37cIN9/

No, G6/3

A CONCURRENT VALIDATION STUDY OF A PAPER AND PENCIL

TEST BATTERY FOR A SALES POSITION

THESIS

Presented to the Graduate Council of the

University of North Texas in Partial

Fulfillment of the Requirements

For the Degree of

MASTER OF SCIENCE

By

Deedra Kim Irons, B.S.

Denton, Texas

May, 1990

Irons, Deedra Kim, A Concurrent Validation Study of a

Paper and Pencil Test Battery for a Sales Position. Master

of Science (Industrial/Organizational Psychology), May,

1990, 126 pp., 15 tables, 10 figures, bibliography, 71

titles.

Participating in this study were 251 decorator

consultants. The decorator consultant position is a direct

sales position. The primary objective of this study was to

demonstrate that a relationship existed between decorators'

selection test scores and their job performance. The SRA

Verbal Form, the EAS Numerical Ability Test, the EAS Space

Visualization Test, and the Sales Attitude Checklist were

evaluated as potential selection tests. Behavioral criteria

and managerial ratings were used to assess job performance.

Correlational analyses revealed that all the tests but the

SRA Verbal Form were significantly correlated with two or

more criteria.

TABLE OF CONTENTS

PageList of Tables . . . . . . . . . . . . . . . . . . . . iv

List of Figures . . . . . . . . . . . . . . . . . . . v

Chapter

I. INTRODUCTION . . . . . . . . . . . . . . . . . . . . 1

Test ClassificationsPersonality TestsTests of Intellectual AbilitiesTests of Spatial and Mechanical AbilitiesTests of Perceptual AccuracyTests of Motor Abilities

Alternative MethodsBiographical InformationInterviewsPeer EvaluationsSelf-AssessmentsProjective TechniquesGraphologyAssessment Centers

Statement of Hypotheses

II. METHOD . . . . . . . . . . . . . . . . . . . . . . 41

SubjectsIncumbent PopulationJob Analysis SampleField Testing SampleExperimental Design

Predictor and Criterion DevelopmentPredictorsCriteriaProcedure

III. RESULTS . . . . . . . . . . . . . . . . . . . . . 58

IV. DISCUSSION . . . . . . . . . . . . . . . . . . . . 68

APPENDICES . . . . . . . . . . . . . . . . . . . . . . 77

REFERENCES . . . . . . . . . . . . . . . . . . . . . . 118

iii

LIST OF TABLES

Table Page

1. Ghiselli's (1966) Validity Coefficients forSales Occupations . . . . . . . . . . . . . . . . 5

2. Ghiselli's (1973) Validity Coefficients forSales Clerks versus Salesmen . . . . . . . . . . 14

3. Hunter & Hunter (1984) Mean Validities ofVarious Predictors for Entry-level Positions . . 15

4. Descriptive Statistics for the Predictorsand the Criteria . . . . . . . . . . . . . . . . 59

5. Pearson Product-Moment Correlations between theTest Battery and Job Performance Measures . . . 60

6. Intercorrelations of the Experimental Tests . . 62

7. Correlation Matrix of the Criterion Measures . . 63

8. Descriptive Statistics for Each Test by Age . . 64

9. Mean Score Differences in Z-Score Unitsbetween Decorators Under 40 Years of Ageand Those Over 40 Years of Age . . . . . . . . . 65

10. Correlation of Job Tenure with Test Scores . . . 66

C-il. Numerical Ability Table . . . . . . . . . . . . 88

C-12. Space Visualization Table . . . . . . . . . . . 90

E-13. Task Statements with Incumbent Ratings . . . . . 96

G-14. Task-Dimension Matrix . . . . . . . . . . . . . 115

H-15. Descriptive Statistics for Similar Populations . 117

iv

LIST OF FIGURES

Figure Page

1. Relationship between Sales Attitude Test Scoresand Average Sales Volume . . . . . . . . . . . . . 101

2. Relationship between Sales Attitude Test Scoresand Managers' Ratings of Sales Ability . . . . . . 102

3. Relationship between Sales Attitude Test Scoresand Managers' Ratings of Customer Service . . . . 103

4. Relationship between Sales Attitude Test Scoresand Managers' Ratings of Administrative Duties . . 104

5. Relationship between Sales Attitude Test Scoresand Overall Ratings . . . . . . . . . . . . . . . 105

6. Relationship between Numerical Ability andManagers' Ratings of Administrative Duties . . . . 106

7. Relationship between Numerical Ability andOverall Ratings . . . . . . . . . . . . . . . . . 107

8. Relationship between Spatial Ability and Managers'Ratings of Ability to Design & Price Treatments . 108

9. Relationship between Spatial Ability andManagers' Ratings of Administrative Duties . . . . 109

10. Relationship between Spatial Ability andOverall Ratings .................... ........ 110

v

CHAPTER I

INTRODUCTION

The selection of sales personnel has a rich history.

In the first validation studies reported, salespeople were

used as subjects. In 1916, Munsterberg administered a paper

and pencil test battery, which included cognitive and

perceptual tests, to 450 subjects, 95 of which were in sales

positions. He attempted to correlate test scores to

vocational aptitude. His results demonstrated that a paper

and pencil test, the arrangement of letters, consistently

differentiated salesmanship ability (Burtt, 1917). Another

historical study using salespeople was conducted by Oschrin

in 1918. In this study, a paper and pencil test battery was

given to 18 saleswomen in a large department store.

Oschrin's (1918) results led her to the conclusion that "the

type of sales ability called for in a retail department

store is a fairly measurable function in terms of mental

tests, with which it shows a definite tendency to correlate

positively" (p. 154) .

Sales oriented selection research continued throughout

the 1920's and 1930's, mainly using stock and insurance

salesmen as subjects. Freyd (1926) tested 31 stock salesmen

1

2

using 21 tests in an attempt to differentiate successful

from unsuccessful salesmen. Many different types of

instruments were used in this study; a job knowledge test, a

personality test, a general intelligence test, handwriting

analysis, and biographical information. Sales records were

used to measure success. Only eight of the 21 tests were

able to significantly differentiate successful from

unsuccessful salesmen. Instruments that proved to be

invalid included matching sentences with facial expressions

and a comparison of the length of two statements, one

written right-handed and one written left-handed. Valid

instruments included; an objections to purchasing test (r =

.41), the Will-Temperament test (r = .49), a business

information test (r = .46), the number of impulsive lines in

an applicant's signature, and five biographical questions.

In the insurance industry, Bills (1941) used the Strong

Vocational Interest Blank (SVIB), the Bernreuter Personality

Inventory, and a personal history blank in an attempt to

differentiate successful agents from unsuccessful agents.

The use of the SVIB resulted in a "fair prediction of

whether the man would remain in the business and some

differentiation in production, while combined with the

personal history blank it gives a much more definite

prediction of production if the person remains with the

company" (Bills, 1941, p. 10).

3

Selection research concerning sales has continued using

a number of the instruments employed in these early studies

as well as others, in an attempt to identify valid

predictors of sales performance. The identification of

valid predictors of sales performance has not been an easy

task as demonstrated by recent meta-analyses. Schmitt,

Gooding, Noe and Kirsch (1984) conducted a meta-analysis of

validation studies published between 1964 and 1982 in both

the Journal of Applied Psychology and Personnel Psychology.

The mean correlation of 50 validities, of various predictors

with job performance in a sales position, was found to be

.17. Similar results were generated in a more extensive

review and meta-analysis by Churchill, Ford, Harley, and

Walker (1985). Their study incorporated both published and

unpublished studies for the years 1918 to 1982. A mean

correlation across 1653 validities of various predictors

with sales performance was found to be .19. These

correlations are discouraging, yet they resulted from a

combination of studies which employed numerous different

types of predictors and criteria. Average validities

obtained from using numerous predictors within a single

occupational category do not reveal the real practical

value, the predictive power, of each individual predictor.

Thus, if the results of using a specific type of predictor

were reviewed, the correlations may be somewhat more

encouraging as well as more insightful.

4

Ghiselli (1966) attempted to do just this, he reviewed

extensively the validity of occupational aptitude tests in

numerous occupational categories as classified by the

Dictionary of Occupational Titles (DOT). He reviewed

several sources of information; published literature between

1919 to 1964, test manuals and technical reports, and

unpublished literature from business and governmental

organizations. Ghiselli classified tests into five types;

(a) intellectual ability, (b) spatial and mechanical

ability, (c) perceptual accuracy, (d) motor ability, and (e)

personality tests. Ghiselli was only able to obtain

information concerning the validity of tests for six out of

the fifteen DOT sales classifications. The six

classifications were as follows: (a) salesmen, insurance

(1-57); (b) salesmen, stock & bond (1-65); (c) salesclerks

(1-70); (d) salespersons (1-75); (e) salesmen to consumers

(1-80); (f) salesmen & sales agents except to consumers

(1-85 to -87). The correlations which were found between

the different types of tests and measures of job proficiency

are given in Table 1.

Ghiselli was unable to find any information on the

validity of tests of motor abilities for sales occupations,

thus tests of motor abilities are not included in Table 1.

However, a great deal of information concerning the validity

of personality tests for sales occupations was found. From

5

Table 1

Ghiselli's (1966) Validity Coefficients for Sales

Occupations

SalesmenInsur.

IntellectualAbilities

Spatial &MechanicalAbilities

PerceptualAccuracy

PersonalityTests

.12b

.33

Salesmen Sales Sales Salesmen SalesmenStocks Clerk Person Consum. & Agents

.45a

.35d .46b

. 36

.22

aLess than 100 cases

b 1 00 to 499 cases

500 to 999 cases

d1,000 to 4,999 cases

this information, Ghiselli (1966) concluded that ".. .

measures of personality generally give the best and quite

accurate predictions of the job success achieved in sales

occupations" (p. 77). Each test classification; personality

tests, tests of intellectual abilities, tests of spatial and

mechanical abilities, tests of perceptual accuracy, and

tests of motor abilities will be discussed in terms of their

applicability to the selection of sales personnel.

I I I MIIlls

6

Test Classifications

Personality tests. Personality tests have been widely

used to predict sales success. A number of studies that

employed personality tests will be reviewed. The Minnesota

Multiphasic Personality Inventory (MMPI) was given to 182

sales representatives in an attempt to demonstrate its

validity as a predictor of sales performance (Ruch & Ruch,

1967). Ruch and Ruch proposed that the MMPI had predictive

power because it could be faked. They hypothesized that

good salesmen know what the job demands personality-wise and

thus can "put their best foot forward" when completing the

inventory. However, they proposed that the MMPI as well as

other personality instruments have correction factors that

act as suppressor variables when attempting to predict sales

success. Five scales without the K correction significantly

differentiated between good and poor salesmen. The

significant scales were as follows: (a) hypochondriasis, (b)

psychopathic deviate, (c) psychasthenia, (d) schizophrenia,

and (e) hypomania. When the K correction was applied the

validity for all five scales decreased. This decrease in

validity was statistically significant for three of the

scales and approached significance for one scale. The

decrease in validity for the fifth scale was not

statistically significant.

7

Personality tests were also used as a predictor of

sales performance by Lamont and Lundstrom (1977). They

conducted a concurrent validation study using multiple

predictors and criterion. The predictors included measures

of the personality traits: dominance, endurance, social

recognition, empathy, and ego strength; and the personal

characteristics: age, height, weight, formal education,

outside activities, and civic/professional organizations.

The personality traits were assessed using scales from

Jackson's Personality Research Form (PRF), Cattell's 16

Personality Factors (16PF), and Hogan's Personality

Inventory. The criteria employed were managerial ratings,

measures of sales compensation including commissions and

incentive earnings, and measures of sales activity including

sales quota, new business conversion, and call frequency.

The personality variables of endurance, empathy, and ego

strength were effective in predicting managerial ratings,

whereas the personal characteristics were effective in

predicting sales compensation and sales activity.

Deb (1983) compared the scores of 50 successful

salespeople to 300 non-salespeople on the Bernreuter

Personality Inventory and the Strong Vocational Interest

Blank. The subjects were matched on age, education, and

service experience. This comparison revealed that

salespeople were more likely to be extraverted, dominant,

8

well-adjusted, sociable, self-confident, and cheerful than

non-salespeople.

Another study using measures of personality to predict

sales success was conducted using 355 life insurance agents

(Matteson, Ivancevich, & Smith, 1984). A relationship

between type A behavior and sales performance was sought.

The performance measures used were policy amount, premium

income, and total policies. Type A behavior was not

significantly related to any of the performance measures

used (Matteson et al., 1984).

Merenda and Jacob (1987) did a study comparing 245

salespersons' self-concept profiles to a sales position job

profile. Each salesperson had completed the Activity Vector

Analysis (AVA) prior to being hired. Of the 245 subjects,

125 were still employed at the end of the calendar year and

their profile compatibility was compared to their sales

figures. The other 120 subjects had been terminated within

the calendar year, so their profile compatibility was

compared to their length of service. Higher compatibility

coefficients were associated with higher sales in the

employed group and with longer tenure in the terminated

group.

Frautschi (1987) also attempted to predict sales

success using a personality test, the California Personality

Inventory (CPI). The CPI scores of 20 home improvement

9

representatives were correlated with net and gross closing

ratios. None of the CPI scales differentiated between good

and poor representatives using gross closing ratio as the

measure of sales performance. But, when using net closing

ratio as the measure of sales performance, three scales;

responsibility, intellectual-efficiency, and psychological-

mindedness were able to differentiate successful from

unsuccessful home improvement representatives. However,

these results did not replicate the findings of an earlier

pilot study.

Hollenbeck, Brief, Whitener, and Pauli (1988) conducted

a study concerning the interaction of personality and

aptitude tests in selecting life insurance salespersons.

Self-esteem and locus of control were assessed using the

Janis-Field Feelings of Inadequacy Scale and the Rotter

Locus of Control Scale. Aptitude was measured with the

Aptitude Index Battery (AIB). The AIB measures an

individual's aptitude for life insurance sales. The self-

esteem/aptitude interaction was statistically significant

(R2 = .18, p < .05). The locus of control/aptitude

interaction was not significant. The results indicated that

self-esteem is a more efficient predictor of sales

performance when interactively combined with a measure of

aptitude.

10

In summary, as a predictor of sales success personality

tests have been and continue to be widely used, as is

evident by the number of studies present in the literature.

Ghiselli's (1966, 1973) reviews of the literature have

demonstrated that personality tests are a valid means of

predicting sales success. However, the applicability of

personality test results are called into to question because

follow-up studies often do not replicate earlier findings,

as was seen in the Frautschi (1987) study.

Another criticism of the use of personality tests for

selection is that test scores equate the absence of

psychopathology with the presence of competence. However,

this assertion has been weakened by the development of

personality measures designed specifically for

"nonpathological" individuals and selection purposes such as

the Guilford-Zimmerman Temperament Survey and the Sales

Attitude Checklist.

Tests of intellectual abilities. Tests of intellectual

abilities have also been employed to select salespeople.

Tests of intellectual abilities include tests of

intelligence, memory, substitution, and arithmetic. Schultz

(1935) tested 556 life insurance salesmen using tests of

intellectual abilities, personality tests, and biographical

information. If the agents had been hired based on their

personality and intelligence test scores, 70% of the agents

11

with the best production records would have been chosen, and

70% of the agents with the poorest production records would

not have been hired. The use of the intelligence tests in

addition to the personality tests helped eliminate more poor

agents such as those who would not succeed in training.

Using biographical information did not show any appreciable

effect.

Miner (1962) tested 65 salesmen of a petroleum company

using tests of intellectual abilities, tests of spatial and

mechanical abilities, and personality tests. Objective

criteria were developed using sales figures. After cross

validation, two tests were able to significantly

differentiate good salesmen from poor salesmen, the Wechsler

Adult Intelligence Scale (WAIS) arithmetic subtest and the

Tomkins-Horn Picture Arrangement Test (PAT). The WAIS

arithmetic subtest, a test of intellectual ability, yielded

uncorrected correlations between .23 and .35 with the

performance measures employed. The PAT, a personality test,

yielded uncorrected correlations between .31 and .51 with

the performance measures.

