Technology Change, Creative Destruction, and Economic Feasibilty
IJPR (2014) Testing a Theoretical Model Underlying the ‘Toyota Way'
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Testing a theoretical model underlying the ‘Toyota
Way’ – An empirical study involving a large global
sample of Toyota facilities
Nihal P. Jayamaha
a
, Jürgen P. Wagner
a
, Nigel P. Grigg
a
, Nicky M. Campbell-Allen
a
& Warwick
Harvie
b
a
School of Engineering and Advanced Technology, Massey University, Palmerston North, New
Zealand
b
Toyota Global Knowledge Center, Torrance, CA, USA
Published online: 12 Feb 2014.
To cite this article: Nihal P. Jayamaha, Jürgen P. Wagner, Nigel P. Grigg, Nicky M. Campbell-Allen & Warwick Harvie (2014):
Testing a theoretical model underlying the ‘Toyota Way’ – An empirical study involving a large global sample of Toyota
facilities, International Journal of Production Research, DOI: 10.1080/00207543.2014.883467
To link to this article: http://dx.doi.org/10.1080/00207543.2014.883467
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3. research on the TPS on its introduction to the USA in 1984. This introduction of TPS was as a joint venture between
Toyota and General Motors, named New United Motor Manufacturing (Camacho-Miñano, Moyano-Fuentes, and
Sacristán-Díaz 2013). Krafcik is generally credited with first using the term around 1988 to denote a manufacturing sys-
tem that results in elimination of waste. This body of research resulted in (inter alia) the seminal publication ‘The
Machine that Changed the World’ (Womack, Jones, and Roos 1990). The research and resulting publications therefore
established a clear link between the TPS and the foundations of contemporary notions of Lean thinking (Holweg 2007).
One of the most salient links identified between JIT and TPS was Toyota’s ‘pull system’, whereby the quantity of
work-in-process (WIP) produced by a workstation is determined by the workstation that makes immediate use of that
WIP in the production line, when required, with the initial signal to pull originating from the customer at the down-
stream end of the value chain (Hopp and Spearman 2004). Toyota was able to consistently eliminate waste (muda in
Japanese) from its value chain by analysing its processes continually by working as teams, harnessing the full capabili-
ties of its people and the suppliers (Davy, White, and Merritt 1992; Ohno 1988; Womack and Jones 2003). A recent
study by Netland (2013) on 30 world-class manufacturing organisations that have their own tailor-made production
system found that in the main, the 30 company-specific production systems shared most of the key features of the TPS:
standardised work (93%), kaizan/CI (83%), total quality (77%), pull system (70%), and so on. This suggests the
profound impact the TPS has had on the production front.
1.2 The Toyota Way (TW)
In 2001, the guiding principles that led to the development of the TPS were formalised by Toyota into the TW (TMC
2001a). The TW incorporates the TPS (as illustrated later in Figure 2, based on TMC 2006) but is applicable to all
functions, departments and operations within Toyota. It is stated as being ‘… an ideal, and a guiding beacon for the
people of the global Toyota organisation. It expresses the beliefs and values that are shared by us all’ (TMC 2006, 8).
In short, the TW represents Toyota’s organisational culture. The TW is representative of the general principles upon
which the TPS and its upstream and downstream value chain activities are built (Liker and Hoseus 2008). Figure 1
shows the TW conceptual framework. It is founded on two pillars of continuous improvement (CI) and respect for peo-
ple, and consists of the following five elements: challenge, kaizen, genchi genbutsu, respect and teamwork. Toyota man-
agement perceives these five elements as different aspects (concepts) of the TW, and hence we have discussed each of
the five elements separately in our paper. The reader will note, however, that these five elements are not distinctly differ-
ent from one another statistically since they are highly inter correlated according to the measurement system used by
Toyota to measure the TW (see Section 4.2.2).
Having traced this conceptual development, it is reasonable to assert that there is at least a high degree of overlap
between JIT, TPS, Lean and that all these elements are a manifestation of the TW. JIT as a specific set of practices is
fundamental to the TPS, aimed at achieving Lean production though continuous flow of materials or other inputs. JIT
as a wider philosophy is synonymous with Lean, in referring to a conceptual framework that encompasses both practices
and thinking that are focused on the creation of value for the customer, continual improvement of the productive process
and the elimination of non-value adding activity. The TW represents the guiding principles of Toyota (from which Lean
takes its origins). In this paper, these terms will variously appear, and some of these parallels will be further
demonstrated through literature.
Figure 1. The TW conceptual framework (TMC 2001b).
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4. 1.3 Research aims
While there have been a plethora of studies on Lean manufacturing practices, tools and techniques, as well as
operational definitions of Lean (as discussed in Section 2), there is an identified need to explore the foundation upon
which the practices, tools, techniques, and operational definitions of Lean are built. This can be addressed by under-
standing the conceptual basis of the TPS (Jayaram, Das, and Nicolae 2010; Schonberger 2007). In this paper, we take
the position that the conceptual basis of TPS is Toyota’s unique culture, which they have communicated to their global
community as the TW. We set out to empirically test the conceptual framework underlying the TW using empirical data
from Toyota’s logistics, sales, and marketing functions across 27 countries. The data were analysed using exploratory
factor analysis (EFA) and structural equation modelling (SEM).
This paper is organised as follows. In Section 2 (literature review), we review published empirical research pertain-
ing to JIT/Lean in general, and the TPS in particular, and then describe how the TW can be understood to bring about
competitive advantage; in Section 3 (methodology), we explicate our theoretical model of the TW, and describe how
data were collected and analysed to test this model; in Sections 4 and 5 (results and discussion) we present our findings,
including a discussion of the validity of the operational measures used to measure the core concepts of the TW and
interpretation of structural relationships of the theoretical model both from a technical and practical perspective; and in
Section 6 we conclude by presenting the key findings, limitations of the study, and implications for future research.
2. Literature review
The following review will attempt to delineate the central constructs within the TW (and TPS, where relevant), and
summarise previous empirical research with the purpose of establishing our underlying theoretical model and analytical
methodology.
2.1 Defining the TW in relation to the TPS
Based on the literature published by the TMC on the TW (TMC 2001a, 2006) and other relevant literature (e.g. Hines,
Holweg, and Rich 2004) we define the TW as the strategic, high performance work system that sits at the very core of
the TPS and other value adding systems and processes in Toyota’s value chain. Essentially, the TW determines the
fundamental principles according to which things are done at Toyota (Rother 2010). As to why the working practices at
the TMC were codified only after so long is best revealed in some of the statements made in the foreword of the ‘TW
Booklet’ by Fujio Cho, the president of the TMC (TMC 2001a).
The rapid growth, diversification and globalisation of Toyota in the past decade have increased the scope of our of our
company’s manufacturing and marketing presence throughout the world […] In this booklet we have identified and defined the
company’s fundamental DNA, which summarises the unique and outstanding elements of our company culture and success…
It is essential that our global leadership team embrace the concepts of the Toyota Way as we achieve our business goals in host
countries which have a wide variety of customs, traditions and business practices. (TMC 2001a, 1)
Figure 2 illustrates the high-level relationship between TW and TPS.
We present the remaining literature on the TPS/TW under two headings: general literature on the TPS/TW, and
empirical studies on Lean and similar Toyota-style production systems. The general literature refers to practitioner-
focused literature, which provides the context-bound information relating to the constructs of the TW. The empirical
studies we have included primarily cover operationalisations of Lean. Having covered the literature on the TPS/TW, we
interpret the TW in the light of the strategy literature on competitive advantage.
