times, less one, as there were employees in the
group. Analyses were run between aggregated
intent to leave and the aggregated job satisfaction
scores across individuals, assigning to the in-
dividuals the aggregated job satisfaction score
("Group") that did not contain their own expres-
sion of job satisfaction. Although this method of
aggregation may still be “contaminated,” the
removal of the individual from the aggregated
group job satisfaction score reduced the threat of
individually-based response contamination. To
look for the possible effects of method variance,
we also computed the aggregated group job
satisfaction score ("Group'TM") leaving in the
individual score; this score reflects the actual
aggregated score of job satisfaction (i.e., the
mean job satisfaction score of the occupational
group).

RESULTS

The analyses plan followed the criteria for
aggregation. First, analyses of variance were
used to identify possible differences in intent to
leave and level of job satisfaction across different
occupational groups. Occupational group dif-
ferences in both intent to leave (F 1/13 = 3.0, p
< .01) and job satisfaction (F 1/13 = 11.7, p <
.01) were statistically significant. The means and
standard deviations of the intent to leave and job
satisfaction scales for each of the occupational
groups are presented in Table 1. As shown there,
there was some variability between the occupa-
tional groups in both intent to leave and level of
job satisfaction. The finding that some occupa-
tional groups (¢.g., air traffic control and logis-
tics) had both low intent to leave and low job
satisfaction scores suggests that a number of
other factors may affect intentions to leave. For
example, air traffic control personnel have
relatively fewer career alternatives than other
workers, so that even when they experience low
job satisfaction, leaving the organization may be
an unlikely alternative.

Second, researchers have argued that ag-
gregated measures should meet criteria of within-
group agreement (i.e., homogeneity) to avoid
aggregation bias (Drexler, 1977; James, 1982).
The intraclass correlation coefficient provides an
estimate of interrater agreement (James, 1982).

We employed the intraclass correlation coeffi-
cient -- ICC(1,k) — discussed by Shrout and
Fleiss (1979, p. 426) as the lower bound estimate
of the mean rater reliability of the aggregate
score. The coefficients are in the lower end of
the acceptable range of those reported in previous
studies (Glick, 1985) for the intent to leave item
[ICC (1,k) = .66], but in the higher end for the
job satisfaction scale [ICC (1,k) = .91].

Third, as shown in Table 2, individual-level
scores on the satisfaction measure were very
weakly and negatively related to occupational
group-level intent to leave scores (r = -.11, p <
.01). In other words, individual expressions of
job satisfactions were essentially unrelated to the
mean group-level intent to leave.

Occupational group-level satisfaction scores,
however, were moderately related to group-level
intent to leave scores (GroupTM: r = -.65, p <
.01 vs. Group’: r = -.40, p < .01). These
results are consistent with earlier studies showing
that correlations of aggregate variables based on
homogeneous groups are higher than their
individual counterparts (cf. Rousseau, 1985).

To further assess the final criterion for
aggregation, multiple regression analyses were
employed to assess individual and occupational
group contributions to the criterion measure of
occupational group-level intent to leave
(Mossholder & Bedeian, 1983). First, given the
findings demonstrating the relationships between
biodata and intent to leave, 5 biodata variables -
- pay grade, age, education level, gender, and
number of years worked in the organization -
were entered into the equation. These individual-
level demographic variables accounted for a
small but significant amount of the variance in
occupational group-level intent to leave R =
.07, F 5/4737 = 72.88, p < .01). Scores on the
job satisfaction measure for each individual were
then entered into the equation, the results of
which are presented in Table 3. As shown,
individual job satisfaction scores contributed only
an additional 1% of the variance. The aggregated
job satisfaction scores -- Group" and Group" -
- were then entered into the equation in separate
analyses. As shown in Table 3, the data indicated
that the addition of Group” and GroupTM” to the


Intent to leave has been conceptualized as an
individual phenomenon. However, a common
anecdote is the comparison of organizations as
having employees with different levels of inten-
tions to leave and commensurate turnover rates.
Indeed, it is likely that organizations and or-
ganizational subsystems engender different levels
of job satisfaction that may affect intent to leave;
thus, to some extent it is a unit-level phenom-
enon. Aggregation of individual job satisfaction
permits prediction of organizational or subsystem
intent to leave, which may be of considerable
interest to managers. The data discussed here
suggest that the application of the Jones and
James (1979) criteria for aggregation provides
appropriate helpful guidelines for pursuing such
a task.

