Effects of Flexitime on Employee Attendance and Performan.docx

Effects of Flexitime on Employee Attendance and Performance:
A Field Experiment
Author(s): Jay S. Kim and Anthony F. Campagna
Source: The Academy of Management Journal, Vol. 24, No. 4
(Dec., 1981), pp. 729-741
Published by: Academy of Management
Stable URL: https://www.jstor.org/stable/256172
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? Academy of Management Journal
1981, Vol. 24, No. 4, 729-741.
Effects of Flexitime on Employee
A ttenadance and Performance:
A Field Experiment1
JAY S. KIM
ANTHONY F. CAMPAGNA
The Ohio State University
The effects of a flexitime program in a county welfare
agency are assessed. The analysis of covariance on the
employees' attendance and performance revealed that
(1) the flexitime program appears to permit employees
to reduce their use of unpaid absences and (2) perfor-
mance efficiency tends to be higher among employees
under the flexitime program.
Flexitime as an organization development intervention has been
increas-
ingly popular in American industry. According to one report,
approxi-
mately 13 percent of the employing organizations in the private
sector
have adopted a form of flexitime program since it was
introduced in the
early 1970s. This represents about three million American
workers (Nollen
& Martin, 1978). The purpose of this study is to investigate the
effects of

flexitime on employee attendance and performance in a field
setting.
Although there are a number of variations in its form, the basic
model
of flexitime usually consists of five interrelated components:
(1) a band
width, or the total number of hours in a given workday, (2) a
core time, or
designated period of time during which all employees are
required to be
working, (3) a flexible band of hours both before and after the
core time
that allows employees to vary their starting and quitting times,
(4) bank-
ing, which allows carry-over of surplus or deficient hours
worked, and
(5) variability of schedule-the employees' freedom to vary
working hours
from one period to another without prior approval from their
supervisor
(Golembiewski & Proehl, 1978). The degree of flexibility and
amount of
discretion permitted employees depend on the variations in the
above five
components in the program.
In spite of its popularity in application and numerous success
stories,
very little is known about the effectiveness of flexitime
programs. Most
'An earlier version of this paper was presented at the National
Academy of Management Confer-
ence, Detroit, Michigan, August, 1980. The authors would like
to thank S. D. Nollen and two anony-

mous reviewers for their suggestions on an earlier version of
the paper.
729
18:12:41 UTC
730 Academy of Management Journal December
studies of them are anecdotal, testimonial, and post hoc in
nature; few are
based on rigorous empirical investigation. Following an
extensive review
of literature on flexitime, Golembiewski and Proehl (1978)
have reported
that of the 16 empirical studies examined, only one included
any statistical
treatment of the data reported. Thus, the results typically
attributed to the
flexitime program could be artifacts that would cast serious
doubt on the
internal validity of the findings. Other methodological and
measurement
weaknesses commonly shared by the flexitime studies include:
(1) the ab-
sence of a control group, (2) lack of pre-intervention measures,
and
(3) the use of "soft" data as criteria.
Notwithstanding these weaknesses, a number of investigators
have ar-
gued that flexitime has a positive impact on employee attitudes

among su-
pervisory employees (Partridge, 1973) and nonsupervisory
employees in a
large insurance company (Evans, 1973), among employees in a
pharma-
ceutical firm (Golembiewski & Hilles, 1977), and in a
computer firm
(Hopp & Sommerstad, 1977). In addition, flexitime has been
reported to
help reduce absenteeism and sick leave (Golembiewski &
Hilles, 1977;
Mueller & Cole, 1977) and to help increase productivity
(Martin, 1975;
Nollen & Martin, 1978). In general, the proponents of this
program have
argued that permitting employees to exercise flexibility in their
arriving
and quitting time will reduce absenteeism, tardiness, overtime,
etc., be-
cause these would be accounted for under allowed discretionary
time. Fur-
ther, it has been argued that under the flexitime program the
employees
would be able to adjust their work activities to their
individually more pro-
ductive hours, resulting in a more efficient utilization of labor
input in a
work setting (Nollen, 1979). This increase in performance
efficiency would
further allow the employees to make positive alterations in
their attending
and their producing behavior.
Although this proposition has not been explicitly tested, three
studies
with acceptable methodology and measurements have dealt

