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Abstract Number: 003-0121
Title: Gender Differences in Lean Production Job Stress
Conference: Sixteenth Annual Conference of POMS, Chicago, IL, April 29 - May 2, 2005.
Authors:Jannis Angelis Templeton CollegeUniversity of OxfordOxford OX1 5NY, UK(E): [email protected]. (F): +44 1865 422501. (T): +44 1865 422576.
Robert ContiBryant UniversitySmithfield, RI 02917, USA(E): [email protected]. (F): 401 232 6319. (T): 401 232 6462.
Cary CooperLancaster University Management SchoolLancaster, LA1 4YX, UK (E): [email protected]. (F): +44 1524 594720. (T): +44 1524 594326.
Brian FaragherSchool of Management, UMISTManchester, UK(E): [email protected]. (F): +44 161 200 3505. (T): +44 161 236 3311.
Colin GillInstitute for ManufacturingUniversity of CambridgeCambridge CB2 1RX, UK(E): [email protected]. (F): +44 1223 338177. (T): +44 1223 338776.
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ABSTRACT
A large scale earlier study, funded by the British Engineering and Physical Sciences Research
Council (EPSRC), investigated the relationships between worker job stress and the conditions
that workers were exposed to – a set of twenty lean production work practices and the degree of
lean implementation. Statistical analysis revealed significant associations between job stress and
eleven of the work practices. An unexpected non-linear, convex relationship between job stress
and the level of implementation was identified. A total of 1,391 workers responded to our survey
– 1,063 men and 328 women. The total sample was split by gender and the statistical analyses
repeated for men and women. There were significant gender differences in the stress responses to
both work practices and the level of lean implementation. These differences are discussed in the
context of relevant gender behavioural research.
Introduction
The roots of Lean Production (LP) are in the Toyota Production System (TPS) of post World War
II Japan (Ohno, 1988). It has diffused worldwide, initially as Just-in-Time production (JIT),
arguably becoming the global competitive standard for products assembled from discrete parts.
TPS diffusion was aided by the International Motor Vehicle Project (IMVP), which coined the
term ‘Lean Production’ to characterise the evolved version of JIT (Womack et al., 1990:48).
Lean production has exhibited the potential to simultaneously reduce costs and improve quality.
The IMVP results revealed that, on average, cars produced in lean plants required one-third fewer
hours and had one-third fewer defects than those built using traditional mass production. These
favourable results are countered by evidence that lean production can generate high levels of job
stress (Lewchuck et al., 2001; Bruno and Jordan 2002), raising the question: “Is lean production
deterministically stressful, with benefits gained at the expense of workers?”. Our earlier study
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(Conti et al., 2004) answers with a qualified “No”. Stress levels are heavily dependent on
management choices of lean production policies and practices. A synopsis of the study is given in
Appendix A and full coverage is provided in the Conti et al. (2004) working paper. The study
results provide guidance for designing and operating effective lean systems that control job
stress. Recommended practices are summarised in Appendix A.
The large data base of our earlier study offered the opportunity for added insights into lean
production stress – specifically the nature of gender-based differences in stress responses. Our
sample was split into 1,063 males and 328 females and the statistical analyses repeated. Patterns
of differences in the stress responses of the two samples are identified and analysed.
Work Practice Regression Results
Table 1 summarises three sets of hypothesis test regression results: all workers (our earlier study),
male respondents and female respondents. The twenty work practice hypotheses were tested
using stepwise regression. For all workers, eleven of the hypotheses, highlighted in bold, were
supported at significance levels of p<.05. The pattern of significant practices for males and
females reveals several differences and some overlap. Three practices are significant for both
genders: pace/intensity, doing the work of absent workers, and ergonomic difficulties. Five are
significant only for males: long hours, low cycle time, feeling of blame for defects, team working
and control of pace and three only for females: (resource removal, lack of tools and job rotation).
TABLE 1 Hypothesis Test Regression ResultsAll Workers Male Workers Female Workers
n=1391 n=1063 n=328Hypothesis Predictor Std Beta Sig. Std Beta Sig. Std Beta Sig.
1 Work Pace 0.143 (.000) * 0.146 (.000) * 0.179 (.001) *2 Resource Removal 0.065 (.009) * 0.021 (.459) 0.131 (.010) *3 Long Hours 0.163 (.000) * 0.205 (.000) * 0.085 (.104)
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4 Low Cycle Time 0.079 (.002) * 0.062 (.037) * 0.009 (.866)5 Use of Buffers 0.003 (.901) 0.004 (.876) -0.013 (.805)6 Do Work of Absentees 0.08 (.002) * 0.067 (.021) * 0.106 (.042) *7 Feeling Blamed for Defects 0.142 (.000) * 0.148 (.000) * 0.085 (.113)8 Individual Output Display 0.009 (.700) -0.002 (.943) 0.026 (.588)9 Ergonomic Difficulties 0.147 (.000) * 0.155 (.000) * 0.119 (.032) *10 Working in Teams -0.089 (.000) * -0.119 (.000) * 0.014 (.778)11 Task Support -0.068 (.005) * -0.073 (.009) * -0.081 (.106)12 Parts Fit Difficulties -0.004 (.887) -0.02 (.483) 0.046 (.374)13 Work Flow Interruptions 0.008 (.768) 0.041 (.160) -0.026 (.618)14 Lack of Training -0.028 (.224) -0.042 (.117) -0.015 (.759)15 Lack of Proper Tools 0.065 (.010) * 0.03 (.286) 0.181 (.001) *16 Control of Work Pace -0.028 (.281) -0.065 (.036) * 0.025 (.618)17 Autonomy for Changes -0.032 (.182) -0.034 (.207) 0.016 (.748)18 Commenting on Changes -0.018 (.455) -0.009 (.745) -0.043 (.384)
19Continuous Improvement Participation -0.062 (.009) * -0.038 (.169) -0.081 (.103)
20 Job Rotation -0.006 (.816) 0.105 (.587) -0.11 (.032) ** Significant at p < 0.05 Adj R Sq = .300 Adj R Sq = .353 Adj R Sq = .358
Gender Behavioural Differences
Jick and Mitz (1985) reviewed 19 gender work stress studies. The studies employed three
explanations for sex differences in stress symptoms: genetic/biological differences (inborn
tendencies), structural differences (different working conditions and hence different stressors),
and social/psychological differences (differing cognitive appraisals of stressors and coping
strategies). They conclude that “The explanatory power of genetic factors, as such, is seen to be
weak and inadequate to explain the sex differences in level and type of distress”. This is
consistent with the emphasis of the literature on structural and social/psychological effects.
