Person-Environment Congruence as a Predictor of Customer Service Performance

Journal of Vocational Behavior 54, 59 –70 (1999) Article ID jvbe.1998.1645, available online at http://www.idealibrary.com on

Person-Environment Congruence as a Predictor of Customer Service Performance Barbara A. Fritzsche University of Central Florida

Amy B. Powell Psychological Assessment Resources, Inc.

and Russell Hoffman American Motivation Center Within the framework of Holland’s theory, we examined the use of person-environment congruence in predicting job performance for a sample of customer service representatives. It was predicted that: (1) Congruence scores based on specific environment classification derived by job analytic methods would correlate more highly with performance than congruence scores based on a more general environmental classification; (2) Congruence and cognitive ability would correlate with different aspects of performance (task v. contextual performance); and (3) Congruence scores would significantly relate to job performance, whereas interest test scores would not. No support for the first hypothesis was found. Instead, there were no significant differences between the environment typing methods, and congruence predicted Quality performance ratings. Partial support was found for the second and third hypotheses. Congruence was significantly correlated with task-related ratings, whereas cognitive ability was not significantly correlated with any performance ratings. In addition, none of the three relevant interest test scores (Conventional, Social, and Enterprising) were significantly correlated with performance. A significant negative correlation was found, however, between performance ratings and Investigative interest scores, suggesting a need for personenvironment fit indices to take into account all six interest scores. Overall, this study provides some evidence that person-environment fit, when guided by theory, may be a useful predictor of job performance. © 1999 Academic Press

An earlier version of this paper was presented at the 12th annual conference of the Society for Industrial and Organizational Psychology (April, 1997), St. Louis. The authors thank John L. Holland and Gary D. Gottfredson for their comments on an earlier draft of this paper. Address correspondence and reprint requests to Barbara A. Fritzsche, Department of Psychology, University of Central Florida, PO Box 161390, Orlando, FL 32816-1390. 59 0001-8791/99 $30.00 Copyright © 1999 by Academic Press All rights of reproduction in any form reserved.

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Person-environment fit has been of great interest to researchers and practitioners because of its expected relation with work outcomes such as job satisfaction, psychological and physical health, coping and adaptation, motivation, performance, absenteeism, turnover, and vocational choice. Most studies of personenvironment fit have focused on matching the desires of the individual (e.g., interests, preferences, and values) with what the environment supplies (e.g., job, organizational, and occupational characteristics). These studies have generally found that fit is positively related to job satisfaction. In other words, individuals’ needs are satisfied by person-environment fit. However, less is known about the relation between matching the person with organizational demands and how that relates to criteria such as job performance (Edwards, 1991; Hogan & Blake, 1996; Kristof, 1996). According to Edwards (1991), most studies examining the relation between person-environment fit and job satisfaction have been based on Holland’s (1966, 1973, 1985, 1997) theory of vocational personalities and work environments. According to Holland, individuals and work environments can be described in terms of six personality types: Realistic, Investigative, Artistic, Social, Enterprising, and Conventional. Positive work outcomes are more likely to occur when persons are in environments that offer activities, values, and roles that are consistent with their vocational personalities. Work outcomes suggested include choice of vocation, job changes, vocational achievement, personal competence, and educational and social behavior (Holland, 1997). However, both Edwards and Kristof (1996) have argued that interests, as measured by Holland’s theory, should not relate to performance. Instead, a match between individuals’ abilities and organizational demands should relate to performance. Edwards and Kristof are not alone in this view. In fact, contributors to both the Handbook of Industrial and Organizational Psychology and the International Review of Industrial and Organizational Psychology have concluded that interests “ . . . take a backseat to abilities, which are still the best predictors of satisfactoriness” (Dawis, 1991; pp. 853) and “Existing evidence does not support the use of interest inventories for personnel selection in the sense of predicting job performance” (Schmitt & Noe, 1986; p. 79). In the past, similar conclusions have been drawn (e.g., Guion & Gottier, 1965) regarding the value of personality measures in personnel selection. However, the recognition that job performance is multidimensional and that different predictors are expected to predict different aspects of performance (Campbell, 1990) has led to the understanding that personality measures can be more useful in selection than was generally thought 30 years ago (Guion, 1987; Tett, Jackson, & Rothstein, 1991). Although interests and personality are often discussed separately (e.g., see Schmitt & Noe, 1986), Hogan and Blake (1996) acknowledge that, “virtually all the major players have, at one time or another, suggested that inventoried interests are manifestations of a more basic set of personality characteristics.” (p. 93). Holland (1966, 1973, 1985, 1997) is no exception. His theory states that a