with the im-
pact of flexitime on employees' attendance and performance.
Investigat-
ing approximately 60 employees in research and development
units under
a flexitime program, Golembiewski, Hilles, and Kagno (1974)
reported
findings that suggest that flexitime reduces overtime and
absenteeism.
They found that the total number of paid absences in the
experimental
group during a 375-day period was reduced by 35 percent from
the imme-
diately preceding year, while absenteeism increased 15 percent
in the con-
trol group. On the other hand, the expected decrease in short
term ab-
sences (a single day or less) did not occur in the experimental
group. In
fact, they increased by nearly 13 percent, as compared to an
increase of 21
percent in the control group. These findings refute the common
belief that
flexitime reduces short term absences more than long term
absences. In
addition, as the authors themselves pointed out, "experimentals
and com-
parisons started from substantially different bases" (1974, p.
528). This
initial difference should have been taken into account when
experimental
and control groups were compared on criterion variables. In the
second
18:12:41 UTC

1981 Kim and Campagna 731
study, Harvey and Luthans (1979), investigating the effect of
flexitime on
employee attendance in a state agency, concluded that flexitime
appears to
have a relatively favorable effect on absenteeism. However,
they did not
offer any statistical treatment of the absenteeism data in their
study. As is
frequently the case, the positive effect of flexitime on
employee atten-
dance has been claimed with relatively tenuous empirical
evidence.
Studies investigating the impact of flexitime on performance
are just as
limited as are those on absenteeism. One notable exception is a
study by
Schein, Maurer, and Novak (1977). They investigated the
impact of flexi-
time on the performance of 246 clerical level employees in five
production
units within a large financial institution over a period of four
months. For
two of the production units, in which both an experimentally
designated
control group and pre- and post-measures were employed, the
results
revealed no significant differences in performance between the
experimen-
tal and control groups. In another production unit, however,

productivity
during the flexitime period was found to be significantly
greater than that
in the same period of the previous year. Based on these
findings, the
authors suggested that no clear-cut conclusions with respect to
perfor-
mance can be offered but that flexitime appears to have no
adverse impact
on it. In that study, however, the potential changes in the total
work hours
resulting from the flexitime program were not taken into
account in mea-
suring productivity. Because the flexitime program has been
reported to
influence the employees' attending behavior (Golembiewski et
al., 1974;
Harvey & Luthans, 1979), the results of the Schein et al. study
on produc-
tivity may have been attributable in part to the confounding of
the cri-
terion measure with the changes in the total hours worked
during the ex-
perimental period.
The present study attempts to remedy some of the
methodological
weaknesses of previous studies in several important ways.
First, this study
employs a pre-intervention measure of each criterion for both
the experi-
mental and the control group. This allows the necessary
adjustment of cri-
terion variables for the initial differences between groups.
Second, this
study investigates the effectiveness of flexitime using "hard"

criterion
measures. Especially, it uses the performance efficiency
measure after the
potential impact of flexitime on attendance behavior is taken
into ac-
count. This permits testing whether employees under the
flexitime pro-
gram are performing more efficiently on an hourly basis. Third,
the nature
of the task under investigation is taken into account when
performance
measures are analyzed because Nollen (1979) suggested that
employees'
behavioral responses to flexitime tend to vary with different
types of tasks.
Fourth, this study attempts to increase the external validity of
the findings
reported by Schein et al. (1977) by investigating the same
research issues in
a public sector setting. According to Nollen (1979), there is
some evidence
suggesting that flexitime has a greater impact on performance
in the pri-
vate than in the public sector. Given the increasing number of
flexitime
implementations in the public sector, such information is
required in order
to guide future action.
18:12:41 UTC

