Symposium/Forum

TITLE

Acuity Theory: A study of two faking resistant non-cognitive measures

ABSTRACT

This paper describes a new method of non-cognitive measurement that doesn’t involve introspective

self report. We manipulated level of incentive (within and between group design) to motivate a sample

of Spanish sales incumbents to maximize their scores. We found criterion-related validity only under

incentivized conditions and show resistance to faking.

PRESS PARAGRAPH

The theory of cognitive acuity proposes that the more one possesses any mentally held characteristic

the more one will be sensitive to phenomena that represent that characteristic. Sensitivity is measured

by presenting pairs of contrasted phenomena (e.g., calibrated written statements) which are treated as

signals to be detected. This paper describes this method of non-cognitive measurement that doesn’t

involve introspective self-report. We manipulated level of incentive (within and between group) to

motivate a sample of Spanish sales incumbents to maximize their scores. We found criterion-related

validity only under incentivized conditions and show resistance to faking.

WORD COUNT

2896

The problem of faking on non-cognitive measures continues to be a concern for both

researchers and practitioners alike. Studies examining the causes and consequences of faking

behavior proliferate in the social sciences. At the most basic level, Snell and Sydell (1999)

proposed that faking behavior is a function of 1) the applicant’s ability to fake and 2) the

applicant’s motivation, tendency, or propensity to fake. These authors point out that motivation

to fake may be related to individual traits, demographic characteristics, and perceptual factors.

However, the motivation to distort ones responses on a measure in order obtain a more desirable

score would seem to be a rational and fundamental test-taking impetus and one which all high

stakes test takers would likely share especially as the rewards of test performance increase. This

study presents an experimental non-cognitive testing method and manipulates the degree of test-

taker-motivation (TTM) by varying the test performance reward using a monetary reward and a

within and between subjects research design. We aim to criterion-validate this method and show

how incentivizing test performance improves rather than degrades criterion-related validly.

TTM Background

Arvey, Strickland, Drauden, and Martin (1990) described TTM as, “the extent to which

respondents demonstrate effort, diligence, and focus in writing a test.” These authors also

describe research suggesting that that levels of TTM vary between applicants and incumbents

and that those differences could be related to test validity and test performance. Avery and

colleagues also report that when incumbents were compared to applicants, the applicants showed

higher test-taking motivation and excreted more effort to answer correctly even after controlling

for the effects of ability level.

It is widely known that low-stakes testing often leads to a lower effort from the test-taker

(Wise & DeMars, 2005). If participants feel that there is nothing to gain from the test, they won’t

be motivated to take the test and their scores may not serve as valid indicators of their true level

of the construct of interest (Sundre, 1999; Sundre & Kitsantas, 2004; Wise & DeMars, 2005).

Most of the research conducted on low-stakes testing and TTM suggests attempting to increase

examinee motivation (Wise, Bhola, & Yang, 2006) and filtering out examinees with low

motivation (Sundre & Moore, 2002; Wise & Kong, 2005; Wise, Wise, & Bhola, 2006) are

possible ways to reduce construct-irrelevant variance. O’Neill, Goffin, & Gellatly (2010)

maintained that, “motivated test-takers might be inclined to distort or ‘fake’ their responses to

achieve personal ends” and suggest that higher TTM will result in higher validity. If it were

possible to measure non-cognitive constructs in a similar way as cognitive constructs then we

might capitalize on test takers motivation set to improve test validity.

The theory of cognitive acuity

The theory of cognitive acuity postulates that 1) the more one possesses any mentally held

construct (e.g., extroversion), the more one will be sensitive to distinctions in construct-representative

phenomena (e.g., objects, statements, events) and 2) that we can measure the degree to which one

possesses any mentally held construct by presenting construct –representative phenomena of various

magnitudes of construct-representative signal strength and observe how sensitive (i.e., acute) the

respondent is to these distinctions. The more acute one is, the more he/she is likely to possess the

construct and manifest it behaviorally (e.g., job performance). For example, because of his/her greater

exposure to extroversion phenomena (e.g., participating in social events), an extrovert is expected to be

more attuned to the difference between the following two statements—“An extrovert enjoys loud

parties” versus “An extrovert enjoys being with friends”. Acuity theory treats these statements as

construct-relevant signals which are differentially detectable depending on one’s possession of the

construct. Another example using the customer service orientation (CSO) construct would be to present

the following two statements.