2.2 The conceptual basis of the TW
Having studied Toyota for over 20 years, Liker (2003) observed that the TPS is guided by 14 management and
operational principles:
taking a long-term perspective on management decisions;
creation of smooth continuous flow by matching the customer demand rate and the production line;
use of pull systems to avoid over production;
levelling out the workload (heijunka);
stopping the work (jidoka) to fix problems;
standardising the tasks;
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5. using visual controls and keeping workplace tidy;
relying on validated technology only;
grooming future leaders;
developing exceptional individuals and teams;
respecting the partners in the value chain;
going to the place where ‘real action’ takes place (gemba) and ‘thoroughly understanding the situation’ (genchi
genbutsu);
making decisions by consensus;
organisational learning through kaizen (described later).
The TW, as shown in Figure 1, is based on two central pillars of CI and respect for people. CI is measured as
challenge, kaizen and genchi genbutsu. Challenge, first, reflects the fact that CI involves process-oriented thinking,
rather than short-term focused results-oriented thinking. The process-oriented thinking is based on the premise that the
results will eventually improve when the company is able to overcome the challenges that inhibit process improvement
are faced with courage (Imai 1986; Mika 2006; TMC 2001a). Thus, ‘challenge’ reflects long-term oriented visionary
thinking, on the part of the leadership (Liker 2003; Schonberger 2007).
According to Imai (1986), who popularised the term ‘kaizen’ in the western world, even though kaizen is a widely
used word in Japan meaning improvement, in relation to a workplace, kaizen refers to CI of processes and outcomes
involving everybody in the organisation to improve quality and productivity. In the context of the TW, the term ‘kaizen’
is used to mean the existence of a variety of what are known as kaizen activities at any given time. Kaizen activities
are small-scale operational level activities that are undertaken by small groups such as quality circles and work
improvement teams to improve productivity, quality and workplace safety (Sandberg 2007; Shimizu 2004). While a
kaizen activity has a definite start and end time (hence each activity in itself is not continuous) the existence of a variety
of kaizen activities at any given time (hence continuity) reflects CI (Mika 2006).
A third important aspect of CI is going to the source to find out what the real problems are (Imai 1997; Liker
2003). Both Imai and Liker identified going to the shop floor (or gemba, meaning the place where real action takes
place in order to understand problems) as a salient feature of Toyota. Toyota calls this genchi genbutsu. Thus, challenge,
kaizen and genchi genbutsu can be viewed as the indicators of CI.
Moving to the second pillar of the TW, respect for people (Figure 1), the TW conceptual model represents
humanisation of kaizen/JIT activities by giving due consideration to the roles being played by Toyota employees
(Sandberg 2007; Shimizu 2004, 2007). Shimizu (2007), who refers to people at Toyota as the ‘motor within the Toyota
machine’, observes that unlike many other manufacturing firms in Japan, Toyota was able to quickly respond to Japan’s
labour concerns in the 1990s. These concerns particularly related to high employee turnover due to the nature of JIT
activities and reduction of available high-school graduates in the blue collar labour force. Toyota responded to the crisis
by redefining the work activities (e.g. increased automation) and the working environments (e.g. new plant layouts).
Shimizu observes that because traditionally, employee remuneration in Japan is tightly linked to labour productivity,
Figure 2. Relationship between guiding principles, TW and TPS and other systems in the value chain (adapted from TMC 2006).
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6. which in turn is linked to the intensity of JIT activity, JIT systems in the 1990s were used to put enormous pressures on
the individual Japanese worker, which resulted in work stress and turnover. One of the policies Toyota adopted in the
1990s, as a remedial measure to this was that JIT ‘should not be applied to people’ and that production efficiency
should not be the sole end goal of a JIT-based system, in that consideration should also be given to social relations at
work (Shimizu 2007, 400). Hence, we envision the concept respect for people as an advanced human resource develop-
ment concept unique to Toyota, which sets it apart from its competitors who use otherwise use the same production
methods (Section 2.4).
Womack (2007) observes that respect for people as conceptualised by Toyota differs from respect for people as
understood by a western manager; namely, affording people the liberty to perform, while holding them accountable for
their action. Womack asserts that for Toyota, respect for people means a psychological process in which a manager
enters into a series of meaningful dialogues with their subordinates to help them to identify root causes of a problem
and counter measures that need to be taken to eliminate the root causes. Womack describes four sequential manager-sub-
ordinate dialogues in this regard: understanding how activities are ‘currently being done’ to jointly workout what the
‘real problem’ is, examining the root causes to the problem, examining the countermeasures selected along with the
basis of selection out of possible other alternative solutions, and testing the selected countermeasures (against the agreed
assessment criteria) to ascertain success. Thus, respect for people can be viewed as an intrinsic human motivating factor
that benefits the organisation.
Rother (2010) observes that critical aspects of Toyota (which are invisible) are managements’ thinking patterns and
routines (kata). Rother identified two unique kata in Toyota: improvement kata and coaching kata. Rother defined
improvement kata as ‘the repeating routine by which Toyota improves, adapts, and evolves’ in order to achieve its
outcomes (18). In more basic terms this can be referred to as problem solving in a CI environment. Coaching kata to
Rother is ‘the repeating routine by which Toyota leaders and managers teach the improvement kata to everyone in the
organisation’ (18). Thus Rother implies that coaching kata is the primary driver that enables improvements to take place.
The coaching kata can be viewed as people development to solve problems in an individual or a team environment.
There are clear parallels between Rother’s concept of coaching kata and Womack’s respect for people (Womack 2007).
The difference between the TW and TPS is that the TW represents difficult to measure cultural aspects of Toyota
while the latter represents the sociotechnical system that manifests primarily as tools and techniques that Toyota uses.
TW forms the basis upon which the TPS is built – that is, TW is the manner in which the technical activities (including
application of tools and techniques) are embedded in Toyota. In practitioner-focused literature, the elements of the TW
are often incorporated in the elements of the TPS (for example, the 14 management and operational principles of Toyota
identified by Liker 2003).
2.3 Empirical studies related to Toyota-like production systems
Scholars have conceptually analysed the elements of the TPS and its underlying philosophy. While earlier writers
focused on the technical aspects of Lean operations, more recent contributions highlighted the need for a holistic view
on the production system with its philosophical and human-centred underpinnings. The following section examines
some of the empirical studies relating to these conceptual frameworks.
Using survey data on perceptions about different facets of JIT from 446 respondents, Davy et al. (1992) empirically
derived (through EFA) three underlying constructs of a JIT management system: operating structure and control, product
scheduling, and quality implementation. Based on content analysis of these constructs, they developed 12 hypotheses to
constitute a theory on a JIT management system. The propositions covered both hard elements (e.g. design simplifica-
tion, procurement, demand forecasting) and soft elements (e.g. an organisational culture characterised by leadership
commitment, participatory supervision and employee involvement) as causal antecedents of JIT outcomes (timeliness
and product quality).
Shah and Ward (2007) derived the underlying factor structure of a Lean system using EFA. They then used
confirmatory factor analysis to cross-validate the factor structure using data that were not used to generate their factor
model. Shah and Ward identified ten factors (dimensions) that represent a Lean manufacturing system: supplier
feedback, JIT delivery by suppliers, supplier development, customer involvement, pull system, continuous flow, setup
time reduction, total productive/preventive maintenance, statistical process control, and employee involvement.
