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Total Quality Management & Business Excellence
ISSN: 1478-3363 (Print) 1478-3371 (Online) Journal homepage: http://www.tandfonline.com/loi/ctqm20
Lean, process improvement and customer-focused
performance. Themoderating effect of perceived
organisational context
Marcel F. van Assen
To cite this article: Marcel F. van Assen (2018): Lean, process improvement and customer-
focused performance. Themoderating effect of perceived organisational context, Total Quality
Management & Business Excellence, DOI: 10.1080/14783363.2018.1530591
To link to this article: https://doi.org/10.1080/14783363.2018.1530591
© 2018 The Author(s). Published by Informa
UK Limited, trading as Taylor & Francis
Group
Published online: 09 Oct 2018.
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Lean, process improvement and customer-focused performance.
The moderating effect of perceived organisational context
Marcel F. van Assen*
TIAS School for Business and Society, Tilburg University, Tilburg, The Netherlands
Lean is often considered as a collection of practices that can be used to achieve high
operational performance. However, based on contingency theory and the theory of
rational accounts, we show that organisations create fit between Lean practices and
the perceived organisational context. Specifically, we show that the impact of Lean
on process improvement performance is enhanced in an environment where process
standardisation is deemed important. However, we also show that Lean is positively
related to customer-focused performance and that this relationship is positively
moderated in an environment where customer effectiveness is deemed important.
Finally, we show that the relationship between Lean and customer-focused
performance is partially mediated by the extent of process improvement.
Keywords: Lean; standardisation; process improvement; customer performance;
organisational context
1. Introduction
Lean is defined as a collection of practices that work together synergistically to create a high
quality, streamlined system that produces finished products at the rate of customer demand
with little waste (Shah & Ward, 2003). Practices commonly associated with Lean include
the capability to create flow including set-up time reduction and pull (Cagliano, Caniato, &
Spina, 2006), quality control (Narasimhan, Swink, & Kim, 2006) and human resource
development (Sakakibara, Flynn, Schroeder, & Morris, 1997), ultimately to improve firm
performance (Eroglu & Hofer, 2011) due to process improvement performance and custo-
mer-focused performance, i.e. the extent to which an organisation effectively meets its cus-
tomer needs (Patel, Azadegan, & Ellram, 2013). Indeed, Lean is a practical approach to
improve processes by identifying and eliminating non-value-adding activities from a cus-
tomer perspective (Schonberger, 2007) resulting in higher customer-focused performance
such as quick response to customer inquiries, speed of complaint handling and customer
satisfaction through the improvement of business processes, though this has never been
empirically validated (Jasti & Kodali, 2015; Negrão, Filho, & Marodin, 2017). Lean’s per-
formance contribution reported in the literature varies: some studies found that Lean has a
positive impact on operational and financial performance (Claycomb, Germain, & Dröge,
1999; Fullerton, McWatters, & Fawson, 2003) while others found no impact (Jayaram,
Vickery, & Droge, 2008). This inconsistency is partly explained by pointing out that
there are various mediating factors in the relationship between Lean and financial perform-
ance, including the use of non-financial performance measures (Fullerton & Wempe, 2009),
© 2018 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group
This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License
(http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium,
provided the original work is properly cited, and is not altered, transformed, or built upon in any way.
*Email: m.vanassen@tias.edu
Total Quality Management, 2018
https://doi.org/10.1080/14783363.2018.1530591
environmental complexity and dynamism (Azadegan, Patel, Zangoueinezhad, & Linder-
man, 2013) and the building of close relationships with key supply chain partners
(Jayaram et al., 2008). Scholars also noticed that Lean is not an unambiguously universal
concept (Sousa & Voss, 2001) that can be easily implemented as a standard off-the-shelf
method (Lewis, 2000); instead it must be adapted and tailored to the specific organisational
context to gain full benefits (e.g. Chavez et al., 2015; Mackelprang & Nair, 2010; Marodin
& Saurin, 2015) as Lean works different in different contexts. As a consequence, contextual
variables, and the way Lean is implemented accordingly, moderate the relationship between
Lean and performance. Indeed, Zhang, Linderman, and Schroeder (2012) showed that the
impact of various practices on performance is moderated by various contextual variables
such as perceived environmental (un)certainty. This can be explained with contingency
theory suggesting that organisations create fit between operations management practices
and perceived organisational context (Sousa & Voss, 2001,2008). Organisations operating
in stable environments, in which standardisation is deemed important, are likely to adapt
Lean mainly to this aim (i.e. reduce waste, variability and complexity as much as possible),
while organisations operating in environments in which customer effectiveness are deemed
important, tailor Lean to increase customer-focused performance by adapting customer-
related variability and complexity. In this paper, we aim to examine the influence of
these two perceived contextual factors on the performance benefit of Lean. The research
question of this paper is whether the effect of Lean on both process improvement perform-
ance and customer-focused performance are moderated by the level of perceived impor-
tance attached to (process) standardisation in the market and the level of perceived
importance attached to customer effectiveness in the market?