Gender-specific work practice stressors are discussed next, with the hypothesis number, practice
description, beta coefficient and significance level shown for each.
Work Practice Stressors Significant Only for Males
H3: Job stress is positively associated with working longer hours than desired (Beta 0.205,
p<.001). This result is unexpected since women tend to experience greater “dual role conflict”
time pressures of meeting both job and family demands – a burden made more difficult by long
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work hours. (Lowe and Northcutt, 1988). Two factors may explain the lower sensitivity to work
hours exhibited by our female respondents: research showing the benefits of work to family
women and structural gender differences in work assignments at our sites.
Positive work effects can reduce the stress of working long hours. Cleveland et al. (2000:333),
commenting on work-family conflict, point out that “work can have a number of beneficial
effects for women, including increased decision-making within the marriage, increased sense of
competence and increased family living standards”. Similar findings are reported by Barnett and
Baruch (1985). While acknowledging the dual role conflict, they conclude “In general, however,
women’s work roles appear to have positive effects on women’s psychological and physical well-
being. Non-employed wives and mothers experience more anxiety when they feel stress in family
situations than do wives and mothers who are employed”. Similarly, Russo (1990:52) reports that
“Compared with housewives, working married women with lower incomes appear to be more
affected by stress caused by child rearing but less affected by other life events. It may be that
employment provides a buffer for other types of stress”.
Favourable effects of work for women are reported in a 2002 Gallup poll (Robinson: 2002):
“Presumably, because a majority of mothers work, one would think that fewer women would be
completely satisfied with the flexibility of their hours”. However, “By a 68% to 58% margin,
women are more likely to say they are completely satisfied with the flexibility of their hours”.
Also, a study of 966 Canadians workers by Roxburgh (1996) showed that, compared to men,
“Women are more adversely affected by high job routinisation and less adversely affected by
working hours”.
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While favourable effects of working for some women may help to explain our female response,
they do not explain the male response. It may be due to the nature of lean production and the
much higher percentage of men on assembly lines at our sites (26.2% of men versus 9.5% of
women). Lean assembly lines employ constant rate continuous work flow. The output of a
constant rate system is most efficiently increased by working more hours at that rate – using
overtime. Males reported significantly higher overtime (t=3.60, p<.001), working 5 to 7
additional hours a week compared to 2 to 4 hours for women. The much lower female overtime
may also be due to managers recognising the stressful nature of dual roles for many women. This
may lead them to favour males for overtime assignments and be more willing to excuse women
from their overtime assignments. There is another possible contributor to the response of males,
linked to their role as family providers. (Agassi, 1979). In the WERS98 study of workplace
industrial relations in Britain. 62% of surveyed assemblers reported that they worked overtime
primarily for the money. (Cully et al., 1999:157). A significantly higher percentage of male
workers gave this reason than did females, consistent with their ‘breadwinner’ roles. A conflict
between the desirable income of overtime and the undesirable decreased control over their
personal time may contribute to the male response.
H4: Job stress is positively associated with decreasing cycle times (Beta 0.062, p=0.037). Cycle
time is the elapsed time at a work station for completing one set of assigned tasks. It is inversely
proportional to the degree of task repetition. Highly repetitive work has been shown to be
associated with high stress. (Smith, 1985:60). However, the higher sensitivity of male
respondents to short cycles is unexpected since research shows that women tend to be more
affected by repetitive work, or ‘routinisation’. Roxburgh (1996) reports that in a sample of 966
Canadian workers, “Results show that, controlling for exposure, marital status and income,
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women are more vulnerable to the negative effects of routinisation”. The unexpected response
may have a structural cause – the much higher percentage of males assigned to assembly lines.
Each cycle presents the stressful danger of a worker stopping the line because of a defect. Shorter
cycles result in higher frequencies of exposure to this danger. Also, spatial constraints make
assembly line workers less able to receive task help from co-workers than those in work cells.
These factors may result in the higher male sensitivity to short cycle times.
H7: Job stress is positively associated with a feeling of being blamed for defects (Beta 0.148,
p<.001). This feeling is a significant stressor, with the largest uniquely male beta coefficient.
‘Quality at the source’ is widely practiced in lean production. Workers are responsible for
inspecting the work of prior assemblers as well as their own. If a defect is discovered a signal is
often activated and the line stopped until the cause is corrected. Delbridge and Turnbull (1992)
suggest that this interdependent flow, with the ability to trace a defect to a specific individual,
creates a “blame culture”. The responses to this culture can be linked to gender traits of ‘locus of
control’ and primary life roles; as well as differences in work assignments.
Terborg (1985:255) describes the locus of control: “People who believe they are primarily
responsible for what happens to them and who believe in personal power and control are said to
have an internal locus of control. In contrast, people who believe that their actions have little
impact on what happens to them and who attribute outcomes to outside causes are said to have an
external locus of control. There is a tendency for women to be more external than men, sensing
that they have little or no control over what happens to them and attributing events to luck more
frequently than men”. This may cause greater feelings by males of being responsible for defects
and being blamed for them. Kenrich and Trost (1993) describe cross-cultural gender
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consistencies relevant to the blame response: “On average, women are less aggressive, less
concerned about position in social dominance hierarchy – while men are more aggressive and
competitive”. The male concern for job performance and success on the job can make men more
sensitive to being linked to negative work outcomes such as defects – even without any overt
fault-finding or blame by supervisors. This concern is consistent with the male view of being
primarily a provider (Agassi, 1979; Cleveland et al., 2000).
