Purpose -The purpose of the paper is to examine the relationship between two age cohorts within the baby boomer group, younger baby boomers (born between 1956-1965) and older baby boomers (born between 1946-1955), based on various behavioral variables. It is postulated that, even though this group is exceedingly large in number, there are more similarities than differences among its younger and older members. Design/methodology/approach -The study sample was a convenience sample and consisted of 295 respondents who were in the 40-58 age category. A questionnaire was administered with scales that were well established and that have been used in previous research. Findings -With the exception of cognitive age, there were no significant differences between younger and older baby boomers regarding a large number of salient behavioral variables. This conclusion suggests that marketers use caution when applying the widely accepted age segmentation strategy of splitting baby boomers into younger and older boomers. Originality/value -The results of this study caution the marketer in further dividing the baby boomers group based on cohort segmentation. The results of this study suggest that cohort segmentation is a viable beginning for dividing consumers into groups, but that other demographic and/or psychographic methods need to be considered in subsequent segmentation efforts for baby boomers.

This paper offers support that those students who felt they had stronger reasons for committing unethical academic behaviors are more likely to report committing academic dishonesty than those who felt they had weaker reasons for unethical academic behaviors.  This relationship held for all four categories of academic dishonesty:  cheating (on tests), seeking outside help, plagiarism (on papers), and E-cheating (electronic cheating on tests).  This suggests that students are rationalizing their academic dishonest behaviors and those students who feel they have stronger reasons for committing academic dishonesty are more likely to be academically dishonest.

The FDA has only focused upon the physical safety of cosmetics and has ignored the significant reasonability of advertising claims. As such, the present article is intended to examine/ascertain the extent to which cosmetics claims contain deceptive content in fashion ads. Through a content analysis, the study reported herein revealed that cosmetics claims were not evenly distributed. To that end, the preponderance of the claims appeared to be described primarily by three categories (scientific, performance and subjective). The results also showed that more cosmetics claims were classified as deceptive than were deemed as acceptable. Close examination of these trends revealed that, for instance, most superiority claims were categorized as false, whereas scientific claims tended to be classified as vague or as omitting important information. Furthermore, performance claims were likely to be viewed as vague and endorsement claims were seen to be acceptable. The study concludes with practical and public policy suggestions that need to be addressed by advertisers and the FDA.

No abstract

The online administration of student evaluations has its shortcomings, including low participation, or low response rates, and bias. This study examines nonresponse bias in online student evaluations of instruction, that is, the differences between those students who complete online evaluations and those who decide not to complete them. It builds on the work of Estelami that revealed a response bias based on the timing in which the evaluations were completed, that is, differences in early evaluations versus later evaluations. In contrast, this study examines the demographic variables that have contributed to nonresponse bias in online student evaluations, namely gender, grade point average, and ethnicity. It also examines multiple psychographic variables that may contribute to nonresponse bias: time poverty, complaining behavior, and technology savviness. The study utilized t tests and logistic regression (logit analysis) to analyze the data collected from undergraduate business students. This study found that there are significant differences between those who complete online student evaluations and those who do not. Implications for academic administrators are discussed.