GCOE Discussion Paper Series
Global COE Program

Human Behavior and Socioeconomic Dynamics
Discussion Paper No. 147

Organization Adjustments, Job Training and Productivity:
Evidence from Japanese Automobile Makers

Kenn Ariga, Masako Kurosawa, Fumio Ohtake, Masaru Sasaki, and Shoko Yamane

July 2010; revised September 2012GCOE Secretariat
Graduate School of Economics

OSAKA UNIVERSITY

1-7 Machikaneyama, Toyonaka, Osaka, 560-0043, 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 **Kinki University

September 11, 2012+

The authors are grateful to the co-editor, an anonymous referee and the participants in the 2009 and2010 Trans-Pacific Labor Seminar at the JILPT, Tokyo and UCSB, Santa Barbara, FESAM 2009, and the2009 Japanese Economic Association Meeting for their valuable comments. We also thank the personnel
departments of the two automobile makers that helped us collect the data and allowed us to use them forthis research. Any errors are of course our responsibility. This research is partially supported by theJapanese Society for the Promotion of Science, Grand-in-Aid, No. 18330049.
†
KIER, Kyoto University, Yoshida-Honmachi, Sakyo, Kyoto, 606-8501, Email: ariga@kier.kyoto-u.ac.jp‡
GRIPS, 7-22-1, Roppongi, Minato, Tokyo, 106-8677, Email: mkurosawa@grips.ac.jp#
ISER, Osaka University, 6-1 Mihogaoka, Ibaraki, Osaka, 567-0047, E-mail: ohtake@iser.osaka-u.ac.jp∗
Corresponding to: Graduate School of Economics, Osaka University, 1-7 Machikaneyama, Toyonaka,
Osaka, 560-0043, Japan. E-mail: sasaki@econ.osaka-u.ac.jp**
Graduate School of Economics, Osaka University, 1-7 Machikaneyama, Toyonaka, Osaka, 560-0043,
Japan. E-mail: hgp001ys@mail2.econ.osaka-u.ac.jp1

ABSTRACTThis 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. We employ original survey data from two Japanese
automobile makers. The analysis includes estimations of determinants of on-the-job
training, and of how much such training contributes to improvements in individual
productivity. We also investigate effects of the characteristics of workplace practices,
including the behavior of foremen as well as assemblers, on the incentives forindividual assemblers to seek job training and productivity improvements.
Keywords: Job training, productivity improvement, relocation, rotation, workplace
practices
JEL classification: J24, M53

2

1. Introduction
Does job training really contribute to improvements in productivity? Do even veteranworkers keep on receiving job training? If so, why? Is job training useful foraccomplishing multiple tasks in response to unexpected shocks? Using original survey
data from the manufacturing establishments of two Japanese automobile firms, we offer
answers to these questions. The purpose of this paper is threefold. We first find that
there is continuous provision of job training, including for veteran assemblers, althougheach task in the assembly line seems relatively simple and easily learnt. That being so,
why is continuous job training necessary? Second, we estimate the determinants of theincidence and intensity of on-the-job training (OJT). Finally, we consider the impact of
OJT and workplace environments and practices on an individual assembler’s
productivity. It is, of course, imperative to measure the costs and benefits of OJT fromthe viewpoint of the firm’s human resources management strategy, to establish whether
and by how much individual productivity improves through the provision of job training.
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. The collected data provide a direct
link between the intensity of OJT and productivity improvements. Because it is difficult
to measure objectively the extent and intensity of OJT and productivity improvements,
we use subjectively assessed measures for those variables, even though somemeasurement error may be involved. To examine its appropriateness as a measure of
productivity improvement, we alternatively employ the change in the number ofoperational tasks that assemblers can perform satisfactorily as evaluated by theirforemen. According to the factory director interviewed, assemblers usually assessed3their own productivity improvements when responding to the survey questionnaire interms of an increase in the number of operational tasks they could perform. However,data on operational tasks were available only from a single automaker in the third waveof the survey. Nevertheless, while the original data have some disadvantages, they also
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 even though they should by then havemastered all the operations they usually perform. Using our original data, we are able tolook 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 the characteristics
of both teams and individuals (including their workplace environment and practices)
affect the determinants of job training and the extent of productivity improvements (ifany). Changes in the workload and assembly line speed responded to by foremen are
included in the characteristics of teams, and these capture the extent and intensity of any
demand shocks. In addition, kaizen proposals for job efficiency improvements and thenumber of quality control (QC) meetings are also studied, and these capture the extent
and intensity of supply shocks. 1 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 generates a demand for job training for assemblers,even veteran assemblers, so they can adjust to the environmental changes. Importantly,
while the literature includes the effects of individual characteristics on the intensity of1

Kaizen means operational improvement in Japanese. In many manufacturing sectors, including theautomobile sector, assemblers are encouraged to suggest proposals to improve efficiency in theirassembly line.
4job training, our study also includes the interaction between individual and teamcharacteristics.
There is some evidence that job training is highly selective, at least in OECD
countries other than Japan where no systematic study yet exists. Using data fromThailand, Ariga and Brunello (2006) found that while off-the-job training (OffJT) andeducation were complements, OJT and education were substitutes. In general, training
is most intensive in the early stages of an assembler’s career and experience. As for the
returns to job training, some studies found very high returns, but these were likely tosuffer from selection bias. In fact, and as pointed out by Leuven and Oosterbeek (2008),
past studies have relied on data collected from highly heterogeneous workplaces thatthey likely fail to control. Our samples, on the other hand, use original data from the
manufacturing establishments of two Japanese automobile makers that are homogenous
in terms of worker characteristics, underlying technology, workplace environment andorganizations. Thus, our analysis should not suffer from the selection bias foundelsewhere. 2
The next section discusses why and how an automobile establishment adjusts todemand and supply shocks, and why organization adjustments frequently occur in theJapanese manufacturing sector. Section 3 explains the data, followed by descriptive
statistics for job training and subjectively and objectively assessed productivity in
Section 4. Section 5 discusses the econometric methodology and Section 6 includes theresults. Section 7 shows a simple simulation to discuss the cost and benefit of internal

2

Assemblers are not usually transferred across establishments and their turnover rate is very low, butforemen are often instructed to relocate to a different establishment.
5

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 relatively simple and easy to learn? This subsection explains
the linkages 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 and workload, thereby increasing the demand for training.
Here we focus attention on two types of organization adjustments: job or task rotation
within the same team and relocation across teams. We define rotation within the sameteam as a transfer between production operations in the same team, and define
relocation as a broader transfer between teams but within the same establishment.
Hildreth and Ohtake (1998) also deal with workforce adjustment through organization
adjustments, using establishment-level data from an automobile maker. They find that
this automobile maker uses two methods to accommodate changes in labor demand:
either a long-term transfer indicating relocation of assemblers across establishments, ora short-term transfer between assembly lines and between production andnonproduction sectors as well as between establishments. Short-term transfers allow 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 this paper emphasizes

6

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. 3 For example, there are fads concerning choice of color in Japan.
There was a time when it looked as if every new car was white, and then black turned
out to be the most popular color, then light blue, shiny pink, and so on. More (fewer)
assemblers are located in the assembly line to cope with the increased (decreased)
workload. Flexible organization adjustments reduce the number of redundantassemblers and the surplus of human resource, 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 throughrotation within their own team. For these reasons, even old and veteran assemblers
continuously receive training to perform multiple tasks, as shown shortly below. 4

3For example, buyers began to receive tax credits for buying hybrid cars or ecofriendly cars in April
2009 in Japan. Since then, the demand for those cars (the Toyota Prius in particular) has been rapidly
growing.
4
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, and machine malfunctions
7

