achievement motivation theory and occupational choice

European Journal of Social Psychology, Vol. 17, 327-346 (1987)

Achievement motivation theory and occupational choice*

KAREN JANMAN Department of Psychology. University College London, London WC1 OAP. U.K.

A bstract

Two studies are reported which aimed to answer several questions relating to Atkinson’s model of achievement motivation. Firstly, how successfully the theory can predict the occupational choices of two different populations and what changes, i f any, need to be made to the model to make it more suited to such predictions. Several conceptual errors were found in the theory which make it unsuitable in its present form for predicting occupational choices and suggestions are made as to the possible correction of these. Secondly, a comparison is made bet ween Atkinson’s model and the expectancy-valence models currently utilized to describe and predict occupational decision-making. In particular Atkinson 3 incentive component is contrasted with the valence measure described by expectancy- valence models, and the possible influences of the motive factors (motive to succeed and motive to avoid failure) are considered since these are typically omitted by other models of career choice. Finally, the existence of sex differences in career choice, as well as in the various components of the model are studied and discussed. The changing conceptualization of ‘fear of success’ is also included in this consideration.

INTRODUCTION

The achievement motivation theory developed by Atkinson and McClelland (Atkinson, 1957; McClelland, Atkinson, Clark and Lowell, 1953) defines the tendency to approach an achievement task (Ta) in terms of two motive factors, the motive to approach success (Ms) and the motive to avoid failure (Mf), and four situational factors, the probabilities of success and failure (ps and Pf) and the incentives of success and failure (Is and If ) .

This research was conducted in partial fulfilment of the degree of D. Phil. at the University of Oxford, Great Britain and was funded by the E.S.R.C. The author would like to thank Dr M. Argyle and Dr M. Wittig for their constructive comments on early drafts of this paper and to acknowledge the invaluable and greatly missed guidance of Dr J . Jaspars.

Requests for reprints should be sent to Karen Janman, Department of Psychology, University College London, 26 Bedford Way, London WCI OAP, U.K.

OO46-2772/87/030327-20$10.00 01987 by John Wiley & Sons, Ltd.

Received 2 July 1986 Revised 20 January 1987

328 K . Janman

Atkinson provided precise equations summarizing the relationship of these factors to achievement tendency such that

Ta = (Ms x Ps x Is) - (Mf x Pf x I f ) (1)

The motive to approach success was defined as a capacity for reacting with pride in accomplishment, while the motive to avoid failure was defined as a capacity for reacting with shame and embarrassment when the outcome of performance is failure. The four remaining components of the equation, those describing situational factors, were defined according to a series of assumptions about their interdependence. The probability of success was seen by Atkinson as a subjective estimate of the likelihood of success at each given task. However, in experimental investigations this probability was either simply defined (e.g. distance from the goal in a ring-toss game, Atkinson and Litwin, 1960; McClelland, 1958), or was defined for the subject by the experimenter (Feather, 1961). The probability of failure was defined by Atkinson as (1 - Ps), that is, the assumption was made that subjects are aware of the inverse probability relationship adopted by statisticians. A second assumption was made by Atkinson to overcome the initial difficulties encountered when attempting to define the incentive value of success. This states that Is = (1 - Ps), based upon the rationale that more pride is experienced following success at a difficult task than at an easy one. Similarly, the incentive value of failure was defined according to the third of Atkinson’s assumptions, that If = (1 -A). That is, that greater shame is felt at failing on an easy task than on a difficult one.

When these assumptions are substituted into the equation a simplified form is derived such that

Ta = (Ms - M f ) x Ps x (1 - Ps) (2)

Experimental investigations suggested the validity of this model and its assumptions, predicting choices in ring-toss games (Atkinson and Litwin, 1960) and choices between tasks of different difficulties (Feather, 1961). However, two problems emerged from this literature. Firstly, an over reliance upon male subjects made generalizations to female populations difficult. When females were included, results suggested that sex differences may exist in the motive components of the equation and in the predictive validity of the model (French and Lesser, 1964; Veroff, Feld and Crokett, 1966). Such findings led Horner (1968, 1972) to suggest the need for an additional motivational component when considering female achievement. She introduced the notion of a ‘motive to avoid success’ or a ‘fear of success’ (FOS) in women, that is, a disposition to become anxious about achieving success because they expect negative consequences (such as social rejection and/or feelings of being unfeminine) as a result of succeeding. Horner reported that 62 per cent of women compared with only 9 per cent of men produced negative imagery when given story cues concerning the success of a member of their own sex.

The vast literature that resulted from this early study revealed some serious methodological and conceptual flaws in Homer’s theory which are well-documented and discussed elsewhere (Tresemer, 1976; Zuckerman and Wheeler, 1975). In particular, many researchers have questioned Homer’s motivational interpretation of fear of success, and have argued instead that it is better understood as a situational

Achievement theory and occupational choice 329

response involving expectancies about the consequences of behaviour (Lockheed, 1975; Robbins and Robbins, 1973). Support for this approach comes from studies which show that both male and female subjects write more FOS stories in response to cues containing female actors than they do to those containing male actors. In addition, certain specific situational variables such as deviance from sex-role stereotypes in occupational choice or role overload have been found to have differential effects dependent upon the sex of the cue character (Bremer and Wittig, 1980; Janman, 1984). Thus, it is argued, these measures are evoking the subjects’ knowledge of sex-roles rather than tapping their intrinsic motives. Whilst it is no longer certain that an additional motivational factor is needed to explain female achievement behaviour, there is increasing evidence that certain situational components of achievement tasks may differ between the sexes. This shift in emphasis from the motive to the situational components of achievement has recently been included in investigations of sex differences in mathematics choices (Eccles, Adler, Futterman, Goff, Kaczala, Meece and Midgley, 1983; Eccles, Adler and Meece, 1984).