“A true CSO person thinks about past interactions with customers”

“A true CSO person puts the customer’s needs above the need to make a sale”

The more one possesses the CSO construct the more sensitive he/she will be to the fact that one of

these statements was rated by construct saturants (those highly possessed of their respective

constructs, i.e., strong extroverts) as a stronger representation of the CSO construct than the other.

Note that no introspection is called for in deciding which is the stronger CSO- representative statement

and thus we minimize respondent’s reliance on introspection which is prone to distortions and biases

(Nisbett & Wilson, 1977; Pronin, & Kugler, 2007).

CSO and Extroversion

Evidence for the criterion-related validity of CSO measures has been provided by a meta-analysis

conducted by Frei and McDaniel (1998) who, after a review of 41 studies, reported an unadjusted

validity coefficient of r = .24 when supervisory performance ratings were the criteria. Likewise, the

personality trait of extroversion has frequently been studied as an important construct for effective

sales worker performance (Hausknecht and Langevin, 2010). Barrick and Mount (1991) conducted a

meta analysis involving 2,316 subjects across 22 studies and report a mean correlation of r = .09

(estimated true correlation = .15 ) between extroversion and performance criteria. In a 1998 meta-

analytic review by Vinchur, Schippmann, Switzer, and Roth report an average unadjusted criterion-

correlation of r = .09 between extroversion and sales performance.

Recently, Grant, (2013) examined the extroversion-sales performance relation in the extant

literature and proposed that ambiverts, those who demonstrate a more flexible pattern of talking and

listening, are more apt to be the better performers and posited an inverted U-shaped (-shaped)

relation between extroversion and sales performance. Grant (2013) went on to demonstrated that

among 340 call-center representatives, the addition of a quadratic extroversion term in the regression of

sales revenue on extroversion produced a significant effect showing that the relation is better modeled

as -shaped function.

Hypotheses

H1 Among the incentivized (but not the un-incentivized) samples, sales associates’ sensitivity to

contrasts in CSO representativeness among CSO statements will be significantly related to observed CSO

behavior (i.e., sales performance).

H2 Among the incentivized (but not the un-incentivized) sales associates’ sensitivity to contrasts in

extroversion representativeness among extroversion statements will be significantly quadratically (-

shaped) related to observed extroversion behavior (i.e., sales performance).

Method

Instrument Development

Based on a literature review of the respective constructors, a total of 123 extroversion

statements and 119 CSO statements were developed. These statements were written to range from not-

at-all representative of the respective constructs to extremely representative.

Statement construct-calibration survey development and translation

A survey was constructed for the extroversion and CSO constructs which was intended to collect

opinions from construct saturants as to the degree to which each statement was representative of its

respective construct. A five-point scale was used to rate representativeness and ranged between 1 - Not

at all representative to 5 - Extremely representative. We also developed a conventional self-report

measure of both CSO and extroversion to serve a control measure. Based on the construct/measure

review a 16-item extroversion and 15-itme CSO self-report measure were developed. Next we identified

a total of 15 construct saturants for both the CSO and extroversion statement construct-calibration

effort. The survey and conventional measures were professionally translated into Castilian Spanish and

administered to the saturants in order to calibrate our measures. Each of the statements in the

construct-calibration survey was rated by its respective saturant and thus it was possible to evaluate the

degree to which any statement garnered weak versus strong agreement from among the saturants who

rated it. Statement ratings were evaluated for consistency using Brown, Reagan and Hauenstein’s (2005)

coefficient of agreement aWG(1) (a variant of rWG ). Those response options producing aWG(1). < .80 were

removed from the analyses. The mean saturant rating of the surviving statements was used as the

estimate of that statement’s construct-representativeness. Surviving statements from both surveys

were next paired with other statements in their construct in order to form construct-representativeness

contrasts (i.e., signals to be detects) which would be used as the final test items for the CSO and

extroversion measures. For each construct a set of 100 pairs were selected to form two instruments

which were translated into Castilian Spanish.

