Holland's Vocational Preference Inventory and the Myers-Briggs Type Indicator as predictors of vocational choice among master's of business administration

Journal of Vocational

Behavior 29, 51-65 (1986)

Holland’s Vocational Preference inventory and the Myers-Briggs Type Indicator as Predictors of Vocational Choice among Master’s of Business Administration DAVID American

C.

MARTIN University

AND

KATHRYN University

M.

BARTOL

of Maryland

The ability of Holland’s Vocational Preference Inventory (VPI) and the MyersBriggs Type Indicator (MBTI) to predict student business concentration was tested with master’s in business administration students. The usefulness of Holland’s congruence notion in predicting student program completion also was assessed using R. Iachan’s (1984, Journal of Vocational Behavior, 24, 133-141) index of agreement to measure congruence between VP1 personality type and business concentration. Significant discriminant analysis results were obtained for both the VP1 and the MBTI as predictors of concentration area. Classification analyses supported the potential usefulness of the VP1 for counseling MBA students regarding concentration choice, but suggested limitations in the utility of the MBTI for this purpose. Canonical correlation of the VP1 and the MBTI indicated parallels between the measures on two dimensions. D 1986 Academic PRESS. II-C.

Despite their burgeoning numbers, relatively little research has focused on predicting vocational choices among business students, including those pursuing master’s degrees in business administration (MBA). Yet, the term business only vaguely profiles the vocational interests of such students. The reason is that business students typically also chose an area of Computer analyses for this project were supported through the facilities of the Computer Science Center of the University of Maryland. The authors are grateful to Arnold R. Spokane and Rebecca 0. Williams for helpful suggestions regarding this research. The authors, of course, bear full responsibility for the final outcome. Reprint requests should be sent to Dr. David C. Martin, Kogod College of Business Administration, American University, Washington, DC 20016. 51

OOOl-8791/86 $3.00 Copyright 0 1986 by Academic Press, Inc. All rights of reproduction in any form reserved.

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concentration from among several business specialties (finance, marketing, etc.). Their concentration choice then serves as a primary basis for the types of positions that they seek upon graduation and, therefore, more adequately defines their future career direction. Because the specialties within business are rather diverse, however, the choice of a concentration area may constitute a fairly difficult vocational decision. Unfortunately, theories and accompanying measures which hold some promise of facilitating such concentration choices among business students have not been adequately tested among specialties within business. Two theories with particular potential for predicting vocational preferences among business students have been provided by Holland (1973; 1985a) and by Jung (1921) and further developed by Myers (1962; Myers & McCaulley, 1985). The Holland theory includes a typology of six personality types which theoretically can be used to differentiate among specialties within business. The Myers approach, implemented through the Myers-Briggs Type Indicator (MBTI), has not been adequately tested as it relates to vocational choice, but it suggests that individuals in various business specializations can be distinguished by differences in four personality orientations identified by Jung (Myers & McCaulley, 1985). Holland’s

Theory

More specifically, Holland’s (1985a) theory views vocational interests as expressions of personality and argues that individuals make occupational choices which will place them in environments that are compatible with their predominant personality characteristics. Accordingly, Holland has identified six major personality orientations and has classified many occupations according to the types of environments they provide and the personality orientations with which they are most compatible. The hierarchy of an individual’s resemblance to the six personality orientations is known as an individual’s personality pattern, with the three strongest orientations constituting one’s main personality type. The six personality orientations, typically measured for research purposes using the Vocational Preference Inventory (VPI) developed by Holland (1978), are Realistic, Investigative, Artistic, Social, Enterprising, and Conventional. A large body of research provides strong support for the ability of Holland’s theory to distinguish among individuals in various college majors and occupations (Eberhardt & Muchinsky, 1984; Holland, 1985a; Osipow, 1983). However, few attempts have been made to test the applicability of the theory specifically to business students in various concentrations. In the most direct test among business students to date, Utz and Hartman (1978) found support for the ability of personality type as measured by the Self-Directed Search (SDS; Holland, 1979), a more limited self-administered version of the VPI, to distinguish between undergraduate

