Scaling in Research Methods for Business
An
Assignment
on
Scaling in Research Methods
Submitted to:
Madam Tahira
Submitted by:
Muhammad Usman Ahmad
University of Education
Dated: 15-02-2019
Scaling
Introduction:
Scaling is the procedure of measuring and assigning the objects to the numbers according to the specified rules. In other words, the process of locating the measured objects on the continuum, a continuous sequence of numbers to which the objects are assigned is called as scaling.
Suppose that we want to measure customers’ behavior toward Android mobile usage. After developing one or more scale items or questions, we will decide on a scale that allows us to assign numbers to the attribute (behavior toward Android mobile usage) of our objects (customers). This allows us to successively classify our objects (customers) in terms of how unfavorable or favorable they are toward using an Android mobile. One of the many options we have to classify customers is a Likert scale. The Likert scale is a scale designed to examine how strongly respondents agree with a statement (such as “I enjoy using an Android mobile”) on a five-point scale with the following anchors:
1 = Strongly Disagree,
2 = Disagree,
3 = Neither agree nor Disagree,
4 = Agree,
5 = Strongly Agree.
Hence, the Likert scale allows us to distinguish customers in terms of how they differ from one another in their attitude toward Android mobiles, each respondent being assigned a number indicating a more or less unfavorable, neutral, or more or less favorable.
Now the questions worthy to ask are:
- What are the meanings of the numbers 1, 2, 3, 4, and 5?
- Does the scale that we have used allow us for instance to rank our objects (2 is more than 1)?
- Does it allow us to compare differences between objects (in other words is the difference between 1 and 2 the same as the difference between 2 and 3?
- Does it allow us to calculate certain statistics such as a mean (or average) and a standard deviation?
The answer to all these questions is: it depends. It depends on the type of the scale (that is, the basic scale type) that we have used.
Types of Scale:
There are four types of scale:
vNominal
v Ordinal
v Interval
vRatio.
Let’s have a closer at each one.
Nominal Scale:
The nominal scale is one that allows the researcher to assign subjects to certain categories or groups. It is a scale which represents only the names or where the numbers serve only as labels or tags to categorize or identify the objects. It deals with variables that are non-numeric or where the numbers have no value. In other words, we can put them in any order and it wouldn’t matter. The nominal scale gives some basic, categorical, gross information.
Examples:
1. Please select the degree of discomfort of the disease:
· 1-Mild
· 2-Moderate
· 3-Severe
2. Where do you live?
· A-North of the Equator
· B-South of the Equator
· C-Neither: In the international space station
3. How would you describe your behavioral pattern?
· E-Extroverted
· I-Introverted
· A-Aggressive
Notice that all of these scales are mutually exclusive (no overlap) and none of them have any numerical significance. A good way to remember all of this is that “nominal” sounds a lot like “name” and nominal scales are kind of like “names” or labels.
Elaboration:
Think about the numbers on the jerseys of football players. Is the player wearing number 1 a better player than the player wearing number 82? Maybe, but that doesn’t have anything to do with the numbers they wear.
Jersey numbers have no value as far as telling us anything about the ability of the players; it’s just a way to identify them. Other examples of variables measured on a nominal scale include gender, race and the number on pool balls.
Sometimes for statistical analysis, a researcher will give non-numeric variables numeric values. For example, we might say that students who eat a healthy breakfast are -1, the students who eat an unhealthy breakfast are 0, and the students who do not eat breakfast are +1. These numbers are just a way to mark who is in which group but don’t really have value.
Ordinal Scale:
An ordinal scale not only categorizes the variables in such a way as to denote differences among the various categories, it also rank-orders the categories in some meaningful way. With any variable for which the categories are to be ordered according to some preference, the ordinal scale would be used. The preference would be ranked (e.g., from best to worst; first to last) and numbered 1, 2, and so on.
Examples:
- How satisfied are you with our products?
- Totally Satisfied
- Satisfied
- Neutral
- Dissatisfied
- Totally Dissatisfied
- How happy are you with our customer services?
- Very Happy
- Happy
- Neutral
- Unhappy
- Very Unhappy
- How would you rate the service of our staff?
- Excellent
- Very Good
- Good
- Poor
- Worst
- Totally Satisfied
- Satisfied
- Neutral
- Dissatisfied
- Totally Dissatisfied
- Very Happy
- Happy
- Neutral
- Unhappy
- Very Unhappy
- Excellent
- Very Good
- Good
- Poor
- Worst
Elaboration:
The ordinal scale possesses the quality of magnitude. Here the numbers are assigned to the object to determine the relative extent to which certain characteristics are possessed, i.e. identifying whether an object has less or more characteristic than another object. This scale not only assigns values to the variables but also measures the rank or order of the variables, such as:
- Grade
- Satisfaction
- Happiness
Interval Scale:
Interval Scale is a scale in which the numbers are used to rank attributes such that numerically equal distances on the scale represent equal distance in the characteristic being measured. The interval scale allows us to compare differences between objects. The difference between any two values on the scale is identical to the difference between any other two neighboring values of the scale. The interval scale possesses both the magnitude and equal intervals, but no absolute zero.