Analysis Methods

Measurement of Acuity using Binary Logistic Regression Analysis (BLRA)

To test our hypotheses we first had to estimate how sensitive each respondent was to the

statement contrast signal magnitudes. The challenge was to model the respondent’s pattern of binary

signal detections (dependent variables) associated with the continuous statement contrast signal

magnitudes (independent variables). After much research and discussions with colleagues the authors

elected to use binary logistic regression analysis (BLRA) to estimate respondent’s sensitivity to the

contrast magnitudes.

Acuity Score Generation

When applied to each respondent’s set of binary responses (dependents) and continuous

independents (paired contrasts), the BLRA generates two parameter estimates which are relevant to our

measurement of extroversion and CSO statement contrast signal sensitivity.

Logistic beta weights (Beta). The BLRA resulting Beta weight (slope) is the natural log of the odds

ratio and represents the importance with which the respondent regarded the statement pair contrast in

his/her decision to select one option over the other and serves as an indicator of construct-relevant

sensitivity. We will denote these Beta weight scores as Acuity_CSO_Beta and Acuity_Extro_Beta

respectively.

Logistic chi square (χ2). The Pearson goodness-of-fit chi-square statistic tests the null hypothesis

that the person-specific model adequately fits the data and is regarded as a measure of the

respondent’s sensitivity as it captures the goodness of fit between the respondent’s pattern of

statement selection decisions and the pattern of statement contrast magnitudes. We will denote these

scores as Acuity_CSO_χ2 and Acuity_Extro_ χ2. These χ2 fit statistics are interpreted such that high

scores indicate poor fit and hence weak respondent acuity while low scores indicate good fit and strong

acuity.

As controls we also computed raw binary scores for each respondent based simply on the

proportion of correct versus incorrect signal detections. Thus,

Acuity_CSO_Raw_Score = the mean of the 100 binary acuity CSO items

Acuity_Extro_Raw_Score = the mean of the 100 binary acuity extroversion items

Conventional Score Generation

The following additional control scores were collected based on the previously discussed

conventional self report measures.

Self_Report_CSO_Score = the mean of the 5-point Likert scale 15-item CSO self-report measure

Self_Report_Extro_Score = the mean of the 5-point Likert scale 16-item extroversion self-report

measure

Participants

Sample One consisted of 285 Spanish general merchandise retail store sales employees who

were recruited from eight different department stores (in three different cities) within the company.

Participants were asked to volunteer to complete the predictor measures. Of this number 69 were males

and 213 were females with 3 being undisclosed. Their average age was 42.50 (S.D = 9.36). All

incumbents completed the measures while on company time.

Sample Two consisted of 56 incumbent employees including 12 males, 44 females, with an

average age of 40 (S.D = 7.92). Like Sample One, this sample was also recruited voluntarily from the

same general population and completed all measures. However, two weeks after completing the

measures, this subsample was asked to complete the measures a second time under an incentivized

condition in order to simulate a high stakes testing environment. In this condition the participants were

asked to perform their best on the test and were offered one of three 100 Euro gift certificates to be

awarded to the highest scorer.

Performance Measures

The supervisors of each of the participating employees rated that employee’s performance on

three dimensions using a 1-4 point scale with 1 = Low, 2 = Normal, 3 = Good, 4 = Excellent. The three

dimensions were;

1. Overall Rating: the global rating assigned to the sales representative

2. CSO Rating: "Treat kindly and knows how to adapt to the customer"

3. Sociability Rating: "Integrates with peers, maintaining a good working climate". The Sociability Rating

relates to one of the stronger aspects of workplace-relevant extroversion in Spanish retail environments

(Oviedo-García, 2007).

Results

No estimates of internal consistency reliability were available for the acuity scores because the

signal detection methodology presents different magnitudes of construct-relevant signal and saturant

agreement is perhaps the best measure of reliability.