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accounting majors and those in management and marketing, but the measure failed to separate majors in the latter two categories. However, the use of the SDS and methodological limitations in the manner in which the comparisons were made precluded a full test of the potential predictive power of Holland’s theory. Hence a major purpose of this research is to directly test the ability of Holland’s typology to distinguish among areas of concentration for MBA students. One important aspect of Holland’s theory centers on the concept of congruence between personality type and one’s chosen occupational environment. Holland (1985a) argues that individuals are more successful when they operate in environments that are congruent with their personality type because such environments provide opportunities and rewards that are more compatible with their needs. Consequently, it might be expected that the more compatible the chosen concentration is with personality type, the more likely it is that the student will be successful in the particular academic program. Overall, there is limited support for the congruence notion in academic settings (Holland, 1985a; Spokane, 1985; Walsh, Spokane, & Mitchell, 1976). In a study close to the concerns here, Bruch and Krieshok (1981) found that freshman engineering students who were high investigative types were more likely to persist in required theoretical mathematics and science classes than students who were high realistic types whose personalities were incongruent with the environments of the required classes. One limitation with many congruence studies, however, is that they have focused mainly on relating congruence between personality and environment with affective responses at one point in time, rather than using the degree of congruence to predict important future outcomes (Spokane, 1985). In addition, congruence studies frequently have relied on rather rough measures of congruence, such as categorizing individuals based only on their single highest personality score or using the 6-point ZenerSchuelle Index of Agreement (Zener & Schuelle, 1976). More recently, Iachan (1984) has developed a 28-point index which is aimed at more adequately capturing the true degree of congruence between personality type and occupational environment. Therefore, a second purpose of this research is to use the Iachan Index to evaluate the extent to which congruence between personality type and chosen concentration is predictive of future student academic success. For purposes of this study, success is considered to be obtaining the MBA degree. Myers’ Approach

In addition to the Holland theory, a second approach based on Jung’s (1921) personality typology has been proposed as a differentiator among occupational specializations (Myers, 1962; Myers & McCaulley, 1985). Jung’s theory focuses on cognitive orientations and posits that individuals

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have basic preferences in the ways in which they perceive and judge that can be encapsulated in four basic dimensions. These dimensions are measured by the four indexes of the MBTI (Myers & McCaulley, 1985). The Extraversion-Introversion index reflects the extent to which individuals are oriented toward the outer world of people and things versus the inner world of concepts and ideas. The Sensing-Intuition index measures the extent to which the individual’s perceptions are likely to rely on direct use of the five senses to monitor concrete characteristics versus a more indirect unconscious process which relies more on ideas and abstractions. The Thinking-Feeling index reflects the extent to which the individual’s decision making relies on impersonally evaluating whether something is true or false versus on subjective feelings associated with personal values. The Judgment-Perception index measures the extent to which an individual adopts a judging attitude and aims to regulate and control his or her life versus being relatively open-minded and preferring to adapt to what happens. Although the MBTI has been commonly associated with cognitive approaches to problem solving (e.g., Hellriegel, Slocum, & Woodman, 1983), Myers (1962; Myers & McCaulley, 1985) also holds that these differences in psychological orientation are reflected in different types of occupations. Despite the fact that the vocational implications of Jung’s theory and the MBTI have not been extensively tested, there is limited support for the MBTI as a predictor of college majors (Goldschmid, 1967). Although Myers (1962) gives examples of occupations associated with different combinations of the Sensing-Intuition and Thinking-Feeling dimensions based on limited empirical evidence, the theoretical basis for placing particular business concentrations within particular categories has not been adequately outlined. More recently, Myers and McCaulley (1985) posit that the different psychological types within the Jungian typology are found in virtually all occupations; however, various occupations attract some types more than others. In arguments similar to those of Holland (1985a), they reason that serious mismatches between type and occupation may lead to lower motivation, whereas work is likely to be more satisfying and intrinsically motivating when it involves processes more closely related to one’s personality orientations. They further provide descriptive data for each Jungian dimension showing the percentages of individuals at each end of the continuum in various occupational samples. Although direct comparisons are not made, the data are suggestive of a potential for the Jungian typology to differentiate among business specialties. Thus, a third purpose of the current research is to explore the extent to which the personality orientations associated with the MBTI may underly various business concentrations at the MBA level. Not surprisingly, there also is some evidence that cognitive orientations may be related to Holland’s typology and there have been some recent