The third reason is that kaizen proposals encourage the reorganization of operational
procedures through rotation within a team and the relocation of assemblers across teams,
which leads to increases in team productivity and production efficiency. Monden (1997),
which gives detailed examples of the workings at one of the representative automakers
in Japan, Toyota Motor Co., shows that through QC meetings, a team scrutinizes thewhole operations and proposes which operation is wasteful and should be eliminated, or
which operative machine should be refined to improve team efficiency. 5 These raiselabor productivity of an assembler in a team and therefore enable the team to produce
the same amount of output with a smaller number of assemblers. Moreover, not all
kaizen proposals are productivity enhancing. Some of them are designed to create ahealthier workplace, reduce health hazards, or to enhance the amenity of the workplace.
To the extent that some of them necessitate substantive changes in workload
distributions, task assignments, and other parameters of the working conditions, thekaizen proposals are the ones that capture the supply shock.
According to Monden (1997), 6 at Toyota Motor Co.’s Tsutsumi factory, not only
assemblers but also foremen, supervisors and managers rotate within and across teams.
Even after they became multiskilled, job rotations among all assembly line processes
occurred every 2–4 hours. The main purpose of this job rotation is to prepare forflexible personnel arrangement in response to exogenous shocks. Monden also suggeststhat need to be resolved quickly on the spot. The “depth” enhances the team productivity by minimizing
the delay or stoppage of operation after the incidence. Unlike multiskilling, it seems there is a need forsome of the assemblers in the team to have this capability. Note that our original data are not applicablefor testing the implications from Koike (1994, 2002).
5
For example, to identify which operation is wasteful, a foreman and his assemblers measure how
many minutes it takes each operation to produce a unit of output by stopwatch. As another example, agrinder machine is modified so that a dust collection cover is installed below the grinder. This reduces
assemblers’ cleanup time.
6
See Chapter 11.
8some additional merits of job rotation, such as that it prevents assemblers frombecoming bored, and that by assigning different tasks, foremen can assign assemblers
across operations 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 can address problems in a new operation and put forward a kaizen proposal
for improvements. 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 the wage isdetermined for each job, which encourages assemblers to specialize in a single
operation and does not give assemblers an incentive to learn a range of skills. He findsthat 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 ofindirect 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 the assembler
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.
9Channel [3] in Figure 1 represents this process. In a similar manner, the need for job
training arises when assemblers rotate to work on new operations within their own team.
Assemblers provided with job training acquire new skills and should then assess theirimprovements in productivity. Channel [4] in Figure 1 represents this process. However,relocated assemblers may not have mastered new skills immediately after they havereceived job training. If so, they may subjectively assess a low productivity gain in the
new team.
3. The survey of workers at two automobile assembly plants in Japan
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 in 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. Thanks to the generous cooperation fromthe personnel departments of Firm A and B, we completed three waves of the survey forboth firms, 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, 7 and that both assemblers and foremen subjectively
assessed the extent of productivity improvements at the individual level. 8 This allows us
to estimate directly the impact of various types of job training on productivity
improvements at the individual level.

7

Thus, we have generated matched sets of assembly workers and their foreman for 20 to 30 teams ineach assembly plant.
8
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).
10

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
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 may also be of somerelevance that the sample establishment in the Firm A survey had 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 on
the assignments 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 final wave, we collected datafrom 24 foremen and 127 assemblers.

11

The assembler’s questionnaire consisted of 20 questions classified into four
categories. 9 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 kaizen proposals for job efficiency improvement, and (4) evaluation of
one’s own foreman, workplace environment, and practices. The questionnaire forforemen consisted of nine questions on the workplace environment and practices intheir assembly team, the number of QC meetings, and the productivity improvements intheir own team. Because the personnel departments of both firms strongly encouraged
their assemblers and foremen to participate in the survey, their response rates are almost
100%.
It is technically difficult to measure individual productivity improvement, so we
asked for subjective assessments over the past year. 10 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. 11 We used
this as a proxy measure of the individual productivity improvement. 12

9The questionnaires for both assembler and foreman are given in the 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.
11
This 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.
12
The sampled foremen were also questioned about the improvement in productivity in their own
team in a subjective way as follows: “If the productivity of your workplace 12 months ago was 100, what10

12

To supplement the subjective measure of individual productivity, we alternatively
use the extent of how many operational tasks an assembler had newly acquired over the
past year as the objective measure of productivity improvements at the individuallevel. 13 Because it is not difficult for assemblers to count the number of operationaltasks they can perform satisfactorily, we regard this variable as an objective measurewith little measurement error. Unfortunately, we could obtain the data on operationaltasks 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 theincrease in the number of operational tasks approved by their own foreman. A table ofaccomplished operational tasks was prepared for all assemblers and posted on thebulletin board, so everyone understood who had acquired new tasks and how many. We
will show the factory director’s evidence that the subjective assessment of productivity
improvement is correlated positively with this objective measure of the operationaltasks, using our data in Section 4.4.
We collected data on the extent of various types of job training, including OJT,OffJT and self-development. Due to space limitation and our priority for informal job
training within an establishment, however, we restrict the subsequent analysis 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, despite the fact that tenure or years of service has often been

do you think the productivity levels were 6 months ago and today?” In response, the foremen were to fillin any number, implying productivity improvements if the number exceeded 100, otherwise a
productivity decline. Because we focus on the impact on an individual employee’s productivity, we
preclude the analysis of team productivity in this research.
13
Note that an operational task is different from an operational process in that one operational
process comprises multiple operational tasks.
13

used to proxy the extent of training on the assumption that assemblers in the workplace
are provided with training. 14 We asked assemblers several questions concerning OJT
intensity. 15 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 OJT hours in the previous month were zero;otherwise zero. Since our purpose is to capture the provision of OJT for the entire past
year, if a person’s receipt of zero OJT hours in the previous month is perceived to beless OJT than usual, we interpret this person to have received some OJT in the past year.
Moreover, we calculate the hours spent in OJT by multiplying the hours of OJT in theprevious month by 12, and then divide by 2.5, 1.5, 1, 0.5, or 0.33, if the assembler
responded that the hours of OJT in the previous month were more than double, one anda half times, the same amount, about half, or less than half the average, respectively.
However, we need to recall that these methods cannot accurately measure the extent
and intensity of OJT, because it is difficult for assemblers to correctly identify whether
job activities are considered as OJT, which in turn leads to measurement 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 toestimate the impact of workplace environment and practices on individual
productivity. 16

14In 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.
15
We asked how many hours of OJT were received in the previous 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.
16
To be comparable, Kurosawa, Ohtake and Ariga (2005) originally collected two-period panel datafrom 830 randomly selected manufacturing establishments, including information on workplace practices,human resource management and training.
14