H10: Job stress will be negatively associated with the opportunity for team working (Beta -0.119,
p<.001), and H11: Job stress will be negatively associated with support from peers and
supervisors in meeting time and quality standards (Beta -0.073, p=0.009). These work practices
are analysed together because team working and task support are correlated (r=0.113, p<.001).
Our gender team assignments were roughly comparable (45.7% of females and 41.1% of males),
so stress response differences are likely due to social/psychological rather than structural factors.
Male support for the two hypotheses is consistent with several research studies. Vannanen (2003)
found that sickness absence (an outcome of job stress) in a sample of 3,895 industrial workers in
Finland was positively associated with a lack of co-worker support for men, but not for women.
Morrison and Payne (2003), in a review of 64 job stress studies, conclude that “In the few studies
examining the moderating effect of social support on the impact of high strain, supportive results
are restricted to males”. Muhonen and Torkelson (2003), in a study of the validity of the demand-
control-support stress model for Swedish telecom workers, concluded that “Only demands
predicted women’s health, while both demands and support predicted men’s health”.
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Team working involves a stress trade off. Task support has the favourable effect of reducing job
demands. However, teams bring with them increased interpersonal conflict. Russo (1990:48)
reports that “women appear to have a greater vulnerability to stress arising from interpersonal
problems”. This is supported by Agassi’s (1979:65) study of needles trade workers in the US,
Germany and Israel. He found that the two top priorities in desirable jobs for men are ‘high pay’
and ‘interesting work’, while women favour ‘friendly management’ and ‘friendly co-workers’.
Similar results are reported in Health and Medicine Week. (Peterson, 2004). In a sample of 1100
workers from large US corporations, men valued ’pay and benefits’ most highly as compared to
‘friends and relationships at work’ for women. Also Bellman et al. (2003), in an Australian study,
found that “women are more likely to experience stress from organisational politics than men” –
an indication of greater sensitivity to interpersonal conflict. Fondas (1997), in a review of
contemporary gender writings, describes the qualities that researchers associate with females,
including “orientations towards integrative goals such as group cohesiveness and stability; and
interpersonal sensitivity”. Further empirical support is provided by Melin et al. (1999) in
comparing the responses of engine assemblers to two forms of work: traditional assembly line
and small autonomous teams. There were significantly lower irritation levels for assembly line
workers than for the flexible team members. The authors speculate that “A possible explanation
for this might be that this (flexible) type of organisation puts more social pressure on the
individuals within a team, i.e. a greater need for social skill and coping strategies in making
group decisions”. The greater sensitivity of women to interpersonal conflict in teams may explain
their responses to this form of working.
Despite the interpersonal conflicts, their greater emphasis on job performance apparently makes
males react favourably to teams. Agassi (1979:3) found that “Men’s adaptations to inferior or
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alienating jobs does not damage them psychologically as long as their family role is not called
into doubt – the role, that is, of provider or main breadwinner for their families”. Peterson
(1991:174) similarly observes “As the male role is very important to identity, men may ignore
some of the stressful implications of factory work”, while Fondas (1997) describes the male trait
of “a capacity to ignore personal, emotional considerations in order to succeed”.
H16: Job stress is negatively associated with the degree of control over work pace (Beta -0.065,
p=0.036). This hypothesis was rejected in the total sample (Beta -0.028, p = 0.281), due to the
very low utility of pace control for females. In contrast, male workers respond favourably to this
control, consistent with the male characteristics described by Fondas (1997), including “an
interest in taking charge, control and domination”. The greater desire of males to control their
environment would include controlling the rate at which they perform work tasks.
Work Practice Stressors Significant Only For Women
H2: Job stress is positively associated with the frequency of resource removal (Beta 0.131,
p=.010). Some lean production systems remove workers from smoothly operating cells or lines,
to highlight improvement opportunities. This can be stressful for the remaining workers who
must work faster to maintain the same output until improvements are made. After improvements
are made, and a new equilibrium reached, the procedure is repeated, in what has been described
as ‘improvement by stress’.
The faster work pace for remaining workers increases job demands, which are more stressful for
women than men. (Muholen and Torkelson, 2003; Roxburgh, 1996). Also social relationships are
disturbed when workers are removed from the line and tasks are reassigned. This more adversely
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affects females with their greater need to converse and socialise with co-workers in stable work
groups. (Bellman et al., 2003; Cox and Mackay, 1979; Fondas, 1997). Another contributor may
be the greater importance of management behaviour for women. As discussed previously, women
rank ‘friendly management’ as the most important characteristic of a good job. (Agassi, 1979). A
study of 2000 Swedish workers found that the long-term health of women, measured by
absenteeism, was more affected by ‘support from the chief’ than was the health of men.
(Aronsson and Lindh, 2004). Removing workers may be seen by women as an unfair and
‘unfriendly’ management action and a lack of management support - stressful for the affected
female workers.
H15 Job stress will be positively associated with a lack of proper tools (Beta 0.181, p=.001). This
stressful response is consistent with the observations of researchers on shortcomings in the design
of production tools and equipment. Terborg (1985:274) concludes that “Physical demands and
unfamiliarity with tools and equipment make high performance in blue collar jobs more difficult
for women than for men” and “Many blue collar work settings were not designed for women”.
The deficiencies include problems with work bench heights and required reaches. Similarly,
Peterson (1999:205), citing a study of an Australian manufacturing firm, reports that women
were more likely to suffer from musculoskeletal disorders than men, “including pains and injuries
of the spine, back and neck pain. Where lifting is involved, awkward movements can result from
workplace design and workflow requirements”. Nelson et al. (2002:232) state that “In the blue
collar world, the equipment used and the industrial processes employed were designed around
men’s bodies”.
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The much lower percentage of women assigned to assembly lines may also be a contributor. The
level of capital investment and ergonomic support provided on the assembly lines at the survey
sites was much greater and more sophisticated than that employed in the sub assembly and bench
assembly areas manned primarily by females. Gender shortcomings in job and process design are
exacerbated by societal differences that make males more familiar with tools and their uses from
an early age - differences often reinforced in school when boys take shop courses and girls study
cooking.
