«RATIONAL AND INTUITIVE STYLES: COMMENSURABILITY ACROSS RESPONDENTS' CHARACTERISTICS' By: W. M. Taggart, Enzo Valenzi, Lori Zalka, and Kevin B. Lowe ...»
Finally, we note these results are not consistent with those of other studies. For instance, briefly consider the gender characteristic. Intuition in Decision Making: AIM (Agor, 1992) uses 12 items from the Myers-Briggs Type Indicator's (Briggs & Myers, 1993) Intuition scale to assess intuitive orientation. The selected items are used to score an individual on a range from a maximum of 12 for thinking representing a highly rational orientation through 6 for thinking and 6 for intuitive representing a balance to a maximum of 12 for intuitive representing a highly intuitive orientation. In a study of 3000 managers, Agor found that "Women consistently scored higher on the intuition scale than men in every group sampled" (Agor, 1986, p. 18).
Parikh, et al. (1994) surveyed 1300 senior and top managers in nine industrialized nations. They included both an objective scale using 10 pairs of terms that represent the intuition-analysis dichotomy and a subjective rating where the subjects responded on a 5-point scale to the question: "How do you rate yourself on intuition?" (Parikh, et al., 1994, pp. 52-57). They found that the proportions of women rating high on both the objective and self-rating scales were significantly greater than of men.
In contrast to the Agor and Parikh, et al. results, Allinson and Hayes (1996) found that women scored higher on analysis and lower on intuition than men in four samples totaling 716 respondents. (This result was not found in one sample of 130 respondents.) Their Cognitive Style Index is composed of 38 items scored on a 3-point scale of 0 (false), 1 (uncertain), and 2 (true) such that the closer to the maximum score of 76, the more analytical and closer to the minimum of 0, the more intuitive the respondent.
Kirton (1994) reported similar results using the Kirton Adaption-Innovation Inventory (1987), a measure with 32 items each of which is scored on a scale from 1 to 5 giving a theoretical range of scores from 32 to 160.
Lower values are associated with the adaptor style (a rational orientation) and higher with the innovator styles (an intuitive orientation). Kirton (1994, p. 54) found that "females tend, on the average, to be more adaptive than males." Since Agor and Parikh, et al. found that women scored higher, and Allinson and Hayes, and Kirton found that men scored higher on in tuition-related scales, further theoretical and empirical study is needed to examine this disparity in results.
We conclude with several implications of our study. Scales such as those for the Personal Style Inventory which delineate the intuitive-rational dimensions in greater detail may more likely display commensurability across characteristics than more aggregate scales. More refined scales may assess constructs closer to the personality core. The closer to the essence of individual styles, the closer we may be to more commensurable dimensions of style. These disparate results highlight the need for further research on commensurability across respondents' characteristics. Within the limitations noted earlier, the results suggest that separate norms for the Personal Style Inventory on these six characteristics are not needed. This study needs to be extended to more representative samples and to explore other characteristics that might be relevant such as education and cultural background.
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APPENDIXThe first data column in Table Al (pp. 32-33) lists the frequencies for each group for each characteristic. The ns range from 132 for ethnic group (discussed in the next paragraph) to 493 for gender. "Other" and "missing" cases account for the difference between the total sample size of 495 and the smaller sample size for each characteristic: gender n=493 (missing=2), age n=449 (missing =46), ethnic group n=132 (other =5, missing =23), birth country n=374 (other =24, missing = 97), industry n=401 (other =5, missing = 89), and occupation n=358 (other =121, missing =16). "Other" represents groups for which subsample sizes were insufficient or too unequal to include in the analysis. Table Al also lists the means and standard deviations for each PSI variable for each group and for each characteristic as a whole.
Due to the limited number of noncaucasian subjects in the Australian, English, and New Zealand groups, these countries were excluded from the analysis for ethnic group. Seven ethnic classifications were used in the data collection: African American, Hispanic, American Indian, Asian, Caucasian, Malayan, and Other. However, the small United States frequencies for the American Indian (n=0), Asian (n=4), and Malayan (n=0) groups precluded meaningful interpretation. For further analysis, we eliminated these groups as well as the Other classification due to its small sample size (n=1) and the ambiguity of interpreting the group classification.
The respondents' work organizations were classified using the four digit codes from the Standard Industrial Classification Manual (U.S. Department of Commerce, 1972). These were summarized and counted into seven categories: Manufacturing (2000-3999), Transportation (4000-4999), Trade (50005999), Finance (6000-6999), Services (7000-8999), Public Administration (9000-9999), and Other (0000-1999).
Respondents' position titles were classified using the nine digit codes from the Dictionary of Occupational Titles (U.S. Department of Labor, 1977). Nine groups were consolidated based on similar types and levels of responsibility. The five larger groups were of sufficient size to identify separately in the analysis: 18 Engineers (019-061-010); 70 Trainers (166-227-010), Training Managers (166-167-010), and Consultants (189-167-010);
94 Supervisors (169-167-012) and Project Managers (189-117-030); 149 Managers (189-167-022) and Vice Presidents (189-117-034); and 27 Owner-Managers (189-167-024). Occupations for the other 121 cases were not considered sufficiently similar in responsibility or numerous in frequency for inclusion in the analysis.