Balanced incomplete block designs: selected business-related applications and usage caveats

Abstract

Whenever respondents must rank-order a large number of items and/or the reliability of their rankings may be questionable, balanced incomplete block designs (BIBDs) represent a more effective means for doing so than either complete rankings or paired comparisons for business and marketing researchers. By providing a type of balancing and replication across items and respondents, BIBDs significantly reduce the number of subjective evaluations each individual must make. But, at the same time, BIBDs allow a limited number of respondents as a group to rank many items. This balancing and replication in BIBDs also reduces standard deviation, which increases the precision of a study. BIBDs, therefore, can improve response rates as well as increase the accuracy and reliability of the data collected. After discussing the general nature of BIBDs and statistical techniques for analyzing preference data collected by BIBDs, three business-related applications are presented to illustrate the benefits of BIBDs. Next, caveats concerning the use of BIBDs are presented. In the last section, advantages of BIBDs are discussed.