In Ghiselli's (1966) review of the literature, he found

divergent validity coefficients for various sales

occupations, ranging from -.10 for salespersons to .45 for

salesmen of stocks and bonds, when tests of intellectual

abilities were used to predict sales performance. When the

12

lower sales occupations (sales clerks) were grouped together

and the higher sales occupations (salesmen) were grouped

together, Ghiselli (1973) found tests of intellectual

abilities correlated -.03 for sales clerks and .33 for

salesmen. Each type of test of intellectual ability

correlated negatively for sales clerks, except for

arithmetic tests which correlated .10 (Ghiselli, 1973).

As a predictor of sales performance, tests of intellectual

abilities have demonstrated validity for the higher sales

occupations such as technical and industrial salespeople;

however, these tests have not demonstrated validity for the

lower sales occupations such as sales clerks.

Tests of spatial and mechanical abilities. Another

type of test used to select salespeople is tests of spatial

and mechanical abilities. Tests of spatial and mechanical

abilities include tests of spatial relations, location, and

mechanical principals. Miner (1962) tested 65 petroleum

salesmen using the Survey of Mechanical Insight. A

correlation less than .20 was obtained between this test and

each criterion, thus this test was not included in the cross

validation study. Ghiselli (1973) states that tests of

spatial and mechanical abilities are valid means of

selection of both sales clerks and salesmen. However,

Ghiselli (1966, 1973) did not find a study involving sales

clerks which utilized a test of mechanical ability. Thus,

13

it would be more precise to state that tests of spatial

abilities are a valid means of prediction for sales clerks

and tests of spatial and mechanical abilities are valid

means of prediction for salesmen.

Tests of perceptual accuracy. Tests of perceptual

accuracy have been used to select sales personnel. Tests of

number and name comparison, cancellations, and pursuit are

types of perceptual accuracy tests. Ghiselli (1973) reported

correlations of -.02 for sales clerks and .23 for salesmen

between tests of perceptual accuracy and job proficiency.

Tests of motor abilities. Tests of motor abilities

have not been widely employed in the selection of

salespeople. Ghiselli (1966) did not find a single study

that used tests of motor abilities in the selection of

salespeople. Ghiselli (1973) was able to find studies which

incorporated tests of motor abilities in the selection of

salespeople. The validity coefficient found between tests

of motor ability and measures of job proficiency for all

sales occupations was .12 (Ghiselli, 1973). Tests of motor

abilities include tests of finger, hand, and arm dexterity;

dotting; tapping; and tracing.

The validity of each type of test is different for

different sales occupations. Ghiselli's (1973) review

clarifies these differences (see Table 2).

14

Table 2

Ghiselli's (1973) Validity Coefficients for Sales Clerks

versus Salesmen

Sales Clerks Salesmen

PersonalityTests .36 d.29

IntellectualAbilities -. 03d .33d

Spatial & Mechanical b

Abilities .14b.20

PerceptualAccuracy -. 02d.23

MotorAbilities .09C .16b

aLess than 100 cases C500 to 999 cases

b1 0 0 to 499 cases d1 ,0 0 0 to 4,999 cases

From Ghiselli's (1973) review it is apparent that tests

of intellectual abilities, perceptual accuracy, and motor

abilities are not valid selection measures for sales clerks.

Tests of spatial and mechanical ability have some value for

the selection of sales clerks. But, personality tests have

the most value for the selection of sales clerks. Each type

of aptitude test has at least moderate validity for the

selection of salesmen. However, personality tests and tests

15

of intellectual abilities are the most valid means to select

salesmen.

Each type of test has its advantages as well as its

disadvantages as described above. But, the validity of

tests exceeds that of all other selection devices for entry-

level positions (see Table 3).

Table 3

Hunter & Hunter (1984) Mean Validities of Various Predictors

for Entry-level Positions

MeanPredictors Validity

Ability Composite (tests) .53

Job Tryout .44

Biographical Inventory .37

Reference Check .26

Experience .18

Interview .14

Training & Experience Ratings .13

Academic Achievement .11

Education .10

Interest .10

Age -.01

16

Hunter and Hunter's (1984) validity coefficients are based

on sample sizes of 1,089 to 32,124 and 3 to 425 validity

coefficients. The ability of tests to accurately predict

on-the-job performance has been established, but tests are

not as widely used as would be expected.

The use of tests is less than expected due to the

possibility of litigation. The use of some tests has

resulted in adverse impact, and when a test adversely

impacts a racial group, evidence has to be presented that a

significant relationship exists between the test scores and

job performance, usually in the form of a validation study.

Adverse impact results when a Title VII protected group is

not hired or hired at a lower rate due to lower test scores.

Some individuals hypothesize that a difference in

actual ability between racial groups does not exist, and

that the lower test scores obtained by a given racial group

are the result of unfair tests (test bias hypothesis). These

individuals assume that if the culturally biased content was

removed from tests, the tests would not result in adverse

impact. They also believe that tests have single-group

validity as well as differential validity. Single-group

validity is "validity for one group and not for others"

(Hunter & Hunter, 1984, p. 73). Differential validity is

"validity differences between subgroups" (Hunter & Hunter,

1984, p. 73). But,the empirical evidence gathered over the

17

past 15 years has not supported these assertions. It has

been demonstrated that single-group validity and

differential validity are artifacts of small sample sizes

(Boehm, 1977; Katzell & Dyer,1977; O'Connor, Wexley, &

Alexander, 1975; Schmidt, Berner, & Hunter, 1973; Bartlett,

Bobko, Mosier, & Hannan, 1978; Hunter, Schmidt, & Hunter,

1979). It has also been established that a difference in

mean test scores reflect a difference in mean ability

(Hunter & Hunter, 1984). Thus, aptitude tests are viable

means of selection, but evidence that a relationship exists

between the test scores and job performance must be

presented if use of the tests result in adverse impact.

Alternative Methods

The validity of aptitude tests has been demonstrated

for a wide variety of jobs and populations, including sales

occupations (Ghiselli, 1966; Pearlman, Schmidt, & Hunter,

1980; & Hunter & Hunter, 1984). However, the use of

alternative methods of selection which are equally valid,

but produce less adverse impact has been advocated by the

Federal Government via the judicial system and the Uniform

Guidelines of Employee Selection Procedures. In Section 3B

of the Uniform Guidelines it is stated that:

Whenever a validity study is called for by

these guidelines, the user should include, as

a part of the validity study, an investigation

18

of suitable alternative methods of using the

selection procedure which have as little

adverse impact as possible, to determine the

appropriateness of using or validating them

in accord with these guidelines. (Dreher & Sackett,

1983, p. 129)

Alternatives to aptitude tests will be discussed in terms of

their applicability to sales selection, these alternatives

include: biographical information, interviews, peer

evaluations, expert judgement, self-assessments, projective

techniques, graphology, and assessment centers.

Biographical information. Biographical information is

the most widely used alternative to aptitude testing for

sales selection. In the studies reviewed by Schmitt et al.

(1984) biographical information was used five times more

often than the next most widely used procedure in the

selection of sales personnel. Biographical information is

an empirical technique utilizing personal history to predict

job performance. Biographical items may vary on the

following dimensions: verifiable-unverifiable, historical-

futuristic, actual-hypothetical behavior, memory-conjecture,

factual--interpretive, specific-general, response-response

tendency, and external-internal (Asher, 1972). Items are

considered 'hard' or 'soft' depending on how they vary on

these dimensions.

19

The first study which employed biographical information

as a predictor of sales performance was conducted by Phoenix

Mutual Life Insurance (Holcombe, 1922). A relationship was

found between sales performance and three biographical

items; education, number of dependents, and selling

experience.

In 1938, biographical information was again used as a

predictor of sales performance in the insurance industry

with the development and use of the Life Insurance Salesman

Aptitude Index (Kurtz, 1938). The Aptitude Index contains

two independent parts the prediction scale, consisting of

personal history items and the personality characteristic

scale, consisting of four subtests of personality items.

The instrument has continued to be used throughout the years

in revised forms and today is referred to as the Aptitude

Index Battery.

The successful use of biographical information to

select salesmen has been demonstrated in numerous studies.

Harrell (1960) conducted a study using food company salesmen

and found that biographical items significantly

differentiated between resigned salesmen and two

classifications of employed salesmen, and between fired

salesmen and one classification of employed salesmen. In

yet another study, an objectively scored mail questionnaire

was developed that eliminated three-fourths of the salesmen

20

whose sales performance did not meet minimum standards

(Appel & Feinberg, 1969).

The biographical items of age, education, and marital

status were reviewed for 123 retail salesclerks to see if a

relationship existed between these variables and average

daily sales. Correlations of .90 between age and daily

sales, and .80 between education and daily sales were found

(Weaver, 1969). But, more education only correlated with

more sales up to a point, high school graduates generated

more sales than those individuals with some college. Sales

clerks who were married or divorced had higher daily sales

than those clerks who were separated.

Asher (1972) compared the predictive power of

biographical items to other selection instruments, and

biographical items were found to be more predictive. The

number of validity coefficients .50 or higher, .40 or

higher, and .30 or higher was found to be greater for

biographical items then for tests measuring intelligence,

mechanical aptitude, personality, finger dexterity, and

spatial relation ability (Asher, 1972).

Hinrichs, Haanpera, and Sonkin (1976) cross validated a

biographical inventory for the selection of office equipment

salespeople across nationalities. Validity coefficients

ranged from .24 to .72. Validity decreased as one moved

further away from the cultural and occupational groups used

21

to develop the key. Overall, the results indicated that

cross-national validity exists between personal history

items and success in office equipment sales.

In a review of the literature, Owens (1976) found an

average validity of .35 between biographical information and

sales success. In Reilly and Chao's (1982) review of the

literature, they found an average validity of .40 between

biographical information and supervisor ratings, and a

validity of .62 between biographical information and

measures of productivity in sales occupations.

In some of the most recent research, Childs and

Klimoski's (1986) attempted to predict general occupational

success using a biographical inventory. The biographical

inventory was administered to students within introductory

Real Estate Principles courses. Two years later, the

subjects were sent a questionnaire consisting of 12

occupational success questions. These 12 questions were

factor analyzed and three factors emerged; job success,

personal success, and career success. Multiple regression

of the biographical items and these three success factors

was conducted. Of the subjects employed in sales

occupation, correlations of .45 with job success, .33 with

personal success, and .58 with career success were found.

As a predictor of sales performance biographical

information has a long and successful history. Biographical

22

information is considered to have high utility as a

selection instrument because there are minimal costs

involved in collecting the information and it has

demonstrated relatively high validity (Reilly & Chao, 1982).

However, there are disadvantages associated with using

biographical information as a predictor of sales success. A

large sample size is needed to establish stable estimates of

key weights. England (1971) recommended a minimum sample

size of 150 when using biographical information. Hunter and

Hunter (1984) recommended that a sample size of 400 to 1,000

be used initially and larger sample sizes in follow-up

studies when using biographical information.

Another disadvantage to using biographical inventories

is that they require revalidation, because they tend to lose

validity over time. The loss of validity is due to the

capitalization on chance inherent in the developing of the

keys. Schuh (1967) reviewed a number of biodata studies and

found that the mean initial validity was .66 but the

validity dropped to .52 to .36 to .07 in successive follow-

up studies.

The use of biographical information also poses legal

questions such as, whether the question is an invasion of

privacy or an indirect indicator of race or sex. The

advantages of using biographical information in the

selection of sales personnel however have to be weighed

against the disadvantages.

23

Interviews. Interviews are also a widely used

alternative to aptitude tests. Even though numerous reviews

(Arvey, 1979; Schmitt, 1976; Mayfield, 1964; Wagner, 1949)

have consistently revealed that interviews have low

reliability and validity, they continue to be extensively

used. In 1982, Opren (cited in Opren, 1985) found that

individuals responsible for hiring generally refuse to stop

using the interview as their primary selection procedure,

even when informed that psychological tests are more valid

predictors of performance in that job. Attempts have been

made to improve interviews due to their widespread use such

as through structured interviewing techniques. Studies that

have utilized these techniques in a sales population will be

reviewed.

The Life Insurance Marketing and Research Association

(LIMRA) has been utilizing structured interviewing

techniques in the selection of life insurance salespeople

for the past two decades. The insurance industry first

started selecting life insurance salespeople using

structured interviewing techniques via the Agent Selection

Kit (ASK). The ASK fell into disuse because of the time

required to complete the selection process. The ASK

interview consisted of two separate session that took over 3

hours to conduct. LIMRA was convinced that a valid yet

applicable interview could be conducted, so they learned

24

from their experience with the ASK and developed the

Selection Interview Blueprint (SIB). The SIB takes

approximately one hour to administer. Mayfield, Brown, and

Hamstra (1980) did two studies utilizing the SIB. The first

study required 270 office and field managers to listen to an

SIB interview and rate the applicant. In the second study,

163 SIB rating forms which had actually been used in the

selection process were collected from managers. The rating

obtained in each study were factor analyzed. "The results

indicate that it is possible for managers to agree on their

evaluation ratings of an applicant, that there is a stable

factorial structure for the ratings, and that the ratings

are related to the selection decision although not all items

carry the same weight" (Mayfield et al., 1980, p. 725).

These results show that the SIB has potential to assess

applicants for the position of life insurance salesperson.

Presently, the validity of the SIB in the field is being

researched through the gathering of performance data.

Opren (1985) conducted a comparative validity study of

patterned behavior description interviews and unstructured

interviews. Patterned behavior description interviewing is

a structured interviewing technique based on the premise

that past behavior will predict future behavior. Applicants

for a life insurance sales position were the subjects of

this study. Each applicant was interviewed four times;

25

twice by interviewers trained in patterned behavior

description interviewing and twice by interviewers trained

in unstructured interviewing. The interviewers were

randomly assigned to the two techniques and received the

same amount of training. The interviewers were to gather

information in order to predict the future sales performance

of the applicant. They gave each applicant a rating from 1

(very unsuccessful) to 7 (very successful). The applicants

had not been screened by any instrument prior to the

interviews and all applicants were hired regardless of their

ratings.

In a comparison of all the behavior description

interview predictions (r = .48, p < .01) to all the

unstructured interview predictions (r = .08) with

supervisors rating of "overall effectiveness" as the

criterion, the behavior description predictions were

significantly higher (p < .05). Using dollar amount of sales

as the criterion, behavior description predictions (r = .61,

p < .01) were also significantly (p < .05) higher than

unstructured predictions (r = .05). The test-retest

reliability of the behavior description interviews (r = .72)

did not differ significantly from the test-retest

reliability of the unstructured interviews (r = .68).

Arvey, Miller, Gould, and Burch (1987) developed a

structured interview for seasonal retail sales clerks. A

26

job analysis was conducted which revealed that applicants

would be more successful sales clerks if they had prior

experience, good interpersonal skills, knowledge about the

products sold, and were readily available to work. A 15

item interview schedule was developed assessing these items.

A 16 item job performance rating form was also developed

that paralleled the interview schedule in content. In the

first year, a correlation of .42 (N = 312, p < .01) was

obtained between interview scores and performance ratings.

In the second year, a correlation of .61 (N = 205, p < .01)

was obtained. These correlations were corrected for

criterion attenuation and restriction of range.

Weekley and Gier (1987) developed a situational

interview for a sales position within a national jewelry

chain. Situational interviewing is a structured

interviewing technique based on the premise that expressed

behavioral intentions are predictive of subsequent behavior.

Four-hundred critical incidents were gathered and used to

develop thirty-six questions in a situational format. A

pilot study was conducted with store managers as the

interviewers and corporate employees as the interviewees.

The pilot study resulted in a 16 item interview form with an

interrater reliability of .84. A validation study was then

conducted with 24 hired applicants which resulted in a

correlation of .47 (p < .02) between their interview scores

27

and their sales-per-hour over a nine month period. The

correlation was corrected for criterion attenuation (r,=

.91).

