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Introduction
Statement
of the Problem
The Pygmalion effect (a variant of self-fulfilling prophecy) has
long been recognized in the fields of economics, psychology, political
science, medicine, administrative organization, and education. The
Pygmalion hypothesis is confirmed if subjects perform and achieve by
what is expected of them, independent of their abilities. Since the
publication of the first experiment employing this design in the
classroom (Rosenthal & Jacobson, 1968), there has been a great deal of
research and controversy concerning the nature of Pygmalion effect, its
magnitude, and possible methodological flaws in the study of
expectations (Barber & Silver, 1968; Elashoff & Snow, 1971; Thorndike,
1968). Subsequent studies and meta –analyses have now established the
fact that raising teachers’ expectations influences pupil achievement (Jussim
& Harber, 2005, Trouilloud et al, 2002, Babad, 1993; Dusek, 1975; Hall &
Merkel, 1985; Harris & Rosenthal, 1985; Rosenthal, 1985; 1991). Many
authors (Benabou and Tirole, 2003; Kierein & Gold, 2000; McNatt, 2000,
Barling & Beattie, 1983; Crawford, Thomas & Fink, 1980; Eden,
1984,1990,1995; Eden & Ravid, 1982; Eden & Shani, 1982; Eden & Zuk,
1995; King, 1971,1974; Livingston, 1988; Miller & Turnbull, 1986; Oz &
Eden, 1994) have noted that the Pygmalion effect operates in a variety
of military and industrial settings. There is enough experimental data
to suggest that self-fulfilling prophecy is true (Garner, 2005).
Ferraro (2005) has established the fact that social science theories can
become self-fulfilling by shaping institutional designs and management
practices, as well as social norms and expectations about behaviour.
Despite this lively treatment of the authority of expectations in the
educational and social psychological literature, management and
organizational behavioral specialists have barely dealt with it in the
sales field, where motivation is of prime concern. In addition since
the preponderance of research has been experimental in nature, there
have been few efforts at modelling casual sequences. Although
experiments have been the favorite method among psychologists, one of
its limitations is the number of factors that can be controlled by the
researcher. Large-scale surveys, while foregoing researcher-manipulated
variables, allow for sophisticated causal modelling using a large number
of predictor variables. The study is designed to examine the impact of
the Pygmalion effect in motivating a sales force using causal
modelling. The paper adds to the sales literature since the
psychological effects of sales managers’ expectations of salespersons is
an area, which has not yet been widely researched and validated. The
development of the causal model also adds to the literature since there
is not much work in this area.
Theoretical Rationale
The underlying theoretical assumption is that the higher a sales
manager’s expectations of salespersons’ performance, the greater the
likelihood that sales performance will be high. If sales managers’
expectations are low, salesforce productivity is likely to be poor. This
is called a self-fulfilling prophecy, often referred to as the Pygmalion
effect. A self-fulfilling prophecy is based on an assessment of previous
experience and it is a projection or anticipation that effectuates its
own accuracy. For example, because of previous experience with the
performance of a category of employees (e.g., women, older males), a
supervisor may anticipate whether or not a specific employee who fits
that category will be effective. Sales managers who hold low
expectations of certain groups of persons may subtly influence their
workers to perform at low levels or may view worker performance levels
as inadequate even though the workers may be actually performing better
than others who are expected to perform higher, but are actually
performing less effectively. Thus, low expectations can influence
subsequent perception, which may, in turn, influence evaluation. At the
same time, low expectations that are accepted by workers or performers
can influence perception, which may, in turn influence behavior.
Background
of the Problem
Thomas’s
sociological dictum that “things perceived as real are real in their
consequences” (Merton, 1957) is applicable to self-perception as well as
to interpersonal perceptions. In the area of sales performance, persons
who perceive themselves as good salespersons are likely to be better
salespersons than those who do not see themselves as good salespeople.