A second shortcoming inherent in the experimental investigations based upon the Atkinson model relates to the validity of extrapolating from the type of laboratory tasks chosen by the experimenter to real life achievement behaviour. Atkinson himself argued that the ultimate test of the predictive validity of his model would lie in its applicability to real life choices such as academic and career behaviour. Unfortunately the literature is very poor in this area and it is impossible to conclude at present that the achievement motivation theory can predict such behaviour.

These problems associated with Atkinson’s model were highlighted by Parsons and Goff (1980). In a detailed examination of the development of Atkinson’s model they argue that his assumptions and experimentation result in an elimination of the incentive value as a key determinant of approach behaviour, an over-simplification of the concept of the probability of success and a limitation on the range of achievement goals considered.

Despite the apparent neglect on the part of researchers to investigate achievement motivation effects and occupational choice, there do exist established models of occupational choice elsewhere in the literature. Vroom’s (1964) expectancy-value theory describes occupational choice as

F j=EjxVj (3)

where, F j = the force to choose occupation j, Ej = the strength of the expectancy that the choice of occupation j will result in the attainment of occupation j , and Vj = the valency of occupation j.

A strong parallel exists between the Ej measured by Vroom and his coworkers and the probability of success (Ps) measured by Atkinson. Both represent the likelihood of attaining a particular outcome. The former investigators typically measure this by asking subjects to rate how likely they feel they are to succeed in an occupation. As discussed above however, Atkinson generally acquired only simple measures of probability as a result of the typically laboratory-based tests of his theory. It is likely that individual differences in expectancy of success for different occupations will prove important in understanding career choice.

330 K. Janman

The valance or incentive components of the two types of model differ somewhat more than do the expectancy components. In the expectancy-value theory the valence of an occupation is described as

Where, Vj =the valence of occupation j, vi = the valence of outcome i, fij =the cognized instrumentality of occupation j for the attainment of outcome i, and n is the number of outcomes considered. Occupations that are most instrumental for important rewards and outcomes will have the most positive occupational valence and will be preferred over other occupations. Thus, factors which may be seen as relevant to occupational choice, e.g. pay, promotion prospects, opportunities for responsibility etc. are represented both by how important they are to the person (the valence) and how likely it is that this factor will be present in a particular occupation (the instrumentality). It can be seen that this measure contrasts sharply with Atkinson’s incentive value of success which was described as dependent upon the probability of success. Some of the various factors measured by expectancy theory may in part relate to the difficulty of the task (e.g. high salary, respect, chance for leadership etc.) but many others are unlikely to do so (e.g. chance to benefit society, friendly coworkers, job security, etc.). If Atkinson’s theory is to be applicable to career choice it would appear that a wider conceptualization of incentive will be needed to reflect the many aspects of a career, other than its difficulty, that make up its incentive value or valence. In particular, several studies have shown that sex differences exist in the importance attributed to certain of these factors (Manhardt, 1972: Siegfried and MacFarlane, 1981). These, according to expectancy-value theory, will then affect the final valence of an occupation. Such factors will similarly need to be included in Atkinson’s model to account for this.

Perhaps the most obvious difference between the two types of model is that the expectancy-value model of career choice does not contain any measure of individual difference in motives. Prior to the present study there was no evidence either to support or to contradict the suggestion that individual differences in the motives to achieve or to avoid failure actually affect career choice. Existing models have shown good predictive powers without the inclusion of such motives (Vroom and Deci, 1971; Sheridan, Richards and Slocum, 1975; Wheeler and Mahoney, 1981) but this is not to say that their inclusion would not benefit these models.

Finally, Atkinson’s model also takes into account an individual’s consideration of failure, including the likelihood and negative affect attached to this. Alternative models of career choice rarely, if ever, include such a consideration.

The studies to be described here represent an attempt to apply Atkinson’s model to career choice, whilst allowing both a comparison of its success with that of the existing expectancy-value model and permitting an investigation into the sex differences that may exist within its components.

In particular the following hypotheses were tested: (1) That Atkinson’s model, in its simplified form, would be limited in its ability

to predict career choice. (2) That the assumptions inherent in the simplified equation may be responsible

for this inability. Specifically, the assumed relationships between the incentives and probabilities are likely to be too narrow and therefore to cause a breakdown

Achievement theory and occupational choice 33 1

of the predictive validity of Atkinson’s model when it is simplified according to these assumptions. Summation models of incentive or valence were hypothesized to be more representative of the attractiveness of an occupation than Atkinson’s incentive value that takes probability as the key determinant.

(3) That sex differences would be found in some or all of the components of the model, particularly the situational components, and that these would be especially important for understanding and predicting sex-differential career choice.

Two studies are described here. An initial study was carried out upon university undergraduate subjects to ascertain whether such hypotheses were worthy of further investigation. Details of this study are included here since the results also allow an interesting comparison between this population and that used for the main study. The second, larger study was carried out upon 15-16-year-old school pupils.

STUDY ONE

Method

Subjects

The subjects for this study were Oxford university undergraduate students (20 male and 20 female). These came from a cross-section of honours subjects and were aged from 19-22 years.

Measures

A ten-page questionnaire was completed by each subject. This was designed to measure each of the components of Atkinson’s equation for a series of fourteen occupations.