4. Preliminary data analysis
4.1. 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 one of the proxies
capturing the extent of the demand shock. This analysis also includes data from both
Firms A and B. As shown, the number of assemblers increases in a team when the speedof the assembly line also increases, while the number of assemblers decreases in a teamwith a low assembly line speed. Assemblers were then relocated from the slack team tothe busy team to meet the increasing product demands. This implies that assemblers arelocated across teams efficiently and flexibly in response to frequently arriving shocks.
Alternatively, an increase in the assembly line speed might encourage a foreman torotate his assemblers within the same team to cope with this demand shock. Our
speculation is that the speed of the assembly line would rather be considered as theproxy indicating the extent of the cross-team demand shock; that is, this shock spreads
to the whole operation across all teams through a change of assembly line speed. Whenassembly line speed increases, relocations across teams may not be an effective means
for adjustments because all teams suffer from a shortage of hands. Therefore, each
foreman copes with plant-level demand shocks through rotation within their own teams.
Figure 3 shows the relationship between the number of assemblers within a team andthe workload of the team as evaluated by the sampled foremen. It might be that unlike
assembly line speed, the workload evaluated by the foremen is one indication of theextent of the within-team demand shock, so this shock may be team specific. As shown,15

the number of assemblers increases in a team where the workload increases, but isreduced in a team where the workload decreases. This strengthens the view that
assemblers are transferred from slack teams to busy teams to cope with frequent
demand changes. It should be noted that a change of the workload evaluated by theforemen may also be in response to the cross-team demand shock by some measures.
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. Figure 4 shows adifference in the average tenure within the firm by assemblers relocated to different
teams and those who are not. According to Figure 4, the average tenure is longer forrelocated assemblers, particularly in 2007 and 2009. One possible interpretation to
support this result is that older and veteran assemblers can adjust to the environmental
changes more quickly than the younger assemblers.
4.2. Training (Channel[ 3])As depicted in Channel [3] in Figure 1, we explore here if and when assemblers
relocated to a different team receive job training. Figure 5 displays the extent andintensity of OJT, depending on the timing of the relocation across teams. We find that
assemblers relocated more recently to a different team are more likely to receive OJT.
This is perhaps because newcomers needed to receive job training to accommodate newtasks in the assembly line. However, the difference in the timing of job training within
six months and within one year is minimal. A similar phenomenon is evident in therelationship between average training hours and the timing of relocation. Here,

16assemblers relocated within six months spend more hours on OJT than those relocatedwithin one year.
According to Figures 4 and 5, we find that older and veteran assemblers are more
likely to be relocated than young assemblers, and that assemblers relocated to a different
team are more likely to receive job training. This therefore implies that even old andveteran assemblers are continuously provided with training to perform multiple and newtasks. Figures 6 and 7 display the incidence and intensity of OJT by tenure within thefirm. As shown in Figure 6, more than 80% of assemblers received OJT, regardless of
the length of tenure within the firm. According to Figure 7, the OJT duration would be
longer for veteran assemblers than for nonveteran assemblers. Our finding confirms thatolder and veteran assemblers are more likely to be relocated to a different team because
they adapt themselves to a new workplace environment more quickly, thereby
encouraging even older and veteran assemblers to receive job training to performdifferent tasks following relocation.
4.3. 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 about their work proficiency of a year before using the following
five categories: (1) 100–95, (2) 95–90, (3) 90–85, (4) 85–80, and (5) less than 80,
assuming that the current work proficiency is 100. We then calculate the class values ofwork proficiency according to a lognormal distribution function. Table 1 provides theseclass values. We consider the increase in work proficiency as a proxy for productivity

17improvements. We assume that assemblers interpret work proficiency in the samemanner. We show the evidence supporting this assumption in the next subsection.
We now explore the relationship between the improvement in individual productivity
and job training. Figure 8 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 before, assuming that the current work
proficiency is 100, and therefore implies that productivity improves as we move further
away from the origin on the horizontal axis. We combine data from both firms in Figure
8. As shown, assemblers who stayed in the lower category of work proficiency a year
before are more likely to receive OJT. We reject the null hypothesis that the OJT
incidence does not vary by the category of work proficiency at the 1% significance level.
However, over 80% of assemblers receive OJT, regardless of the extent of work
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 before) spend the longest hours in OJT.
Figure 9 displays the extent of subjectively assessed productivity improvement by
participation in OJT over the previous year, using data from both firms. We computethe class values of current work proficiency, assuming that the work proficiency of ayear ago is 100, shown on the left vertical axis. The horizontal axis is then an indicatorof whether an assembler received OJT over the previous year. As shown, assemblers
who received OJT perceived higher productivity improvements than those who did not.
This implies that OJT is effective in raising productivity.
18

4.4. Operational tasks (Channel [4])To supplement the subjective assessment of productivity improvement at anindividual level, we alternatively assess how many more operational tasks an assembler
newly acquired over the previous 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 enumerate 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. This ensures that the sampled assemblers responded on
the subjective measure of their work proficiency in the same way. 17

17

Because we could not obtain data indicating how many additional operational tasks assemblers
acquired over the previous year in Firm A, it may not be guaranteed that these assemblers interpret
subjectively measured work proficiency in the same manner. However, we found from the literature on
19

We are interested in the relationship between productivity improvements, asmeasured by an increase in the number of operational tasks, and the extent and intensity
of OJT.
Figure 9 shows the productivity improvement as measured by the increase in thenumber of operational tasks and participation in job training in the previous year. The
right vertical axis represents the number of operational tasks that one could performcurrently, assuming that its number a year before is normalized at 100. The horizontal
axis is an indicator of participation in job training over the previous year. Assemblers
who received OJT tend to be able to accomplish more operational tasks than those who
do not, although the null hypothesis that there is no difference in terms of an increase in
the number of operational tasks is not significantly rejected. This partially implies thatOJT is effective in improving productivity as measured by the number of operationaltasks at the individual level.
5. Estimation strategy
We pool the data for each firm for estimation purposes. The appendix gives a list of
independent and dependent variables, their definitions and descriptive statistics. We
first attempt to estimate the relationship between the productivity shock andorganization adjustments, including rotation within the same team and relocation acrossteams, mainly using the data collected from the responses in the foremen’squestionnaire. Here, we employ the extent of assembly line speed (speed) and theworkload (workload) responded by foremen as variables capturing the demand shocks
that occur to each team. Kaizen proposals suggested from inside and outside the same
Firm A’s business strategy that it employs the same measurement system to capture how many
operational tasks are newly acquired.
20

team (kaizen_in and kaizen_out) and change in the way of conducting QC meetings
within the same team (∆qc) are used as variables capturing supply shocks that occur toeach team. Here, kaizen_in and kaizen_out are, roughly speaking, considered as thewithin-team supply shock and the cross-team supply shock, respectively. The dependent
variable of rotation is a categorized variable indicating that foremen responded that theopportunities for rotation for their own assemblers within the team increased, remained
the same, or decreased over the year (rotation). Unfortunately, there are nocorresponding variables indicating that foremen responded on how relocation of own
assemblers occurred. Using instead the data collected from the responses in theassemblers’ questionnaire, we substitute the years assigned in the current team averaged
across assemblers within each team as a dependent variable indicating the extent of
relocation across teams (avg_tenure_team). The short average years of tenure in thecurrent team across assemblers implies that relocation takes place less frequently in thisteam. It may be possible that we observe the short average years of tenure in a teamacross assembler because many young newcomers just join in the team. To deal withthis problem, we add the average age of assemblers by team as an independent variable.
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 (ojthour).
Explanatory variables indicate individual characteristics and workplace environments
and practices. The individual characteristics include education (education), tenure
within the firm (tenure), tenure within the current team (indv_tenure_team), and skill
level (skill). The workplace environments and practice include the number of21

operational processes in the same team (#operation), its change over the year(∆#operation), whether there is an increase in opportunities for rotation for assemblers
within the same team from foremen’s viewpoint using the data from the responses in theforemen’s questionnaire (rotation2), a change in the way of conducting QC meetings
within the same team (∆qc), and the extent of OJT for other assemblers within the sameteam and for all other teams (ojt_team, ojthour_team, ojt_all, and ojthour_all). For
these characteristics, we collected subjectively assessed data from assemblers andforemen.
There are two points on variables regarding rotation and relocation in the probit
model. First, we here use the length of tenure of an individual assembler in their current
team (indv_tenure_team) as a proxy indicating the extent of relocation at the individuallevel. If the assembler is simply transferred into a new team, his indv_tenure_team iszero. On the other hand, staying in the same team for longer implies that relocation
across teams has occurred less frequently. The second point is that because there are nocorresponding variables indicating how an assembler responded he rotated within theteam, we instead use a dummy variable indicating a value of one if foremen responded
that the opportunities for rotation for their own assemblers within the team increased, ora value of zero if they remained the same or decreased over the year (rotation2). We
assume that rotation2 not only describes the overall extent of rotation in the whole team,
but proxies how an assembler rotates within the team.
In this case, rotation within the same team should arguably be treated as endogenous
because the decision rests on the foreman of the team. In other words, unobserved
foreman’s characteristics may not only affect the provision of OJT to own teamassemblers, but also the choice of rotation within own team. To control for the potential
22

