Journal of Japanese Management Vol.1, No.1, November 2016

ISSN 2189-9592

Impacts of Overtime Reduction on Psychological Well-Being
for Japanese Research and Development Engineers:
Positive and Negative Sides of Work Time Regulations
Tetsushi Fujimoto

Doshisha University, JapanThe Japanese Association of Administrative Science
Hideki S. Tanaka

Aomori Public University, Japan
Japan Society of Human Resource Management
Shiming Xia

Doshisha University, JapanThe Japanese Association of Administrative Science
Abstract
In recent years, Japanese employers increasingly impose restrictions on employees’ work time.
Reduced overtime work has impacted a large number of engineers employed in private firms,
making it more difficult to put in extra hours to complete their work. As a result, the incidences ofexperiencing incompletion and non-accomplishment in work have grown among Japanese engineers.
This study investigates whether and how the overtime reduction affects engineers’ work experiences
and their psychological well-being. Results show that intensification in overtime reduction
negatively affects engineers’ work experiences regardless of their managerial status. It increases
their job demands and unfinished work, while it reduces their workplace communication.
Furthermore, overtime reduction is likely to deteriorate engineers’ psychological well-being.
Reduced overtime exhibited negative indirect influence on their work engagement and mental
health via increased demands and reduced communication. Findings suggest that managing
overtime work is an important aspect of human resource management of engineers, and it isimperative that we recognize immoderate work time regulations may bring about unintended
negative consequences in engineers’ work.
Keywords
overtime reduction, engineers, work engagement, depression, Japan27

Journal of Japanese Management Vol.1, No.1, November 2016

ISSN 2189-9592(1) Introduction
Long hours of work have been regarded formany years as an important characteristic ofJapanese work lives (cf. Kuroda & Yamamoto,2012; Ogura, 2007). It is officially reported thatthe annual work hours in Japan between 1999
and 2009 were over 1800 hours, and that the
average annual hours worked exceeded 2,000
hours1 in several years during this period (SeeTable1; Ministry of Health, Labour and Welfare,2011). Full-time employees in Japan worked
approximately 2000 hours per year, and thiswas 400 hours longer than the hours theircounterparts in Germany and France worked(The Japan News, 2012).
Japanese employers, however, started to
cut back on the hours of employees’ overtime
work soon after the financial crisis hit theeconomy in 2008 (See Table 1). Employer’s
restriction of overtime work has impacted alarge number of R&D engineers employed in
private firms, making it increasingly difficult forthem to put in extra hours in work. As a result,the incidences of experiencing incompletion andnon-accomplishment in work grew among
Japanese engineers.
Japan is an island country with limited
natural resources, so that innovative,
technological contributions that R&D engineers
make are a crucial requisite for Japan’s
economic development. In order to elicit theircontinued contributions, it is important to lookcarefully at R&D engineers’ work conditions.
Up till today, a limited number of studies
have explored the psychological experiences of
R&D engineers in Japan. Fujimoto and Nakata(2007) reported that Japanese engineers’
motivation had declined between 1994 and 2005.
They found that the negative effect of
dissatisfaction with HRM on work motivation

had become exacerbated during the 9 years
between 1994 and 2005. Such results imply thatJapanese R&D engineers’ psychological wellbeing may have deteriorated during the past
two decades. Psychological well-being isconceptualized as a combination of positive
affective states such as happiness (the hedonic
element) and functioning with optimal
effectiveness in individual and social life (theeudaimonic element) (Deci & Ryan, 2008).
Huppert (2009) claims that psychological wellbeing is about lives going well, and it is the
combination of feeling good and functioning
effectively. Based on Schaufeli & Bakker (2004),
we view engagement in work and mental healthas two important factors of psychological wellbeing. While we believe that “living well” isimportant to all people regardless of occupations,
it is highly likely that well-being is an important
psychological resource which enables R&D
engineers’ creative performance at work. Yet,
only a limited attention has been paid to thisday to the Japanese R&D engineers’
psychological well-being in relation to thecircumstances of their employment.
The purpose of this study is to investigate how
the intensified reduction of overtime work inJapanese firms after the financial crisis in 2008
affected R&D engineers’ work experiences andtheir psychological well-being. Specifically, we
address the following research questions: (1)Does reduction in overtime work increase
Japanese engineers’ job demands and decrease
their workplace communication? If so, does it
exert stronger impacts on managerial engineers
than on non-managerial engineers? (2) Does
overtime reduction deteriorate engineers’ work
engagement and mental health? If so, does it
exert an indirect influence on them via
increased job demands and decreased

12007 exceeded 2000 hours. In 2007, the average reached2033 hours.