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person’s interests and competencies create a personal disposition or personality pattern, and that career choices are expressions of personality. In fact, the correspondence between Holland’s theory and the five-factor model of personality has been established empirically (e.g., Ackerman & Heggestad, 1997; Costa, McCrae, & Holland, 1984; Gottfredson, Jones, & Holland, 1993; Hogan & Hogan, 1993; Holland, Johnston, Asama, & Polys, 1994; Tokar & Swanson, 1995). These authors indicate that the five-factor model and Holland’s theory relate in predictable ways (e.g., Social and Enterprising vocational personalities relate to Extraversion), but the correlations are not high enough to conclude that the five-factor model and Holland’s theory are interchangeable (Gottfredson, Jones, & Holland, 1993; Hogan & Blake, 1996). Like other personality measures, interest inventories may also be more useful in predicting performance than is currently thought. If performance is recognized as multidimensional, predictions and measures are based on theory, and more attention is paid to measuring the environment code, then findings may be more positive. The present study addresses these three concerns by using dimensional ratings of performance, measures of person, environment, and fit that are consistent with theory, and a job analytic method for measuring the environment code. Regarding the multidimensional nature of performance, Hogan and Blake (1996) argued that interests may relate more to performance ratings than to objective performance dimensions. This is because raters tend to take a more global view of performance than is indicated by job analytic results and raters may be influenced by individuals’ interests. Hence, significant correlations between fit and performance may result when raters judge performance and when various aspects of performance are judged. In addition, choice of person-environment fit measure should be guided by theory. Several studies of the interest-performance relation did not use a measure of fit. Instead, they used interest scores themselves (e.g., Dyer, 1987; Reeves & Booth, 1979). Others have used measures of fit that, to be consistent with Holland’s terminology, are called “congruence indices.” Numerous ways of measuring congruence have been proposed (e.g., Brown & Gore, 1994; Iachan, 1984, 1990; Miller, 1992; Sutherland, Fogarty, & Pithers, 1995), but only a few of them, such as the Kwak and Pulvino (1982) index and Brown and Gore’s (1994) C-Index, are consistent with Holland’s notion that interest areas are structured in a hexagonal pattern (Brown & Gore, 1994; Camp & Chartrand, 1992; Lent & Lopez, 1996). Finally, more attention should be given to the measurement of the environment code. Typically, the person code is measured by using a well-established interest inventory. The environment code, however, is often established by using translations of occupations from the Dictionary of Occupational Titles (DOT) into Holland Codes. For example, Gottfredson and Holland (1989) have published Holland Codes for every occupation listed in the DOT, but the codes provided in the Dictionary of Holland Occupational Codes (DHOC) are predicated on the

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assumption that the job under study is similar in fundamental ways to the DOT description chosen. In response to the need for a reliable, valid, and practical measure of the environment code, Gottfredson and Holland (1991) developed the Position Classification Inventory (PCI). The PCI provides a Holland Code for an environment by having subject matter experts respond to 84 items about the activities, skills, abilities, and personal characteristics required by the work environment. Hence, it is a job-analytic technique for establishing the environment code, and it is designed to parallel interest inventory measures of the person code (Austin, 1993). In his review of the PCI, Austin suggests that further validation of the PCI should consist of establishing correlations between congruence and work outcomes using the PCI. The present study used job analytic results to examine the concurrent validity of person-environment congruence and job performance dimension ratings in a sample of customer service representatives. In addition to interests, measures of the five-factor model and cognitive ability were also included. The following hypotheses were proposed: Hypothesis 1. Congruence scores based on specific environment classification derived by job analytic methods will correlate more highly with performance than congruence scores based on a more general environmental classification. Hypothesis 2. Congruence and cognitive ability will correlate with different aspects of performance. Congruence scores will correlate significantly with contextual performance ratings (Conduct), whereas cognitive ability will correlate with task-related performance ratings (Quality). Hypothesis 3. Congruence scores will be related significantly to job performance, whereas interest test scores will not. METHOD Participants Participants were 90 customer service representatives (86% female) employed by a large, national insurance company that is based in the western U.S. Ages ranged from 20 to 51 years (M 5 28.78), and 81% of the sample had at least some college education. They had been working for the company from ,1 year to 8 years (M 5 1.3), and they had been working as customer service representatives from ,1 year to 20 years (M 5 4.1). Procedure Each participant completed a job analysis questionnaire, an interest inventory, a measure of the five-factor model 1, and a cognitive ability measure. Performance data were made available from employee records. Eight supervisors and the 1

