Be forewarned these exercises usually make monsters out of


Case 3.7 Critiquing Questionnaires is on pages 274 – 279. Using questionnaire information in the text and gathered from outside sources, develop the strengths and weaknesses of the surveys in Figures 3.7.4 through 3.7.7.

The paper must be two to three pages in length and formatted according to APA style. You must use at least two scholarly resources other than the textbook to support your claims and sub-claims.

Critiquing Questionnaires

Be forewarned! These exercises usually make \monsters" out of otherwise meek business school students. Once you learn to critique a questionnaire, you’ll never be able to look at another survey in quite the same way.

Instead of answering the marketing researcher’s questions, you’ll be looking at the question thinking, I could have worded that better!" That’s okay with us—it’s a good measure of your knowledge!

So, to get you started, take a look at the following real surveys (these are all \real," but we’ve changed the brand names to protect the incompetent).

Figure 3.7.1 was a postcard-sized survey. You see the front. On the back was the address of the office for ease of the customer return (though it was not stamped).

What are the survey’s strengths? It’s short, and obviously so, so consumers know immediately that filling out the survey won’t take too much of their time.

Short surveys enhance response rates. ! Better response rates mean more representative samples.

In addition, a number of different attributes are assessed, to enhance the multidimensionality of the ser- vice assessment. There is an open-ended section so that the consumer may say whatever is on his/her mind, whether anticipated by the rating scales of quality, timeliness, etc., or not.

What are the survey’s weaknesses? The trade-off on length is that the survey will yield little information. Further, if any of the features is deemed weak, are any of the scales precise enough to diagnose how to remedy the service? A complaint about marketing research that you always want to avoid is, We can’t do anything on the basis of these data."

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