The average annual hours of work between 2002 and28

Journal of Japanese Management Vol.1, No.1, November 2016

communication, or does it exert direct impacts
on them?
This paper is organized in the following order.
First, we overview the situations surrounding
engineers’ work in Japan, and we briefly review

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our theoretical framework and analytic model.
Then, we provide details of our method andreport the results of statistical analysis. Finally,
we discuss our findings and conclude this paper
by indicating the direction for future research.

Table 1. Changes in Annual Work Hours between 1999 and 2009
Average of Official

Average of Actual

Average of Overtime

Year

Work Hours

Work Hours

Work Hours

1999

1834

1990

156

2000

1835

1999

164

2001

1835

1990

155

2002

1836

2000

164

2003

1843

2016

173

2004

1836

2015

179

2005

1832

2012

180

2006

1837

2024

187

2007

1841

2033

192

2008

1820

1996

176

2009

1807

1972

165

Source: Ministry of Health, Labour and Welfare (2011)
Note: The survey was conducted among full-time employees in Japan.

(2) Backgrounds
1. Work Hours in Japan
In Japan, the importance of work-lifebalance is increasingly recognized by employers
and employees, as well as the government. Mostof the past research on work-life balance evolved
around the key issue of how to reduce long hours
of work in order to ensure sufficient time forprivate life. Needless to say, regulating longhours of work is important to improve workers’
well-being. In this sense, it is probably true that
overtime restriction in and of itself is a blessing
for a majority of Japanese workers.
A cross-national comparison of the averageannual hours actually worked by employees

shows that Japan is not the only country withlong hours of work, but workers in Japan, U.S.
and Korea work equally long hours 2 (Japan
Institute for Labour Policy and Training[JILPT], 2013)3. In addition, the proportion of
employees who work more than 60 hours per
week is over 10 percent in Japan (Ministry ofInternal Affairs and Communications, 2013),
and the proportion of those who put in longhours of work is not only larger compared withother industrialized nations but is also as large
as in other developing countries (Ogura, 2008).
The average annual hours of overtime forJapanese workers between 2006 and 2008
(before the financial crisis) exceeded 180 hours.

2

3 Note that there are differences in the ways work hours areThis comparison included both full-time and part-timeworkers.

defined between OECD countries (JILPT, 2013; Ogura,2008).

29

Journal of Japanese Management Vol.1, No.1, November 2016

ISSN 2189-9592

Also, Research Institute for Advancement of
Living Standards (2009) pointed that the
average daily hours of overtime for Japanese
workers, especially men, exceeded 100 minutes.
Note that this number does not include hours of
unpaid overtime, or so-called “service overtime.”
Therefore, if we are to include those hours,
overtime work for Japanese workers will
become even longer.
Historically, overtime work has been an
integral part of Japanese management, and this“structured overtime” is one of thecharacteristics of the management in Japan.
While firms are to pay extra to employees who
work overtime,4 Japanese employers in manycases load their employees with an amount ofwork that easily exceeds what an employee canhandle within standard work hours (Sato, 2008).
Japanese employers tend to view this mismatchnecessary since it allows them to adjust flexibly
the volume of work without firing employees
during the time of recession. This mismatch isone of the important background factors thatsustained Japanese long-term employment,
and both employers and employees tacitly agree
to maintain the system. However, just after thefinancial crisis in 2008, most Japaneseemployers started to impose restrictions on
overtime work in order to reduce labor costs. A
survey on Japanese employers’ employment
adjustment practices between 2009 and 2011
revealed that, followed by a temporary
suspensionofbusinessandlayoff,approximately 30% of Japanese enterprises
regulated overtime work after the financial
crisis (JILPT, 2014). In this survey, 42.1% ofJapanese respondent firms reduced overtime
work in 2008 (immediately after the financial
crisis), and 34.7% in 2009 (See Table 2; JILPT,2014). Due to this employer reduction of
overtime, work hours for Japanese employees,
including R&D engineers, were significantly cut
down.

4 As a common practice in Japan, employees in managerial

time when trying to accomplish their work. Research anddevelopment is one of the “professional services” jobs
designated in the discretionary labor system. In addition,
managers’ work hours are usually not regulated by Japan’sLabor Standards Act.