At the same time, as the social interactionists have noted, our
perceptions of ourselves are a consequence of the ways in which others
treat us (Stryker, 1980). Thus, it is to be expected that
self-perceptions be conceptualised as mediators between the perceptions
and treatment of the individual by others and the individual’s behavior
(see figure 1).
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The
self-fulfilling model posits that sales managers’ expectations and
treatment of salespersons will be influenced by background factors of
the salespersons (e.g., age gender, ethnicity, experience). These
expectations and treatment by the sales manager will, in turn, influence
the salespersons’ self-expectations, which will ultimately influence the
performance of the salespersons. Direct evidence of the relationship
between perceiver expectations and target performance comes from Brew
and Hall (1964), Eden (1984), Rosenthal and Jacobson (1968), Sterdy and
Kay (1962), and Sutton and Woodman (1989). These studies and others
within the literature on the Pygmalion effect support the fact that
individuals who successfully meet performance expectations set for them
are usually rewarded with salary increases, good grades, or promotions.
If performance expectations are usually high or close to peoples’ own
levels of aspiration, they will feel personal satisfaction at having
achieved the goal. Such positive outcomes lead to a higher level of
aspiration and a more positive attitude toward the job. The existence of
a relationship between perceiver expectations and perceiver behavior is
supported by extensive research in the educational literature (Babad,
1990, 1993; Harris & Rosenthal, 1985; Rosenthal, 1974). The “teachers’
pet” studies of Babad (1993) and Tal and Babad (1989,1990) suggest that
the inequitable and favoristic division of a teacher’s affect (“playing
favorites”) evokes strong reactions among the students, reducing
students’ morale, satisfaction, and the desire on the part of non
favorites to continue to study with the teacher who plays fovorites.
Statement of Hypotheses
The model of self-fulfilling prophecy casual chain in figure
1 is the basis for the hypothesis stated below:
H1: The higher the sales managers’ expectations of salespersons, the
higher their sales persons’ performance
H2: The higher the sales managers’ expectations of salespersons, the
higher their salespersons’ self-expectations.
H3: The higher the sales managers’ expectations of salespersons, the
higher their salespersons’ evaluation of their own performance.
H4: The more positively salespersons perceive their treatment by sales
managers, the higher their self-expectations.
H5: The more positively salespersons perceive their treatment by sales
managers, the higher their performance.
H6: The higher the salespersons’ self-expectations, the higher their
performance.
Methods
Sample
In order to
test the hypotheses, survey data were collected on 193 sales employees
from three retail sales companies located in New York City. These retail
sales companies are involved in mass merchandising, upscale
merchandising, and specialty retailing. The companies provided a sample
population of 193 salaried sales employees working under 24 managers.
Upon receipt of permission, the researcher made arrangements with
supervisory personnel to distribute the questionnaires. Supervisor’s
ratings were collected on 174 of the sales persons with 19 employees not
evaluated by their managers. Full data on the Pygmalion variables were
available for 174 salespersons.
The sales forces are predominantly female (60.6%) and young, with nearly
two-third (64.2%) under 30 years of age. An additional one-quarter
(26.9%) was between 31 and 40 years of age. Most (53.4%) were single;
slightly less than one –third (31.1%) were married. The workforce was
multiracial and multicultural. Nearly half (45.6%) the sales staff were
of Hispanic or Latino background; slightly less than one-quarter (24.9%)
were African-American; 14.5% were white; 10.4% were Asian. Nearly half
(48.7%) of the sales staff had completed high school, 28.0% had attended
some college, and 6.2% had college diplomas. Slightly more than
one-tenth (11.9%) had not earned a high school diploma. The respondents
had a mean of 3.23 (SD =4.07) years of sales experience. They had a mean
of 2.70 (SD =2.82) years of experience with their present employer.