The five-factor model measure will not be discussed, as it is not relevant to the testing of the hypotheses.

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customer service representatives participated as subject matter experts by completing the PCI for the customer service representative position. Instruments Position Classification Inventory (PCI). The PCI (Gottfredson & Holland, 1991) describes the environment according to Holland’s theory, and it yields a three-letter code (e.g., SIE) summarizing the combination of the Holland types the position most resembles. To complete the PCI, subject matter experts describe the demands, skills, and personal characteristics required by rating on a 3-point scale (Often, Sometimes, Seldom/Never) how often each of 84 items describes the position. For example, one PCI question asks, “What skills, abilities, or personal characteristics must be exercised by a person in this position?” and the subject matter expert rates a series of characteristics such as, “Manual skill” (Realistic), “Scholarship” (Investigative), “Originality” (Artistic), “Ability to deal with the public” (Social), “Assertiveness” (Enterprising), and “Clerical skill” (Conventional). Scoring consists of totaling responses for each RIASEC category. Across several samples of incumbents and supervisors, coefficient alphas ranged from .80 –.91 for the Realistic scale, .76 –.90 for the Investigative scale, .78 –.94 for the Artistic scale, .80 –.84 for the Social scale, .78 –.82 for the Enterprising scale, and .70 –.75 for the Conventional scale. Construct validity has been established by assessing the agreement between PCI code and the DHOC, an independent classification of occupations. Agreement between the high-point PCI code and the first-letter DHOC code has ranged from 41% to 89%. In general, higher agreement was found when more than one subject matter expert completed the inventory. Validity has also been established by correlating supervisors and incumbents ratings. Convergent correlations ranged from .58 to .79 and discriminant correlations (as expected for hexagonally-opposite environmental types) ranged from 2.60 to .12 (Gottfredson & Holland, 1991). Self-Directed Search (SDS). The SDS (Holland, 1994) was used to assess the vocational interests of the person. The SDS describes the person according to Holland’s theory and also yields a three-letter code which summarizes his/her primary interest areas. The SDS includes 228 items that measure Activities (what you would like to do), Competencies (what you can do well), Occupations (the types of work that appeal to you), and ability Self-Estimates (how you see yourself in comparison with others). Scores are calculated by summing the number of endorsements for each interest area, and a 3-letter summary code is derived based on the highest 3 of the 6 scores (Holland, Powell, & Fritzsche, 1994). Numerous studies have been conducted in support of the reliability and validity of the SDS (see Holland, Fritzsche, & Powell, 1994 for a summary). Recent data collected on the 1994 edition found that internal consistency estimates (KR-20) ranged from .72 to .94, and test-retest reliability estimates (over a 4 to 12 week interval) ranged from .76 to .89. As a test of validity, correspon-