2. Changes in Japanese R&D Engineers’ Work
Intensification in employer reduction of
overtime after the financial crisis has caused
unexpected problems in Japanese engineering
workplaces. An earlier interview research
conducted in Japanese manufacturing firms
reported that engineers underwent a serious
time shortage due to the overtime reduction,
and as a result the incidences of experiencing
incompletion/ non-accomplishment in work
were growing among them (Fujimoto,
Shinohara, Tanaka, & Nakata, 2013). In
addition, managerial engineers and teamleaders, who normally worked in discretionary
labor system5, were likely to be left with the jobtasks that their subordinates could not complete
within standard hours, so that the total amountof their work significantly increased, and moretime pressure and stress were added on them.
In general, reduced overtime may be a
blessing for workers. However, Fujimoto et al.
(2013) pointed out that due to the intensified
overtime reduction after the crisis a large
number of Japanese employees, R&D engineers
in particular, became increasingly unable to put
in sufficient amount of time in work. Findingsin this study showed that reduction of R&D
engineers’ work hours had a significant negative

positions are treated as exempt. However, “the level andtiming of assigning employees as exempt vary among firms
depending on their own long standing practices” (Kuroda &Yamamoto, 2012, pp.252).
5 Discretionary labor system is an example of the flexible
work hour system, and it is designed to allow employees incertain designated jobs to decide on how they utilize their

30

Journal of Japanese Management Vol.1, No.1, November 2016

impact on the sense of accomplishment forJapanese engineers.
These results imply that reduction of

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overtime may carry a connotation for R&D forengineers different from what we typicallybelieve about reducing workers’ overtime.

Table 2. Employment Adjustment Practices between 2008 and 2011 in JapanYear
Total Number of respondent companies

2008

2009

2010

2011

N

974

2,108

1,997

1,913

%

100.0

100.0

100.0

100.0

N

410

731

591

529

%

42.1

34.7

29.6

27.7

Standstill/Reduction of Employment of

N

203

344

337

309

New School Leavers

%

20.8

16.3

16.9

16.2

Standstill/Reduction of Mid-Career

N

231

377

317

276

Recruitment

%

23.7

17.9

15.9

14.4

Temporary Suspension of Business and

N

477

1,499

1,342

1,281

Layoff (Daily)

%

49.0

71.1

67.2

67.0

Temporary Suspension of Business and

N

154

379

373

406

Layoff (Hourly)

%

15.8

18.0

18.7

21.2

Cutback in Overtime Work

Source: JILPT (2014), p.60.
Note: Numbers in the table represent multiple responses.

(3) Theoretical Framework
Our main focus in this study is whether andhow overtime reduction affects Japaneseengineers’ work experiences and their
psychological well-being. We explore how
reduced overtime influences engineers’ jobdemands, unfinished work and workplacecommunication, and then how these in turnaffect their work engagement and depression.
We draw on the job demands-resources model toframework these relationships among JapaneseR&D engineers.

employee’s adaptive capability” (Bakker,
Hakanen, Demerouti & Xanthopoulou, 2007).
Specifically, job demands are “physical, social,or organizational aspects of the job that
require sustained physical and/or psychologicaleffort on the part of the employee, and are
therefore associated with certain physiologicaland/or psychological costs” (Demerouti, Bakker,
Nachreiner & Shaufeli, 2001). Examples of job
demands include work pressure (including timepressure), emotional demands, adverse physicalwork environment, role ambiguity, role conflicts
and overload.
Job resources, on the other hand, refer towork conditions that provide supportive meansfor employees when trying to accomplish theirwork. Specifically, job resources are “physical,
psychological, social, or organizational aspectsof the job that may (a) reduce job demands andthe associated physiological and psychological

1. Job Demands-Resources Model
Job demands-resources (JD-R) model(Demerouti, Bakker, Nachreiner & Shaufeli,2001) focuses on two types of work conditions,
i.e., job demands and job resources. Job
demands refer to “characteristics of the job that
potentially evoke strain, in case they exceed the31

Journal of Japanese Management Vol.1, No.1, November 2016

costs, (b) are functional in achieving work goals,
and (c) stimulate personal growth, learning anddevelopment” (Demerouti, Bakker, Nachreiner& Shaufeli, 2001). Job resources may be locatedin several different levels, includingorganization (e.g., salary, career opportunities,
job security), inter-personal (e.g., supervisor andco-worker support), organization of work (e.g.,role clarity, participation in decision-making),
and task (e.g., performance feedback, skill
variety, autonomy) (Bakker, Demerouti &Verbeke, 2004).
Generally, past research suggests that job
demands and resources are negatively related
to each other, because high demands are likely
to prevent the mobilization of job resources, andavailability of job resources are likely to reducejob demands (Bakker and Demerouti, 2007).
JD-R model suggests that an increase in job
demands and a decrease in job resources may
deteriorate individuals’ psychological well-being
and reduce their work engagement.
Work engagement is defined as a positive
work-related state of mind that is characterizedby vigor, dedication and absorption (Shaufeli etal., 2002). Since vigor and dedication are
considered as a reverse condition of exhaustionand cynicism, engagement is assumed to be
negatively related to burnout (Shimazu et al.,2008). As Schaufeli et al. (2006) stress, work
engagement and depression are negatively
related, and engagement in work ameliorates
individual mental health.