Using linear multiple regression, Jayaram, Das, and Nicolae (2010) studied the empirical relationship between TPS
practices, TPS principles, and the two-way interaction between TPS practices and TPS principles (predictors) and the
manufacturing performance (response) of US manufacturing firms that implement Lean manufacturing. Jayaram et al.
defined TPS principles as the ‘overarching rules of joint problem solving and work design for bottom level
organisational initiative and learning’ (286). The TPS principles used by them included joint problem solving with
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7. supplier, direct communication links between buyer and supplier production schedulers, cross-training workers,
manufacturing operator teams, decentralised decision making for micro production scheduling, and decentralised
decision making for operator daily tasks. They operationalised manufacturing performance using four measures: cycle
time reduction, quality performance, cost reduction and delivery speed. Jayaram et al. showed that the main effects TPS
practices and TPS principles as well as their two-way interaction were significant and positively related to
manufacturing performance.
Premising setup time reduction and machine downtime reduction as key outcomes of a Lean production system,
using systems dynamics and ‘factory physics approach’ (Hopp and Spearman 2001), Filho and Uzsoy (2013) showed
that in uncertain decision-making environments, simultaneous small changes to several parameters do render same
benefits to the system as a large change of a single parameter does. This study highlights the importance of having
kaizan activities in the factory floor as in the TPS.
2.4 The TW in relation to the resource-based view of competitive advantage
The resource-based view (RBV) is a dominant theory of competitive advantage. This explains how a firm can combine
its tangible and intangible resources and capabilities to outperform other firms in the market that produce similar
products and services (Barney 1991; Barney, Wright, and Ketchen 2001; Herrmann 2005; Wernerfelt 1984). The RBV
holds that a firm can consistently outperform its competitors (i.e. gain sustainable competitive advantage) so long as it
is able to possess the criteria of owning ‘valuable’, ‘rare’, ‘imperfectly imitable’ (that is difficult to imitate) and ‘non-
substitutable’ resources (Barney 1991). There are two types of resources that fulfil the above criteria: tangible resources
and intangible resources. Tangible resources are the resources that become visible to an outsider. In a Lean context,
these resources include JIT, CI and other visible elements published in the literature and discussed in Section 2.2.
Intangible resources are the resources and capacities of a firm that are not directly visible. In a Lean context, these are
teamwork, people development and organisational learning (Liker 2003; Schonberger 2007; Shah and Ward 2007).
Looking back at the two pillars of the TW (Figure 1) it can be deduced that the first pillar (CI) represents Toyota’s
tangible resources while the second pillar (Respect for People) represents Toyota’s intangible resources. Neither of these
sets of resources can be easily imitated by the competitors, in the name of ‘best practice’. Toyota developed its process
improvement practices through its pioneers such as Kiichiro Toyoda and Taiichi Ohno many years ago (post World War
II), taking into account the historical circumstances faced by the Japanese motor industry at the time: limited resources,
smaller production batches, and having to set up machines frequently (Liker 2003; Sugimori et al. 1977). Co-operation
of the employees and mutual respect was central to the CI of the manufacturing systems of Toyota and to making the
company viable in post-war Japan (Ohno 1988). Even though the historical circumstances of Toyota have since
changed, throughout its over 75-year history Toyota has been able to pass on its basically unaltered process
improvement recipe from senior members to junior members through its unique corporate culture.
Thus, in keeping with the RBV of competitive advantage, it can be argued that Toyota’s unique set of tangible and
intangible resources are so bundled that it becomes difficult for other firms to acquire or imitate similar resources and
enjoy the same success in the market as Toyota does. Empirical research involving world-class manufacturing firms
supports the notion that bundling of resources is an effective manufacturing strategy to gain competitive advantage. For
example, using data from 164 different manufacturing plants in five developed countries, Schroeder, Bates, and Junttila
(2002) empirically demonstrated that competitive advantage of a firm results from its unique resources (which they
called ‘proprietary processes and equipment’) being driven by organisational learning. These firm-specific resources
were defined as resources and capabilities that cannot be easily duplicated by a competitor. Although Schroeder et al.
mainly captured tangible resources in their measurement model on unique resources, the intangible resources were
embedded in their measurement model on organisational learning. Consequently, what Schroeder et al. showed was that
the firm’s intangible resources drive its tangible resources to gain superior performance (competitive advantage).
Spear and Bowen (1999) attempted to capture the difficult to imitate organisational learning (more specifically the
tacit knowledge) embedded in the TPS through four rules. These rules cover work standardisation (rule 1), direct
customer-supplier link (rule 2), simplified direct pathway between suppliers (rule 3) and scientific problem solving under
the tutelage of a ‘teacher’ (rule 4). We note that some proportions of Spear and Bowen (1999) are embedded in Toyota’s
survey instrument used in our study to capture the TW (Appendix 2).
The importance of intangible resources (e.g. people and capabilities) on competitive advantage has been more
directly demonstrated through a series of empirical studies that followed Powell’s seminal study (Powell 1995) on
competitive advantage. Powell showed that competitive advantage comes not by adhering to routines such as
benchmarking and total quality management but by developing ‘tacit, behavioural, imperfectly imitable’ resources and
capabilities such as ‘open culture’ and ‘employee empowerment’ (Powell 1995, 15).
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8. 2.5 Knowledge gaps and justification of the study
As we demonstrated in the previous sections, there is a substantial amount of literature covering either (non-quantitative)
descriptions of the TPS or Toyota’s company culture, or empirical studies that investigate the relationship between the
application of Lean principles and manufacturing performance. However, despite the widespread claim that Toyota’s
unique culture is at the core of its competitiveness, studies that draw the link between Toyota’s organisational practices
and its culture based on genuine data from within Toyota are still lacking. In other words, the theoretical basis of the
TW, in the form that is presented to its global community as a conceptual model (Figure 1) on Toyota’s culture, has not
been examined in published research. In this paper, we address this knowledge gap.
We showed earlier (Section 2.1) that TW is an upshot of TMC attempting to codify its company culture (in 2001)
for its global community, on account of Toyota’s increased global presence since the 1990s in very diverse national
cultures. The TW has been presented in a booklet in a manner that can be easily understood by the practitioner.
In this research, we view the TW conceptual model as a parsimonious model that reflects the culture of the overall
Toyota organisation. While a theoretical model of the TPS would be applicable to Toyota’s manufacturing operations, the
TW conceptual model has the advantage of pertaining to the overall Toyota organisation and its functional units (including
manufacturing) covering a wide verity of value chain activities. Hence, the latter model is more generalisable across
Toyota’s functional units. By including wider issues such as people development, it also serves as a more representative
proxy for Lean systems. In this study, we aim to empirically validate the TW using data obtained from Toyota.
3. Methodology
3.1 Postulating the theoretical framework for empirical testing
We used the TW conceptual framework developed by Toyota (Figure 1) as the starting point. The two constructs CI
and respect for people in the conceptual model are indicated by three measures (challenge, kaizen, and genchi genbutsu)
and two measures (respect and teamwork), respectively. Based on the works of Rother (2010) and Womack (2007), as
analysed in the literature review, we justified the use of the above five measures to capture the conceptual domains of
their two underlying constructs.
The labels given by Toyota to the two constructs of their conceptual model may cause some confusion with the
labels given to their measures. For example, CI confounds with the operational measure kaizen. We argued earlier
(Section 2.1) that as far as Toyota’s conceptual model is concerned the term ‘kaizen’ basically means kaizen activities
conducted by quality/work improvement teams. To avoid label conflicts, we replaced the labels CI and respect for
people with process improvement and people development, respectively. We provide the general meaning of these two
constructs as follows:
Process improvement is a construct that captures the level of CI activities as reflected by the level of kaizen
activities, long-term focus (challenge), and tackling problems at the source (genchi genbutsu) (Figure 1). If CI was to be
measured through responses from employees in a Toyota production line, much of the CI activities would relate to
eliminating waste (Shimizu 2007; Sugimori et al. 1977).