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dence between SDS high-point codes and one-letter aspiration codes was examined, and an overall hit rate of 54.7% was found. In addition, correlations ranged from .75 to .89 between the summary scales of the 1985 and 1994 editions of the SDS. Hence, some support was found for the equivalence of the latest version of the SDS and the prior version. Wonderlic Personnel Test. Cognitive ability was measured using the Wonderlic Personnel Test (Wonderlic, 1992), a timed, 50-item, paper-and-pencil measure of general cognitive ability designed specifically for use in personnel selection. In almost 60 years of use, this measure has also accumulated considerable reliability and validity evidence to support its use. Test-retest correlations have ranged from .82 to .94, and alternate forms reliability coefficients have ranged from .73 to .95. One way validity has been examined is by correlating the Wonderlic with the Wechsler Adult Intelligence Scale Full Scale IQ score. Correlations ranging from .91 to .93 have been found. In addition, meta-analytic findings suggest a correlation as high as .63 between Wonderlic test scores and pre-employment and admissions selection decisions (Wonderlic, 1992). Congruence Indices. Because they are consistent with Holland’s theory that interests are structured in terms of a hexagon, the Kwak and Pulvino Index (K-P; Kwak & Pulvino, 1982) and the Brown and Gore Congruence Index (C; Brown & Gore, 1994) were calculated to assess person-environment congruence. The K-P index incorporates correlations among Holland types, and it also weights matches between person and environment that occur in the first letter codes as twice that of matches in the second letters and four times that of matches in the third letters. Scores range from 21 to 1, and higher scores indicate greater congruence. Because the K-P index is somewhat mathematically complicated, Brown and Gore developed the C-Index. The C-Index weights first letter agreement by three, second letter agreement by two, and third letter agreement by one. Then, scores are given to each comparison depending on their hexagonal distance (i.e., 3 5 identical person and environment letters to 0 5 opposite hexagonal person and environment letters). C-Index scores can range from 0 to 18, and higher scores indicate higher congruence. Performance Ratings. Three types of supervisory performance ratings were obtained: (1) Quality. Based on individual call audits, this dimension included telephone techniques/communication skills; job knowledge; and paperwork returned from customers due to errors; (2) Productivity. Based on objective measures of performance, this dimension included talk time (seconds/call) and after-call processing (minutes/call); and (3) Conduct. Based on supervisor observations, this dimension included attendance/punctuality; professional behavior, maturity, and self-control; teamwork; and showing initiative. To facilitate the reliable observation of performance, supervisors used behavioral checklists that were designed specifically for the customer service position. However, the reliability and validity of the performance measures has not been demonstrated.

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RESULTS The means and standard deviations of the PCI scores for the customer service position were: Realistic (M 5 2.71; SD 5 2.04), Investigative (M 5 4.22; SD 5 2.81), Artistic (M 5 3.00; SD 5 2.46), Social (M 5 10.45; SD 5 1.87), Enterprising (M 5 5.16; SD 5 3.10), and Conventional (M 5 9.45; SD 5 2.32). These means yield a PCI summary code of SCE (Social-ConventionalEnterprising). The DHOC, on the other hand, listed a summary code of CES for the customer service representative job. Hypothesis 1 postulated that higher congruence-performance correlations would be found for the SDS-PCI congruence indices than for the SDS-DHOC congruence indices. As seen in Table 1, the C-Index was significantly correlated with rated performance Quality, regardless of whether the PCI or DHOC environment codes were used (r s 5 .23 and .22, respectively). The K-P index, on the other hand, was not significantly correlated with any of the performance dimensions. Hotellings t tests were calculated to determine if the correlations between each performance dimension and the respective SDS-PCI and SDS-DHOC indices were significantly different. No significant differences were found, indicating no superiority of the PCI code in predicting performance. Hypothesis 2 postulated that person-environment congruence and cognitive ability would be related to different performance dimensions. Specifically, it was TABLE 1 Means, Standard Deviations, and Intercorrelations for the Scales, Congruence Indices, and Performance Criteria SDS Scale Self-Directed Search Realistic Investigative Artistic Social Enterprising Conventional SDS-PCI Congruence Kwak-Pulvino C-Index SDS-DHOC Congruence Kwak-Pulvino C-Index Wonderlic Performance Criteria Quality Productivity Conduct

R

I

A

SDS-PCI

M

SD

S

E

C

K-P

10.21 14.18 17.41 22.02 19.39 19.02

7.18 7.56 8.17 6.26 7.58 7.79

47 36 19 37 34

45 39 44 18

39 50 08

64 26

47

.44 10.58

.25 3.31

215 216

205 217

206 206

27 21

07 14

10 14

91

.39 9.69 21.13

.25 3.79 6.24

206 204 02

223 229 11

226 239 07

218 210 06

07 13 09

03 17 202

42.70 21.04 18.07

4.99 6.89 2.38

211 201 208

227 203 208

214 220 210

06 204 08

06 201 201

09 20 14

SDS-DHOC

C

K-P

C

259 237 203

244 226 201

89 203

203

16 207 203

23 202 207

17 17 12

22 21 12

Performance W

16 13 13

Q

P

C

15 38

04

Note. Ns ranged from 81 to 90, due to missing data. Decimal points were omitted. Correlations greater than 6.21 were significant at p , .05.