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efforts to more fully understand these relationships (Winchell, 1984). In fact, Holland (1985) notes that there may be an analogous relationship between his typology which grew out of the vocational literature and Jung’s formulation. Further exploration of a possible positive relationship between the two measures may lead to the identification of cognitive orientations underlying Holland’s theory. Thus, the final purpose of the present research is to evaluate the relationship between Holland’s VP1 and the MBTI. METHOD Subjects and Procedure

Subjects were 168 new MBA enrollees at a large Eastern state university over a 2-year period, who declared an MBA concentration in one of the following six areas: accounting, finance, information systems, management, management science/operations research, or marketing. The six concentration areas were chosen prior to data collection because they represent main functional concentrations commonly found in business schools. The 168 subjects were obtained by including study questionnaires in a packet of materials sent to all new MBA students just before they began their MBA program. Study questionnaires were sent to all students in order to obtain current areas of concentration. An accompanying letter asked the students to participate in a long-term study of predictors of career satisfaction among MBA students. After two follow-ups, 246 students had completed questionnaires, for a response rate of 82.3%. Data for respondents who indicated that they were undecided as to concentration or who indicated concentrations other than the designated six were then removed from the sample. Data for four students who met the area of concentration criterion for inclusion in the study had missing values for one or more variables and also were eliminated. The resulting study sample was 168, including 96 males and 72 females. The percentages of females in the concentration areas were as follows: accounting, 43.7; finance, 37.7; information systems, 46.9; management, 50.0; management science/operations research, 42.1; and marketing, 44.4. Measures

Preferences for the six Holland personality categories, Realistic, Investigative, Artistic, Social, Enterprising, and Conventional were measured using the Vocational Preference Inventory (Holland, 1978). The VP1 has been used extensively in vocational research and considerable favorable documentation exists regarding the validity and reliability of the measure (Holland, 1978, 1985a; Osipow, 1983). The VP1 contains 160 occupational titles, for which subjects indicate liking or not. Although subjects completed the entire inventory, only 84 of the job titles (14 for each personality category) are actually used to determine preferences. Scores for each of

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the six occupational personality scales were determined by summing the number of “like” responses on each of the respective scales for each individual. Scores on all six personality categories for each individual, encompassing the individual’s vocational preference pattern, were used to predict area of concentration. In order to determine congruence scores to test the congruence hypothesis associated with the Holland theory and successful completion of the MBA program, Holland’s three-letter codes were used. Each individual’s vocational type was characterized by a three-letter code which indicated the order of strength of the individual’s three strongest orientations (e.g., ESC for Enterprising, Social, and Conventional). Threeletter codes for each of the MBA concentration areas were determined from the three-letter codes associated with the most common jobs obtained by individuals in the concentration areas. The codes were obtained from the Dictionary of Holland Occupational Codes (Gottfredson, Holland, & Ogawa, 1982). The codes used for each of the concentration areas are as follows: Accounting, CES; Finance, CSI: Information Systems, IER; Management, ESC; Management Science/Operations Research, IRE; and Marketing, ESA. A congruence score for each individual was then obtained using the method developed recently by Iachan (1984) for determining the degree of match between the individual’s three-letter code and the three-letter code of his or her concentration area. Basically, the Iachan approach involves assigning a congruence score ranging from 0 to 28, depending both on the presence of and respective order of matching letters in the three-letter concentration code relative to the individual’s three-letter code obtained from scores on the VPI. The Myers-Briggs Type Indicator (Form GH; Myers, 1962) is a 126item forced choice questionnaire aimed at measuring the ExtraversionIntroversion, Sensing-Intuition, Thinking-Feeling, and Judgment-Perception dimensions described earlier. Although the MBTI has not been used extensively in vocational research, a recent review of literature related to the MBTI indicates that the measure demonstrates acceptable reliability levels and that there is evidence of its validity as a measure of Jung’s (1921) intended dimensions (Carlyn, 1977). In completing the MBTI, the respondent chooses between two or sometimes three forced choices per item. The choices are based on how the respondent usually feels or acts or, in some cases, on which alternative is more appealing. In scoring the instrument, point scores are first obtained by summing responses on subscales for each of the eight variables associated with the four dimensions of the MBTI. The numbers of items making up the variable subscales are as follows: Extraversion, 19; Introversion, 19; Sensing, 24; Intuition, 16; Thinking, 20; Feeling, 14; Judgment, 20; and Perception, 23. As is common with forced choice formats, some items