REFERENCES

Bass, B. M., Aviolo, B. J., & Yammarino, F.
J.(1988, April). A strategy for evaluating
single-source bias. Presented at the mid-year
conference of the Society for Industrial and
Organizational Psychology, Dallas, Texas.

Blau, G., & Boal, K.(1989). Using job involve-
ment and organizational commitment interac-
tively to predict turnover. Journal of
Management, 15, 115-127.

Dansereau, F. & Markham, S. E.(1986). Levels
of analysis in personnel and human resources
management. Working Papers Series No.
683. State University of New York at
Buffalo.

Drexler, J. A., Jr.(1977). Organizational climate:
Its homogeneity within organizations. Journal
of Applied Psychology, 62, 38-42.

Fishbein, M.(1967). Attitude and the prediction
of behavior. In M. Fishbein (Ed.), Readings
in attitude theory and measurement. New
York: Wiley.

Galtung, J.(1967). Theory and methods of social
research. New York: Columbia University
Press.

Glick, W. H. (1985). Conceptualizing and mea-
suring organizational and psychological cli-
mate: Pitfalls in multilevel research.
Academy of Management Review, 10, 601-
616.

Hom, P. W., Katerberg, R., Jr., & Hulin, C.
L.(1979). Comparative examination of three
approaches to the prediction of turnover.
Journal of Applied Psychology, 64, 280-290.

Howe, J. G.(1977). Group climate: An ex-
ploratory analysis of construct validity. Or-
ganizational Behavior and Human Perfor-
mance, 19, 106-125.

James, L. R.(1982). Aggregation bias in es-
timates of perceptual agreement. Journal of
Applied Psychology, 67, 219-229.

Jolma, D. J.(1990). Relationship between nursing
work load and turnover. Nursing Economics,
8, 110-114.

Jones, A. P., & James, L. R.(1979).
Psychological climate: Dimensions and
relationships of individual and aggregated
work environment perceptions.
Organizational Behavior and Human
Performance, 23, 201-250.

Kraut, A.(1975). Predicting turnover of
employees from measured job attitudes.
Organizational Behavior and Human
Peformance, 13, 233-243.

Lachman, R., & Aranya, N.(1986). Job attitudes
and turnover intentions among professionals
in different work settings. Organization
Studies, 7, 279-293.

Lachman, R., & Diamant, E.(1987). Withdrawal
and restraining factors in teachers’ turnover
intentions. Journal of Occupational
Behaviour, 8, 219-232.

Lance, C. E., Hedge, J. W., & Alley, W.
E.(1989). Joint relationships of task
proficiency with aptitude, experience, and
task difficulty: A cross-level, interactional
study. Human Performance, 2, 249-272.



has received increasing attention in fields such as
political science, education, technology, and
sociology. The process of determining the exis-
tence of multi-level effects with regard to job
satisfaction requires demonstration that both
individual and aggregate components contribute
significantly to group intent to leave (i.e., up-
ward cross-level inference).

Jones and James (1979) proposed 4 criteria
to justify aggregation of individual-level
perceptual data: (a) significant mean differences
in perceptions across different subunits (Drexler,
1977), (b) interperceiver agreement or reliability
of the perceptions (Howe, 1977), (c) homogen-
eous situational characteristics, and (d) meaning-
ful relationships between the aggregated percep-
tion score and various individual, subunit, or
organizational criteria (Pritchard & Karasick,
1973), such as the relationship between employee
perceptions of organizational effectiveness and
organizational profit levels. Once these criteria
are met, “cross-level formulation" (Dansereau &
Markham, 1986) or a justification for group-
level satisfaction is established.

The purpose of the present study was to
assess the utility of cross-level effects of job
satisfaction in the prediction of intent to leave by
applying the Jones and James (1979) criteria.