To test H1 we used Spearman rank order correlations because much of the data were found to

be non-normal according to Shapiro-Wilk tests of each independent and dependent variable. Table 1

present the descriptive statistics and correlation coefficients for the conventional and acuity CSO

measures along with the criterion variables. Results show that only under incentivized conditions did the

Acuity_CSO_Beta significantly correlate with supervisors’ CSO Rating (r = .31, p < .05) but not with

Overall Rating (r = .23, NS) or Sociability Rating (r = .24, NS) although results are in the expected

direction. Again, only under incentivized conditions did Acuity_CSO_2 significantly correlate with both

supervisors’ Overall Ratings (r = -.28, p < .05) and Sociability Ratings (r = -.30, p < .05) but not to CSO

Ratings (r = -.18, NS). However, again, all effects were in the expected negative direction. Under the

incentivized condition the Acuity_CSO_Raw_Score was significantly related to Sociability Rating (r = .29,

p < .05) but not to Overall Rating (r = .00, NS) or CSO Rating (r = .10, NS). Thus H1 is partially supported.

-----------------------------------------------------------------------

Place Table 1 About Here

----------------------------------------------------------------------

To test hypothesis H2 we used a hierarchical regression analysis procedure proposed by Aiken

and West (1991) and employed by Grant (2013). For each of the two relevant dependent variables

(Overall, and Sociability ratings) a 2-step hierarchal regression analyses was conducted for each of the

two indicators (2 and Beta) of extroversion . Table 2 presents the descriptive statistics and Table 3

presents the results of this analysis which were divided into two sections based on which of the two

dependent variables was being regressed.

-----------------------------------------------------------------------

Place Table 2 and 3 About Here

----------------------------------------------------------------------

In step 1 the linear independent term was entered and in step 2 the quadratic term (acuity score

squared) was entered with significant improvement to the regression beta weight taken as evidence for

a significant curvilinear effect. For only the incentivized condition, and where Overall Rating was the

Dependent Variable, significant effects were observed for both Acuity_Extro_Beta ( = -1.14, p < .05) in

model a and b and for Extro_ χ2 ( = -1.69, p < .05) for model c and d. Neither the linear nor curvilinear

functions of Acuity_Extro_Raw_Score or Self_Report_Extro_Score were found to be significant

contributors to supervisors’ Overall Rating of their employees.

Under incentivized conditions (but not un-incentivized) and where supervisors’ Sociability Rating

was the Dependent Variable, a significant improvement to the linear relation was observed after the

introduction of the quadratic term for Acuity_Extro_Beta ( = -1.04, p < .05) in models a and b. The

Extro_ χ2 indicator was borderline significant ( = -1.40, p < .06) for models c and d. Again, neither the

linear nor curvilinear functions of Acuity_Extro_Raw_Score or Self_Report_Extro_Score were found to

be significant predictors of supervisors’ Sociability ratings of employees. Thus H2 is partially supported

with three out of four significant effects and one borderline effect observed. All significant effects

occurred in the incentivized condition while evidencing the predicted -shape. Neither the conventional

self report measures nor the acuity raw scores produced significant effects.

Discussion

Acuity theory holds that the more one possesses a construct (e.g., extroversion) the more

sensitive one will be to the distinctions in construct-representative phenomena (e.g. statements). In this

study we estimated the degree to which respondents were sensitive to distinctions in the CSO and

extroversion-representativeness of paired statements. For example, for the extroversion construct, one

statement may read “A true extrovert enjoys being with friends” while the other reads “A a true

extrovert enjoys loud parties”. The latter is posited to be a stronger representation of the extroversion

construct than the former. Importantly, recognizing these distinctions does not require that the

respondent engage in introspection and self-report (e.g., “I like loud parties”). By removing the

introspective self-report component, we anticipated and found that respondents produced more

criterion-valid responses even under monetarily incentivized conditions. We suspect that this occurred

because respondents exerted effort to detect the small differences in construct-representative

statements rather than exerting effort toward contriving socially desirable responses. Our results

support the proposition that, when applied to non-cognitive constructs, acuity methods may offer

resistance to socially desirable responding (SDR) because the task before the respondent is not

construct self-report but rather construct-representativeness detection.

Acuity-based estimation methods shown in this study were precise enough to model quadratic

(-shaped) relations between extroversion sensitivity and supervisor-observed sales job performance

consistent with hypothesis. These results were anticipated given the seminal research by Grant (2013)

who found that intermediate levels of extroversion are optimal while either very high or very low levels

are sub-optimal for sales performance. Rather, we found that those who are intermediate in their

sensitivity to distinctions in extroversion representative statements were more likely to receive a high

sales performance rating from their supervisor.