H20 Job stress will be negatively associated with the frequency of job rotation (Beta –0.11,
p=.032). Female workers responded favourably to job rotation – being assigned to a set of
different jobs on a regular schedule. Job rotation is used to maintain a flexible, trained work force
and prevent repetitive motion injuries. Unlike team task sharing, job rotation tends to involve a
variety of individual tasks. This reduces exposure to the interpersonal conflict of task sharing that
women find distasteful. Job rotation may also be more attractive to women because of the ability
to socialise regularly with a greater variety of co-workers than single job assignments. Job
rotation helps prevent repetitive motion injuries by providing task variety. This is favourable
since women react more negatively to repetitive work than do men. Roxburgh (1996) reports that
in a sample of Canadian workers “Results indicate that, controlling for exposure, marital status
and income, women are more vulnerable to the negative effects of routinisation”. This
vulnerability is intensified by the tendency of women to cope with a problem by thinking about
it, while men respond by avoiding thinking about it. Routine work requires little concentration,
with time to think, and excessive thinking about problems has been shown to lead to stress and
depression. (Nolen-Hoeksema, 1987). Thus, the favourable reaction of women to job rotation
appears linked to increased socialisation and reduced routinisation.
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Stress Responses to Lean Implementation – EPSRC Study
The implementation hypothesis in our earlier EPSRC study was: “Job stress is positively
associated with the degree of lean production implementation”. It was based on the tendency of
lean production to intensify work by systematically eliminating work flow interruptions. Elgar
(1990) calls this intensification a decreasing of the ‘porosity’ of the work day for workers,
resulting from “paring down of pauses, resting and waiting time and thus a closer filling of the
pores of the working day”. The lean implementation level was measured by a scale of ten lean
production elements (alpha=.816). The hypothesis was rejected since the relationship between
stress and implementation was more complex than hypothesised. It is non-linear, with the best fit
a convex quadratic curve. (F=6.65, df=1388, p<.001). The relationship exhibits an initial zone of
increasing stress at low implementation, a middle zone of stress levelling off to an inflection
point and a final phase of decreasing stress.
Figure 1
Gender Differences in Stress Responses to Implementation
Figure 1 shows both the quadratic relationship of the original study and a joint plot of the male
and female responses from the split sample. The male relationship follows the non-linear
response of the total sample. The female response, however, shows the hypothesised relationship
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of steadily increasing stress over the full range of implementation – a dramatically different
result. Koenigsaecker (2000) identifies three lean implementation stages based on several lean
conversions: He characterises the first two years as a period of “dissension and anti-change”, year
three as one of “change stabilisation and building the long-term foundation” and years four and
beyond as a period where change becomes the norm and “pride in lean accomplishments
develops and results begin to compound”. His description fits our male response, but not that of
the females.
Two behavioural processes are at work during a lean production implementation: an initial
resistance to change, followed by reactions to the lean production practices Both men and women
face an initial period of uncertainty and anxiety about changes in job tasks, job security, work
loads and shop floor relationships. Cleveland et al. (2000:329) point out that “Uncertainty over
one’s future, one’s duties, and relationships within organisations is a significant source of stress”.
The stress of uncertainty is reinforced by the pressures of learning new jobs and coping with
work intensification. Males, however, appear to better adapt to the changes, with their stressful
responses levelling off, followed by reduced stress. The latter response is likely due to favourable
aspects of lean production such as cleaner and better organised shops, reduced role ambiguity and
outcome uncertainty, fewer frustrations from missing parts, machine breakdowns and quality
problems; and improvements in quality and cost. These factors can create a sense of pride and
enhanced job security.
While male stress levels are lower at high lean implementation, they are higher than those of
women in the initial stage. These differences over the three stages may lie in the effects of the
male ‘breadwinner’ role, the female ‘dual role’ conflict, gender differences in socialisation needs
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and sensitivity to repetitive tasks; and job demand and adaptation differences. These are
examined for each stage.
Implementation Stage Responses and Gender Differences
A major fear in lean production is the loss of jobs due to increased productivity. Therefore, the
stress levels of males in the early stage are likely to be higher because of their family provider
roles. Kessler and McLeod (1984) state that “men are more vulnerable to stress related to their
provider role such as job security and income loss”. Nelson et al. (2002:230) citing increasing
stress due to job insecurity, report that men have much greater concerns for this factor than
women. On a six point scale, our male respondents averaged significantly higher concerns for job
insecurity than females: 3.48 vs. 3.05 (t= 4.484, p<.001).
In the intermediate stage, stress levels off for males but increases for females, perhaps due to
greater adaptability of males to work practice changes. Mechanic (1968:86) argues that the key
factors in adaptation are developing the capacities and skills to adapt to changes, and having the
motivation to do so. Higher turnover of female workers leads to longer service times and higher
skill levels for male workers, aided by their greater familiarity with tools. The motivation for
adapting is stronger for men because of their greater need for success at work. The positive
reactions of the men to high levels of implementation contrasts sharply with the negative
responses of women. Increased job demands from intensification are more stressful for females.
Also lean job tasks tend to become more routine, and hence more stressful to females, as a result
of techniques such as foolproof assembly designs and standard operating procedures (SOPs).
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The ‘dual role’ conflict, faced primarily by women, adds to the stressful consequences of work
intensification. Beehr (1987:84) points out that “women tend to keep their non-work roles (such
as wife and mother) when they enter the workforce and these roles tend to be more important to
them than the male’s non-work roles are to them. Thus they are pulled two ways more strongly
than men in our society”. This dual role results in women working longer total hours (work plus
non-work) on average than men. Nelson and Burke (2002:4) conclude that “This increased
workload makes it more difficult for women to ‘wind down’ after work and threatens their
mental and physical health”. Our female respondents reported this situation. A four point scale
measured difficulty in finding time to wind down, and women averaged 2.68 versus 2.50 for men
(t=3.11, p=.002). This difference is important since difficulty in winding down is correlated with
total stress in our study (r=0.399, p<.001).
