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Surviving Layoffs: The Effects on Organizational Commitment and Job Performance
LEON GRUNBERG, RICHARD ANDERSON-CONNOLLY and EDWARD S. GREENBERG
Work and Occupations 2000 27: 7
DOI: 10.1177/0730888400027001002
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Grunberg
WORK
AND
et al.OCCUPATIONS
/ SURVIVING LAYOFFS
This article tests the hypotheses that the effects of layoffs on surviving employees’level of organizational commitment and job performance will vary according to (a) how close employees are
to the layoffs, (b) their perceptions of the fairness of the layoffs, and (c) their position in the
organizational hierarchy. Analyses were conducted on 1,900 respondents employed by a large
U.S. company. Results indicated that although perceptions of layoff unfairness were associated
with lower commitment regardless of employee position, close contact with layoffs was associated with the greater use of sick hours by surviving managers and professionals, but with lower
use of sick hours and higher work effort by employees in lower positions.
Surviving Layoffs
The Effects on Organizational
Commitment and Job Performance
LEON GRUNBERG
RICHARD ANDERSON-CONNOLLY
University of Puget Sound
EDWARD S. GREENBERG
University of Colorado, Boulder
A
wave of corporate restructuring has swept American corporations over
the past decade (Cappelli et al., 1997), reaching almost floodtide levels
after the publication of Hammer and Champy’s (1993) Reengineering the
Corporation. A central aspect of this corporate restructuring has been the
intentional shedding of large numbers of employees in a process that has
come to be known as downsizing (Freeman & Cameron, 1993). The evidence
suggests that this downsizing is affecting large numbers of employees1 (Cappelli et al., 1997) and producing a range of negative attitudinal and behavioral
outcomes.
Authors’ Note: This research is supported by grant No. AA10690-02 from the National Institute of Alcohol Abuse and Alcoholism of the National Institutes of Health.
We would like to thank Sarah Moore, two anonymous reviewers, and the editor for
their helpful comments.
WORK AND OCCUPATIONS, Vol. 27 No. 1, February 2000 7-31
© 2000 Sage Publications, Inc.
7
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WORK AND OCCUPATIONS
It has been suggested, for example, that downsizing is putting into doubt
the unwritten yet implicit psychological contract that underlay the postwar
employment system in large, core firms (Cappelli et al., 1997; Edwards,
1979). The sense of reciprocal obligation, whereby companies rewarded
their employees with long-term job security in exchange for loyalty, commitment, and full work effort, is being replaced by a more fragile and contingent
relationship (Morrison & Robinson, 1997).
Research also indicates that downsizing has had serious adverse consequences for the many working Americans who lost their jobs during these
episodes, with evidence of declining incomes, psychological deterioration,
alcohol abuse, and family tensions (“The Downsizing of America,” 1996;
Kozlowski, Chao, Smith, & Hedlund, 1993). Less is known, however, about
layoff survivors, the vast majority of Americans who, while retaining their
jobs, have found themselves working for companies where substantial layoffs have occurred. In this article, we focus on this somewhat neglected group
of working Americans and examine the effects of their layoff experiences on
their sense of loyalty or commitment to their employer and on their job
performance.
RESEARCH ON LAYOFF SURVIVORS
Recent comprehensive reviews of the literature have found the impact of
layoffs on survivors to have been more negative than positive (Kozlowski et al.,
1993). As expected, survivors tend to be angry; less productive; less trustful
of their work organizations, supervisors, and managers; more anxious about
their jobs and financial futures; less likely to innovate and take risks; and
more likely to suffer from low morale and job dissatisfaction (also see Mone,
1994; Sadri, 1996; Shaw & Barret-Power, 1997; Tombaugh & White, 1990).
They also seem to have more health problems (Kanter, 1997; Vahtera, Kivimaki, & Pentti, 1997).
However, as Brockner and his associates have shown, survivors’ reactions
are not uniform. Employees’ responses to layoffs seem to vary according to
how close the survivors are to those laid off, how they assess the fairness of
the organization’s behavior in the layoff process (Brockner, Grover, Reed,
DeWitt, & O’Malley, 1987), the survivors’ prior level of identification with
the organization (Brockner, Tyler, & Cooper-Schneider, 1992), their level of
self-esteem (Brockner, Davy, & Carter, 1985), and their sense of job insecurity (Brockner, Grover, Reed, & DeWitt, 1992).
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9
Although suggestive, the existing studies on layoff survivors are marked
by several limitations. Many are based, for example, on in-depth interviews
with very small numbers of people in single companies, thus making it hard
to generate systematic, generalizable knowledge (Grunberg, Knudsen, &
Greenberg, 1997; Kets de Vries & Balazs, 1997; Noer, 1993), or on laboratory experiments conducted on undergraduate students, a study population
rather different from the kinds of people and work settings involved in realworld layoffs (Brockner & Greenberg, 1990). The few existing survey-based
investigations are characterized by small sample sizes (Armstrong-Stassen,
1993; Davy, Kinicki, & Scheck, 1991; Mone, 1994; Tombaugh & White,
1990), making it very difficult to specify and test elaborate models. Very few
studies have examined the effects of layoffs on survivors’ job performance,
and those that have have either been conducted in the artificial environment
of the laboratory (Brockner et al., 1987) or have relied solely on self-report
measures (Brockner, Grover, et al., 1992).
Moreover, very little systematic research exists on how layoffs affect different groups of employees across the organizational hierarchy (ArmstrongStassen, 1993). This is particularly germane as recent layoff activity has gone
beyond the traditional blue-collar victims and begun to affect relatively privileged and previously insulated employees such as managers and professionals (Cappelli et al., 1997, pp. 68-69). Whether such relatively privileged
employees react to downsizing episodes by remaining loyal to their companies (Heckscher, 1995) or by feeling a stronger sense of betrayal because
their supposed high level of prior commitment is violated (Brockner, 1992;
Cappelli, 1992) is an important question for the continued viability of traditional models of corporate organization, which depend on bureaucratic control and internal labor markets (Edwards, 1979).
This article aims to build on the existing research on layoff survivors and
to address some of the limitations we have discussed above. In particular, we
wish to examine the effects that two critical conditions of the layoff experience may have on the degree of employees’ commitment to their company.