Several important limitations to this study must be considered. 1) The sample size of n = 56

provided very small statistical power. 2) Rather than using the newly developed measures of CSO and

extroversion presented here, subsequent research might use instruments with established

measurement properties. 3) Finally, subsequent research would benefit from comparing measurement

properties of statistics obtained from acuity methods and those derived from Item Response Theory

(IRT). Despite these limitations, the preliminary findings reported here support continued research in

applying acuity-based construct estimation methods as they appear to offer resistance to SDR and may

point to new directions in mental measurement.

References

Aiken, L. S., & West, S. G. (1991). Multiple regression: Testing and interpreting interactions. Newbury

Park, London, Sage.

Arvey, R. D., Strickland, W., Drauden, G., & Martin, C. (1990). Motivational components of test taking.

Personnel Psychology, 43, 695–716.

Barrick, M.R. & Mount, M.K. (1991). The big five personality dimensions and job performance: A meta-

analysis. Personnel Psychology, 44, 1-26.

Brown, T. J., Mowen, J. C., Donavan, D. T., & Licata, J. W. (2002). The customer orientation of service

workers: Personality trait effects on self and supervisor performance ratings. Journal of Marketing

Research, 39, 110–119. doi:10.1509/jmkr.39.1.110.18928

Grant, A. (2013). Rethinking the extraverted sales ideal: The ambivert advantage, Psychological Science,

24, 1024–1030.

Hausknecht, J. P., & Langevin, A. M. (2010). Selection for service and sales jobs. Retrieved 4/27/2014

from Cornell University, ILR School site: http://digitalcommons.ilr.cornell.edu/articles/190

Leeds, J.P. (2012). The theory of cognitive acuity: Extending psychophysics to the measurement of

situational judgment, Journal of Neuroscience, Psychology, and Economics, 5, 3, 106-181.

Leeds, J., P. & White, A. (2013). Estimating cognitive acuity in two situational judgment tests: More

lessons from psychophysics. Paper presented at the 25th Annual Convention of the Association for

Psychological Science, Washington DC.

Nisbett, R. & Wilson, T. (1977). Telling more than we can know: Verbal reports on mental processes.

Psychological Review, 84, 231-259.

O’Neill, T. A., Goffin, D. G., Gellatly, I. R. (2010). Test-taking motivation and personality test validity.

Journal of Personnel Psychology, 9, 3, 117-125.

Oviedo-García, M. A. (2007). Internal Validation of a Biodata Extraversion Scale for Salespeople. Social

Behavior and Personality, 35, 5, 675-691.

Pronin, E. & Kugler, M. B., (2007). Valuing thoughts, ignoring behavior: The introspection illusion as a

source of the bias blind spot. Journal of Experimental Social Psychology, 43, 565-578.

Snell, A.F., Sydell, E.J., & Lueke, S.B. (1999). Towards a theory of applicant faking: Integrating studies of

deception. Human Resource Management Review, 9, 219-242.

Sundre, D., L. & Kitsantas, A. (2004). An exploration of the psychology of the examinee: Can examinee

self-regulation and test-taking motivation predict consequential and non-consequential test

performance? Contemporary Educational Psychology, 29, 6–26.

Sundre, D. L., & Moore, D. L., (2002). The Student Opinion Scale: A measure of examinee motivation.

Assessment Update, 14, 8-9.

Sundre, D. L (1999). Does examinee motivation moderation the relationship between test consequences

and test performance? Paper presented at the annual meeting of the American Educational

Research Association, Montreal, Quebec, Canada.

Vinchur, A. I., Schippmann, J. S., Switzer, F. S., III, & Roth, P. L. (1998). A meta-

analytic review of predictors of job performance of salespeople. Journal of

Applied Psychology, 83, 586-597.

Wise, S. L., & DeMars, C. E. (2005). Low examinee effort in low-stakes assessment: Problems and

potential solutions. Educational Assessment, 10, 1-17.

Wise, S. L., & Kong, X. (2005). Response time effort: A new measure of examinee motivation in

Computercased tests. Applied Measurement in Education, 16, 163183.