Motive to approach success This was assessed with Mehrabian and Bank’s (1978) measure of achievement tendency. This 38-item measure is balanced for response bias such that 19 are negatively worded. Examples of items are ‘I find it especially satisfying to complete an important job that requires a lot of effort’ (positive) and ‘I like tasks that require little effort once I’ve learned them’ (negative). Subjects were asked to indicate extent of agreement or disagreement with each item on a 7-point scale. A total score was computed for each subject by algebraically summating his or her responses to the positively worded items and subtracting from this the sum of his or her responses to the negatively worded items.

Motive to avoid failure This was assessed with Alpert and Haber’s (1960) debilitating and facilitating anxiety scales. This questionnaire consists of 19 items which indicate ‘debilitating’ and ‘facilitating’ anxiety, e.g. ‘Nervousness while taking an exam or test hinders me from doing well’ (debilitating) and ‘The more important the exam or test the better I seem to do’ (facilitating). Subjects again indicated degree of agreement or disagreement with each item on a 7-point scale. A total score was computed for each subject by summating the agreement with debilitating anxiety items and subtracting from this the summed score on the facilitating anxiety items.

332 K. Janman

Probability and incentive value of success Subjects were asked to consider each of fourteen occupations in turn. For each they were instructed to suppose that they had decided to pursue that occupation and then to complete two 7-point scales concerning (a) what they considered their chances of actually succeeding in that occupation would be and (b) the value that they would attach to success in that occupation. These scales ran from ‘Impossible to succeed’ to ‘Certain to succeed’ and ‘Low value’ to ‘High value’ respectively.

Probability and incentive value of failure Subjects were next asked to reconsider each of the fourteen occupations but this time to indicate (a) how likely they were to fail at that occupation and (b) how negatively they would view that failure (i.e. how concerned they would be). These scales ran from ‘Impossible to fail’ to ‘Certain to fail’ and ‘Not at all concerned about failure’ to ‘Very concerned about failure’ respectively.

Summation model of incentive or valence In addition to the single measure of incentive value described above, details were also obtained as to the importance to the subjects of a variety of factors likely to be considered when choosing an occupation. Eleven such factors, high salary, opportunity for promotion, does not interfere with personal life, job security, opportunity for responsibility, fringe benefits, job involves a contribution to society, good relationships with coworkers and voice in decision-making (adapted from Siegfried and MarFarlane, 1981), were listed and subjects asked to rate each on a 7-point scale running from ‘Not very important’ to ‘Very important’. Following this subjects were asked to rate how likely each aspect was to be present in each of the fourteen occupations, on a 5-point scale ranging from ‘Very likely’ to ‘Very unlikely’ This was presented as a 14 (occupations) by 11 (job factors) grid, each cell representing the likelihood of a particular factor being present in a particular occupation.

Subjects were also asked to rank the occupations according to how likely they thought they would be to choose each of them if they had to make a forced choice. Finally, details of age, sex and actual career intentions were obtained.

Occupations The fourteen occupations considered in this study were taken from statistics provided by the career services department of the university in an attempt to investigate those careers which the graduates may realistically have been considering. These were, insurance, nursing, banking, teaching, research or further study, civil service, design, management, social work, advertising, journalism, accountancy and sales representative.

Subjects were allowed as much time as they needed to complete the questionnaire. Most completed it in approximately 45 minutes.

Results

Having obtained values for all six components of Atkinson’s equation, it was possible to calculate for each subject a ‘tendency to approach’ (Ta) value for each of the fourteen occupations. Since, in Atkinson’s theory, the Ta value indicates the likelihood of choosing a task from a series of alternatives, a high positive correlation between the Ta value and the rank ordering would represent support for the predictive validity of the Atkinson model. This test was applied to the two forms of the equation (Equations 1 and 2). For the simplified form, Equation 2, that is, substituting the motive to succeed, the motive to avoid failure and the probability of success into the equation and correlating the resultant Ta values with the rank ordering of choice for each subject, a mean value of Pearson’s rho of 0.01 (S.D. =0.31) was obtained.


This was not the positive correlation that Atkinson’s theory would predict. Indeed, for 48 per cent of the subjects this correlation was actually negative.

When the extended form of the equation (Equation 1) was tested in a similar manner, including the values of probability of success and failure, subjective ‘total’ incentive value of success and incentive value of failure obtained independently from the subjects, a mean value of rho of +0.59 (S.D.=0.19) was obtained.

This then provided strong support for the predictive validity of Atkinson’s equation when applied in its original form, but suggests that one or more of the assumptions inherent in its simplified form are invalid. To ascertain which of these it may be, the assumed negative correlation between A and Is, between A and Pf and between Pf and If were tested for each subject. The mean values of rho obtained for each ofthesetestswere +0.33(S.D.= 0.24), -0.8(S.D.=O.l9)and -0.20(S.D.=0.36) respectively. These results suggest that, whilst there is some support for the relationships between probability of success and probability of failure, and between probability of failure and incentive of failure as proposed by Atkinson, the incentive value of success was actually positively related to the probability of success. The latter was the case for over 90 per cent of the subjects.

No significant sex differences were found for any of the individual components of the equation in this sample.

No further analyses will be presented for the pilot study, due to its small size and rather specialized population. A more detailed examination of the hypotheses will be presented in the second, larger study.

Discussion

The results of the pilot study strongly supported the hypothesis that some of the assumptions in Atkinson’s theory may make it inappropriate, at least in its simplified form for predicting sex differences in occupational choice. In particular, the assumption that the incentive value of success is negatively related to the probability of success seems invalid in this context. Instead, it appears that the more likely people feel they are to succeed, the higher the incentive value they attach to that success. Discussion of the possible reasons for this will be postponed until later.