We ask to what extent employees’ organizational commitment is affected by
differences in their own experiences with layoffs and in their evaluations of
the fairness of their company’s behavior during the layoff process. We ask
further about the extent to which these experiences, perceptions, and attitudes translate into actual behavioral outcomes, such as absenteeism and
lower work effort. These questions are investigated using a large sample of
employees, paying particular attention to the differential experiences of
employees who occupy different positions in the organizational hierarchy.
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WORK AND OCCUPATIONS
ARGUMENT AND HYPOTHESES
ORGANIZATIONAL COMMITMENT
This study assumes that there will be significant variations in how layoffs
are experienced by surviving employees and that these variations will matter
in predicting survivors’ job attitudes and performance. Our fieldwork
revealed considerable variation in survivors’ experiences with layoffs. We
found that some employees had themselves been laid off in the past and then
rehired, whereas others had been put on notice that they were next on the list
to be let go, should additional rounds of layoffs occur. Some had avoided such
direct experiences with layoffs but had witnessed the layoffs of close work
friends or colleagues. A few unfortunate employees had experienced several
of these occurrences, whereas others had experienced none of them. Thus,
the contact with layoffs may be directly personal, as when employees are laid
off and subsequently rehired or receive “warn notices”; or the contact may be
more indirect, as happens when those with social ties to the survivors are laid
off (i.e., close friends or coworkers at the firm). Although any contact with
layoffs is likely to increase survivors’ sense of job insecurity and to decrease
their morale and commitment to their company, we suspect that direct experiences with layoffs are likely to have stronger effects on employees than indirect ones.
Another likely source of variation is how employees evaluate the fairness
or justice of their company’s layoff activity. Research has shown that
employee perceptions concerning procedural justice issues are important
factors influencing employees’ evaluations of their organizations (McFarlin &
Sweeney, 1992; Rousseau & Tijoriwala, 1998). We, therefore, expect those
who perceive the layoff process as having been conducted in an unfair manner to have more negative attitudinal and behavioral reactions than those who
believe the company acted fairly (Brockner, Tyler, et al., 1992). Previous
research and our own fieldwork among layoff survivors indicate that employees attend to two principal factors when assessing the relative fairness of
company behavior during layoffs: first, how fair the company decision
process is in selecting employees for layoffs (decisions based on connections
or friendship were often seen as “political” and unfair); and second, whether
those who were let go were treated well by the company (Brockner & Greenberg, 1990).
We also expect that the employee’s position in the organization will affect
how layoffs shape organizational commitment. Those higher up in the
organization are typically those who are most favored in terms of material
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11
rewards, authority, and autonomy and therefore tend to be the most committed to the organization (Lincoln & Kalleberg, 1990). They are also more
likely to have internalized the goals and values of the company (Edwards,
1979). If, as Brockner, Tyler, et al. (1992) argue, “employees’ attitudes
depend on the relationship between prior belief and subsequent experiences”
(p. 259), then the layoff experience should be most disturbing for those who
had identified most closely with the organization, namely managers and professionals. Similarly, we expect those at the bottom of the organizational
hierarchy, who are typically afforded little autonomy, authority, and trust by
the organization and who receive fewer material rewards, to feel less
“betrayed” or violated by the layoffs and to respond less negatively.
Based on this discussion, we propose the following set of hypotheses,
which address the effect of the two layoff variables on the organizational
commitment of layoff survivors:
Hypothesis 1a: Greater contact with layoffs will be associated with lower levels of
organizational commitment.
Hypothesis 1b: Greater perceived unfairness of layoffs will be associated with
lower levels of organizational commitment.
Hypothesis 1c: Layoff contact will have a stronger negative association with
organizational commitment for managers and professionals than for employees lower down the organizational hierarchy.
Hypothesis 1d: Perceived unfairness will have a stronger negative association with
organizational commitment for managers and professionals than for employees lower down the organizational hierarchy.
In sum, the first two hypotheses claim that layoffs should have a negative
impact on all employees, whereas the second two propose that the negative
effects will be even greater for the employees in the highest positions.
JOB PERFORMANCE
Although there is a growing body of literature on the psychological effects
of layoffs on survivors’ attitudes, there has been very little research on survivors’ job performance. Surveys of companies that have downsized indicate
that, although morale has clearly been harmed, this low morale has rarely
damaged company performance (Greenberg & Canzoneri, 1996). Indeed,
many companies report improvements in productivity (Cappelli et al., 1997).
Cappelli and his colleagues speculate that survivors “cannot act out their
frustration with the break in the psychological contract” (p. 201) because
such behavior is extremely risky in a loose job market. Although there may be
some validity to this argument, we will argue that the impact on individual
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WORK AND OCCUPATIONS
performance will vary depending on the amount of autonomy or power
employees enjoy within the organization as well as on their options in the
labor market (Schellenberg, 1996). In this article, we examine two aspects of
performance over which employees have some control: (a) absences, of
which a significant portion is probably not due to illness but rather is volitional in nature (Hackett, 1989; Hammer & Landau, 1981); and (b) the
employee’s level of work effort (Hodson, 1991).
We argue that both layoff contact and the perceived justice of the company’s behavior during the layoff process will affect these performance measures but that their impact will vary according to the employee’s position in
the organizational hierarchy. Although layoffs may produce a sense that the
psychological contract between employer and employee has been violated
and may generate a desire to restore equity or balance in the relationship
through a decline in individual performance (Adams, 1965), it is important to
remember that this psychological outcome operates within an organizational
structure that provides differential opportunities and constraints for translating psychological states into behavior (Walsh & Tseng, 1998). The most
important structural cleavage, we argue, is the occupational one between
managerial and professional employees (such as accountants, lawyers, and
the like), on one hand, and lower-ranking employees, on the other.
Employees lower down the organizational hierarchy, who tend to have
fewer market options should they be laid off and who tend to be more closely
supervised and monitored, are less likely to engage in risky behavior (such as
absences or reduced work effort), no matter what their feeling is toward the
company (Bowles, Gordon, & Weisskopf, 1983). Indeed, the threat of job
loss, which may become more powerful the more contact employees have
with layoffs, may actually lead to declines in absence behavior and increases
in work effort during and following large-scale layoffs. Such workers have
a strong incentive to keep their heads down and not draw attention to
themselves.