Wise, S. L., Bhola, D., & Yang, S. (2006) Taking the time to improve the validity of lowstakes tests: The

effort monitoring CBT. Paper to be presented at the annual meeting of the National Council on

Measurement in Education, San Francisco, CA.

Wise, S.L., Bhola, D.S., & Yang, S. (2006). Taking the time to improve the validity of low-stakes tests: The

effort-monitoring CBT. Educational Measurement: Issues and Practice, 25, 21-30.

Table 1 Spearman Correlation Analyses of Customer Service Orientation Acuity Scores on Sales

Associates Job Performance Within and Between Subjects Comparision

UNINCENTIVISED

1. Acuity_CSO_Beta 1.38 .80 .08 -.31 117.43 6.89 .75 1.82 1

3. Acuity_CSO_Raw_Score † .73 .09 -.38 -.17 14. Self_Report_CSO_Score† 4.54 .34 -.68 -.24 .04 .09 -.12 .835. Overall Rating † 3.04 .64 -.19 -.04 .04 -.08 -.00 .06 .826. CSO Rating † 3.24 .61 -.19 -.56 .05 -.01 -.01 .04 17. Sociability Rating † 3.12 .76 2.36 .24 -.00 -.07 -.04 .05 1

Sample 2 - Time 1 (N =56)UNINCENTIVISED

1. Acuity_CSO_Beta 1.51 .79 .25 -.73 116.94 7.43 .74 .49 1

3. Acuity_CSO_Raw_Score .73 .09 -.90 1.24 14. Self_Report_CSO_Score† 4.52 .32 -.30 -.72 .18 .00 -.07 .835. Overall Rating † 3.09 .51 .15 .86 .03 -.16 .13 -.10 .836. CSO Rating † 3.23 .54 .14 -.15 -.03 -.20 .08 .04 17. Sociability Rating † 3.07 .57 .02 .23 .02 -.08 .22 .06 1

Sample 2 - Time 2 (N =56)INCENTIVISED

1. Acuity_CSO_Beta 1.85 .89 .20 -.35 1

15.71 6.70 .23 -.90 1

3. Acuity_CSO_Raw_Score .74 .10 -.69 .86 .86

4. Self_Report_CSO_Score† 4.56 .31 -.15 -1.13 .15 .09 -.07 .85

5. Overall Rating † 3.09 5.14 .15 .86 .23 .00 .13 1

6. CSO Rating † 3.23 5.39 .14 -.15 -.18 .01 .10 1

7. Sociability Rating † 3.07 5.68 .02 .23 .24 .07 1

**. Correlation is significant at the 0.01 level (2-tailed).

*. Correlation is significant at the 0.05 level (2-tailed).

† Shapiro-Wilk test of departure from normality for small samples was significant (the data are non-normal)

2. Acuity_CSO_c2 † -.53**

.53** -.37**

.66**

.61** .54**

2. Acuity_CSO_c2 † -.46**

.34* -.32*

.72**

.53** .41**

2. Acuity_CSO_c2 † -.50**

.34* -.39**

-.28*

.31* .72**

-.30* .29* .53** .41**

Table 2 Descriptive Statisitcs for Extraversion Acuity Scores on Sales Associates Job Performance Within