The remaining analyses showed that, at least in this undergraduate sample, there were no significant sex differences in the probabilities and incentives for each occupation. The sexes were also very similar in terms of their scores on motive to achieve and fear of failure. However, it should be recognized that the sample was a somewhat unusual one. The lack of sex differences may well have been due to the particular sample and occupations that were chosen. Because of this, together with the relatively small sample size of the pilot study, a second study was carried out on a larger, more representative, sample.

STUDY TWO

Method

Subjects

The subjects for this study were 168 fifth form pupils, (85 females and 83 males), attending a comprehensive school in Oxfordshire, Great Britain. Their median age

334 K. Janman

was 15 years, 8 months. The pupils completed a ten-page questionnaire very similar to that used in the pilot study. An important change was made concerning the occupations that the pupils were asked to consider. These again were chosen to represent occupations that the pupils may have been considering and were: insurance, nursing, banking, teaching, doctor, journalism, design, management, butcher, secretary, mechanic and shop assistant.

Measures

Measures of probabilities and incentive values (both as a single measure and in accordance with the summation model described in the previous study) of success and failure were obtained from all subjects for each occupation as were their scores on Mehrabian and Bank’s (1978) measure of achievement tendency and Alpert and Haber’s debilitating and facilitating scales. Finally, the subjects were asked to rank order the occupations for choice and to indicate their age, sex and career intentions.

Results

Testing Atkinson’s model

As in the previous study, Pearson’s rho was computed between the values of Ta and the rank ordering of choice for each subject according to Equations 1 and 2. A mean rho value of -0.17 (S.D. =0.57) was obtained when the simplified form of the model (Equation 2) was used, and a mean rho value of + 0.58 (S.D. = 0.25) when the extended form of the model (Equation I ) was used. The three assumed relationships, between Ps and Is, between Ps and Pf, and between Pf and If were again tested utilizing correlations between the relevant variables and yielded mean values of rho of +0.52 (S.D.=0.37), -0.73 (S.D.=0.21) and -0.28 (S.D.=0.38) respectively.

Again therefore it appears that, when measured independently, the situational components of Atkinson’s model promote predictions of career choice. To establish exactly how useful each of these components is, multiple regression analyses were carried out for males and females with the career choice ranking as the dependent variable and the probabilities of success and failure and the incentive values of success and failure as the independent variables. A summary table showing the beta weights for each of these variables is given in Table 1.

Table 1 . Multiple regression with occupational choice as the dependent variable, separately for males and females

Independent variable Males Females

Probability of success + 0.26 + 0.32

Beta weights

Probability of failure - 0.01 - 0.07 Incentive of success + 0.34 + 0.31 Incentive of failure + 0.08 + 0.02


The results of the regression analyses suggest that both of the success components of the equation are important predictors of career choice. However, the failure components add little to the predictions, due to a high mean correlation between If and Is (+ 0.71) and between Ps and Pf (- 0.84).

Sex differences

It was hypothesized that sex differences would be found in some or all of the components of Atkinson's model. To test whether this was the case for the motive components, motive to succeed and motive to avoid failure, t-tests for independent samples were carried out on the male and female scores on these two measures. Whilst males and females did not differ significantly in their motive to succeed scores, there was a significant difference between their motive to avoid failure scores, with females typically scoring higher (mean of 1 1.8) than their male counterparts (mean of 2.8; t = 4.6, p< 0.001).

Sex differences were also investigated in the four situational components of Atkinson's model. A one between (sex), one within (occupation) analysis of variance was carried out for each of the measures (Ps, Pf, Is, and I f ) . The two probability measures, Ps and Pf, both showed a main effect of occupation (F11,139=21.85 pc0.001, and (Fi32= 16.47 pcO.001 respectively) and a significant interaction between sex of subject and occupation (F11,139=26.75, pcO.001, and F11,~32=23.14, pcO.001 respectively). The interpretation of this interaction can best be seen by considering the mean values given in Table 2.

Thus, males and higher probabilities of success and lower probabilities of failure than females for such male sex-typed occupations as mechanic, butcher, manager and doctor. Conversely, females had higher probabilities of success and lower probabilities of failure than males for such female sex-typed occupations as secretary, nurse, shop assistant and teacher. There were no main effects of the sex of the subject.

Table 2. Mean values of probability and incentive of success and failure for each occupation, by sex

Ps Male 4.6 3.6 4.2 4.1 3.2 3.7 3.6 3.7 2.7 3.8 2.1 2.0 Female 2.0 2.2 3.8 3.9 2.9 3.6 3.5 4.0 3.4 5.0 4.0 4.5

Male 3.1 4.0 3.6 3.5 4.8 4.0 3.7 3.5 4.6 3.3 5.2 5.3 Female 4.0 5.3 3.8 3.8 4.4 3.6 3.8 3.8 4.3 3.0 4.0 3.0

Male 4.3 3.1 4.1 4.2 4.0 3.3 3.2 3.7 3.2 3.0 3.1 2.3 Female 3.0 2.3 4.0 4.3 4.8 3.8 4.1 4.5 4.1 3.5 4.9 4.1

Pf

Is

If Male 4.1 2.9 2.8 3.0 3.4 3.0 2.1 2.8 2.5 2.0 2.8 2.0 Female 3.0 2.7 2.6 3.3 4.1 3.5 3.5 4.0 3.9 3.8 3.9 4.1

336 K. Janman

The incentive value components, Is and If, showed a similar main effect of occupation (Fll,132= 19.05, pc0.01 and F]],]36= 10.65, ~ ~ 0 . 0 1 respectively) as well as an interaction between sex of subject and occupation (Fll,132= 15.12, ~ ~ 0 . 0 1 and F]l,l36= 17.75, ~ ~ 0 . 0 1 ) . Thus, for mechanic, butcher and designer, males had higher incentives than females, whilst the reverse was true for such occupations as secretary, nurse, shop assistant and teacher (see Table 2). However, in the case of the incentive components there was also a main effect of subject sex, with females having higher incentive values of success and failure across occupations than males (F,,13z = 10.75, p<O.OOl, and Fl,136=77.71, p<O.OOl for Is and If respectively).