There are several additional reasons why lower level employees may
respond to layoffs with increases in their work performance relative to upper
level employees. For one thing, they are subject to closer supervision and performance measurement so they are less able than others to shirk. They are
also more likely to be uncredentialed, with very job-specific skills, and therefore to have fewer opportunities in the external job market than upper-level
employees. Typically, they also receive less generous severance pay and job
search assistance than upper level employees (Brockner, 1992), increasing
both the expected decrease in income after a layoff and the expected time
spent unemployed.
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13
Finally, we note that the wage premium, that is, the gap between current
wages and those prevailing on the local labor market, paid to production
workers, is higher than the premium paid to upper level workers for this particular firm.2 Therefore, the cost of job loss may be much higher for production workers than for managers and professionals (Bowles et al., 1983).
In contrast to lower level workers, managers and professionals face a different set of opportunities and constraints. Because they are not as closely
monitored, they can respond to company layoffs with greater absences and
lower levels of work effort without drawing attention to themselves or incurring disciplinary sanctions. Furthermore, they may be in a better position
because of their credentials and skills to find other acceptable employment.
We expect, therefore, that position in the organizational hierarchy will moderate the effects of layoff contact on absences and work effort.
Whether organizational position also moderates the effects of layoff fairness on work performance is less clear. Although employees may expect that
improved performance could spare them from being laid-off when the layoff
is seen as having been conducted fairly, there may be less reason to believe
that improvements in individual performance will enable them to escape a
layoff when the layoffs are perceived as having been unfairly or arbitrarily
carried out. Therefore, we expect perceived unfairness to harm performance
across all job categories, but to a greater extent for managers and professionals, as they face fewer constraints in determining their level of work
performance.
Our argument then suggests a second set of hypotheses for job
performance:
Hypothesis 2a: For managerial and professional employees, greater contact with
layoffs will be associated with higher levels of absences.
Hypothesis 2b: For managerial and professional employees, greater contact with
layoffs will be associated with lower levels of work effort.
Hypothesis 2c: For lower level employees, greater contact with layoffs will be
associated with lower levels of absences.
Hypothesis 2d: For lower level employees, greater contact with layoffs will be
associated with higher levels of work effort.
Hypothesis 2e: Across all job categories, greater perceived unfairness of layoffs
will be associated with higher levels of absences.
Hypothesis 2f: Across all job categories, greater perceived unfairness of layoffs
will be associated with lower levels of work effort.
Hypothesis 2g: The magnitude of the effect of perceived unfairness on absences
will be larger for upper level employees than for lower level employees.
Hypothesis 2h: The magnitude of the effect of perceived unfairness on work effort
will be larger for upper level employees than for lower level employees.
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WORK AND OCCUPATIONS
METHODS
STUDY SITE
This study was conducted in a very large manufacturing division of a company on the west coast of the United States.3 At the time of the study (mid1996 to early 1997), the division employed more than 80,000 people who
worked at every level in the job skill hierarchy, ranging from design engineers
to semiskilled assemblers, from managers and lawyers to receptionists. The
division operates in an industry subject to cyclical fluctuations in demand. As
we began our study, the division was just completing a 5-year process of layoffs that had reduced the workforce by 27%. These layoffs coincided with the
strong economic recovery from the 1991 to 1992 recession, both nationally
and regionally, with unemployment in the metro region declining from 7% in
1992 to 3.5% in 1997.
The layoffs were distributed across all job categories (known as pay codes
in the organization) in rough proportion to each pay code’s representation in
the company. For example, the drop in the number of employees between the
peak of the cycle in January 1992 and its trough in January 1996 was 29% for
hourly production workers and 26% for managers. Thus, hourly workers
made up 49% of the labor force in 1992 and 47% in 1996. The proportion of
managers remained constant at 10%. We should also note that the vast majority of the layoffs were involuntary, although some employees did subscribe to
4
a voluntary buy-out program offered by the company. In addition, many
employees who were not laid off received warn notices notifying them that
they might be laid off, should further workforce reductions prove necessary.5
The company undertook the layoffs both as a response to a decline in market demand and in an attempt to restructure the design and production
process. The restructuring program included conversion to a computerized
and streamlined design and parts-ordering system, the introduction of lean
manufacturing modeled on the Toyota system (Womack, Jones, & Roos,
1990), and experiments with cross-functional teams in certain areas and
product lines.
Although the division’s orders were growing rapidly and workers were
being hired in large numbers in early 1997, morale among the workforce was
6
still very low. Many employees believed the company had undertaken
unnecessarily large reductions, despite current profitability, as a way to drive
up the company’s stock price—and hence the value of top management’s
stock options—and as a way to cow the labor force. Even several months into
the recovery and rehiring (early 1997), large numbers of employees (30% to
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15
40% of the sample) reported, in answer to a question on the survey, that they
believed their jobs would be put at risk in the future by various aspects of
restructuring (e.g., lean production, new technologies, or outsourcing).
DATA COLLECTION
Both the company and the two unions, which together represent about
70% of the labor force, cooperated in the study. The company allowed us to
examine important documents and statistical information, giving us access to
key policy makers and to employees, on condition of complete confidentiality. The two unions agreed to let us speak to shop stewards and to advertise in
union newspapers so that we could encourage widespread participation in the
survey.
Data were collected in three forms. First, in-depth interviews and focus
groups were conducted with a randomly selected sample of about 80 employees, representing all job categories and management levels. A key purpose of
these interviews and focus groups was to gain a sense of the range of workplace changes employees and managers had experienced and to assess the
nature of their reactions to the layoffs and to the restructuring program. Second, a variety of data, including number of sick hours used, was collected
7
directly from company records. Finally, a questionnaire was mailed to 3,700
randomly selected and currently employed workers who had worked for the
division for at least 2 years.8 Of these, 2,279 valid questionnaires were
returned, representing a 62% return rate. Respondents were each paid $20 for
participating. Analysis was conducted on those respondents with no missing
values.9
VARIABLES
The measures used in this study are either standard measures from the
social science literature or were developed specifically for this study and pretested on a group of employees. One of the performance measures, sick leave
hours, is taken directly from internal company records.