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are scored on more than one subscale, depending on subject responses. Based on a key provided with the MBTI, some responses on each of the subscales are given a double weighting and there are separate keys for females and males on the Thinking and Feeling subscales. After the point scores for the eight variables are obtained, differences are computed between the point scores for each pair of variables making up the MBTI dimensions. The respective differences are then converted to a preference score for each dimension using tables provided (a preference score for the Extraversion-Introversion dimension, etc.). The preference score indicates the strength of the preference, while the variable in the pair which has the largest point score indicates the direction of the preference. To obtain continuous scores for research purposes, each preference score is converted to a continuous score either by subtracting the preference score from or adding it to 100, depending on the direction of the preference. This conversion method yields a continuous score for each MBTI dimension, with 100 marking the midpoint of the continuum associated with the dimension. Thus, in the case of the Extraversion-Introversion subscale, for example, scores below 100 fall on the extraversion side of the continuum, while scores above 100 constitute the introversion side of the continuum. Further scoring details can be obtained from the MBTI manual (Myers & McCaulley, 1985). Data regarding successful completion of the MBA program were obtained from University records after the general cohort had graduated. A score of 2 was recorded for successful program completion and a 1 was given for failure to complete the program. Analyses

Discriminant analysis is a particularly useful means for assessing the ability of multiple test scores to classify individuals into categories or groups (Kerlinger & Pedhazur, 1973). Accordingly, discriminant analysis was used to evaluate the degree to which individual scores on the six dimensions of the VP1 were able to predict area of concentration. The extent to which congruence between Holland’s personality type and area of concentration was related to program completion was evaluated using correlational analysis. The relationship between MBTI scores and area of concentration also was evaluated with discriminant analysis. Finally, canonical correlation analysis was used to explore the relationship between Holland’s personality types as measured by the VP1 and the MyersBriggs Jungian types as measured by the MBTI. RESULTS

Means and standard deviations for the VP1 and MBTI subscales by area of concentration are shown in Table 1. In assessing Holland’s theory, discriminant analysis supported the ability of the VP1 to distinguish among

102.12 (25.35) 112.62 (24.27) 94.00 (17.95) 95.25 (24.97)

2.81 (3.73) 4.75 (4.07) 4.37 (4.30) 5.75 (2.84) 6.06 (2.98) 5.87 (4.42)

Accounting (N = 16)

Note. Standard deviations are in parentheses.

MBTI subscales ExtraversionIntroversion SensingIntuition ThinkingFeeling JudgmentPerception

Artistic

Enterprising

Conventional

Social

Investigative

VP1 subscales Realistic

VP1 and MBTI subscales

102.42 (24.72) 100.81 (29.27) 84.26 (20.57) 85.58 (26.24)

2.16 (2.83) 3.43 (4.00) 2.40 (2.89) 4.84 (2.83) 5.58 (3.32) 4.61 (3.93)

Finance (N = 61)

108.42 (21.88) 102.16 (25.33) 76.10 (19.39) 78.42 (20.70)

4.06 (3.63) 6.09 (4.51) 3.59 (3.59) 4.25 (2.95) 5.50 (3.44) 7.19 (4.04)

Information systems (N = 32)

Concentration

116.26 (20.30) 99.84 (23.82) 84.47 (24.77) %.16 (27.35)

4.95 (3.50)

cm

1.95 (2.07) 5.84 (4.55) 3.47 (2.63) 2.31 (2.03) 3.74

Management science (N = 19)

areas

TABLE 1 Means and Standard Deviations for VP1 and MBTI Subscales by Concentration

100.67 (31.94) 103.89 (21.44) 75.11 (21.88) 79.78 (17.45)

0.76 (1.30) 2.59 (2.73) 4.23 (4.01) 4.12 (3.48) 6.53 (2.58) 5.65 (3.66)

Marketing (N = 18)

Area

94.09 (22.80) 107.54 (27.67) 87.73 (21.01) 84.82 (24.83)