Strong sex differences were also found in the first choices made by subjects, with a high degree of sex-typing present in the occupations assigned as first choice. These are represented in Figure 1. The occupation most often chosen by females was secretary, chosen by 31 per cent of the female subjects. This was followed by nurse (17 per cent) and designer (16 per cent). The occupation most preferred by males was designer (perhaps somewhat unexpectedly), chosen by 30 per cent of the male subjects, followed by mechanic (21 per cent) and management (13 per cent).

Perhaps more information can be gained from the final section of the questionnaire which asked pupils to state which career, if any, they were actually considering. Most noticeable here was the considerably smaller number of occupations that were being considered by females (10) compared with the males (24). This was also reflected in the strong stereotyping present in their occupational choices with nearly half choosing between the three occupations of secretary, nurse and hairdresser. The males showed more variety in their considerations than the females. Another difference between the sexes worth noting was the proportion of males and females who did not have specific occupational plans when completing the questionnaire. Of the females, 27 per cent replied that they did not know what career they might follow. Only 11 per cent of the males gave this reply.

30t

25 iil 5 3 2

W FEMALES 0 MALES

OCCUPATION

Figure 1 . First (forced) occupational choices of males and females


Comparing Atkinson ’s model with existing models

To test the predictive powers of the expectancy-value model for the present sample, occupational valences were computed for each subject according to Equation 4. These valences were then incorporated into the further model of occupational choice as in Equation 3. The resultant F j values were then correlated with the career choice ranking of each subject giving a mean correlation across subjects of +0.64.

To allow a more direct comparison between Atkinson’s model and Vroom’s expectancy-value model a correlation was also calculated between the product of A and Is (as measured independently) and occupational choice. This yielded a mean correlation of 0.66. Thus occupational choice can be predicted slightly more successfully by Ps and Is in the form

Ta=(PsxIs) ( 5 )

than by the original formulation (Equation 2). The regression analyses suggest that this may in part be due to the inclusion of If in the avoidance side of the equation. The small but positive beta weighting assigned to If suggets that, counter to Atkinson’s theorizing, a high incentive to avoid failure is associated with a high occupational choice ranking. A new form of the equation was therefore tested such that:

Ta = (Ms x A x Is x If) - (Mf x Pf) (6)

This increased the prediction to a mean correlation between Ta and occupational choice of + 0.68.

The comparison between the expectancy-value model (Equation 3) and the parallel form of Atkinson’s components (Equation 5 ) which yielded very similar mean correlations between occupational choice and their predictor value (0.64 and 0.66 respectively) suggests a marked similarity between the Is as measured independently and the Vj of the expectancy-value model. However, a correlation between Is and Vj for each subject yielded a relatively low mean correlation of only + 0.35. To establish the relative utility of including either Is or Vj in a model of career choice, another multiple regression analysis was carried out but this time including both Is and Vj. From the beta weights assigned to Vj (+0.09 for males, +0.07 for females) compared with the beta weights assigned to Is (+0.28 for males and +0.23 for females) it appears that the valence measure is considerably less useful for the prediction of career choice than the single measure of incentive value of success. One possible reason for this is that Vroom’s measure does not take into account the degree of sex-typing present in an occupation nor how important this is to the subject. To test for this an analysis of variance (sex by occupation) identical to that described for incentive value was carried out for Vj. Unlike incentive value of success the valence measure showed no main effect of sex and no interaction between sex and occupation. Thus, it appears that Vj was less useful than Is for predicting career choice when both male and female sex-typed careers were considered since it did not allow for the expression of sex-typing effects upon the valence measure.

338 K. Janman

Achievement motives and occupational choice

The almost equal success of Atkinson’s and Vroom’s models when predicting career choice suggests that those models which are used at present to explain occupational choice would not be improved by the inclusion of Atkinson’s motive factors. The final series of analyses therefore sought to investigate in more detail the possible relationship between an individual’s motives to succeed and to avoid failure and hidher occupational choices.

Researchers have shown that whilst most individuals choose predominantly intermediate difficulty tasks, this is more true of high achievement oriented individuals (Ms > M f ) than of low achievement oriented individuals (Mf>Ms) (Atkinson and Litwin, 1960; McClelland, 1958). Similarly, it may be predicted that high achievement oriented individuals will more often choose intermediate difficulty occupations than will low achievement oriented individuals. Subjects were therefore divided by a median split (with 50 per cent scoring above the median classified as high and 50 per cent scoring below the median classified as low) on both Ms and Mf, resulting in each individual being classified as either H H (high Ms, high Mf) , HL (high Ms, low Mf), LH (low Ms, high Mf) or LL (low Ms, low Mf).

Two measures of difficulty were utilized. Firstly a form of objective difficulty was taken, whereby the occupations were assigned to one of five categories according to their socio-economic status. These were ( 5 ) professional, employers and managers (doctor and manager); (4) intermediate non-manual (designer, journalist, teacher); (3) skilled (nurse, insurance, banking); (2) semi-skilled and personal service (butcher, mechanic, secretary); and (1) unskilled (shop assistant) (Social trends, 1984). The percentage of subjects in each motive group choosing (first forced choice) an occupation in each of these five categories is shown in Figure 2.

