CHAPTER 1 — BUSINESS RESEARCH

1. Business Research (p. 7)

Business research is the systematic and organized process of collecting, analyzing, and interpreting information to help solve business problems and support decision-making.

Businesses use research to:

  • Understand customers’ needs and behaviors

  • Identify new market opportunities

  • Improve products, services, or internal processes

  • Monitor competitors and industry trends

  • Reduce risk and uncertainty before acting

In short: Business research turns data into actionable insights.

2. Scientific Method (p. 8)

The scientific method is a structured process used to generate reliable knowledge.
It relies on:

  • Observation

  • Logical reasoning

  • Evidence-based conclusions

  • Replication (results should be repeatable)

Steps:

  1. Identify a problem or question

  2. Review existing information

  3. Form a hypothesis

  4. Collect data to test the hypothesis

  5. Analyze and interpret results

  6. Accept, revise, or reject hypothesis

It ensures research is objective, rigorous, and free from personal bias.

3. Reasoning Approaches (p. 17–18)

Induction (p. 17)

Induction moves from specific observations → general conclusions.
Example:
You observe that multiple customers prefer sustainable packaging → you conclude that sustainability influences buying decisions.

Used when developing new theories.

Deduction (p. 18)

Deduction moves from general theory → specific prediction.
Example:
Theory says higher satisfaction leads to loyalty → you predict satisfied users of your product will repurchase.

Used when testing existing theories.

4. Concepts, Constructs, and Definitions

Concept (p. 9)

A general idea representing something real or abstract that we want to study.
Examples: Quality, leadership, morale.

Construct (p. 10)

A a definition specifically invented to represent an abstract phenomena for a given research project
We measure constructs using indicators.
Examples:

  • Job satisfaction (measured through survey ratings)

  • Motivation (measured through behavior or self-report)

Conceptual Scheme (p. 11)

A framework that shows how multiple concepts relate to each other.

the interrelationship between concepts and construct
It helps researchers organize thought and explain phenomena.

Example:
Service Quality → Satisfaction → Loyalty

Operational Definition (p. 11)

Specifies exactly how a concept will be measured in a study.
It ensures clarity and consistency.

Example:
“Brand loyalty will be measured by number of repeat purchases within 3 months.”

5. Variables in Research (p. 12–15)

A variable is any characteristic that can take on different values.

Independent Variable (IV / Predictor Variable) (p. 12)

The variable that is manipulated or believed to influence another variable.
Example: Advertising Spending.

Dependent Variable (DV / Criterion Variable) (p. 12)

The variable that is measured and is affected by the IV.
Example: Sales Revenue.

Extraneous Variable (EV) (p. 13)

A variable not intentionally studied, but which may influence the DV.
Researchers try to control or remove these.

Control Variable (CV) (p. 14)

A variable that is held constant to prevent it from affecting results.
Example: Conduct all interviews at the same time of day.

Confounding Variable (CFV) (p. 14)

An uncontrolled factor that impacts the DV and makes it hard to tell whether the IV caused the effect.
These threaten the validity of research.

Moderating Variable (MV) (p. 13)

A variable that changes the strength or direction of the relationship between IV and DV.
Example: Advertising (IV) affects purchases (DV) more strongly among younger consumers (MV).

Intervening Variable (IVV) (p. 15)

A variable that explains how or why the IV affects the DV.
Example:
Training (IV) → Increases Knowledge (IVV) → Improves Job Performance (DV)

6. Hypotheses and Theories (p. 16)

Hypothesis

A testable prediction about the relationship between variables.

Types of Hypotheses:

Type

What it Predicts

Example

Descriptive Hypothesis

Describes what exists

“30% of employees use flexible work hours.”

Correlational Hypothesis

Variables move together but without proving cause

“Employee engagement is positively related to productivity.”

Causal Hypothesis

IV causes change in DV

“Increasing training hours increases performance.”

Relational Hypothesis

Specifies how variables are related

“As price increases, demand decreases.”

Theory (p. 16)

A theory is a well-supported set of ideas explaining how phenomena work. It drives the research.
It is built from repeated research findings.

Model (p. 16)

A simplified visual or mathematical representation of a theory.
Helps communicate relationships clearly.

Case (p. 16)

The entuty of thing the hypothesis talks about, when the hypothesis is based on more than one case, it would be a generalization 

7. Data Blending (p. 5)

Data blending means combining data from multiple sources to increase insight.
Examples:

  • Internal sales data + customer demographics

  • Survey data + website analytics

This leads to richer, more accurate conclusions.