endogeneity of rotation within the same team, we employ two approaches for the twostage estimation. The first is a standard model with instruments, where the first stage
consists of an OLS estimation of the choice of rotation to derive the predicted value,
which 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 therecursive 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 inthe second stage. Excluded instruments we employ in the first stage are speed, workload,
the number of absentees in a team (injury), kaizen_in, and kaizen_out. These
instruments are closely correlated with the choice of rotation but do not directly affectthe determinants of OJT. The changes of these instruments first affect the organization
adjustment to produce more efficiently, then encouraging foremen to provide OJT with
their assemblers to cope with the organization adjustment. We confirmed the validity of
excluded instruments in the first stage of estimations.
The primary focus is on measuring the effects of rotation and relocation (as measured
by tenure within the current team) on the provision of job training. Another hypothesisis that the frequent meetings and opportunities for individual development through QC
meetings and kaizen proposals raise assembler morale, thereby encouraging them toparticipate in and spend more hours in job training.
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 (ojthour) or a dummy variable taking a value of one if
23

assemblers received training (ojt). The dependent variable represents the likelihood of
productivity improvement with respect to either subjective or objective measurement(∆p and ∆#task). 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. Results
6.1. Relocation across teams and rotation within the same team
We 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. For each team in the sample, the dependent variable iscategorized as –1 for a decrease in rotation opportunities, 0 for unchanged and 1 for an
increase in rotation opportunities conducted to foremen over the past year (rotation).
The assembly line speed (speed) has a positive effect on the extent of rotation within thesame team at the 1% level of significance in columns (1) and (3), while the workload(workload) is statistically insignificant for rotation. It would then appear that to copewith demand shocks, foremen rotate assemblers across different operations within thesame team. The variables capturing supply shocks are statistically insignificant for
rotation in columns (2) and (3). Foremen rotate their own assemblers across various
operations within their own teams, regardless of whether kaizen proposals are put
forward.
24

Table 4 displays the results of the OLS models used to estimate the determinants ofrelocation across teams over the past year. As mentioned before, we substitute the teamassigned tenure of years averaged across assemblers within each team as the dependent
variable because there are no variables indicating the extent of relocation across teams
from the foremen’s questionnaire. We obtain the dependent variable from the responses
in the assemblers’ questionnaire. Note that F-values are not large enough to pass an F
test except for column (2). We find that the workload has a negative but marginal effectat the 10% level of significance in column (1) although the assembly line speed remains
insignificant. Here, as a foreman has a greater workload in his own team, he demands anincrease in the number of assemblers in his own team, and this reduces average tenureacross assemblers within the current team. The variables capturing supply shocks
remain statistically insignificant. It thus appears that demand shocks induceorganization adjustments, including relocation of assemblers across teams and rotationof assemblers within the same team.
In a nutshell, we interpret that these two results may indicate the selective use of job
rotations and relocations, depending upon the nature of the demand shock. Assumingthat a change in the line speed is relatively considered as the proxy indicating the extent
of cross-team demand shocks as discussed in Sevtion4.1, it makes sense that job
rotation within the team is used when this demand shock arrives. Reshuffling task
assignments can be used in each team to cope with the establishment -wide changes in
the workload, but relocation across teams cannot cope with such a demand shock
affecting all the teams in the same plant. For example, in slack periods, each team canmake use of a lower workload to assign line workers to new tasks (OJT), whereas theforeman reshuffles team assemblers to maximize their output in meeting demand.
25

On the other hand, assuming that a change in the workload of a team is relatively
considered as the proxy indicating the extent of team-specific demand shocks, we
suspect that relocation is primarily used to accommodate this shock. We guess that as
the shock is localized, the best way to cope with such shocks is to use worker
reallocation across teams to smooth workload distribution across teams. Unfortunately,
the estimates in Table 4 are not robust or strong enough to confirm our guess.
Nevertheless, it might be fair to say that the result in Table 4 at least shows that the
localized or team-specific shock (workload) induces relocation, but not the cross-teamshock (speed).
6.2. Determinants of job training
Tables 5 and 6 display the estimated results of the probit and Tobit models for thedeterminants 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 the extent of rotation within thesame team (rotation2) has a positive effect on OJT incidence at the 5% level ofsignificance. This result supports the hypothesis that assemblers are encouraged toreceive 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 to26

occur. Remind that the variable indicating the extent of rotation within the same team(rotation2) is collected from the responses in the foremen’s questionnaire because there
are no variables measuring how an individual assembler rotates within his team fromthe responses in the assemblers’ questionnaire. Therefore, the extent of rotation within
the same team (rotation2) is endogenously biased in such a way that unobserved
foreman’s characteristics may not only affect the provision of OJT to own teamassemblers, but also the choice of rotation in own team.
Columns (6) and (7) take into account this endogenous problem, which thus gives
unbiased estimates of the effect of rotation within the same team on OJT participation.
Columns (6) and (7) display results of a standard model with instruments and arecursive maximum likelihood method, respectively. Similar to column (5), rotation
within the same team (rotation2) remains positively significant in column (6), butrotation within the same team turns out to be insignificant in column (7). After
controlling for the endogeneity of rotation, the effect of rotation2 on the incidence of
OJT is mixed.
According to Table 6, tenure within the current team (indv_tenure_team), which
proxies the extent of relocation that an individual assembler has experienced, has anegative effect on the average hours of OJT at the 5% level in columns (4) to (7). This
indicates that as assemblers are relocated to a different team, they spend more timelearning new skills through OJT. Rotation within a team (rotation2) is statisticallyinsignificant for the OJT duration when rotation within a team is treated as exogenous.
Even after controlling for the endogeneity of rotation, the significance of both variables
remains unchanged in columns (6) and (7), comparable with column (5), although themagnitudes of some coefficients are different.
27

In conjunction with measurement error, there may be “recall bias” among assemblers.
There are two possible types of OJT. First, through OJT, assemblers acquire new skills
for newly assigned tasks, and secondly, assemblers repeatedly operate the same tasks
and thus polish skills that they have already acquired. The assemblers are more likely torecall the former as OJT, thereby underreporting the intensity of OJT. In theseestimations, as we repeat, the variable indicating the extent of rotation within the team(rotation2) does not imply the extent of how an individual assembler has rotated within
his team, but the extent to which the team as a whole has undertaken rotation within theteam from the viewpoint of each foreman. Therefore, it is fair to say that recall bias is
not a serious issue in our estimations. Moreover, there is the collateral evidence that
also indicates recall bias is not an issue. According to the appendix (descriptive
statistics), on the one hand, approximately 50% of foremen responded that rotation
increased across their own assemblers within the team, and the mean probability for an
assembler being relocated across teams is calculated as 38.8%. 18 On the other hand, atleast 80% of assemblers responded that they received OJT, regardless of the length oftenure within the firm (see Figure 6). This comparison implies that some assemblers not
only received OJT to acquire new skills for newly assigned tasks through rotation or
relocation, but also that other assemblers were aware they needed to receive OJT topolish their skills for the same task. Therefore, again, it is fair to say that assemblers
considered training just to polish skills as OJT.