The research issues investigated in this study are:
(1) Does the flexitime program affect the employees'
absenteeism?
(2) Does the flexitime program affect the employees'
performance effi-
ciency?
METHOD
Subjects and Procedure
A total of 353 employees in 4 divisions of a county welfare
agency par-
ticipated in this study. Each division consisted of several
administrative
units, and each administrative unit was supervised by a
common superior.
Approximately 78 percent of the participants were female, 53
percent were
black, and 90 percent had at least a high school education or
some college
training. The participants were responsible primarily for
determining the
eligibility of welfare cases and were all at the same
organizational level.
A nonequivalent control group design was employed in this
study. Prior
to the flexitime intervention, the administrative units in each
division were
randomly assigned to the experimental group and to the control
group.
This randomization procedure, repeated in each division,
allowed approx-

imately equal numbers of employees in the experimental group
and the
control group.
The employees participating in the experimental group were
allowed to
begin their work any time between 6:30 a.m. and 9:30 a.m. and
leave be-
tween 3:00 p.m. and 6:00 p.m. (the designated pre- and post-
work band).
All employee participants were required to be at work between
the hours
of 9:30 a.m. and 3:00 p.m. (the designated core time). In
addition, all par-
ticipants were required to work an 8-hour day. Those
employees assigned
to the control group continued to work their normal 8-hour
days (8:00
a.m. to 4:30 p.m.). All employees who had overtime had the
choice of tak-
ing one and a half compensatory time-off or taking one and a
half over-
time pay. During the four months of the experimental period,
there was
no change in the supervisory personnel in any of the
administrative units
under investigation.
Measures
The criterion measures were collected on each participant in
the experi-
mental and control groups from organizational records for the
month
prior to the flexitime intervention and for the subsequent four
months of

the intervention period. Two different types of absenteeism
were ob-
tained: paid absences and unpaid absences. Each of these was
divided fur-
ther into short-term and long-term absences. Short-term paid
absences for
an employee were operationally defined as a monthly total of
paid ab-
sences (i.e., sick leave) which was taken in blocks of two hours
or less a
day. Long-term paid absences were operationally defined as the
monthly
total of paid absences taken in blocks of more than two hours a
day.
18:12:41 UTC
Similarly, short-term unpaid absences for an employee were
operation-
ally defined as the monthly total of leave time without pay that
amounted
to two hours or less a day. Long-term unpaid absences were
operationally
defined as the monthly total of leave time without pay that
amounted to
over two hours a day. These four measures defined on an a
priori basis
were available for 161 employees in the experimental group
and for 185
employees in the control group.

In regard to performance, it was found that four divisions under
the
study varied as to the required routine actions, the client
contact, the na-
ture of the cases to be processed, etc. Consequently, this
agency had em-
ployed different performance measures in each of these
divisions. There-
fore, in order to provide a basis for comparison, a performance
efficiency
measure was computed and was standardized within each
division across
the 5-month period. The performance efficiency measure for an
employee
was operationally defined as the rate of output quantity per
hour by com-
puting the ratio of monthly output to the actual hours worked
during a
given month. The actual hours worked during the month were
obtained by
subtracting the total hours of absences, vacation time, and
compensatory
leave time from the total work hours available plus overtime
worked for
the month. These performance efficiency measures, analyzed
for each sep-
arate division, included: (1) the total number of cases approved
during the
month for Division 1; (2) the total number of routine actions
completed
during the month for Division 2; (3) the total number of cases
processed
during the month for Division 3, and (4) the total number of
cases pro-
cessed during the month for Division 4. To supplement the four

division
analyses, the performance efficiency measure was standardized
within
each division to provide the basis for comparison across all
four divisions.
It was learned that this agency had been monitoring the
employees' at-
tendance behavior much more closely than it had the producing
behavior
such as output quantity. Consequently, when the measures to
compute
performance efficiency were compiled, it was found that for
only 94 em-
ployees was there a complete set of necessary data (i.e., output
measure,
paid and unpaid absences, compensatory leave time, vacation
time, over-
time, etc.) for each of the five months of the intervention
period. All data
were compiled by the employees in the personnel department
from the
centralized standard logs and organizational records, which the
unit super-
visors were required to report on a monthly basis.
In order to control for the pre-intervention differences between
the ex-
perimental and the control group, analysis of covariance using
the pre-
intervention measure as a covariate was employed in analyzing
the cri-
terion variables for each separate division and for the four
divisions com-
bined.