Layoff contact experience. This additive index is original to this study and
is designed to measure the degree of contact surviving employees have with
layoffs. It is constructed from four questions that probe the details of respondents’ direct and indirect experience with layoffs in their present company.
The questions ask respondents, all of whom were employed by the company
when the survey was conducted, whether they had at any time in the past 5
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WORK AND OCCUPATIONS
years (a) been laid off (and then rehired), (b) received a warn notice that they
might be laid off in the next round of downsizing, or (c) had close friends at
the company and/or (d) coworkers laid off. To take account of the relative
severity of the layoff experience, items are weighted so that the more direct
and close the contact with layoffs was, the greater the weight. We assume that
direct personal contact with layoffs is likely to have more powerful effects on
the survivors’sense of vulnerability to job loss and on any negative emotional
response to the company than witnessing the layoff of a friend or colleague.
We also assume that the emotional effect of the layoff of a close friend will be
stronger than that of a coworker because of the closer social ties and greater
identification that exists with a close friend (Brockner et al., 1987).10 Therefore, having been laid off and rehired is scored as 4, receiving a warning about
a pending layoff is scored as 3, having a friend in the company laid off is
scored as 2, and having a coworker laid off is scored as 1. The resulting index
ranges from 0 to 10.
Sense of layoff justice. Two questions make up this additive index.11 One
asks whether the respondent believes the company acted fairly in selecting
those who were to be let go during the last round of layoffs; the other asks
how well the company treated those who were let go. The measure is coded so
that higher scores reflect greater perceived justice. Alpha for this index = .66.
Position in the organizational hierarchy. Employees in the company are
divided into six pay codes, ranging from managers, professionals, and
administrators at the top, down through engineers, technicians, and general
office staff to hourly production workers. We have divided these six pay
codes into a dichotomous variable based on our own and company insiders’
assessments of the degree of autonomy and power each pay code has within
the company. Managers, along with professionals and administrators, are in
one category because they exercise power over others and/or enjoy wide latitude in deciding how to carry out their work. The other job categories—engineers, technicians, clerical, and hourly production workers—tend to be more
closely supervised and to have less autonomy on the job in this company.12
Layoff Contact · Position in the Organizational Hierarchy. This interaction term allows the relationship between layoff contact and the dependent
variables to differ for each organizational position. Because organizational
position is a dummy variable (1 = manager or professional; 0 = other), the
value of this variable will equal the value of layoff contact for managers and
professionals and will equal 0 for everyone else.
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17
Sense of Layoff Justice ´ Position in the Organizational Hierarchy. As
with the preceding interaction, this variable allows the effect of layoff justice
to differ between the organizational positions.
Organizational commitment. This three-item index measures one central
component of organizational commitment, namely, how attached respondents are to the business enterprise in which they are employed (O’Reilly &
Chatman, 1986). The questions ask respondents to indicate their agreement
or disagreement, using a 5-point Likert-type scale format, with the following
statements: “I feel very little loyalty to this company”; “I am proud to work
for this company”; “I would turn down another job with more pay in order to
stay with this company.” This is a shortened version of the scale used by Lincoln and Kalleberg (1990) and has an alpha of .72.
Individual job performance. We employ both an objective and a selfreport measure to assess the performance effects of the layoff experience.
Sick leave hours is one of the few company-recorded indicators of individual
absenteeism and measures the total number of hours each employee has used
from his or her sick leave account. Because employees across all the pay
codes receive the same 2 weeks of paid sick leave hours per year and because
all employees have a similar incentive to economize on the hours used
(unused sick leave hours are returned to employees in some form of money
payment), variations in the hours used across individuals or pay codes is a
useful indicator of both voluntary and involuntary absences. The measure we
use in the analysis represents the hours used over 30 months prior to the study
(July 1, 1994 to December 31, 1996) and hence captures absence behavior
during and just after the height of the layoff activity.
The second measure is original to this study and asks respondents to estimate the proportion of each day that they work to their full potential (answer
categories include the following: nearly all the time: i.e., 90% or more, most
of the time, i.e., 75% to 90%, some of the time, i.e., 50% to 75%, not much of
the time, i.e., less than 50%). The question taps into another dimension of
performance; namely, the effort employees expend when they are in attendance at work. Of course, the question assumes that technical aspects of work
organization do not severely constrain the ability of employees in different
pay codes to determine their effort levels. Although it is true that some production jobs may provide very little opportunity for individuals to control
their work effort (e.g., assembly line work), in this division there was no moving assembly line. The product moved from station to station, but the flow
was not machine-paced. Similarly, we recognize that effort norms may be the
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WORK AND OCCUPATIONS
result of explicit or implicit collective decisions of teams or groups (Barker,
1993), and this may constrain individual choices regarding work effort.
Although in this division, teams were more prevalent at the higher levels of
the organization, there was absolutely no difference in the average effort levels reported by those in higher and lower level positions (both scoring 2.94 on
the full potential variable). These observations, as well as the feedback we
received in a pretest of the question and the response categories, convinces us
that the question is a reasonably valid indicator of individuals’ perceived
work effort across all positions in the organization.
Control variables. We employ a large number of controls so we can better
assess the independent effects of the two layoff variables. In addition to the
standard background variables of age, gender, time worked at the company,
family income, and whether the respondent is married or living with a partner
and has children under 18 living at home, we also control for a number of
important attitudinal variables that have been linked to organizational commitment, absences, or work effort in the literature. These are job challenge,
job satisfaction, organizational support, work stress, role overload, and the
respondents’ sense of mastery (Brooke & Price, 1989; Lincoln & Kalleberg,
1990; Mayer & Schoorman, 1998; Mowday, Porter, & Steers, 1982). To control for the possibility that organizational restructuring is responsible for
changes in work performance, we include a measure of the total amount of
change an employee has experienced due to reengineering. Finally, to better
assess the effects of the layoff variables on voluntary absence behavior (as
opposed to involuntary absences due to illness), we have added a control for
the number of symptoms of bad health respondents report (see Appendix for
details of the items in the various control measures).
RESULTS
Table 1 provides the ranges, means, and standard deviations for the variables used in the analysis. Table 2 presents the results of ordinary least
squares (OLS) regressions, with commitment and the two performance
measures regressed separately on the control variables and the study variables described in the previous section.