18

According to the appendix, the mean of tenure within the firm (tenure) is 13.537 years, while themean of tenure that an assembler has belonged to the current team (indv_tenure_team) is 5.252 years.
Therefore, the mean probability of an assembler being relocated across teams is calculated by 5.252
divided by 13.537.
28

Looking at Table 6, the number of operational processes in a team (#operation) is
negative for OJT hours at the 1% level of significance in columns (3)–(5). 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 to spend time on OJT. Columns (5)–(7) in Table 5 and columns (5)and (6) in Table 6 indicate that the average OJT incidence and duration of any otherassembler across all teams (ojt_all and ojthour_all) are significantly negative for an
assembler’s own OJT incidence and its duration. This implies that one assembler
receives OJT when other assemblers do not. It would then appear that OJT issubstitutable between assemblers; that is, one receives OJT while another cannot. In
contrast with our prediction, skill level and tenure within the firm are statisticallyinsignificant for both OJT incidence and its duration. 19
6.3. 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 foremost interest among
the dependent variables are the dummies indicating the incidence of job training and thecontinuous variables for hours of job training. As shown in Table 7, the incidence of19

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.
29

OJT (ojt) has a positive effect on improvement in productivity at the 1% level ofsignificance. As one would expect, this supports the hypothesis that OJT contributes tomaking an individual assembler more productive from a subjective viewpoint. This
result is partially comparable with those obtained in Kurosawa (2001) and Kurosawa,
Ohtake and Ariga (2005). In the former, the effect on wages does not clearly differ byform of training, 20 and in the latter, OJT participation has an insignificant effect onestablishment-level productivity. 21 Our concern now is with the effects of OJT duration.
In contrast with our prediction, OJT duration (ojthour) is statistically insignificant for
the improvement in productivity, except in column (1) in Table 8.
Some other factors affect improvements in productivity. The improvement inproductivity assessed from a subjective viewpoint in the one-year lagged period(∆p_past) has a positive effect on that subjectively assessed over the previous 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 tend to assess
higher improvements now. A change in the way of conducting QC meetings over theprevious year (∆qc) is statistically insignificant, which is comparable with Kurosawa,
Ohtake and Ariga (2005) where participation in suggestion meetings has a significantly
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 the20

The exception is that the effect of formal training on wages was significantly negative forassemblers over 45 years of age.
21
However, the effect of OffJT participation is significantly positive on establishment-levelproductivity.
30

third 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
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, we consider theincrease in operational tasks to be an objective variable representing an improvement inproductivity.
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 (∆#task). First, except for column (1) in Table 11, we cannot
significantly reject the joint hypothesis that the coefficients on all explanatory variables
are zero according to the F test. Our estimations thus do not explain much of thevariation. Despite this, we report estimated results. The incidence of OJT (ojt) is
statistically insignificant for an increased rate of operational tasks. The incidence of
OJT is significantly positive for the subjectively assessed improvement in productivity,
as shown in Table 7, but insignificant in the model where the increase in operationaltasks is the dependent variable. One possible reason is that, as discussed earlier, thesmall sample size may increase the standard error of the coefficient and therefore reduce
the significance. Because the estimates cover the three waves of the survey from both
Firms A and B in Table 7, while the estimates in Table 10 include only the third waveof the survey from Firm B, we cannot directly compare the estimated results. We atleast obtain a positive sign of the coefficient on OJT, which is consistent with the results
31

in Table 7. The OJT hours (ojthour) are marginally and significantly positive in column(1) in Table 11, but the significance declines when including other explanatory variables.
Although the subjectively assessed improvement in productivity is correlated
significantly with the increase in operational tasks, we have different results for theeffect of OJT incidence depending on the measure of productivity improvement used as
the dependent variable in Tables 10 and 11. This may be a result of the small sample
size increasing the standard error of the coefficient on OJT.
7. 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 relocated.
The assembler size is normalized at one for simplicity. We consider cases in which theindividual cost for job training is higher for a newly hired assembler than for an
incoming internal assembler by 10%, 25%, 50% and 100%.

32

In the case of 10%, Firm A would have increased its total training cost by 3.3% if
32.68% of assemblers had been obtained from the external labor market. 22 In a similarmanner with 25%, 50% and 100%, Firm A has the greater burden of training costs by
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.
8. 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 to enhance human resource development. We collected unique 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 relatively 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) Firms provide OJT to assemblers when they are
assigned to different operations in which the skills they have thus far obtained become

22

The cost that Firm A would have paid if 32.68% of assemblers in the establishment were hiredfrom the external labor market is calculated as follows: 0.3268×(1+0.1)+(1–0.3268)=1.033, assuming thatthe adjustment cost of internal transfer is normalized to one. In cases of 25%, 50% and 100%, 0.1 are
replaced by 0.25, 0.5, and 1 in the above equation, respectively.
33

useless, through both rotation within the same team and relocation to a different team.
(2) Firms undertake organization adjustments 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 veteran assemblers are more likely to be
relocated to a different team because they adapt to change more quickly than do theyoung, implying that even older and veteran assemblers need to receive job training toperform different tasks following relocation.
Our original data allow us to gauge measures that are important but difficult to obtain,such as OJT incidence and productivity improvement at an individual level. Our paper’s
novel contribution is to detect the relationships between the incidence of OJT andproductivity improvement. It may be problematic that the period within which we aremeasuring the impact of training activities on productivity is too short; we cannot
therefore capture the long-term effects of OJT on productivity improvements. Thosequestions will be topics for future research.
References
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Hildreth, A. K. G., Ohtake, F., 1998. Labor Demand and the Structure of Adjustment
Costs in Japan. Journal of the Japanese and International Economics 12(2), 131–150.
Kawaguchi, D., 2006. The Incidence and Effect of Job Training among Japanese
Women. Industrial Relations: Journal of Economy and Society 45(3), 469–477.
Koike, K., 1994. Learning and Incentive Systems in Japanese Industry. In: Aoki, M.,
Dore, R. (Eds.). The Japanese Firm, Oxford: Clarendon Press, 41–65.

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Koike, K., 2002. Intellectual Skills and Competitive Strength: Is a Radical Change
Necessary? Journal of Education and Work 15(4), 391–408.
Krueger, A., Rouse, C., 1998. The Effect of Workplace Education on Earnings,
Turnover, and Job Performance. Journal of Labor Economics 16(1), 61–94.
Kurosawa, M., 2001. The Extent and Impact of Enterprise Training: The Case of
Kitakyushu City. Japanese Economic Review 52(2), 224–242.
Kurosawa, M. 2006. The Determinants of Participation in OJT and OffJT. Japan
Institute for Labour Policy and Training Material Series 13, 36–55.
Kurosawa, M., Ohtake, F., Ariga, K., 2005. Productivity, Training, and Human
Resource Management Practices—Disentangling Complex Interactions Using a
Survey of Japanese Manufacturing Firms, Discussion Paper No. 062, Kyoto Instituteof Economic Research, Kyoto University.
Leuven, E., Oosterbeek, H., 2008. An Alternative Approach to Estimating the Wage
Returns to Private-Sector Training. Journal of Applied Econometrics. 23, 423–434.
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35

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 80-85

103[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. Standard deviations are in parentheses.

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

Operational tasks
95-100

90-95

85-90

80-85

-80

Total

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 numberof operational tasks that one could perform one year ago, assuming that the current number isnormalized 100. On the other hand, the vertical categories represent subjectively-assessed
productivity level of one year ago, assuming that the current productivity level is 100.

36

Table 3: Determinants of rotation(1)
Coefficient(2)
p value

Coefficient(3)
p value

Coefficient

p value

firm_A-0.147 [0.519]

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]-0.247 [0.268]-0.153 [0.522]

kaizen_in

0.258 [0.432]

0.313 [0.349]

kaizen_out-0.236 [0.324]-0.175 [0.482]∆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. Standard errors are in parentheses. The dependent variable iscategorized as -1 for decease, 0 for unchanged and 1 for increase obtained from the responses in theforemen’s questionnaire (rotation). The ordered probit estimation method is employed. Independent
variables: dummy for Firm A (firm_A), assembly line speed in a team (speed), the burden of
workload in a team (workload), the number of absentees in a team (injury), Kaizen proposals
suggested from inside the team (kaizen_in), Kaizen proposals suggested from outside the team(kaizen_out), and a change in the way of conducting the Quality Control meetings (∆qc)

37

Table 4: Determinants of relocation(1)
Coefficient(2)
p value

Coefficient(3)
p value

Coefficient

p valueconstant

3.282 [0.260]-0.173 [0.954]

2.142 [0.482]

firm_A-0.93 [0.094]*-1.327 [0.021]**-1.156 [0.043]**

avg_age_team

0.085 [0.312]

0.16 [0.067]*

0.103 [0.230]

speed-0.109 [0.719]-0.009 [0.975]

workload-0.715 [0.081]*-0.691 [0.107]

injury-0.424 [0.369]-0.57 [0.244]

kaizen_in

0.594 [0.487]

0.351 [0.664]

kaizen_out

0.818 [0.186]

0.71 [0.235]∆qc

0.195 [0.769]

0.413 [0.517]

obs = 117

obs = 115

obs = 113

F(5, 111) = 1.80

F(5, 109) = 1.96

F(8, 104) = 1.72

Prob > F = 0.119

Prob > F = 0.090

Prob > F = 0.103

R-squared = 0.075

R-squared = 0.083

R-squared = 0.117

Adj R-squared = 0.033

Adj R-squared = 0.041

Adj R-squared = 0.049*** 1%, ** 5%, * 10% significance. Standard errors are in parentheses. The dependent variable isthe average tenure across assemblers within the current team obtained from the data of responses in
the assemblers’ responses (avg_tenure_team). The OLS estimation method is employed.
Independent variables: dummy for Firm A (firm_A), average age of assemblers in a team
(avg_age_team), assembly line speed in a team (speed), the burden of workload in a team(workload), the number of absentees in a team (injury), Kaizen proposals suggested from inside theteam (kaizen_in), Kaizen proposals suggested from outside the team (kaizen_out), and a change inthe way of conducting the Quality Control meetings (∆qc)

38

Table 5: Determinants of OJT incidence(1)
Coefficient(2)
p value

Coefficient(3)
p value

Coefficient(4)
p value

Coefficient(5)
p value

Coefficient(6)
p value

Coefficient(7)
p value

Coefficient

p valueConstant

1.966 [0.000]***1.278 [0.000]***2.147 [0.000]***2.381 [0.001]***33.22 [0.000]***39.740 [0.000]***36.735 [0.000]***

firm_A-0.152 [0.371]-0.022 [0.908]-0.28 [0.262]-0.343 [0.206]-0.559 [0.074]*-0.580 [0.032]**-0.685 [0.025]**#operation-0.032 [0.028]**-0.039 [0.097]*-0.048 [0.065]*-0.046 [0.105]-0.070 [0.004]***-0.064 [0.028]**0.013 [0.559]

0.02 [0.424]

0.017 [0.529]

0.024 [0.298]

0.023 [0.383]

tenure0.008 [0.680]

0.002 [0.933]

0.000 [0.996]

0.002 [0.905]

skill

0.005 [0.982]

0.082 [0.717]

0.066 [0.728]

0.066 [0.765]

indv_tenure_team-0.032 [0.087]*-0.033 [0.100]-0.013 [0.523]-0.029 [0.205]

rotation20.401 [0.026]**

1.733 [0.000]***1.019 [0.137]∆qc-0.379 [0.187]-0.506 [0.035]**-0.398 [0.178]

ojt_team

0.231 [0.705]-0.275 [0.614]

0.021 [0.973]

ojt_all-34.292 [0.000]***-41.668 [0.000]***-38.000 [0.000]***∆#operation-0.009 [0.634]

Obs = 566

Obs = 317

Obs = 317

Obs = 291

Obs = 285

Obs = 268

Obs = 268

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) = 57.25

Wald chi2(10) = 2.80

Prob > chi2 = 0.087

Prob > chi2 = 0.887

Prob > chi2 = 0.388

Prob > chi2 = 0.385

Prob > chi2 = 0.007

Prob > chi2 = 0.000

Prob > chi2 = 0.012

Pseudo R2 = 0.013

Pseudo R2 = 0.001

Pseudo R2 = 0.014

Pseudo R2 = 0.032

Pseudo R2 = 0.121*** 1%, ** 5%, * 10% significance. Standard errors are in parentheses. 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, while a probit estimation is employed in the first stage in column (7). Both columns employ a probit
estimation for the OJT incidence in the second stage. Instruments: assembly line speed in a team (speed), the burden of workload in a team (workload), the number of absentees in a team (injury), Kaizen proposals
suggested from inside and outside the team (kaizen_in and kaizen_out). Independent variables: dummy for Firm A (firm_A), the number of operation processes in team (#operation), a change in the number ofoperation processes in a team (∆#operation), tenure within the firm (tenure), skill level (skill), tenure of an assembler in the current team (indv_tenure_team), dummy for rotation (rotation2), a change in the way of
conducting the Quality Control meetings (∆qc), team-average of OJT reception except self (ojt_team), and average OJT (ojt_all). Education is dropped because of perfect collinearity.

39

Table 6: Determinants of OJT hours(1)
Coefficient(2)
p value

Coefficient(3)
p value

Coefficient(4)
p value

Coefficient(5)
p value

Coefficient(6)
p value

Coefficient(7)
p value

Coefficient

p valueconstant

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

301.275 [0.002]***543.897 [0.002]***2872.137 [0.064]*

2459.549 [0.091]*

firm_A

38.4 [0.071]*

55.402 [0.027]**

2.77 [0.928]-11.165 [0.729]

13.095 [0.713]-39.490 [0.279]-36.562 [0.314]#operation-3.89 [0.042]**-8.967 [0.005]***-10.068 [0.002]***-8.577 [0.008]***-8.302 [0.03]**-7.677 [0.041]**

4.68 [0.101]

5.156 [0.072]*

4.235 [0.142]

4.999 [0.096]*

4.905 [0.104]

tenure0.009 [0.997]

0.259 [0.898]

0.382 [0.855]

0.430 [0.838]

education-26.341 [0.608]-42.858 [0.387]-64.110 [0.226]-68.158 [0.197]

skill

13.027 [0.600]

14.056 [0.560]

21.646 [0.395]

21.857 [0.393]

indv_tenure_team-6.005 [0.012]**-5.378 [0.022]**-6.065 [0.034]**-6.501 [0.021]**rotation2-22.06 [0.262]-26.424 [0.801]-62.797 [0.502]∆qc-51.997 [0.129]-54.963 [0.169]-47.630 [0.222]

ojthour_team

0.169 [0.166]

124.692 [0.112]

130.109 [0.097]*

ojthour_all-2.197 [0.074]*-2943.250 [0.086]*-2483.281 [0.123]
Obs∆#operation-0.137 [0.952]

= 287

= 287

Obs = 565

Obs = 317

Obs = 317

Obs = 311

Obs = 305Obs

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(10) = 36.04 Wald chi2(11) = 36.11