Because individuals responsible for hiring are

committed to the use of interviews, and traditional

interviews have consistently demonstrated low reliability

and validity as well as racial and gender bias (Arvey, 1979;

Schmitt, 1976; Mayfield, 1964; Wagner, 1949) interviewing

has taken on new forms which are generating promising

results in sales selection.

Peer evaluations. Another alternative to aptitude tests

is peer evaluations. The rationale for using peer

evaluation for personnel selection is that peers have the

opportunity to observe each others' behavior across a wide

range of situations, thus peers are better able to ascertain

each other's typical level of performance. Peer evaluations

can be in the form of ratings, rankings, full nominations,

or high nominations. The military has extensively used peer

evaluations to successfully predict later performance (Lewin

& Zwany, 1976; Hollander, 1954). Studies utilizing peer

evaluation in the selection of sales personnel will now be

reviewed.

Waters and Waters (1970) conducted a study in which 53

salesmen nominated each other on six traits, sales

potential, and friendship. The traits were as follows:

28

assertive, agreeable, dependable, calm, polished, and

vigorous. Nominations on friendship were a part of the

experimental design in order to determine the effect of

friendship on the trait nominations. Three friendship

groups were identified for each salesman; those who

nominated him high on friendship, those who nominated him

low on friendship, and those who did not mention him as high

or low on friendship. The correlations between the traits

and the criterion were not significantly different for these

three friendship groups. Ratings on three traits and on

sales potential were significantly correlated with the

objective measures of sales performance; new business sales

and percentage of quota.

Mayfield (1970) used peer nominations in a study with

154 life insurance agents in three different companies. The

agents were asked to nominate three other agents in response

to work and social questions. The agents were told these

nominations would be used as part of the selection process

for assistant managers within their companies. Chi-square

analysis revealed a significant correlation between the

nominations and supervisory ratings in all three companies.

Mayfield (1972) conducted another study using peer

evaluation with insurance agents. Pearson product-moment

correlations of .29 with retention and .30 with productivity

(p < .01) were found.

29

Peer evaluations have demonstrated applicability for

sales selection. However, a number of disadvantages are

associated with the use of peer evaluations. Peer

evaluations are difficult to impossible to obtain for

applicants of entry-level positions. They also lack

standardization. Such variables as size of the peer group

and the average level of the trait being evaluated within

the peer group greatly influence the standardization of peer

evaluations.

Also, the method of peer evaluation used effects the

metric and distributional properties of the evaluations

(Reilly & Chao, 1982). If ratings are used, it is likely

that a highly skewed distribution will be obtained due to

leniency errors. If full nominations are employed, a

trimodal distribution will likely result because each group

member is required to choose a specific number of peers as

high, medium, and low on a given trait when using this

method. If rankings are used, a rectangular distribution

will likely be obtained. "Depending on the needs of a given

organization, one or more of these distributions may be ill-

suited for selection purposes" (Reilly & Chao, 1982, p.25).

Another problem when using peer evaluations is the

acceptance of the program. Often participants of peer

evaluation programs favor discontinuation of the program due

to perceived friendship bias and/or perceived lack of

30

validity. Racial bias is also a disadvantage encountered

when using peer evaluations. Lewin and Zwany (1976) state

that racial bias is generally to be expected in peer

evaluation programs. "Members of a given race tend to

evaluate their same race peers higher" (Reilly & Chao, 1982,

p. 24).

Expert judgements. Expert judgement is an alternative

method of selection used for sales personnel. Expert

judgement is a means by which to combine and summarize

objective data. Few studies utilizing expert judgement have

been reported recently due to research supporting

statistical prediction over judgmental prediction. Pearson

(cited in Reilly & Chao, 1982) used expert judgment via

psychological evaluations of 64 applicants for sales

positions. The psychological evaluation combined

information from a biodata questionnaire, personnel records,

Wonderlic scores, and two inventories developed by a private

consultant. Two psychologists made recommendations of the

64 applicants. The applicants were divided into two

subsamples of 21 and 42. A correlation of .37 (p < .10) for

the subsample of 21 and a correlation of .29 (p < .05) for

the subsample of 42 were obtained between the psychologists

recommendations and managerial performance ratings.

Roose and Dougherty (1976) conducted a study using

expert judgment in the selection of 360 life insurance

31

agents. The experts in this study were life insurance

agency managers, the individuals who usually hire the

agents. Roose and Dougherty prepared protocols for each

applicant. The protocols contained 66 cues from

biographical, test, and interview data. The managers had to

state, "yes" or "no", whether the applicant would be

successful at the end of one year. The average validity of

the judgments was .13. When combined with the objective

scoring, the judgements added .04 to the R2. This suggested

possible non-linear combination of the 66 cues by the

managers.

These two studies suggest applicability of expert

judgements for sales selection. However, no evidence was

given in regard to the comparability of the data combined

judgementally as to it combined statistically. Expert

judgement is also costly and time consuming.

Self-Assessments. Self-assessments have also been

employed in the selection of sales personnel. Self-

assessments are self-evaluations of knowledge, skills,

abilities, and other characteristics. The use of self-

assessments as predictors of job performance has been

minimally researched and used. Levine, Flory, and Ash

(1977) propose that the minimal use of self-assessments is

because it is assumed that self-assessments are inflated and

unreliable and thus have low validity.

32

Farley and Mayfield (1976) used self-assessments with

1,119 applicants for life insurance sales jobs. Each

applicant was to write down ten friends names and rate each

friend as higher or lower than oneself on need for

achievement and willingness to work hard. An applicant's

score on each variable was the number of friends lower than

the applicant on that variable. The criteria used were

survival of one year and commission credits over $6,000 in

one year. Neither score correlated with either criterion.

Self-assessments are quick and inexpensive to obtain,

but low reliability and validity have plagued the usefulness

of self-assessments as predictors of sales performance.

Self-assessments were reported to have a median test-retest

reliability of .32 by Ekpo-Ufot (1979).

Protective techniques. Another means by which to

select sales personnel is by using projective techniques. A

projective technique involves the presentation of new and/or

ambiguous stimuli. Subjects are observed to see how they

react and structure the situation, and from these

observations, inferences to the personality structures of

the subjects are made. The use of projectives is appealing

for two reasons; to measure characteristics not assessable

by more direct approaches and to overcome response bias.

Kinslinger (1966) reviewed a number of different

validity studies using projective techniques as predictors.

33

Nine studies in which he reviewed involved sales personnel.

These studies generated varied results. Cox (1948) found 19

items from a multiple-choice version of the Rorschach to

differentiate the most successful from the least successful

sales clerks. However, he did not report validity

coefficients or attempt to cross validate his results.

Botha and Koper (cited in Kinslinger, 1966) correlated TAT

scores with managerial ratings. They found better salesmen

scored significantly higher in need for achievement than

average salesmen. A significant difference between better

and average salesmen was not found for need for power.

Spencer and Worthington (1952) employed the Worthington

Personal History (P-H) to predict sales performance and

tenure. Biserial correlations of .31 with sales volume and

.34 with tenure were found. Worbois and Kanous (1954) also

used the Worthington P-H to predict sales performance;

however, no significant correlations were found.

Since Kinslinger's review few studies have used

projective techniques as predictors. One study using a

projective technique to select sales applicants was found.

Tullar and Barrett (1976) utilized an unusual projective

technique, a future autobiography, with 36 sales trainees.

The autobiographies were scored on three constructs which

were as follows: (a) agency, "the extent to which a person

sees himself as the prime agent in determining the course of

34

his future life," (b) demand, "the extent to which an

individual portrays his life as a long-term, continuing

effort on his part," and (c) differentiation, "the extent to

which an individual has created a complex detailed mapping

of his future." The scores obtained by each trainee on

these three constructs were correlated with ten performance

rating obtained from behaviorally anchored rating scales.

Of the thirty correlation coefficients, only five were

significant. All five of the significant correlation

coefficients were with the agency construct. With word

count partialed out, seven coefficients with the agency

construct and two. coefficients with the demand construct

were significant.

Disadvantages to using projective techniques include;

poor face validity, the need for psychological

interpretation, and the possibility of contrived responses.

Generally, projectives lack sufficient reliability and

validity to predict job performance (Reilly & Chao, 1982).

Graphology. Another alternative to aptitude tests

which has been employed in the selection of sales personnel

is graphology. Graphology is the analysis of character

through handwriting. Graphology is commonly referred to as

handwriting analysis.

Zdep and Weaver (1967) employed graphology as a means

to differentiate successful from unsuccessful life insurance

35

salesmen. Handwriting samples from 63 life insurance agents

were analyzed. No significant correlations and in many

instances negative correlations were obtained between 13

traits selected intuitively by the handwriting analysts and

policy commissions. The correlations obtained when using

the traits dominantly found in successful salesmen

handwriting and policy commissions were also not

significant. However, some success was achieved in

selecting unsuccessful salesmen if they lacked certain

traits in their handwriting. Of the salesmen that were

identified as "failures" due to lack of certain traits a

significant number were actual "failures".

Rafaeli and Klimoski (1983) also conducted a study

employing graphology. Neutral and autobiographical

handwriting samples of 70 real estate sales associates were

analyzed. The performance measures used in this study were

supervisory ratings, self-ratings, and productivity

measures. Very low nonsignificant validity coefficients

were obtained regardless of the type of handwriting sample

and the performance measure used. However, some evidence of

interrater reliability was seen in this study.

Graphology is quick, inexpensive, and technically

simple. But, graphology has failed to demonstrate validity

as a predictor of job performance in sales occupations.

36

Assessment centers. Another procedure used to select

sales personnel is assessment centers. An assessment center

is a means by which to evaluate candidates using multiple

assessment techniques. The methodology of assessment

centers is a primary asset. They are considered to be

objective, reliable, content valid, acceptable to the EEOC

(Thornton & Byham, 1982). The utilization of assessment

centers in selecting sales personnel will be reviewed.

American telephone and telegraph (AT&T) was a pioneer

in the development and use assessment centers and continues

to widely utilize assessment center methodology in the

selection of sales personnel (Thornton & Byham, 1982). Bray

and Campbell (1968) evaluated candidates for a sales

position using an assessment center consisting of four

cognitive paper and pencil tests, an interview, and

individual and group simulations which included; a

leaderless group discussion, an oral fact-finding exercise,

and a consulting case. The judgements of the assessment

center staff correlated .51 with field performance ratings

given by a special observational team. However, assessment

staff judgments were not significantly related to supervisor

or trainer ratings, but these ratings were also not

significantly related to field performance ratings.

Ritchie (cited in Thornton & Byham, 1982) conducted a

study using an assessment center to select commissioned

37

salespersons. He found a significant relationship between

the salespersons' overall assessment rating (OAR) and their

field performance and two training criteria. Also, he found

assessees rated as acceptable turned-over at one-half the

rate of assessees rated as less than acceptable.

Assessment center methodology has been utilized in the

selection of salespersons for a variety of organizations

including Sears, Allstate, Ethan Allen, Xerox, and Merrill

Lynch (Thornton & Byham, 1982). These organizations have

not published the results of using assessment center

methodology as a means of selection. Hollenbeck in personal

conversation (cited in Thornton & Byham, 1982) stated that

Merrill Lynch's use of assessment center methodology has

resulted in a 42% reduction in turnover among "recommended"

stockbrokers.

The use of assessment centers in the selection of sales

personnel has been limited, with very few studies being

published. The use of assessment centers in the selection

of sales personnel has its disadvantages such as, difficulty

in implementation and operation, cost of operation, and the

amount of time required to train assessors. Another

disadvantage of assessment centers is possible biased

ratings. In a recent study, an assessment center was used

to evaluate the job potential of 1035 applicants for a

professional sales position (Walsh, Weinberg, & Fairfield,

38

1987). Walsh et al. (1987) found a significant main effect

for applicants' sex (F = 7.54, p < .01) and a significant

interaction effect between the sex composition of the

assessor group and applicants' sex (F = 4.56, p < .05).

Female applicants (M = 7.56) received higher ratings than

male applicants (M = 6.93). The all-male assessor group

gave female applicants significantly higher ratings than

male applicants (t = -3.38, df = 423, p < .001).

In Reilly and Chao's (1982) extensive review of

alternatives to aptitude tests, two other alternatives were

reviewed; reference checks and academic performance.

However, no studies utilizing reference checks or academic

performance to predict sales performance were found, thus

they were not reviewed. Of the alternatives reviewed, most

were not viable means of selection for an entry-level sales

position. Biographical information is not a suitable

selection method, because of the large sample size required

and the loss of validity over time. Because peer

evaluations are nearly impossible to obtain for an entry-

level position, peer evaluations are not a viable selection

procedure. Due to the lack of evidence of the superiority

of expert judgments over statistical procedures when

combining and summarizing objective data, expert judgments

were not a suitable selection method. The low reliability

and validity of self-assessments and projective techniques

39

eliminated these alternatives from being considered as a

means of selection. Because graphology demonstrated no

validity it is not a viable option. Since assessment

centers are time consuming and costly, they are also not a

suitable selection procedure. Interviews in a structured

format demonstrated promising reliabilities and validities,

thus this technique was considered a viable selection method

along with aptitude tests.

Statement of Hypotheses

The selection of successful salespeople is a prevalent

issue within personnel. The review of possible means by

which to select salespeople pointed to two viable

procedures; tests and structured interviews. This study

will attempt to demonstrate the validity of tests for the

selection of individuals for an entry-level sales position.

Hypothesis one. Verbal ability as measured by the SRA

Verbal will be positively correlated with sales volume, and

managerial ratings of sales ability, customer service,

administrative duties, and the overall rating.

Hypothesis two. Numerical ability as measured by the

Employee Aptitude Survey (EAS) Numerical Ability Test will

be negatively related to average number of remakes and

service requests, and positively related to managerial

ratings of the ability to design and price treatments,

administrative duties, and the overall rating.

40

Hypothesis three. Spatial ability as measured by the

EAS Space Visualization Test will be negatively correlated

with average number of remakes and service requests, and

positively correlated with managerial ratings of the ability

to design and price treatments, administrative duties, and

the overall rating.

Hypothesis four. Sales attitudes as measured by the

Sales Attitude Checklist will be positively correlated with

sales volume, and managerial ratings of sales ability,

customer service, administrative duties, and the overall

rating.

CHAPTER II

METHOD

Subjects

Participating in this study were 251 decorator

consultants employed by a national retail chain. The

decorator consultant position is a direct sales position.

Typical duties include: (a) selling merchandise to

customers outside of the store, (b) measuring and

calculating window product sizes, (c) handling customer

complaints and questions, and (d) staffing in-store

decorating center.

Incumbent population. Employed by the retail chain are

1,504 decorator consultants. Decorator consultants are

predominantly caucasian females, 94% of the decorators are

caucasian and 96% are female. Of the decorators employed,

43% are under 40 years of age and 57% are over 40 years of

age. The average tenure of the decorators employed was 3

years and 6 months.

Job analysis sample. In the job analysis phase, 20

decorators were interviewed and 150 were sent task-list

questionnaires. A representative sample of decorators was

desired, so the job analysis interviews were conducted in

41

42

divergent geographical locations. Job analysis interviews

were conducted in California, Georgia, and Texas. Also to

obtain a representative sample, the task questionnaires were

sent to randomly selected decorators. Of the questionnaires

sent out, 144 (96%) were returned and used in the analysis.

Of the decorators who participated in job analysis

interviews, 100% were caucasian and 90% were female. In this

phase, 50% of the decorators who were interviewed were under

40 years of age, and 50% were over 40 years of age. The

average tenure of the decorators who participated in job

analysis interviews was 4 years and 2 months.

Field testing sample. In the field testing phase, 87

decorators participated. Criteria data were unavailable for

ten decorators, so the sample size in the final analysis of

this phase was 77. Field testing took place in California,

Ohio, and Texas. The geographical breakdown of the testing

sample was as follows: 40% were tested in California, 38% in

Ohio, and 22% in Texas. The number of decorators tested in

each location was dependent upon the number of decorators

who worked out of that particular location.

Of the decorators who participated in the field testing

phase of this study, 96% were caucasian and 95% were female.