RESULTS
Table 1 is a summary of the means, adjusted means, and
standard de-
viations of the short-term and the long-term unpaid absences.
The
18:12:41 UTC
TABLE 1
Summary of Means, Adjusted Means, and Standard Deviations
of Unpaid Absences
(N=346)
PRE 1-Month 2-Month 3-Month 4-Month Marginal Criterion
Measures M SD M SD M SD M SD M SD Meansb
Short-term unpaid absences:
Experimental group (n = 161) .192 .583 .124 .527 .118 .442
.161 .517 .093 .400 .124
(.128)a (.122) (.166) (.097) (.128)
Control group (n = 185) .218 .742 .256 .783 .262 .807 .332
1.062 .267 .794 .279
(.252) (.258) (.328) (.263) (.275)
Long-term unpaid absences:

Experimental group (n = 161) 4.232 19.384 1.335 5.032 2.962
8.913 3.422 11.346 1.465 5.222 2.296
(1.281) (2.909) (3.368) (1.412) (2.242)
Control group (n= 185) 2.005 6.937 2.389 8.420 3.921 11.567
4.662 20.510 4.921 35.921 3.973 (2.435) (3.968) (4.708)
(4.968) (4.019)
aThe adjusted means using the monthly measure immediately
preceding the intervention as covariate.
bThe average of the criterion measure for the four month
intervention period combined.
TABLE 2
of Paid Absences
(N= 346)
PRE 1-Month 2-Month 3-Month 4-Month Marginal
Criterion Measures M SD M SD M SD M SD M SD Meansb
Short-term paid absences:
Experimental group (n = 161) .503 1.108 .422 .944 .332 .815
.403 .809 .319 .793 .369
(.418)a (.328) (.399) (.315) (.365)
Control group (n = 185) .368 .873 .256 .636 .244 .582 .291
.796 .397 .834 .292
(.260) (.228) (.295) (.400) (.295)
Long-term paid absences:

Experimental group (n= 161) 9.875 10.619 6.732 7.725 6.807
7.583 8.416 12.060 7.484 7.635 7.359 (6.688) (6.762) (8.371)
(7.439) (7.315) Control group (n =185) 7.737 9.552 7.718
14.602 8.762 11.828 8.172 8.912 7.659 9.746 8.077 (7.757)
(8.800) (8.211) (7.698) (8.116)
18:12:41 UTC
adjusted mean of short-term unpaid absences during the 4-
month inter-
vention period was .128 for the experimental group and .275
for the con-
trol group. A 2 (experimental vs. control) x 4 (time) analysis of
covariance
using the pre-intervention measure as a covariate revealed a
statistically
significant difference between the experimental and the control
group
(F1,343= 9.15, p < .002). This result represents approximately
a 35 percent
decrease in the experimental group's short-term unpaid
absences from the
pre-flexitime period to the flexitime period, and there was

about a 28 per-
cent increase in the short-term unpaid absences among the
employees in
the control group. Neither the time effect nor the interaction
effect was
statistically significant.
Long-term unpaid absences in the experimental group
decreased by 45
percent from the pre-flexitime period to the flexitime period.
On the other
hand, there was about a 98 percent increase in the same
measure among
the employees in the control group. This increase appears to be
notable,
but it did not reach a level of statistical significance when the
initial differ-
ence between the experimental and the control group was
accounted for
(F1,343 = 2.24; N.S.). As with short-term unpaid absences,
neither the time
effect nor the interaction effect was noted. Yet, the trend of the
data on
unpaid absences seems to be clear. Long-term unpaid absences
were lower
in the experimental group than in the control group in every
month during
the 4-month flexitime intervention period. In fact, the long-
term absen-
teeism among the employees in the control group was more
than three
times greater than that in the experimental group for the last 30
days of the
flexitime intervention.
Table 2 shows the findings on the short-term and the long-term