Instrumentation
The data were derived from the
company personnel survey (CPS) comprising the employee perception of
Supervisors’ Expectations Scale (SES), the Supervisors’ Authoritarian
Behavior Scale (SABS), the Positive Achievement Motivation Behavior
Scale (PAMBS), the Employee Self-expectation Scale (ESS), and the
Employee Self-Evaluation Scale (ESES) (Kohli, 1985). In addition to the
self-perception and supervisor behavior scales, several demographic
items were included in the CPS. They were age bracket, sex, marital
status, ethnicity, educational attainment, years in sales, and years
with the present company. The Supervisors’ Employee Evaluation Survey
(SEES) contained two scales: the Supervisors’ Evaluation of Present Work
Scale (SEPWS) and the Supervisors’ Expectancy scale (SES).
The Employee Expectation Scales (EES) is a 5-item instrument with four
items using a 5-point Likert-type response mode. A typical item is “I
expected my sales performance to be.” The response modes are as
follows: 1 = far below most of my peers. A fifth item asked respondents
to rate themselves on their performance relative to their peers on a
scale of 0% to 100 %, with 0% indicating that they are better than none
of their peers and 100% indicating that they are better than all of
their peers. Because the fifth item used a different measuring scale
than the other four items, EES items, scores were transformed into
standard scores with means of 0 and standard deviations of 1. Sutton
and Woodman (1989) reported a reliability coefficient of .89 for the
measure. The Employee Evaluation of Present Work (EEPW) and Employee
Perception of Supervisor’s Expectation Scale (EPSES) used the same items
as the EES; however, the respondents were asked to report their
perceptions of actual quality of their present work in the former, and
their perceptions of supervisor expectations for their work in the
later.
Supervisors’ behavior was measured through the CPS by having employees
report on their supervisors’ behavior. Three scales refined by Kohli
(1985) were used: the Supervisor Arbitrary and Punitive Behavior Scale (SAPBS),
the Supervisor Contingent Approving Behavior Scale (SCABS), and the
Supervisor Achievement –Oriented Behavior Scale (SAOBS). All supervisor
behavior scales were keyed to 5-point Likert-type response modes from
“very false” (1) to “very true” (5). All of the supervisor scales
reported by Kohli (1985) began with generic pronoun ‘‘He.” This was
changed to a stem of “My supervisor.” This change brought the items
into conformance with the mandates of the publication Manual of the
American Psychological Association, 4th edition (1994), which advises
the avoidance of “generic he” construct. It also reflects the fact that
women are in supervision, and hence, is more accurate. This SAPBS
consists of 8 items. A typical item is “ My supervisor speaks in a
manner not to be questioned”. The theoretical range of scores is from 8
to 40, with 8 indicating low levels of arbitrary and punitive behavior,
and 40 indicating the high levels. Kohli (1985) improved the scale and
reported an alpha reliability coefficient of .83. Supervisor Contingent
Approving Behavior Scale (SCABS) was measured by a 4-item scale
originally developed by House (House & Mitchell, 1974). A typical item
is “ My supervisor gives clear recognition for outstanding work”. The
theoretical range of scores is from 4 to 20, with 4 indicating low
levels of contingent approving behaviour and 20 indicating high levels.
The measure has been found to discriminate between contingent approving
and contingent disapproving behavior (Fulk & Wendler, 1982). Kohli
(1985) improved the scale further and reported an alpha reliability
coefficient of .95 for the scale.
The SOABS contained 4 items, a typical item is “ My supervisor shows
approval of me when I put forth my best efforts”. It has the same
theoretical range as the SCABS; Kohli (1985) improved the scale and
reported an alpha reliability coefficient of .70.
Supervisors’ behavior was scaled into two variables with eight items
each. One scale was termed “Authoritarianism,” since it dealt with the
supervisors’ authoritative behavior, such as, “My supervisor rules with
an iron hand.” The other was named “Positive Achievement Orientation
Behavior (PAMB) since the items that comprised it dealt with
supervisors’ attempts to positively influence sales persons’
performance. A typical item was: “My supervisor gives me recognition for
improvement in my performance”. Both scales had alpha reliability
coefficients higher than .90, indicating strong internal consistency.