METHOD
Subjects and Procedure

Questionnaires were mailed to a random sample
of 8,029 employees of the Federal Aviation
Administration (FAA). The sample was stratified
by facility and occupational group in order to
increase the probability of obtaining a
representative sample. Returning _ completed
questionnaires were 5,586 employees (69.5%;
4,423 males and 1,163 females). Ages reported
by the respondents were as follows: 29 and under
(15.8%), between 30 and 39 (38.2%), between
40 and 49 (33.7%), and 50 or over (12.3%).
Over 92% indicated education or training beyond
that of a high school diploma, with 49.8%
reporting some college education, 21.7% having
received a bachelor’s degree, and 13.8% indicat-
ing that they have education above the bachelor

level. About 27% indicated that they had worked
for the FAA 3 years or less, 34.4% for 4 to 9
years, 15.5% for 10 to 15 years, 12.1% for 16
to 20 years, and 10.4% for 20 or more years.

The occupational group (e.g., accounting
workers, air traffic controllers, airway facilities
specialists, computer programmers) represented
the organization’s subsystem that would have
sufficient homogeneous situational characteristics
to permit aggregation. Although employees
within occupational groups worked at different
sites, they worked in organizational structures
unique from other groups and shared relatively
common organizational cultures. Moreover,
assessment of job attitudes by occupational group
has a tradition in the FAA (e.g., Myers, Sch-
roeder, Van Deventer, & Collins, 1988).

Measures

Intent to leave was assessed by a single item
(M = 2.66, SD = 1.37), “Taking everything
into account, how likely or unlikely is it that you
will leave the FAA for any reason within the
next five years?" Response options were
presented on a 5-point Likert-type scale (1 =
very unlikely; 5 = very likely). Job satisfaction
was assessed by the Schroeder, et al.(1986) 10-
item measure (alpha = .82, M = 33.34, SD =
7.61). Items (e.g., "In general, how satisfied are
you with your job - the kind of work you do?"
and "Overall, how satisfied are you with your
pay?") were presented on a 5-point Likert-type
scale (1 = very dissatisfied; 5 = very satisfied).

A major concern with data collections of this
type is the threat of single-source bias (Bass,
Aviolo, & Yammarino, 1988) or method variance
(Podsakoff & Organ, 1986; Spector, 1987). The
notion of method variance suggests that collecting
data from the single source of individuals leads
to an artificially inflated relationship between the
constructs measured, because the ratings for each
individual share a single information processing
and. dispositional basis. To both avoid and
examine the possible effect of method variance,
we implemented a procedure suggested by
Schneider (personal communication, May 2,
1990). For each occupational group, we ag-
gregated the job satisfaction scores as many


equations predicting occupational group intent to satisfaction score. The R® of the GroupTM” equa-
leave added appreciable variance over-and-above tion was considerably higher (R’ = .44) than the
the variance contributed by individual-level job Group” equation (R? = .20).

Table 1

Intent to Leave and Job Satisfaction Scales Score
Means and Standard Deviations Across Occupational Groups

Intent to Leave Job Satisfaction

Occupational Group Mean sD Mean sD

Accounting 2.81 1.37 34.55 7.21
Air Traffic Control 2.59 1.35 32.24 7.50
Aircraft Certification 2.71 1.40 36.24 7.05
Airports 2.74 1.49 35.98 7.74
Airway Facilities 2.79 1.41 34.13 7.49
Aviation Standards 2.53 1.24 35.67 7.57
Budgeting 3.23 1.20 35.48 7.37
Flight Standards 2.66 1.34 35.22 7.52
Human Resources Management 2.92 1.29 35.80 7.63
Logistics 2.58 1.39 33.83 7.92
Computing 2.85 1.54 35.02 7.95
Medical 2.92 1.42 36.63 6.13
Security 2.83 1.26 33.39 7.96

Table 2

Intercorrelation Matrix

Variable 1 2 3 4

1. Individual Satisfaction Scores

2. Group” Satisfaction Scores 17

3. GroupTM Satisfaction Scores .07 64

4, Individual Intent to Leave Scores -.29 -.05 -.04

5. GroupTM” Intent to Leave Scores -.11 -.40 -.65 .07

Note: All correlations are p < .01.


Marsh, R., & Mannari, H.(1977). Organizational
commitment and turnover: A predictive
study. Administrative Science Quarterly, 22,
57-75,

Martin, T. N.(1979). A contextual model of
employee turnover intentions. Academy of
Management Journal, 22, 313-324.