paid ab-
sences taken by the employees in the experimental and the
control groups.
Although the short-term paid absences among the employees
under the
flexitime program were slightly greater than the same measure
among the
employees in the control group, no statistically significant
difference was
observed during the 4-month intervention period (M'=.365 vs.
M'=
.295; F1,343 = 2.27, N.S.). Neither time effect nor the group by
time interac-
tion effect was statistically significant. For the long-term paid
absences,
the findings were reversed with the similar statistical results.
The em-
ployees under the flexitime program tended to show a lower
amount of
paid absenteeism than those in the control group, but this
difference did
not reach a statistical level of significance. Again, neither time
effect nor
the group by time interaction effect was statistically
significant.
As suggested earlier, two different analyses were conducted for
perfor-
mance efficiency: (1) four separate division analyses to account
for the
variations in the nature of the task; and (2) a combined analysis
across the
four divisions to increase the degree of generalizability. Table
3 shows the
summary of means, adjusted means, and standard deviations of
perfor-

mance efficiency for each of the four divisions under study.
For division 1, the adjusted mean for the experimental group
was .803
as compared to .583 for the control group during the 4-month
intervention
18:12:41 UTC
TABLE 3
of Performance Efficiency in Four Divisions
(N= 94)
PRE 1-Month 2-Month 3-Month 4-Month Marginal Criterion
Measuresa M SD M SD M SD M SD M SD Meansc
Division 1:
Experimental group (n=6) .507 .586 .768 .559 .802 .671 .671
.598 .590 .157 .707 (.793)b (.833) (.699) (.889) (.803) Control
group (n = 5) .568 .032 .763 .190 .587 .082 .553 .082 .804 .746
.676 (.733) (.550) (.500) (.549) (.583)
Division 2:
Experimental group (n =14) .725 .314 .948 .332 .745 .332 .873
.279 .794 .260 .840 (.969) (.758) (.887) (.808) (.855) Control

group (n= 16) .769 .288 .732 .342 .681 .408 .827 .375 .741 .450
.745 (.714) (.671) (.814) (.728) (.731)
Division 3:
Experimental group (n =16) .286 .114 .301 .120 .300 .131 .246
.069 .263 .075 .277 (.285) (.281) (.238) (.250) (.263) Control
group (n = 26) .237 .075 .262 .085 .259 .097 .248 .089 .224 .107
.248 (.271) (.271) (.253) (.232) (.256)
Division 4:
Experimental group (n 6) .165 .067 .177 .078 .247 .120 .240
.130 .172 .083 .209
(.178) (.249) (.240) (.172) (.209)
Control group (n = 5) .168 .162 .164 .104 .395 .472 .194 .079
.234 .055 .246 (.164) (.393) (.193) (.234) (.246)
aDivision 1: Hourly rate of cases approved during the month;
Division 2: Hourly rate of routine actions completed during the
month; Division 3: Hourly
rate of cases processed during the month; Division 4: Hourly
rate of cases processed during the month.
bThe adjusted means using the monthly measures immediately
CThe average of the criterion measure for the four month
18:12:41 UTC

period. A 2 (experimental vs. control) x 4 (time) analysis of
covariance
using the pre-intervention measure as a covariate revealed a
statistically
significant difference between the experimental and the control
group
(F1,8 = 12.642; p < .007). Although the pattern of performance
efficiency
between the two groups appeared to be different during the
experimental
period, the group by time interaction effect failed to reach a
statistical
level of significance (F3,24 = 1.948; N.S.). The results for the
remaining
three divisions showed that neither the main nor the interaction
effect was
statistically significant. Yet, in two (divisions 2 and 3) of these
three divi-
sions, performance efficiency tended to be higher for the
experimental
group than for the control group. For example, when the initial
difference
in performance efficiency prior to the intervention was
accounted for, it
was found that the average hourly rate of routine actions
completed for
the experimental group in division 2 was about 17 percent
higher than that
for the control group during the intervention period. In division
4, a re-
versed trend was shown. The average hourly rate of cases
processed for the
experimental group was about 16 percent lower than that for

the control
group during the intervention period.
Table 4 shows the findings on the standardized performance
efficiency
for all four divisions combined. The standardized average
performance ef-
ficiency adjusted for the initial difference was higher for the
experimental
group (M' = .109) than for the control group (M' = -.076).
However, this
difference did not reach a statistical level of significance
(F1,91 = 1.590;
N.S.). Neither the time effect nor the group by time interaction
effect was
statistically significant.
Although excluded from the overall experimental design of this
study,
additional data were obtained by an evaluation committee of
seven agency
members on the employees' reactions on the flexitime time. The
em-
ployees' responses to the flexitime program, obtained by the
questionnaire
after the intervention period, were very favorable. For example,
among
those in the experimental group, approximately 84 percent
reported that
flexitime had a strong positive influence on their morale; 92
percent re-
ported that the flexitime program had a strong influence on
arranging time
for personal matters outside of agency hours; 62 percent
reported that the