Examples:
- How likely is it that you would recommend a Samsung Galaxy S5 mobile to a friend or colleague?
Not at all likely extremely likely
0
1
2
3
4
5
6
7
8
9
- An example of an interval scale is the Celsius scale of temperature. In the Celsius temperature scale, the distance between 20 degrees and 40 degrees is the same as the distance between 75 degrees and 95 degrees.
- Using any numbers from 0 to 9, where 0 is the worst health care possible and 9 is the best health care possible, what number would you use to rate all the health care you got in the last 12 months?
Best Health Care
8
7
6
5
4
3
2
1
Worst Health Care
Not at all likely extremely likely
|
0
|
1
|
2
|
3
|
4
|
5
|
6
|
7
|
8
|
9
|
|
Best Health Care
|
8
|
7
|
6
|
5
|
4
|
3
|
2
|
1
|
Worst Health Care
|
Elaboration:
Interval scale contains all the properties of ordinal scale, in addition to which, it offers a calculation of the difference between variables. The main characteristic of this scale is the equidistant difference between objects. Interval scales are nice because the realm of statistical analysis on these data sets opens up. For example, central tendency can be measured by mode, median, or mean; standard deviation can also be calculated.
Like the others, you can remember the key points of an “interval scale” pretty easily. “Interval” itself means “space in between,” which is the important thing to remember, interval scales not only tell us about order, but also about the value between each item.
Even if interval scales are amazing, they do not calculate the “true zero” value which is why the next scale comes into the picture.
Ratio Scale:
Ratio Scale is the highest level of measurement scales. This has the properties of an interval scale together with a fixed (absolute) zero point. The absolute zero point allows us to construct a meaningful ratio. Ratio scales permit the researcher to compare both differences in scores and relative magnitude of scores. The ratio scale measures the magnitude of the differences between points on the scale but also taps the proportions in the differences.
Examples: Weights, Lengths and Times
- What is your daughter’s current height?
· Less than 5 feet
· 5 feet 1 inch – 5 feet 5 inch
· 5 feet 6 inches – 6 feet
· More than 6 feet
- What is your weight in kilograms?
· Less than 50 Kilograms
· 51 – 70 Kilograms
· 71 – 90 Kilograms
· 91 – 110 Kilograms
· More than 110 Kilograms
- How often do you visit your grandpa and granny in a month?
Elaboration:
Ratio scale is the most powerful of the four scales because it has a unique zero origin (not an arbitrary origin) and subsumes all the properties of the other three scales. In market research, a ratio scale is used to calculate market share, annual sales, the price of an upcoming product, number of consumers etc.
The weighing balance is a good example of a ratio scale. It has an absolute (and not arbitrary) zero origin calibrated on it, which allows us to calculate the ratio of the weights of two individuals. For instance, a person weighing 250 pounds is twice as heavy as one who weighs 125 pounds. Note that multiplying or dividing both of these numbers (250 and 125) by any given number will preserve the ratio of 2:1.
Rating Scales:
The following rating scales are often used in business research:
- Dichotomous scale
- Category scale
- Semantic differential scale
- Numerical scale
- Itemized rating scale
- Likert scale
- Fixed or constant sum rating scale
- Stapel scale
- Graphic rating scale
- Consensus scale
Dichotomous Scale:
The dichotomous scale is used to elicit a Yes or No answer.
For example:
- Do you own a car?
- Yes
- No
- Is it raining?
- Yes
- No
- Will you take the Finance Lecture Today?
- Yes
- No
Category Scale:
The category scale uses multiple items to elicit a single response, as per the following examples. These also uses the nominal scale.
Examples:
1. Where do you reside in London?
· East London
· West London
· North London
· South London
· Outskirts
2. What is your cast?
· Malik
· Awan
· Pathan
· Bukhari
Semantic Differential Scale:
The semantic differential scale is used to assess respondents’ attitudes toward a particular brand, advertisement, object, or individual. The responses can be plotted to obtain a good idea of their perceptions. A semantic differential scale is ordinal in nature. However, it is often treated as an interval scale.