In this phase, 30% of the decorators tested were under 40

years of age, and 70% were over 40 years of age. The

average tenure of the testing sample was 5 years and 5

43

months. The age and tenure of the testing sample are

somewhat inflated due to the elimination of ten decorators

who had not been employed with the company long enough to

generate criteria data. Of these ten decorators, 90% were

under 40 years of age and their average tenure was 2.5

months.

Experimental Design

The primary objective of this study was to develop a

selection process that was valid; valid, meaning a

relationship exists between predictors (instruments used to

assess the knowledge, skills, and abilities needed to

successfully perform in this position) and criteria

(measures of job performance). A concurrent criterion-

related validity study was determined to be the manner in

which to accomplish this objective. A concurrent criterion-

related validity study was also chosen due to the immediate

need for a new selection process because of financial loses

in terms of service requests, remakes, and turnover. A

concurrent study involves assessing incumbents' knowledge,

skills, and abilities via predictors and correlating these

results with criteria, measures of job performance. This

design allows predictor and criteria information to be

gathered simultaneously or within a short interval of each

other.

44

Criticisms of current designs include; "missing

persons," restriction of range, motivational and demographic

difference between incumbents and applicants, and

confounding by job experience. These criticisms have led

many to believe predictive designs are superior. However,

Barrett, Phillips, and Alexander (1981) found that these

criticisms had a minimal effect on the size of the validity

coefficient. Bemis (1968) empirically compared 71

predictive and 69 concurrent validities of the General

Aptitude Test Battery. This comparison indicated that the

two designs result in virtually identical validity

coefficients. The meta-analyses conducted by Schmitt et al.

(1984) revealed that "concurrent validation designs produce

validity coefficients roughly equivalent to those obtained

in predictive validation designs" (p. 407)

Predictor and Criterion Development

The primary objective of the job analysis was to obtain

information that will aid in the development of both

predictors and criteria. The job analysis interviews

resulted in the identification of 80 tasks. With the

assistance of custom decorating subject matter experts

(SMEs), these 80 tasks were sorted into activity areas. The

activity areas are as follows: (a) taking

measurements/designing and pricing treatments,

(b) consultation/selling to customers, (c) customer service,

45

(d) completing paperwork for orders, (e) prospecting

(obtaining leads/referrals), (f) updating/maintaining files

and records, (g) staffing the studio, (h) training-related

activities. The questionnaires were used to determine the

criticality of these 80 tasks. Eighteen personal

characteristics (knowledge, skills, abilities, and other

characteristics, hereafter, KSAs) were identified in the

interviews. The personal characteristics were reviewed with

the assistance of custom decorating SMEs and grouped

together to form job dimensions. Seven dimensions were

formed and the definition of these dimensions along with

their associated KSAs are listed in Appendix D. The

dimensions are as follows: sales ability, planning &

organizing, adaptability, attention to detail, verbal

ability, numerical ability, and spatial ability.

The decorators' ratings on the task questionnaires

indicated that they did not consider the 80 tasks as

difficult. Only six tasks out of eighty (7.5%) received an

average rating greater than three, which is defined as "more

difficult than half my tasks and easier than half". Not a

single task received a mean difficulty rating greater than

3.2. Since the eighty tasks received highly similar

difficulty ratings, this scale was not a central component

in determining the criticality of each task.

46

Frequency ratings and importance ratings were utilized

to determine the criticality of the tasks. All tasks

performed by less than 25% of the decorators surveyed were

to be eliminated, but not a single task was performed by

less than 25% of the decorators surveyed. A criticality

index for each task was formulated by multiplying the

frequency rating of the task by the importance rating of the

task. All tasks having a criticality index of six or less

(indicating moderate to low importance and moderate to low

frequency) were eliminated. Eight tasks were eliminated on

this basis. Tasks with a criticality index of twenty or

greater (indicating very high to high importance and very

high to high frequency) were viewed as critical. Sixteen

tasks had a criticality index of twenty or greater. The

task statements with the incumbent ratings are contained in

Appendix E.

Using the results of the task questionnaires and the

task-KSA matrix, the sixteen tasks which were deemed

critical according to the questionnaire ratings were

reviewed in terms of the KSA's required to successfully

perform these critical tasks. A matrix was generated that

shows the job dimensions relative to the sixteen critical

tasks (see Appendix G).

Based upon the information obtained in the job analysis

four tests were chosen to be used as predictors: the SRA

47

Verbal, the Employee Aptitude Survey (EAS) Numerical Ability

Test, the EAS Space Visualization Test, and the Sales

Attitude Checklist. Eight measures of job performance were

chosen to be used as criteria. Three behavioral criteria

were chosen sales volume, number of service requests, and

number of remakes. Managerial ratings of sales ability,

ability to design and price treatments, customer service,

administrative duties, and an overall rating were also

chosen to be used as criteria.

Predictors

Tests were determined though a review of the literature

to be the most appropriate means by which to assess the

knowledge, skills, and abilities needed to successfully

perform in this position. Four paper and pencil tests

composed the experimental test battery: SRA Verbal Form,

Employee Aptitude Survey (EAS) Numerical Ability, EAS Space

Visualization, and Sales Attitude Checklist. These

instruments were chosen to assess the knowledge, skills, and

abilities needed to perform the tasks deemed critical in the

job analysis. These instruments were also chosen based on

their technical adequacy in terms of reliability and

validity as well as the degree in which the tests met other

administrative requirements such as testing time and face

validity.

48

Testing time is an important concern because maximum

validity per unit of testing time is desired. In other

words, optimal utilization of testing time is desired.

Increasing validity by lengthening a test is possible, yet

uneconomical. Composing a battery of tests which each

measure a unique job-related factor is an efficient way in

which to increase validity of the test battery (Ruch & Ruch,

1980).

Face validity, the degree to which a test seems to be

relevant to the job, is also an important concern. An

applicant's motivation and reaction to the test battery are

effected by its face validity. If a particular test does

not seem related to the job, test performance may not

reflect actual abilities.

Since verbal ability was deemed critical, the SRA

Verbal was chosen to assess this ability. The SRA Verbal

form consists of linguistic and quantitative reasoning

items, 84 in all. The SRA Verbal Examiner's Manual (1984)

refers to the SRA as a "basic mental ability test" which

"measures primary mental abilities necessary to function

normally in almost any occupation in today's society" (p.1).

The SRA's test-retest reliability is .76 for the

linguistic score, .80 for the quantitative score, and .78

for the total score, each significant at the .01 level

(Thurstone & Thurstone, 1984). Another measure of

49

reliability is intercorrelations of subscores. Using an

occupationally mixed sample, the intercorrelations of the

SRA subscores were as follows: the quantitative score and

the linguistic score were correlated .75, the quantitative

score and the total score were correlated .92, and the

linguistic and the total score were correlated .95

(Thurstone & Thurstone, 1984). These intercorrelations

demonstrate the highly verbal nature of the quantitative

items.

In a study employing 27 chemical product salespersons,

the SRA linguistic score correlated .56 (p = .01) with sales

volume and the total SRA score correlated .43 (p = .05) with

sales volume (Thurstone & Thurstone, 1984). The SRA

quantitative score did not correlate at a significant level

with sales volume. In another study involving 150

department store floor salespersons, the SRA subscores

correlated from .24 to .26 at a significance level of .01

with supervisor ratings (Thurstone & Thurstone, 1984).

These studies demonstrated the applicability of the SRA to a

sales population.

An instrument which assesses numerical ability was

chosen because the following tasks: (a) calculate window

product sizes, (b) calculate drapery pricing, and (c)

calculate price breaks, along with the ability to add,

subtract, multiply, and divide whole numbers or fractions

50

and calculate percents were deemed to be critical. The EAS

Numerical Ability test was chosen since it contains

addition, subtraction, multiplication, and division problems

that employ whole numbers (Part I), decimals (Part II), and

fractions (Part III). It also contains problems that

require the calculation of percents (Part II).

The EAS Numerical Ability test has an alternate form

reliability of .87 (Ruch & Ruch, 1980). In a study

employing 30 dairy product salesmen, a correlation of .68

with supervisor rating was achieved (Ruch & Ruch, 1980).

However, in a study involving 19 dinnerware salesmen a

correlation with supervisory ratings of only .16 was found

(Ruch & Ruch, 1980). The sample size used in this study was

extremely small, thus the correlation may be arbitrarily

low. Two other factors led to the incorporation of the EAS

Numerical test into the experimental test battery; a testing

time of 10 minutes and the similarity of the test's content

to essential abilities and tasks identified in the job

analysis led to its selection.

Spatial relations ability was identified by decorators

as an essential ability needed to be a successful decorator.

The EAS Space Visualization was the instrument chosen to

assess this ability. The Space Visualization test uses the

block format which is a compromise between factorial purity

and predictive validity (Ruch & Ruch, 1980). The alternate

51

form reliability of the Space Visualization test was -found

to be .89 (Ruch & Ruch, 1980). In a study employing 19

dinnerware salesmen, the correlation was found to be .70

with supervisor rating (Ruch & Ruch, 1980). Since the test

is also face valid and has a testing time of 5 minutes, it

was chosen to be a part of the decorator consultant test

battery.

The decorators deemed critical a number of tasks and

abilities which were sales related. Thus, an instrument

that assessed sales ability was chosen, the Sales Attitude

Checklist. The Sales Attitude Checklist is a self-

descriptive questionnaire containing desirable and

undesirable behavioral attributes and attitudes of

salespeople (Taylor, 1985). The items are forced choice in

format.

No reliability information is available for the Sales

Attitude Checklist. The authors of the Sales Attitude

Checklist have not attempted to determine the reliability of

the test, because the existing methods by which to estimate

reliability are not adequate for an instrument such as this

(Taylor, 1985). However, validation evidence in sales

situations has demonstrated that a relationship exists

between Sales Attitude Checklist test scores and job

performance. In a study involving 197 new car salespeople,

a correlation of r = .31, significant at the p = .01, level

52

was obtained between test scores and average monthly

earnings (Taylor, 1985). In another study employing 166

railroad traffic salespeople, correlations ranged from .02

to .44. The wide range of correlations resulted from

groupings based on age and position (Taylor, 1985). In

addition to the validation evidence for a sales population,

the face validity of this instrument led to its selection.

Criteria

Behavioral criteria and managerial composite ratings

were employed in order to assess on-the-job performance.

The behavioral criteria used were average sales volume,

average number of.service requests, and average number of

remakes. These averages were taken over a six month period,

from March through August, 1989. Sales volume is the amount

of custom decorating merchandise the decorator sells. A

service request is a request by a customer to have the

decorator whom she or he purchased from solve one or more

problems she\he is having with products that were purchased.

Decorator errors include measurement errors in length and

width, as well as specification errors such as wrong fabric

specification. These errors result in the manufacturing of

products that do not meet the customers' needs and wishes

and thus have to be remade.

Of the participating decorators, 84% had sales volume

figures for the entire six month interval. Twelve of the

53

participating decorators, 16%, did not have sales volume

figures for the entire six months because they were on

vacation or sick leave, or they were hired within the six

month interval in which figures were collected. The number

of remakes attributable to each decorator for the entire six

month interval were obtained for only 28% of the

participating decorators. No figures were available for the

number of service requests attributable to each decorator

for the entire six months. The lack of figures for the

entire six month interval is due to the absence of a

standard method of recording keeping for these two

variables, did not exist until June 1989. In June, both

remakes and requests began to be tracked using a computer

program.

Managerial ratings were also used as criteria. Sales

managers rated decorators in four areas; sales ability,

ability to design and price treatments, customer service,

and administrative duties. They also gave each decorator an

overall rating. The sales managers were asked to review

each participating decorator's performance over a six month

period (from March through August, 1989) and rate their

performance on a scale of 0 to 5. The rating codes were as

follows: 0 = not applicable/unable to rate, 1 =

unsatisfactory, fails to meet job requirements, 2=

improvement needed to meet job requirements, 3 = meets job

54

requirements, 4 = exceeds job requirements, 5 = outstanding,

greatly exceeds job requirements (see Appendix A).

Managerial ratings were used as criteria by averaging

the ratings assigned to all the questions in a given area.

Ratings on single questions were not used as criterion. For

example, the area of sales ability had four questions and

the average of these four questions was the composite rating

for sales ability. Also, used as a criterion was an overall

rating which was obtained by averaging all eleven questions

on the rating form. The overall rating directly given by

the sales managers was not used as a criterion because the

rating was open to divergent interpretations. Five

managerial composite ratings were used as criteria.

Procedure

The primary objective of this study was to demonstrate

that a relationship exists between decorators' test scores

and their job performance. In order to accomplish this

objective several steps had to be carried out. These steps

are as follows: job analysis, test selection, incumbent

testing, and statistical validation.

A thorough investigation of the decorator consultant

position was first conducted. This job analysis had three

primary goals: (a) the identification of tasks performed by

decorator consultants, (b) the determination of tasks which

are critical to success as a decorator consultant, and (c)

55

the identification of knowledge, skills and abilities needed

to perform these critical tasks effectively. Interviews and

questionnaires were used to accomplish these goals, but

first existing job information was collected and studied to

become familiar with the position. This information

included the existing job description and relevant job

descriptions from the Dictionary of Occupational Titles.

Also, individuals from the American Society of Interior

Designers and the Foundation for Interior Design Education

and Research were contacted to familiarize the analysts with

the position.

Interviews were then conducted with decorators in the

field to identify the tasks which they perform and the

personal characteristics (e.g., knowledge, skills, and

abilities) needed to perform these tasks. Interviews were

also conducted with seven subject matter experts (SME); five

sales managers and two trainers.

In order to determine the criticality of the tasks

which were identified in the interviews, 150 questionnaires

were sent to randomly selected decorators. First, the

decorators were asked whether they performed the task, if

they never performed the task, they were asked to circle "0"

on the frequency scale and move on to the next task. If the

decorators did perform the task, they were asked to rate the

task on three scales: frequency, difficulty, and

56

importance. Each task was analyzed to determine the

frequency of each of the responses and the mean response for

each scale. Job experts were then asked to identify which

knowledge, skills, and abilities that were identified in the

interviews were required to perform each of the tasks

identified in the interviews. This resulted in a large task-

KSA matrix. Tests were then selected to assess the

knowledge, skills, and abilities needed to successfully

perform the tasks which were rated as critical. The

instruments which were chosen are described above.

Incumbent testing was the next step, testing took place

in the custom decorating service centers. The service

centers were chosen because they provided adequate space,

lighting, and ventilation. Groups of two to ten decorators

were tested at one time. With each group, standardized test

administration procedures were followed as specified by the

test publishers (see Appendix B). The test battery was

administered by individuals with advanced training in the

testing field. The decorators were ensured that their test

results would be kept confidential and would be used for

research purposes only. Testing time was approximately one

hour for each group.

The tests were scored by hand following standardized

scoring procedures (see Appendix C). The test results were

then statistically analyzed using Statistical Analysis

57

Systems (SAS) software. Basic descriptive statistics were

computed for each test. Frequency tables of the test scores

were run in order to provide the decorators with feedback.

Pearson product-moment correlations were obtained for the

predictors with the criterion. The predictors included the

total score of each test, four in all. The criterion

included the behavioral criteria and the managerial

composite ratings, eight in all. The bivariate

distributions that resulted were also examined (see Appendix

F). Also computed were intercorrelations of the predictors

and intercorrelations of the criterion. An analysis of

variance procedure was conducted using age as the

independent variable. Analysis of variance was also

employed using testing location as the independent variable

to ascertain if the decorators which were tested in

different locations obtained significantly different test

scores. In addition, the correlation between job tenure and

age, and the correlations between job tenure and the test

scores were computed.

CHAPTER III

RESULTS

The primary objective of this study was to demonstrate

that a relationship exists between decorators' test scores

and measures of their job performance. Such a relationship

was observed, three of the four tests within the test

battery were significantly correlated with two or more

criteria. The decorators' test results on the Sales

Attitude Checklist demonstrated the strongest relationship

with the measures of job performance used within this study.