flexitime program improved their job satisfaction; 88 percent
reported
that the flexitime program had a strong positive effect on the
reduction of
morning tension; 91 percent reported that flexitime had a
positive influ-
ence on the reduction of commuting time and traffic congestion
problems,
and 61 percent reported that the flexitime program reduced
their parking
problem.
CONCLUSION AND DISCUSSION
In spite of a general lack of empirical supports, it has been
often sug-
gested that the employees under a flexitime program would
reduce absen-
teeism and increase their productivity. The results of this study
suggest
18:12:41 UTC
TABLE 4
Summary of Means, Adjusted Means, and Standard Devilations
of Standardized Performance Efficiency in Four Divisions
Combilned
(N = 94)

PRE .1-Month 2-Month 3-Month 4-Month Marginal Criterion
Measures M SD M SD M SD M SD M SD MeanSb
Experimental group (n =42) .095 1.192 .246 1.118 4154 1.065
.121 1.092 .098 .972 .154 (.195)a (.107) (.080) (.057) (.109)
Control group (n =52) -.055 .895 -.148 .884 -.053 .959 -.044
1.017 -.100 1.049 -.086 (-.107) (-.015) (-.01 1) (-.067) (-.076)
18:12:41 UTC
that flexitime significantly reduces employees' unpaid absences
in general.
However, the positive impact of flexitime on short-term unpaid
absen-
teeism (leave without pay for two hours or less a day) appears
to be much
stronger than on the long-term unpaid absenteeism (leave
without pay for
more than two hours a day). This finding suggests that the
flexible work-
ing hours allowed under the flexitime program have served as a
substitute
for short-term leave without pay. This substitutability was not
apparent

for the long-term unpaid absences. However, no substantial
increase or
decrease in paid absences was noted. Employees under the
flexitime pro-
gram tend to take just as many paid absences (i.e., sick leave)
as the em-
ployee with regular work hours.
As stated earlier, empirical studies investigating the effect of
flexitime
on performance are virtually nonexistent. One study by Schein
et al.
(1977) suggested that a flexitime program has no adverse
impact on per-
formance in a private sector organization. The results of the
present study,
conducted in a public sector agency, concurs with that finding.
In three
out of four divisions, the performance during the 4-month
flexitime
period was higher in the experimental group than in the control
group, al-
though in only one of these divisions did it reach a statistical
level of sig-
nificance. Thus, one may conclude that flexitime had either a
positive im-
pact on performance or did, at a minimum, encourage an
increase in per-
formance among public employees.
The results of this study imply that the employees under
flexitime tend
to take it as an alternative benefit to be used for nonwork
activities with-
out affecting their economic benefits. This would imply that,
although

one may expect the reduction of employees' leave without pay
under the
flexitime program, the costs associated with absenteeism would
not neces-
sarily be reduced. Yet, to the extent to which flexitime
increases efficiency
of labor input, the overall organizational effectiveness can be
enhanced.
However, the findings also imply that the potential positive
impact of
flexitime on performance efficiency may not be constant across
different
tasks. For example, Partridge (1973) reported findings that
suggest that
flexitime tended to hinder managers in supervising their staffs,
in fitting in
with unpredictable work times, and in setting up formal
meetings in the
office. He concluded that flexitime can generate difficulties in
coordinat-
ing subordinates' activities that arise from uneven work flow.
One can
argue that the degree of difficulty caused by flexitime would
vary accord-
ing to the kind of coordination needed for the completion of a
certain
task. If the job requires an extensive communication and
information ex-
change among supervisors, co-workers, clients, etc., the
potential payoff
in performance under flexitime may be low. On the positive
side, if the
nature of the task and task interdependence is such that each
employee can
perform an entire module in a relatively autonomous manner

