Christie H. Paksoy

Analysis of covariance for the removal of temporal effects in experiments with serial treatments

This research demonstrates the value of analysis of covariance for removing temporal effects from data collected through a retail experiment in which treatments are applied sequentially in a single store with rest periods interposed between treatments. Time series factors which were significant at the 0.05 level in a stepwise, dummy variable, multiple regression analysis became covariates in the analysis of variance models for both the treatment week data and the rest week data of each experimental product. For three of the four experimental products, the regression analysis revealed time series factors which may have affected the experimental treatments. For two of the experimental products, time series factors adversely affected the traditional ANOVA models. However, the application of analysis of covariance successfully removed the effects of these factors from the ANOVA models.

Replicating the Effect of Advertised Specials at Regular Price on Food Shopper Price Evaluation

Abstract This study verifies a previous finding that food shoppers can correctly identify the advertised price level for items featured at the regular price in the context of a newspaper ad. Morever, advertising regular-priced items in prominent positions did not materially affect their price accuracy scores.

Life-Style Analysis of Major Bank Credit Card Users

While life-style analysis appears to be a major tool in segmenting the bank credit card market, few studies have considered the multidimensional nature of the life-style variables which are frequently employed to characterize bank credit card users. In an attempt to overcome this problem, principal axis factor analysis, combined with a varimax rotation procedure, was used to identify the underlying life-style dimensions. Once these life-style dimensions were established factor scores were used as the predictor variables in developing bank credit card users from nonusers. The results of the study indicated that a general credit usage dimension and to a lesser degree a fashion consciousness dimension were most important in differentiating between users and nonusers of bank credit cards.

Older Female Apparel Consumers: Have Retailers Overlooked This Market Segment?

The graying of America has led to an increasing number of women aged 55 and older who have considerable buying power and an interest in consuming women’s apparel. While several studies, reported herein, have examined older women’s attitudes toward fashion and their perception of retailer neglect, this study examines retailers’ current perceptions of older women’s shopping behavior and their marketing strategies used to attract this growing segment. Managers from retail stores carrying women’s apparel located in a major metropolitan area were interviewed. This study found that while retailers believed that older women apparel shoppers represent an important market segment with special problems, these respondents felt that these women purchased fewer clothes than other segments, and, therefore, no changes were needed in the retailing mix to better serve this age group.

The Use of Blacks in Magazine Advertising: Some Changes in the 1970 to 1980 Period

The black consumer is becoming increasingly important to marketers of consumer products. This importance can be seen in increases in numbers of black consumers as well as in increases in their discretionary purchasing power. To determine if these increases are resulting in greater use of black models in advertisements appearing in mass circulation magazines, a study was conducted on print media for the years 1970, 1975 and 1980. Additional issues examined in the study were the roles depicted by blacks in subject ads, and the products with which they were associated. The findings indicate that although blacks are now portrayed more frequently than in the past, marketers continue to underplay the significance of this important consumer segment.

An international trade model to capture linkages among supply-constrained economies

Abstract The development of a countrys domestic and international markets depends on its own actions as much as on those of its trading partners. The study of market linkages is thus vital for policy making. Borrowing from the conceptual framework of Leontiefs input-output analysis and from the national accounts equation, this paper presents a new model to calculate multilateral trade multipliers while minimizing data requirements. The novelty of the approach consists in the column-wise (supply-oriented) normalization of trade as opposed to the row-wise (demand-oriented) normalization that prevails in the literature. The explanatory power of the model has been successfully tested on data that refer to 1973–1974. Divergence from reality inevitably reflects the great fluidity that characterized trade during that period. Although most successful when applied to trade among supply-oriented economies (such as those of socialist or developing countries), at present empirical tests have been run only for a handful of OECD and OPEC countries.