Those subjects who were low achievement oriented (LH) tended to choose lower status occupations most often e.g. mechanic, secretary etc. whereas high achievement oriented individuals (HL) tended to choose higher status occupations most often e.g. insurance, banking, journalist, teacher etc. There was also some support for the suggestion that low achievement oriented subjects more often chose the highest status

~OCIO-E~ONOHIC STATUSOF acwm

Figure 2. Socio-economic status of first (forced) choice occupation by motive group


Figure 3. Subjective probability of success of first (forced) choice occupation by motive group

Table 3. Mean values of probability and incentive of success and failure for each occupation by motive group

5 High status

Ps HL LH HH LL

HL LH HH LL

HL LH HH LL

HL LH HH LL

Pf

IS

If

4.0 3.0 3.2 3.1 3.6 3.3 3 .3 3.6 3.4 3.6 4.0 3.3 4.8 3.6 3.1 3.1 3.8 3.8 3.0 2.4 3.2 3.3 3.3 2.2 5.4 4.0 3.6 3.3 4.9 4.3 3.2 3.6 4.1 4.4 4.6 3.4 4.1 2.8 3.4 2.1 3.0 3.1 2.6 2.3 3.0 3.4 3.3 2.1

3.8 5.0 4.6 4.8 4.1 4.1 4.3 4.0 4.1 3.8 3.4 4.2 3.2 4.1 4.5 4.9 3.8 3.8 4.4 4.8 4.3 4.0 3.6 5.2 3.1 4.0 4.1 4.2 3.1 3.2 3.2 3.6 3.3 3.6 3.2 3.6 3.5 4.8 4.8 4.6 4.6 4.4 4.5 5.0 4.1 4.3 4.1 5.3

3.0 2.6 3.4 2.4 3.8 3.5 3.9 3.8 3.6 4.2 4.3 4.0 3.1 3.8 3.5 2.5 4.2 3.8 3.5 3.4 3.4 3.9 3.8 3.9 3.4 3.9 3.6 3.2 4.3 4.1 4.1 3.9 4.0 4.3 4.4 4.4 2.6 3.0 3.2 3.1 3.6 3.0 3.2 3.3 3.2 3.8 3.9 3.8

2.7 2.8 3.2 2.3 3.2 2.8 3.4 3.3 3.0 3.4 3.2 3.1 3.0 3 .3 3.2 2.6 3.2 3.1 2.8 2.9 3.1 3.2 3.3 3.0 2.2 2.5 3.2 2.2 3.1 3.2 3.2 2.8 3.3 3.2 3.4 3.6 3.1 2.9 3.6 2.8 2.8 2.9 2.5 2.9 2.1 3.2 3.0 2.9

340 K . Janman

occupations (doctor and manager) than their high achievement oriented counterparts although this difference was less marked. Choices of subjects who were either high or low on both motives (HL or LL) lay between these two extremes. These results are therefore compatible with those of Atkinson and Litwin (1960).

A second measure of difficulty was also studied, that of subjective probability of success. Figure 3 . shows the percentage of subjects choosing occupations at each level from 1 (very likely to succeed) to 7 (very unlikely to succeed).

These results illustrate the importance of distinguishing between objective and subjective difficulty. Whilst low achievement oriented subjects typically chose lower status occupations that require fewer qualifications, they saw themselves as less likely to succeed at their chosen occupation than did their high achievement oriented counterparts, even though the latter were typically choosing higher status occupations.

This suggests that individuals with different motive components may perceive their probabilities of success somewhat differently. Since the effects may be confounded here by the tendency to choose different occupations a one between (motive group), one within (occupation) analysis of variance was carried out with the probability of success as the dependent variable. A significant effect was obtained for both occupation (F]],1]6= 15.67, p<O.O1) and motive group (F3,116, p<O.Ol). From the means given in Table 3 , the latter appears to have resulted from the HH subjects having consistently higher subjective probabilities of success for each occupation than the other subjects whilst the LL subjects had consistently lower subjective probabilities of success. Most interestingly, an interaction was obtained between motive group and occupation (&3,]16= 1.63, p<0.05) which from Table 3 appears to have resulted from the cross over between low and high status occupations for the HL and LH motive groups. Thus, HL subjects had lower probabilities of success than LH subjects for low status occupations, whilst they had higher probabilities of success for high status occupations.

Having established that an individual’s motives may influence hidher perceived probability of success for a given occupation it was considered useful to apply similar analyses to the three remaining situational components of Atkinson’s model.

Whilst an individual’s motives did not have a direct effect upon the magnitude of hidher incentives of success there was again an interaction between motive and occupation (F33,1 = 1.51, p < 0.05) such that the HL subjects had higher incentives for high status occupations and lower incentives for low status occupations than did LH subjects. There was also a main effect of occupation (Fll,llo= 14.98., p<O.OI).

Probability of failure showed only a main effect of occupation (F11,116= 12.17, p<O.O1) and of motive group (F3,ll6= 6.50, p<O.O1) with LL subjects having higher probability of failure and H H having lower probability of failure than the other motive groups.

Finally, incentive of failure showed only a main effect due to occupation (F11,114 = 7.68, p<O.Ol). Neither probability nor incentive of failure showed an interaction effect between motive group and occupation.

Discussion

Testing and comparing models of career choice

This second study further supports the hypothesis that, in its present form, Atkinson’s model is too simplistic either to explain sex differences in achievement behaviour,


or to predict such complex decisions as career choices. It was again shown that a knowledge of the two motivational factors and the probability of success is insufficient to predict occupational choice. This insufficiency appeared to stem from invalid assumptions made by Atkinson concerning the relationships between the situational components of the equation. Both the positive correlation between A and Is (for two very different populations) and the beta weight assigned to Is as a result of the regression analysis suggests that the incentive value of success is an important component of career choice and that it should be measured independently of A.