The two supervisor behavior scales were developed by taking the 16
supervisor items and conducting a factor analysis on them using
principal components factor extraction and varimax rotation.
Data collection
The researcher received from each
participating supervisor a list of the salespersons that he or she
supervised. These lists were then coded with four-digit code numbers
that were keyed as follows: the thousand and hundreds column digits
identified the supervisor and the tens and unit columns identified the
individual salesperson. For example ID No. 1307 indicated salesperson
number 07 who was supervised by supervisor number 13. That is,
salesperson ID numbers were nested within supervisor IDs. Therefore,
for each participating salesperson, there were two completed surveys
with identical numbers: the CPS completed by the salesperson and the
SEES completed by the supervisor. Only the researcher had the key that
matched the respondent to the code numbers. The Pygmalion variables all
had alpha coefficients above .90, indicating high levels of internal
consistency.
Data Analysis
Data analysis follows a
correlation design. All hypotheses were tested using Pearson
correlations and partial correlations, controlling for background
variables for gender, marital status, ethnicity, length of employment,
and years of sales experience.
Finally the model was tested using a series of multiple regression
equations. The dependent variable was the score on the SEPWS. In the
model, the relationship between salespersons’ self-expectations and
salespersons’ performance was assessed with a zero-order correlation.
The indirect effects of sales managers’ treatment of salespersons’
performance was tested using a hierarchical multiple regression
analysis, entering in the sales managers’ treatment of salespersons’
variables and salespersons’ sales-expectations prior to the entry of
sales managers’ expectations. A similar regression was run using
salespersons’ background variables as a predictor. In addition, sales
managers’ treatment of salespersons was regressed on salespersons’
background variables and sales managers’ expectations. These analyses
were conducted recursively until path coefficients were assigned to all
arrows in the model.
Results
Hypothesis Testing
Six hypotheses of the study are tested.
The first three hypotheses are concerned with the relationships between
supervisors’ expectations, their ratings of the performance of sales
employees, employee self-expectations, and employee performance
self-ratings. Table 1 presents the Pearson and partial correlations for
supervisors’ expectations and employee outcomes. The partial correlation
coefficients were computed controlling for gender, marital status,
ethnicity, sales experience, length of employment, and years of sales
experience.
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Table 1:
Correlations between Supervisor Expectations and Employee Outcomes |
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|
Supervisor Expectations |
| |
|
Employee
Outcomes |
Pearson |
Partial |
| |
|
|
|
Performance rating by Supervisor |
.72** |
.67** |
|
Employee Self-Expectation
|
.45**
|
.49** |
|
Performance
Rating by Employee
|
.42**
|
.45** |
|
(N) |
170 |
124 |
|
________________________________________________________ |
|
Note: *p <. 05; **p <. 01
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The Pearson correlation comparing supervisor expectations and supervisor
ratings indicates a very strong positive relationship (r = .72, p <. 01.
The partial correlation coefficient was similar (r=. 67, p<. 01). The
data support the hypothesis that supervisor expectations and ratings are
positively related. The Pearson correlation comparing supervisor
expectations and employee self-expectations indicate a moderate positive
relationship (r=. 45, P <. 01). The partial correlation coefficient was
similar (r=. 49, p<. 01). The data support the hypothesis that
supervisor expectations and employee self-ratings are positively
related. The Pearson correlation comparing supervisor expectations and
employee self-ratings indicate a moderate positive relationship (r=. 42,
p<. 01). The partial correlation coefficient was similar (r= .45, p <
.01). The data support the hypothesis that supervisor expectations and
employee self-ratings are positively related.
Hypotheses 4 through 6 examine relationships between supervisor
behaviors and supervisor’ rating of employees, employee
self-expectations, and employee performance self-ratings, respectively.