1.36 (1.36) 4.36 (3.68) 6.73 (3.86) 2.54 (2.97) 6.00 (3.25) 6.64 (4.42)

Management (N = 22)

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groups by area of concentration. The analysis showed three significant discriminant functions, signifying that the data had an underlying threedimensional structure, Function 1: percentage variance = 50.49, x*(30) = 94.62, p G .OOl; Function 2: percentage variance = 29.06, x*(20) = 40.66, p s .OOl; Function 3: percentage variance = 16.60, x2(12) = 20.62, p 6 .05. Subsequent data analyses focused on the three significant discriminant functions. The multivariate means (centroids) for each of the six concentration groups on the three respective significant discriminant functions are shown in Table 2. The centroids give an indication of the relative relationships and statistical separation among the groups. The discriminant structure matrix is also shown in Table 2. This matrix indicates the correlation between the original predictor variables and the derived discriminant function scores. The matrix, which was subjected to varimax rotation to facilitate interpretation, is helpful in further delineating the relationship of the predictor variables to the discriminant functions (Borgen & Seling, 1978). The discriminant matrix structure, viewed in conjunction with the centroids, indicated that on the first discriminant function, the accounting and finance groups were separated from the management science group by higher scores on the Conventional Holland dimension. On the second discriminant function, the management group was separated from the TABLE 2 Group Centroids by Concentration Area and Discriminant Structure Matrix for the VP1 Discriminant Function Analysis Discriminant Variables

1

function

2

3

Group centroids Concentration group Accounting Finance Information systems Management Management science Marketing

0.381 0.327 0.081 -0.616 - 0.985 0.195

0.008 -0.402 0.034 1.034 - 0.230 0.316 Discriminant

VP1 subscales Realistic Investigative Social Conventional Enterprising Artistic

0.221 - 0.269 -0.091 0.720 0.479 0.134

0.101 -0.167 0.746 - 0.289 0.121 - 0.650

structure matrix 0.007 0.036 0.809 - 0.096 0.402 0.496

0.836 0.632 0.013 0.065 -0.102 0.446

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finance group by higher scores on the Social dimension. On the third discriminant function, the information systems group was separated from the marketing group by higher scores on the Realistic dimension and to a lesser extent by higher scores on the Investigative dimension. These interpretations are compatible with the raw cell means in Table 1 and with univariate F ratio results (not shown). The discriminant function analysis also indicated the degree of accuracy with which membership in each concentration group could be determined from scores on the VP1 scales. Overall, 37.87% of the subjects were classified accurately against a prior probability of 16.66% however, the percentages of accurately classified subjects differed across groups: accounting, 12.5%; finance, 32.3%; information systems, 31.3%; management science, 63.2%; marketing, 38.9%; and management, 59.1%. Because the first letter in the three-letter Holland codes for the concentration areas are the same in some cases, a separate discriminant analysis also was conducted by combining concentration areas with the same first letter code. This resulted in three groups: accounting-finance, information systems-management science, and marketing-management. Discriminant analysis resulted in two significant discriminant functions (JJ < .OOl). Based on the centroids and the discriminant structure matrix (not shown), the first function separated the accounting-finance group from the marketing-management groups based on higher Social and lower Conventional scores in the latter group. The second function separated the information systems-management science group from the marketingmanagement group based on lower scores on the Realistic and Investigative dimensions in the latter group. Based on these functions, the discriminant analysis was able to accurately classify 57.4% of the subjects by concentration area compared to a prior chance probability of 33.3%. The percentages of correct classifications for the three groups were accountingfinance, 52.6%; information systems-management science, 56.9%; and marketing-management, 67.5%. Correlational analysis was used to test the hypothesis that the degree of congruence between one’s three-letter code based on VP1 scores and the Holland three-letter code associated with the concentration area would be predictive of program completion. Results showed that the point biserial correlation between the congruence score and program completion was significant (rpb = .156, p d .05), thus supporting the congruence hypothesis. Discriminant analysis also was used to assess the ability of the MBTI to predict student concentration area. Results showed one significant discriminant function: percentage variance = 47.43, x2 = 32.61, p G .05. The multivariate means or centroids and the discriminant structure matrix, both shown in Table 3, indicated that the management science group was separated from the management group by higher scores on