The decorators' scores on this test correlated at a

significant level with six of the eight criteria. The

decorators test results on the SRA Verbal did not

significantly correlate with any one criterion. Overall, a

stronger relationship was seen between the test scores and

the managerial ratings, than between the test scores and the

behavioral criteria.

Descriptive statistics for the four tests and the eight

performance measures are given in Table 4. Descriptive

statistics published in the test manuals which were obtained

by similar subjects are given in Appendix H. The

correlational analyses conducted yielded the correlation

matrix in Table 5.

58

59

Table 4

Descriptive Statistics for the Predictors and Criteria

M S. D. Range N

Predictors

SRA Verbal

NumericalAbility

SpaceVisualization

Sales AttitudeChecklist

CriterionObi ective

Avg. SalesVolume

Avg. # ofRequests

Avg. # ofRemakes

Subjective

Sales Ability

Design & PriceTreatments

CustomerService

AdministrativeDuties

Overall Avg.Rating

44.4

26.0

18.6

31.7

10.9

10.8

8.6

5.4

$17,082

5.1

1.7

3.4

3.3

3.2

3.3

3.3

$6,057

3.5

1.6

.66

.51

.70

.58

.50

15 - 75

7 - 55

0 - 36

21 - 42

$808 - $28,593

0 - 22

0 - 13

1 - 5

2 - 4

2 - 5

2 - 5

2 - 5 77

77

77

77

67

77

76

76

77

77

77

77

60

Table 5

Pearson Product-Moment Correlations between the Test Battery

and Job Performance Measures

EAS EAS SalesSRA Numerical Spatial Attitude

Verbal Ability Visualization Checklist

Avg. SalesVolume

Avg. # ofRequests

Avg. # ofRemakes

ManagerialRatings

SalesAbility

Design &Price Trmt.

CustomerService

Admin.Duties

OverallAvg. Rating

-. 076

(77)

-. 012(76)

-. 137(76)

.023

(77)

-. 104

(76)

-. 127

(76)

.014

(77)

.116(77)

.068(77)

.134

(77)

.097

(77)

.198(77)

.179

(77)

.187

(77)

.247*

(77)

.246*

(77)

.008

(77)

-.037(76)

-.117(76)

.269*

(67)

.115(66)

.115

(66)

.119

(77)

.238*

(77)

.180

(77)

.312**

(77)

.237*

(77)

.495***(67)

.368**(67)

.282*(67)

.250*(67)

.484***

(67)

** = p < .01, *** = p < .001* = p < .05,

61

The Sales Attitude Checklist scores of ten decorators

were not included in any statistical analyses, because the

checklist was not completed according to the given

instructions.

The data in Table 5 display the statistical support

found for hypotheses two, three, and four. The EAS

Numerical Ability test was positively correlated at a

significant level with managerial ratings of administrative

duties and overall ratings, however it was not correlated at

a significant level with managerial rating of the ability to

design and price treatments. The EAS Space Visualization

test was significantly correlated with each of the

managerial ratings that was hypothesized in hypothesis

three. Average number of service requests and average

number of remakes were not significantly correlated with the

EAS Numerical Ability test or the EAS Space Visualization

test as was hypothesized. The Sales Attitude Checklist

correlated significantly with each criterion that was

hypothesized, as well as with an additional criterion,

managers' ratings of ability to design and price treatments.

No statistical support was found for hypothesis one, the SRA

Verbal did not correlate at a significant level with any one

criterion.

The bivariate distributions of the predictors with the

criteria were examined for nonlinearity, a number of these

62

distribution are in Appendix F. Linear, power, logarithmic,

and exponential equations were fit to the data. Linear

equations resulted in the best fit. Thus, the relationship

between decorator consultants' test performance and their

job performance appears to be linear.

Several supplementary analyses were carried out in

addition to the primary analysis. These are described

below. The predictors were intercorrelated to examine the

extent of overlap of the tests (see Table 6).

Table 6

Intercorrelations of the Experimental Tests

SRA Num. Space SalesVerbal Ability Visual- Attitude

ization Checklist

SRAVerbal 1.00 ---- ---- ----

NumericalAbility .57* 1.00 ---- ----

SpatialVisualization .38* .41* 1.00 ----

Sales AttitudeChecklist .04 .06 -.03 1.00

* = p < .001

63

A number of the eight criteria were significantly

correlated with each other (see Table 7). Average sales

volume, a dollar-valued performance measure, correlated

significantly with four of five managerial ratings. A

significant relationship was also found between the

managerial ratings.

Table 7

Correlation Matrix of the Criterion Measures

Avg Avg Avg Sales Trmt. Cust. Admin. Oversales req remk Serv. Duties all

Avgsales 1.00

Avgreq .45** 1.00

Avgremk .30* .58** 1.00

Sales .67** .24 .15 1.00

Trmt. .18 -. 11 -.07 .43** 1.00

CustServ .42** .15 -.02 .63** .41** 1.00

Admin.Duties .34* .12 -.12 .49** .55** .73** 1.00

Overall .51** .14 -.01 .81** .70** .88** .85** 1.00

** = p < .001* = p < .01

64

The scores on the test battery of decorators under 40

years of age and those over 40 years of age were examined.

The descriptive statistics for each test by age are

presented in Table 8. These two age groups were chosen

because The Age Discrimination in Employment Act of 1967, as

amended in 1978, prohibits discrimination on the basis of

age between the ages of 40 and 70, unless age is a bona fide

occupational qualification.

Similar data by sex and race is not presented because

the testing sample contained only 4 male decorators (5%) and

only 3 non-caucasian decorators (4%). The percentage of

minority incumbents in this study reflects the percentage

that are in the incumbent population, therefore validity

analyses by racial group was precluded.

Table 8

Descriptive Statistics for Each Test by Age

TEST AGE GROUP N M S.D. F

SRA Verbal < 40 23 43.4 10.8 .57> 40 53 45.4 10.2

Numerical < 40 23 28.6 11.4 1.61Ability > 40 53 25.2 10.2

Space < 40 23 23.0 7.8 9.07*Visualization > 40 53 16.9 8.2

Sales Attitude < 40 20 33.1 5.1 1.99Checklist > 40 46 31.0 5.5

*= p < .01

65

An analysis of variance procedure was performed using

age as the independent variable. This analysis revealed

that a significant difference between decorators test scores

who were under 40 years of age and those who were over 40

years of age existed on the Space Visualization test (F =

9.07, p < .005). The other three instruments did not show

significant differences between the scores of the two age

groups. Mean score differences in z-score units between age

group were computed (see Table 9). The differences between

the groups' scores were less than one standard deviation on

each of the four tests.

Table 9

Mean Score Differences in Z-Score Units between Decorators

Under 40 Years of Age and Those Over 40 Years of Age

Test U-O

SRA Verbal -.18

Numerical Ability .32

Space Visualization .71

Sales Attitude Checklist .39

Note. The differences were computed using the following formula

Under 40 group mean - Over 40 group meanTotal sample standard deviation

66

An analysis of variance procedure was also carried out

using testing location as the independent variable. No

significant differences between decorators' test scores

tested in different locations were found.

Using correlational analysis the relationship between

job tenure and test scores was also examined. The

correlations (see Table 10) indicated that longer tenure

Table 10

Correlation of Job Tenure with Test Scores

Test r p

SRA Verbal -.13 .26

Numerical Ability -.18 .12

Space Visualization -.27 .02*

Sales Attitude Checklist .18 .15

does not necessarily result in higher test scores or vice

versa. However, scores on the Space Visualization test were

negatively correlated at a significant level with tenure.

This indicates that decorators with longer tenure obtain

lower scores on this test. This result is likely due to the

relationship between tenure and age, because longer tenure

is associated with greater age. Since it was found that

decorators over 40 years of age scored significantly lower

67

on the space test than decorators under 40 years of age,

those decorators with longer tenure are also likely to score

lower.

DISCUSSION

Overall, the results of this study were quite

favorable. Three of the four tests within the experimental

test battery demonstrated concurrent-related validity and

were recommended to be used in the selection process for the

decorator consultant position.

The Sales Attitude Checklist was significantly

correlated with the behavioral criterion, average sales

volume, as well as with each of the managerial ratings. Two

explanations for the validity of the Sales Attitude

Checklist are possible. As Ghiselli (1966, 1973) found in

his reviews of the literature, personality measures are a

valid means of predicting sales success and the Sales

Attitude Checklist is a personality measure. Hogan,

Carpenter, Briggs, & Hansson (1985) maintain that

personality measures can be valid predictors of job

performance when they are designed for the specific

population in question and the Sales Attitude Checklist was

developed specifically for sales selection.

The EAS Spatial Visualization test was significantly

correlated with several managerial ratings. Two

explanations for the correlations that were achieved are

68

69

given. Tests of spatial ability have demonstrated validity

in predicting job proficiency of sales clerks and salesmen

(Ghiselli, 1966, 1973), thus this type of test was

applicable in this study. Another possible explanation is

that the position of decorator consultant is a specialized

sales position with one of its job requirements, spatial

ability.

The EAS Numerical Ability Test was significantly

correlated with mangers' ratings of administrative duties

and the overall average rating. The validity of this test

may be due to the specific job requirements of this position

and/or due to the validity of arithmetic tests in predicting

job proficiency in sales clerks (Ghiselli, 1966, 1973)

The SRA Verbal did not correlate at a significant level

with any one criterion. Three explanations for the lack of

validity between the SRA Verbal test results and the

measures of job performance used are possible. First, the

SRA Verbal did not seem job-related to the decorators, as

expressed by a number of decorators during testing. If a

test does not appear face valid it can effect the motivation

as well as the performance of the examinees.

Second, the reliability of an instrument effects the

validity of that instrument. The test-retest reliability

coefficients of the subscores and total score of the SRA

Verbal were reported to range from .76 to .80 (Thurstone &

70

Thurstone, 1984). These reliabilities are somewhat lower

than desired for a selection instrument.

Third, a "basic mental abilities" test such as the SRA

Verbal may not have been appropriate for this position. The

selection of specialized salespeople may require the use of

more specialized tests to assess specific knowledge, skills,

and abilities that are needed to be successful in that

position rather than the assessment of basic mental

abilities.

The SRA Verbal was not included in the final

recommended test battery because of the lack of concurrent-

related validity and face validity. Also, the SRA Verbal

was not included due to low reliability, high

intercorrelations with other predictors, and a long testing

time, 15 minutes, in comparison to the other tests within

the experimental test battery.

A stronger relationship was seen between the test

scores and the managerial composite ratings than between the

test scores and the behavioral criteria. Two of the three

behavioral criteria, average number of service requests and

average number of remakes, were not significantly correlated

with any of the predictors. This may be due to the very

small percentage (28%) of decorators that had these figures

for the entire six month interval. Since computer tracking

of these two variables just began in June, 1989 it was not

71

possible to obtain these figures for the entire six month

interval. Three months of figures (June through August,

1989) were obtained for 53% of the decorators which were

tested and two months of figures (July and August, 1989)

were obtained for 99% of the decorators tested . However,

the correlations were in the hypothesized direction; high

scores on the numerical and space tests were associated with

fewer service requests and remakes.

Another possible reason for the stronger relationship

between the test scores and the managerial ratings is the

rating form itself. The selection battery and the rating

form were both developed from the information obtained in

the job analysis. The form also included definitions of

common rater errors to aid the sales managers in making

their ratings.

A multiple cutoff approach (establishing a minimum

passing score for each test) was recommended. The passing

score proposed for the EAS Numerical Ability test was a

total score of 17 or greater. A passing score of 12 or

greater was suggested for the EAS Space Visualization test.

The passing score suggested for Sales Attitude Checklist was

a total score of 28 or greater. Therefore, proficiency in

one area can not compensate for deficiency in another. The

applicant must demonstrate a minimum level of proficiency in

three areas (numerical, spatial, and sales) in order to

72

achieve favorable results in this first phase of the

selection process, and thus be able to proceed to the next

phase, the structured interview.

Passing scores were set considering two goals of the

selection process: upgrading the quality of the workforce

and managing applicant flow for an entry level position. To

upgrade the quality of the workforce, each passing score was

set at the level that excluded the bottom 20% of the

incumbents who took that test. Of the incumbents which were

tested, 47% received scores below the passing scores on one

or more of the tests. This indicates that if the incumbents

had been applicants, 47% would not have been hired. These

results indicate that the proposed level of the passing

scores would help accomplish the objective of a higher

quality workforce. The selection ratio (SR) for this

position varies from .05, hiring 1 in 20 applicants, to .20,

hiring 1 in 5 applicants. The selection ratio varies

depending on geographical location and time of year. These

passing scores would help the organization to be more

selective when they have an ample number of applicants (SR =

.05). These passing scores would also encourage improved

recruitment of applicants.

To manage applicant flow, the test battery was

recommended to be used as an initial screening device

eliminating those individuals that do not demonstrate the

73

necessary knowledge, skills, and abilities needed to be

successful in this position. Thus, those individuals do not

proceed any further in the selection process, saving their

time as well as the company's time.

Multiple regression was not suggested, because it is

not practical to expect individuals within the field to plug

raw scores into an equation. Field personnel would likely

be resistent due to the complexity of the process and the

time required. This resistance may result in numerous

errors or even abandonment of the selection process.

Ranking was not proposed for two reasons. The

organization has a goal of representativeness and if ranking

was used, achievement of this goal would be difficult due to

typical minority/majority differences in test performance.

Also, the test battery was proposed to be used as an initial

assessment device followed by a structured interview to

assess other job requirements. Thus, a pass/fail approach

seems to be more appropriate.

Three follow-up studies are recommended. The number of

remakes and requests attributable to each decorator for the

entire six month interval were only obtained for a small

percentage of decorators who were tested, this limits the

reliability of these two criteria. Thus, a follow-up study

should be conducted in order to obtain six months of data

concerning the number of service requests and remakes

74

attributable to the decorators which were tested. These

data could then be correlated with the numerical and space

test scores to ensure that a relationship exists as

hypothesized in hypothesis two and three.

Another follow-up study should be conducted to factor

analyze the data. The intercorrelations of the SRA Verbal,

EAS Numerical Ability, and EAS Spatial Visualization were

somewhat higher than expected. This indicates the

possibility of a common second order factor. Thus, if the

data were factor analyzed and a second order factor was

found, then a more advantageous means of selection could

possibly result from using multiple regression with the

Sales Attitude Checklist.

Another follow-up which should be conducted is an

empirical validation study of the structured interview

and/or the entire selection process. The development and

validity of the second phase of the selection process, the

structured interview, is not thoroughly discussed in this

document. However, the basic features of the structured

interview are as follows: (a) each applicant is asked the

same questions, (b) each question is directly related to a

dimension, (c) each question focuses on obtaining examples

of past behavior, and (d) rating anchors are given to guide

consistency of rating.

75

The use of a structured interview was proposed for

numerous reasons. A review of the literature indicated that

two selection procedures were viable means of selection for

the purposes of this study: tests and a structured

interview. The job analysis revealed a variety of

knowledge, skills, and abilities were needed to successfully

perform in this position. By using a structured interview

knowledge, skills, and abilities which would be difficult or

even impossible to assess with paper and pencil tests may be

assessed. The use of a structured interview was also

proposed because as Opren (1985) found, individuals

responsible for hiring generally refuse to stop using the

interview as their primary selection technique even when

informed that tests are more valid predictors of performance

in that job. An interview is the primary selection

procedure that is being utilized to hire decorator

consultants at this time. Thus, by having a selection

process which attempts to measure each KSA in the most

appropriate manner as well as takes into account the

individuals who will administer the process, a valid process

is more likely to be developed as well as sustained.

This study demonstrates the utility of the entire

validation process. If a through review of the literature,

job analysis, and selection of assessment instruments are

first conducted, followed by standardized administration of

76

the selection instruments and comprehensive statistical

analyses, then the objective of demonstrating that a

relationship exists between predictors, selection

instruments, and criteria, measures of job performance, is

achievable. This relationship was observed in this study

due to adherence to the above statement. All that remains

to be done is the cross validation of the present findings.

This study illustrates that the selection of successful

sales personnel was possible by using a personality measure

that was developed specifically for sales selection.

