Experiments and quasi-experiments: methods for evaluating marketing options; hospitality managers could achieve greater success with marketing initiatives using experiments or quasi-experiments to test those initiatives.

(25.) In other words, if the unit being randomly assigned is days or restaurants then the outcome measure should be a daily or restaurant average. There are statistical techniques that allow researchers to correctly analyze experiments where the units of random assignment and the units of outcome measurement are different, but those are new and sophisticated statistical techniques that are likely to be beyond the typical executive or manager's ability to implement. Thus, we advise randomly assigning and measuring the same units.

(26.) See: Laura A. Branon and Amy E. McCabe. "Time-restricted Sales Appeals: The Importance of Offering Real Value," Cornell Hotel and Restaurant Administration Quarterly, Vol. 42, No. 4 (August-September 2001), pp. 47-52.

(27.) Rachel Kennedy and Andrew Ehrenberg, "There Is No Brand Segmentation," Marketing Research, Spring 2001, pp. 4-7.

(28.) Corliss L. Green, "Differential Responses to Retail Sales Promotion among African-American and Anglo-American Consumers," Journal of Retailing, Vol. 71 (1995), pp. 83-92.

(29.) See: Myers, op. cit.; and A.W. Wicker, "Attitudes versus Actions: The Relationship of Verbal and Overt Behavioral Responses to Attitude Objects," Journal of Social Issues, Vol. 25, pp. 41-78.

(30.) STEP measurement involves giving subjects a booklet that describes all the major competitors in a product category and instructs subjects to distribute ten stickers among the competing options to reflect the likelihood that the subjects would buy the products as described. Each product description is on a separate page of the booklet. Product descriptions include a brand name, a picture, a price and a summary of product attributes and benefits (taken from real promotional materials on that product). The number of STEP stickers a person gives a product is related to that persons subsequent purchase behavior. Furthermore, the average shares of STEP stickers products receive correlate at .92 with the products' actual market shares. See: Marder, op. cit.

RELATED ARTICLE: Glossary of Terms

Quasi-experiments: A class of common field-research techniques in which at least one treatment is manipulated and there is at least one comparison. The difference between quasi- and true experiments is that in quasi-experiments consumers are not randomly assigned to treatments.

Random assignment: Assignment of consumers to treatments in such a way that each consumer has an equal chance of getting each treatment.

True laboratory experiment: A true experiment conducted in a model of the real world (a lab). Laboratory experiments are useful in basic research in consumer behavior because they can identify and explain the general conditions that influence consumer choices. While laboratory experiments are high in internal validity, they tend to be low in external validity.

True field experiment: An experiment conducted in the real world. Field experiments use random assignment, but do not attempt to control all factors extraneous to the ones being manipulated. Field experiments are useful for answering applied hospitality marketing questions because they have high internal validity and high external validity.

Type-1 error: Concluding that the treatments being tested had an effect when they really did not.

Type-2 error: Concluding that the treatments being tested had no effect when they really did.--A.L. and M.L.

Adjusting Sample Size: A Temptation to Avoid

The procedure for deciding on a sample size described in the accompanying article is the correct method. However, the required sample sizes indicated by this method are usually large, and marketers often want to avoid the costs of working with such large samples. In those cases, marketers may be tempted to run an experiment with smaller sample sizes than the number recommended by standard procedure, analyze the results, and then add additional subjects if a practically meaningful but not statistically significant effect is found.

We advise against this two-step procedure for two reasons. First, the small initial sample sizes may result in chance reductions of the observed effect such that what is in reality a practically meaningful effect appears not to be so. In that case, marketers will not add subjects, and the statistical power needed to avoid this Type-2 error will not be available. Second, the decision to run the experiment with additional subjects only when there is a sizeable but not significant effect in the initial, small sample biases the final test with the larger sample and increases the probability of a Type-1 error. If marketers can afford the additional subjects required by the second step of this procedure, they should use that larger sample size in the first place.

Ann Lynn, Ph.D. is an assistant professor in the department of psychology at Ithaca College (alynn@ithaca.edu).

Michael Lynn, Ph.D. is an associate professor at the School of Hotel Administration at Cornell University (wml3@cornell.edu)