Martin, T. N., & Hunt, J. G.(1980). Social
influence and intent to leave: A path-analytic
process model. Personnel Psychology, 33,
505-528.

Mobley, W. H., Hand, H. H., Baker, R. L., &
Meglino, B. M.(1979). Review and
conceptual analysis of the employee turnover
process. Psychological Bulletin, 86, 493-
522.

Mobley, W., Horner, S., & Hollingsworth,
A.(1978). An evaluation of precursors of
hospital employee turnover. Journal of
Applied Psychology, 63, 408-414.

Mossholder, K. W. & Bedeian, A. G.(1983).
Cross-level inference and organizational
research: Perspectives on interpretation and
application. Academy of Management Review,
8, 547-558.

Myers, J. G., Schroeder, D. J., Van Deventer,
A., Collins, W. E.(1988). 1988 FAA job
Satisfaction survey: National report.
Washington, D. C.: FAA Office of Aviation
Medicine.

Podsakoff, P. M., & Organ, D. W.(1986). Self-
reports in organizational research: Problems
and prospects. Journal of Management, 12,
531-544.

Prestholdt, P. H., Lane, I. M., & Mathews, R.
C.(1987). Nurse turnover as reasoned action:
Development of a process model. Journal of
Applied Psychology, 72, 221- 227.

Price, J., & Mueller, C.(1981). Professional
turnover: The case of nurses. New York:
Spectrum Publications, 1981.

Pritchard, R. D. & Karasick, B. W.(1973). The
effect of organizational climate on managerial
job performance and job satisfaction. Or-
ganizational Behavior and Human Perfor-
mance, 9, 126-146,

Rousseau, D. M.(1985). Issues of level in or-
ganizational research: Multi-level and cross-
level perspectives. In B. Staw and L. L.
Cummings (Eds.), Research in
Organizational Behavior (pp. 1-37). New
York: JAI Press.

Schroeder, D. J., Thomas, S., Weltin, M., Van
Deventer, A., Collins, W. E., Dollar, C. S.,
& Ritchie, L.(1986). 1986 FAA employee
survey: National report. Washington, D. C.:
FAA Office of Aviation Medicine.

Shore, L. M., & Martin, H. J.(1989). Job
satisfaction and organizational commitment in
relation to work performance and turnover
intentions. Human Relations, 42, 625-638.

Shrout, P. E., & Fleiss, J. L. (1979). Intraclass
correlations: Uses in assessing rater re-
liability. Psychological Bulletin, 86, 420-
428.

Spector, P. E.(1987). Method variance as an
artifact in self-reported affect and perceptions
at work: Myth or significant problem?
Journal of Applied Psychology, 73, 11-19.

Steel, R. P., & Ovalle, N. K.(1984). A review
and meta-analysis of research on the
relationship between behavioral intentions
and employee turnover. Journal of Applied
Psychology, 69, 673-686.

Wright, R. D.(1982). Intent to leave: A
multivariate, _multi-organizational study.
Unpublished Doctoral Dissertation, Boston
University, Boston.

$CU.S. GOVERNMENT PRINTING OFFICE: 1991 - 661-017/40269


Office of Aviation Medicine
Washington, D.C. 20591.
j ‘s
| , 3 : L.Alan Wite
_ Chan M. Hellman
ae Civil Aeromedical Institute. °° SS
| ~.. Bederal Aviation Administration =
| “ ~ Oldahoma City, Oklahoma 73125
f ‘ *
October 1991
Final Report

>

This document is available to the public thrpuigh
the National Technical Information Setvics,
Springfield, Virginia P2161

U.S. Departriont
of Transportation

‘Administration



Table 3
Results of Hierarchical Regression Analyses

Individual and Occupational

Group-Level Full Model
Predictor Variables R EF p<
Ind. & Group” Satisfaction 20 170.84 .01

Ind. & GroupTM” Satisfaction 44 544.76 .01

Addition of Addition of
Individual Sat. Group Sat.
aR EF p< AR OE p<

.01 41.27 01.12 724.65 01
01 68.13 01 .37 3134.18 01

Note: The full model includes the addition of the GroupTM” or Group” satisfaction scores to the equation

of the biodata predicting intent to leave.