From column 1, we see that the perceived fairness of the layoffs has a
highly significant association with commitment, indicating that the greater
the perception of company fairness by employees, the greater their level of
organizational commitment. The result is consistent with Hypothesis 1b. To
test Hypothesis 1d, the claim that the response of upper level employees to
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Grunberg et al. / SURVIVING LAYOFFS
TABLE 1:
19
Descriptive Statistics of Variables Included in the Regression Analyses
Mean
Range
Organizational commitment
10.04
Sick hours
103.37
Full potential
2.94
Layoff contact
2.51
Layoff justice
3.71
Organizational position
(1 = manager/professional)
0.27
.57
Layoff contact organizational position
Layoff justice organizational position
1.00
Job challenge
10.31
Organizational support
10.35
Mastery
26.24
Role overload
9.41
Age
43.60
Gender (0 = male)
0.24
Tenure with company
14.55
Married/partner
0.77
Children
0.48
Family income
3.73
Stress
10.80
Job satisfaction
11.24
Bad Health Index
1.81
Reengineering change
51.25
3-15
0-624
1-4
0-10
0-6
´
´
0-1
0-10
0-6
3-15
4-20
8-35
3-15
24-93
0-1
0-42
0-1
0-1
1-7
0-18
3-15
0-6
14-70
SD
n
2.50
58.88
0.77
1.90
1.40
2,229
2,262
2,246
2,262
2,130
.45
1.22
1.83
2.67
3.61
4.71
2.63
8.72
0.43
7.17
0.42
0.50
1.55
5.91
2.37
1.24
7.96
2,262
2,262
2,235
2,236
2,241
2,213
2,245
2,248
2,252
2,262
2,225
2,228
2,201
2,172
2,238
2,217
2,119
perceived unfairness will be more negative than the response of lower level
employees, we must examine the value and significance of the coefficient of
the interaction term of perceived fairness and organizational position.13 We
see that the interaction term between perceived fairness and organizational
position is quite small and statistically insignificant, indicating that perceived
fairness has a similar effect on all employees, no matter what their position in
the organization.
Contrary to our expectations specified in Hypotheses 1a and 1c, layoff
contact does not have a significant negative impact on commitment for any
group of employees. Finally, several of the control variables, age, job tenure,
job challenge, and organizational support, have the expected significant
effects on commitment.
In column 2, we see that sick hours are significantly related to layoff contact. The coefficient for layoff contact without the interaction term indicates that higher levels of layoff contact are significantly associated with
reduced sick hours for lower level employees, supporting Hypothesis 2c. The
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WORK AND OCCUPATIONS
TABLE 2:
OLS Regressions for Commitment, Sick Hours, and Full Potential
Dependent Variable
Independent Variable
Layoff contact
Layoff justice
Organizational position
Layoff contact ×
organizational position
Layoff justice ×
organizational position
Organizational commitment
Job challenge
Organizational support
Mastery
Role overload
Age
Gender
Tenure with company
Married/partner
Children
Family Income
Stress
Job satisfaction
Bad Health Index
Reengineering change
Constant
n
R2
(1) Organization
Commitment
(2) Sick
Hours
(3) Full
Potential
0.050 (0.027) –2.144** (0.816) 0.023*
0.242*** (0.041) –2.163
(1.247) 0.006
0.042 (0.360) –27.54* (10.84)
0.036
–0.055 (0.065) 5.366** (1.950) –0.017
(0.010)
(0.016)
(0.138)
(0.025)
–0.015
(0.028)
(0.074)
2.946
(2.228) –0.029
–1.594* (0.776)
–0.653
(0.638)
0.636
(0.506)
0.452
(0.318)
–0.376
(0.635)
–0.564** (0.203)
25.922*** (3.363)
–0.211
(0.245)
5.121
(3.814)
0.781
(3.074)
–4.669*** (1.043)
–0.205
(0.280)
–1.309
(0.861)
4.498*** (1.154)
0.606** (0.200)
2.543*** (0.471) 139.23*** (16.458)
1,951
1,759
0.39
0.10
0.168*** (0.019)
0.288*** (0.015)
0.015 (0.010)
–0.029 (0.018)
0.028*** (0.007)
0.218* (0.109)
0.034*** (0.008)
–0.012 (0.126)
0.035 (0.101)
–.030 (0.035)
†
(0.010)
0.019
0.040*** (0.008)
0.0003 (0.006)
0.017*** (0.004)
0.001
(0.008)
0.007** (0.003)
0.306*** (0.043)
–0.005
(0.003)
0.103* (0.048)
–0.012
(0.039)
–0.036** (0.013)
0.013*** (0.004)
0.037*** (0.011)
–0.017
(0.015)
0.0005 (0.003)
0.958*** (0.209)
1,748
0.14
NOTE: OLS = ordinary least squares.
†p =.051. *p <.05. **p < .01. ***p < .001.
interaction term is also significant, suggesting that managers and professionals differ from other workers in their response to layoff contact. In fact, based
on the equation, we expect that, on average, managers and professionals will
increase their sick time by 3.2 hours for each unit increase in their score on the
index of layoff contact. Computing the standard error from the covariance
matrix (not shown), this value is found to be significantly greater than zero ( p =
0.04). This result supports Hypothesis 2a.
We do not find support for the hypotheses (2e and 2g) that relate layoff
fairness and absences. The coefficient of perceived fairness does not achieve
significance for either set of employees. We do find, however, that employee
commitment is significantly related to sick hours, such that higher commitment is associated with fewer sick hours used. Not surprisingly, the index of
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21
bad health has a significant positive association with sick hours, as does being
female and experiencing a lot of reengineering change.
Column 3 of Table 2 shows the regression for the other performance variable, working at full potential.14 Consistent with Hypothesis 2d, we find that
higher scores on the index of contact with layoffs is associated with a greater
propensity to report working to their full potential for lower level employees.
Unlike the analysis of sick hours, the effect of layoff contact on working at
full potential for upper level employees does not significantly differ from that
for lower level employees. This is shown by the statistical insignificance of the
interaction term. However, the magnitude of the effect, as measured by the
points estimates, is much stronger for lower level employees: The coefficient
of layoff contact for lower level employees is 0.023; for upper level, 0.006 ( =
0.023 – 0.017). But because the estimate of the effect for upper level employees is positive (although small), we do not find support for Hypothesis 2b.