Existing models of career choice conceptualize incentive (valence) in terms of the various aspects of an occupation that a person may consider when making career decisions e.g. whether an occupation involves responsibility, high salary, good working conditions etc. The reported success of such models together with the results of the two studies presented here stongly support the criticisms levelled at Atkinson’s assumption that incentives can be considered purely as a function of expectancy. Instead they are important determinants of occupational choice and must necessarily be treated as factors independent of expectancy.

The two remaining assumptions made by Atkinson appear more robust even when applied to career choice. Certainly, both university undergraduates and school pupils seemed to represent expectancy of failure as the inverse of expectancy of success. The very low beta weight accorded to Pf by the multiple regression analysis further supports this interdependence. Whilst incentive of failure did correlate negatively with probability of failure this correlation was invariably rather weak ( - 0.24 across the two populations studied here). More interestingly, the mulitple regression analyses gave If a positive weighting. When included in the ‘approach’ side of the equation a slightly better prediction of career choice was made.

The comparison between the Is of Atkinson’s model and the Vj of Vroom’s showed the failure on the part of the latter to include an adequate representation of the degree of sex-typing present in an occupation. The design of the experiments used to test expectancy-valence theory have minimized the importance of this since the occupations studied (i.e. included as possible choices for the subjects) are often narrow and restricted to the area of choice thought appropriate to the subjects. Thus, sex- inappropriate choices are not included. Whilst this measure of valence may represent a meaningful model of such narrow decisions it does not explain sex-differential choices. Consequently, when included in the multiple regression analyses of the present study the valence measure received a low beta weight when compared with the single measure of incentive. The latter would appear best conceptualized as a function both of the valence and of an additional sex-typing component which further boosts or deflates the resultant value.

Achievement motives and occupational choice

The findings of previous studies that high achievement oriented (Ms > M f ) subjects are more likely to make intermediate difficulty choices than low achievement oriented (Ms Mf) subjects were found to be more complex in the present setting. In laboratory tests of this hypothesis subjects are told the probability of success by the experimenter, or it is simply determined as in the distance stood from the goal in the ring-toss game. However, in the more complex situation of occupational decisions there are few such objective criteria for establishing probabilities. Subjects are likely to appreciate the

342 K. Janman

important effects of individual differences in ability, qualifications, personality etc. when considering how likely they are to succeed at an occupation, as well as such external forces as job availability, the current state of the employment market etc.

For the more objective measure of probability considered, socio-economic status, subjects who were high achievement oriented tended to choose intermediate status occupations when compared with low achievement oriented subjects who tended to choose more low status occupations and to a lesser extent, more high status occupations. These results directly support those of Atkinson and Litwin (1960) and suggest that a knowledge of a subject’s achievement motives do enable a better understanding of their occupational choices. However, the previous finding that their inclusion in the predictive equation did not increase the predictive success appeared to represent something of a contradiction. The solution lay in the results of the second test of the risk choices made by high and low achievement oriented subjects; that which took a subjective measure of probability. Together with the relevant analysis of variance this showed that high achievement oriented subjects had lower probabilities of success than low achievement oriented subjects for low status occupations, but higher probabilities for high status occupations. Similar results were found for the incentive value of success such that high achievement oriented subjects had higher incentives for high status occupations than did low achievement oriented subjects whilst the reverse was true for low status occupations. This then illustrates how an individual’s achievement orientation can affect his or her career choices, and in particular why high achievement oriented individuals tend to choose higher status occupations than do low achievement oriented individuals (McClelland, 1961).

The success of career choice models which do not measure motive factors (e.g. expectancy-valence models) does not therefore mean that such factors are unimportant in understanding occupational choice. The studies reported here have shown that such models, without recognizing it, have unavoidably included such influences when measuring expectancies and valences. Such findings add another important dimension to other understanding of how occupational decisions are made.

Sex differences in career choice

The second study, looking at the occupational choices of school pupils, showed very strong sex differences in the first choices made by subjects, with a high degree of sex-typing in occupations assigned as first choice. What was even more striking was that, given an open-ended question about career plans 50 per cent of the males confined their expecatations to a selection of one out of seven occupations, whereas 50 per cent of the females confined their expectations to one of three occupations. The three occupations most often chosen by males were builder, designer and mechanic. The reason for the somewhat surprising popularity of designer with the males, both in the forced choice and in the open choice situation became clearer in the open-ended question of occupational intentions. In the free choice question, for the males ‘designer’ tended to accompany such careers as architect, builder, technical drawing and landscaping. However, for the females it was more often associated with hairdressing, artist and fashion designing. Thus it appears that the term ‘design’ may have been differentially interpreted by the sexes.

The findings from this study support those of other researchers who have found that occupational choices differ between the sexes at all age levels (Currie, 1982;


Feather and Said, 1983). The finding that males showed more variety in their choices than the females supports the findings of a number of studies ranging from those among elementary school pupils (Looft, 1971) to secondary school students (Bain and Fottler, 1980; Siegel, 1973). The larger percentage of females that did not yet know which occupation they would follow suggests that the males were more aware of a necessity to make career decisions and were more advanced in this decision process than were the females.

Whilst the males and females did not differ significantly in their motive to succeed scores, there was a significant difference between their motive to avoid failure scores with the females typically scoring higher than males. This is compatible with the literature which shows high motive to avoid failure or anxiety scores for females (Hill and Sarason, 1966) and suggests an important area of research for understanding female achievement. More specifically, it has already been shown in this study that an individual’s motive factors can significantly affect his or her occupational choices. If females typically score higher on fear of failure than males then more will fall into the low achievement oriented group who tend to choose lower status occupations.