Newsome (2003) observes that a shift from intermittent flow batch manufacturing to continuous
flow lean production can bring lower autonomy and higher intensity - particularly undesirable for
women. Peterson (1999:154) describes another consequence of this shift: “The quality of the
work relationship is affected by the type of workflow procedure employed”. Specifically, the
continuous lean flow makes it difficult to maintain social contact and conversation with co-
workers. Bellman et al. (2003) point out that “Females, because they derive satisfaction from
talking over their feelings with their friends, are more likely to perceive benefits from social
support”. Cox (1985:95) reports that in a pharmaceutical company, women “who could socialise
and talk with other women tended to describe their work more positively and as more pleasant
than those who could not”. High levels of lean production implementation inhibit female workers
in pursuing desirable socialisation and social support.
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The combined effects of increased job demands, lower job control and lower social support at
high implementation levels appear to contribute to the linear stress response of female workers.
Male workers, however, tend to react favourably to several facets of high implementation lean
production. Their strong concerns for job security appear to be met by improved product quality
which improves the firm’s competitiveness. The strong identification of males with job
performance helps them to react positively to the improved consistency and rhythm of workflow
and the reduced frustrations of flow interruptions. Participation in continuous improvement
projects is associated with reduced stress levels (Beta -0.062, p=.009) for our total sample.
Female participation, however, is significantly lower than that of males (t=3.298, p<.001). This
may be due to improvement programs taking place primarily on voluntary overtime, a hardship
for many females with after-work family duties.
In summary, the dramatic observed gender stress differences appear to result from the combined
effects of unfavourable female responses to high lean implementation conditions and favourable
male responses to these same conditions.
Job Dissatisfaction and Commitment
The ASSET survey measured the levels of job dissatisfaction and commitment to the firm, as
well as stress. Figure 2 shows the combined male and female responses of these measures to the
level of lean implementation. The curves tend to support the validity of our gender stress
responses with the dissatisfaction curves following the pattern of the stress curves and the
commitment curves exhibiting an inverse relationship to them.
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Figure 2
Gender Differences in Stress Responses to Demographic and Life-style Variables
Analysis of Variance (ANOVA) was used to check the relationships between stress and the
response levels of demographic and life-style survey items for both genders. There were no
significant relationships for either gender for marital status, age, number of children and their
ages, and alcohol use. There were significant relationships for both males and females (p<.05) for
the degree of hobbies and social mixing; as well as similar stress responses to exercise. (female
p=.059 and male p=.038). Only smoking exhibited a gender-specific response, significant only
for males (p=.006). However, the UK National Health Service categorises “smoking more to get
through the day” as a symptom of work related stress rather than a causal stressor. It appears that
demographic and life-style factors do not materially affect the validity of our results.
Conclusions
The results of our earlier study represent a breakthrough. For the first time, linkages between job
stress and a range of specific management lean production choices have been identified and
measured. This understanding is valuable for designing and operating systems that can provide
workers with the job security of high performance, while exercising adequate concerns for their
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health and well-being. Our gender results expand our earlier breakthrough. They provide a deeper
understanding of lean production stress by identifying gender differences in stress responses –
making possible more focused stress reduction measures. Peterson (2004) states that “Knowing
and managing the (gender) differences helps to not only generate consistent quality results, but to
foster loyalty and overall emotional and physical health”. Our results support the conclusion of
Muhonen and Torkelson (2004) that “separate analyses for men and women are needed to
investigate potential gender differences that might otherwise go unnoticed”.
Nelson and Burke (2002:11) suggest a proactive strategy in using the results of gender stress
research: “If organisations want to design gender-specific interventions, they should focus on
eliminating the stressors to which each gender is especially vulnerable”. This approach mirrors
the lean manufacturing philosophy of identifying and eliminating the fundamental causes of
problems instead of merely attacking their symptoms. A useful framework for implementing this
strategy is the pursuit of gender-inclusive lean production systems. Such systems would feature
‘structural integration’ – with “no correlation between demographic group membership and job
status”. (Cleveland, et al, 369) This would expand job opportunities for women (and older
workers), increase the functional flexibility of the entire work force and reduce job stress for both
genders. Gender-inclusion requires integrated changes in job design, product and process design,
ergonomics, and human resource policies. The Toyota Motor Company design of their Kyushu
plant is an example of such an approach. (Shimizu, 1995:383)
High turnover and difficulty in hiring assembly workers in the 1980s led Toyota to “humanise”
its production system by following the principle that “just-in-time” should not be applied to the
workers. The Kyushu plant was designed and operated under the new philosophy in the early
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1990s. One of the stated objectives was designing the system “to make the work place fit for
older and female production workers. If older workers are unable to work there, it is the factory
which is bad”. (Shimizu, 1995:393). The focus of capital investments shifted accordingly to the
support of the workers. Mikio Kitano, ‘Toyota’s top production guru’, stated that “the main
purpose of automation is to relieve the burden on the worker”. (Benders, 1996). Table 2
summarises the major changes made at the Kyushu plant, and the associated gender
consequences for women (W) and men (M).
Table 2 Toyota Kyushu plant changes
Work Practice Changes Gender ConsequencesAvoid isolation of workers through teams Increased socialization (W) and increased task support (M) Buffer inventories between teams Increased work pace control (M) and socialization (W)No overtime or night work Decreased long hour stress (M) and dual role stress (W)Eliminated periodic mandated reductions in number of line workers
Decreased resource removal stress (W)
Increased training for new workers and emphasis on vocational competence
Improved understanding of tools and their use (W)
Added fatigue allowances to standard times Reduced work pace/intensity and job demands (W & M)'Toyota verification of assembly line' method to quantify workloads, identify heavy work and correct
Reduced ergonomic difficulty stress (W & M)
Adjustable height work stations Improved tools (W), reduced ergonomic difficulties (W & M)Increased hiring of women Expanded job opportunities made possible by gender inclusive
changes in policies (W). It also expands opportunities for older workers
Apparently the enlightened approach taken by Toyota at Kyushu was not at the expense of
manufacturing performance. The 2001 JD Power Initial Quality Study rated Kyushu the best auto
plant in the world. While the Kyushu design was economically motivated the steps taken appear
to be consistent with our empirical results. With appropriate site-specific modifications, it may
serve as a guide for designing and operating gender-inclusive lean systems.