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VP1 AND MBTI AS PREDICTORS TABLE 3 Group Centroids by Concentration Area and Discriminant Structure Matrix for the MBTI Discriminant Function Analysis Variables

Discriminant

function

Group centroids Concentration group Accounting Finance Information systems Management Management science Marketing

0.157 0.013 -0.140 -0.338 0.752 -0.324 Discriminant

MBTI subscales Extraversion-Introversion Sensing-Intuition Thinking-Feeling Judgment-Perception

structure matrix 0.615 -0.135 0.269 0.626

Introversion and lower scores on Judgment. Univariate F ratios (not shown) supported only the significant difference on Introversion. Analysis of the ability of the MBTI scores to accurately classify subjects by concentration area showed that only 17.75% of the subjects were correctly classified. Given a prior probability of 16.66 that an individual would fall into a particular group by chance, overall the MBTI was not able to improve appreciably on chance in classifying concentration areas. The success of the classification by MBTI scores varied greatly across areas: accounting, 25.0%; finance, 0%; information systems, 9.4%; management science, 68.4%; marketing, 5.6%; and management, 40.9%. There was some evidence, however, that the differentiations made by the MBTI did parallel some of those made by the VPI. Canonical correlation was used to further assess the relationship between the dimensions of the VP1 and the MBTI. Results showed two significant dimensions, Dimension 1: percentage variance = .279, R, = S28, x2(24)= 80.58,p s .OOl, and Dimension 2: percentage variance = .097, R, = .312, x2(15) = 28.06, p s .05. Since the significant dimensions constitute two linear composites that are orthogonal relative to each other, they indicate two independent sources of variance between the measures (Kerliner & Pedhazur, 1973). The two sets of canonical variates are shown in Table 4. For the first set, a positive relationship between the Artistic subscale of the VP1 and the Sensing-Intuition subscale of the MBTI is indicated by the size and matching signs of the respective variates (- .814 and - .954). Thus the data show that the higher the score on the Artistic subscale, the higher the score on the Sensing-Intuition subscale, i.e., the closer the score is likely to be to the Intuition end of the Sensing-Intuition

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TABLE 4 Results of the Canonical Analysis of VP1 and MBTI Dimensions Measure VP1 subscales Realistic Investigative Social Conventional Enterprising Artistic MBTI subscales Extraversion-Introversion Sensing-Intuition Thinking-Feeling Judgment-Perception

First set

Second set

,230 - ,023 - ,203 .24.5 -.136 - ,814

-.134 ,462 - .845 ,059 - ,433 ,429

.171 - ,954 - ,252 ,196

.906 .381 - .449 .151

continuum. Similarly, for the second set of canonical variates, a negative relationship between the Social subscale of the VP1 and the ExtraversionIntroversion subscale of the MBTI is demonstrated by the respective variates (- .845 and .906). These data indicate that the higher the score on the Social subscale, the lower the score on the Extraversion-Introversion subscale, i.e., the closer the score is likely to be to the extraversion end of the Extraversion-Introversion continuum. DISCUSSION The results of this investigation support Holland’s (1985a) theory as a significant predictor of concentration area among MBA students. The three discriminant functions which resulted from the multivariate analysis generally separated groups on dimensions that are compatible with Holland’s approach. For example, the Holland three-letter code for management science does not include Conventional, the factor that separated management science from accounting and finance; while both accounting and finance include Conventional as the first letter in their three-letter codes. Similarly, the information systems group was separated from the marketing group by the Realistic and Investigative dimensions. Both of these dimensions appear in the three-letter code for information systems, but not for marketing. However, the finance and management groups were separated by higher Social scores in the latter group, even though both the finance and management concentrations were assigned three-letter codes with the Social dimension in the second position. Since Holland’s theory allows for somewhat different emphases within particular career paths, it is possible that many of the students concentrating in finance were anticipating staff positions which involved less interaction with others. Nevertheless, the Holland code for financial analyst, typically a staff position, carries