Successful sales selection was also achieved using tests

that measured specific abilities needed to perform

successfully. However, the differentiation of successful

from unsuccessful salespeople was not achieved using a

general mental abilities test. Further research should be

conducted concerning the development of personality tests

for specific populations. If personality tests developed

for a specific populations are valid predictors of

performance within those populations, this would have impact

on test development, test usage, and validation results.

This study also indicates that the measurement of specific

abilities rather than the measurement of "general mental

abilities" may result in a more valid selection process,

further research should be conducted concerning this issue.

APPENDIX A

DECORATOR CONSULTANT SELECTION PROGRAM

PERFORMANCE REVIEW

77

78

DECORATOR CONSULTANT SELECTION PROGRAMPERFORMANCE REVIEW

Name of the Decorator:

Social Security #: -- --

INSTRUCTIONS TO SALES MANAGERSCircle the ratings on the following pages as they apply to the decorator

shown above. Use the following rating codes; and focus your ratings on thepast six months only.

0 - Not applicable/Unable to rate1 - Unsatisfactory, fails to meet job requirements2 - Improvement needed to meet job requirements3 - Meets job requirements4 - Exceeds job requirements5 - Outstanding, greatly exceeds job requirements

Evaluations of this nature call for judgments to be made. Judgments aresometimes subject to error and/or bias. Common types of errors are listedbelow along with suggestions of how to minimize them.

ERROR 1:

ERROR 2:

ERROR 3:

ERROR 4:

ERROR 5:

Rating a decorator in all areas according to your generalimpression of the decorator. Concentrate on rating eacharea separate from your general impression.

Rating all decorators in each area at the same level -average, regardless of their actual performance in thoseareas. Do not hesitate to give high or low ratings if thedecorator's performance warrants such ratings.

Rating all decorators too high or too low. Recognize thatdecorators perform at different levels in different areas.Rate them accordingly.

Ratings based on recent performance only. Ratings shouldreflect the decorator's performance over the entire sixmonth period.

Ratings influenced by the decorator's social status, sex,age, etc. Consider only job-related activities when ratingdecorators.

THANK YOU FOR YOUR COOPERATION AND ASSISTANCE

Appendix A -- Continued

0 - Not applicable/Unable to rate1 - Unsatisfactory, fails to meet job requirements2 - Improvement needed to meet job requirements3 - Meets job requirements4 - Exceeds job requirements5 - Outstanding, greatly exceeds job requirements

SALES ABILITIES

1. CUSTOMER INTERACTION:arrives promptly, greets customer,maintains conversation, listens well,answers questions

2. PERSUASIVE COMMUNICATION:determines what the customer wants(intended uses & preferences ofproducts), advises customers, handlesobjections, & follows through with sale

3. SALES PRESENTATIONS:presents appropriate product samples& pictures of completed treatments,knowledgeable of all products

4. SALES VOLUME:volume as compared to other decorators

DESIGN & PRICE TREATMENTS

1. ACCURATELY MEASURES FORPRODUCT MANUFACTURING &INSTALLATION:measures inside & outside windowdimensions, drapery length & width,carpet yardage

2. EFFECTIVELY DESIGNSTREATMENTS:requires few remakes

CIRCLE RATINGS

0 1 2 3 4 5

0 1 2 3 4 5

0 1 2 3 4 5

0 1 2 3 4 5

0 1 2 3 4 5

0 1 2 3 4 5

79

Appendix A -- Continued

0 - Not applicable/Unable to rate1 - Unsatisfactory, fails to meet job requirements2 - Improvement needed to meet job requirements3 - Meets job requirements4 - Exceeds job requirements5 - Outstanding, greatly exceeds job requirements

3. ACCURATELY CALCULATES PRODUCTSIZES, AMOUNTS, & PRICES:calculates drapery & drapery trim yardage,fabric for accessory items, labor charges,& price breaks

CIRCLE RATINGS

0 1 2 3 4 5

CUSTOMER SERVICE

1. SPECIAL FUNCTIONS: 0 1 2 3 4 5informs customer of payment options,& delivery date. Also, handles customercomplaints & processes remakes

2. MAINTAINS CUSTOMER CONTACT: 0 1 2 3 4 5gives customers status reports on theirorders, inquires about customer satisfaction,conducts mailouts, attains referrals

ADMINISTRATIVE DUTIES

1. ACCURATELY COMPLETESPAPERWORK:fills-out work orders, purchase orders,sales slips, & right to cancel slips

2. EFFECTIVE INTERNALCOMMUNICATION:communicates effectively with; servicecenter, the credit department,& the studio coordinator

OVERALL RATING AS ADECORATOR CONSULTANT

0 1 2 3 4 5

0 1 2 3 4 5

0 1 2 3 4 5

80

APPENDIX B

ADMINISTRATION PROCEDURES

81

82

ADMINISTRATION PROCEDURES

I. VERBAL ABILITY (SRA Verbal Form)

Distribute the following items to each examineeSRA Verbal Form2 pencils2 pieces of scratch paper (inform examinees thatcalculators and any other computational aidsshould not be used)

Instruct the examinees toPRINT THEIR NAME in the blank provided on the righthand side of the form and ignore the other blanks

READ THE DIRECTIONS and WORK THROUGH the sample testproblems

While the examinees are reading the directions andworking through the sample problems the examiner shouldassure that everyone understands:

-how to work the problems-how to mark their answers

The examiner should allow as much time as needed by theexaminees and answer any questions by referring to theappropriate sentence in the printed instructions on the testform. When everyone has completed the sample problems andall questions have been answered, the examiner gives thestarting signal: "BEGIN"

The examinees should be allowed exactly 15 MINUTES to work.At the end of 15 minutes the examiner should say: "STOP.Put down your pencil & close your test booklet."

Appendix B -- Continued

II. NUMERICAL ABILITY

Distributea test form (directions side up)2 pencils with erasers2 pieces of scratch paper (inform examinees calculatorsand any other computational aids should not be used)

Instruct examinees-NOT to turn the sheet over until the signal is given-PRINT THEIR NAME in the blank provided on the lefthand side of the test form and ignore the other blanks

THEN SAY:I am going to read the directions with you. Follow

them carefully. Look at the sample problems below. Eachproblem is followed by four possible answers and an "X."You are to work each problem and put a heavy black markbetween the little dotted lines below the correct answer.If the correct answer is not given, make a heavy black markbetween the dotted lines below the X. Now work the sampleproblems below. The first one has been answered correctly.

Allow time for the examinees to answer the sample problems.Then say: Beginning with sample problem number 2, youshould have marked 6, 25, X, 13. Are there any questions?Clarify any questions. Then say:

On the back of this sheet are 75 problems. They aredivided into 3 parts. When the signal is given you are toturn this sheet and work as many of these problems as youcan beginning with Part I. At the end of 2 minutes I willsay "Stop on Part I, go to Part II." After 4 minutes I willsay "Stop on Part II, go to Part III." You will have 4minutes for Part III. If you finish a Part early, checkyour work on that part while waiting for the signal to go tothe next part. Are there any questions?Clarify any questions. Then go on:

Work as fast and accurately as possible. Remember thatthe correct answer is not always given. When the correctanswer is not given, mark the space below "X." Make nomarks except your answers on the reverse side of the sheet.If you want to change an answer, erase completely.

READY. . .GO!

At the end of exactly 2 minutes say:STOP on Part I. GO on to Part II.

At the end of exactly 4 more minutes say:STOP on Part II. GO on to Part III.

At the end of exactly 4 more minutes say:STOP (and collect the papers)

8-3

Appendix B -- Continued

III. VISUALIZE SPATIAL RELATIONSHIPS (Space Visualization)

Distributea test form (directions side up)(pencils have previously been distributed)

Instruct examinees-NOT to turn the sheet over until the signal is given-PRINT THEIR NAME in the blank provided on the lefthand side of the test form and ignore the other blanks

Then say:I am going to read the test directions with you. In the

piles of blocks shown below, all the blocks are the samesize and shape. Your task is to look at each lettered blockand figure out how many other blocks in the pile it touches.Look at the first pile of blocks shown below. Block Atouches 2 other blocks - one above and one below.Therefore, to the right of the letter A, the answer spaceunder 2 has been marked. Note that Block D is not countedas touching Block A, because they come together only attheir corners. Count only the number of blocks touchingsides, tops, bottoms, or ends. Now look at Block B. It iseasy to see that it touches the blocks marked C and D, butif you look carefully you will see that it also touches theblock marked E. Because Block B touches 3 other blocks, thethird answer space following the letter B has been marked.The correct answers have also been marked for C, D, and E.Check them now to see that you agree with answers given.

Allow time for the examinees to inspect the first blockpile. Say:

Now look at the next pile of blocks below. Block Atouches 6 other blocks-1 on the left, 2 on the right, and 3below. See if you can find them all (Allow Time). Now markthe answer spaces to show the number of blocks touching B,C, D, and E (Allow Time). You should have marked 1 for B, 5for C, 2 for D, and 6 for E. If you have made any mistakes,check them carefully. Do you have any questions?

Clarify any questions. Then go on:When the signal is given, turn the page and work as

many of the problems like these as you can in 5 MINUTES. Inmarking your answers, make a heavy black mark between thelittle dotted lines below the answer you have chosen. Ifyou want to change an answer, be sure to erase completely.

READY...GO!

At the end of exactly 5 MINUTES say:STOP (and collect the papers)

84

Appendix B -- Continued

IV. SALES ATTITUDES (Sales Attitude Check List)Distribute

A test form (directions side up)(pencils have previously been distributed)

Instruct examinees-PRINT THEIR NAME in the blank provided on the left

hand side of the test form and ignore the other blanks

Then say:This is a measure of your sales attitudes and habits.

Now read the printed instructions silently while I read themaloud. This booklet contains statements that are commonlyused by salespeople to describe their attitudes andbehaviors. These statements are grouped into sets of four.Read over the four statements in a set and think of yourperformance as a salesperson. Select the one statement inthe set that is most like you. Put an X in the box besidethat statement in the column headed M (for most). Thenconsider the remaining three statements in the set. Decidewhich one of these three is least like you and put an X inthe box beside that statement in the column headed L (forleast). Leave the boxes besides the other two statements inthe set blank.

Look at the completed example below. Note that one(and only one) box has been marked in the M column and one(and only one) box in the L column.

At times you may find that it is difficult to decidewhich statements to mark because you feel that none of thestatements in a set describes you very well. Make the bestchoice you can. Do not skip any sets, because the bookletcan not be scored properly if you do not work through everyset. Be sure that in each set you always mark one statementas most like you and one statement as least like you, andthat you leave the remaining two statements unmarked.

If you wish to change an answer, draw a circle aroundthe choice you have marked. Then put a new X in the boxbeside the statement that you feel is a better choice.There is no time limit for this checklist.

Answer any questions. Then say:Even though some choices will be difficult to make, do

not spend too much time on any one item. If the choicesseem about equal to you, make the first one that comes toyour mind, but DO NOT omit any items or your Checklistcannot be scored. Be sure to mark one 'M' and one 'L' ineach set. If you want to change an answer, draw a circlearound your first 'X' and then mark your new answer.

When the applicants are finished collect all materials.Make sure the applicant's name is on each part of the test.

85

APPENDIX C

SCORING PROCEDURES

86

87

SCORING PROCEDURES

I. NUMERICAL ABILITY

*Place the Numerical Ability RIGHTS key, printed sideup, over the test form so that all edges line up.The key must be positioned so that only answer spacesare visible through the holes.

*Count the number of answer marks showing through theholes (in parts I-III), this is the total rightsscore. Record this score on the applicant's ScoreRecord in the appropriate blank

*In the same manner, place the WRONGS key over theanswer sheet & count the number of marks showing

through the holes (in parts I-III), this is the totalwrongs score. Record this score on the applicant'sScore Record.

*Use the enclosed Numerical Ability Table (p. 8) toobtain the Total Score

- Go down the Wrong Score column until you findthe row in which the applicant's wrongs scorefalls

- Trace this row across to the column whichcorresponds to the applicant's Rights Score

- The number in the body of the table at thisintersection of the wrongs score row & therights score column is the Total Score

- Record this score on the applicant's ScoreRecord

*For example, if an applicant obtains a rights scoreof 21, and a wrongs score of 20, then the applicant'stotal score would be 16. Similarly, a rights scoreof 55 and a wrongs score of 4 would result in a totalscore of 54. See the table for these answers.

Appendix C -- Continued

Table C-l

Numerical Ability Table

0.N

ti

F,N

F,S

F,6

#4

.4F,

0

F,

0.N

N

N

p.N

3%4

O

#4

6

f6#4

4

60#4

N

.4

N

8 4

'4

#4

.4

.4

.40

'4

0.

0.

3%

N

N

6

F,

N4

0

nI n

nh nnn

nnn

fin "

r n anf F

nm@nnnne n

N.10

nnnj

n n N

n9 n

00.0n Na.0 h

N N N

a h %0

h O

NNNr n NN N N4

O a aN r4 4

r4 V4 rd

9%

r4 r4 r4

66l

,4 f 4

f6 F,4 O

10 n N

r,.400

a00.

a0 h ,4

n

0.03%

0006

'.44.

3%66

'.4.4.

IA m.

IVjnM N

ri4 O

0040

aNN

nN N

nejej00.0nlj@j

0oI.0

Inq*n

vNN NCNNNnN NNri0

A 4ONNf9eO1

.j~j4j

03%'0

.jr43%66b

In e e4r4 r4 r1rA h

r4 r4 r4Ajn N

r!4 Ae4

t, r 4 0At r4 O4

r4 rlO A cr4

A co '

14 1% j

N0 60.N 1060

1 4 .4,44 jff.F

W 4 V4 V 4 49I a;:La 400161

88

O oN N N01oN N

nN N

.- %to

rm N

.400.

N N N

n~j"00.0

n N

NNN0.0ON('4

03%'@

"4""

3%'06""#4

6646

.j 0 a

.4.4,

('4.404

"4""

.400.

"#4.41

to qv1A Ae4

fN(00.0

4.404

000%4040

0006.4.4.4

0006e 6 -#

.400

.4.4

.4e4

0.03%

03%'

3%66

6OO6

661'S

6(5(4

nrl,4

#4,40

O400

a

N

.NNN

a0 t

N NN*4 N

NNIO A ANC'.

#4 #4

O4A

#44

n#4.4#- .j #4

.j,40

%a 0 -AAA

.400.'

'4 ,4,ee

.4.A H/ %6

O it

r O O

.4.4.

3%66

.4.404

0046

04.4.

0005

.4.4.4

0 04

.000

.4,4

00.0

.4O

0.03%

.OO 6

3%66

666

O6(5

6fl#4

n#4.4

('4.4

O400

N#4 #0.

.4 00.

NNr4

i O"4ri.40.03%

.4i4.

.4.,4.

3%66

4944

.4.4.4

66b9

'en

.4,4.-4

0 A-m

06400.4091-0e

.4.04

000

goo

.4

000

000

.3%

.000

000

000

000

000seg

000 -G

000 O

000 O

000 O

000

000

000

000

000

a3%6

'4

0t

0.

a

a

A

3%

a

aa

a66A.4

a

a

0

60.

a

aa0.a

a

3%

"

a

6a6

"

66

F,

"

#4

6

'4

6

0

6

A.

6

0.

6

3%6

6s6

6

#46

.4

6In6

Nt1

NM

r4 03%3%

O0A co

06%'

I6nq

v4 0 0

666

le40

6 n1j040

03 6

I6nN lO In

Sa a n

40 r e

6 6.400

00.0

In r rGba Nia

666 O

co N.0

666

03% 6666

qw 40w

N%66

O666

666666

F, ('.

00.0

Gb ca

6 nej

0.03%n9j F

66'O

6

66

n

.40

O A"en1

inn

nnn

@m mine

nnj66.j

nRj n

'0

O

A

h

N 'OIn

"m

6101

na 04o a 1A

r1 0 A601090

(h6

a"

mCIO .-

66"

66r66"

m..