Further sex differences were found in the four situational components of Atkinson’s equation. Whilst males and females did not differ in their expectations of success and failure over all occupations, there was a significant interaction such that males gave higher probabilities of success and lower probabilities of failure than females for male sex-typed occupations, whilst the reverse was true for female sex-typed occupations. These results support the suggestion made by some researchers that sex- role relatedness of the task should be considered when assessing expectancies (Stein, Pohly and Mueller, 1971: Deaux and Emswiller, 1974; Lenney, 1977). The emerging literature on ‘self-efficacy’ as a major factor governing women’s occupational choices (Hackett and Bett, 1981) is beginning to support this supposition.

Similar interactions between sex of subject and the occupation being considered were found for the incentive value components of the equation. Thus, in the same way that an individual’s achievement motives influence the probabilities and incentives of occupations according to their status, an individual’s sex seems similarly to influence the probabilities and incentives of occupations according to the extent to which that occupation is sex-typed. Females perceive themselves as more likely to succeed at, and give a higher incentive value to, those occupations traditionally chosen by women. Possible reasons for the higher incentives come from research which has shown that girls rate highly helping others, working with people and combining career and family. Boys conversely, rate more highly freedom from close supervision, high prestige, high income and a stable, secure future (Beswick, 1975; Siegfried and MacFarlane, 1981). Such differences seem to be reflected in the incentive given to an occupation since those occupations which allow expression of the factors that females rate as important are most often found in the occupations that they choose e.g. nursing, teaching etc. This supports the criticism that defining incentive value in terms of expectancy is far too narrow and that this has:

‘Severely limited the explanatory power of the one factor that is most clearly linked to gender role socialization’ (Parsons and Goff, 1980).

Incentive values were very much affected by the sex of the subject and the degree of sex-typing of the occupation. Indeed, as described earlier in this discussion, this

344 K. Janman

influence may best be considered separately from valence measures that also, but not solely, contribute to the incentive value. If an occupation is opposite sex-typed to the individual this appears to dramatically reduce the resultant incentive value even if the occupation contains many of the factors which an individual would otherwise consider very important. This leads to another possible criticism of both Atkinson’s restricted definition of incentive value and of the valence measure of expectancy- valence models. In both, the incentivehalence is seen to be determined purely by the positive consequences associated with success. The recent move of the fear of success literature away from a motivational and towards a situational explanation of female underachievement has illustrated that an equally important component of the incentive value of success for a female may be the negative components that she expects to accompany certain success.

In the sense that fear of success may now best be defined as a set of

‘realistic expectancies about the negative consequences of deviancy from a set of norms’ (Condry and Dyer, 1976)

it may be envisaged that, as a result of these expectancies, women have lowered incentives for occupations traditionally viewed as inappropriate for women.

An important outcome of this definition is that the concentration of the fear of success research upon females may represent only half of the picture. Instead it should be viewed as an explanation of the sex-typed choices of both men and women. Thus the incentive values of males considering traditionally female occupations are as likely to be depressed due to concern about a loss of masculinity and rejection by peers and members of the opposite sex, as are those of females considering traditionally male occupations. Such lowered incentives were very evident in the second study.

A recent move to a more comprehensive representation of task value can be found in the model of achievement proposed by Eccles et al. (1984). The inclusion of ‘cost’ defined by these authors as: ‘what is lost, given up, or suffered as a consequence of engaging in a particular activity’ (p. 29) is similar to the negative consequences of success which have been discussed above. Costs, such as effort and time lost from other activities have been shown to be important considerations in students’ choices regarding mathematics. However, the findings of the present studies point to the possibly more significant factor of fears of loss of femininity/masculinity and/or social rejection expected as a result of engaging in opposite sex-typed occupations. The inclusion of such influences in models of achievement and occupational choices is clearly important if such choices are to be accurately understood and predicted for both males and females.

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of fear of success’, Psychological Bulletin, 6: 932-946.

Deux expkriences, dont le but est de rtpondre P certaines questions concernant le modkle de la motivation la rtussite (‘achievement motivation’) de Atkinson, sont rapportks. Premibement , avec quelle prtcision la thbr ie peut-elle predire le choix professionnel de deux populations diffbrentes et quels changements, P supposer qu’ils soient necessaires, doivent Stre apporth au modkle pour le rendre plus prtdictif. Differentes erreurs conceptuelles qui, dans sa forme actuelle, rendent la thtorie inapte P la prddiction des choix professionnels, sont mises en evidence et des suggestions sont faites pour y apporter des corrections. Deuxitmement, une comparaison est faite entre le modtle d’Atkinson et les moddes de la ‘valence attendue’ (‘expectancy-valence’) couramment utilists pour dkcrire et prMire la prise de decision professionnelle. En particulier, la dimension ‘d’incitation’ du modtle de Atkinson est comparke B la mesure de la valence dtcrite par les modtles de la ‘valence attendue’, et les influences possibles de facteurs motivationnels (motivation P la rkussite et motivation P kviter I’erreur) sont prises en considtration, puisque celles-ci sont couramment negliges dans les autres modkles sur le choix de carrihe. Finalement, I’existence de differences en fonction du sexe dans le choix professionnel, ainsi que dans les difftrentes composantes du modtle, est ttudide et discutde. Un changement dans la conceptualisation de la ‘peur du succts’ est aussi inclue dans cette considtration.

achievement motivation theory and occupational choice

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