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the Social dimension in the second position (Gottfredson et al., 1982). At the same time, it is not surprising that individuals with management concentrations would score high on the Social dimension, particularly given the emphasis on interpersonal skills inherent in most management curricula. As part of a related study of influences on choice of major among business students, Barnowe, Frost, and Jamal (1979) had nine faculty judges independently rate the degree of person involvement associated with various business-related fields of work. On a lo-point scale, with 10 as the highest rating, the judges gave an average of 9.2 to organizational behavior (management) and 1.8 to finance. These general findings were replicated with an additional panel of 11 faculty members and with analogous ratings from 485 students. Thus, it is possible that the Holland codes for financial occupations overstate the degree of social emphasis inherent in them. Future research should focus on further delineating the Social dimension as it relates to business occupations and particularly to finance and management positions. When the concentration groups with the same first letter in their Holland three-letter codes were combined for multivariate analysis, two significant discriminant functions separated the groups. This analysis supported the trend found in the discriminant analysis with all six concentration groups in that the combined accounting-finance group was separated from the combined marketing-management group by lower scores on the Social dimension. However, higher scores on the Conventional dimension also supported separation in the combined analysis, an outcome supportive of Holland’s theory. The separation of the information systems-management science group from the marketing-management group by higher scores on the Realistic and Investigative dimensions also is consistent with the discriminant analysis findings involving the six concentration groups and with Holland’s theory. Since the discriminant analysis with three combined groups was able to classify almost 60% of the students with the correct concentrations, the results suggest that the VP1 may be a particularly useful tool in helping students to select an area of concentration compatible with their personality type. As Holland’s approach generally suggests, students could pay particular attention to their high scores and use them as a basis to explore possible concentrations which are most congruent with their personality type (Holland, 1985b). The fact that the degree of congruence between one’s personality type and one’s concentration area was predictive of program completion also supports the use of the VPI. In addition, the congruence findings bolster the usefulness of the Iachan measure of agreement, an improved method of measuring congruence proposed by Iachan (1984) and incorporated in this study. Despite the fact that the correlation between congruence and program completion was not large, it does suggest that congruence is one factor influencing success in the context of the study. Although Holland’s notion that

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individuals who operate in environments that are congruent with their personality type are likely to be more successful has intuitive appeal within the framework of his theory, the emirical support has been mixed (Holland, 1985a). Use of the Iachan Index in future studies including those which match Holland personality types with actual job choices using the Iachan measure of agreement may provide greater support for the congruence notion. Relatively weak support was found for the utility of the MBTI as a facilitator of vocational choice. Discriminant analysis did reveal a significant discriminant function which separated the management science group from the management group by higher scores on Introversion and lower scores on Judgment in the former group. However, use of the discriminant function to classify individuals according to concentration based on their MBTI scores showed that only about 18%; barely better than chance, were correctly classified. Furthermore, the Extroversion-Introversion and the Judgment-Perception dimensions accounted for the separation, even though Myers (1962) had originally proposed that the SensingIntuition and Thinking-Feeling dimensions would differentiate among occupations. Interestingly, the differentiation made by the MBTI between the management science group and the management group did parallel some findings with the VP1 whereby the management group was separated from others by a relatively high orientation toward people. Along similar lines, canonical correlation analysis suggested a positive relationship between the Social dimension of the VP1 and Extroversion on the MBTI. In addition, there was a positive relationship between the Artistic dimension of the VP1 and Intuition on the MBTI, a factor which may have had less importance with this sample than might be the case with occupations with Artistic codes under Holland’s scheme. While there was some common variance associated with the two measures, as suggested by Holland (1985a), the two measures appear to have substantial areas of nonconvergence as well. Overall, these results support Holland’s theory and the use of the VP1 as a potential tool in assisting with the choice of areas of concentration within business. At the same time, the findings here suggest that the MBTI has only limited utility as an aid to vocational choice, at least for choosing among areas of concentration within business. However, it is possible that the MBTI may have utility for other research purposes not addressed by this study, such as that related to cognitive orientation or to vocational choice in other areas (Carlson, 1980; Carlyn, 1977; Myers & McCaulley, 1985). REFERENCES Barnowe, .I. T., Frost, P. J., & Jamal, M. (1979). When personality meets situation: Exploring influences on choice of business major. Journal of Occupational Psychology, 52, 167-176.

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Borgen, F. H., & Seling, M. .I. (1978). Uses of discriminant analysis following MANOVA: Multivariate statistics for multivariate purposes. Journal of Applied Psychology, 63, 689-697.

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