Examples:
- Courageous Timid
- Honest Dishonest
- Beautiful Ugly
- Responsive Unresponsive
Numerical scale:
The numerical scale is similar to the semantic differential scale, with the difference that numbers on a five-point or seven-point scale are provided, with bipolar adjectives at both ends. This scale is also often treated as an interval scale, although it is formally ordinal in nature.
Examples:
- How pleased are you with your new car?
Extremely pleased 7 6 5 4 3 2 1 extremely Displeased
- How would you rate the honesty of your friend?
Honest [7 6 5 4 3 2 1] Dishonest
Itemized Rating Scale:
A five-point or seven-point scale with anchors, as needed, is provided for each item and the respondent states the appropriate number on the side of each item, or circles the relevant number against each item. The responses to the items are then summed. This uses an interval scale.
Examples:
- Circle the number that is closest to how you feel for the item below:
|
Not at all
interested
|
Somewhat interested
|
Moderately Interested
|
Very much interested
|
|
1
|
2
|
3
|
4
|
How would you rate your interest in changing current organizational policies?
1 2 3 4
Likert Scale:
The Likert scale is designed to examine how strongly subjects agree or disagree with statements on a five-point scale with the following anchors:
|
Strongly Agree Disagree Neither Agree nor Disagree Agree Strongly Agree
1 2 3 4 5
|
Example:
State the extent to which you agree with each of the following statements:
My work is very interesting 1 2 3 4 5
I am not engrossed in my work all day 1 2 3 4 5
Fixed or Constant Sum Rating Scale:
In this scale, the respondents are asked to allocate a constant sum of units such as points, rupees, or chips among a set of stimulus objects with respect to some criterion. For example, you may wish to determine how important the attributes of price, fragrance, packaging, cleaning power, and lather of a detergent are to consumers.
Examples:
- Please distribute 100 points across the following types of support according to importance
Telephone Support ____
Online Chat Support ____
Email Support ____
Online Documentation ____
Online Forum Support ____
100
Stapel Scale:
This scale simultaneously measures both the direction and intensity of the attitude toward the items or events.
Example:
- State how you would rate your supervisor’s abilities with respect to each of the characteristics mentioned below, by circling the appropriate number.
|
+3
|
+3
|
+3
|
|
+2
|
+2
|
+2
|
|
+1
|
+1
|
+1
|
|
Adopting Modern Technology
|
Product Innovation
|
Interpersonal Skills
|
|
-1
|
-1
|
-1
|
|
-2
|
-2
|
-2
|
|
-3
|
-3
|
-3
|
Graphic Rating Scale:
A graphical representation helps the respondents to indicate on this scale their answers to a particular question by placing a mark at the appropriate point on the line. Respondents can select a particular option on a line or scale to depict rating. This rating scale is often implemented by HR managers to conduct employee evaluation.
Example:
- On a scale of 1 to 10, how would you rate your supervisor?
—– 10 Excellent
—–
—–
—–
—–
—– 5 Adequate
—–
—–
—–
—– 1 Very Bad
Consensus Scale:
Consensus scale is developed after the selected items have been examined and tested for their validity and reliability. One such consensus scale is the Thurstone Equal Appearing Interval Scale, where a concept is measured by a complex process followed by a panel of judges.
Ranking Scales:
Ranking scales are used to tap preferences between two or among more objects or items (Ordinal in nature). However, such ranking may not give definitive clues to some of the answers sought.
Alternative methods to ranking scale are;
- Paired Comparison
- Forced Choice
- Comparative Scale
Let’s elaborate each one of them briefly.
Paired Comparison:
The process of rank ordering the objections from most to least important is best approached through the questioning technique known as ‘paired comparison’. Each of the objections is paired by the researcher. This is a comparative scaling technique in which a respondent is presented with two objects at a time and asked to select one object according to some criterion. The data obtained are ordinal in nature
Examples:
Which of the following was the more important in making you decide not to buy the plough?
· The plough was too expensive
· It proved too difficult to transport
In ‘paired comparisons’ every factor has to be paired with every other factor in turn. However, only one pair is ever put to the farmer at any one time.
Forced Choice:
The forced choice enables respondents to rank objects relative to one another, among the alternatives provided. This is easier for the respondents, particularly if the number of choices to be ranked is limited in number.
Example:
· Rank the following magazines that you would like to subscribe to in the order of preference, assigning 1 to the most preferred choice and 5 to the least preferred.
Fortune —
Playboy —
Time —
People —
Prevention —
Comparative Scaling:
Comparative rating scale, as the name suggests, expects respondents to answer a particular question in terms of comparison, i.e. on the basis of relative measurement or keeping other organizations/products/features as a reference.
Example:
Respondent is asked to rate sweet shop ‘X’ in comparison to sweet shop ‘Y’ in Kochi:
