Discussion Paper No. 784

ORGANIZATION ADJUSTMENTS,JOB TRAINING AND PRODUCTIVITY:
EVIDENCE FROMJAPANESE AUTOMOBILE MAKERS
Kenn Ariga
Masako Kurosawa
Fumio Ohtake
Masaru Sasaki
Shoko Yamane

July 2010

The Institute of Social and Economic Research
Osaka University
6-1 Mihogaoka, Ibaraki, Osaka 567-0047, Japan

Organization Adjustments, Job Training and Productivity:
Evidence from Japanese Automobile Makers
Kenn Ariga
Masako Kurosawa Fumio Ohtake
Kyoto University
GRIPS
Osaka University
Masaru Sasaki 
Osaka University

Shoko Yamane
Osaka University

July 15, 2010

Abstract
This paper considers the demand for job training and its interaction with organization
adjustments through rotation within a team and relocation across teams in response to
demand and supply shocks. The analysis includes estimations of determinants of on-thejob training, and of how much such training contributes to improvements in individual
productivity. We employ original assembler survey data from two Japanese automobile
makers. We also investigate effects of the characteristics of workplace practices,
including the behavior of foremen, on the incentives for individual assemblers to seek
job training and productivity improvements.
Key words: Job training, productivity improvement, relocation, rotation, workplace
practices
JEL Classification: J24, M53

Corresponding to: ISER, Osaka University, 6-1 Mihogaoka, Ibaraki, Osaka, 567-0047, Japan. Email: sasaki@econ.osaka-u.ac.jp. The authors are grateful to the participants in the 2009 TransPacific Labor Seminar at the Japan Institute for Labour Policy and Trainings (JILPT) Kasumigaseki
Office, Tokyo, FESAM 2009, the 2009 Japanese Economic Association Meeting for their valuablecomments. We also thank the personnel departments of the two automobile makers that helped us
collect the data and allowed us to use it for this research. Any errors are of course our responsibility.
11.

Introduction
Does job training really contribute to improvements in productivity? Why do evenveteran workers keep receiving job training? Is job training useful for accomplishingmultiple tasks in response to unexpected shocks? Using original survey data from the
manufacturing establishments of two Japanese automobile firms, the purpose of thispaper is threefold. First, we investigate the continuous provision of job training,
including for veteran assemblers when each task in the assembly line is simple andeasily learnt. If this is the case, why is continuous job training necessary? Second, we
estimate the determinants of the extent and intensity of firm-level training such as onthe-job training (OJT). Finally, we consider the impact of OJT and workplaceenvironments and practices on an individual assembler’s productivity. It is, of course,
imperative to measure the costs and benefits of OJT from the viewpoint of the firm’s
human resources management strategy, to establish whether and by how muchindividual productivity improves through the provision of job training. We estimate theeffect of job training on productivity changes at the individual level using original datafrom selected establishments of two Japanese automobile makers.
The main contribution of this paper is the analysis of original survey data collectedfrom assemblers and foremen in representative Japanese automobile makers on theirsubjective assessment of productivity improvements. These data allow us to provide a
direct link between the intensity of OJT and productivity improvements. Because it isdifficult to measure objectively the extent and intensity of OJT and productivity
improvements, we use subjectively assessed measures for those variables, even thoughsome measurement error may be involved. To support its appropriateness as a measureof productivity improvement, we alternatively employ the change in the number ofoperational tasks that assemblers can perform satisfactorily as evaluated by theirforeman. According to the factory director interviewed, assemblers usually assessed
their own productivity improvements when responding to the survey questionnaire interms of an increase in the number of operational tasks they could perform. However,the data on operational tasks were available only from a single automaker in the third
wave of the survey. Nevertheless, while the original data have some disadvantages, theyalso have several redeeming qualities. For instance, many economists and businessacademics have long been suspicious that older workers with long tenure in Japanese
automakers remain engaged in job training, despite the fact that the operations theyusually perform are simple and do not take a long time to learn.1 Using our original data,
we are able to look inside the black box that until now concealed the effect of OJT on
productivity.
Another distinguishing feature of this study is that it explores how both thecharacteristics of teams and individuals (including the workplace environment andworkplace practices) affect the determinants of job training and the extent of
productivity improvements (if any). Changes in the workload and assembly line speed
responded to by foremen are included in the characteristics of teams, and these capture
1

A major alternative reason to provide old and veteran assemblers with training is to develop talent that
can handle “unusual operations” (Koike 1994 2002). The depth of the skill (as opposed to the width) is
such that the highest (deepest) skill involves capability to deal with accidents, machine malfunctions thatneed be resolved quickly on the spot. The “depth” enhances the team productivity by minimizing thedelay or stoppage of operation after the incidence. Unlike multiskilling, it seems there is a need for someof the assemblers in the team to have this capability.

2the extent and intensity of any demand shocks. In addition, the proposed Kaizen drafts
for job efficiency improvements and the number of quality control (QC) meetings arealso studied, and these capture the extent and intensity of any supply shocks. 2 We
predict that frequent demand and supply shocks lead to assignment changes for
assemblers through rotation within their own team and/or relocation across teams. This
provides the ongoing demand for job training for assemblers, even veteran assemblers,so they can adjust to the environmental changes. Importantly, while the literatureincludes the effects of individual characteristics on the intensity of job training, ourstudy also focuses on the interaction between individual and team characteristics.
There is some evidence suggesting that job training is highly selective, at least inOECD countries other than Japan where no systematic study yet exists. Using Thai data,
Ariga and Brunello (2006) found that while off-the-training (OffJT) and education werecomplements, OJT and education were substitutes. In general, training is most intensivein the early stages of an assembler’s career and experience. Some studies found very
high returns to job training, but these were likely to suffer from selection bias. In fact,
and as pointed out by Leuven and Oosterbeek (2005), past studies have relied on datacollected from highly heterogeneous workplaces that they likely fail to control. Using
original data from the manufacturing establishments of two Japanese automobile
makers, we investigate the types of job training provided in the various career stages.
Further, as our unique survey includes assemblers within the same establishment, we do
not potentially suffer from the selection bias found elsewhere.
The paper is organized as follows. The next section discusses how an automobile
establishment adjusts to demand and supply shocks, why organization adjustments arenecessary, and why organization adjustments frequently occur in the Japanesemanufacturing sector. Section 3 explains the data, followed by descriptive statistics forjob training and subjectively and objectively assessed productivity in Section 4. Section
5 discusses the econometric methodology and Section 6 includes the results. Section 7
shows a simple simulation to discuss the cost and benefit of internal labor adjustments.
The final section provides some concluding remarks and future research directions.

2.

Organization Adjustments in Response to Demand and Supply Shocks
Why is job training continuously provided, even for veteran assemblers, despite
tasks in the assembly line being simple and easy to learn? This subsection explains thelinkages between unexpected productivity shocks, the provision of job training, andproductivity improvements. Figure 1 depicts these linkages.
We predict that shocks from the demand or supply side induce organization
adjustments in assembly lines, thereby increasing the demand for training. We here
focus attention on two types of organization adjustments: rotation within the same teamand relocation across teams. Rotation within the same team is defined as a transfer
between production operations in the same team; on the other hand, relocation isdefined as a broader transfer between teams but within the same establishment. 3
2

Kaizen means operational improvement in Japanese. In many manufacturing sectors, including
automobile sector, assemblers are encouraged to suggest drafts to improve efficiency in their assemblyline.
3
Assemblers usually are not transferred across establishments, but foremen are often instructed torelocate to a different establishment.

3

Hildreth and Ohtake (1998) also deal with labor demand adjustment throughorganization adjustments, using the establishment-level data from an automobile maker.
They find that this automobile maker uses two methods to adjust labor demand; the first
method is a long-term transfer indicating relocation of assemblers acrossestablishments; the second method is a short-term transfer between assembly lines andbetween production and nonproduction sectors as well as between establishments. The
short-term transfer allows the automobile maker to cope with demand fluctuation,
showing that it can adjust employment quickly and flexibly, contrary to the common
belief that labor demand adjustment is slower in Japan than in Western countries. As thispaper emphasizes within-establishment relocation, it is close to the short-term transfer
model in Hildreth and Ohtake (1998).
Why is it worthwhile to undertake organization adjustments? There are three reasons
to support them. The first is that assemblers rotate within the same teams or are
relocated to a different team to cope with demand shocks, including the business cycle,
seasonal adjustments and establishment-level shocks. Demand shocks occur regularly
for a host of different reasons. Organization adjustments occur more or lesscontinuously, as one model is experiencing growing demand, whereas others’ market
share is declining. 4 Fads concerning choice of color are also evident in Japan. There
was a time when every new car was white, and then black was the most popular color,then light blue, shiny pink, and so on. More (fewer) assemblers are located in theassembly line to cope with the increased (decreased) workload. Flexible organization
adjustments reduce the number of redundant assemblers and the surplus of humanresource, thereby raising production efficiency.
The second reason is that assemblers are relocated to a new team and receive job
training beforehand, so they can perform multiple tasks whenever exogenous shocks
occur in the future. Alternatively, to cope with future shocks, a foreman ex ante provides
his own assemblers with job training to perform multiple tasks through rotation within
their own team. The third reason is that the proposed Kaizen drafts encourage thereorganization of operational procedures through rotation within a team and therelocation of assemblers across teams, which leads to increases in team productivity andproduction efficiency. The proposed Kaizen drafts are the ones capturing the supply
shock.
According to Monden (1997), 5 at Toyota Motor Co.’s Tsutsumi factory, not only
assemblers but also foremen, supervisors and managers rotate within and across teams.
After they became multiskilled, job rotations among all assembly line processes
occurred every 2–4 hours. The main purpose of job rotation is to prepare for flexible
personnel arrangement in response to exogenous shocks. Monden (1997) suggests some
additional merits of job rotation, such as that it prevents assemblers from becomingbored, and that by assigning different tasks, foremen can assign assemblers acrossoperations fairly. Thus veteran assemblers are encouraged to hand down various skills
to young assemblers, and assemblers can see the whole picture of the operation process
and feel responsible for their own team’s goals, while newly assigned assemblers canaddress problems in a new operation and propose a draft Kaizen for improvements.
4

For example, buyers began to receive tax credits for buying hybrid cars or eco-friendly cars in April
2009 in Japan. Since then the demand for those cars (the Toyota Prius in particular) has been rapidly
growing.
5
See Chapter 11.

4

Channels 1 and 2 in Figure 1 represent this process.
Monden (1997) also discusses why multiskills are cultivated in Japan, but not in the
US. He points out that in US automakers, jobs are excessively classified and that thewage system is determined in each job, which encourages assemblers to specialize in asingle operation and does not give assemblers an incentive to learn a range of skills. He
finds that because of a lack of OJT, blue-collar assemblers do not have an opportunity toobtain a range of skills.
We should be aware of the cost incurred by undertaking organization adjustments.
According to Hildreth and Ohtake (1998), such adjustments incur direct and indirect
costs. The direct cost is the transaction cost involved in transfers. There are two types of
the indirect cost. The first is the efficiency loss of having an incoming assembler
assigned to a different operation process; the other is the loss of the gain that theassembler would have produced in the former operation without his/her transfer.
What the firm can do to minimize possible loss of efficiency is to provide job
training to assemblers assigned to new operations, thereby minimizing the initial
indirect cost or lowering the efficiency loss. Assemblers relocated to a new team in
response to a demand or supply shock are required to perform new tasks, and thisencourages those assemblers, even veterans, to receive job training to acquire new skills.
Channel 3 in Figure 1 represents this process. In a similar manner, the need for job
training arises when an assembler rotates to work on new operations within their own
team.
Assemblers provided with job training acquire new skills and should then assess
their improvements in productivity. Channel 4 in Figure 1 represents this process.
However, even though relocated assemblers provided with job training acquire newskills, because they no longer employ the skills used in the previous team, they may
subjectively assess a low productivity gain.

3.

Characterization of the Survey
We conducted unique surveys of the manufacturing establishments of two different
Japanese automobile makers, referred to as Firm A and Firm B to preserve anonymity.
The two firms are typical of other automobile makers listed on the First Section of theTokyo Stock Exchange. The two firms have establishments in Japan and abroad. Eachestablishment is an independent production unit, producing several different products
under the “just-in-time” production system. We completed three waves of the survey forboth Firm A and B, so that we have two sets of panels for assemblers and foremen. The
distinguishing feature of the surveys is that they cover both assemblers who worked in
the assembly line and their foremen, and that both assemblers and foremen subjectively
assessed the extent of productivity improvements at the individual level. 6 This allows us
to estimate directly the impact of various types of job training on productivity
improvements at the individual level.
We conducted the first wave of the survey of manufacturing establishments for Firm
A in September 2006, with the second and third waves carried out in May 2007 andMay 2008, respectively. We collected valid responses from 22 foremen and 100
6

The wage level is used as an alternative variable indicating the extent of individual productivity toidentify the effect of training on individual productivity (Kawaguchi 2006, Yoshida 2004).

5

assemblers in the first wave, 23 foremen and 95 assemblers in the second wave, and 17
foremen and 101 assemblers in the final wave. During this time, the entire auto industry
was operating at peak capacity, with Firm A especially in constant need of temporary
workers. The firm was chronically short of labor, hiring so many temporary workers
that regular full-time workers needed to devote much of their time to teaching theseirregular workers, and so lacked any spare time to train themselves. It therefore appears
conceivable that the sample period is somewhat unusual in terms of the heavy
workloads and the large share of untrained irregular workers. It should also be of somerelevance that the sample establishment in the Firm A survey has plans in the near future
to undergo a very fundamental and thorough redesign and retooling of its production
line. This may also have had some impact on work allocation, as well as theassignments of regular assemblers and foremen. The survey targeted only full-time
employees.
In a similar manner, we conducted consecutive yearly surveys of the manufacturing
establishment of Firm B in October 2007, October 2008, and October 2009. The firstwave collected valid responses from 27 foremen and 140 assemblers belonging to oneof the assembly teams under the supervision of foremen in the manufacturing
establishment. The second wave collected information from 26 foremen and 139
assemblers working in the same establishment. For the third and the last, we collected
data from 24 foremen and 127 assemblers.
The assembler’s questionnaire consisted of 20 questions classified into four
categories. 7 These are: (1) the extent of individual-level training intensity (OJT, OffJT,
and self-development); (2) the extent of productivity improvements, the acquisition ofskills, and the number of fully fledged operational processes that one can perform; (3)the number of proposed Kaizen drafts for job efficiency improvement; and (4)evaluation of one’s own foreman, workplace environment, and practices. Meanwhile,the questionnaire for foremen consisted of nine questions on the workplace environment
and practices in their assembly team, the number of quality control (QC) meetings, andthe productivity improvements in their own team.
It is technically difficult to measure productivity improvement per assembler, so we
asked for its subjective measurement over the past year. 8 The survey asked the sample
assemblers the following question: “Assuming that your current work proficiency is 100
and that your productivity immediately after you joined the firm and were assigned to aworkplace was zero, what do you think your proficiency level was six months and one
year ago?” In response, assemblers were required to choose from the following fivecategories: (1) 100–95, (2) 95–90, (3) 90–85, (4) 85–80, and (5) less than 80. 9 We used
this as a proxy measure of the individual productivity improvement. 10
7

The questionnaires for both an assembler and a foreman are atahced in Appendix.
Krueger and Rouse (1998) also use subjective data to measure the extent and intensity of individual
productivity and then estimate the effects of corporate training consisting of basic skills development,
including reading, writing, and mathematics.
9This survey rules out the possibility that an assembler perceives that productivity has deteriorated during
the past year. We justify this on the basis that human capital accumulates year by year through job
training and barely depreciates in the short run.
10
The sampled foremen were also questioned about the improvement in productivity in their own team ina subjective way as follows: “If the productivity of your workplace 12 months ago was 100, what do you
think the productivity levels were 6 months ago and today?” In response, the foremen were to fill in any
number, implying productivity improvements if the number exceeded 100, otherwise a productivity
86

To complement the subjective measure of individual productivity, we alternatively
used the extent of how many operational tasks an assembler had newly acquired overthe past year. We consider assemblers who can acquire additional operational tasks as
those accomplishing productivity improvements at the individual level.11 Because it is
not difficult for assemblers to count the number of operational tasks they can perform
satisfactorily, we regard this variable as an objective measure with little measurement
error. Unfortunately, we could obtain the data on operational tasks only from the third
wave of the survey from Firm B. The factory director of Firm B told us that assemblers
measured their own productivity improvement based on the increase in the number ofoperational tasks approved by their own foreman. A table of accomplished operationaltasks was prepared for all assemblers and posted on the bulletin board, so everyone
understood who had acquired new tasks and how many. We presume from the factory
director’s evidence that the subjective assessment of productivity improvement isassessed from this objective measure of the operational tasks.
We collected data on the extent of various types of job training, including OJT,OffJT and self-development. Due to limited space, however, we restrict ourselves to theextent and intensity of OJT and its effect on improvements in productivity at theindividual level. Measuring the intensity of individual-level OJT is subjective and selfexplanatory in this study, while tenure or years of service has hitherto been a proxy
indicating the extent of training, on the assumption that assemblers in the workplace areprovided with training. 12 We asked assemblers several questions concerning OJT
intensity. 13 The OJT dummy took a value of one if an assembler responded with
nonzero hours for OJT in the previous month or if the assembler responded that there
was less OJT than usual, even if the category including zero OJT hours in the previous
month was chosen; otherwise zero. We capture the provision of OJT in the broad sensethat assemblers spent time in OJT over the past year, even though they did not receive
any in the previous month. We calculate the hours spent in OJT by multiplying the hours
of OJT in the past month by 12. We then divide by 2.5, 1.5, 1, 0.5, or 0.33 if theassembler responded that the hours of OJT in the previous month were more thandouble, one and a half times, the same amount, about half, or less than half the average,
respectively.
However, we need to remind ourselves that these methods cannot accurately
measure the extent and intensity of OJT. Because it is difficult for assemblers to identify
correctly those job activities considered to be OJT, it is less likely that assemblers areable to measure the frequency and length of OJT accurately, and this leads tomeasurement error. We also gathered data on demographic and individual characteristics,
including age, tenure, education, and duty position. We merge the surveys for foremen
and assemblers to estimate the impact of workplace environment and practices on

decline. Because we focus on the impact on an individual employee’s productivity, we preclude theanalysis of team productivity in this research.
11
Note that an operational task is different from an operational process in that one operational process
comprises multiple operational tasks.
12
In a similar manner, Kurosawa (2001) collected explicit data on the extent of intensity of training from
44 establishments in Kitakyushu City, Fukuoka between 1993 and 1994.
13
We asked: how many hours of OJT did you receive in the last month; who provided the OJT (either
colleagues or foremen) and how much; and whether they participated in OJT voluntarily or under
instructions from their own foreman.

7individual productivity. 14

4.
Data Analysis
a. Organization Adjustments (Channels 1 and 2)
We begin with Channels 1 and 2 as depicted in Figure 1. Figure 2 shows therelationship between the number of assemblers within a team and the assembly line
speed, as evaluated by the sampled foremen. Assembly line speed is considered as oneof the proxies capturing the extent of the demand shock. This analysis also includes datafrom both Firm A and B. As shown, the number of assemblers increases in a team when
the speed of the assembly line also increases, while the number of assemblers decreases
in a team with a low assembly line speed. Assemblers were then relocated from theslack team to the busy team to meet the increasing product demands. This implies that
assemblers are located across teams efficiently and flexibly in response to frequently
arriving shocks. In a similar manner, Figure 3 shows the relationship between thenumber of assemblers within a team and the workload of the team as evaluated by the
sampled foremen. The workload is one indication of the extent of the demand shock. As
shown, the number of assemblers increases in a team where the workload increases, but
is cut in a team where the workload decreases. This strengthens the view that
assemblers are transferred from slack teams into busy teams to cope with frequent
demand changes.
We now explore exactly who is relocated across teams through organization
adjustments in response to these demand and supply shocks, using the data of individual
assemblers. We predict that assemblers relocated to a different team are more likely toreceive job training because they must now perform different tasks. Figures 4–6 show
differences in the average age, tenure within the firm, and skill level accredited by theirown company for assemblers relocated to different teams and those who are not.
According to Figure 4, the average age is higher for relocated assemblers, particularly in2007 and 2009. One possible interpretation is that older and veteran assemblers who canadjust to the environmental changes more quickly than younger assemblers are
relocated to completely different teams where their current skills are useless andtherefore, they still need to acquire new skills to engage in different operations. We
obtain almost similar results in Figures 5 and 6.
b. Training (Channel 3)
We now focus attention on whether the arrival of demand and supply shocks
encourages assemblers to receive job training, as depicted in Channel 3 in Figure 1.
Figure 7 indicates the extent of job training and its average hours using the rate ofchange in operational processes within the same team on the horizontal axis; thisgenerally shows that the higher the rate of change in operational processes within theteam, whether an increase or a decrease, the more likely assemblers are to receive OJT.
This implies that assemblers were required to receive OJT, to respond to thereorganization of their own assembly line caused by the arrival of a demand shock.
However, the null hypothesis that the OJT incidence does not vary by the rate of change
14

To be comparable, Kurosawa, Ohtake and Ariga (2005) originally collected two-period panel data from
830 randomly selected manufacturing establishments, including information on workplace practices,human resource management and training.

8

in operational processes is not significantly rejected. We obtain a roughly similar result
when we consider the association between the average hours of job training and thechange in operational processes; that is, the higher the rate of change in operational
processes within the team, the longer assemblers spend in OJT. However, again, the null
hypothesis that the average OJT hours do not differ by the rate of change in operational
processes is not significantly rejected. The extent and intensity of OJT and the rate ofchange in operational processes are apparently but not significantly associated.
We explored here whether and when assemblers relocated to a different team receive
job training. Figure 8 displays the extent and intensity of OJT, depending on the timingof the relocation across teams. We find that assemblers relocated more recently to adifferent team are more likely to receive OJT. This is perhaps because newcomers
needed to receive job training to accommodate new tasks in the assembly line. However,the difference in the timing of job training less than six months and within one year isminimal. A similar phenomenon is evident in the relationship between average training
hours and the timing of relocation. Here, assemblers relocated within six months spend
more hours on OJT than those relocated within one year.
c. Productivity Improvements (Channel 4)This subsection provides descriptive statistics of the improvement in productivity as
measured by subjective assessment. Recall that the survey requested the sampledassemblers to respond on their work proficiency of a year ago from the following fivecategories: (1) 100–95, (2) 95–90, (3) 90–85, (4) 85–80, and (5) less than 80, assumingthat the current work proficiency is 100. We then calculate the class values of work
proficiency according to a lognormal distribution function. Table 1 provides these classvalues. We consider the increase in work proficiency as a proxy for productivity
improvements.
We now explore the relationship between the improvement in individual
productivity and job training. Figure 9 displays the proportion of assemblers receiving
OJT and its average hours by category of productivity improvement. The horizontal axis
represents the categories of work proficiency of a year ago, assuming that the current
work proficiency is 100, and therefore implies that productivity improves as we movefurther away from the origin on the horizontal axis. We combine data from both firms in
Figure 9. As shown, assemblers who stayed in the lower category of work proficiency ayear ago are more likely to receive OJT. The null hypothesis that the OJT incidence
does not vary by the category of work proficiency is rejected with the level ofsignificance. However, over 80% of assemblers receive OJT, regardless of the extent ofwork proficiency. This is consistent with the practice of continuous training for any
productivity level. According to the relationship between productivity improvements
and hours spent in OJT, assemblers spend on average at least 100 hours per year in OJT.
Assemblers who perceive lower improvements in productivity (a 90–95 work
proficiency level a year ago) spend the longest hours in OJT. This could also be a formof reverse causality in the sense that those accomplishing low improvements in
productivity put more effort into job training.
We have so far not considered the direction of causality between training andproductivity; that is, either high-productivity assemblers are less likely to receive job
training or those who receive job training succeed in improving their productivity. To
control for this reverse causality, Figure 10 shows the extent of subjectively assessed

9productivity improvement by participation in OJT over the past year, using data fromboth firms. We compute the class values of current work proficiency, assuming that thework proficiency of a year ago is 100, and they are displayed in the left vertical axis.
The horizontal axis is then a one-year lagged indicator of whether to participate in job
training as of a year ago. This should take account of the reverse causality problem. As
shown, assemblers who received OJT perceived higher productivity improvements thanthose who did not. This implies that OJT is effective in raising productivity.
d. Operational Tasks (Channel 4)
To complement the subjective assessment of productivity improvement at anindividual level, we alternatively employ how many more operational tasks anassembler newly acquired over the past year. This is because we consider additional
operational tasks as productivity improvements at the individual level. This variable canalso be objective with little measurement error because both assemblers and theirforeman can correctly number the operational tasks they can sufficiently perform.
Unfortunately, the data on operational tasks are available only from the third wave of
the survey from Firm B. Whether an operational task is accomplished or not isdetermined by one’s own foreman. A table of accomplished operational tasks is postedon the bulletin board, so everyone knows who acquires how many operational tasks.
Table 2 provides the correlations between the subjectively assessed productivity
improvement and an increase in the number of operational tasks using the data from thethird wave of Firm B. As shown, assemblers acquiring more (fewer) operational tasks
respond with higher (lower) productivity improvements. This implies that the subjective
and objective measures of productivity improvement are strongly correlated. This isconsistent with the evidence provided by the factory director of Firm B, who stated in
the interview that assemblers measured their own productivity improvement based on
the increase in the number of operational tasks posted on the bulletin board whencompleting the questionnaire. We are concerned about the relationship between
productivity improvements, as measured by an increase in the number of operationaltasks, and the extent and intensity of OJT. According to Figure 11, we obtain a positive
relationship between the increase in operational tasks and the proportion of thosereceiving OJT. Looking at the relationship between the increase in operational tasks andjob training hours, assemblers who acquire more operational tasks spend more hours on
OJT at a moderate level of increase in operational tasks (about 101–150). The extent
and intensity of OJT are positively but weakly correlated with productivity
improvements with respect to the measure of operational tasks. 15
We again take into consideration the direction of causality. Figure 10 shows the
productivity improvement as measured by the increase in the number of operationaltasks and participation in job training in the previous year. The right vertical axis
represents the number of operational tasks that one can perform currently, assuming thatits number of a year ago is normalized at 100. The horizontal axis is a one-year laggedindicator of whether to participate in job training as of a year ago to take account of thereverse causality problem. Assemblers who receive OJT experience the accomplishmentof more operational tasks than those who do not, although the null hypothesis that there
15

We significantly reject the null hypothesis that the OJT incidence does not differ by an increase inoperational tasks, but cannot significantly reject the null hypothesis that the average OJT hours differ by
an increase in operational tasks.

10

is no difference of an increase in the number of operational tasks is not significantly
rejected. This partially implies that OJT is effective in improving productivity as
measured by the number of operational tasks at the individual level.

Estimations
We pool the data for each firm for estimation purposes. The appendix section showsa list of variables, their definitions and descriptive statistics. We first attempt to estimate
the relationship between the productivity shock and organization adjustments, including
rotation within the same team and relocation across teams, using the team-average data.
Here, we employ the extent of assembly line speed (speed) and the workload(workload) as variables capturing the demand shocks. Kaizen drafts suggested frominside and outside the same team (kaizen_in and kaizen_out) and change in the way of
conducting QC meetings within the same team (d_change_qc) are used as variables
capturing supply shocks. These variables are drawn from the responses in the foremen’questionnaire. The dependent variable of rotation is a categorized variable indicatingthat foremen responded that the opportunities for rotation for their own assemblers
within the team increased, remained the same, or decreased (rotation) over the year. We
specify the team-average years assigned in the current team as a dependent variableindicating the extent of relocation across teams (exp_gr).
We next use a probit model for estimating the propensity that an individual
assembler receives training while a Tobit model yields the equation for hours of training.
The dependent variable is the propensity to receive job training in the probit model (ojt)
and the censored variable of hours spent in job training in the Tobit model (ojt12).
Explanatory variables indicate individual characteristics and workplace environments
and practices. The individual characteristics include education (d_hs), tenure within thefirm (tenure), tenure within the current team (exp), and skill level (skill). The workplaceenvironments and practice include the number of operational processes in the same team(allp), its change over the year (allpdiff), whether there is an increase in opportunities
for rotation for assemblers within the same team (rotation2), a change in the way of
conducting QC meetings within the same team (d_change_qc), and the extent of OJT
for other assemblers within the same team and for all other teams (ojt_within,ojt12_within, ojt_all, and ojt12_all). 16 For these characteristics, we collectedsubjectively assessed data from assemblers and foremen. The primary focus is theeffects of rotation and relocation (as measured by tenure within the current team) on theprovision of job training. Another hypothesis is that the frequent meetings andopportunities for individual development through QC meetings and Kaizen proposals
raise assembler morale, thereby encouraging them to participate in and spend more
hours in job training.
It might be true that rotation within the same team should be treated as endogenous
because whether or not to rotate is an option determined by the foreman. To control forthe potential endogeneity of rotation within the same team, we employ two approaches
for the two-stage estimation. The first is a standard probit model with instruments; thatis, the first stage consists of an OLS estimation of the choice of rotation to derive the5.

16Note that rotation is the categorized variable while rotation2 is the dummy indicating one if an
assembler receives OJT and zero otherwise. In addition, note that exp represents tenure within the current
team while exp_gr indicates team-average years assigned in the current team.

11

predicted value, and it is then used as an instrument variable in the probit estimation of
OJT incidence and the OLS estimation of OJT duration. As the second approach, we
employ the recursive maximum likelihood method. The first stage uses a probit
estimation of the choice of rotation, and then the predicted value is included as an
instrument variable in the second stage.
Our attention now turns to the estimation of the effect of training on the
improvement in productivity at the individual level. The propensity for productivity
improvement is determined by vectors of explanatory variables reflecting individual
characteristics, the workplace environment and practices, and either a continuous
variable for training hours (ojt12) or a dummy variable taking a value of one if
assemblers received training (ojt). The dependent variable represents the likelihood of
productivity improvement with respect to either subjective or objective measurement (rrand oaskl_gr). Our principal focus is the estimated coefficient of the training variable.
Our hypothesis is that productivity improvements are positively associated with theextent and intensity of training.

6.
Resultsa. Relocation across Teams and Rotation within the Same TeamWe begin by estimating the determinants of relocation across teams and rotation
within the same team. We hypothesize that organization adjustments, such as relocation
and rotation, are caused by exogenous shocks from both the demand and supply sides,
which thereby demand that assemblers receive job training to acquire different skills.
Table 3 provides the results of the ordered probit model estimating the determinantsof rotation within the same team where the dependent variable is categorized as –1 for adecrease in rotation opportunities, 0 for unchanged and 1 for an increase in rotation
opportunities (rotation) over the past year. The assembly line speed (speed) has apositive effect on the extent of rotation within the same team at the 1% level ofsignificance in columns (1) and (3), while the workload (workload) is statisticallyinsignificant for rotation. It would then appear that to cope with demand shocks,
foremen rotate assemblers across different operations. The variables capturing supply
shocks are statistically insignificant for rotation in column (2). Foremen rotate their own
assemblers across various operations within their own teams, regardless of whether
Kaizen drafts are proposed.
Table 4 displays the results of the OLS models used to estimate the determinants ofrelocation across teams over the past year. Note that F-values are not large enough topass an F test. When the average tenure within the current team is employed as thedependent variable (exp_gr), the workload has a negative effect at the 5% level ofsignificance although the assembly line speed remains insignificant. Here, as a foreman
has a greater burden of workload in his own team, he demands the firm to increase thenumber of assemblers in his own team, and this reduces average tenure within thecurrent team. The variables capturing supply shocks remain statistically insignificant. It
thus appears that demand shocks induce organization adjustments, including relocationof assemblers across teams and rotation of assemblers within the same team.
b. Determinants of Job Training
Tables 5 and 6 display the estimated results of the probit and Tobit models for the12determinants of OJT incidence and the hours spent in OJT. We pooled data from both
firms and estimated each model. When we look closely at the factors that individuallyand significantly affect the determinants of job training and its duration, there arecertain characterizations of the workplace and the team that affect OJT incidence and its
duration for both automobile makers.
It is worth noting from column (5) in Table 5 that when the extent of rotation within
the same team (rotation2) is treated as exogenous, it has a positive effect on OJT
incidence at the 5% level of significance. This result supports the hypothesis that
assemblers are encouraged to receive OJT and acquire new skills to perform different
tasks assigned from transfers through rotation. As discussed, because organization
adjustments such as rotation within the same team are efficiently and flexibly
undertaken in response to demand shocks, assemblers receive OJT after rotation
whenever shocks occur or are expected to occur.
Columns (6) and (7) take into account the interrelation between the OJT incidence
and the rotation decision, which thus gives unbiased estimates of the effect of rotation
within the same team on OJT participation. Columns (6) and (7) display results of astandard probit model with instruments and a recursive maximum likelihood method,respectively. Similar to column (5), rotation within the same team (rotation2) remains
positively significant at the 1% level in column (6) and at the 5% level in column (7).
On the other hand, tenure within the current team (exp) is insignificant in column (6),but negative at the 10% level of significance in column (7). After controlling for theendogeneity of rotation, the results remain similar to those of column (5), which ensuresthat treating rotation as exogenous is acceptable.
According to Table 6, tenure within the current team (exp) has a negative effect on
the average hours of OJT at the 5% level in columns (4) and (5), while rotation within ateam (rotation2) is statistically insignificant for the OJT duration when rotation within ateam is treated as exogenous. This indicates that assemblers are relocated to a different
team in which the skills they have obtained are useless and they then spend more timelearning new skills through OJT. After controlling for the endogeneity of rotation, thesignificance remains unchanged in columns (6) and (7), comparable with column (5),although the magnitudes of some coefficients are different.
Looking at Table 6, the number of operational processes in a team (allp) is negative
for OJT hours at the 1% level of significance. This implies that assemblers either cannot
afford to spend time on OJT in a busy team in which there are many operational
processes or, because they operate only a few simple tasks in one operation process if
operational tasks are segmented into many operation processes, they do not need tospend time on OJT. Columns (5)–(7) in both tables indicate that the average OJT
incidence and duration of any other assembler across all teams (ojt_all and ojt12_all)are significantly negative for an assembler’s own OJT incidence and its duration. Thisimplies that one assembler receives OJT when other assemblers do not. It would thenappear that OJT is substitutable between assemblers; that is, one receives OJT while
another cannot. In contrast with our prediction, skill level and tenure within the firm arestatistically insignificant for both OJT incidence and its duration. 17

17

According to Kurosawa (2006), assemblers with shorter tenure are more likely to participate in OffJT
and self-development programs. However, the impact on the incidence of OJT is not addressed.

13

c. Does Job Training Improve Productivity?
This subsection reports the effect of job training on the improvements in subjective
and objective productivity. We estimate OLS models where the dependent variable
represents the extent of productivity improvement over the past year.
We begin with explaining the estimated results shown in Tables 7 and 8. The
incidence of job training is included in the explanatory variable vector in the former
while the duration of job training is included in the latter. Of first and foremost interest
among the dependent variables are the dummies indicating the incidence of job training
and the continuous variables for hours of job training. As shown in Table 7, theincidence of OJT (ojt) has a positive effect on improvement in productivity at the 1%
level of significance. As one would expect, this supports the hypothesis that OJT
contributes to making an individual assembler more productive from a subjective
viewpoint. This result is partially comparable with those obtained in Kurosawa (2001)
and Ariga, Kurosawa and Ohtake (2006); in the former, the effect on wages does notclearly differ by the form of training, 18 and in the latter OJT participation has an
insignificant effect on establishment-level productivity. 19 Our concern now is the effects
of OJT duration. In contrast with our prediction, OJT duration (ojt12) is statisticallyinsignificant for the improvement in productivity according to Table 8.
Some other factors affect the improvements in productivity. Tenure within thecurrent team (exp) has a significant negative effect on individual productivity
improvement at the 1% level of significance in columns (4)–(6) in both Tables 7 and 8.
Tenure within the current team, which proxies the extent of relocation across teams,
contributes negatively to the improvement in productivity directly and indirectly
through the channel of the demand for job training. The implication of the direct effectis that assemblers realize that productivity increases less proportionally with tenure
within the current team, and this is consistent with the general property of diminishingmarginal returns. This finding suggests that specialization in certain tasks in the sameteam discourages an assembler from perceiving an improvement in productivity. The
indirect effect is that assemblers who stay long in the current team do not need toreceive OJT to learn new skills, which does not raise their productivity. The
improvement in productivity assessed from a subjective viewpoint in the previous year
(rr_past) has a positive effect on that subjectively assessed in the current year at the 1%
level of significance, as shown in both Tables 7 and 8. This result implies that
assemblers who assess higher improvements in productivity in the past year tend toassess higher improvements this year. A change in the way of conducting QC meetings
over the past year (d_change_qc) is statistically insignificant, which is comparable with
Ariga, Kurosawa and Ohtake (2006) where participation in suggestion meetings has asignificantly positive effect on establishment-level productivity.
Here we examine the effect of job training at an individual level on improvements in
productivity from an objective viewpoint using the data on the operational tasks that
assemblers can sufficiently perform. Recall that the data are only available from thethird wave of the survey from Firm B. Because the sample size is small, the standard
error may be large, thereby reducing the significance of the variables. Before estimating
the effect of job training on productivity improvement as measured by the increase in
18

The exception is that the effect of formal training on wages was significantly negative for assemblers
over 45 years of age.
19
However, the effect of OffJT participation is significantly positive on establishment-level productivity.

14

the number of operational tasks, we examine the relationship between the productivity
improvements from the subjective and objective viewpoints. According to Table 9, an
increase in operational tasks is positively correlated with a subjectively assessed
improvement in productivity at the 1% level of significance. Therefore, the increase inoperational tasks can be considered an objective variable representing the improvementin productivity from a subjective viewpoint.
Tables 10 and 11 display the OLS estimates where the dependent variable iscontinuous, indicating the change in the number of operational tasks that assemblers cansufficiently perform (oaskl_gr). First, we cannot significantly reject the joint hypothesisthat the coefficients on all explanatory variables are zero according to the F test. Ourestimations thus do not explain much of the variation. Despite this, we report estimatedresults. The incidence of OJT (ojt) is statistically insignificant for an increased rate ofoperational tasks. The incidence of OJT is significantly positive for the subjectively
assessed improvement in productivity, as shown in Table 7, but insignificant in themodel where the increase in operational tasks is the dependent variable. One possible
reason is that, as discussed earlier, the small sample size may increase the standard errorof the coefficient and therefore reduce the significance. Because the estimates cover thethree waves of the survey from both Firms A and B in Table 7 while the estimates inTable 10 include only the third wave of the survey from Firm B, we cannot directlycompare the estimated results. The OJT hours (ojt12) are marginally and significantly
positive in column (1) in Table 11, but the significance reduces when including otherexplanatory variables. Accordingly, these estimations do not explain much of thevariation in Tables 10 and 11 because of the small sample size.
Although the subjectively assessed improvement in productivity and the increase inoperational tasks are statistically correlated, we have different results for the effect of
OJT incidence depending on the measure of productivity improvement used as thedependent variable. One possible interpretation is that the individual and workplacecharacteristics in the three waves for Firms A and B are different from those from thelast wave for Firm B.

Cost Effects of Organization Adjustments
This section briefly discusses a comparison of labor adjustment costs by internaltransfer (organization adjustment) with hiring/firing from the external labor market.
Table 12 shows that 32.68% and 19.86% of assemblers are on average relocated to adifferent team over one year in Firms A and B, respectively. We calculate the cost thatthe firm would have incurred if the same percentages of assemblers had been replacedby hiring or firing from the external labor market and then compare it with theadjustment cost of the internal transfer.
Table 12 shows the cost adjusted through the external labor market, normalizing thetraining cost for an internal assembler to be one, regardless of whether or not to be
relocated. The assembler size is normalized at one for simplicity. We consider cases inwhich the individual cost for job training is higher for a newly hired assembler than for
an incoming internal assembler by 10%, 25%, 50% and 100%.
In the case of 10%, Firm A would have increased its total training cost by 3.3% if
32.68% of assemblers were obtained from the external labor market. In a similarmanner with 25%, 50% and 100%, Firm A has the greater burden of training costs by
7.

15

8.2%, 16.3% and 32.7%, respectively. Firm B would also have incurred a larger burdenof training costs by hiring assemblers from the external labor market. This exercise
implies that when labor adjustment frequently and largely occurs in response to demand
shocks, labor adjustment through internal transfer such as relocation is cheaper thanlabor adjustment by hiring from the external labor market.

Concluding Remarks
It is difficult to measure the effect of job training on productivity at the individuallevel, but there is no doubt that it is very important for constructing and evaluating a job
training strategy from the viewpoint of human resource development. We collectedunique data on job training and productivity improvements from the establishments of
two Japanese automobile makers and evaluated the subjective impact of OJT on
individual productivity improvements. We investigated (1) whether OJT is continuously
provided to any assembler, even when each task is easy to learn; (2) the determinants ofthe extent and intensity of firm-level training such as OJT; and (3) the impact of training
and workplace environments and practices on subjective and objective individual
productivity improvements.
Our main findings are as follows. (1) OJT is provided to assemblers because they are
assigned different operations in which the skills they have thus far obtained become
useless through organization adjustment, including both rotation within the same teamand relocation to a different team. (2) Organization adjustments are undertaken in
response to productivity shocks. (3) Assemblers who receive OJT perceive their gains in
productivity from a subjective viewpoint. Another finding is that older and veteranassemblers are more likely to be relocated to a different team because they adapt tochange more quickly than do the young, implying that even older and veteranassemblers need to receive job training to perform different tasks following relocation.
Unfortunately, endogeneity of the choice of OJT complicates our estimation strategy.
For instance, when there is a negative productivity shock, firms may opt to increase
their investment in OJT as the opportunity cost of these activities has declined. If true,
the impact of training hours tends to be underestimated. To correct for this endogeneity
problem, we attempted to estimate a model with a set of instrumental variables, but
none of the variables was significant. As a result, the estimated model itself lost
significance. It is also problematic that the period within which we are measuring theimpact of training activities on productivity is too short, so we cannot capture a longterm effect of OJT on productivity improvements. Those are our future research
directions.
8.

References
Ariga, Ken, and Giorgio Brunello. 2006. “Are Education and Training always
Complements? Evidence from Thailand,” Industrial and Labor Relations Review,Vol. 59, No. 4, pp. 613–629.
Hildreth, Andrew K.G., and Fumio Ohtake. 1998. “Labor Demand and the Structure of
Adjustment Costs in Japan,” Journal of the Japanese and International
Economics, Vol. 12, No. 2, pp.131-50.

16

Kawaguchi, Daiji. 2006. “The Incidence and Effect of Job Training among Japanese
Women,” Journal of Economy and Society, Vol. 45, No. 3, pp. 469–477.
Koike, Kazuo. 1994. “Learning and Incentive Systems in Japanese Industry,” In
Masahiko Aoki and Ronald Dore, ed., The Japanese Firm, pp. 41–65, Oxford:
Clarendon Press.
Koike, Kazuo. 2002. “Intellectual Skills and Competitive Strength: Is a Radical Change
Necessary?” Journal of Education and Work, Vol. 15, No. 4, pp. 391–408.
Krueger, Alan and Cecilia Rouse. 1998. “The Effect of Workplace Education on
Earnings, Turnover, and Job Performance,” Journal of Labor Economics, Vol. 16,
No. 1, pp. 61–94.
Kurosawa, Masako. 2001. “The Extent and Impact of Enterprise Training: The Case of
Kitakyushu City,” Japanese Economic Review, Vol. 52, No. 2, pp. 224–242.
Kurosawa, Masako. 2006. “The Determinants of Participation in OJT and Off-JT,”
Japan Institute for Labour Policy and Training Material Series, No. 13, pp. 36–
55.
Kurosawa, Masako, Fumio Ohtake, and Ken Ariga. 2005. “Productivity, Training, andHuman Resource Management Practices—Disentangling Complex Interactions
using a Survey of Japanese Manufacturing Firms,” Discussion Paper No. 062,
Kyoto Institute of Economic Research, Kyoto University.
Leuven, Edwin, and Hessel Oosterbeek. 2005. “An Alternative Approach to Estimating
the Wage Returns to Private-Sector Training,” Discussion Paper No. 061, Kyoto
Institute of Economic Research, Kyoto University.
Monden, Yasuhiro. 1997. Toyota Production System: An Integrated Approach to Just-InTime, Third Edition, Norcross, Georgia: Engineering & Management Press.
Yoshida, Keiko. 2004. “An Empirical Analysis of the Impact on Wages of Workers’
Self-Development,” Japanese Journal of Labour Studies, No. 532, pp. 40–53 (inJapanese).

17

Table 1: Distribution of improvement of productivity with a subjective viewpoint
response

Total

Firm A

Firm B

1 95～100

149(21.88) 40(13.61) 109(28.17)

2 90～95

159(23.35) 66(22.45) 93(24.03)

3 85～90124(18.21) 63(21.43) 61(15.76)

4 80～85103(15.12) 53(18.03) 50(12.92)

5 ～80

146(21.44) 72(24.49) 74(19.12)

The categories represent productivity level of one year ago, assuming that the current productivity
level is 100.

Table 2: Correlation between productivity improvement with a subjective
viewpoint and an increase in operational tasks that an assembler can perform
Operational tasks

Productivity
improvement

～80

Total

95～100

90～95

85～90

80～85

95～100

12

0

1

1

3

17

90～95

7

1

1

1

7

17

85～90

6

0

2

0

9

17

80～85

4

0

0

0

8

12

～80

0

1

0

0

23

24

29

2

4

2

50

87

Total

The third wave of the survey from Firm B was used.
The horizontal categories indicate the number of operational tasks that one could perform one year
ago, assuming that the current number is normalized 100. On the other hand, the vertical categories
represent productivity level of one year ago, assuming that the current productivity level is 100.

18

Table 3: Determinants of rotation
Coefficient

p value

Coefficient

p value-0.247 [0.268]

Coefficient

p valued_firma-0.147 [0.519]-0.153 [0.522]

Speed

0.399 [0.002]***

0.394 [0.002]***Workload-0.04 [0.807]

0.017 [0.921]

Injury0.084 [0.669]

0.009 [0.963]

kaizen_in

0.258 [0.432]

0.313 [0.349]

kaizen_out-0.236 [0.324]-0.175 [0.482]

d_change_qc

0.109 [0.674]

0.087 [0.751]

obs = 118

obs = 116

obs = 114

LR chi2(4) = 11.810

LR chi2(4) = 3.230

LR chi2(7) = 13.140

Prob > chi2 = 0.019

Prob > chi2 = 0.520

Prob > chi2 = 0.069

Pseudo R2 = 0.054

Pseudo R2 = 0.015

Pseudo R2 = 0.061*** 1%, ** 5%, * 10% significance. The dependent variable (rotation) is categorized as -1 fordecease, 0 for unchanged and 1 for increase conducted to foremen. The ordered probit estimation
method is employed.

Table 4: Determinants of relocation
Coefficient

p value

Coefficient

p value

Coefficient

p valueConstant

6.197 [0.000]***5.171 [0.000]***5.681 [0.000]***d_firma-0.936 [0.092]*-1.261 [0.030]**-1.139 [0.047]**

Speed-0.102 [0.735]-0.005 [0.987]

Workload-0.829 [0.036]**-0.843 [0.040]**

Injury-0.414 [0.380]-0.551 [0.261]

kaizen_in

0.675 [0.434]

0.39 [0.630]

kaizen_out

0.695 [0.264]

0.616 [0.299]

d_change_qc

0.005 [0.994]

0.295 [0.640]

obs = 117

obs = 115

obs = 113

F(4, 112) = 1.990

F(4, 110) = 1.560

F(7, 105) = 1.750

Prob > F = 0.101

Prob > F = 0.189

Prob > F = 0.106

R-squared = 0.066

R-squared = 0.054

R-squared = 0.104

Adj R-squared = 0.033 Adj R-squared = 0.019 Adj R-squared = 0.045*** 1%, ** 5%, * 10% significance. The dependent variable is the average tenure within the current
team (exp_gr).

19

Table 5: Determinants of OJT incidence
(1)

(2)

(3)

(4)

(5)

(6)

Coefficient p value Coefficient p value Coefficient p value Coefficient p value Coefficient p value Coefficient(7)
p value

Coefficient p value

Constant

1.966 [0.000]***1.278 [0.000]***2.147 [0.000]***2.381 [0.001]***33.22 [0.000]***41.514 [0.000]***33.566 [0.000]***d_firma-0.152 [0.371]-0.022 [0.908]-0.28 [0.262]-0.343 [0.206]-0.559 [0.074]*-0.232 [0.373]-0.579 [0.059]*

allp-0.032 [0.028]**-0.039 [0.097]*-0.048 [0.065]*-0.046 [0.105]-0.028 [0.208]-0.044 [0.107]

0.013 [0.559]

0.02 [0.424]

0.017 [0.529]-0.001 [0.944]

0.016 [0.547]

tenure0.008 [0.680]

0.002 [0.933]-0.003 [0.815]

0.001 [0.959]

skill

0.005 [0.982]

0.082 [0.717]

0.136 [0.407]

0.115 [0.599]

exp-0.032 [0.087]*-0.033 [0.100]-0.011 [0.566]-0.033 [0.094]*

rotation20.401 [0.026]**

1.594 [0.000]***0.402 [0.024]**d_change_qc-0.379 [0.187]-0.698 [0.001]***-0.315 [0.263]

ojt_within

0.231 [0.705]-0.589 [0.217]

0.187 [0.752]-34.292 [0.000]***-44.401 [0.000]***-34.683 [0.000]***

allpdiff-0.009 [0.634]

ojt_all
= 317

Obs

= 291

Obs

= 285

Obs

= 287

Obs

= 305

Obs = 566

Obs = 317

Obs

LR chi2(2) = 4.88

LR chi2(2) = 0.24

LR chi2(3) = 3.03

LR chi2(6) = 6.35

LR chi2(10) = 24.23

Wald chi2(10) = 119.84 LR chi2(10) = 24.21

Prob > chi2 = 0.087

Prob > chi2 = 0.887

Prob > chi2 = 0.388

Prob > chi2 = 0.385

Prob > chi2 = 0.007

Prob > chi2 = 0.000

Pseudo R2 = 0.013

Pseudo R2 = 0.001

Pseudo R2 = 0.014

Pseudo R2 = 0.032

Pseudo R2 = 0.121

Prob > chi2 = 0.007
Pseudo R2 = 0.118*** 1%, ** 5%, * 10% significance. The dependent variable is the dummy indicating whether or not to receive OJT (OJT). The dummy variable(rotation2) is treated as exogenous in columns (1)-(5) but as endogenous in columns (6) and (7). In column (6), the first stage is an OLS estimation ofrotation, while a probit estimation is employed in the first stage in column (7). Both columns employ a probit estimation for the OJT incidence in thesecond stage. IV for rotation: d_firma, speed, workload, injury, kaizen_in, kaizen_out, d_change_qc20Table 6: Determinants of OJT hours
(1)

(2)

(3)

(4)

(5)

(6)

Coefficient p value Coefficient p value Coefficient p value Coefficient p value Coefficient p value Coefficient(7)
p value

Coefficient p value

Constant

125.909 [0.003]***49.623 [0.008]***240.455 [0.001]***

301.275 [0.002]***543.897 [0.002]***847.288 [0.012]**545.950 [0.002]***d_firma

38.4 [0.071]*

55.402 [0.027]**

2.77 [0.928]-11.165 [0.729]

13.095 [0.713]

10.307 [0.801]

13.242 [0.711]

allp-3.89 [0.042]**-8.967 [0.005]***-10.068 [0.002]***-8.577 [0.008]***-9.323 [0.010]***-8.612 [0.008]***4.68 [0.101]

5.156 [0.072]*

4.235 [0.142]

5.838 [0.400]

4.224 [0.145]

tenure0.009 [0.997]

0.259 [0.898]

1.119 [0.620]

0.251 [0.902]

d_hs-26.341 [0.608]-42.858 [0.387]-56.664 [0.297]-42.541 [0.393]

skill

13.027 [0.600]

14.056 [0.560]

11.236 [0.677]

14.455 [0.550]

exp-6.005 [0.012]**-5.378 [0.022]**-6.658 [0.036]**-5.415 [0.022]**

allpdiff-0.137 [0.952]

rotation2-22.06 [0.262]-138.303 [0.210]-22.238 [0.260]

d_change_qc-51.997 [0.129]-5.875 [0.916]-52.354 [0.128]

ojt12_within

0.169 [0.166]

0.154 [0.257]

0.167 [0.173]

ojt12_all-2.197 [0.074]*-4.068 [0.062]*-2.212 [0.073]*

Obs

= 287

Obs

= 305

Obs = 565

Obs = 317

Obs = 317

Obs = 311

Obs = 305

LR chi2(2) = 14.380

LR chi2(2) = 4.940

LR chi2(3) = 13.010

LR chi2(7) = 21.220

LR chi2(11) = 30.580 Wald chi2(11) = 28.11 LR chi2(11) = 30.56

Prob > chi2 = 0.001

Prob > chi2 = 0.084

Prob > chi2 = 0.005

Prob > chi2 = 0.004

Prob > chi2 = 0.001

Pseudo R2 = 0.002

Pseudo R2 = 0.002

Pseudo R2 = 0.004

Pseudo R2 = 0.006

Pseudo R2 = 0.009

Prob > chi2 = 0.003

Prob > chi2 = 0.001
Pseudo R2 = 0.010*** 1%, ** 5%, * 10% significance. The dependent variable is the OJT duration (OJT12). The dummy variable (rotation2) is treated as exogenous incolumns (1)-(5) but as endogenous in columns (6) and (7). In column (6), the first stage is an OLS estimation of rotation, while a probit estimation is
employed in the first stage in column (7). Both columns employ an OLS estimation for the OJT duration in the second stage.
IV for rotation: d_firma, speed, workload, injury, kaizen_in, kaizen_out, d_change_qc
21Table 7: Determinants of productivity improvement -subjective viewpoint (independent variables: incidence of job training)(1)
Coefficient(2)
p value

Coefficient(3)
p value

Coefficient(4)
p valuep value

Coefficient(5)
p value

Coefficient(6)
p valuep valueConstant

109.871 [0.000]***109.587 [0.000]***70.595 [0.000]***77.807 [0.000]***77.844 [0.000]***341.929 [0.002]***d_firma

3.116 [0.000]***2.189 [0.125]

1.272 [0.350]

0.593 [0.676]

0.622 [0.663]

7.873 [0.018]**

ojt

4.255 [0.001]***

6.223 [0.001]***5.496 [0.002]***

5.697 [0.001]***

5.662 [0.002]***5.639 [0.001]***

allp-0.058 [0.684]-0.015 [0.913]-0.09 [0.517]-0.084 [0.550]-0.089 [0.532]

allpdiff

0.027 [0.844]-0.071 [0.595]-0.047 [0.724]-0.055 [0.686]-0.047 [0.734]

0.341 [0.000]***0.304 [0.000]***0.304 [0.000]***0.298 [0.000]***tenure-0.07 [0.452]-0.071 [0.447]-0.082 [0.378]

d_hs

0.353 [0.871]

0.273 [0.901]

0.106 [0.961]

skill

0.398 [0.716]

0.427 [0.699]

0.547 [0.619]

exp-0.3 [0.005]***-0.302 [0.004]***-0.343 [0.001]***-0.395 [0.788]-0.325 [0.825]

rr_pastd_change_qc
rr_within-0.134 [0.182]

rr_all-2.181 [0.022]**
Obs = 680

Obs = 311

Obs = 305

Obs = 301

Obs = 301

Obs = 300

F(2, 677) = 13.54

F(4, 306) = 4.25

F(5, 299) = 11.51

F(9, 291) = 7.54

F(10, 290) = 6.77

F(12, 287) = 6.38

Prob > F = 0.000

Prob > F = 0.002

Prob > F = 0.000

Prob > F = 0.000

Prob > F = 0.000

Prob > F = 0.000

R-squared = 0.039

R-squared = 0.053

R-squared = 0.161

R-squared = 0.189

R-squared = 0.189

R-squared = 0.211

Adj R-squared = 0.036

Adj R-squared = 0.040

Adj R-squared = 0.147

Adj R-squared = 0.164

Adj R-squared = 0.161

Adj R-squared = 0.178*** 1%, ** 5%, * 10% significance. The dependent variable is rotation.

22

Table 8: Determinants of productivity improvement - subjective viewpoint (independent variables: hours of job training)(1)
Coefficient(2)
p value

Coefficient(3)
p value

Coefficient(4)
p value

Coefficient(5)
p value

Coefficient(6)
p value

Coefficient

p valueConstant

113.702 [0.000]***115.292 [0.000]***75.038 [0.000]***83.022 [0.000]***83.05 [0.000]***337.04 [0.002]***d_firma

3.092 [0.000]***1.858 [0.199]

0.957 [0.487]

0.234 [0.871]

0.286 [0.843]

7.245 [0.033]**

0.004 [0.202]

0.003 [0.415]

0.001 [0.641]

0.001 [0.690]

0.001 [0.833]

allp-0.082 [0.570]-0.041 [0.763]-0.127 [0.370]-0.118 [0.411]-0.129 [0.373]

allpdiff

0.037 [0.793]-0.061 [0.654]-0.031 [0.818]-0.044 [0.749]-0.034 [0.808]

0.348 [0.000]***0.313 [0.000]***0.313 [0.000]***0.309 [0.000]***tenure-0.066 [0.485]-0.068 [0.476]-0.08 [0.396]

d_hs-0.155 [0.944]-0.289 [0.897]-0.484 [0.828]

skill

0.43 [0.700]

0.479 [0.670]

0.594 [0.596]

exp-0.321 [0.003]***-0.324 [0.003]***-0.369 [0.001]***-0.654 [0.665]-0.635 [0.673]

ojt12

0.00005 [0.963]

rr_pastd_change_qc
rr_within-0.148 [0.148]

rr_all-2.078 [0.033]**
Obs = 679

Obs = 311

Obs = 305

Obs = 301

Obs = 301

Obs = 300

F(2, 676) = 7.84

F(4, 306) = 1.76

F(5, 299) = 9.36

F(9, 291) = 6.18

F(10, 290) = 5.57

F(12, 287) = 5.34

Prob > F = 0.000

Prob > F = 0.137

Prob > F = 0.000

Prob > F = 0.000

Prob > F = 0.000

Prob > F = 0.000

R-squared = 0.023

R-squared = 0.023

R-squared = 0.135

R-squared = 0.161

R-squared = 0.160

R-squared = 0.182

Adj R-squared = 0.020

Adj R-squared = 0.010

Adj R-squared = 0.121

Adj R-squared = 0.135

Adj R-squared = 0.132

Adj R-squared = 0.148*** 1%, ** 5%, * 10% significance. The dependent variable is rotation.

23

Table 9: Subjective and objective productivity
Coefficient

p value

Coefficient

p valueConstant

109.373 [0.000]***105.683 [0.000]***oaskl_gr

0.016 [0.000]***0.016 [0.000]***tenure-0.295 [0.055]*

d_hs

7.821 [0.020]**skill

0.903 [0.610]

exp-0.211 [0.210]
Obs = 95

Obs = 92

F(1, 93) = 18.830

F(5, 86) = 6.150

Prob > F = 0.000

Prob > F = 0.000

R-squared = 0.168

R-squared = 0.264

Adj R-squared = 0.160

Adj R-squared = 0.221*** 1%, ** 5%, * 10% significance. The dependent variable is productivity
improvement with a subjective viewpoint (rr).

24

Table 10: Determinants of a change in the number of operational tasks (independent variables: incidence of job training)(1)
Coefficient(2)
p value

Coefficient(3)
p value

Coefficient(4)
p value

Coefficient

p valueConstant

101.786 [0.265]-56.909 [0.713]-155.65 [0.380]-209.694 [0.231]

ojt

64.034 [0.499]

68.482 [0.483]

73.892 [0.304]

73.186 [0.294]

tenure6.935 [0.117]-4.342 [0.230]-4.166 [0.235]

d_hs

104.093 [0.280]

118.773 [0.088]*

103.543 [0.127]

skill

7.971 [0.878]

75.092 [0.065]*

81.032 [0.042]**exp-7.082 [0.152]-1.097 [0.794]-0.335 [0.935]

allp

3.437 [0.441]

6.432 [0.165]

allpdiff-6.449 [0.130]-6.601 [0.111]

d_change_qc-101.260 [0.059]*
Obs = 95

Obs = 92

Obs = 51

Obs = 51

F(1, 93) = 0.46

F(5, 86) = 1.41

F(7, 43) = 1.13

F(8,42) = 1.52

Prob > F = 0.500

Prob > F = 0.230

Prob > F = 0.366

Prob > F = 0.179

R-squared = 0.005

R-squared = 0.076

R-squared = 0.155

R-squared = 0.225

Adj R-squared = -0.006

Adj R-squared = 0.022

Adj R-squared = 0.017

Adj R-squared = 0.077*** 1%, ** 5%, * 10% significance. The dependent variable is an increase in the number of operational tasks (productivity improvement with an objective
viewpoint).

25

Table 11: Determinants of a change in the number of operational tasks (independent variables: hours of job training)(1)
Coefficient
Constant(2)
p value

Coefficient(3)
p value

Coefficient(4)
p value

Coefficient

p value

138.568 [0.000]***-5.450 [0.961]-30.202 [0.854]-82.356 [0.611]

0.232 [0.096]*

0.228 [0.107]-0.034 [0.787]-0.039 [0.746]

tenure6.525 [0.135]-4.850 [0.186]-4.684 [0.188]

d_hs

115.825 [0.226]

109.553 [0.132]

93.427 [0.187]

skill-0.090 [0.999]

71.066 [0.083]*

77.039 [0.054]*

exp-7.790 [0.107]-2.326 [0.577]-1.573 [0.698]

allp2.164 [0.650]

5.111 [0.296]

allpdiff-5.599 [0.204]-5.708 [0.182]

ojt12

d_change_qc-101.956 [0.060]*
Obs = 95

Obs = 92

Obs = 51

Obs = 51

F(1, 93) = 2.83

F(5, 86) = 1.87

F(7, 43) = 0.96

F(8, 42) = 1.36

Prob > F = 0.096

Prob > F = 0.108

Prob > F = 0.473

Prob > F = 0.242

R-squared = 0.030

R-squared = 0.098

R-squared = 0.135

R-squared = 0.206

Adj R-squared = 0.020

Adj R-squared = 0.046

Adj R-squared = -0.006

Adj R-squared = 0.055*** 1%, ** 5%, * 10% significance. The dependent variable is an increase in the number of operational tasks (productivity improvement with an objective
viewpoint).

26

Table 12: Comparison of labor adjustment costs from internal transfers and external labor markets
Firm A

FirmB

Total

relocated

32.68%

19.86%

25.17%

non-relocated67.32%

80.14%

74.83%

internal adjustment

external adjustment

internal adjustment

external adjustment

internal adjustment

external adjustment

10%

1

1.033

1

1.020

1

1.025

25%

1

1.082

1

1.050

1

1.063

50%

1

1.163

1

1.099

1

1.126

100%

1

1.327

1

1.199

1

1.252

The size of assemblers is normalized one. The cost of training is assumed to be one for an internal assembler, regardless of whether she/he is relocatedfrom a different team or remains in the current team. Therefore, the total cost of training is normalized to be one for internal labor adjustments.

27

Figure 1: Chart of demand of job training and its impact on productivity

Figure 2: Change in the number of assemblers within a team by the assembly line
speed
100%
80%
60%
Increased
40%

Same
Decreased

20%
0%
SlowerSame

FasterChanges in the line speed (compared to 12 months ago)

Figure 3: Change in the number of assemblers by the burden of workload within a
team
100%
80%
60%
Increased

40%

Same
20%

Decreased

0%
Decreased

Same

Increased

Changes in the workload in the entire workplace(compared to 12 months ago)28

Figure 4: Average age of assemblers relocated to a different team over the past 12
months
40
35
30

age

25
20

No change

15
Change team within 12
months

10
5
0
2006

2007

2008

2009

year

The 2007 and 2008 data are from both Firm A and B. However, the 2006 data are only from Firm A
while the 2009 data are only from Firm B. Test for difference=0: 2006: t(100) = 1.347 , p = 0.181,
2007: t(233) = -3.125, p = 0.00, 2008: t(235) = -0.626, p = 0.532, 2009: t(124) = -2.155, p = 0.033

Figure 5: Average tenure within the firm of assemblers relocated to a different
team over the past 12 months
20

tenure15

10

No change

5

Change team within 12
months

0
2006

2007

2008

2009

year

The 2007 and 2008 data are from both Firm A and B. However, the 2006 data are only from Firm A
while the 2009 data are only from Firm B. Test for difference=0: 2006: t(100) = 1.831, p = 0.070,
2007: t(233) = -3.346, p = 0.001, 2008: t(235) = -1.342, p = 0.181, 2009: t(124) = -2.249, p = 0.026

29

Figure 6: Average skill level of assemblers relocated to a different team over the
past 12 months
3

skill

2
No change
1

Change team within 12
months

0
2006

2007

2008

2009

year

The 2007 and 2008 data are from both Firm A and B. However, the 2006 data are only from Firm A
while the 2009 data are only from Firm B., Test for difference=0: 2006: t(99) = 1.182, p = 0.240,
2007: t(232) = -2.974, p = 0.003, 2008: t(232) = -2.531, p = 0.012, 2009: t(120) = -1.099, p = 0.274

Figure 7: Incidence and average hours of job training by a change in the numberof operation processes within a team
160

100%

140
80%

120
100

60%

80

%
40%

60
40

20%

h
incidence of OJTAverage hours of OJT

20
0%

0

Test for difference=0: Incidence of OJT: F(8, 308) = 0.59 p= 0.790, Average. Hours of OJT: F(8,308) = 0.43, p = 0.90530Figure 8: Incidence and average hours of job training by the timing of relocation
across teams
100%

180
160

80%

140
120

60%

100

%

80

40%

h
Incidence of OJT

60

Average hours of OJT

40

20%

20
0

0%
within 6
monthswithin 12
monthswithin 2
years

othersTest for difference=0: Incidence of OJT: F(3, 689) = 3.32, p = 0.019, Average hours of OJT: F(3,685) = 3.13 p= 0.025

Figure 9: Incidence and average hours of job training by productivity
improvement
100%

180
160

80%

140
120

60%

100

%

80

40%

60

h

Incidence of OJTAverage hours of OJT

40

20%

20
0%

0
95～100 90～95

85～90

80～85

～80

The horizontal categories represent productivity level a year ago, assuming that the current
productivity is 100. Test for difference=0: Incidence of OJT: F(4, 675) = 3.90, p =0.004, Average
hours of OJT: F(4, 671) = 1.28, p = 0.276

31

Figure 10: Improvement of productivity and an increase in operational tasks by
one-year lagged incidence of training
120

180
160
140

115

120
100

110

80

Improvement of productivity

60
105

An increase in operational tasks

40
20

100

0
No

Yes
OJT_past

The left vertical axis represents the current productivity level, assuming that productivity level of ayear ago is 100, while the right vertical axis indicates the number of operational tasks that one cancurrently perform, assuming that its number of a year ago is normalized 100. Test for difference=0:
Improvement of productivity: t(307) = -2.436, p = 0.015, An increase in operational tasks: t(69) =-0.929, p = 0.356

Figure 11: Incidence and average hours of job training by an increase inoperational tasks (100=no change in the number of operational tasks)
160

100%

140
80%

120
100

60%

80

%
40%
20%

h

60

Incidence of OJT

40

Average hours of OJT

20
0

0%
～99

100

(7)

(26)

101～150 151～200
(21)

(10)

201～
(10)

The horizontal axis indicates categories of the number of operational tasks that one can currently
perform, assuming that its number of a year ago is normalized 100. Test for difference=0: Incidenceof OJT : F(4,69) = 2.39, p = 0.059, Average hours of OJT: F(4,69) = 0.96, p = 0.437

32Appendix: Definitions of Variables
Variables
rotation

exp_grexp

change in rotation conducted to foremen, -1(decrease) 0 (unchanged)
1(increase)change in rotation conducted to foremen, 0 (decrease or unchanged)
1(increase)team-average years assigned in the current teamtenure within the current teaminjuryworkload
speed

the number of absentees in a team, -1(decrease) 0 (same) 1(increase)the burden of workload in a team, -1(decrease) 0 (same) 1(increase)assembly line speed in a team, -1(decrease) 0 (same) 1(increase)kaizen_in
kaizen_out
d_change_qc

the kizen draft proposed within the team raises efficiency =1
the kizen draft proposed from outside of the team raises efficiency =1
change in the way conducting the Quality Control circle =1

allp
allpdiff

the number of operation processes in own teama change in the number of operation processes in own teamtenureskill
d_hs

Tenure within the firmskill level
education level, high school or above=1

ojt
ojt12
ojt_within

dummy indicating whether to receive OJT in the conducted month=1
OJT hours in the past one year
team-average of the dummy indicating whether to receive OJT, except
a person self
all sampled average of the dummy indicating whether to receive OJT,
except a person self
team-average of OJT hours, except a person self
all sampled average of OJT hours, except a person self

rotation2

ojt_allojt12_within
ojt12_allrrrr_pastoaskl_gr

improvement in productivity from a subjective viewpoint
improvement in productivity from a subjective viewpoint in the pastyear
team-average improvement in productivity from a subjective
viewpoint
all sample average improvement in productivity from a subjective
viewpointa change in the number of operational tasks from Firm B

d_firmaDummy indicating Firm A=1 and Firm B=0.

rr_withinrr_allVariable_past represents one-year lagged one of each variable.
33

Appendix: Descriptive Statistics
variables

N

mean

SD

rotation

577

0.414

0.637

expchange_gr
exp_grexp
injuryworkloadspeedkaizen_in
kaizen_out
d_change_qc
allp
allpdiffprprdifftenureskill2
d_hs
ojt
offjt
selfdev
ojt12
offjt12
selfdev12
ojt_within
ojt_allojt12_within
ojt12_allrroaskl_gr

712
709
688
566
578
566
555
557
566
592
342
574
320
700
691
700
693
685
679
692
683
681
722
739
722
739
681
95

0.261
5.248
5.252
0.095
0.452
-0.012
0.879
0.388
0.214
18.4090.750
39.2822.515
13.537
1.754
0.937
0.905
0.488
0.171
131.899
5.803
18.2730.906
0.905
127.033130.839
115.052
161.101

0.258
2.973
5.423
0.566
0.652
0.895
0.326
0.488
0.410
6.017
6.044
30.59726.723
7.378
0.692
0.243
0.294
0.500
0.377
390.678
11.77680.6530.161
0.016
208.150
18.992
10.181
239.456

34

Appendix: Questionnaire of Assemblers

Questionnaire No.1 on Skills Developmentin the Workplace(For Employees)
September 2006
Osaka University, Institute of Social and Economic Research
Kyoto University, Institute of Economic Research〔Request for cooperation in the questionnaire〕
The purpose of this questionnaire is to survey how employees in the workplace acquire knowledge andskills required for the job, and to measure the effectiveness of these activities.
We would appreciate your taking the time from your busy schedule to answer the questionnaire withyour frank opinions. This questionnaire will be conducted 3 times in the coming 12 months. This is thefirst of the three questionnaires. (Questionnaire No.2 scheduled in Feb. 2007, No.3 in July 2007)
The details of your answers will be statistically processed, and please be assured that personal
information entered in this questionnaire will NOT be disclosed whatsoever.
〔Instructions for completing the questionnaire〕
Please follow the instructions given for each question, such as circle the numberthat applies.
When you finish completing the questionnaire, please submit it in the attachedenvelope.

※

If you have any questions, please contact: Personnel Dept. (Direct) XXX-XXXX

35

Please tell us about yourself.
Q1．When did you graduate from your last school?
In １９

年

Q2．In the system to acquire specialized technical skills, what is your level of certification?
1.

Level S

2.

Level A

3.

Level B

4.

Level C5.

Not certified

Q3．Is there anyone in your family (parents, brother/sister, child, etc) who has worked for (or is workingfor) this company? (Circle one answer)
1.

Yes

2. No

These are questions on how you acquire knowledge and skills required for the job.
Q4．When you are in the workplace and a senior staff or colleague teaches you how to do the job while
actually showing it to you, or learning by looking at how others work or referring to work manuals iscalled On-the-Job Training (OJT). How many hours of On-the-Job Training did you experience inthe past month? If you did not receive any training, fill in zero (0).

About

Calculation example: An entire day of OJT is 8 hrs

hours last month

Q5．What percent of On-the-Job Training that you received last month was hours taught by a supervisor,senior worker or colleague? (Circle one choice)
1. ０～３０％ （Mimimal）

2. ４０～５０％ (About half)

3. ６０～７０％ (More than half)

4. ８０～１００％ (Almost all)

Q6．Looking at the situation in the past 6 months, was there more On-the-job Training than usual or lesstraining than usual last month? (Circle one choice)
1. More than twice the average in the past 6 months
2. 1.5 times the average in the past 6 months
3. The same amount as in the past 6 months
4. About half the average in the past 6 months
5. Less than half the average in the past 6 months
Q7．Was the On-the-Job Training conducted last month mainly in response to your request, or did asupervisor give instructions to conduct the training? (Circle one choice)
1. I requested the training

2. The supervisor instructed the training

Q8．Which of the following applies to the On-the-Job Training conducted last month? (Circle one choice)
1. It was training to make up for lack of skill/knowledge
2. It was training was to acquire higher skills

36

Q9．Did you receive Off-the-Job Training (Off-JT) in the past 6 months? Off-the-Job Training is groupseminars or training conducted away from the production line.
１． Yes 

2． No  Skip to Q12

Go to Q10
Q10．In the past 6 months, how many times did you experience Off-the-Job Training (Off-JT), and in
average how long did each Off-JT last? (Circle one choice)
Number of times:

1. 1 time
2. 2 times 3. 3 times 4. 4 times
5. Between 5 and 9 times 6. More than 10 times

Average duration for each Off-JT:
1. Less than 30 min.

2. 30 min. to less than 60 min. 3. 60 min. to less than 90 min.

4. 90 min. to less than 2 hours

5. 2 hours to less than 3 hours

6. More than 3 hours

Q11．Which of the following applies to the Off-the-Job Training conducted in the past 6 months?
(Circle one choice)
1. It was training to make up for lack of skill/knowledge
2. It was training was to acquire higher skills
Q12．In the past 6 months, did you do any studying on you own (Self Development) for your present job orfor a job that you want to do in the future?
※“Self Development” is study done during off duty hours by reading books or textbooks, or taking
classes at vocational schools or colleges, or studying by correspondence. (This does not include
hobbies unrelated to your work, leisure, sports, or health maintenance or promotion activities)
1. Yes 

2. No  Skip to Q14

Go to Q13
Q13. What is the frequency and average duration of each Self Development study in the past 6 months?
time(s) a month

Average duration of study was abouthour(s)Additional Q13-2 Is the skill/knowledge that you acquired through Self Development study in the past 6months useful only for your current job? Or do you think that it would also be useful for a similar
type of job at another company? Choose one reply from the 5 items below and circle the number.
2. It is also useful at another company
1. It is useful only at my current workplace
3. It is not useful at my current workplace or another company
4. It is not useful immediately at my current workplace or another company, but it will broaden myabilities as a professional in the long term
Q14．Circle all that apply to your day-to-day life in the past month.

37

1. Busy but fulfilling

2. Frankly speaking, a bit overworked

3. Enjoyed the days off

4. Exercised regularly

5. Refrained from drinking alcohol

6. Stopped smoking

These are questions on your job and how you work in your current and past workplaces.
Q15．How long have you belonged to the current Kumi (team)?

years

monthsQ16 Assuming that your current work proficiency is 100 and that your productivity immediately after you
joined the company and assigned to a workplace was zero, what do you think your proficiency level
was 6 months ago and 1 year ago? Choose one reply from the 5 choices below and circle the number.
(1) Proficiency 6 months ago・・・1. 95～100

2. 90～95

3. 85～90

4. 80～85

5. Less than 80(2) Proficiency 1 year ago・・・・・・1. 95～100

2. 90～95

3. 85～90

4. 80～85

5. Less than 80

Q17．This is a question for those who have worked in the current workplace for more than one year. Whatwas your proficiency level immediately after being assigned to the current workplace? This is
assuming that your current work proficiency is 100 and that your productivity immediately after
you joined the company and assigned to a workplace was zero. Choose one reply from the 5 choices
below and circle the number.
1. 90～100

2. 80～90

3. 70～80

4. 60～70

5. Less than 60

Q18．Of all processes in your workplace, how many processes are you fully capable of doing?
Confirm with GL and fill in the
total number of processes

Of allprocesses, I can doprocesses

Q19．In the past month, how many Kaizen improvement or creative proposals did you submit? Of these
proposals, how many were actually adopted?
Total number of proposals, , of which

proposals were adopted

Q20．How well do the following items describe your direct supervisor (GL or CL) in the workplace? Checkthe number that best describes each item.

1. Work plans and allocations are done properly
2. Properly voices what needs to be said to department
and section leaders and relevant departments
3. Makes fair evaluations
4. Really understands the subordinate’s worries andDoes notdescribe
the person

Somewhatdoes notdescribe１２

１Neither

Somewhatdescribes

Describes
the person

３

４

５

２

３

４

５

１

２

３

４

５

１

２

３

４

５

１

２

３

４

５

complaints
5. Friendly and easy to talk to38

6. Is a competent supervisor compared to the

１

２

３

４

５

１

２

３

４

５

predecessor
7. Allows workers to actively experience many
processes

Q21．How well do the following items describe your workplace? Check the number that best describes
each item.
Does notSomewhatdescribe my does notworkplacedescribe

1. The workplace is well organized
2. Information that needs to be shared by everyone iswell communicated in the workplace
3. There is an atmosphere to help others even if it does
not concern your own task
4. Meetings are conducted in an efficient and active
manner
5. Roles and responsibilities of each member is clear
and controlled
6. The supervisor instructs and trains each member
according to his/her characteristic
7. The workplace is not active and the mood tends to be
depressing

Neither Somewhat
describes

Describes
my workplace

１

２

３

４

５

１

２

３

４

５

１

２

３

４

５

１

２

３

４

５

１

２

３

４

５

１

２

３

４

５

１

２

３

４

５

＊This is the end of the questionnaire. Thank you very much for your cooperation.

39

Appendix: Questionnaire of Foremen

Questionnaire No.1 on Skills Developmentin the Workplace(For Supervisors)
September 2006
Osaka University, Institute of Social and Economic Research
Kyoto University, Institute of Economic Research〔Request for cooperation in the questionnaire〕
The purpose of this questionnaire is to survey how employees in the workplace acquire knowledge andskills required for the job, and to measure the effectiveness of these activities.
We would appreciate your taking the time from your busy schedule to answer the questionnaire withyour frank opinions. This questionnaire will be conducted 3 times in the coming 12 months. This is thefirst of the three questionnaires. (Questionnaire No.2 scheduled in Feb. 2007, No.3 in July 2007)
The details of your answers will be statistically processed, and please be assured that personal
information entered in this questionnaire will NOT be disclosed whatsoever.
〔Instructions for completing the questionnaire〕
Please follow the instructions given for each question, such as circle the numberthat applies.
When you finish completing the questionnaire, please submit it in the attachedenvelope.

※

If you have any questions, please contact: Personnel Dept. (Direct) XXX-XXXX

40

Please tell us about your workplace. “Workplace” here refers to the Kumi (team).
Which of the category best describes the attitude in your workplace for each item below? Circle theQ1.

number that applies.
Does not Somewhat does Neither
describe not describe
workplace① Asks employees to work according to instructions
rather than to think on their own and take action
on their own.
② Personnel allocation emphasizes putting theright person in the right place at that time,rather than on a long-term perspective to develop
human resources.

Somewhatdescribes

Describes
workplace

１

２

３

４

５

１

２

３

４

５

Q2. Circle all items that apply to your workplace.
１. We have daily morning meetings

２. Hot time meetings are held daily

３. There are frequent rotations

４. Fixed-term employees are often hired(as full-time employees)

Q3． When was the last time a large-scale investment was made in the production line in your workplace?

Around Year

Month

Q4．The following are questions on how long it takes to become proficient in the work processes
in your workplace.
(1) How many processes do you have in your workplace?
(2) How long does it take for an average high school graduate to become proficient in all process
in your workplace?
Years

Months

Q5．Please tell us about the QC circle meetings held in your workplace in the past 6 months. What are thefrequency and average duration of each meeting?

(1)

times a month(2) Average duration per meeting is about

hours(s)Q6．Has there been any changes described below in your workplace in the past 12 months? Check the itemthat applies.
41

Compared to 6 months ago

Compared to 12 months ago

1.

Changes in the total number ofpeople in the workplace

１ Increased ２ Same ３ Decreased

１ Increased ２ Same ３ Decreased

2.

Turnover of talented people

１ Left１ Left3.

Changes in the number of rotation
opportunities
Changes in the workload in theentire workplace
Revisionsintheworkplacetarget/index(i.e.
changedtoemphasize cost and safety instead of
efficiency)
Orders from upper management tochange the direction of humanresource
developmentintheworkplace

4.
5.

6.

7.

Changes in the line speed

２ None ３ Joined

１ Increased ２ Same ３ Decreased

２ None３ Joined

１ Increased ２ No change ３ Decreased

１ Increased ２ Same ３ Decreased

１ Increased ２ Same ３ Decreased

１ Target was revised ２ No change

１ Target was revised２ No change

１ There were orders to make changes

１ There were orders to make changes

２ No change
１ Faster ２ Same8.

Someone in the workplace fell sick or
was injured
9. Kaizen improvement proposals fromthe workplace were adopted and thework was made easier
10. Kaizen improvement proposals fromoutside the workplace were adopted
and the work was made easier
11. Revisions were made in the
personnel allocation

２ No change
３ Slower

１ Faster ２ Same

３ Slower

１ Yes

２ No

１ Yes

２ No

１ Yes

２ No

１ Yes

２ No

１ Yes

２ No

１ Yes

２ No

１ Yes

２ No

１ Yes

２ No

12. The work steps were changed

１ Yes

２ No

１ Yes

２ No

13. Operation methods for the QC circle
were changed

１ Yes

２ No

１ Yes

２ No

Q7．If the productivity of your workplace 12 months ago was 100, what do you think are the productivity
levels for 6 months ago and now?
(1) Productivity 6 months ago・・・・・・・・・・％(2) Current productivity・・・・・・・・・・・・・％

Q8．Check all items that apply to your workplace.
１．The workplace has difficulties in responding to changes in the line speed
２．There are many processes, and a long training period is required
to become proficient in all of them
３．There is a variance in the proficiency among my subordinates,
and work management requires my full attention
４．There are many processes that require higher skills compared to other Kumi on the same line42

５．I’m very busy and cannot find enough time to train my subordinates
６．There are many challenges, but I am fortunate to have good people and we work well together
Q9．In the past month, how many Kaizen improvement or creative proposals were submitted? Of these
proposals, how many were actually adopted?
Total number of proposals, , of which

proposals were adopted＊This is the end of the questionnaire. Thank you very much for your cooperation.

43