& Between Subjects Comparison

Skewness Kurtosis

UNINCENTIVISED Sample 1 (n = 285)Acuity_Extro_Beta -.04 2.24 -.30 .78

31.16 213.97 12.27 162.19

Acuity_Extro_Raw_Score .70 .13 -.80 1.90

Self_Report_Extro_Score 2.43 .46 .07 .59

Overall Rating 30.35 6.45 -.19 -.04

CSO Rating 32.43 6.13 -.19 -.56

Sociability Rating 30.88 6.48 -.48 .83

UNINCENTIVISED Tample 2 - Time 1 (n = 56)Acuity_Extro_Beta 2.19 1.06 .32 -.18

28.53 9.37 .36 -.14

Acuity_Extro_Raw_Score .67 .14 -.23 .88

Self_Report_Extro_Score 2.60 .34 -.29 -.16

Overall Rating 30.89 5.14 .15 .86

CSO Rating 32.32 5.39 .14 -.15

Sociability Rating 30.71 5.68 .02 .23

INCENTIVISED Sample 2 - Time 2 (n = 56)Acuity_Extro_Beta 2.28 .98 .70 1.11

29.08 9.51 .15 -.48

Acuity_Extro_Raw_Score .71 .11 .02 -.43

Self_Report_Extro_Score 2.63 .34 .05 -.31

Overall Rating 30.89 5.14 .15 .86

CSO Rating 32.32 5.39 .14 -.15

Sociability Rating 30.71 5.68 .02 .23

CSO Rating: Supervisor rating "Treat kindly and knows how to adapt to the customer"

MeanStd.

Deviation

Acuity_Extro_c2

Acuity_Extro_c2

Acuity_Extro_c2

Overall Rating = Rating by supervisor in the last year (10 = Low, 20 = Normal, 30 = Good, 40 = Excellent)

Sociability Rating: Supervisor rating "Integrates with peers, maintaining a good working climate"

Table 3 Hierarchical Regression Analyses Testing for Quaderatic Effects of Extraversion Acuity Scores

on Sales Associates Job Performance Within & Between Subjects Comparison

UNINCENTIVISED Sample 1 (n = 285) UNINCENTIVISED Tample 2 - Time 1 (n = 56) INCENTIVISED Sample 2 - Time 2 (n = 56)

Model b R F Change b R F Change b R F Changea. Step 1 -.01 .01 .03 .86 .11 .11 .59 .45 -.12 .12 .76 .39

b. Step 2 -.10 .06 .91 .34 -.97 .28 3.85 .06 -1.14* .34 5.80 .02*

c. Step 1 -.03 .03 .24 .62 -.16 .15 1.18 .28 .01 .01 .01 .92

d. Step 2 -.04 .03 .10 .75 .57 .18 .67 .42 -1.69* .31 5.68 .02*

e. Step 1 .08 .07 1.59 .21 -.05 .05 .13 .72 -.10 .10 .53 .47

f. Step 2 -.02 .08 .00 .95 .08 .05 .01 .92 .43 .11 .09 .77

g. Step 1 -.03 .03 .19 .67 -.02 .02 .01 .91 -.04 .00 .08 .78

h. Step 2 .18 .03 .11 .74 1.07 .10 .43 .51 -1.66 .14 .94 .34

Dependent Variable: Overall Rating

a. Step 1 -.05 .05 .68 .41 .12 .11 .69 .41 -.05 .05 .13 .72

b. Step 2 -.18 .12 3.28 .07 -.78 .24 2.46 .12 -1.04* .29 4.62 .04*

c. Step 1 -.02 .02 .08 .78 -.13 .07 .29 .59 -.13 .13 .96 .33

d. Step 2 -.09 .05 .59 .44 -.01 .19 1.67 .20 -1.4 .29 3.83 .06

e. Step 1 .00 .00 .00 1.00 .01 .10 .53 .47 .11 .11 .66 .42

f. Step 2 -.36 .06 1.18 .28 -.24 .11 .08 .77 -1.66 .19 1.35 .25

g. Step 1 -.04 .01 .25 .62 .01 .03 .03 .86 .01 .01 .01 .92

h. Step 2 .13 .07 .07 .80 -.07 .10 .36 .55 -2.11 .17 1.55 .22

Dependent Variable: Sociability Rating

a. Acuity_Extro_Beta

b. Acuity_Extro_Beta Squared

e. Acuity_Extro_Raw_Score

f. Acuity_Extro_Raw_Score Squared

g. Self_Report_Extro_Score

h. Self_Report_Extro_Score Squared

* Significant at the 0.05 level (2-tailed).

† Sample size for the Conventional_Customer_Service_Raw_Score Between Subjects analysis = 168 .

Sociability Rating: "Integrates with peers, maintaining a good working climate"

Overall Rating is the rating assigned of the sales representative by the immediate supervisor in the last year

Sig. F Change

Sig. F Change

Sig. F Change

c. Acuity_Extro_c2

d. Acuity_Extro_c2 Squared

No statistically significant (p < .05) effects were found or reported where CSO_Rating was the dependent variable.