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expected that congruence would relate to Conduct ratings and cognitive ability would relate to Quality ratings. Congruence did not significantly correlate with Conduct ratings (rs ranged from 2.07 to .12), and Wonderlic scores did not correlate with Quality ratings (r 5 .16). Wonderlic scores were not significantly related to any of the performance dimensions, but congruence scores correlated significantly with Quality performance ratings. Hence, weak support for this hypothesis was found. Hypothesis 3 postulated that person-environment congruence would relate to job performance, whereas interest test scores would not. Table 1 reveals that although Social, Conventional, and Enterprising (S,C, and E) were identified as important interest areas for the job, none of the correlations between performance ratings and the C, S, or E interest scores were significant (r s ranged from 2.04 to .20). Unlike any of the relevant interest areas, the C-Index was significantly correlated with Quality performance ratings when either the PCI or DHOC environment code was used (r s 5 .23 and .22, respectively). In addition, the SDS-DHOC congruence correlation was .21 ( p 5 .057). Interestingly, however, an interest area not expected to be highly related to performance, Investigative, was significantly negatively correlated with Quality performance ratings (r 5 2.27). Overall, these findings indicate partial support for the hypothesis. DISCUSSION The present study provides a test of the usefulness of person-environment congruence in predicting performance in a sample of job incumbents. The results indicated no superiority of the PCI-derived over the DHOC-derived environment code in predicting performance. In fact, both codes identified the same top-three interest areas for the customer service representative job, but in different orders. In another study, Lent and Lopez (1996) found identical environmental codes when they compared the DHOC to a more direct environmental assessment, even though the jobs studied seemed different from the DOT description. Both our findings and the findings of Lent and Lopez suggest that the DHOC provides useful environmental codes. In partial support for the second hypothesis, cognitive ability and congruence did not relate to the same performance ratings. Cognitive ability did not relate to any performance dimension whereas congruence was related to Quality ratings. It is unclear why cognitive ability did not relate to performance, especially given the ample evidence that cognitive ability predicts performance across a wide range of jobs (e.g., Hunter & Hunter, 1984). It is interesting that congruence did relate to Quality ratings, though, as Hogan and Blake (1996) argue that interests may relate to performance ratings (as opposed to objective performance measures) because supervisors’ perceptions of person-environment fit may influence their ratings. An examination of the relation between interests, cognitive ability, subjective ratings, and objective performance measures could help clarify these findings. Without such an examination, and because little is known about the reliability of the performance measures, the possibility that these results were due