People development is a construct that captures the degree of human resource development that takes place in a
culture that values problem solving through teamwork and mentoring (Rother 2010; Womack 2007). In Toyota’s
conceptual framework (Figure 1), people development is termed respect for people, which should not be interpreted as
some kind of laissez-faire leadership style (see Section 2.1).
Propositions in the literature (e.g. Emiliani 2006; Liker 2003; Rother 2010; Schroeder, Bates, and Junttila 2002)
suggest that it is people development that actually enables process improvement. For example, Emiliani observes the
following:
The correct practice of Toyota’s management system – lean management – would require, at a minimum, acknowledgement
and practice by management of both principles: continuous improvement and respect for people. However, most managers
practice only the first principle, continuous improvement, which greatly limits amount of improvement that can be achieved …
It is the second principle, respect for people, that enables the first principle. (p. 169)
Hence, our first causal-predictive research hypothesis is:
H1: Process improvement (response) is caused by people development (predictor).
The next step is to relate the concepts process improvement and people development with a criterion variable. A direct,
performance-related criterion variable such as the quality performance or bottom line results was deemed unsuitable for
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9. our research due to two reasons. First, outcomes such as financial performance and quality performance in different
countries (or regions) from which the data have come for our study can be significantly moderated by country or
region-specific variables (e.g. size of the operation, competition, disposable income of end customers, and definitional
issues of terms such as non-conformity). Second, because both predictor variable data and criterion variable data for our
study come from multiple respondents of the same operational unit, interpretation of bottom-line results or quality
performance results could be very problematic; in theory, we cannot have very different estimates for bottom-line results
and quality performance from the respondents in the same operational unit. For these reasons, we selected an indirect
criterion variable, which was termed as ‘TW deployment’. The conceptual model shown in Appendix 1 shows this
indirect criterion variable (modelled as a latent variable) also.
TW deployment is a construct that captures the uptake of TW principles across any given operational unit of Toyota.
TW deployment can be viewed in two ways. One way is to view it purely as a criterion variable that should be related
to the TW. A strong relationship between this criterion variable and its predictors – process improvement and people
development – would indicate concurrent validity (Byrne 2010; Nunnally 1978) of the TW. Another way is to view TW
deployment (the Result) as a causal outcome of people development and process improvement (the enablers). A
business unit of Toyota that is strong on TW deployment would frequently apply the TW principles (see survey item
Q25 in Appendix 2), show outstanding knowledge of the TW (see survey item Q26 in Appendix 2), and show evidence
of healthy dialogue between managers and their subordinates as to how the TW could be used to improve business
results (see survey item Q27 in Appendix 2).
Thus, our next two causal-predictive hypotheses are:
H2: TW deployment (response) is caused by process improvement (predictor).
H3: TW deployment (response) is caused by people development (predictor).
A technical issue we had to resolve prior to data collection was to decide whether to conceptualise the constructs
process improvement and people development as first-order constructs or, more abstract second-order constructs. If we
were to treat the said constructs as second-order constructs (suggesting multidimensionality), then the elements that
belong to the constructs (e.g. respect and teamwork for the construct people development) also become constructs (more
precisely first-order constructs) in their own right. We modelled process improvement and people development as first-
order constructs for two reasons. First, the survey instrument that has been used to collect data (see Section 3.2 and
Appendix 2) has not been designed by Toyota to such an abstract level as to treat process improvement and people
development as second-order constructs. Second, the data analysis (more precisely, EFA) suggested that process
improvement and people deployment are uni-dimensional constructs. Therefore, the elements that belong to the
constructs do become the ‘indicators’ of the constructs, in the terminology used in SEM (Figure 3). Each indicator of
the construct (e.g. kaizen belonging to the construct process improvement) is captured through multiple questionnaire
items in the survey instrument.
3.2 Data collection
We collected data from Toyota’s Global Knowledge Centre (GKC), based in Torrance, USA. The main aim of the GKC
is to facilitate the sharing of knowledge and best practices in sales and marketing among Toyota distributors around the
world. Specifically, it is dedicated to collaborating with Toyota distributors to promote the TW in sales and marketing.
The GKC conducts an annual survey across Toyota’s logistics, sales, and marketing units across several countries
outside Japan to measure the extent to which the TW is approached and deployed. The 27-item questionnaire uses a
5-point Likert scale (Appendix 2). It has been designed by GKC experts, and is administered to stratified samples
representing different countries/regions. Q1 through Q24 measure the use of practices associated with genchi genbutsu,
kaizen, challenge, respect and teamwork, while the last three items (Q25, Q26 and Q27) examine to what extent the
TW is deployed. The dataset consisted of responses from 2,613 respondents from a cross-section of Toyota logistics,
sales, and marketing facilities in 26 countries, representing: North America (e.g. Canada); Central America (e.g. Panama,
Nicaragua); South America (e.g. Brazil, Argentina); Africa (e.g. Egypt, Nigeria); Middle East (e.g. Jordan, Yemen);
Europe (e.g. U.K., France); and the Asia Pacific region (e.g. Australia, New Zealand, Thailand).
3.3 Testing for absence of substantial method bias
To test for absence of substantial common method variance (bias) from questionnaire responses, we conducted two
statistical procedures: Harman’s one-factor test and the common latent factor method, as prescribed by Podsakoff et al.
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10. (2003). Both tests indicated that the responses were unlikely to have been affected by a significant common method
bias. Common method bias or common method variance, which is not an unusual condition in self-reports and
self-assessments, is a condition that biases the results due to the way the data are being collected and/or the survey is
being administered, rather than due to flaws in the measures being used.
If the results had been significantly affected by common method bias, all of the 27 survey items in our survey
instrument would have extracted just a single common factor, according to Harman’s single factor test (Podsakoff et al.
2003). To test how many factors are extracted, we conducted PCA on the dataset (n = 2613) involving all 27 items
(Appendix 2). This PCA analysis revealed that more than one factor is extracted as there were three eigenvalues exceed-
ing 1.0 (the values being 13.00, 1.22 and 1.11). Thus, Harman’s one-factor test cleared the survey data from being
significantly tainted by common method bias.
As our second test on common method bias, we used the common latent factor test, also known as the test on
controlling for the effects of an unmeasured latent methods factor, which is described in Podsakoff et al. (2003, 891).
For the purpose of the common latent factor test, we superimposed a common latent factor that reflects all 27 items (with
equal loading) on our theoretical model. The loading on questionnaire items by the method factor was low (= 0.18)
suggesting low common method variance. Thus, the common latent factor test too cleared the survey data from being
significantly affected by common method bias. Therefore, we went on to analyse the data.
3.4 Data analysis
Since the survey instrument was designed by Toyota’s GKC and not by us, we first set out to verify through EFA that
the first 24 survey items do indeed capture the two constructs of the TW: CI (process improvement as labelled by us)
and respect for people (people development as labelled by us). Since it is not proper to confirm the validity of the con-
structs (through CFA) from the very data that created the constructs (through EFA) (Hair et al. 2006), we used 50% of
the data for EFA and the remaining 50% data for CFA and testing the three hypotheses. Hence, we randomly divided
the total dataset (n = 2613) into two samples: the training sample (n = 1307) and the cross-validation sample (n = 1306).