Prob > chi2 = 0.001

Prob > chi2 = 0.084

Prob > chi2 = 0.005

Prob > chi2 = 0.004

Prob > chi2 = 0.001

Prob > chi2 = 0.000

Pseudo R2 = 0.002

Pseudo R2 = 0.002

Pseudo R2 = 0.004

Pseudo R2 = 0.006

Pseudo R2 = 0.009

Prob > chi2 = 0.000*** 1%, ** 5%, * 10% significance. Standard errors are in parentheses. The dependent variable is the OJT duration (ojthour). 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, 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. Instruments: assembly line speed in a team (speed), the burden of workload in a team (workload), the number of absentees in a team (injury), Kaizen proposals suggested from inside andoutside the team (kaizen_in and kaizen_out). Independent variables: dummy for Firm A (firm_A), the number of operation processes in team (#operation), a change in the number of operation processes in a team(∆#operation), tenure within the firm (tenure), education (education), skill level (skill), tenure of an assembler in the current team (indv_tenure_team), dummy for rotation (rotation2), a change in the way of
conducting the Quality Control meetings (∆qc), team-average of OJT reception except self (ojt_team), and average OJT (ojt_all)40Table 7: Determinants of productivity improvement -subjective viewpoint (independent variables: incidence of job training)

constant

(1)
(2)
(3)
(4)
(5)
(6)
Coefficient
p value
Coefficient
p value
Coefficient
p value
Coefficient
p value
Coefficient
p value
Coefficient
p value109.871 [0.000]***109.587 [0.000]***70.595 [0.000]***70.593 [0.000]***70.592 [0.000]***299.978 [0.006]***

firm_A

3.116 [0.000]***2.189 [0.125]

1.272 [0.350]

1.202 [0.395]

1.205 [0.397]

7.59 [0.025]**

ojt

4.255 [0.001]***

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

6.126 [0.001]***

6.123 [0.001]***

6.175 [0.001]***#operation-0.058 [0.684]-0.015 [0.913]-0.024 [0.862]-0.024 [0.868]-0.02 [0.890]∆#operation

0.027 [0.844]-0.071 [0.595]-0.077 [0.566]-0.077 [0.573]-0.066 [0.641]

0.341 [0.000]***0.331 [0.000]***0.331 [0.000]***0.327 [0.000]***tenure-0.066 [0.485]-0.066 [0.485]-0.074 [0.434]

education

1.284 [0.551]

1.277 [0.557]

1.227 [0.571]

skill

0.214 [0.845]

0.217 [0.845]

0.339 [0.759]-0.038 [0.979]

0.129 [0.931]∆p_past∆qc∆p_team-0.07 [0.481]∆p_all-1.947 [0.044]**
Obs = 680

Obs = 311

Obs = 305

Obs = 304

Obs = 304

Obs = 303

F(2, 677) = 13.54

F(4, 306) = 4.25

F(5, 299) = 11.51

F(8, 295) = 7.27

F(9, 294) = 6.44

F( 11, 291) = 5.76

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 = 0.165

R-squared = 0.165

R-squared = 0.179

Adj R-squared = 0.036

Adj R-squared = 0.040

Adj R-squared = 0.147

Adj R-squared = 0.142

Adj R-squared = 0.139

Adj R-squared = 0.148*** 1%, ** 5%, * 10% significance. Standard errors are in parentheses. The dependent variable is the extent of improvement in productivity from a subjective viewpoint (∆p). Independent variables: dummy for Firm
A (firm_A), dummy for OJT (ojt), the number of operation processes in team (#operation), a change in the number of operation processes in a team (∆#operation), productivity improvement in the one-year lagged
period (∆p_past), tenure within the firm (tenure), education (education), skill level (skill), a change in the way of conducting the Quality Control meetings (∆qc), team-average of productivity improvement(∆p_team), and average productivity improvement (∆p_all)41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

113.376 [0.000]***115.292 [0.000]***75.038 [0.000]***75.732 [0.000]***75.713 [0.000]***288.501 [0.010]***

firm_A

2.909 [0.000]***1.858 [0.199]

0.957 [0.487]

0.868 [0.546]

0.887 [0.539]

6.796 [0.049]**

ojthour

0.004 [0.054]*

0.004 [0.202]

0.003 [0.415]

0.003 [0.374]

0.003 [0.389]

0.002 [0.440]#operation-0.082 [0.570]-0.041 [0.763]-0.054 [0.702]-0.051 [0.723]-0.053 [0.715]∆#operation

0.037 [0.793]-0.061 [0.654]-0.063 [0.640]-0.068 [0.626]-0.053 [0.710]

0.348 [0.000]***0.342 [0.000]***0.342 [0.000]***0.338 [0.000]***tenure-0.061 [0.525]-0.061 [0.523]-0.071 [0.463]

education

0.774 [0.723]

0.734 [0.740]

0.679 [0.758]

skill

0.208 [0.853]

0.224 [0.842]

0.332 [0.769]-0.219 [0.885]-0.083 [0.957]∆p_past∆qc∆p_team-0.082 [0.422]∆p_all-1.788 [0.069]*
Obs = 676

Obs = 311

Obs = 305

Obs = 304

Obs = 304

Obs = 303

F(2, 673) = 9.36

F(4, 306) = 1.76

F(5, 299) = 9.36

F(8, 295) = 5.67

F(9, 294) = 5.03

F(11, 291) = 4.54

Prob > F = 0.0001

Prob > F = 0.137

Prob > F = 0.000

Prob > F = 0.000

Prob > F = 0.000

Prob > F = 0.000

R-squared = 0.027

R-squared = 0.023

R-squared = 0.135

R-squared = 0.133

R-squared = 0.133

R-squared = 0.147

Adj R-squared = 0.024

Adj R-squared = 0.010

Adj R-squared = 0.121

Adj R-squared = 0.110

Adj R-squared = 0.107

Adj R-squared = 0.114*** 1%, ** 5%, * 10% significance. Standard errors are in parentheses. The dependent variable is the extent of improvement in productivity from a subjective viewpoint (∆p). Independent variables: Firm A=1(firm_A), hours of OJT (ojthour), the number of operation processes in team (#operation), a change in the number of operation processes in a team (∆#operation), productivity improvement in the one-year lagged
period (∆p_past), tenure within the firm (tenure), education (education), skill level (skill), change in the way of conducting the Quality Control meetings (∆qc), team-average of productivity improvement (∆p_team),
and average productivity improvement (∆p_all)42Table 9: Subjective and objective productivity
Coefficient

p value

Coefficient

p valueconstant

109.373 [0.000]***105.321 [0.000]***∆#task

0.016 [0.000]***0.016 [0.000]***tenure-0.316 [0.039]**

education

7.271 [0.029]**

skill

0.813 [0.647]
Obs = 95

Obs = 92

F(1, 93) = 18.83

F(4, 87) = 7.24

Prob > F = 0.000

Prob > F = 0.000

R-squared = 0.168

R-squared = 0.250

Adj R-squared = 0.160

Adj R-squared = 0.215*** 1%, ** 5%, * 10% significance. Standard errors are in parentheses.
The dependent variable is the extent of improvement in productivity froma subjective viewpoint (∆p). Independent variables: a change in the number
operational tasks in Firm B (∆#task), tenure within the firm (tenure), andeducation (education), and skill level (skill)43

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]-94.676 [0.537]-160.881 [0.356]-211.498 [0.218]

ojt

64.034 [0.499]

92.195 [0.342]

78.49 [0.255]

74.576 [0.264]

tenure6.431 [0.146]-4.363 [0.223]-4.171 [0.229]

education

89.475 [0.353]

115.884 [0.088]*

102.606 [0.120]

skill

6.157 [0.906]

75.099 [0.062]*

81.058 [0.039]**#operation

3.365 [0.445]

6.422 [0.161]∆#operation-6.342 [0.130]-6.569 [0.107]∆qc-101.673 [0.054]*
Obs = 95