Finally, the relationship between perceived fairness of the layoffs and
working to one’s full potential is small and insignificant for all employees,
rejecting Hypotheses 2f and 2h. Again, as with sick hours, we find that higher
commitment is associated with a greater propensity to work to one’s full
potential.
DISCUSSION
Our purpose in this article was to examine the effects of two important
aspects of layoffs on the organizational commitment and job performance of
a large group of employees in different positions of authority in a large manufacturing company. We find mixed support for the hypotheses relating the
two layoff variables to organizational commitment. Only Hypothesis 1b,
which predicts a negative association between perceptions of layoff unfairness and organizational commitment, is supported. No support is found for
the hypothesized negative association of layoff contact with commitment
(Hypothesis 1a), nor for a differential effect of either layoff variable on the
commitment of managers and professionals in contrast to employees lower
down the organizational hierarchy (Hypotheses 1c and 1d). The result that
perceived layoff unfairness has a strong, significant, and negative impact on
organizational commitment, given the control that is present for other relevant work variables, for example, job challenge and organizational support,
can plausibly be interpreted as supportive of our theoretical proposition—
when workplace norms are violated through what is perceived to be an unjust
layoff process, workers respond by decreasing their commitment to the
organization.
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WORK AND OCCUPATIONS
We suggest two possible explanations for the lack of support for Hypothesis 1d, that managers and professionals would respond more strongly to perceived layoff injustice than lower level employees. One is that norms of justice are equally strong across the organization. Even though organizational
commitment seems to be more essential to obtain adequate performance
from managers and professionals, workers in other positions in the organization can often be as committed to the organization and can respond as
strongly to violations of the norms of workplace justice. In addition, at certain critical times, such as when companies engage in large-scale layoffs, all
workers, regardless of their organizational position, may be reminded that
they are vulnerable to someone else’s decision.
Perhaps for similar reasons, we did not find support for the claim that layoff contact would be associated with reduced employee commitment to the
organization (Hypothesis 1a). Layoff contact, controlling for the perceived
fairness of the layoff, may not diminish commitment because workers may
expect such behavior in the modern economy. In response to the recent widespread and continuous downsizing and restructuring activity, workers may
have learned to regard layoffs as a normal element of a competitive marketplace and thus no longer see them as violating the implicit reciprocal obligations of the psychological contract. Indeed, the postwar contract may no
longer be shaping many employees’ expectations. However, the perception
of the justice of the layoff is not dictated by competitive marketplace pressures, and employees seem unwilling to commit to the organization when it
appears to be acting unfairly.
The fact that employees in all occupational groups in the organization
respond strongly to normative violations would explain the unexpected statistical insignificance of the interaction term for layoff contact and employee
position in the organization. We believed that managers and professionals
would have a more negative response to layoff contact. It seems that many
employees at this level of the organization also have learned to accept downsizing as an inescapable fact, controlling for the manner in which it was conducted. Heckscher (1995) found such a result for middle managers, who
reported that they believed downsizing to be necessary and did not reduce
their loyalty to the firm in its wake.
Turning to the effects of the two layoff variables on work performance, we
again find mixed support for our hypotheses. Whereas the perceived fairness
of the layoff seems to affect employee commitment, the degree of contact
with layoffs seems to matter in the case of employee job performance. As
hypothesized (2a and 2c), we find that the work performance of employees
does not respond uniformly to contact with layoffs. For employees in engineering, technical, clerical, and production positions in the organization,
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greater layoff contact is associated with lower use of sick hours. On the other
hand, for managers and professionals, greater contact with layoffs tends to be
associated with higher use of sick hours. This result is significant, even with a
large number of controls entered for other variables that might influence
absences. Indeed, the inclusion of the symptoms of poor health variable as a
control increases the likelihood that the sick hours that are being predicted
are not primarily due to ill health (including ill health that might have been
15
caused by the stresses associated with layoffs). It should also be remembered that all employees are allocated an equal number of sick hours and have
similar financial incentives to economize on their use.
So what explains the divergent behavior of these two groups of employees? As we have argued, we suspect that the behavior of lower level employees may represent a rational response to their perceived threat of job loss.
With less authority and autonomy in the organization than managers and professionals, and with fewer options in the job market, these workers may seek
to change their behavior (for example, by reducing their absences) so as to
minimize their chances of being selected for layoffs in any future rounds of
downsizing. This interpretation gains some support from the findings in a
recent longitudinal study of the effects of downsizing on absenteeism.
Whereas downsizing increased the rate of medically certified long-term sick
leave, it reduced short-term absences not related to ill health (Vahtera et al.,
1997). Similarly, our findings that lower level employees with the greatest
contact with layoffs report that they are more likely to work to their full
potential throughout the day bolster this interpretation.
The behavior of managers and professionals who have had the greatest
contact with layoffs (higher absences but no noticeable effect on their selfreported work effort) does not seem to indicate a retributive or hostile reaction. If that were the case, as we hypothesized, then we should see particularly steep declines in their levels of organizational commitment and in their
self-reported levels of work effort. Neither is evident. This suggests that the
greater use of sick hours by managers and professionals may be due to jobsearch behavior. We speculate that such employees, when they see impending layoffs, use the greater freedom from supervision their positions provide
and the marketability of their skills to begin to absent themselves from work
in the search for alternative employment (Drago & Wooden, 1992; Mowday
et al., 1982, p. 91). This interpretation was supported by several managers at
16
the company who were asked to comment on the findings.
Employees’ perceptions of the fairness of the layoffs has no direct or main
effect on either of the performance measures, nor do we find an interaction
effect with the employees’ position in the organization. Whatever effect layoff fairness has on performance is mediated through the effect on
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WORK AND OCCUPATIONS
organizational commitment and is similar for all job categories in the organizations. Perceptions of unfairness are associated with lower organizational
commitment, and lower commitment is associated with increased absences
and reduced work effort. It appears, therefore, that layoffs can affect survivors’ individual job performance in two ways. Contact with layoffs seems to
improve lower level employees’ work performance, at least in the short run,
whereas it seems to have either little or a negative effect on higher level
employees. Perceptions of layoff unfairness worsen employee performance
by lowering commitment across all positions in the organization.