The gender study is subject to the same limitations as our earlier study, outlined in Appendix A,
since it is an extension of that study. This characteristic imposes an additional limitation - the
study was not designed to address gender differences in job stress responses. There is a need for
20
additional studies, specifically designed to address the gender issue, with formal hypotheses
based on gender behavioural theory, suitable controls over factors such as gender mix and job
assignments; and reliable survey items for hypothesis testing.
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24
Correlations for women Mean Std. D Stress Parts fit Flow
interruptAbsentee worker
Erg Job rotation Removal freq
Team work
Cycle time
Pace control
Pace/Intensity
Task support
Tools Buffer use
Change autonomy
Training Comments on change
Indiv. display
Blame Impov. projects
Physical and Mental Stress
38.37 10.287 1
Parts fit 2.69 .952 .226** 1 Flow interruptions 2.70 .849 .134* .309** 1 Absentee worker 1.85 .925 .258** .079 .269** 1 Ergonomics 2.75 1.292 .357** .237** .307** .281** 1 Job rotation 1.66 .476 -.208** -.003 .118* -.020 -.096 1 Removal freq 1.87 .990 .287** .191** .110* .193** .109* .023 1 Team work 1.62 .487 -.058 -.017 .034 .123* -.109* .192** .075 1 Cycle time 1.77 .421 .021 -.088 .078 .053 .125* .064 .040 -.012 1 Pace control 2.57 .835 -.120* -.115* -.050 -.051 -.099 .014 -.229** -.028 -.252** 1 Pace/Intensity 2.71 .961 .407** .247** .157** .233** .308** -.114* .288** -.038 -.015 -.179** 1 Task support 1.53 .500 -.246** -.071 -.077 -.131* -.129* .145** -.133* .103 -.102 .056 -.139* 1 Lack of tools 2.29 .777 .373** .214** .153** .197** .334** .006 .195** -.133* -.003 -.162** .290** -.124* 1 Buffer use 2.21 .706 -.085 -.091 -.162** -.045 -.035 .110* -.061 -.037 -.134* .217** -.097 .153** -.002 1 Change autonomy 2.21 .674 -.046 -.145** -.064 -.102 .043 .074 -.042 -.033 .062 .165** -.089 .083 -.023 .285** 1 Training 2.96 1.022 -.042 -.018 -.112* -.051 .012 .012 -.141* -.102 -.155** .053 -.039 .086 .052 .121* .078 1 Change comments 2.38 .729 -.115* -.050 .160** .126* -.047 .074 -.016 .055 .088 .074 -.114* .124* -.105 -.083 .028 -.195** 1 Indiv. display 1.78 .546 .044 -.002 -.110* .002 .014 .077 .101 .066 .037 -.049 -.045 -.046 .026 .112* -.042 -.009 -.090 1 Blame 1.88 .979 .344** .248** .121* .156** .237** -.307** .176** -.092 -.142* -.045 .307** -.173** .244** -.082 -.105 .020 -.106 .042 1 Improv projects 1.30 .461 -.157** -.095 -.074 .021 -.241** .174** .046 .006 -.065 .077 .043 .075 -.111* .091 -.040 -.061 -.022 .008 -.175** 1 Long hours 3.10 1.647 .271** .140* .102 -.002 .167** -.168** .111* -.125* .072 -.105 .281** -.312** .136* -.142** -.027 -.163** -.138* .041 .239** -.031 ** Correlation is significant at the .01 level (2-tailed). * Correlation is significant at the .05 level (2-tailed).
Correlations, Men Mean Std.
D.Stress Parts fit Flow
interruptAbsent worker
Ergo Job rotation
Removal freq
Team work
Cycle time
Pace control
PaceIntensity
Task support
Lack of tools
Buffer use
Change autonomy
Training Change comments
Indiv. output display
Blame Impr.projects
Stress 36.3910.668 1 Parts fit 2.80 .935 .186** 1 Flow interrupt 2.86 .840 .186** .326** 1 Absent worker 1.87 .931 .240** .198** .313** 1 Ergonomics 2.75 1.158 .311** .281** .309** .331** 1 Job rotation 1.57 .495 -.044 .043 .076** .074* .003 1 Removal freq 1.70 .910 .212** .162** .203** .302** .207** .157** 1 Team work 1.61 .487 -.117** .033 .119** .081** .017 .202** .140** 1 Cycle time 1.53 .500 .184** .049 .042 .124** .074* .106** .225** .101** 1 Pace control 2.36 1.044 -.268 -.173 -.160 -.180 -.113*
*-.006 -.253** -.075 -.423** 1
Pace/Intensity 2.88 1.013 .335** .278** .121** .227** .198** -.147** .214** -.032 .019 -.234** 1 Task support 1.51 .500 -.228** -.064 -.070 -.106** -.104*
*.132** -.106** .116** -.147** .211** -.244** 1
Lack of tools 2.31 .765 .218** .210** .148** .167** .256** -.070* .099** -.046 -.059 -.100** .319** -.173** 1 Buffer use 2.17 .733 -.179** -.093** -.075* -.063* -.084*
*-.015 -.138** .029 -.254** .306** -.198** .249** -.061* 1
Change autonomy
2.25 .693 -.141** -.070* -.101** -.081** -.022 -.044 -.177** .010 -.164** .221** -.053 .130** .021 .217** 1
Training 2.77 1.008 .031 .081** .002 .087** .073* -.070* .051 -.087** -.079** .004 .158** -.103** .171** .023 .031 1 Change comments
2.36 .771 -.116** -.101** -.019 -.028 -.102**
.111** -.041 .102** -.027 .103** -.107** .146** -.115** .182** .096** -.148** 1
Indiv. display 1.76 .596 .019 -.024 .049 .007 -.007 .141** .074* .098** .103** -.073* -.017 .081** -.030 .007 -.048 -.022 .077* 1 Blame 1.93 .944 .340** .201** .135** .168** .172** -.028 .191** -.015 .093** -.257** .332** -.209** .276** -.193** -.162** .101** -.120** .090** 1 Imp. projects 1.40 .490 -.172** -.086** -.113** -.039 -.134*
*.105** -.123** .076 -.161** .247 -.057 .082** -.051 .069* .124** .017 .113** .024 -.174*
*1
Long hours 3.56 1.641 .362** .181** .119** .118** .193** -.073* .188** -.049 .193** -.198** .229** -.087** .150** -.160** -.092** .009 -.112** .050 .219** -.120** ** Correlation is significant at the .01 level (2-tailed). * Correlation is significant at the .05 level (2-tailed).