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resource that engineers particularly value when
they try to accomplish their work, and therefore
overtime reduction necessarily decreases theirvalued resource of time, affecting the ways inwhich engineers engage in work.
Since overtime work is often allowed forwhen Japanese employers estimate the amountof work assigned to engineers, unless the total
amount of work assignment is significantly cut
back when overtime is reduced, they are likely
to experience work overload and become unable
to complete their assignment without extra
work time to put in. Also in a situation like this,engineers may feel they have so little time forcommunication with others at work. Therefore,
we expect that overtime reduction increases job
demands and unfinished work for engineers,
while it decreases the level of their workplacecommunication, and these in turn negatively
affect engineers’ work engagement and mental
health.
Note that overtime reduction usuallyaffects work hours for non-managerial
engineers, making it more difficult for them tocomplete their work within standard work
hours. However, the work that non-managerial
engineers are unable to complete has to befinished by their managers and team leaders.
Managerial engineers and team leaders ingeneral take charge of a wider range of jobs. In
addition, leaders and managers in R&D
divisions tend to participate in multiple R&D
teams/ projects. In consequence, their job
demands may increase significantly when theymust take on additionally their subordinates’
unfinished tasks. Hence, the reduction of
overtime work may affect managers and nonmanagers differently. We predict that overtime
reduction has stronger impacts on engineers inmanagerial status, and it is likely to exert
stronger influence on work engagement andmental health for managerial engineers. In this

2. Analytic Model
The JD-R model emphasizes that job
demands and resources are the two key
determinants of employee well-being, and it ispredicted that an increase in job demands andreduction in job resources are likely to result in
deterioration of employees’ work engagement
and mental health. We argue that time is a job
32

Journal of Japanese Management Vol.1, No.1, November 2016

study, we test an analytic model as shown in
Figure 1, using data collected from among R&D
engineers in Japan.

registered at one online survey company, which
consisted of 6,740 research and development
engineers,
6,480
systems development
engineers, 5,341 systems planning engineers.
While the target number of respondents was set
for 4,500, 4,482 engineers completed the survey.
Our analytic sample for this study was 4,374
engineers, which consisted of 2,226 engineers inmanagerial positions and 2,148 engineers in
non-managerial positions.

(4) Methodology
1. Data
The data used in this study come from an
online survey “Survey on Work and Life among
Research and Development Workers” conductedby Fujimoto in March, 2012. Samples weretaken from over 22,500 Japanese engineers

Increase in
Job Demands
Intensificationof Overtime
Reduction

ISSN 2189-9592＋
Depression

ReducedTemporalResource

Engagement
Increase in
Unfinished Tasks &Decrease in
Workplace
Communication－

Figure 1. Analytic Model

2. Variables
2.1. Dependent Variable (1): Work Engagement
Work engagement was measured by using
the shortened Japanese translation of Utrecht
Work Engagement Scale (UWES, Schaufeli,
Bakker, & Salanova, 2006; Shimazu et al., 2008).
The 9 items in the shortened UWES
represented 3 facets of engagement (vigor,
dedication, and absorption), including items
such as “At my work, I feel that I am burstingwith energy (vigor),” “My job inspires me(dedication),” and “I get carried away when I am
working (absorption).” Responses ranged from
“1= strongly disagree” to “4= strongly agree”,
such that higher scores indicated stronger
engagement in work. We computed the averageof these 9 items and used it as a composite scale.

The internal reliability (Cronbach’s alpha) of thescale was .93 for managerial engineers and .94
for non- managerial engineers.
2.2. Dependent Variable (2): Depression
Depression was measured by using 10
items from the Japanese version of Selfreporting Depression Scale (Zung, 1965).
Respondents were asked their physical andmental conditions (e.g., “I feel down andmelancholy,” “I cannot sleep at night” etc.) witha 4-point response scale (1 = hardly ever to 4 =always.) We computed the average of these 10
items and used it as a composite scale. Theinternal reliability of the scale was .60 for bothmanagerial and non-managerial engineers.
2.3. Intervening Variable (1): Job Demands
Job demands was measured by a scale
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Journal of Japanese Management Vol.1, No.1, November 2016