(i.e., pooled
interdependence), performance can be increased under the
flexitime pro-
gram. Because the nature of interdependence and coordination
needs for
task completion was not measured in this study, one can only
speculate on
18:12:41 UTC
the validity of this argument. However, if it is valid, it implies
that the na-
ture of the task should be considered carefully before a
decision to imple-
ment flexitime is made. For example, if the nature of the task is
sequential
in nature (i.e., assembly line), the implementation of flexitime
would not
be feasible or would incur a considerable increase in
coordination costs in
production.
Two methodological limitations of this study should be noted.
First, the
employees in both the control group and the experimental
group knew
that they were participating in a field experiment and that the
results of
this experiment would have potential influence on policy
decisions on flex-

itime program implementation for the entire agency. Because
the em-
ployees were not "blind" to what was taking place, their
responses might
have been influenced by the "Hawthorne effect" and/or by a
"Rosenthal
effect." This possibility could not be totally ruled out from the
current re-
search context: the policy of this agency was such that the
employees were
kept informed on this flexitime experiment. However, the
employees, in-
cluding supervisors, did not have knowledge as to which
criteria would be
employed in evaluating flexitime effectiveness. Further,
because (1) the
employees were led to believe the questionnaire responses to
be the pri-
mary data source for the evaluation of the flexitime program
and (2) the
criterion measures were compiled from the centralized data
pool by a third
party, the possible influence of the expectations on the
experimental group
would have been minimal. Second, subjects were not selected
completely
at random. However, the intact groups (i.e., administrative
units) were
chosen randomly and assigned to the experimental and the
control group
for each division. They thus shared all practical bases such as
common
tasks, common supervision, and common level. Thus,
meaningful com-
parisons could be made in each division.

Notwithstanding these limitations, the results of this study
appear to
justify the argument that the flexitime program has a positive
impact on
attendance and performance among public sector -employees. It
should be
noted that this study investigated only one of several forms of
the flexitime
program. Additional research on various other forms of the
flexitime pro-
gram in different organizational contexts is clearly warranted.
Future
studies might fruitfully investigate the potential moderating
effect of task
on the effectiveness of flexitime as an organization
development interven-
tion.
REFERENCES
1. Evans, M. G. Notes on the impact of flexitime in a large
insurance company: 1. Reactions of non-
supervisory employees. Occupational Psychology, 1973, 47,
237-240.
2. Golembiewski, R. T., & Hilles, R. J. Drug company workers
like new schedules. Monthly Labor
Review, 1977, 100, 69-71.
3. Golembiewski, R. T., & Proehl, C. W. A survey of the
empirical literature on flexible work-
hours: Character and consequences of a major innovation.
Academy of Management Review,
1978, 3, 837-853.

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4. Golembiewski, R. T., Hilles, R., & Kagno, M. S. A
longitudinal study of flexitime effects: Some
consequences of an OD structural intervention. Journal of
Applied Behavioral Science, 1974, 4,
503-532.
5. Harvey, B. H., & Luthans, F. Flexitime: An empirical
analysis of its real meaning and impact.
MSU Business Topics, Summer 1979, 31-36.
6. Hopp, M. A., & Sommerstad, C. R. Reaction at computer
firm: More pluses than minuses.
Monthly Labor Review, 1977, 100, 69-71.
7. Martin, V. H. Hours of work. Washington, D.C.: Business
and Professional Women's Founda-
tion, 1975.
8. Mueller, 0., & Cole, M. Concept wins converts at federal
agency. Monthly Labor Review, 1977,
100, 71-74.
9. Nollen, S. C. Does flexitime improve productivity. Harvard
Business Review, 1979, 57 (5), 16-18,
76, 80.
10. Nollen, S. D., & Martin, V. H. Alternative work schedules,
part I: Flexitime. New York:
AMACOM, 1978.

11. Partridge, B. D. Notes on the impact of flexitime in a large
insurance company: II. Reactions of
supervisors and managers. Occupational Psychology, 1973, 47,
241-242.
12. Schein, V., Maurer, E., & Novak, J. Impact of flexible
working hours on productivity. Journal
of Applied Psychology, 1977, 62, 463-465.
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