Table 2 presents the Pearson and partial correlations controlling for
the effects of gender, marital status, ethnicity, sales experience,
length of employment, and years of sales experience. There was no
relationship between supervisor authoritarianism and their ratings of
employee performance. However, the higher the ratings of supervisors on
PAMB, the higher the ratings of employees’ performance (Pearson r =. 31,
p<. 01; and partial r =. 26, p<. 01). The data supports hypothesis 4
partially.
Hypotheses 5, which specified relationship between employee
self-expectation and supervisor behaviors was not supported for
supervisor authoritarianism. Although, there was a significant
relationship using a Pearson correlation, the correlation attenuated to
nonsignificance when background factors were controlled. Hypothesis 5
was, however, supported for PAMB (r= .40, p <. 01; partial r = .43, p <.
.01).
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Table 2 Correlation between Supervisor Behavior and Employee Outcomes |
| |
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|
Supervisor Behavior |
| |
|
Employee Outcomes |
Pearson |
Partial |
Pearson |
Partial |
|
|
Performance Rating by Supervisor |
|
|
|
|
|
| r |
-.01 |
.11 |
.31** |
.26** |
|
| n |
(174) |
(124) |
(174) |
(124) |
|
|
Employee Self-Expectation
|
|
|
|
|
|
| r |
.18** |
-.01
|
.40** |
.43** |
|
| n |
|
|
|
|
|
|
Performance Rating by Employee |
|
|
|
|
|
| r |
.18**
|
.08 |
.37** |
.40** |
|
| n |
(193) |
(124) |
(193) |
(124) |
|
|
______________________________________________________________ |
|
Notes. PAMB* = Positive Achievement
Motivation Behavior *P <. 05; **p < >01 |
| |
Hypothesis 6 was also not supported for
authoritarianism. However, it was supported for PAMB (r =. 37, p < .01;
partial r = .40, p < .01).
Assessing the Model
The self-fulfilling prophecy model was
tested using a series of multiple regressions. The dependent variable
was the score on the Supervisors’ Evaluation of Present Work Scale (SEPWS).
The first stage of the model indicated sales managers’ expectations and
treatment of employees being influenced by employee backgrounds. Table
3 presents the results of the regressions analysis for supervisor
expectations. Coefficients used in the model are typed in boldfaced
print.
Table 3 Summaries of Multiple Regressions
of Sales Managers’ Expectations on
Background Variables (N =
130)
|
Variable |
B |
SE B |
b |
|
Male |
-.84 |
.0.44 |
-.17 |
|
Single |
.60 |
0.46 |
.11 |
|
White |
-0.12 |
0.79 |
-.02 |
|
Hispanic |
-0.02 |
.64 |
-.00 |
|
African – American |
-0.10 |
0.67 |
-.02 |
|
Age |
-.03 |
0.49 |
-.01 |
|
Education |
0.24 |
0.28 |
.08 |
|
Sales experience |
0.20 |
0.07 |
.26** |
|
Length of Employment |
0.11 |
0.12 |
.12 |
|
Knowledge of Employee |
0.27 |
0.22 |
.13 |
Note, R =. 48, R2 = .23, p < .01. Bold/italicised
coefficients were used in the model in figure 2. * P < .05. **P < .01.
The regression analysis
indicates that the background variables accounted for 23% of the
variance in supervisors’ expectations, which was significant (R=. 48,
p<. 01). However, when examining the bivariate relationships, sales
experience, was the only variable significantly related to expectations
(b = .26, p< .01). The greater the length of sales experience, the
higher the supervisor’s expectations.
Table 4 contain the results
of the regression analysis for sales managers’ authoritarianism. The
data in Table 2 indicate that employee background variables accounted
for 39% of the variance in supervisors’ authoritarianism (R = .63, p <
.01). Bivariate analyses indicate that the greater the sales experience
of the salespersons, the higher the perceived level of supervisors’
authoritarianism (b = .47, p< .01), and the greater the supervisors’
knowledge of the employee, the lower the authoritarianism (b = -.57, p<
.01).