which is the unweighted average of thefollowing three items: “Do you think that thevolume of work is balanced with the amount oftime available in your workplace? (4=strongly
disagree, 3=disagree, 2=agree, 1= strongly
agree.) ” “Because of a shorter delivery period,
many people at my work cannot work
satisfactorily.” “During the past year, I have had
verylittletimeindelivering
mywork.”(4=strongly agree to 1= strongly
disagree.) The internal reliability of the scale
was .64 for both managerial and nonmanagerial engineers.
2.4. Intervening Variable (2): Increase in
Unfinished Work
Increase in unfinished work was measured
by using a single item phrased “During the past
year, I am increasingly being unable to finish
my job (1= strongly disagree to 4= strongly
agree).”
2.5. Intervening Variable (3): Decrease in
Workplace Communication
Decrease in workplace communication was
tapped by a single item phrased “During thepast year, the atmosphere for communication
has deteriorated at my work (1= strongly
disagree to 4= strongly agree).”
2.6. Focal Independent Variable (1): Reduction
in Overtime Work
The focal independent variable in thisstudy was intensification of overtime reduction.
Respondents were asked whether reduction in
overtime work had been intensified during thefive years prior to the survey (i.e., between 2007
and 2012). In our analysis, the variable wasdummy-coded as 1= intensified, 0= no change orrelaxed.
2.7. Focal Independent Variable (2): Managerial
StatusManagerial status was coded as 1=manager,
0=non-manager.
2.8. Control Variables

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We included the following independent
variables as controls. First, years working for
current employer were measured in years. We
controlled for years working for current
employer, instead of respondents’ age, because
these two variables are significantly and highly
correlated each other (r=.662). Educational
attainment was measured as 1=junior highschool or high school, 2=some college, 3=college,
4=master degree, and 5=doctoral degree.
Income in the past year (in Japanese yen) wascoded as 1=less than 3 million yen (equivalent
to approximately US $35,000 or less), 2=3.003.49 million yen (approximately US $35,00040,000), 3=3.50-3.99 million yen, … 15=9.509.99 million yen, and 16= 10 million yen(approximately US $120,000) or over. Monthly
overwork hours were measured in hours.
Number of projects currently involved was also
controlled. Type of industry was dummy-coded,
such as communication/IT (reference category),
manufacturing, or other types of industry.
Finally, area of work was dummy-coded as
research(reference
category),
development/planning, information processing/software development, or other areas.
3. Statistical Procedure
Our analysis proceeded in two steps. First,
we conducted mean comparisons between
managerial and non-managerial engineers inovertime reduction, work engagement,
depression and other major job outcome
variables. Then, Ordinary Least Squares (OLS)
regression models were estimated to examine(1) whether intensified overtime reduction
exerts differential impacts on job demands,
increase in unfinished work, and decrease inworkplace communication for managerial andnon-managerial engineers, and (2) whether andhow the above work intervening variables inturn affect engineers’ engagement and mental
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Table 3. Mean Comparisons of Variables in Analysis: Managerial andNon-Managerial Engineers
Managerial(N=2,226)

NonManagerial(N=2,148)

Mean

S.D.

Mean

S.D.

Mean
Difference

Intensified Overtime Reduction

.415

.493

.389

.488

†

Work Engagement

2.472

.616

2.263

.657

***

Depression

2.064

.346

2.047

.358

Job Demands

2.631

.638

2.569

.666

***

Increase in Unfinished Work
Decrease in Workplace Communication

2.460

.853

2.360

.903

***

2.360

.770

2.320

.827

Sex (1=female)

.068

.252

.255

.436

Education

3.870

.976

3.880

1.013

Marital Status (1=married)

.779

.415

.525

.499

***

Children (1=present)

.675

.469

.397

.489

***

Annual Income

9.220

4.529

5.050

3.522

***

Tenure16.870

9.390

9.800

8.556

***

Recruitment Status (1=regular)

.560

.497

.500

.500

***

Employment Status (1=regular)

.530

.499

.620

.485

***

Monthly Hrs. of Overtime Work78.47073.35267.66072.376***

N of projects R participates

2.920

3.588

2.130

3.273

***

Firm Size

3.620

1.499

3.560

1.469

Job Type: Research (reference)

.101

.304

.119

.324

Job Type: Development

.320

.467

.305

.460

Job Type: Systems Engineering

.342

.474

.364

.481

Industry: Manufacturing

.417

.493

.401

.490

Industry: IT (reference)

.334

.472

.380

.486

***

Industry: Other

.235

.424

.213

.409

†

Focal Variables

Control Variables***†

Note: *** p <.001, ** p <.01, * p <.05, † p <.10

health.

scores between managerial and non-managerial
engineers for all variables in analysis. First, wefind that engineers in managerial positions
were more likely than their non-managerial
counterparts to experience intensification in
overtime reduction. While at a marginal level(5) Results
1. Descriptive Results
Table 3 reports the results of t-tests
conducted to examine the difference in mean
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Journal of Japanese Management Vol.1, No.1, November 2016

