Business Research Methods BUSINESS RESEARCH DESIGN UNIT SIX BBA 3843 Measurement and Scaling Techniques Measurement: Task of assigning numbers to characteristics of objects being investigated Variable: A characteristic of an object that can be measured is called a variable e.g. age, level of education Scaling: A criteria in which a characteristic is measured against e.g. age in years Four types of measurement Nominal Ordinal Interval Ratio Measurement and Scaling Techniques: Nominal scale A nominal scale is a figurative labelling scheme(plan)in which the numbers serve only as labels for identifying and classifying objects. For example, the numbers assigned to the respondents in a study constitute a nominal scale, thus a female respondent may be assigned a number 1 and a male respondent 2. When a nominal scale is used for the purpose of identification, there is a strict one-to-one correspondence between the numbers and the objects. Each number is assigned to only one object, and each object has only one number assigned to it. Common examples include student registration numbers at their college or university and numbers assigned to football players or jockeys in a horse race. In marketing research, nominal scales are used for identifying respondents, brands, attributes, banks and other objects. When used for classification purposes, the nominally scaled numbers serve as labels for classes or categories. For example, you might classify the control group as group 1 and the experimental group as group 2. The classes are mutually exclusive and collectively exhaustive. Measurement and Scaling Techniques: Ordinal Scale An ordinal scale is a ranking scale in which numbers are assigned to objects to indicate the relative extent to which the objects possess some characteristic. An ordinal scale allows you to determine whether an object has more or less of a characteristic than some other object, but not how much more or less. Thus, an ordinal scale indicates relative position, not the magnitude of the differences between the objects. The object ranked first has more of the characteristic as compared with the object ranked second, but whether the object ranked second is a close second or a poor second is not known. Common examples of ordinal scales include quality rankings, rankings of teams in a tournament and occupational status. In marketing research, ordinal scales are used to measure relative attitudes, opinions, perceptions and preferences. Measurements of this type include ‘greater than’ or ‘less than’ judgments from the respondents. Measurement and Scaling Techniques: Interval Scale In an interval scale, numerically equal distances on the scale represent equal values in the characteristic being measured because it is metric. An interval scale contains all the information of an ordinal scale, but it also allows you to compare the differences between objects. The difference between any two scale values is identical to the difference between any other two adjacent values of an interval scale. There is a constant or equal interval between scale values. The difference between 1 and 2 is the same as the difference between 2 and 3, which is the same as the difference between 5 and 6. A common example in everyday life is a temperature scale. In marketing research, attitudinal data obtained from rating scales are often treated as interval data. Interval is a metric scale, so it is possible to calculate the arithmetical means of interval scale. Interval scale can be five, seven or nine-level scale. Measurement and Scaling Techniques: Ratio Scale A ratio scale possesses all the properties of the nominal, ordinal and interval scales, and in addition, an absolute zero point. Thus, in ratio scales we can identify or classify objects, rank the objects, and compare intervals or differences. It is also meaningful to compute ratios of scale values. In marketing, sales, costs, market share and number of customers are variables measured on a ratio scale. In Economics income, inflation rate, exchange rate, population, income per capita etc. are good examples of ratio scale. Division by non-zero value is meaningful operation in ratio scale. Examples: Mass, length, time, Height, weight, age, income, expenditure are ratio scale variables. Measurement and Scaling Techniques Attitude measurement: Likert’s Scale This is a widely used rating scale that requires the respondents to indicate a degree of agreement or disagreement with each of a series of statements about the stimulus objects. Typically, each scale item has five response categories, ranging from ‘strongly disagree’ to ‘strongly agree’. Likert scale is not a kind of question. It is a scale which measures an attitude or behavior. Attitude measurement: Semantic Differential Scale The semantic differential is a seven-point rating scale with end points associated with bipolar labels that have semantic meaning. In a typical application, respondents rate objects on a number of itemized, seven-point rating scales bounded at each end by one of two bipolar adjectives, such as ‘cold’ and ‘warm’. Generally, positive adjectives are placed at left and the negative adjectives at right and the numbers are given from 7 to 1 in the same order Thurstone-equal appearing interval scale This scale was developed by Robert Thurstone to approximate measurement in equal-appearing interval levels. Thurstone scale is defined as a unidimensional scale that is used to track respondent’s behavior, attitude or feeling towards a subject. This scale consists of statements about a particular issue or topic where each statement has a numerical value that indicates the respondents attitude towards the topic as favorable or unfavorable. Respondents indicate the statements that they agree with, and an average is computed. A mean score of the agreements or disagreements is calculated as the attitude of the respondent towards the topic. The first step of scale construction is to select a sufficient number of statements that relate to the variable being measured The next step would be to have a panel of judges rate each item on a scale of 1 to 11 where 1 is the least favorable attitude towards the common vector – diversity hiring and 11 is an extremely favorable attitude. It is important to note that the judges are required to rate each option and not agree or disagree with them. The data collected from all judges is to then be analyzed to draw up a table with the mean or median values in the ascending order. Using median or mean is a personal choice and the options throw up accurate results in the use of either. Thurstone-equal appearing interval scale The data has to be sorted on the basis of smallest to largest median/mean and the IQR’s for each median/mean have to be in a descending order. Selecting final variables or options In scale construction by using Thurstone's 'Equal Appearing Interval Scale' method, at first the opinion of judges are sought and after that the statements are administered to the final respondents. Respondents only make their choices based on the given continuum by the researcher. This technique produces quantifiable data about the measures of strength of the respondents' opinions/ feelings. This method is widely used for psychometric scale construction and considered one of the most commonly used method for attitude scale construction. MDS – Multi dimensional scaling Multidimensional scaling (MDS) is a technique for visualizing distances between objects, where the distance is known between pairs of the objects. The input to multidimensional scaling is a distance matrix. The output is typically a two-dimensional scatterplot, where each of the objects is represented as a point. To illustrate the basic mechanics of MDS it is useful to start with a very simple example. The distance matrix below shows the distance, in kilometers, between four Australian cities. From these distances alone, we can reconstruct the map (shown below) which shows the distance between the cities.
