Measurement & Scaling Techniques (Part 2)
Measurement scales
The various types of scales
used in marketing research fall into two broad categories: comparative and non
comparative. In comparative scaling, the respondent is asked to compare one
brand or product against another. With non comparative scaling respondents need
only evaluate a single product or brand. Their evaluation is independent of the
other product and/or brands which the marketing researcher is studying.
Non comparative scaling is
frequently referred to as monodic scaling and this is the more widely used type
of scale in commercial marketing research studies.
# Comparative scales1.
Paired Comparison
2.
Rank order
3.
Constant sum
# Non Comparative scales
1. Continuous rating scale
2.
Itemized rating scale
a. Likert scale
b. Semantic differential
scale
c. Stapel scale
Paired Comparison Scale:
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.
For example, there are four types of cold
drinks - Coke, Pepsi, Sprite, and Limca. The
respondents can prefer Pepsi to Coke or Coke to Sprite, etc.
Example 2 - Suppose the organisation responsible wants to
know which factors is foremost in the farmer's mind. It may well be the case
that if those factors that are most important to the farmer than the others,
being of a relatively minor nature, will cease to prevent widespread adoption.
The alternatives are to abandon the product's re-development or to completely
re-design it which is not only expensive and time-consuming, but may well be
subject to a new set of objections.
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 so that
with 5 factors, as in this example, there are 10 pairs
Example:
Rank Order Scale:
This is another
type of comparative scaling technique in which respondents are presented with
several items simultaneously and asked to rank them in the order of priority.
This is an ordinal scale that describes the favored and unfavored objects, but
does not reveal the distance between the objects.
The resultant
data in rank order is ordinal data. This yields better results when direct comparisons
are required between the given objects.
The major
disadvantage of this technique is that only ordinal data can be generated.
Constant Sum
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. Respondents might be asked to divide a constant sum to indicate the
relative importance of the attributes.
The advantage of
this technique is saving time. However, main disadvantages are the
respondents may allocate more or fewer points than those specified. The second
problem is respondents might be confused.
Non Comparative Scaling Techniques
In
non-comparative scaling respondents need only evaluate a single object. Their
evaluation is independent of the other object which the researcher is studying.
The
non-comparative scaling techniques can be further divided into:
(a)Continuous
Rating Scale, and (b) Itemized Rating Scale.
Continuous
Rating Scales:
It is
very simple and highly useful. In continuous rating scale, the respondent’s
rate the objects by placing a mark at the appropriate position on a
continuous line that runs from one extreme of the criterion variable to the
other.
Example:
Question:
How would you rate the TV advertisement as a guide for buying?
Itemized
Rating Scales:
Itemized
rating scale is a scale having numbers or brief descriptions associated with
each category. The categories are ordered in terms of scale position and the
respondents are required to select one of the limited number of categories that
best describes the product, brand, company, or product attribute being rated.
Itemized rating scales are widely used in marketing research.
Itemised
rating scales is further divided into three parts, namely
(a) Likert scale,
(b) Semantic Differential Scale, and
(c)
Stapel Scale.
The itemized
rating scales can be in the form of:
(a)
Graphic, (b) verbal, or (c) numeric
as shown below :
(a) Likert
Scale:
Likert, is extremely popular for
measuring attitudes, because, the method is simple to administer. With the
Likert scale, the respondents indicate their own attitudes by checking how
strongly they agree or disagree with carefully worded statements that range from
very positive to very negative towards the attitudinal object. Respondents
generally choose from five alternatives (say strongly agree, agree, neither
agree nor disagree, disagree, strongly disagree).
A
Likert scale may include a number of items or statements. Disadvantage of
Likert Scale is that it takes longer time to complete than other itemised
rating scales because respondents have to read each statement.
Despite the above disadvantages,
this scale has several advantages.
It is easy to construct, administer
and use.
(b) Semantic
Differential Scale:
This is a seven point rating scale
with end points associated with bipolar labels (such as good and bad, complex
and simple) that have semantic meaning. It can be used to find whether a
respondent has a positive or negative attitude towards an object. It has been
widely used in comparing brands, products and company images. It has also been
used to develop advertising and promotion strategies and in a new product development
study.
The
Stapel scale was originally developed to measure the direction and intensity of an attitude simultaneously. Modern versions of the Stapel scale place
a single adjective as a substitute for the Semantic differential when it is
difficult to create pairs of bipolar adjectives. The modified Stapel scale
places a single adjective in the centre of an even number of numerical Values.
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