(p<.10), the mean of overtime reduction was
higher for managers (.415) than for nonmanagers (.389).
Mean comparison revealed that managers
were more likely than non-mangers to engage inwork. Mean scores of work engagement were
2.472 for managers and 2.263 for non-managers.
Managers exhibited a significantly higher meanscore in job demands (2.631) than nonmanagers (2.569). Also, managers perceived asignificantly higher level of increase in
unfinished work (2.460) than non-managers(2.360). However, we found no significant meandifferences in depression and decrease inworkplace communication between engineers inmanagerial and non-managerial positions.
Mean scores for indicators of demographic
characteristics also showed differences between
managerial and non-managerial engineers. For
instance, significantly more non-managers were
women (25.5%) than managers (6.8%).
Managers’ tenure in the current employer was
significantly longer (16.87 years) than nonmanagers (9.80 years). While we observed nosignificant mean difference in educational
attainment, managers earned a higher level ofannual income (9.220) than non-managers(5.050). Managers worked significantly longer
monthly hours of overtime (78.470 hours)
compared with non-managers (67.660 hours),
and managers were also involved in more
projects (2.920) than non-managers (2.130).
Thus, managers were working more intensively
than non-managers in our sample. We found nostatistically significant mean differences in firm
size and type of industry. As to job type, nonmanagers were slightly more likely (11.9%)
than managers (10.1%) to work in research,while approximately equal proportion ofmanagers and non-managers were working indevelopment/planning and systems engineering.
In terms of family status, managers were much

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more likely (77.9%) than non-managers to havespouse (52.5%). Managers were significantly
more likely (67.5%) than non-managers (39.7%)
to have children in the household.
2. Multivariate Results
Table 4 reports the result of OLS regression
predicting job demands, increase in unfinished
work,
and
decreaseinworkplacecommunication. First, the regression result forjob demands indicate that intensified overtime
reduction is likely to increase engineers’ jobdemands, and managerial engineers weresignificantly more likely than non-managerial
engineers to feel burdened with their high job
demands. Yet, we found no significant
interaction effect of over time reduction andmanagerial status. Several demographic
characteristics were significantly associatedwith job demands. For instance, women wereless likely to experience high job demands
compared with men. Higher income level andlonger tenure were negatively associated with
job demands, while longer hours of overtime
and more projects currently involved werepositively related to job demands. Those who
were in manufacturing industry were more
likely to experience a higher level of job
demands than those in other industries.
Engineers in development and systems
engineering were more likely to be burdenedwith demands, compared to those who were in
research.
Second, we find that intensification of
overtime reduction tends to increase engineers’
unfinished work, and that those in managerial
positions were significantly more likely thantheir counterparts in non-managerial positions
to experience an increase in unfinished work,when controlling for demographic conditions.
Yet here again, we found no significant
interaction effect of over time reduction and36

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Table 4. OLS Regression Coefficients for Models of Job Demands, Increase in Unfinished Work,and Decrease in Workplace Communication
Job
Demands

Increase in
Unfinished
Work

beta

Sig

beta

Sig

beta

Sig

Overtime Reduction

.206

***

.101

***

.098

***

Manager《Interaction Term》
Overtime Reduction * Manager

.057

***

.072

***

.016

Sex (1=female)-.059

Education

.023

.020

.021

Marital Status (1=married)

.013

.021

.011

Children (1=present)

-.018

-.042

Annual Income

-.063

**

-.016

Tenure

-.045

*

-.095

Recruitment Status (1=regular)

.034

*

Employment Status (1=regular)-.020

Monthly Hrs. of Overtime Work.033

N of Projects R Participates.085

Firm Size-.021

Development.144

Systems Engineering.117

Other Job Types.034

Manufacturing

.036

R2

.073

.010

.016
***

-.037

Decrease in
Workplace
Communication

-.003
*

*

-.049

**

.010
-.048

*

***

.033

+

.068

***

-.038

*

-.033

*

.032

*

*

.049

***

.031

*

***

.067

***

-.007

.004

.005

***

.030

.013

***

.011

-.008

-.033

.006

.022

.017

.035

.015

*

Note: + p<.10, * p<.05, **p<.01, ***p<.001
Coefficients indicated in table are standardized beta coefficients.
Reference category for job type is basic & applied research.

managerial status. Several demographic
characteristics were significantly associatedwith increase in unfinished work. For instance,
women were less likely than men to experience
increase in unfinished work. Longer tenure wasnegatively associated with the increased
unfinished work, while working longer hours ofovertime and being involved in more projects
were positively related to the increase.