Table 4: Summary of Regression Analysis
of Sales Managers’ Authoritarianism Background Variables (N = 130)
|
Variable |
B |
SE B |
b |
|
Male |
.67 |
1.33 |
.04 |
|
Single |
-0.33 |
1.40 |
-.02 |
|
White |
0.84 |
2.37 |
-.03 |
|
Hispanic |
0.80 |
1.90 |
.05 |
|
African – American |
-0.77 |
2.02 |
-.04 |
|
Age |
-0.42 |
1.49 |
-.03 |
|
Education |
1.12 |
0.83 |
.11 |
|
Sales experience |
1.23 |
0.22 |
.47** |
|
Length of Employment |
-0.20 |
0.36 |
-.06 |
|
Knowledge of Employee |
-4.02 |
0.68 |
-.57** |
Note, R =. .63, R2 = .39, p < .01.
Bold/italicised coefficients were used in the model in figure 2. * P <
.05. **P < .01.
Table 5 presents the results
of the multiple regression of supervisors’ PAMB by the background
variables. The data indicate that the background variables accounted
for 14% of the variance in supervisor PAMB (R = .38, p < .01). The only
variable that accounted for a significant proportion of the variance is
the supervisors’ knowledge of the employee (b = .24, p< .05).
Table 5: Summary of Multiple Regression
of Sales Managers’ Positive Achievement Orientation Behavior on
Background Variables (N = 130)
|
Variable |
B |
SE B |
b |
|
Male |
-0.52 |
1.08 |
-.05 |
|
Single |
1.61 |
1.12 |
.13 |
|
White |
-2.34 |
1.91 |
-.14 |
|
Hispanic |
0.16 |
1.53 |
.01 |
|
African – American |
-1.16 |
1.63 |
-.09 |
|
Education |
-1.09 |
0.67 |
-.15 |
|
Sales experience |
0.22 |
0.17 |
.12 |
|
Length of Employment |
0.40 |
.29 |
.19 |
|
Knowledge of Employee |
1.15 |
0.55 |
.24* |
Note, R =. .38, R2 = .14, p <
.01. Bold/italicised coefficients were used in the model in figure 2.
* P < .05. **P < .01.
The next link in the causal chain was salespersons’
self-expectations. They were conceived as being influenced by sales
managers’ expectations, sales managers’ authoritarianism, and sales
managers’ PAMB. This link was tested using a hierarchical multiple
regression analysis, first entering the background variables followed by
the supervisor variables. The results of the final solution are
presented in Table 6. The data in table 6 indicate that the
demographic background variables accounted for 35% of the total variance
in employee self-expectations (R= .60, p< .01). The longer the
supervisor knew the employee, the lower the self-expectations (b
= -.19, p< .05); and the greater the amount of sales experience, the
higher the self-expectations (b
= .32, p< .01). The supervisory variables added 22% to the explained
variance(R = .76, p < .01). Supervisor expectations were positively
related to self-expectations (b
= .38, p< .01) and supervisors’ PAMB was positively related to
self-expectations (b
= .28, p < .01).
Table 6 Summaries of Multiple Regressions of
Employees’ Self-expectation Background Variables and Supervisor
Variables (N = 130)
|
Variable |
B |
SE B |
b |
|
Step 1
Step 2 |
Male |
-0.85 |
0.31 |
-.19** |
|
Single |
-0.22 |
0.33 |
.05 |
|
White |
-0.25 |
0.56 |
-.04 |
|
Hispanic |
-0.16 |
0.45 |
-.04 |
|
African – American |
-0.86 |
0.47 |
-.17 |
|
Knowledge of Employee |
-0.37 |
0.18 |
-.19* |
| |