CONCLUSION
Although our study has sought to address some of the weaknesses of previous research in this area, it is still marked by several limitations. First, even
though the sample was large and occupationally heterogeneous, our results
are based on a sample of employees in only one company, and therefore the
question of generalizability is raised. We make no definitive claims about the
effects of layoffs on survivors across the whole U.S. economy. We believe,
however, that what is going on in this firm in terms of outsourcing, downsizing, digitalization of design and manufacturing, and lean production is fairly
typical of what is going on in large manufacturing firms across the country
and that our findings may be cautiously extended to this economic sector.
Whether this is a valid assumption must, however, await further research on
other companies in other industries.
Second, it is possible that some of the reported relationships may be bidirectional, or the product of third unmeasured variables. For example, organizational commitment may influence perceptions of unfairness, and the relationship between commitment and work effort may be the result of a general
positive effect. Similarly, job performance may have influenced who was
selected for layoffs, with work sections with the worst performance singled
out for the most layoffs. Although it is plausible to argue that there was such a
selection process at work for those who received warn notices, or even perhaps for those who had close colleagues laid off, it is highly unlikely that the
company selected layoff victims based on their friends’ level of organizational commitment and job performance. So although we recognize that only
longitudinal studies with baseline data can definitively untangle issues of
causality, we nevertheless believe that our interpretation—that it is the layoff
experiences that produced the effects—is valid.
A third limitation concerns our measure of layoff contact, which does not
include organizations that experienced no layoffs and therefore does not have
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the total possible variation in the condition. Even those individuals who
scored zero on our measure were almost certainly aware that the organization
was laying off large numbers of employees and thus were somewhat affected
by the experience. Studies that use a quasi-experimental longitudinal design
or that include organizations with no or very few layoffs are necessary to provide a complete determination of the effects of layoff contact. However, we
should note that such firms are increasingly hard to find in the manufacturing
sector of the economy, as even nonunion companies, such as IBM, Kodak,
and Sears, which had never previously experienced large-scale layoffs, have
downsized (Jacoby, 1998).
Despite these limitations, this study reinforces the prevalent notion in the
literature that downsizing and large-scale layoffs have important effects on
surviving employees. Moreover, the effects are evident a full 2 years after the
last major round of layoffs, at a time when the company was undergoing rapid
growth in sales and employment. And, even as downsizing and layoffs have
become routine practices in large companies and, therefore, are no longer
seen as serious violations of an implicit postwar contract, our findings suggest that employees’ sense of commitment may still be strongly affected by
how the layoffs are carried out and by how those who are laid off are treated.
Indeed, this new climate of job uncertainty has led some commentators to
predict the emergence of a new kind of work commitment, one tied to a “mission or task rather than to a company” (Heckscher, 1995). The archetypal
employee will have to become “flexible” and “emotionally detached”
(Rudolph, 1998). Whether such a psychological shift is occurring is unclear
at present. Future researchers might want to explore more systematically
whether such contingent attachments are emerging and what their consequences are for employees and the companies that employ them (McGovern,
Hope-Hailey, & Stiles, 1998).
The results also shed light on the somewhat puzzling observation of low
employee morale coexisting with solid or at worst mixed work performance
in downsizing companies (Cappelli et al., 1997). As we have seen, not all
employees face the same set of constraints and opportunities in selecting
their behavioral responses. Lower level employees may feel levels of anger or
demoralization similar to those in more privileged positions in the wake of
layoffs; however, with less power and fewer options, they may have to swallow hard and toe the line. However, it is doubtful whether such a basis for
worker effort augurs well for the long-term performance of America’s large
firms.
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APPENDIX:
Control Variable
Variable (source)
Question
Age
How old were you on your last birthday (in years)?
Children
Do any children under the age of 18 live with you in your
home? (Yes/No)
Gender
Are you male ( = 0) or female ( = 1)?
Married/partner
What is your marital status? (1 = married or living with partner, 0 = other)
Job tenure
How long have you worked at the company (in years)?
Index of Job Challenge
Sum of three items: On my job I seldom get a chance to use
my special skills and abilities (reverse coded); Success on
my job requires all my skill and ability; My job is very challenging. 5-point Likert-type response categories from
strongly disagree (SD) to strongly agree (SA). Alpha = .74
Index of General Job
Satisfaction (Camman,
Fichman, Jenkins, &
Klesh, 1983)
Sum of three items: All in all, I am very satisfied with my job;
In general I don’t like my job (reverse coded); In general I
like working here. 5-point Likert-type responses from SD
to SA. Alpha = .86
Mastery Scale (Pearlin &
Schooler, 1978)
Sum of seven items: I have little control over the things that
happen to me; There is really no way I can solve some of
the problems that I have; There is little I can do to change
many of the important things in life; I often feel helpless
dealing with the problems of life; Sometimes I feel I’m being pushed around in life (all five previous items are reverse coded); What happens to me in the future mostly
depends on me; I can do just about anything I really set my
mind to do. 5-point Likert-type responses from SD to SA.
Alpha = .82
Index of Poor Health
Sum of five items asking respondents if they had experienced (Yes/No) any of the following in the last year: back
pain, ulcers, indigestion, high blood pressure, heart problems.
Index of Perceived
Organizational Support
(Eisenberger, Huntington, Hutchinson, &
Sowa1986)
Sum of four items: The company appreciates extra effort
from me; The company really cares about my well-being;
If I did the best job possible, the company would be sure to
notice; The company cares about my opinions. 5-point
Likert-type response categories from SD to SA. Alpha =
.88
Index of Work Overload
(Camman et al., 1983)
Sum of three items: I never seem to have enough time to get
everything done; I have too much work to do everything
well; The amount of work I am asked to do is fair (reverse
coded). 5-point Likert-type responses from SD to SA.
Alpha = .76
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27
APPENDIX Continued
Variable (source)
Question
Index of Stress in
General (Smith
et al., 1992)
Respondents were asked: Think of your job in general. All in
all, what is it like most of the time: pressured, hassled,
pushed, many things stressful, relaxed (reverse coded).