Third, while overtime reduction does
decrease workplace communication, we
found no significant effect of being inmanagerial position on the decreased
communication at work. Here again, sex
exhibited a significant negative effect,indicating that women were less likely thanmen to feel the decrease in workplacecommunication. Those who earn higher annual37

Journal of Japanese Management Vol.1, No.1, November 2016

ISSN 2189-9592

Table 5. OLS Regression Coefficients for Model of Work Engagement

Work Engagement
Model 1Model 2

beta

Sig

beta

Overtime Reduction

-.057

***

-.022

Manager《Interaction Term》
Overtime Reduction * Manager

.091

***

.093

Sig
***

-.017

-.016

Sex (1=female).058

Education

.006

.010

Marital Status (1=married)

.029

.029

Children (1=present)

.029

.033

Annual Income.113

Tenure.021.030

Recruitment Status (1=regular)

-.022

-.029

+

Employment Status (1=regular)

-.055

***

-.050

***

Monthly Hours of Overtime Work

.029

+

.031

*

Number of Projects R Participates

.065

***

.070

***

Firm Size

-.047

**

-.051

**

Development

-.096

***

-.071

**

Systems Engineering

-.158

***

-.138

***

Other Job Types

-.079

***

-.067

**

Manufacturing

.023

.029

+

Job Demands

-.197

***

Increased in Unfinished Work

.155

***

Decrease in Workplace Communication

-.109

***

R2

.069

***

***

.047

.098

**

***

.114

Note: + p<.10, * p<.05, **p<.01, ***p<.001
Coefficients indicated in table are standardized beta coefficients.
Reference category for job type is basic & applied research.

income are less likely to feel the decrease incommunication. Longer tenure was positively
associated with the decreased communication,
while longer overtime was negatively related tothe decrease.
Tables 5 and 6 show the results of OLS
regression predicting work engagement anddepression. First, we examined whether

intensification in overtime reduction exerted a
direct impact on each dependent variable(Model 1). Then we entered additionally job
demands, increase in unfinished work, anddecrease in order to examine whether and how
these intervening variables affect engagementand depression, and whether intensification of
overtime reduction affect engagement and de38

Journal of Japanese Management Vol.1, No.1, November 2016

ISSN 2189-9592

Table 6. OLS Regression Coefficients for Model of Depression
Depression
Model 1beta

Model 2
Sig

beta

Sig
*

Overtime Reduction

-.012

-.033

Manager《Interaction Term》
Overtime Reduction * Manager

.025

.016

-.007

-.009

Sex (1=female)

.098

***

.105

***

Education

.034

+

.031

+

Marital Status (1=married)

.016

.013

Children (1=present)

-.017

-.013

Annual Income.042

Tenure

-.015

-.006

Recruitment Status (1=regular)

.013

.007

Employment Status (1=regular)

.004

.006

Monthly Hours of Overtime work

.027

+

.020

Number of Projects R Participates

.074

***

.065

Firm Size

-.018

-.017

Development

.012

.002

Systems Engineering

-.043

-.050

Other Job Types

.015

.016

Manufacturing

-.022

-.026

*

.048

*

***

+

Job Demands

.048

**

Increased in Unfinished Work

.082

***

Decrease in Workplace Communication

.027

+

R2

.017

.032

Note: + p<.10, * p<.05, **p<.01, ***p<.001
Coefficients indicated in table are standardized beta coefficients.
Reference category for job type is basic & applied research.

pression only through these intervening
variables.
As reported in Table 5, the result in Model
1 for work engagement shows that intensified
overtime reduction exerted a significant
negative impact on work engagement. However,when we added job demands, increase in

unfinished work, and decrease in workplacecommunication in Model 2, the negative effect ofovertime reduction was reduced to nonsignificance. These results suggest that
intensification in overtime reduction affects
work engagement only via these intervening
variables.
39

Journal of Japanese Management Vol.1, No.1, November 2016

All three intervening variables entered
Model 2 exhibited statistically significant effects
on work engagement. Job demands anddecreased workplace communication werelikely to reduce work engagement, whereas
increased unfinished work was likely toenhance engagement for engineers.
The regression results in Models 1 and 2
also show that managerial engineers weresignificantly more likely than non-managerial
engineers to be engaged in work, controlling forvarious demographic characteristics. Hereagain, we found no significant interaction effectof over time reduction and managerial status.
Several demographic characteristics weresignificantly related to work engagement(Model 2). For instance, women were more
likely to be engaged in work compared with men.
Higher income level and more projects currently
involved were positively associated withengagement, while working in larger firms was
negatively related to engagement. Those who
worked in manufacturing industry were more
likely to engage in work than those in otherindustries. Work engagement for engineers inresearch and development tends to be higher
than those who were in other types ofengineering jobs. Turning to the results fordepression (Table 6), intensified overtime
reduction exerted no significant effect on
depression. In Model 2, however, the negative
effect of overtime reduction turned statisticallysignificant after controlling for job demands,
increase in unfinished work, and decrease inworkplace communication. These results
suggest that intensification in overtime
reduction has a direct impact on depression, in
addition to the indirect effects via job demands,
increase in unfinished work, and decreased
workplace communication.
The results in Model 2 revealed that higher
job demands and increase in unfinished work

