Another rating scale used quite often in marketing research projects is the semantic differential scale. This type of scale is unique in its use of bipolar adjectives and adverbs (good/bad, like/dislike, competitive/noncompetitive, helpful/unhelpful, high quality/low quality, dependable/undependable) as the endpoints of a symmetrical continuum. Typically there will be one object and a related set of factors (or attributes), each with its own set of bipolar adjectives to measure either a cognitive or an affective element. Because the individual scale descriptors are not identified, each bipolar scale appears to be a continuum. In most cases, semantic differential scales will use between five and seven scale descriptors, though only the endpoints are identified. Respondents are asked to select the point on the continuum that expresses their thoughts or feelings about the given object.
In most cases a semantic differential scale will use an odd number of scale points, thus creating a so-called neutral response that symmetrically divides the positive and negative poles into two equal parts. An interpretive problem that arises with an odd-number scale point format comes from the natural neutral response in the middle of the scale. A neutral response has little or no diagnostic value to researchers or decision makers. Sometimes it is interpreted as meaning “no opinion,” “don’t know,” “neither/nor,” or “average.” None of these interpretations give much information to researchers. To overcome this problem, researchers can use an even-point (or forced-choice) format and incorporate a “not applicable” response out to the side of the bipolar scale.
A semantic differential scale is one of the few attitudinal scales that enable researchers to collect both cognitive and affective data for any given factor. But both types of data cannot be collected at the same time. For a given factor, a bipolar scale can be designed to capture either a person’s feelings or cognitive beliefs. Although some researchers believe a semantic differential scale can be used to measure a person’s complete attitude about an object or behavior, this scale type is best for identifying a “perceptual image profile” about the object or behavior of concern.
The actual design of a semantic differential scale can vary from situation to situation. To help understand the benefits and weaknesses associated with design differences, we present three different formats and discuss the pros and cons of each. In the first situation, researchers are interested in developing a credibility scale that can be used by Nike to assess the credibility of Tiger Woods as a spokesperson in TV or print advertisements for Nike brands of personal grooming products. Researchers determine the credibility construct consists of three factors—(1) expertise, (2) trustworthiness, and (3) attractiveness—with each factor measured using a specific set of five bipolar scales (see Exhibit 12.3).
Randomization of Positive and Negative Pole Descriptors
While the semantic differential scale format in Exhibit 12.3 appears to be correctly designed, there are several technical problems that can create response bias. First, notice that all the positive pole descriptors are arranged on the left side of each scale and the negative pole descriptors are all on the right side. This approach can cause a halo effect bias.4 That is, it tends to lead respondents to react more favorably to the positive poles on the left side than to the negative poles on the right side. To prevent this problem, researchers should randomly mix the positions of the positive and negative pole descriptors.
Lack of Extreme Magnitude Expressed in the Pole Descriptors
A second response problem with the scale format displayed in Exhibit 12.3 is that the descriptors at the ends of each scale do not express the extreme intensity associated with end poles. Respondents are asked to check one of seven possible lines to express their opinion, but only the two end lines are given narrative meaning. Researchers can only guess how respondents are interpreting the other positions between the two endpoints. Consider, for example, the “dependable/ undependable” scale for the trustworthiness dimension. Notice that the extreme left scale position represents “dependable” and the extreme right scale position represents “undependable.” Because dependable and undependable are natural dichotomous phrase descriptors, the scale design does not allow for any significant magnitudes to exist between them. The logical question is what the other five scale positions represent, which in turn raises the question of whether or not the scale truly is a continuum ranging from dependable to undependable. This problem can be corrected by attaching a narratively expressed extreme magnitude to the bipolar descriptors (“extremely” or “quite” dependable, and “extremely” or “quite” undependable).
Use of Nonbipolar Descriptors to Represent the Poles
A third response problem that occurs in designing semantic differential scales relates to the inappropriate narrative expressions of the scale descriptors. In a good semantic differential scale design, the individual scales should be truly bipolar so that a symmetrical scale can be designed. Sometimes researchers will express the negative pole in such a way that the positive one is not really its opposite. This creates a skewed scale design that is difficult for respondents to interpret correctly.
Consider the “expert/not an expert” scale in the “expertise” dimension in Exhibit 12.3. While the scale is dichotomous, the words “not an expert” do not allow respondents to interpret any of the other scale points as being relative magnitudes of that phrase. Other than the one endpoint described as “not an expert,” all the other scale points would have to represent some intensity of “expert,” thus creating an unbalanced, skewed scale toward the positive pole. In other words, interpreting “not an expert” as really meaning “extremely” or “quite” not an expert makes little or no diagnostic sense. Researchers must be careful when selecting bipolar descriptors to make sure that the words or phrases are truly extremely bipolar in nature and that they allow for creating symmetrically balanced scale designs. For example, researchers could use pole descriptors such as “complete expert” and “complete novice” to correct the above-described scale point descriptor problems.
Matching Standardized Intensity Descriptors to Pole Descriptors
The scale design used by Bank of America for a bank image study in Exhibit 12.4 eliminates the three problems identified in the example in Exhibit 12.3, as well as a fourth—it gives narrative expression to the intensity level of each scale point. Notice that all the separate poles and scale points in between them are anchored by the same set of intensity descriptors (“very,” “moderately,” “slightly,” “neither one nor the other,” “slightly,” “moderately,” “very”). In using standardized intensity descriptors, however, researchers must be extra careful in determining the specific phrases for each pole—each phrase must fit the set of intensity descriptors in order for the scale points to make complete sense to respondents. Consider the “makes you feel at home/makes you feel uneasy” scale in Exhibit 12.4. The intensity descriptor of “very” does not make much sense when applied to that scale (“very makes you feel at home” or “very makes you feel uneasy”). Thus, including standardized intensity descriptors in a semantic differential scale design may force researchers to limit the types of bipolar phrases used to describe or evaluate the object or behavior of concern. This can only raise questions about the appropriateness of the data collected using this type of scale design.
The fundamentals can help researchers develop customized scales to collect attitudinal or behavioral data. To illustrate this point, Exhibit 12.5 shows a semantic differential scale used by Midas Auto Systems Experts to collect attitudinal data about the performance of Midas. Notice that each of the 15 different features that make up Midas’s service profile has its own bipolar scale communicating the intensity level for the positive and negative poles. This reduces the possibility that respondents will misunderstand the scale.
Exhibit 12.5 also illustrates the use of an “NA”—not applicable—response as a replacement for the more traditional mid-scale neutral response. After the data are collected from this scale format, researchers can calculate aggregate mean values for each of the 15 features, plot those mean values on each of their respective scale lines, and graphically display the results using “profile” lines. The result is an overall profile that depicts Midas’s service performance patterns (see Exhibit 12.6). In addition, researchers can use the same scale and collect data on several competing automobile service providers (Firestone Car Care, Sears Auto Center), then show each of the semantic differential profiles on one display.