669

66'0

61'S

6ee

n#4In"

666

(1'.4666

.400.666

00.0666

0.03%666

03%6w

6na

666

N.j:j

Q

V

E4milH

nN.4

#4.0

r400

000

000

000

000

a"0 "0. v0. .N. O'.1 4 0 , 4 606 0n ""t 060I WAI 4 1 '1,1. 1 1 1 1 1 1

1" I 0.+ a %, USoot h ,4 a__,__1NNj ____ ____I w

x

Appendix C -- Continued

II. SPACE VISUALIZATION

- Place the Space Visualization RIGHTS key, printedside up, over the test form so that all edges lineup. The key must be positioned so that only answerspaces are visible through the holes.

*Count the number of answer marks showing through theholes, this is the rights score. Record this scoreon the applicant's Score Record in the appropriateblank

*In the same manner, place the WRONGS key over theanswer sheet & count the number of marks showingthrough the holes, this is the wrongs score. Recordthis score on the applicant's Score Record.

*Use the enclosed Space Visualization Table (p. 10) toobtain the Total Score

- Go down the Wrong Score column until you findthe row in which the applicant's wrongs scorefalls

- Trace this row across to the column whichcorresponds to the applicant's Rights Score

- The number in the body of the table at thisintersection of the wrongs score row & therights score column is the Total Score

- Record this score on the applicant's ScoreRecord

*For example, a rights score of 34 and a wrongs scoreof 25 would result in a total score of 29.

89

Appendix C -- Continued

Table C-12

Space Visualization Table

N0

a"N

.90

N

N.9

N

NO

#4

U,.4

0

0N

N"

#4

.9

#4

N#-

.9

#40

#4

M#

#4

.4

a#4

.9

.4

N

.4

I,

.4N9.4N.4N9

.4

0.4

#4.4

.4

"

N9

0

N9

N

0

* r '@

ynna

eann

09nfnne

1'1 N

O A 0

fnn

fnn

A1.40finn

A 0 P

N n N00r

gin n

tl'@0

ow

gin"

N nN

""n

ANr

0(1.4

Nin n

gin n

ra,,

" V4

000

".4.4

.44.

* r% %aA.44

r4 4 t.44.

V4@0.9r

44.4

0010.4.4.4

"

n40

0004.

nnnfr innonfn fi

finn

fnnfin L

m0f%fin

gin

N N N

N N

in"N N.N

(1""

0.90

gin N N.N

.40-"".4

0.9*"4.4

to n

4 .4

Ar

o A a

-"''0

M44.

e"'@00.0

000.

0 i

.44.

NIOfnn

non i

0010finn

rhi A

nhe

gin n.f N

""Li

"gne.40 .

"".40.9@

".4.4

N N N

to v

.4.4.

N N N

AN"

MC.4.

N A 0

.4.4.4

r+0.9

.4.4.4

0.90

c44w

Nri

A 0(A.4.4.4

10(1.4. 4.

te.4.44.4

A.40V4.4.40.90

.4 N1

A N 1"

'I"'.r

N "'@O

A r4.r

40q0

+000

0000

000

NI N lNA rl N noN A

ocoim m ioo"

NPb t

N(10hr

gin

gin.90

h ON"1

".4N1

.40an

eco4hAA a

A A

.4 .4

ea

.1

.-. 4

.4 .4

.4.4

0.9.4.4

.0

.4A.4

.40

to

4.4

r.4

.40

00"

"0

'0

0.9

.0

00

00

00

h

.9

0N'

#4

Vr

I

N9.9

VIv9

a9v9.9

.4

0VI

aIa

.90VIa.9Nr0

14000VI.9"

.9

v%

.9

.9

0

.9Ai

0h"

.9

N1"h4

Nooih h

.-1

h h'

O A@

(1.140

i0t9

000

* 80%N

0 O t

000

101.4h 000(1.41000~14001

a r"141414

(' NN.9.9.

N'N0.9

.9.9.

0.9fi.9.9.

.9 fi (1

.9.9.

fio.4.9.9.9

.9 in 0108%finn

'O

0

00

00

0r

00

00

n h.4

10010

0108%

100 t.9.9.9

'@0.9

.90 gi.9.9.94fir..9.9.9

.9.9.9

r4O0 Q.9.9fi

0010

(4(01%

nfl fi

!'f

fiO

Oa

(44e

.9.9

mm0.9.9

01r

("@

In .rn

.9 i Li.C nnCn

fi$.4

nnn

1 4 4 ##U

~~ MMO.900 .90Mm

90

V1

Appendix C -- Continued

IV. SALES ATTITUDE CHECKLIST

*Tear off the perforated edge on the right of the testbooklet & discard the carbon insert. Turn to the lastpage in the test booklet.

*Begin where it signifies to begin (lower left-handcorner) and follow the arrows up & down the columnscounting the boxes marked with an X. DO NOT COUNT abox if a circle has been draw around the X in thatbox.

*Record this number in the scoring table in the celllabeled "X" boxes.

*Next, count the number of blank circles following thesame path. DO COUNT an X circled by the applicant

within a circle as a blank circle.

*Record this number in the scoring table in the celllabeled blank circles

-Add the two numbers within the scoring table toobtain the Total Score

*Record the Total Score in the corresponding blank onthe applicant's Score Record

91

APPENDIX D

JOB DIMENSIONS

92

93

JOB DIMENSIONS

1. Sales Ability

Persuasive self-expression when presenting ideas orproducts to an individual. Includes gathering andconveying information as well as adjusting one'scommunication style to that of others. Decorators mustpresent various ideas and products in a persuasivemanner. They must also attempt to understand customers'needs, and be able to meet these needs in a way which isprofitable for the company.

KSAO's: Ability to effectively communicate verballyAbility to persuasively communicateAbility to make sales presentations

2. Planning & Organizing

Establishing a course of action for meeting specifiedwork objectives. Includes setting priorities & followingthrough with results. Decorators must plan/organize theirschedules. Decorators must also determine appointmenttimes and lengths, schedule time for paperworkcompletion, and ensure adequate studio time.

KSAO's: Ability to organize & manage one's timeAbility to attend to detail

3. Adaptability

Maintaining effectiveness in varying environments andwith numerous types of individuals. Decorators need toadjust their sales presentations in accordance withcustomers' tastes & wishes.

KSAO's: Ability to adapt one's behavior to changingsales encountersAbility to handle sales objectionsAbility to persist

Appendix D -- Continued

4. Attention to Detail

Focusing on component parts or aspects of a situation.Decorators must accurately complete sales slips & workorders with minimal errors. Decorators must alsomaintain price lists, lists of discontinued items, &lists of policy changes which are all particular parts ofa quality and up-to-date sales presentation.

KSAO's: Ability to attend to detailAbility to communicate effectively throughwriting

5. Verbal Ability

Effective self-expression. Includes the ability togather and convey information accurately. Decoratorsmust greet and establish a rapport with customers. Theymust also answer and ask questions.

KSAO's: Ability to effectively communicate verballyAbility to persuasively communicate

6. Numerical Ability

Manipulating numbers with accuracy and reasonable speed.Decorators must calculate window product sizes andprices. They must also calculate price breaks anddiscounts.

KSAO's: Ability to add, subtract, multiply, and dividewhole numbers and/or fractions (including thecalculation of percents)

7. Spatial Relation Ability

Visualizing relationships between objects, and betweenobjects and their environment. Decorators must visualizethe existence of window products in order to determine ifthey will fit appropriately and fulfill the purpose theywere intended to fulfill.

KSAO's: Spatial Relations Ability

94

APPENDIX E

TASK STATEMENTS WITH INCUMBENT RATINGS

95

Table E-13

Task Statements with Incumbent

I. TAKE MEASUREMENTS/DESIGNAND PRICE TREATMENTS

1. measure inside and outside windowdimensions for window products

2. calculate window product sizes

3. read width charts to obtainfabric amount

4. estimate number of yards of fabricgiven different widths (includingfabric repeats)

5. calculate drapery pricing

6. calculate drapery trim yardage

7. calculate drapery trim labor charges

8. measure drapery length and width

9. measure and estimate yardage forcarpet installation (square yards)

10. record measurements on work order

11. use electronic calculator to calculatepricing and/or measurements

12. use tape measure to measure feet,inches, fractions

Ratings

% thatperform

100%

99%

Avg.Freq.

4.77

4.68

Avg.Duff.

2.14

2.45

Avg.Impt.

4.85

4.68

98% 4.31 1.63 4.34

99%

100%

100%

99%

97%

100%

100%

3.93

4.55

2.02

2.09

4.39

2.25

4.27

2.24

2.30

2.61

2.61

2.08

2.84

2.14

4.20

4.54

3.57

3.65

4.61

4.29

4.68

99% 4.72 1.60 4.45

100%

13. price hardware 100%

14. visualize completed window treatmentsbefore writing up order for work room 100%

15. calculate price breaks 96%

4.85

4.37

4.38

4.57

1.79

1.73

2.40

2.20

4.59

4.00

4.18

4.31

96

Crit.Index

23.42

22.40

19.66

17.05

20.76

07.71

08.12

21.04

09.89

20.17

21.66

22.39

17.72

18.61

20.57

Appendix E -- Continued

% thatperform

16. measure and calculate amount offabric for accessory items (e.g.window seats, 100% pillows,headboards, bed products)

17. examine window treatment area forobstacles around window

18. identify and calculate additionallabor charges for carpet installation

19. calculate carpet pricing

II. CONSULTATION/SELLINGTO CUSTOMERS

20. make appointments with customerson telephone or in studio

21. greet customer at customer's houseor in studio

22. ask questions about and listen tocustomer's fabric and stylepreferences

23. present customers with appropriateproduct samples

24. sketch drawings of sample windowcoverings for customer'sinspection/understanding

25. provide customers with suggestionsregarding window covering color,style, fabric

26. discuss fabric styles with customers

27. show customer pictures of windowcoverings

Avg.Freg.

Avg.Diff.

Avg.Impt.

100% 2.10 3.11 3.87

100% 4.20 2.06 4.15

99% 2.12 2.48 4.05

100% 2.20 2.27 4.25

100% 3.63 1.70 4.22

100% 4.63 1.32 4.35

100% 4.69 1.84 4.59

100% 4.70 2.09 4.39

100% 2.96 2.43 3.27

100% 4.63 2.16 4.19

100% 4.33 2.06 3.92

100% 4.50 1.44 3.93 18.04

Crit.Index

08.37

17.86

08.99

09.51

15.71

20.32

21.64

20.76

10.90

19.62

17.37

97

Appendix E -- Continued

28. arrive at customer's home promptlyat scheduled time

29. determine drapery or windowcovering function (e.g., insulation,privacy, light control)

30. follow-up with customers to providestatus report on order

31. obtain customer signature on salesslip and 3-day right to cancel slip

32. discuss payment options withcustomer

33. answer customer questions

34. present price of order to customer

35. obtain "open to buy" or "creditavailable" status on customer fromCredit Department

36. maintain photo album of completedorders for sales presentations tocustomers

% thatperform

100%

Avg.Freg.

4.62

Avg.Diff.

1.96

Avg.Impt.

4.21

100% 4.52 1.91 4.11

99% 3.23 3.05 3.91

100%

100%

100%

100%

4.43

4.47

4.74

4.68

1.85

1.61

1.92

2.29

4.56

4.11

4.39

4.44

94% 2.79 1.87 3.64

97% 2.70 2.47 3.38

III. CUSTOMER SERVICE

37. acknowledge and respond tocustomer complaints

38. travel to customer home usingown vehicle

39. read and interpret road map

40. provide customers with refunds

100% 3.06 3.20 4.48

100% 4.75 1.74 4.08

60% 0.79 2.54 2.89

Crit.Index

19.67

18.82

13.31

20.45

18.67

21.00

20.85

11.57

10.25

13.81

19.54

98

03.62

Appendix E -- Continued

% thatperform

41. process customer remakes or 100%reworks

42. communicate appropriate deliverydate to customer 100%

43. establish rapport with customers 100%

44. follow-up with customers regardingtheir satisfaction with completed order 100%

45. communicate order status to customerswhile order is being fabricated 94%

46. communicate with Service Centeron phone or in person regardingany customer service issue/problem 100%

Avg.Freg.

1.76

4.33

4.76

Avg.Diff.

2.68

2.11

1.65

Avg.Impt.

3.96

4.14

4.65

3.21 2.40 3.96

2.40 3.04 3.48

3.01 3.13 4.23

IV. COMPLETE PAPERWORKFOR ORDERS

47. draw-up drapery sketches/picturesto be used by work room

48. draw-up alternate window productsketches/plans to be used bywork room

49. fill-out and complete work orders

50. fill-out and complete purchase orders

51. fill-out and complete sales slips

52. fill-out and complete "right to cancel"sheet

53. compile sales order pricing (totalsale) components for inclusion onsales slips

100% 2.94 2.42 3.85

94%

100%

53%

100%

1.85

4.31

2.07

4.39

2.15

2.63

2.34

1.84

3.17

4.74

4.40

4.53

100% 4.30 1.52 3.98

11.93

07.03

20.66

18.20

20.06

17.77

100% 4.28 2.15 4.24

Crit.Index

07.09

18.41

22.36

13.26

09.29

13.16

99

18.51

Appenidix E -- Continued

% thatperform

54. make photocopies of order paperwork 39%

55. turn in order paperwork to studiocoordinator 100%

56. communicate on phone or in personwith work room regarding orders 97%

57. maintain periodic expense reports 78%

58. maintain weekly sales/mileage report 100%

Avg.Freg.

Avg.Diff.

Avg.Impt.

1.11 1.57 3.06

3.59 1.81 4.38

2.17 2.67 3.89

1.75 1.81 3.36

2.69 1.77 3.54

V. PROSPECTING

59. request personal leads/referralsfrom current customers 100%

60. give presentations to outsideorganizations regarding customdecorating 61%

61. conduct mail outs to new orexisting customers 98%

62. maintain/update customerprospect file 99%

63. distribute custom decoratingliterature to potential customers 99%

64. conduct follow-up contact withcustomers who do not makepurchase on the first visit 100%

65. ask current customer about additionalwindows for possible future business 100%

3.11 2.59 3.84

0.71. 3.16 2.51 3.23

1.96 2.54 3.40

2.37 2.58 3.58

2.59 2.09 3.38

2.62 2.60 3.70

3.41 2.01 3.82 13.70

Crit.Index

10.74

15.99

09.11

08.25

09.99

12.47

07.32

09.37

09.51

10.18

100

Appenidix E -- Continued

VI. UPDATE/MAINTAIN FILES % that& RECORDS perform

66. read and use computer printoutsregarding back orders 97%

67. read and use computer printoutsregarding discontinued items 100%

68. read and implement computerprintouts regarding Custom Decoratingprocedural changes 100%

69. maintain accurate and up-to-dateprice lists 100%

70. maintain accurate and up-to-dateproduct samples 100%

Avg.Freg.

Avg.Diff.

Avg.Impt.

2.45 2.45 3.42

2.67 2.50 3.87

2.54 2.41 3.73

2.41 2.42 4.34

2.24 2.65 4.19

VII. STAFF STUDIO

71. answer phone calls in studio

72. staff in-store studio as scheduled

73. assist new decorators (answerquestions, allow ride-along)

74. shop the competition

75. use computer terminal in studio tocheck on status of orders

76. design studio displays

77. make entries in and update orderfollow-up log

100%

96%

92%

94%

49%

76%

4.01

2.70

1.55

1.40

1.13

0.90

1.66

1.80

1.88

2.36

2.57

2.27

3.82

3.82

2.87

2.88

3.54

2.81

15.68

11.32

05.34

04.86

10.34

03.34

70% 1.66 2.42 3.43 09.37

Crit.Index

09.22

10.81

10.24

10.90

10.01

101

Appenidix E -- Continued

VIII. TRAINING-RELATED ACTIVITIES

78. attend outside seminars on anytopic related to custom decorating

79. attend and participate incompany meetings

80. attend company sponsoredfollow-up/advanced training

% that Avg. Avg. Avg. Crit.perform Fre. _Duff. Impt. Index

86% 1.11 2.10 2.87 03.93

100% 1.46 1.73 3.66 05.67

91% 1.12 1.80 3.67 04.58

102

APPENDIX F

BIVARIATE DISTRIBUTIONS

103

Appendix F -- Continued 104

00

000

e," "0

"0

"

*"0*- 0

N

"

"

S 0 * . S o

*0 . .