Response categories to the six items were Yes, it describes my
job;No, it doesn’t describe my job;I can’t decide.Alpha = .82
Family income
Measured as 1 = less than $35,000; 2 = $35,000 to $49,999;
3 = $50,000 to $64,999; 4 = $65,000 to $79,999; 5 =
$80,000 to $94,999; 6 = $95,000 to $109,999, 7 = Over
$110,000
Index of Amount of
Reengineering change
Respondent was given a general question, To what extent
have you been expected to do the following things in your
work over the past 2 years? The index is the sum of the
Likert responses (much less to much more) for 14 aspects
of work: To use your skills in new ways, To learn to use new
technology, To work on new problems and tasks you haven’t done before, To upgrade your skills and training just
to stay even, To work with less supervision, To take on
more responsibility for setting work goals, To work with
people in different job categories than your own, To work
on teams, To work longer hours, To add tasks done by others in the past to your own normal responsibilities, To attend more meetings, To adopt a new organizational philosophy, To learn to use computers, To learn new software
programs. Alpha = .86
NOTES
1. As late as 1996, even as the U.S. economy was in its fifth year of expansion, the American Management Association reported that job elimination continued at a pace similar to that
during the early 1990s, with half of the responding firms (1,441 major U.S. firms participated in
the survey) reporting job cuts and about one third engaging concurrently in hiring and firing
(Greenberg & Canzoneri, 1996).
2. Indirect evidence is supportive of our contention. Company and union officials agree
that production workers are paid a generous premium over prevailing wages in the local labor
market, an observation confirmed by a comparison of state-gathered earnings data with the income data in our survey. In contrast, a comparison of the salary of recent MBAs at the leading
business school in the area with those of recent MBA hires at the company suggests that upperlevel workers at this company are paid below the prevailing local average salary.
3. Because we do not approach this study as a case study and because of confidentiality
agreements with the study company, we do not provide rich contextual detail, although we provide enough, we believe, to set our methods and findings in scientific context. Our main concern
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WORK AND OCCUPATIONS
in this study is not this case, moreover, but the relationship among a range of variables about jobs
and the workplace. And, because the study is being conducted in a very large company with several production sites, a wide range of technologies and occupations, many supervisory styles,
and a variety of forms of production organization, we are confident that wide variation exists on
all of our principle variables. Thus, what we lose in broad generalizability, we believe, is compensated for by our ability to examine rich and complex relationships, with, as we have said,
some confidence that our findings can be cautiously generalized to large American manufacturing firms.
4. See Cornfield (1983) for an analysis of the factors that influence the probability of voluntary and involuntary layoffs across different occupational groups. In contrast to the case reported here, Cornfield found variations in the rates of layoffs across occupational groups.
5. Large companies are required, by law, to give at least 60 days notice to employees targeted for layoffs (known as warn notices in this company). Managers admitted they handed out
many more warn notices than were actually activated, thus damaging employee morale more
than necessary.
6. This assessment is supported by comments from managers and union leaders, as well as
by the many employees we interviewed. Evidence from internal company surveys and our survey also confirms this state of low morale.
7. About three fourths of the items in the questionnaire are validated items used by other researchers or by us in the past and are widely discussed in the research literature. The remainder
are items specific to this study, formulated after interviews and focus group sessions with employees. A preliminary version of the questionnaire was pretested on a sample of 104 employees
from one work sector of the larger company. A focus group, organized from among employees
who had participated in the pretest, helped analyze the questionnaire.
8. This was done to exclude new hires who had not experienced the downsizing phase.
9. To assess possible bias due to missing values, missing cases were compared to the cases
included in the regression. The two groups did not differ significantly, and in fact were nearly
equal on a large number of variables, including demographic, job attitude, and performance
measures. We also compared the sample to the division’s workforce on average age and tenure in
the company and on racial and gender composition, finding no significant differences between
the two groups. Specific results are available from the authors.
10. Some support for these assumptions is provided by comparing the scores of survivors
who had experienced any one of these four kinds of contact with layoffs. Those with direct personal experiences reported greater job insecurity than respondents with indirect experiences.
Similarly, survivors who had seen friends laid off reported feeling less trust in top management
than those who had witnessed the layoff of coworkers.
11. The questions included the following: (a) During the last major round of layoffs, how
fair was the procedure that the company used to select those who were let go? (b) During the last
major round of layoffs, how well did the company treat those who were let go? Answer categories were very well, well, not very well, and not well at all.
12. Although we recognize that engineers occupy an ambiguous position in any organizational hierarchy because they are both highly skilled employees and yet subject to monitoring
and supervision, we believe there are two good reasons why engineers can validly be distinguished from managers and professionals and placed with hourly, clerical, and technical employees. First, all the engineers are represented collectively by an association that acts like a union in all negotiations with the company. Their wages and benefits are therefore determined
through collective bargaining with the company, unlike those of managers and professionals.
Second, they report considerably less decision-making authority in the functioning of teams than
do managers and professionals in similar situations. Still, given the ambiguous position of engi-
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29
neers, we reran the three regressions excluding the engineers. Results for the organizational
commitment and the sick hours variables were essentially unchanged except that commitment
no longer had a significant effect on sick hours, whereas layoff justice reduced sick hours used.
The equation for work effort was somewhat different, with layoff contact now having no effect
and the significance of the commitment variable becoming borderline ( p < .10).
13. The beta coefficient for upper-level employees is obtained by summing the coefficient
of perceived fairness with the coefficient of the interaction term. The variances and covariance of
these latter coefficients are used to obtain the standard error of the coefficient for the upper-level
employees.
14. As a reviewer noted, full potential might be better modeled using an ordered logit rather
than an OLS regression. Following this approach, the results were essentially unchanged compared to those presented in Table 2; that is, increasing layoff contact is associated with increasing
work to full potential for lower-level employees. We provide the OLS results instead of the ordered logit because they are more widely understood and easier to interpret. The ordered logit results are available from the authors.
15. Of course, it is certainly possible that close contact with layoffs increases the incidences
of health problems in survivors in all occupational groups (Grunberg, Moore, & Greenberg,
1999). What we are suggesting is that, regardless of the possible reasons for the absences, managers and professionals find it less difficult to absent themselves from work.
16. A reviewer suggested that this interpretation would be strengthened if warn notices,
rather than layoff contact, were a predictor of sick hours for managers but not other employees.
Additional regression analysis (available from the authors) did find that warn notices have a significant positive association with sick hours for managers. The association with other employees
was negative but failed to reach significance.
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