DISCUSSION

Several caveats should be emphasized. First,
data were collected from employees of the FAA
and may not be representative of other work
populations. Second, the present study neither
examined nor controlled for a number of possible
confounding variables, including nonwork vari-
ables relevant to organizational intent to leave,
availability of career options, and events external
to the organization (e.g., budget problems) that
may have affected job satisfaction and/or intent
to leave considerations at the time of measure-
ment. Third, other measures of organizational
intent to leave and job satisfaction may have
yielded different results. Fourth, these data may
be subject to common method variance. The
finding that the relationship between the Group"TM
satisfaction and occupational group-level intent
was appreciably stronger than the relationship
between the Group” satisfaction and occupational
group-level intent supports this notion. Further
research is needed to evaluate Schneider’s (per-
sonal communication, May 2, 1990) suggestion
for reducing the effects of method variance for
data collected from a single source.

The application of the Jones and James
(1979) criteria to these data provided some
support for the aggregation of the job satisfaction
measure. We found significant occupational
group differences. The intraclass correlation

coefficients were of sufficient size to warrant
aggregation. In other words, there may have
been a reasonable degree of homogeneity of
intent to leave and job satisfaction levels within
the occupational groups. The examination of
relations between the aggregated job satisfaction
and intent to leave scores yielded sufficient
increases in variance that were over-and-above
the contributions of individual-level job satisfac-
tion scores. These data suggest that when the
criterion is group-level intent to leave, group-
level job satisfaction is a more appropriate
predictor than is individual-level job satisfaction.
It is likely that certain organizations or organiza-
tional subsystems engender certain levels of job
satisfaction among their employees. By aggregat-
ing individual job satisfaction scores at the unit
level, between-group comparisons and links to
conceptually relevant constructs can be made.
Using the analytic approach described here,
aggregate job satisfaction measures may be
appropriate in the prediction of aggregate intent
to leave or other unit-level phenomenon of
interest. Therefore, we suggest that this approach
may be more meaningful for managers.

The focus of cross-level inferences has been
on organizational climate. Rousseau (1985, p. 6)
suggested that meaning can “be added by ag-
gregation when each individual’s score on a
variable (X) reflects the result of a unit-level
phenomenon whose overall effect is of interest."


Technical Report Documentation Page

DOT/FAA/AM-91/15

Report Ne. 2. Government Accession No.

3, Recipient's Catalog No.

4

Title and Subtitle

Cross-Level Inferences of Job Satisfaction in the
Prediction of Intent to Leave

5. Report Date
October 1991

6. Performing Organization Code

. Author! s)

L. Alan Witt, Ph.D. and Chan M. Hellman, B.S.

8. Performing Organization Report No.

Performing Orgenizotion Nome and Address

FAA Civil Aeromedical Institute
P. 0. Box 25082
Oklahoma City, OK 73125

0. Work Unit No. (TRAIS)

TI. Conteaet or Grant No.

. Sponsoring Agency Nome and Address

Office of Aviation Medicine
Federal Aviation Administration
800 Independence Avenue, S.W.
Washington, D.C. 20591

13. Type of Report and Period Covered

14. Sponsoring Agency Code

. Supplementary Notes

This work was performed under Task AM-C-91-HRR122.

16. Abstract
An emerging literature has demonstrated that proportionately more dissatisfied
employees intend to leave their employing organization while proportionately
more satisfied employees intend to remain. The purpose of the present study
was to apply criteria for aggregation of individual-level data to the group-
level using a measure of job satisfaction in the prediction of aggregated group-
level intent to leave. Data collected from 5,586 employees of the Federal
Aviation Administration provided partial support for aggregation. These
results have general implications for the use of individual-level job satisfac-
tion scores as predictors of group-level intent to leave.

17, Key Words 18. Distribution Statement
job satisfaction; Document is available to the public
intent to leave; through the National Technical
cross-level inference. Information Service, Springfield,

Virginia 22161.