The training sample was used to conduct EFA, in the principal components analysis (PCA) mode, using the SPSS
19.0.0 software package. The purpose of this analysis was to determine to what extent the first 24 questionnaire items
in the questionnaire reflect the TW conceptual model (Figure 1). Specifically, we tested whether or not the data could
be summarised by two factors, and if it is possible to extract two factors whether these two factors (once rotated orthog-
onally) were a good match to the two constructs process improvement, and people development. The cross-validation
sample was used to test our theoretical model in confirmatory mode, using SEM. The structural paths of our model and
the parameter estimates are shown in Figure 3. We used the AMOS 19.0.0 software package for this purpose.
Figure 3. The structural model and parameter estimates.
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11. 4. Results
4.1 The factor structure based on the EFA
The initial (un-rotated) eigenvalues of the factors whose eigenvalue was greater than 1.00 were: 11.31 (this factor
extracts 47.1% total variance); 1.22 (this factor extracts 5.1% total variance); and 1.06 (this factor extracts 4.4% total
variance). The eigenvalues suggested that the 24 questionnaire items under review (the first 24 questionnaire items in
Appendix 2) can be represented by three factors with the possibility of eliminating the third factor (owing to its close to
cut-off eigenvalue). The scree plot (not shown) as well as the three-factor rotated solution did not justify a third factor.
Hence subsequently, SPSS was prompted to generate two factors only. Table 1 shows the rotated (varimax) factor matrix
for both the three-factor solution (discarded) and the two-factor solution.
Results shown in Table 1 suggest that two unidimensional factors indeed exist. Out of the 24 questionnaire items, 3
items (Q13, Q20 and Q24) did not show evidence of a relationship with either of the two factors because these showed
weak loadings (0.5) against both factors. Hence, these three items were dropped, based on the guidelines given by Hair
et al. (2006). Hair et al. state that any factor loading (a factor loading is the correlation between a measure and a factor)
that is less than 0.5 is practically insignificant and that measures (in our case questionnaire items) that load against more
than one factor become candidates for omission, when operationalising the underlying constructs. Based on the loading
pattern of the remaining 21 items, the first factor was labelled people development while the second factor was labelled
process improvement. EFA on the cross-validation sample showed a factor structure similar to that shown in Table 1
(not reported due to space limitations); hence the analysis thereafter was done using data in the cross-validation sample
only (the full sample gives very similar results). Therefore, we established that (with the exception of the three question-
naire items omitted) subject to further testing and confirmation (e.g. CFA), certain questionnaire items under review
belong to people development and that the remaining questionnaire items belong to process improvement. The items
loadings on each of the two factors are shown in Table 2, with the aspect of the construct they are measuring shown in
square parenthesis (for example, see Q3, which measures teamwork as part of people development).
Table 1. The rotated factor matrix for the three-factor and two-factor solutions-factor loadings.
Questionnaire item The content covered by each item (In brief)
Three-factor solution Two-factor solution
Factor 1 Factor 2 Factor 3 Factor 1 Factor 2
Q1 Process standardisation 0.286 0.427 0.516 0.317 0.633
Q2 Consistency of application of processes 0.350 0.431 0.501 0.381 0.624
Q3 Valuing opinions and ideas 0.680 0.338 0.188 0.705 0.338
Q4 Making use of employee’s talent 0.719 0.327 0.211 0.743 0.342
Q5 Encouragement of employee ideas 0.604 0.309 0.278 0.626 0.375
Q6 Leadership direction for employees 0.588 0.384 0.273 0.617 0.433
Q7 Use of widest range of opinions… 0.378 0.654 0.029 0.434 0.511
Q8 Learning from errors 0.522 0.479 0.131 0.561 0.426
Q9 Knowledge sharing among members 0.611 0.472 0.215 0.648 0.465
Q10 Understanding facts prior to decision making 0.224 0.719 0.245 0.284 0.703
Q11 Stop and learn, when mistakes happen 0.250 0.607 0.292 0.300 0.642
Q12 Employee performance appraisal 0.546 0.433 0.182 0.581 0.419
Q13 Seeking consensus on common goals 0.434 0.561 0.088 0.481 0.469
Q14 Strong customer focus 0.183 0.165 0.769 0.187 0.587
Q15 Fair treatment of employees 0.710 0.275 0.217 0.729 0.305
Q16 Operational strategies and process management 0.421 0.497 0.394 0.459 0.607
Q17 Use of best practice ideas 0.361 0.490 0.291 0.400 0.541
Q18 Strong facts and data-based decision making 0.212 0.701 0.248 0.271 0.692
Q19 Prevalence of root cause analysis 0.207 0.696 0.187 0.266 0.651
Q20 Ability of employees to impact the customers 0.375 0.344 0.300 0.401 0.431
Q21 Customer service 0.216 0.149 0.759 0.220 0.567
Q22 Treating subordinates with respect 0.724 0.201 0.261 0.736 0.272
Q23 Opportunities for personal growth 0.810 0.141 0.142 0.818 0.147
Q24 Internal and external co-operation 0.488 0.235 0.336 0.493 0.365
Notes: The three-factor solution was discarded as the factor loadings fail to provide a substantive interpretation. See Table 2 for the
labels given to Factors 1 and 2 in the two-factor solution.
The values in bold (higher loadings) enable the reader to quickly identify the factor to which a particular questionnaire item relates to
(e.g. Q1 relates/belongs to Factor 2).
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12. For the purpose of SEM, the scores of each measure (e.g. kaizen) were calculated using weighted average scores
from the respective questions – for example Q1, Q2, Q7, Q17 and Q19 for kaizen. Having calculated the scores of the
five measures (kaizen, genchi genbutsu, respect and teamwork) and having assigned these measures to the constructs to
which they belong (Figure 3), we went on to test the validity of the measures and their constructs (i.e. validation of the
constructs/measurement scales) using data from the cross-validation sample.
4.2 Validation of the constructs/measurement scales
4.2.1 Testing content validity of the questionnaire items
The content validity of the survey instrument was supported on two counts. First, the questionnaire was prepared by
Toyota’s content experts (based in Toyota’s GKC) and arguably they have more reliable knowledge than anyone on the
TW philosophy, and hence on the content that is required to capture the essence of the TW (both in terms of how the
TW is approached and deployed) in the settings in which the survey is being administered. Second, the EFA supported
the view that the survey items do measure the underlying constructs (after elimination of three questionnaire items).
4.2.2 Testing construct validity and the reliability of the measurement scales
To test the construct validity (more precisely, the factorial validity) of the measurement scales of our theoretical model
(Figure 3), we conducted CFA on the hypothesised factor structure using the data in our cross-validation sample. Using
the statistical procedure described by Lee and Hershberger (1990), it can be easily shown that the theoretical model
depicting our research hypotheses (Figure 3) is equivalent to the CFA model (similar to Figure 3 when the single-headed
arrows are being replaced by the double-headed arrows) in terms of the goodness-of-fit and parameter estimates. In other
words, both the CFA model and the theoretical model shown in Figure 3 provide the exact same goodness-of-fit
measures (Table 3) and parameter estimates (Table 4), irrespective of the dataset being used.
From the global goodness-of-fit estimates depicted in Table 3 relative to the prescribed minimum cut-off values
(Byrne 2010; Hu and Bentler 1999), it becomes evident that the two equivalent models, the CFA model and the
theoretical model linking the hypotheses (Figure 3), are a good fit to the data. Having established factorial validity
Table 2. The results of the content analysis.
Factor 1 – People development Factor 2 – Process improvement
Q3 [TEAM] Q1 [KAIZ]
Q4 [RESP] Q2 [KAIZ]
Q5 [RESP] Q7 [KAIZ]
Q6 [TEAM] Q10 [GENC]
Q8 [TEAM] Q11 [GENC]
Q9 [TEAM] Q14 [CHAL]
Q12 [RESP] Q16 [CHAL]
Q15 [RESP] Q17 [KAIZ]
Q22 [RESP] Q18 [GENC]
Q23 [TEAM] Q19 [KAIZ]
Q21 [CHAL]
Note: The measures (indicators) shown in square parentheses stand for CHALlenge, KAIZen, GENChi Genbutsu, RESPect, and
TEAMwork.
Table 3. The global goodness-of-fit indices for the confirmatory factor analysis model and the theoretical model.
The global goodness-of-fit (GoF) measures Estimated value Prescribed minimum value for a good fit
χ2
/df 5.469 Smaller the better
GFI (goodness-of-fit index) 0.983 0.90 (0.95 preferred)
AGFI (adjusted goodness-of-fit index) 0.964 0.90 (0.95 preferred)
TLI (Trucker–Lewis index) 0.984 0.95
RMSEA (root mean squares error approximation) 0.059 0.70 (0.60 preferred)
Notes: (1) The χ2
and df (degrees of freedom) values that went to the estimation of χ2
/df were 92.971 and 17, respectively.
(2) There is no universally accepted χ2
/df lower bound cut-off value because χ2
/df is extremely sensitive to the sample size. For this
reason the use χ2
/df measure is discouraged (Hu and Bentler 1999).
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13. (i.e. showing that the assumed factor structure is valid subject to scale reliability which is discussed below), we proceed
to the remaining tests on construct validity.
The reliability of the measurement scales is a necessary but not sufficient condition for construct validity (Hair et al.
2006; Nunnally 1978). From the scale reliability coefficient estimates shown in Table 4 relative to the prescribed
minimum cut-off values by Nunnally (1978), it follows that the measurement scales used for the constructs are reliable.
As further tests on construct validity, we also assessed the convergent validity and discriminant validity of the
measures by examining the correlations between the constructs as well as the correlations between the constructs and
the measures (Table 5). The convergent validity can be established if it can be shown that the measures assigned to a
particular construct do strongly correlate with the construct; the discriminant validity can be shown if measures belong-
ing to a particular construct do not correlate with other constructs as strongly as they do with their assigned construct
(Chin 1998; Fornell and Larcker 1981). Based on the correlations shown in Table 5, it becomes evident that convergent
validity is shown by the measures. For example, challenge (CHAL), kaizen (KAIZ) and genchi genbutsu (GENC), the
three measures of process improvement have strong correlations of 0.762, 0.834 and 0.779, respectively. In addition, the
three constructs do extract substantial variation (50%) of their measures as evidenced from the ‘average variance
extracted’ (AVE) figures shown in Table 5. Given that the square root of AVE indicates the average correlation between
the construct and its measures (Chin 1998) and that the square roots of AVE are high (0.792, 0.920 and 0.852 for
process improvement, people development and TW deployment, respectively) this also shows further evidence of
convergent validity.
The discriminant validity of the measures is not fully apparent from the results shown in Table 5. The first three
rows in the table shows the correlations between the constructs. It is evident from the figures reported in Table 5 that
the correlations between the constructs are high, although they are not high enough to be considered multicollinear, as
discussed in the next section; a high correlation between constructs implies low discriminant validity of the measures
Table 4. The scale reliability measures.
Construct Cronbach’s alpha Composite reliability (ρ)
People development 0.916 0.916
Process improvement 0.832 0.833
TW deployment 0.888 0.888
Note: The prescribed minimum value for a reliable scale is 0.70 (Nunnally 1978).
Table 5. The factor correlations, factor loadings and cross-loadings.
Construct
Measure/Construct Process improvement (3) People development (2) TW deployment (1)
Process improvement (3) 1.000
People development (2) 0.915 1.000
TW deployment (1) 0.875 0.802 1.000
CHAL 0.762 0.697 0.666
KAIZ 0.834 0.763 0.729
GENC 0.779 0.713 0.681
RESP 0.831 0.908 0.728
TEAM 0.853 0.932 0.747
Q25 0.775 0.711 0.886
Q26 0.760 0.697 0.869
Q27 0.698 0.640 0.798
Notes:
(i) The average variance extracted (AVE) for process improvement, people development and TW deployment were 0.628, 0.847 and
0.726, respectively, while the square roots of AVE of the constructs were 0.792, 0.920 and 0.852, respectively.
(ii) The correlation between people development and TW deployment after controlling for process improvement (i.e. the partial
correlation) r12,3 was also calculated:
r12;3 ¼
r12 À r13 Â r23
ffiffiffiffiffiffiffiffiffiffiffiffiffiffi
1 À r2
13
p ffiffiffiffiffiffiffiffiffiffiffiffiffiffi
1 À r2
23
p ¼
0:802 À 0:875 Â 0:915
ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi
1 À 0:8752
p ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi
1 À 0:9152
p ¼ 0:00704:
The values in bold show the correlation between a measure and its assigned construct.
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14. being used, unless the constructs under examination are genuinely highly correlated due to conceptual reasons
(Anderson and Gerbing 1988; Byrne 2010; Fornell and Larker 1981). The correlations between the measures and the
constructs (row 4 onwards in Table 5) show that the correlation between a measure and its assigned construct is invari-
ably higher than the correlation between the same measure and a different construct, thus marginally satisfying the basic
requirement of discriminant validity. Given that the responses were not found to be substantially biased by common
method variance (Section 3.3) and that the survey instrument passed all other statistical tests satisfactorily, we concluded
that the measures are reliable and valid and that high inter-correlations observed is due to conceptual reasons rather than
due to any major flaw in the survey instrument or the survey data. For example, the measure teamwork [TEAM], which
is posited to be belonging (related) to people development, is equally strongly related to process improvement. This
finding is consistent with the literature (Flynn, Schroeder, and Sakakibara 1995; Wellins 1991).
We also observe that although the correlations in Table 5 imply low discriminant validity, the three constructs in our
model (Figure 3) are conceptually distinct in that process improvement mediates the relationship between people devel-
opment and TW deployment (hence each construct plays its part in explaining what happens). We verified this as fol-
lows. First, we regressed people development with TW deployment and verified that the former was a significant
predictor of the latter (R2
= 0.64, being the squared bivariate correlation between the two variables). We then calculated
the partial correlation between the two variables after controlling for the variance of the mediating variable process
improvement (see Table 5 for calculations). The partial correlation was found to be 0.00704 (insignificant), suggesting
that after controlling for process improvement, there is no variation left in people development to explain TW
deployment. The challenge for future research (see Section 6) is to determine how to measure the constructs accurately.
4.3 Tests on research hypotheses and practical implications
Having demonstrated that our theoretical model is a good fit to the data, we now discuss the hypothesised structural
relations between the constructs from a practical perspective.
The high standardised structural regression coefficient of 0.92 (p = 0.000) shown in Figure 3 suggests that people
development is a very strong causal antecedent of process improvement. Thus the data support our first hypothesis:
‘Process improvement is caused by people development’. Similarly, the data support our second hypothesis (β = 0.87;
p = 0.000), which posited that ‘TW deployment is caused by process improvement’. However, the non-significant
structural regression coefficient 0.01 (p = 0.940) depicted in Figure 3 suggest that the data do not support our third
hypothesis (TW deployment is caused by people development), in that the relationship between people development and
TW deployment is fully mediated by process improvement.
A summary of the methodology (tests used, etc.) and results is shown in Appendix 1 (Figure A.1).
5. Discussion
5.1 Resources and capabilities
One of the most intriguing findings of our study is that people development has no direct effect on outcomes. Instead, it
has merely an indirect effect on outcomes by leveraging process improvement. This finding underpins the importance of
‘soft’ elements (intangible resources/capabilities) of organisational approaches (Fotopoulos and Psomas 2009; Gadenne
and Sharma 2009), which are hard to measure through questionnaires and are therefore only rarely considered in quanti-
tative empirical studies. In the following we will discuss ‘soft’ elements of organisational approaches in the light of the
RBV that we covered earlier (Section 2.4). Clearly, the distinction between resources and capabilities has striking simi-
larity to our findings. In the literature review (Section 2.4), we suggested that the construct of process improvement with
its measures challenge, genchi genbutsu and kaizen represents Toyota’s tangible resources, while people development
(respect and teamwork) can best be understood as Toyota’s capabilities. In full accordance with Makadok (2001), we
found that people development as a capability had no direct effect on outcomes, while we demonstrated its capacity to
‘improve the productivity of the other resources possessed by the firm’ (389, italics in original), i.e. process
improvement.
While a large number of organisations have adopted Lean/TPS-like practices, many still struggle to achieve similar
levels of performance as Toyota. We argue that this is because Toyota’s people development capabilities are ‘organisa-
tionally embedded nontransferable [and] firm-specific’ (Makadok 2001, 389) and thus not easily imitable by competitors
(Liker 2003; Schonberger 2007; Shah and Ward 2007). As mentioned earlier (Section 2.4), the importance of capabili-
ties on competitive advantage has also been demonstrated through Powell’s seminal study (Powell 1995) on competitive
advantage and a series of empirical studies that followed it. Moreover, as discussed in Section 2.4, Schroeder, Bates,
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15. and Junttila (2002) showed that internal and external learning (a capability according to Makadok’s definition) drives
proprietary processes which in turn drive plant performance. Schroeder et al. also highlighted the role of organisational
learning for the development of new, difficult to duplicate resources, which in turn, will be able to set the organisation
apart from its competitors. This is an important point and leads over to the next subsection.
5.2 Implication for other organisations
If Toyota’s culture is unique and cannot easily be imitated by the other firms, can our findings be generalised across
other Lean organisations? The answer to this important question is twofold: first, our findings demonstrate that ‘soft’
organisational capabilities should not be expected to yield direct results for outcomes, yet they are indispensable to
leverage the effect of ‘hard’ resources such as JIT practices or Lean tools and for the further advancement of all organi-
sational resources (Makadok 2001; Schroeder, Bates, and Junttila 2002); second, if an organisation’s culture is the
results of its unique history and leadership (e.g. Schein 2010), then ‘copying’ Toyota’s culture simply will not do for
other organisations.
As a result, organisational leaders must embark on the long-term endeavour to shape an organisational culture that
facilitates the elements of process improvement, being aware that this culture will neither directly match Toyota’s origi-
nal culture, nor will it yield a direct, measureable impact on business results. Thus, the key challenge for practitioners is
to refrain from adopting piecemeal ‘quick-fix’ Lean initiatives that focus on tools at the expense of the development of
organisational capabilities. For example, managers should constantly check whether their staff development activities
actually provide the basis for process improvement activities, such as through staff retention, constant training in prob-
lem-solving, teamwork, coaching, leadership development, organisational learning and knowledge sharing. This requires
managers to possess not only technical knowhow associated with the processes but also extensive social skills in dealing
with the workforce. Thus, a core finding is that people development should be understood as an integral component of
a complete implementation of Lean. This finding is also consistent with the finding of Shah and Ward (2007) who went
into great detail in explaining why Lean is an integrated management system.
6. Conclusions
In this paper, we have tested the TW empirically. The TW is a result of the TMC codifying its fundamental beliefs and
values, in the form of a basic model for its global membership to adhere to. This is evident from the foreword provided
by the president of the TMC when the TW was first published in 2001. We have shown that the TW models Toyota’s
organisational culture. There are two interrelated pillars of the TW: CI (we called it process improvement) and respect
for people (we called it people development). According to the TMC, these two pillars (which we treated as constructs)
are the key that sets apart Toyota from its competitors. The more well-known features of Toyota such as Lean/JIT pro-
duction are a manifestation of Toyota’s unique culture of developing its people (firm-specific intangible resources and
capabilities) and work methods (firm-specific resources and capabilities). We showed that although the TW is repre-
sented as a very simple model that can be understood by its members around the world, from an academic perspective,
it can be viewed as a model on Toyota’s unique culture that provides Toyota the competitive advantage.
The objective of the TW is to achieve a ‘standardised’ organisational culture globally in all functions (within and
outside production) belonging to Toyota. This is not surprising because standardisation is at the very heart of Lean man-
agement, something that Toyota is renowned for. The theory we tested, which is represented as a model (Figure 3),
explains how people development and CI relate to the TW deployment. A business unit of Toyota that is strong on TW
deployment would frequently apply the TW principles, show outstanding knowledge of the TW, and show evidence of
healthy dialogue between managers and their subordinates as to how the TW could be used to improve results (Lean
outcomes).
The data (n = 2613) that were used by us to test our model came from a climate (culture) survey conducted by
Toyota’s Global Knowledge Centre (based in Torrance, USA) across Toyota’s logistics, sales and marketing functions
across 27 countries around the world. Our large sample empirical study confirmed that the five measures – challenge,
genchi genbutsu, kaizen, respect and teamwork – used by Toyota to operationally define the TW, are reliable and valid
measures of the TW. Our results showed that people development has no direct effect on the TW deployment. However,
our results showed that people development is indirectly related to TW deployment through the strong indirect link peo-
ple development → process improvement → TW deployment. Our study provides empirical evidence that the intangi-
ble/soft facets (modelled by us as people development) of Lean admittedly do not directly achieve results. However, our
study shows that it is these intangible/soft facets of Lean that drive the system to achieve results through the tangible/
hard facets of Lean (modelled by us as process improvement). Our findings are consistent with numerous other
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16. empirical studies that followed the seminal study of Powell (1995) on the impact of intangible resources on competitive
advantage. These other studies showed that it is the set of soft elements and not the hard elements that drive the system
(processes) to gain competitive advantage of a firm. Our study is important to academia and management because our
study is the first of its kind that examines the TW as model on organisational culture, using Toyota’s own data. Our
main finding is that people development should be understood as an integral component of a complete implementation
of Lean.
Our study provides quantitative evidence from the company that arguably invented Lean – of what organisational
theorists suspected for a long time: that while the intangible aspects of Lean may not directly improve results, they must
be understood as an integral component of a complete implementation of Lean. It provides support for a holistic and
long-term Lean strategy.
It is important to note that our study tested Lean in the context of the TW (Figure 1), taking into account the activi-
ties that are organised and done by logistics, sales and marketing staff of Toyota. The measurement of TW outside the
production floor is an attempt by Toyota to ascertain how TW is understood beyond the production floor. This falls in
line with the contemporary notion in production planning and control that internal (production floor) operational effi-
ciency alone is not sufficient for competitiveness (Olhager 2013). We have not contradicted the notion that Lean is best
implemented in a pull system (Hoop and Spearman 2004); the reader will note that Toyota’s GKC that collected the data
(the survey instrument in Appendix 2) have not considered ‘factory physics’ (Hopp and Spearman 2001) in their service
climate survey. Also, we have not invalidated the study by Spear and Bowen (1999) that looked at the tacit knowledge
within the TPS. As mentioned earlier, some of the propositions of Spear and Bowen are embedded in the survey instru-
ment used by Toyota.