Obs = 92

Obs = 51

Obs = 51

F(1, 93) = 0.46

F(4, 87) = 1.22

F(6, 44) = 1.33

F(7, 43) = 1.78

Prob > F = 0.499

Prob > F = 0.308

Prob > F = 0.265

Prob > F = 0.117

R-squared = 0.005

R-squared = 0.053

R-squared = 0.153

R-squared = 0.225

Adj R-squared = -0.006

Adj R-squared = 0.010

Adj R-squared = 0.038

Adj R-squared = 0.098*** 1%, ** 5%, * 10% significance. Standard errors are in parentheses. The dependent variable is an increase in the number of operational tasks(productivity improvement with an objective viewpoint) (∆#task). Independent variables: dummy for OJT (ojt), tenure within the firm (tenure),
education (education), skill level (skill), the number of operation processes in team (#operation), a change in the number of operation processes
in a team (∆#operation), and a change in the way of conducting the Quality Control meetings (∆qc)

44

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

Coefficient(3)
p value

Coefficient(4)
p value

Coefficient

p valueconstant

138.568 [0.000]***-18.244 [0.870]-32.971 [0.839]-85.227 [0.594]

ojthour

0.232 [0.096]*

0.224 [0.115]-0.024 [0.843]-0.033 [0.781]

tenure5.931 [0.176]-4.922 [0.176]-4.729 [0.179]

education

97.686 [0.308]

104.033 [0.145]

89.414 [0.197]

skill-3.274 [0.950]

70.637 [0.082]*

76.868 [0.052]*#operation

2.024 [0.668]

5.074 [0.295]∆#operation-5.371 [0.217]-5.557 [0.187]∆qc-103.941 [0.052]*
Obs = 95

Obs = 92

Obs = 51

Obs = 51

F(1, 93) = 2.83

F(4, 87) = 1.64

F(6, 44) = 1.08

F(7, 43) = 1.56

Prob > F = 0.096

Prob > F = 0.171

Prob > F = 0.388

Prob > F = 0.172

R-squared = 0.030

R-squared = 0.070

R-squared = 0.129

R-squared = 0.203

Adj R-squared = 0.019

Adj R-squared = 0.028

Adj R-squared = 0.010

Adj R-squared = 0.073*** 1%, ** 5%, * 10% significance. Standard errors are in parentheses. The dependent variable is an increase in the number of operational tasks(productivity improvement with an objective viewpoint)(∆#task). Independent variables: hours of OJT (ojthour), tenure within the firm (tenure),
education (education), skill level (skill), the number of operation processes in team (#operation), a change in the number of operation processes
in a team (∆#operation), and a change in the way of conducting the Quality Control meetings (∆qc)

45

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

We assume that the number of assemblers is normalized one. The cost of training is assumed to be one for an internal assembler, regardless of whether
she/he is relocated from a different team or remains in the current team. Therefore, the total cost of training is normalized to be one for internal laboradjustments. The cost that Firm A would have paid if 32.68% of assemblers in the establishment are hired from the external labor market is calculated asfollows: 0.3268×(1+0.1)+(1－0.3268)＝1.033.

46

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)47

Figure 4: Average tenure within the firm by assemblers relocated to a different
team and those who are not 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

Figure 5: Incidence and average hours of job training by the timing of relocation
across teams
100%

180
160

80%

140
120

60%

100

%

80

40%

60

h
Incidence of OJTAverage 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

48

Figure 6: Incidence of OJT by tenure within the firm

The data are from both Firm A and B. Test of difference of the OJT incidence by tenure
within the firm=0: F(5, 683) = 1.02, p = 0.405

Figure 7: Intensity of OJT by tenure within the firm

The data are from both Firm A and B. Test of difference of the intensity of OJT bytenure within the firm=0: F(5, 679) = 1.33, p = 0.251

49

Figure 8: 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

Figure 9: Improvement of productivity and an increase in operational tasks by theincidence of training
120

180
150

115
120
110

90
60

Improvement of productivity
An increase in operational tasks

105
30
100

0
No

Yes
OJT

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. The horizontal axis
represents the OJT incidence over the past year. Test for difference=0: Improvement of productivityt(678) = -3.27, p < 0.000, An increase in operational tasks: t(93) = -0.68, p = 0.450.
50

Appendix: Definitions of variables
Variables
rotationrotation2

Data collected from the responses in the foremen’squestionnaire
category variable indicating a change in rotation within a team–1 (decrease) 0 (unchanged) 1(increase)dummy variable indicating 1 if the extent of rotation increases or 0 if
the extent of rotation decreases or remains unchanged

injurythe number of absentees in a team–1(decrease) 0 (same) 1(increase)
workload
category variable indicating the burden of workload in a team–1 (decrease) 0 (same) 1(increase)speed
category variable indicating assembly line speed in a team–1 (decrease) 0 (same) 1(increase)kaizen_in
kaizen proposals put forward within the team raise efficiency =1
kaizen_out
kaizen proposals put forward from outside the team raise efficiency=1change in the way of conducting the Quality Control meetings =1∆qc#operation
the number of operation processes in own teama change in the number of operation processes in own team∆#operation
Variables
Data collected from the responses in the assemblers’questionnaire
avg_tenure_team years of tenure in the current team averaged across assemblers within
the team calculated using the data collected from the responses in theassemblers’ questionnaire.
indv_tenure_team years of tenure an individual assembler has belonged to the current
team
avg_age_team
average age of assemblers in a team calculated using data collectedfrom the responses in the assemblers’ questionnairetenuretenure within the firm
skill
skill level
education
education level, high school or above=1
ojt
dummy indicating 1 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 OJT hours in the previous
month were zero
ojthourOJT hours in the previous one year
ojt_teamteam average of the dummy indicating whether received OJT, except
a person’s self
ojt_all
all sampled average of the dummy indicating whether to receive
OJT, except a person’s self
ojthour_team
team-average of OJT hours, except a person’s self
ojthour_all
all sampled average of OJT hours, except a person’s self51∆p∆p_past∆p_team∆p_all∆#taskVariablefirm_A

improvement in productivity from a subjective viewpoint over theprevious year
improvement in productivity from a subjective viewpoint in the
one-year lagged period
team-average improvement in productivity over the previous year
from a subjective viewpoint
all sampled average improvement in productivity over the previous
year from a subjective viewpointa change in the number of operational tasks over the previous year
from Firm B
Data collected from the responses in both the foremen’s and theassemblers’ questionnaires
dummy indicating Firm A=1 and Firm B=052

Appendix: Descriptive statistics
Variables
rotationrotation2
injuryworkloadspeedkaizen_in
kaizen_out∆qc#operation∆#operation
avg_tenure_team
indv_tenure_team
avg_age_team
tenureskill
educationojt
ojthour
ojt_team
ojt_allojthour_teamojthour_all∆p∆p_past∆p_team∆p_all∆#taskfirm_A

N
577
577
566
578
566
555
557
566
592
342
709
688
710
700
691
700
693
689
722
739
722
739
681
450
722
739
95
739

53

Mean
SD
0.414
0.637
0.496
0.500
0.095
0.566
0.452
0.652
–0.012
0.895
0.879
0.326
0.388
0.488
0.214
0.410
18.409
6.017
0.750
6.044
5.248
2.973
5.252
5.423
33.313
3.409
13.537
7.378
1.754
0.692
0.937
0.243
0.905
0.294
113.608 188.572
0.906
0.161
0.905
0.016
127.033 208.150
130.83918.992115.052
10.181114.6539.972
114.874
5.829
115.0131.605
161.101 239.456
0.414
0.493

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

54

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

55

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.
1. It is useful only at my current workplace
2. It is also useful at another company
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.
56

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 whichproposals 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 to57

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.

58

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

59

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.
60

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

２ No change

１ Faster ２ Same ３ Slower

8.

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

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 line61

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.

62