25
Appendix A
SYNOPSIS: EPSRC STUDY of LEAN PRODUCTION JOB STRESS
Objectives
Valid information about lean production job stress is necessary for the design and operation of
effective systems that address the well-being of the workers. Our study contributes to this
need by answering the following questions:
What is the relationship between worker stress and the level of lean production to which
workers are exposed?
What are the relationships between various lean practices and worker stress?
Elements of Lean Production
Lean production is an outgrowth of the Toyota Production System. (Ohno, 1988; Womack et
al, 1990) It employs a variety of technical and human resource elements, implemented in an
integrated manner. Ten key lean production elements are described below, and they are used
to measure the implementation level at the survey sites.
Table 1 Lean Production Elements, Definitions and References (a)
LP Element LP Element Definition References/Pages (b)Set-up Reduction Reducing the time to change from making one item to making a
different item. Shortens lead times and reduces inventory.1(63), 2(20), 4(439, 451), 5(33, 167)
Inventory and Waste Reduction
Waste' is an activity that does not add value for the customer. Excess inventory is a major waste and a prime reduction target.
1(112), 2(18), 4(439), 5(7)
Kanban Pull Signals A shop floor control system of visual signals from using to supplying work centres indicating the need for more parts. This 'pulls' the needed replacement parts based on actual usage, or demand.
1(272), 2(85), 4(437, 444), 5(146)
Supplier Partnerships
Lean firms form cooperative supplier relationships, sharing design and cost improvement responsibilities and emphasising the on-time delivery of high quality parts.
1(219), 2(157), 4(441), 5(196)
Continuous Improvement Program
An ongoing program of improving the quality, costs and lead times of processes and products, through the cooperative efforts of shop workers and engineers. Often referred to as 'kaizen'.
1(7), 2(181), 4(443), 5(69)
Mixed-Model Production
Assembling different products and product variations on the same line. Balances shop floor work loads when combined with level production schedules. Reduces lead times and inventories.
1(191, 204), 2(93), 4(440), 5(124)
Total Quality Management (TQM)
Integrated program for improving process and product quality through techniques such as statistical process control (SPC), 'quality at the source' (workers self-inspect and stop the line if defects occur) and supplier pre-delivery quality control.
1(34), 2(49), 4(114, 438), 5(101)
Foolproof (poka-yoke) or Design for
Foolproof techniques seek to eliminate judgement and discretion in performing production tasks to produce high-reliability products. DFA
1(25), 3(3), 5(135)
26
Assembly (DFA) Systems
is a computer rule-based design system for reducing the parts in a product, improving quality and reducing costs.
Total Preventive Maintenance (TPM)
Highly organised program of periodic machine maintenance, and pre-emptive replacement of components such as bearings to minimise the frequency and duration of machine break-downs. Routine minor maintenance during work hours is done by workers.
1(188), 2(136), 4(442), 5(113)
Standard Operating Procedures (SOP)
Detailed descriptions of production tasks are documented to aid in organisational learning, training and ISO 9000 compliance. Helps maintain a cumulative effect of continuous improvement.
1(219), 4(441), 5(135)
a) Adapted from Fullerton et al. (2003)b) 1. Shingo (1981), 2. Schonberger (1982), 3. Schonberger (1998), 4. Krajewski and Ritzman (2003), 5. Suzaki (1987)
JOB STRESS
Cartwright and Cooper (2001) define stress: “When the individual perceives that the demands
placed upon them exceed their ability to cope then they have entered the stress arena”. Our
study measures stress in terms of the physical and psychological strains reported by workers.
RESEARCH DESIGN & METHOD
Management and worker surveys, management interviews and plant tours were
employed. The response variable is total stress – the sum of physical and mental stress
measured by the ASSET survey, whose construct validity is addressed by Johnson and
Cooper (2003). The independent variable for implementation is the degree of lean
implementation at a worker’s site, measured by the scale of ten lean elements.
(Cronbach alpha .816). The independent variables for the work practices are the
perceived work practice levels. The Survey Research Handbook states that “The
maximum practical total sample is about 1,000 respondents”. (Alreck and Settle,
1995:62). This size was chosen, with a target number of twenty lean production sites.
The sample space is the population of assembly workers at UK manufacturers with at
least 60 assemblers and some lean implementation. Sites differing widely in lean
practices were recruited by selecting firms in four SIC codes: 35 (machinery), 36
(appliances and electronics), 37 (motor vehicles) and 38 (instruments) Sample and site
characteristics are shown below. The worker response rate was 1,391 out of 2,555
surveys distributed (54.4%).
27
Mean number of assemblers (range) 127 (62 to 412)Mean JIT/LP implementation score 3.72 (2.06 to 4.87) out of 5.00SIC No. sites Percentage Percentage production employees*35xx 5 23.8% 33.8%36xx 5 23.8% 25.7%37xx 8 38.1% 29.2%38xx 3 14.3% 11.0%*Labour Market Trends, June 2001 v109 n6
WORK PRACTICE HYPOTHESES
Theoretical Basis
The Karasek job stress model was used to link lean practices to expected worker stress.
(Karasek and Theorell, 1990:57; Conti and Gill, 1998). The model incorporates the effects of
job demands (physical and psychological), job control and job support. High stress jobs are
associated with high job demands, low job control and low job support.
Job Demand Hypotheses
The Karasek model predicts that work practices creating high physical and psychological job
demands will be associated with high levels of physical and mental job stress. Therefore:
H1: Job stress is positively related to work pace and intensity.
H2: Job stress is positively related to the frequency of resource removal
H3: Job stress is positively related to working longer hours than desired.
H4: Job stress is positively related to decreasing cycle time.
H5: Job stress is negatively related to buffer inventories between work stations.
