Unit 3: Scaling & Measurement Techniques

Concept of Measurement

Measurement is the process of assigning numbers or symbols to characteristics of objects, people, or events according to specific rules.

In Management Research: We measure intangible variables like employee satisfaction, customer loyalty, or motivation levels using scales and questionnaires.

Example: If a researcher wants to measure employee satisfaction, they might use a survey asking employees to rate their satisfaction on a scale of 1 to 5.

Need for Measurement

• Objectivity: Converts subjective data into quantifiable facts.
• Comparison: Helps compare between groups or over time.
• Decision Making: Aids managers in making evidence-based decisions.
• Validation: Validates assumptions or hypotheses through actual data.

Example: Before launching a new product, a company may measure customer preference to reduce risks.

Problems in Measurement in Management Research

• Abstract Concepts: Many management concepts (e.g., leadership, motivation) are not directly observable.
• Subjectivity: Responses can be influenced by individual perception, mood, or social pressure.
• Cultural Differences: The meaning of responses or behaviors can vary across regions.
• Lack of Standard Scales: In some cases, reliable measurement tools are not available.

Example: When measuring work stress, one employee may see a heavy workload as motivating, another as stressful.

Validity in Measurement

Validity is the extent to which a tool measures what it is supposed to measure.

Types:

• Content Validity: Does it cover all aspects of the concept?
• Construct Validity: Does it truly reflect the theoretical concept?
• Criterion Validity: Does it correlate well with a related outcome?

Example: If a leadership scale only asks about decision-making, it might miss other aspects like communication or empathy (low content validity).

Reliability in Measurement

Reliability refers to the consistency of the measurement. A reliable tool gives the same results under consistent conditions.

Types:

• Test-retest Reliability: Stability over time.
• Inter-rater Reliability: Agreement between different observers.
• Internal Consistency: Consistency within the test items (e.g., Cronbach’s alpha).

Example: If a motivation questionnaire gives different results each time the same person answers it under the same conditions, it lacks reliability.

📌 Summary Table

Levels of Measurement

In research, levels of measurement refer to the different ways variables can be quantified and analyzed. There are four levels, each providing more information than the last.

1. Nominal Scale—Name or Label Only

Classifies data into distinct categories without any order.

Characteristics:

• No ranking or order.
• Only used for identification or classification.

Examples: Gender (Male, Female, Other), Marital Status (Single, Married, Divorced), Department (HR, Marketing, Finance)

🟢 Use: For counting or categorizing (e.g., how many employees are in each department?).

2. Ordinal Scale – Rank Order

Data is categorized with a meaningful order, but the intervals between the ranks are not equal or known.

Characteristics:

• Shows position or order.
• No precise measurement of differences between values.

Examples: Customer satisfaction (Very Satisfied, Satisfied, Neutral, Dissatisfied), Class ranks (1st, 2nd, 3rd), Likert scale responses (Strongly Agree to Strongly Disagree)

🟡 Use: For ranking preferences, satisfaction levels, etc.

3. Interval Scale—Equal Intervals, No True Zero

Ordered scale where the difference between values is meaningful, but it lacks a true zero.

Characteristics:

• Can add and subtract values.
• Cannot multiply or divide because zero is arbitrary.

Examples: Temperature in Celsius or Fahrenheit, Calendar dates (e.g., 1990, 2000)

🔵 Use: In surveys or experiments that measure differences or averages.

4. Ratio Scale – Highest Level with True Zero

Includes all properties of interval scale plus a true zero point.

Characteristics:

• Allows for all mathematical operations (add, subtract, multiply, divide).
• Zero means complete absence of the variable.

Examples: Income (₹0 means no income),Weight (0 kg means no weight), Age, Height, Distance, Sales figures

🟠 Use: For financial, physical, or quantitative data.

📌 Summary Table:

Attitude Scaling Techniques

Concept of Scale

A scale is a tool or method used to measure people’s attitudes, opinions, or perceptions on a particular subject.

In Management Research: It helps understand what people think, feel, or prefer, especially when studying customer satisfaction, employee motivation, or product perception.

Types of Rating Scales

1. Likert Scale

• A popular scale used to measure agreement or disagreement with a statement.
• Structure: Usually a 5-point or 7-point scale ranging from Strongly Agree to Strongly Disagree.

🔹 Example: "Working at my company gives me satisfaction."

• Strongly Agree (5)
• Agree (4)
• Neutral (3)
• Disagree (2)
• Strongly Disagree (1)

✅ Use: To assess attitudes and opinions in surveys or questionnaires.

2. Semantic Differential Scale

• Measures people's reactions to concepts using bipolar adjective pairs (e.g., Good–Bad, Happy–Sad).
• Structure: A 7-point or 5-point scale placed between two opposite adjectives.

Example: Rate our customer service:

| Polite 😃 | — | — | — | — | — | Rude 😠 |

✅ Use: To measure perceptions or image of a product, brand, or service.

3. Constant Sum Scale

Respondents are given a fixed number of points (e.g., 100) to distribute across different items based on their importance or preference.

Purpose: To measure relative importance or preference.

Example: Distribute 100 points based on what influences your purchase decision:

• Price: ___
• Quality: ___
• Brand: ___
• Design: ___
• (Total must be 100)

✅ Use: In market research to find priority areas or customer preferences.

📌 Comparison Table

Graphic Rating Scale

A graphic rating scale is a visual scale where respondents rate a variable (e.g., performance, satisfaction) by marking a point along a continuous line between two extremes.

🟢 Structure: A horizontal line (usually 5 or 7 points), with labels at each end.

🔹 Example: Rate your satisfaction with our service:

| Very Poor 😠 | ————| ————| ————| ————| Very Good 😄 |

Respondents place a mark on the line that best represents their opinion.

🧩 Application:

Used in performance appraisals, customer feedback forms, and attitude surveys.

Ranking Scale

Respondents are asked to rank items in order of preference or importance.

🟢 Structure: Assign numbers (1 = most preferred, higher numbers = less preferred).

🔹 Example: Rank the following features of a mobile phone (1 to 4):

• Battery life ___
• Camera quality ___
• Price ___
• Design ___

🧩 Application:

Used in market research to understand what features or services customers value most.

Paired Comparison Scale

Respondents are given two items at a time and asked to choose one based on a specific criterion.

🟢 Structure: All possible pairs of items are compared.

🔹 Example: Which feature is more important?

• Battery life vs. Price → (Choose one)
• Battery life vs. Camera
• Camera vs. Price

...and so on.

🧩 Application:

Used when comparing a limited number of items, such as product features, training methods, or employee skills.

Forced Ranking Scale

A method where a manager ranks employees by forcing a specific distribution (e.g., top 10%, middle 70%, bottom 20%).

🟢 Structure: Each employee is ranked relative to others, not individually rated.

🔹 Example: In a team of 10 employees:

• Top 2 = High performers
• Middle 6 = Average performers
• Bottom 2 = Low performers

🧩 Application:

Used in performance appraisal systems to promote merit-based rewards or identify underperformers.

📌 Summary Table: