misinterpretation: Coincidence (spurious correlations)

Page 13: Conditions for Inferring Causality

• Necessary conditions include:

  1. Concomitant variation

  2. Time order of events

  3. Absence of alternative causes

• Example of causation framework

Page 14: Example 1 – Promotion Impact on Sales

• Hypothesis: "Buy One Get One Free" increases sales

• Analysis of conditions affecting sales through variation assessments

Page 15: Example 2 – Advertisement Impact on Sales

• Hypothesis: Advertisement spending increases sales

• Comprehensive assessment of associated variation

Page 16: Conducting Causal Research via Experiments

• Experiments enable isolation of relationships between independent and dependent variables:

  1. Change levels of X variables

  2. Observe impact on Y variables

  3. Control other variables

Page 17: Distinction of Experimental Context

• Laboratory vs. Field Experiments:

  • Laboratory: Controlled conditions, higher precision

  • Field: Natural settings, reflects real-life scenarios

Page 18: Advantages and Disadvantages of Experimental Approaches

• Laboratory experiments:

  • (+) Replicability and control

  • (-) Artificiality of setting

• Field experiments:

  • (+) Realistic context

  • (-) Less control over variables

Page 19: A/B Testing in Causal Research

• Explanation of A/B testing as a randomized experiment

Page 20: Market Testing Overview

• Definition: Controlled experiment in selected market segments

Page 21: Characteristics of Experiments

• Key characteristics:

  1. Control of conditions by the experimenter

  2. Random assignment of subjects to conditions

Page 22: Key Variables in Research

• Independent Variables (IVs): Factors being varied to assess impact

• Example: Packaging influence on coffee taste perception

Page 23: Dependent Variables (DVs)

• DVs: Observed attitudes, beliefs, perceptions, and behaviors affected by IVs

• Example: Rating scale for taste perception of coffee

Page 24: Comparative Analysis of Research Designs

• Objective:

  • Exploratory: Discovery of ideas

  • Descriptive: Market characteristics

  • Causal: Cause-and-effect determination

• Distinction of methodology:

  • Exploratory: Qualitative, smaller samples

  • Descriptive: Quantitative, larger samples

  • Causal: Experiments manipulating independent variables

Page 25: Quiz and Assignments

• In-class assignments to reinforce learning concepts.