In spite of being a large-sample study representing Toyota logistics, sales, and marketing facilities worldwide, a
notable limitation of our study was the practitioner focused survey instrument (used by Toyota) from which the data
came (Appendix 2). The correlations between the five measures (challenge, kaizen, genchi genbutsu, respect and team-
work) and their constructs showed concerns for low discriminant validity, implying that all measures do have the same
impact. The discriminant validity of the measures can possibly be improved by developing an alternative survey instru-
ment. Such a survey instrument should adopt reverse coded survey items where relevant with the wordings of the ques-
tionnaire items being changed to examine the constructs at more abstract level. Arguably, a more effective way to
understand how the different elements of the TW impact on outcomes (hence a future research direction) is to conduct
case studies. We did not study to what extent the TW is interpreted differently across countries and regions. This could
also be a future study that could be undertaken, after controlling for various situational factors (e.g. size of the
organisation). Another future research direction would be to conduct a longitudinal study to gain further insights on our
hypothesised relationships for which the RBV would be a promising theoretical perspective.
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19. Appendix 1. Summary of the methodology and results
Figure A.1. A summary of the methodology and results.
18 N.P. Jayamaha et al.
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20. Appendix 2. The survey questionnaire
Responses: Strongly disagree (=1), Disagree (=2), Neither disagree nor agree (=3), Agree (=4), Strongly agree (=5).
Questionnaire item Description
Q1 The processes at my company are clearly standardized
Q2 My company’s processes are consistently applied
Q3 My company treasures diverse opinions and ideas
Q4 My company delights in making the best use of employees’ backgrounds and talents
Q5 My company encourages new ideas that defy conventional wisdom
Q6 Leaders in my company help me see how changes made today will affect my company’s future
Q7 My team considers the widest range of opinions prior to developing a final solution
Q8 The leadership of this company views errors as opportunities for learning
Q9 Sharing knowledge is highly valued in my company
Q10 Before making decisions, we strive to fully understand the facts
Q11 When mistakes happen, we stop and learn from them
Q12 My success is judged based on clear, objective metrics that I can impact directly
Q13 My team always seeks consensus around common goals
Q14 This company places customer interests ahead of all others
Q15 Everyone at this company is treated fairly
Q16 My company’s processes support our strategic objectives.
Q17 In the last six months, my company has implemented a best practice idea
Q18 Our planning process is based on facts and data
Q19 My team always identifies problems at the root cause level
Q20 In the last six months, I have grown in my ability to positively impact our customers
Q21 We always provide the best available product or service to our customers
Q22 The leadership of my company always treats me with respect
Q23 Our management provides opportunities for my growth and development
Q24 There is cooperation between my department and other departments with whom I work
Q25 My company consistently uses the Toyota Way principles in our daily work
Q26 My company demonstrates outstanding knowledge of the Toyota Way
Q27 My company routinely discusses how to best implement the Toyota Way in our business
International Journal of Production Research 19
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Testing a theoretical model underlying the ‘Toyota
Way’ – An empirical study involving a large global
sample of Toyota facilities
Nihal P. Jayamaha
a
, Jürgen P. Wagner
a
, Nigel P. Grigg
a
, Nicky M. Campbell-Allen
a
& Warwick
Harvie
b
a
School of Engineering and Advanced Technology, Massey University, Palmerston North, New
Zealand
b
Toyota Global Knowledge Center, Torrance, CA, USA
Published online: 12 Feb 2014.
To cite this article: Nihal P. Jayamaha, Jürgen P. Wagner, Nigel P. Grigg, Nicky M. Campbell-Allen & Warwick Harvie (2014):
Testing a theoretical model underlying the ‘Toyota Way’ – An empirical study involving a large global sample of Toyota
facilities, International Journal of Production Research, DOI: 10.1080/00207543.2014.883467
To link to this article: http://dx.doi.org/10.1080/00207543.2014.883467
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![Testing a theoretical model underlying the ‘Toyota Way’ – an empirical study involving a
large global sample of Toyota facilities
Nihal P. Jayamahaa
*, Jürgen P. Wagnera
, Nigel P. Grigga
, Nicky M. Campbell-Allena
and Warwick Harvieb
a
School of Engineering and Advanced Technology, Massey University, Palmerston North, New Zealand; b
Toyota Global Knowledge
Center, Torrance, CA, USA
(Received 4 October 2012; accepted 6 January 2014)
In this paper, we empirically test the theoretical model underlying the Toyota Way (TW), based on data obtained from
Toyota’s logistics, sales and marketing functions across 27 countries. TW is the result of Toyota attempting to codify its
culture to the global community. Using structural equation modelling techniques we show that the TW-associated
measures challenge, kaizen, genchi genbutsu, respect and teamwork do adequately operationally define the TW; the first
three measures corresponding to the construct ‘process improvement’ and the final two measures corresponding to the
construct ‘people development’. Empirically, people development is found to have no direct effect on how the TW is
deployed across a business unit. However, people development is found to be indirectly related to TW deployment
through the mediating effect of process improvement. Our study provides quantitative evidence that while the intangible
aspects of the TW (modelled as people development) may not directly relate to the results, they are an integral compo-
nent of a complete implementation of the TW and related ‘Lean’ systems. By logical extension, this provides support for
adoption of a holistic and long-term strategy, integrating soft and hard elements, by those organisations attempting to
implement and sustain Toyota-style systems.
Keywords: Toyota Way; continuous improvement; people development; intangible resources; structural equation
modelling
1. Introduction
It is widely recognised within operations management that when it comes to production and supply chain efficiency, not
many companies can rival Toyota Motor Corporation (TMC) (Finch 2008; Lander and Liker 2007; New 2007; Womack
and Jones 2003). One aspect that sets Toyota apart from others is its unique Toyota Production System (TPS), which
integrates the people of Toyota with its technical system. This socio-technical manufacturing system was first published
by Sugimori et al. (1977), followed by further dissemination by one of Toyota’s founding engineers, Ohno (1988). At
the very outset of his book, Ohno asserts that TPS can be viewed not only as a unique and efficient production system,
but also as a philosophy of getting the best out of its people (Toyota and its partners) through developing the human
resources. Many scholars (e.g. Dyer and Nobeoka 2000; Jayaram, Das, and Nicole 2010; Lander and Liker 2007; Liker
2003; Monden 1998; Rother 2010; Spear and Bowen 1999; Womack, Jones, and Roos 1990) have since researched the
TPS in detail, and extensive literature on the TPS as a prescriptive set of tools, techniques and management practices is
widely available. TPS has more recently come to be generalised globally as being virtually synonymous with Lean, or
Lean thinking (e.g. Womack and Jones 2003), through the mechanisms described as follows:
1.1 The evolution of lean concepts
‘Lean’ is a term and a concept that has evolved over many years (Hines, Holweg, and Rich 2004; Schonberger 2007).
In the 1980s and 1990s, much research was being conducted on just-in-time (JIT) production, which forms a corner-
stone of contemporary conceptualisations of Lean. JIT as a method focused on scheduling of resources in the right
quantity, exactly when needed (Chase, Aquilano, and Jacobs 2004; Schonberger 2007; Shah and Ward 2007). However,
JIT also represented a wider management philosophy. This dichotomy is evidenced through references by Chase,
Aquilano, and Jacobs (2004, 427) to early and later versions of Lean as, respectively, ‘little JIT’ and ‘big JIT’. The term
‘Lean’ began to be adopted after John Krafcik and his team at MIT (led by James Womack) conducted extensive
*Corresponding author. Email: N.P.Jayamaha@massey.ac.nz
© 2014 Taylor & Francis
International Journal of Production Research, 2014
http://dx.doi.org/10.1080/00207543.2014.883467
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