ISSN 2189-9592

are likely to deteriorate engineers’ mental
health. Decreased workplace communication
also exerted a positive influence on depression,
yet the effect was only marginally significant(p<.10).
The regression results for depression(Model 2) also revealed that women were more
likely than men to be depressed, and those who
earned higher income and had more project
assignments were more likely to feel depressed.
We found no significant effect of managerial
status on depression in Models 1 and 2.
(6) Discussion and Conclusion
Present results show that recent
intensification in overtime reduction in
Japanese firms has negatively affected
Japanese R&D engineers’ work. We found that
overtime reduction increased their job demands
and unfinished work, while it decreased thelevel of their workplace communication. We also
found that Job demands and decreased
workplace communication were likely to reduce
work engagement, whereas an increase in
unfinished work was likely to enhance
engagement for Japanese engineers. We
predicted that overtime reduction would exhibit
stronger impacts on engineers in managerial
status, and that it would exert a stronger
influence on work engagement and mental
health for managerial engineers. While
managers were marginally more likely thantheir non- managerial counterparts to perceive
the intensification of overtime reduction, we
observed no differences in the effect of overtime
reduction on work engagement and depression
for engineers in managerial and nonmanagerial positions. Thus, intensified
reduction of overtime work has negative
influence on Japanese engineers irrespective of
their managerial status.
We also found that intensification in40

Journal of Japanese Management Vol.1, No.1, November 2016

overtime reduction only indirectly affects
engineers’ work engagement via job demands,
increase in unfinished work, and decreased
workplace communication, whereas it has both
direct and indirect impacts on depression.
Findings in the present study raisedquestions about the commonly held perceptionof long hours of work for Japanese employees.
Overtime reduction for Japanese engineers may
have both positive and negative sides, and whileon one hand it enhances the time availability for
their life outside paid employment, on the other
hand it reduces the adequacy in time spent forwork. As Yoshimura (2007) claims, scientists ingeneral are highly involved in their jobs,
meaning that work tends to be their central life
interest, and it is an important source of theiridentity. While we found a positive association
between an increase in unfinished work andwork engagement, it may be that engineers
become all the more absorbed in work when
they feel their work-centered identity isthreatened by not being able to accomplish theirwork.
In order to strike an adequate balance
between work and life, it is not sufficient to justreduce time at work, but it is also necessary toevaluate the adequacy in work time
simultaneously. Although employers may
generally believe that reducing employees’
overtime work is an effective means to reducelabor costs, it is important that they realize
immoderate work time regulation may bringabout unintended negative consequences inengineers’ work. In order to improve the wellbeing and creativity for R&D engineers believed
to be motivated by intrinsic aspects of work (fun,challenges etc.), it is necessary to carefully

ISSN 2189-9592

examine the role of “time management.” Ourfinding that work engagement for engineers indevelopment and systems engineering is lower
than those in basic research has an implicationthat we must pay attention to how engineers in
different job types work. We will need tocompare how time at work is differentiallyexperienced by those who work under tightschedule control and those who do not, in orderto evaluate the role of “time management” forengineers in different job types.
Finally, the limitations of the present study
need be mentioned. First, the data used in thisstudy did not allow us to look more carefully at
how overtime reduction affected other aspects ofengineers’ work, such as voluntary unpaid
overtime. While some may argue that reduced
paid overtime is compensated by increase inunpaid overtime, our data did not include
information to examine whether this was true,
and to our best knowledge there is no publicdata available to see whether unpaid “service”
overtime increased between 2007 and 2012.
Perhaps our conceptual model requires awider scope to capture the processes throughwhich overtime reduction affects engineers’
work. In addition, although we looked at the
impact of managerial status in our analysis andhow the effect of overtime reduction isconditioned by incumbency in a managerial
position, we did not carefully compare the waysthat managerial and non-managerial engineers
worked. Future research should also look atwhether and how intensified overtime reduction
has exerted differential impacts on the workand non-work lives for managerial and nonmanagerial engineers.

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