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to criteria unreliability cannot be ruled out. In fact, Conduct was the most subjective of the performance ratings, and neither predictor related to these ratings. It is unclear what effect criterion-related measurement problems may have had on the results. There was also partial support for the third hypothesis that congruence would relate to performance, and interest test scores would not. These findings are interesting because previous research that found little relation between interests and performance have only examined interest test scores rather than congruence. Caution should be taken in interpreting these results however, because the reliabilities of the criteria have not been established, the statistically significant correlation was small, and the sample was relatively small and homogeneous. It is also interesting to note the significant negative correlation between performance and Investigative scores. Lack of interest in investigative activities appears important for job success in customer service. The implication is that, for selection contexts, person-environment congruence indices should be developed that more directly take into account congruence between the lower three RIASEC scores. Of course, DHOC-based environment codes only report the top three interest areas, but the ordering of all six scores are generated when the PCI is used. It is important to evaluate the results of the present study within the context of existing research on Holland’s theory. Like other researchers (e.g., Lent & Lopez, 1996; Young et al., 1998), the current study found that the Kwak-Pulvino and C-Indices were highly correlated (rs 5 .89 and .91). In addition, the results of this study suggest no clear superiority of either the Kwak-Pulvino or C congruence indices in predicting performance. Although previous studies have not been found that evaluate the congruence-performance relation, numerous studies have examined the relation between various congruence indices and job satisfaction. Two meta-analyses (Assouline & Meir, 1987; Tranberg, Slane, & Ekeberg, 1993) suggest that the congruence-satisfaction correlation is small and not significantly greater than zero (overall mean r s 5 .21 and .20). In addition, tests of various congruence indices in predicting satisfaction among college students and employed adults indicate similar or even lower correlations, regardless of congruence index used (Camp & Chartrand, 1992; Lent & Lopez, 1996; Young et al., 1998). These congruence-satisfaction correlations are similar to the correlations found in the present study, which suggests little support for Holland’s congruence hypotheses. It is interesting to note that Young et al. found different congruencesatisfaction correlations depending on Holland person and environment code. Specifically, they found negative correlations for Conventional persons and persons working in Artistic environments. They also found the highest positive correlations for persons working in Investigative and Enterprising environments. Because the present study only investigated persons from one job, and many of these persons had Conventional high-point codes, additional

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studies of the congruence-performance relationship are warranted before drawing firm conclusions. One additional concern about the present study relates to the use of the SDS to derive the person code. Edwards (1991) argues that, because the SDS measures both interests and competencies, one cannot interpret SDS codes as interest scores, alone. This is particularly problematic when trying to distinguish between the person-environment fit obtained by matching the desires of the individual with what the environment supplies versus that obtained by matching the abilities of the individual with the demands of the environment. Additional studies should use alternatives to the SDS, such as the Vocational Preference Inventory (Holland, 1985), that do not confound interests and competencies. Additional research is needed to determine whether these results generalize to other samples and jobs, using various measures of person and environment code. More attention should be given to criterion development, and predictive (as opposed to concurrent) validity designs should be used. Larger sample sizes are needed to provide confidence in the stability of the correlations and to enable the test of additional hypotheses (e.g., the examination of potential mediators as described by Hansen, 1994 and potential moderators as described by Young et al., 1998). Despite the homogeneity and size of the sample, congruence was a significant predictor of performance in this study whereas the relevant interest scores themselves were not. Hence, this study suggests a need to further examine the intuitively appealing proposition that people will be successful when their interests match the requirements of the position. REFERENCES Ackerman, P. L., & Heggestad, E. D. (1997). Intelligence, personality, and interests: Evidence for overlapping traits. Psychological Bulletin, 121, 219 –245. Assouline, M., & Meir, E. M. (1987). Meta-analysis of the relationship between congruence and well-being measures. Journal of Vocational Behavior, 31, 319 –332. Austin, J. T. (1993). Gary D. Gottfredson’s and John L. Holland’s Position Classification Inventory (Form HS) [Test Review]. Measurement and Evaluation in Counseling and Development, 26, 206 –208. Brown, S. D., & Gore, P. A., Jr. (1994). An evaluation of interest congruence indices: Distribution characteristics and measurement properties. Journal of Vocational Behavior, 45, 310 –327. Camp, C. C., & Chartrand, J. M. (1992). A comparison and evaluation of interest congruence indices. Journal of Vocational Behavior, 41, 162–182. Campbell, J. P. (1990). Modeling the performance prediction problem in industrial and organizational psychology. In M. D. Dunnette & L. M. Hough (Eds.), Handbook of Industrial and Organizational Psychology: Vol. 1. (2nd ed., pp. 687–732). Palo Alto, CA: Consulting Psychologists Press. Costa, P. T., McCrae, R. R., & Holland, J. L. (1984). Personality and vocational interests in an adult sample. Journal of Applied Psychology, 69, 390 – 400. Dawis, R. V. (1991). Vocational interests, values, and preferences. In M. D. Dunnette & L. M. Hough (Eds.), Handbook of Industrial and Organizational Psychology: Vol. 2. (2nd ed., pp. 833– 871). Palo Alto, CA: Consulting Psychologists Press.

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