The World’s and America’s Most Admired Companies
The value of the World’s Most Admired Companies rankings, as with Fortune ‘s list of America’s most admired, lies in their having been bestowed by the people who are closest to the action: senior executives and outside directors in each industry, and financial analysts who are in a position to study and compare the competitors in each field. Fortune asked them to rate companies on the eight criteria used to rank America’s most admired innovative ness, overall quality of management, value as a long-term investment, responsibility to the community and the environment, ability to attract and keep talented people, quality of products or services, financial soundness. and wise use of corporate assets. For global ranking, Fortune added another criterion to reflect international scope: a company’s effectiveness in doing business globally. A company’s overall ranking is based on the average of the scores of all criteria attributes. The 2008 top two World’s Most Admired Companies were Apple and General Electric, in that order. The 2008 America’s Most Admired Companies were:
In this example, the ID alphabets used to identify the companies represent a\nomlnal scale. Thus, “E” denotes Procter & Gamble and “P’ refers to FedEx. The ranks represent an ordinal scale. Thus, Johnson & Johnson, ranked 7. received higher evaluations than Target, ranked 8. The company score, the average rating on all the criteria attributes, represents an interval scale. These scores are IIDt shown in the table. Finally. the annual revenue for these companies. also not shown, represents a ratio scale
Measurement and Scaling
Measurement means assigning numbers or other symbols to characteristics of objects according to certain prespecified rules.2 Note that what we measure is not the object, but some characteristic of it. Thus, we do not measure consumers-only their perceptions, attitudes, preferences, or other relevant characteristics. In marketing research, numbers are usually assigned for one of two
reasons. First, numbers permit statistical analysis of the resulting data. Second, numbers facilitate the communication of measurement rules and results
Scaling may be considered an extension of measurement. Scaling involves creating a continuum upon which measured objects are located. To illustrate, consider a scale from 1 to 100 for locating consumers according to the characteristic “attitude toward department stores.” Each respondent is assigned a number from I to 100 indicating the degree of (un) favorableness, with 1 = extremely unfavorable, and 100 = extremely favorable. Measurement is the actual assignment of a number from 1 to 100 to each respondent. Scaling is the process of placing the respondents on a continuum with respect to their attitude toward department stores. In the opening example of most admired companies, the assignment of numbers to reflect the annual revenue was an example of measurement. The placement of individual companies on the annual revenue continuum was scaling.
Scale Characteristics and Levelsof Measurement
All the scales that we use in marketing research can be described in terms of four basic characteristics. These characteristics are description, order, distance, and origin, and together they define the level of measurement of a scale. The level of measurement denotes what properties of an object the scale is measuring or not measuring. An understanding of the scale characteristics is fundamental to understanding the primary type of scales
By description, we mean the unique labels or descriptors that are used to designate each value of the scale. Some examples of descriptors are as follows: 1. Female, 2. Male; I = Strongly disagree,2 = Disagree, 3 = Neither agree nor disagree, 4 = Agree, and 5 = Strongly agree; and the number of dollars eamed annually by a household. To amplify, Female and Male are unique descriptors used to describe values I and 2 of the gender scale. It is important to remember that all scales possess this characteristic of description. Thus, all scales have unique labels or descriptors that are used to define the scale values or response options
By order, we mean the relative sizes or positions of the descriptors. There are no absolute values associated with order, only relative values. Order is denoted by descriptors such as “greater than,” “less than,” and “equal to.” For example, a respondent’s preference for three brands of athletic shoes is expressed by the following order, with the most preferred brand being listed first and the least preferred brand last
The characteristic of distance means that absolute differences between the scale descriptors are known and may be expressed in units. A five-person household has one person more than a fourperson household. which in turn has one person more than a three-person household. Thus. the following scale possesses the distance characteristic.
Number of persons living in your household__________________
Notice. that a scale that has distance also has order. We know that a five-person household is greater than the four-person household in terms of the number of persons living in the household. Likewise. a three-person household is less than a four-person household. Thus. distance implies order but the reverse may not be true
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 I and the experimental group as group 2. The classes are mutually exclusive and collectively exhaustive. The objects in each class are viewed as equivalent with respect to the characteristic represented by the nominal number. All objects in the same class have the same number and no two classes have the same number. However, a nominal scale need not involve the assignment of numbers; alphabets or symbols could be assigned as well. In the opening example, alphabets were assigned to denote specific companies.
The numbers in a nominal scale do not reflect the amount of the characteristic possessed by the objects. For example, a high Social Security number does not imply that the person is in some way superior to those with lower Social Security numbers or vice versa. The same applies to numbers assigned to classes. The only permissible operation on the numbers in a nominal scale is counting. Only a limited number of statistics, all of which are based on frequency counts, are permissible. These include percentages, mode, chi-square, and binomial tests (see Chapter 15). It is not meaningful to compute an average Social Security number, the average sex of the respondents in a survey, or the number assigned to an average department store, as in the following example