.* 00o

_ " ." o

* 0 * E *

06

0 SD

*

* -

0 0*" 6

a,

"

0)0

0o 0Cl) " 0

G) U)

CO 0a) LO0

c@1 c) C) N N

Cl)

Figure 1. Relationship between Sales Attitude Test Scores

and Average Sales Volume.

Appendix F -- Continued 105

U)

"

" " " " " " - ".

)

O ~CO

0)

a)

C

N

0)U

0) LC

SII

FU 2bs

QS p Cc( ) coN 0

Figure 2. Relationship between Sales Attitude Test Scores

and Managers' Ratings of Sales Ability.

Appendix F -- Continued

U)

0

U)

a)

a)as0

U).

c'JII

106

U,(1)

0CV)

L0N

U

U,)'4

S " \ \ \\ , , , , ! , , , , , ., ..

"I

a)U

ai)

E0U)

(10coU)0,CU

~U)N~h.

0)coCCa

cm

0N

Figure 3. Relationship between Sales Attitude Test Scores

and Managers' Ratings of Customer Service.

w

A v

--. 1 1 I 1 I 1 1 1 1 1 1 1 1 ! i L 1 1 1 1

, , ,I

Appendix F -- Continued

0)U)

a,)U)

coco

S

". 0

" f

107

LC)N~

11

I l I

0 U, 0 UNu

LO

LO'4.

" "

S.. @5 .05 0 e

* 0 " 0 "

" 0

2T~

T~

0Cuj

Figure 4. Relationship between Sales Attitude Test Scores

and Managers' Ratings of Administrative Duties.

I.

0

a0

cN)cw

I

I--

Appendix F -- Continued 108

U,

"

L

""" " ""*

" 4

" """" " e)

"* 0 0

0U)U

0

. 0*e .9

UU

CD)

F.ure 5.

o 0

oiue5 eainhpbtenSlsAttd etSoe

and Overall Ratings.

Appendix F -- Continued 109

" 0

* "

C'4J

II

I .. .I

. ,I IIL,1,

L0

0ee -- )

U)

0)

C

0

l

0)

N'

2Ui

o u,T

Figure 6. Relationship between Numerical Ability and

Managers' Ratings of Administrative Duties.

0CO

.0

coU)a)

Ez

0co

U) 0U) t)0o ) U)

cu0Cu

U,1

I

N

(V

I

Appendix F -- Continued 110

U)

"

U)

0

"*" " " U)

N "

* " 0

0t)

0*

e"

7j e cc

CU ,ees e - m

a a)

E* o o U) 0 N 0 T 0 ) 0

* S

* 9

-) C'toJtz

Figure 7. Relationship between Numerical Ability and

Overall Ratings.

Appendix F -- Continued111

""""" " e e"""

** * e *i

" "

S.5

S5 S "See S""

9 9

S.

S "e"

U

U'4.

E

0)

cLO

0

cmI-

0C)

- Cu)

0

o o t o o t

0C1

C\J

LO 0 U) 0 U) 0 U) 0

Co

Figure 8. Relationship between Spatial Ability and

Managers' Ratings of Ability to Design & Price Treatments.

oe

Appendix F -- Continued

LO

" f LO

a)

.C

U)

E"" " """""""". """ 00 ""0 0 0 a

0

0)

lcu

C

*aaer'Raig 0fAmiitr0v Duties

a)000C

U)0

"

+,,

CL CF) ) N O O to

Figure 9. Relationship between Spatial Ability and

Managers' Ratings of Administrative Duties.

112

Appendix F -- Continued

C

I~L

U)cv)

0 U) 0 UC') N N r

113

11)

'

IU

"

"

0

0 " "" ""S"0" "

9. 99 5e

. * 9. 9

0 0s

9 9

* 5

0

, , , ",

T d

0)

T 0

0 0

Figure 10. Relationship between Spatial Ability and

Overall Ratings.

W)a)

0

0

U

mumummumm-mm

c~*

U)

0,)

0)

U)CN

N"

. . . . . . . . . . .

I

APPENDIX G

TASK-DIMENSION MATRIX

114

115

Table G-14

Task-Dimension Matrix

Tasks Dimensions

Num. Spatial Verbal Sales Plan Adapt Detail

1 X X2 X X X5 X X8 X X10 X X11 X X12 X15 X X21 X X22 X X2331 X33 X X X X34 X X43 X X51 X

Note. Appendix E contains the task statements

APPENDIX H

DESCRIPTIVE STATISTICS FOR SIMILAR POPULATIONS

116

117

Table H-15

Descriptive Statistics for Similar Populations

M S . D. Range N

Tests

SRA Verbala 44.3 12.9 12 - 74 162

NumericalbAbility 29.2 14.2 0 - 75 225

SpaceCVisualization 20.7 9.2 0 - 50 176

Sales AttitudeChecklistd 33.5 5.6 20 - 43 86

aSelling Floor Personnel

bRetail Sales Clerks (White)

CWholesale Beverage Salesman

dSales Applicants

REFERENCES

Appel, V., & Feinberg, M. R. (1969). Recruiting door-to-

door salesmen by mail. Journal of Applied Psychology,

53, 362-366.

Arvey, R. D. (1979). Unfair discrimination in the

employment interview: Legal and psychological aspects.

Psychological Bulletin, 86, 736-765.

Arvey, R. D., Miller, H. E., Gould, R., & Burch, P. (1987).

Interview validity for selecting sales clerks. Personnel

Psychology, 40, 1-12.

Asher, J. J. (1972). The biographical item: Can it be

improved? Personnel Psychology, 25, 251-269.

Barrett, G. V., Phillips, J. S., & Alexander, R. A. (1981).

Concurrent and predictive validity designs: A critical

reanalysis. Journal of Applied Psychology, 6i, 1-6.

Bartlett, C. J., Bobko, P., Mosier, S. B., & Hannan, R.

(1978). Testing for fairness with a moderated multiple

regression strategy: An alternative to differential

analysis. Personnel Psychology, 31, 223-241.

Bemis, S. E. (1968). Occupational validity of the General

Aptitude Test Battery. Journal of Applied Psychology,

52, 240-249.

Bills, M. A. (1941). Selection of casualty and life

insurance agents. Journal of Applied Psychology, 25,

6-10.

118

119'

Boehm, V. R. (1977). Differential prediction: A

methodological artifact? Journal of Applied Psychology,

62. 146-154.

Bray, D. W., & Campbell, R. J. (1968). Selection of

salesmen by means of an assessment center. Journal of

Applied Psychology, 52, 36-41.

Burtt, H. E. (1917). Professor Munsterberg's vocational

tests. Journal of Applied Psychology, 1, 201-213.

Childs, A., & Klimoski, R. (1986). Successfully predicting

career success: An application of the biographical

inventory. Journal of Applied Psychology, 71, 3-8.

Churchill, G. A., Ford, N. M., Hartley, S. W., & Walker, 0.

C. (1985). The determinants of salesperson performance: A

meta-analysis. Journal of Marketing Research, 22,

103-118.

Cox, K. (1948). Can the Rorschach pick sales clerks?: An

exploratory study. Personnel Psychology, 1, 357-363.

Deb, M. (1983). Sales effectiveness and personality

characteristics. Psychological Research Journal, 7,

59-67.

Dreher, G. F., & Sackett, P. R. (1983). Perspectives on

employee staffing and selection. Homewood, IL: Richard

D. Irwin.

120

Ekpo-Ufot, A. (1979). Self-perceived task relevant

abilities, rated job performance, and complaining behavior

of junior employees in a government ministry. Journal of

Applied Psychology, 64, 429-434.

England, G. W. (1971). Development and use of weighted

application blanks. Minneapolis: University of Minnesota,

Industrial Relations Center.

Farley, J. A., & Mayfield, E. C. (1976). Peer nominations

without peers? Journal of Applied Psychology, 61,

109-111.

Frautschi, P. (1987). Validity of the California

Psychological Inventory as a tool for sales selection.

Unpublished master's thesis, University of North

Texas, Denton.

Freyd, M. (1926). Selection of promotion salesmen. The

Journal of Personnel Research, 5, 142-156.

Ghiselli, E. E. (1973). The validity of aptitude tests in

personnel selection. Personnel Psychology, 26, 461-477.

Ghiselli, E. E. (1966). The validity of occupational

aptitude tests. New York: Wiley.

Harrell, T. W. (1960). The validity of biographical data

items for food company salesmen. Journal of Applied

Psychology, 44, 31-33.

121

Hinrichs, J. R., Haanpera, S., & Sonkin, L. (1976).

Validity of a biographical information blank across

national boundries. Personnel Psychology, 29,

417-421.

Hogan, R., Carpenter, B. N., Briggs, S. R., & Hansson, R.

0., (1985). Personality assessment and personnel

selection. In H. J. Bernardin & D. A. Bownas (eds.)

Personality assessment in organizations. New York:

Praeger.

Holcombe, J. (1922). A case of sales research: Report on

first steps in a study of selection of life insurance

salesmen. Bulletin of The Taylor Society, 2, 112-121.

Hollander, E. P. (1954). Buddy ratings: Military research

and industrial implications. Personnel Psychology, 7,

385-393.

Hollenbeck, J. R., Brief, A. P., Whitener, E. M., & Pauli,

K. E. (1988). An empirical note on the interaction of

personality and aptitude in personnel selection. Journal

of Management, 14, 441-451.

Hunter, J. E., & Hunter, R. F. (1984). Validity and utility

of alternative predictors of job performance.

Psychological Bulletin, 96, 72-98.

Hunter, J. E., Schmidt, F. L., & Hunter, R. (1979).

Differential validity of employment tests by race: A

comprehensive review and analysis. Psychological

Bulletin, 8_6, 721-735.

122

Katzell, R. A., & Dyer, F. J. (1977). Differential validity

revived. Journal of Applied Psychology, 62, 137-145.

Kinslinger, H. J. (1966). Application of projective

techniques in personnel psychology since 1940.

Psychological Bulletin, 66, 134-150.

Kurtz, A. (1938). Selection-the aptitude index. Life

Insurance Sales Research Bureau, Annual Meeting

Proceedings, 170-180.

Lamont. L. M., & Lundstrom, W. J. (1977). Identifying

successful industrial salesmen by personality and personal

characteristics. Journal of Marketing Research, 14,

517-529.

Levine, E. L., Flory, A., & Ash, R. A. (1977). Self-

assessment in personnel selection. Journal of Applied

Psychology, 62, 428-435.

Lewin, A. Y., & Zwany, A. (1976). Peer nominations: A

model, literature critique and a paradigm for research.

Personnel Psychology, 29, 423-447.

Matteson, M. T., Ivancevich, J. M., & Smith, S. V. (1984).

Relation of type A behavior to performance and

satisfaction among sales personnel. Journal of Vocational

Behavior, 35, 203-214.

Mayfield, E. C. (1964). The selection interview: A re-

evaluation of published research. Personnel Psychology,

17, 239-260.

123

Mayfield, E. C. (1970). Management selection: Buddy

nominations revisited. Personnel Psychology, 23,

377-391.

Mayfield, E. C. (1972). Value of peer nominations in

predicting life insurance sales performance. Journal of

Applied Psychology, 56, 319-323.

Mayfield, E. C., Brown, S. H., & Hamstra, B. W. (1980).

Selection interviewing in the life insurance industry: An

update of research and practice. Personnel Psychology,

33, 725-739.

Merenda, P. F., & Jacob, S. (1987). Validity of Self-

concept measures for selection of sales personnel.

Psychological Reports, 60, 508.

Miner, J. B. (1962). Personality and ability factors in

sales performance. Journal of Applied Psychology, 46,

6-13.

O'Connor, E. J., Wexley, K. N., & Alexander, R. A. (1975).

Single-group validity: Fact or fallacy? Journal of

Applied Psychology, 60, 352-355.

Opren, C. (1985). Patterned behavior description interviews

versus unstructured interviews: A comparative validity

study. Journal of Applied Psychology, 7, 774-776.

Oschrin, E. (1918). Vocational tests for retail saleswomen.

Journal of Applied Psychology, 2, 148-154.

124

Owens, W. A. (1976). Background data. In M. D. Dunnette

(Ed.), Handbook of Industrial and Organizational

Psychology. Chicago: Rand McNally.

Pearlman, K., Scmidt, F. L., & Hunter, J. E. (1980).

Validity generalization results for tests used to predict

job proficiency and training success in clerical

occupations. Journal of Applied Psychology, 65, 373-406.

Rafaeli, A., & Klimoski, R. J. (1983). Predicting sales

success through handwriting analysis: An evaluation of

the effects of training and handwriting sample content.

Journal of Applied Psychology, 8, 212-217.

Reilly, R. R., & Chao, G. T. (1982). Validity and fairness

of some alternative employee selection procedures.

Personnel Psychology, 35, 1-62.

Roose, J. E., & Dougherty, M. E. (1976). Judgement theory

applied to the selection of life insurance salesmen.

Organizational Behavior and Human Performance, 16,

231-249.

Ruch, F. L., & Ruch, W. W. (1967). The K factor as a

(validity) suppressor variable in predicting success in

selling. Journal of Applied Psychology, 51, 201-204.

Ruch, F. L., & Ruch W. W. (1980). Employee Aptitude Survey

technical report. Los Angeles: Psychological Services.

125

Schmidt, F. L., Berner, J. G., & Hunter, J. E. (1973).

Racial differences in validity of employment tests:

Reality or illusion? Journal of Applied Psychology, 58,

5-9.

Schmitt, N. (1976). Social and situational determinants of

interview decisions: Implications for the employment

interview. Personnel Psychology, 29, 79-101.

Schmitt, N., Gooding, R. Z., Noe, R. A., & Kirsch, M.

(1984). Metaanlysis of validity studies published between

1964 and 1982 and the investigation of study

characteristics. Personnel Psychology, 37, 407-422.

Schuh, A. J. (1967). The predictability of employee tenure:

A review of the literature. Personnel Psychology, 20,

133-152.

Schultz, R. S. (1935). Test selected salesmen are

successful. Personnel Journal, 14, 139-142.

Spencer, G. J., & Worthington, R. (1952). Validity of a

projective technique in predicting sales effectiveness.

Personnel Psychology, 5, 125-144.

Taylor, E. K. (1985). Sales Attitude Checklist examiner's

manual. USA: Science Research Associates.

Thornton, G. C., & Byham, W. C. (1982). Assessment centers

and managerial performance. Orlando: Academic Press.

Thurstone, L. L., & Thurstone, T. G. (1984). SRA verbal

examiner's manual. USA: Science Research Associates.

126

Tullar, W. L., & Barrett, G. V. (1976). The future

autobiography as a predictor of sales success. Journal of

Applied Psychology, 61, 371-373.

Wagner, R. (1949). The employment interview: A critical

review. Personnel Psychology, 27, 397-407.

Walsh, J. P., Weinberg, R. M., & Fairfield, M. L. (1987).

The effects of gender on assessment centre evaluations.

Journal of Occupational Psychology, 60, 305-309.

Waters, L. K., & Waters, C. S. (1970). Peer nominations as

predictors of short-term sales performance. Journal of

Applied Psychology, 54, 42-44.

Weaver, C. N. (1969). An empirical study to aid in the

selection of retail sales clerks. Journal of Retailing,

45, 22-26.

Weekley, J. A., & Gier, J. A. (1987). Reliability and

validity of the situational interview for a sales

position. Journal of Applied Psychology, 72,

484-487.

Worbois, G., & Kanous, L. (1954). The validity of the

Worthington Personal History for a sales job. Personnel

Psychology, 7, 209-217.

Zdep, S. M., & Weaver, H. B. (1967). The graphoanalytic

approach to selecting life insurance salesmen. Journal of

Applied Psychology, 51, 295-299.