H6: Job stress is positively related to doing the work of absent fellow workers.
H7: Stress is positively related to the perception of being blamed or defects.
H8: Job stress is positively related to the frequency of displaying individual output.
H9: Job stress is positively related to ergonomic difficulty in performing tasks.
Job Support Hypotheses
The Karasek model predicts that work practices with low support will be associated with high
28
levels of worker stress. Therefore:
H10: Job stress is negatively related to the opportunity for team working.
H11: Job stress is negatively related to support in meeting time/quality standards.
H12: Job stress is positively related to the frequency of parts not fitting.
H13: Job stress is positively related to the frequency of work flow interruptions.
H14: Job stress is positively related to a lack of adequate training
H15: Job stress is positively related to a lack of adequate tools and equipment.
Job Control Hypotheses
In the Karasek model job control is related to the degree of job decision latitude and
autonomy, with higher levels of control associated with lower stress. Therefore:
H16: Job stress is negatively related to the level of work pace control
H17: Job stress is negatively related to autonomy for making task improvements.
H18: Job stress is negatively related to commenting on proposed work changes.
H19: Job stress is negatively related to participation in improvement programs.
H20: Job stress is negatively related to the frequency of job rotation.
These twenty hypotheses are tested to assess the relationship of the practices to the levels of
total stress.
LEAN IMPLEMENTATION HYPOTHESIS
Lean production increases work intensity (the proportion of work time actually spent
performing tasks) and decreases worker autonomy. This increases job demands and reduces
job control – increasing stress in the Karasek model. Therefore:
H21: Job stress is positively related to the level of lean production implementation.
29
IMPLEMENTATION HYPOTHESIS TEST RESULTS
The best fit between stress and lean implementation is the convex quadratic curve shown in
Figure 1 (F=6.65, df=1388, p<.001). Hypothesis 21 is rejected since the relationship is more
complex than hypothesised.
Level of JIT/LP implementation
5.04.54.03.53.02.52.0
Phys
ical
and
men
tal s
tress
40
39
38
37
36
35
34
33
32
31
30
Linear
JIT/LP
Quadratic
JIT/LP
Level of JIT/LP implementation
5.04.54.03.53.02.52.0
Dis
satis
fact
ion
28
27
26
25
24
23
22
21
20
Linear
JIT/LP
Quadratic
JIT/LP
Figure 1. Figure 2.
Level of JIT/LP implementation
5.04.54.03.53.02.52.0
Empl
oyee
com
mitm
ent
9.0
8.8
8.6
8.4
8.2
8.0
7.8
7.6
7.4
Linear
JIT/LP
Quadratic
JIT/LP
Level of JIT/LP implementation
5.04.54.03.53.02.52.0
Perc
eive
d or
gani
satio
nal c
omm
itmen
t
20.0
19.5
19.0
18.5
18.0
17.5
17.0
Linear
JIT/LP
Quadratic
JIT/LP
Figure 3. Figure 4.
The ASSET survey also measures job dissatisfaction, worker commitment to the firm and
perceived commitment of the firm to the worker. The plot of dissatisfaction versus
implementation in Figure 2 exhibits the same shape as the stress curve. The commitment plots
of Figures 3 and 4 exhibit mirror images to those of stress and dissatisfaction, and are also
non-linear. The dissatisfaction and commitment response curves appear to be consistent with
the non-linear relationship of stress to lean implementation.
WORK PRACTICE HYPOTHESIS TESTING RESULTS
30
Statistical Procedure
Analysis of Variance was used to check means and 95% confidence intervals for the stress
responses to each of the five work practice levels. For sequential levels with means that did
not differ significantly the levels were combined and the variable redefined. To allow for
multiple testing, the significance level for each of these analyses was set at .001 or less.
Multiple regressions of the redefined variables were used to test the hypotheses at levels
of .05 or less. The test regression results are presented in Figure 1 of the main text.
Rejected Work Practice Hypotheses Nine of the twenty hypotheses were rejected at the .05 level:H5 Work Pace Control H8 Display of Individual Output H12 Parts Fit Difficulties H13 Work Flow Interruptions H14 Lack of Training H16 Use of BuffersH17 Autonomy for Process Changes H18 Commenting on Work Changes H20 Job Rotation
Supported Work Practice HypothesesEleven of the twenty hypotheses were supported at the .05 level:H1 Work Pace/Intensity H2 Resource Removal (removal of workers) H3 Working Longer Than Desired Hours H4 Low Cycle Times H6 Doing Work of Absent Workers H7 Feeling of Blame for Defects H9 Ergonomic Difficulty H10 Team Working H11 Task Support H15 Lack of Proper Tools H19 Participation in Process Improvement
WORK PRACTICE ANALYSIS SUMMARY
The hypothesis tests show a substantial managerial effect in the determination of job stress
levels, with work practice level variations explaining 30% of stress variations. Work practices
that should be avoided or modified by management are identified, as well as those favourable
31
practices that should be pursued. They are summarised in the Recommended Lean Production
Practices check list.
CONCLUSIONS
Is lean mean? Is it worth it? It appears that lean worker well-being is not deterministic,
depending heavily on management policies and practices. Adler (1998) contends that lean
production can be compatible with reasonable health standards, with “good implementation”.
A ‘good’ lean program appears worthwhile. Our sites experienced positive correlations
between lean implementation and levels of improvement in quality (r=0.749, p<.001),
productivity (r=0.429, p=.046) and delivery times (r=0.577, p=.005).
LIMITATIONS
Testing twenty work practices and the level of lean implementation required a trade-off of
lower measurement reliability for increased scope. Many variables were measured by single
survey items to maintain a survey of feasible length. The sample size of 21 lean sites is
moderate. This was partially addressed by selecting sites with a variety of practices. They are
all in the UK, controlling cultural differences in stress responses. This may limit the
applicability of our results to other countries. Like much stress research, we used self-reported
measurements of variables. To minimise self-reporting limitations we followed Beehr
(1995:131), avoiding “the use of the word ‘stress’ in questionnaire items, and the use of job
dissatisfaction as a strain measure”.
32