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Unclassified Unclassified 10

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Reproduction of completed page authorized


E.P.AL, | pomarcce

CROSS-LEVEL INFERENCES OF
JOB SATISFACTION IN THE
PREDICTION OF INTENT TO LEAVE

Given the negative effects of unwanted
employee turnover on organizational operations,
management sensitivity to the antecedents of
employee intentions to leave the organization is
significant and warrants empirical attention.
Behavioral intentions theory (Fishbein, 1967)
suggests that an individual’s intentions are the
most consistent and dependable predictors of a
resulting behavior. Looking at turnover, Hom,
Katerberg, and Hulin (1979) indicated that the
algebraic formula for Fishbein’s theory is B =
f(BI), where a person’s behavior (B) is a function
(f) of the intention to execute the behavior (BI).
Indeed, intent to leave has consistently been
identified as the best predictor of turnover
(Kraut, 1975; Mobley, Horner, & Hollingsworth,
1978; Prestholdt, Lane, & Mathews, 1987; Price
& Mueller, 1981; Steel & Ovalle, 1984), For
example, Steel and Ovalle’s (1984) meta-analysis
of the literature indicated that the intention to
leave predicted turnover better than such
traditionally considered variables as job
satisfaction and organizational commitment.

Identification of the factors that lead to
turnover before it happens would provide an
opportunity to reduce unwanted turnover. This
might be accomplished by identifying the precur-
sors of intent to leave. While turnover has been
examined quite extensively (cf. e.g., Mobley,
Hand, Baker, & Meglino, 1979), the intent to
leave concept has received comparatively less
attention. Researchers have identified several
antecedents of intent to leave: (a) global job
satisfaction, facets of job satisfaction, or total-
facet job satisfaction (Hom, et al., 1979; Kraut,
1975; Lachman & Aranya, 1986; Marsh &
Mannari, 1977; Martin, 1979; Martin & Hunt,
1980; Mobley, et al., 1979; Price & Mueller,
1981; Shore & Martin, 1989; Wright, 1982), (b)
group cohesiveness, job autonomy, and personal
factors (Marsh & Mannari, 1977), (c) supervisor-
related issues (Hom, et al., 1979), (d) organiza-
tional commitment (Blau & Boal, 1989; Lachman
& Aranya, 1986), (e) job involvement (Blau &
Boal, 1989), (f) workload (Jolma, 1990), (g)
burnout (Lachman & Diamant, 1987), and (h)

life status factors, such as age and tenure in the
organization (e.g., Martin, 1979; Mobley, et al.,
1978; Price & Mueller, 1981).

A methodological issue that has not been
addressed in the literature is the appropriate level
of analysis for investigating intent to leave. The
aforementioned studies have examined the rela-
tionships between individual-level job attitudes
and individual-level intent to leave. We suggest
that when the criterion of interest is organization-
al intent to leave, the organization is the ap-
propriate level of analysis. Similarly, when the
criterion of interest is group (i.e., a subsystem of
the organization) intent to leave, the group is the
appropriate level of analysis. Predicting a par-
ticular employee’s intention to leave may be of
interest, particularly for planning purposes for
individual managers. The group or organization
level intent to leave may also be of interest to
managers. In other words, the level of intent to
leave within a particular organization or
subsystem may sometimes be an important issue,
as it is at this level that predictions of organiza-
tion or group turnover can be made, as well as
between group comparisons. For example, when
human resources planners are estimating turnover
contributions to future personnel needs, the group
level(s) of intent to leave (i.e., the aggregations
of the individual intentions to leave) may be
compared, rather than the individual intentions.

Job satisfaction has been the most frequently
cited antecedent of intent to leave. If we attempt
to predict group-level intent to leave from in-
dividual-level job satisfaction data, then we are
committing the “fallacy of the wrong level"
(Galtung, 1967, p. 45). The purpose of the
present study was to examine cross-level effects
of job satisfaction in the prediction of intent to
leave. As defined by Mossholder and Bedeian
(1983, p. 547), cross-level inference "occurs
when relations among variables at one level are
inferred from analyses performed at a different
level." They suggested that the attempt to infer
individual level relations from higher level
analyses is known as downward cross-level
inference, while the attempt to infer macro level
relations from lower level analyses is known as
upward cross-level inference. As noted by Lance,
Hedge, and Alley (1989), cross-level research