This paper contributes to the existing literature on Lean by examining the perceived
context as a moderator in the relationship between Lean and performance. In addition,
we show that process improvement performance partially mediates the relationship
between Lean and customer-focused performance. This paper is organised as follows:
section 2 presents the research model with hypotheses. Data, variables and research
methods to validate the research model are discussed in section 3 and the statistical
results are described in section 4. The findings and the implications for practice and
(future) research are discussed in section 5.
2. Background and hypotheses
Though the term Lean was introduced by Krafcik (1988), it became globally renowned
after the book ‘The machine that changed the world’by Womack, Jones and Roos was
published in (1990). After that, Lean became related to superior productivity and
quality, supposedly due to the use of various operational tools (Oliver, Delbridge,
Jones, & Lowe, 1994), principles (Liker, 2004) and practices (Shah & Ward, 2003,
2007). A basic premise of Lean manufacturing is operational stability (Ohno, 1988),
which is reflected in standard work (i.e. the standard operating procedures), uniform
workload (Jasti & Kodali, 2015) and level scheduling (Naylor, Naim, & Berry,
1999). A key operational Lean tool to facilitate uniform workload and pace the pro-
duction process is the takt time: the rate of production required to meet demand
(Lander & Liker, 2007). In fact, the takt time is also a target cycle time used to redesign
production and balance the workload to match customer demand. Clearly the use of takt
time implies that demand must be relatively stable to prevent the production system
becoming nervous (Hopp & Spearman, 2004). This concurs with the notion that Lean
was basically developed for repetitive production environments where standardisation
2M.F. Van Assen
is important (Spear & Bowen, 1999). Lean is therefore generally associated with the
commoditisation of processes (Davenport, 2005).
Most Lean practices and operational tools are used on the shop floor to analyse, improve
and control the value stream. Indeed, a core activity in a Lean organisation is to map,
analyse and improve value streams and business processes to eliminate non-value adding
activities: only those activities that really add value for the customer are kept (Jasti &
Kodali, 2015). Lean is therefore considered a process improvement methodology used to
deliver products and services better, faster and at a lower cost (Laureani & Antony,
2017). Indeed, Lean is geared towards the increase of operational efficiency by streamlining
and improving processes. Lean seeks improvement by process simplification (e.g. Schon-
berger, 2007), the identification and elimination of non-value-adding tasks (Shah & Ward,
2003), the reduction of unnecessary internal customer-supplier relationships in each
process, and the reduction of dysfunctional process variability (Hopp & Spearman,
2004). Hence, Lean positively relates to process improvement performance (Choi &
Eboch, 1998; Cua, McKone, & Schroeder, 2001). We, therefore, have the following
proposition:
H1. Lean is positively related to process improvement performance
Lean and its subsystems TQM and JIT are positively related to the value to customer (Tu,
Vonderembse, & Ragu-Nathan, 2001) and greater customer focus (Done, Voss, & Rytter,
2011). Lean is seen as an important method to work in a more customer-oriented way
throughout the organisation (Lin et al., 2010). The use of Lean positively impacts customer
satisfaction (Choi & Eboch, 1998). Lean is used to ensure the production and delivery of
services/products conform to what the customer needs (‘voice of the customer’)by
means of analysing, improving and controlling the value stream, i.e. delivering the
correct product/service at the right time in the right place (Laureani & Antony, 2017).
Indeed, Lean is based on the premise of building close supplier–customer relationships
in which the customer is highly involved in product-development and process improvement
(Lander & Liker, 2007) resulting in a direct relationship between Lean and customer-
focused performance such as delivery reliability, quick response to customer inquiries
and customer satisfaction (Fullerton & McWatters, 2001).
H2. Lean is positively related to customer-focused performance
In order to improve processes from a Lean perspective, first the desired output of that
process must be specified and who the user of that output is. For this it is necessary to
know exactly who the customer is and what customer value is as that defines what waste
is (from a customer perspective). Subsequently, waste (muda) and unnecessary (dysfunc-
tional) variability (mura) are eliminated (see e.g. Hopp & Spearman, 2004). This leads
not only to higher labour productivity and quality, but also to a reduction in customer
lead time (Shah & Ward, 2003). Hence, the ultimate purpose of lean is the continuous
improvement of work processes for the purpose of customer value (Hines, Holweg, &
Rich, 2004). Indeed, Lean is geared towards customer-oriented process improvements
(Holmemo & Ingvaldsen, 2015). Process improvements (i.e. reduction of waste and com-
plexity) result in higher delivery reliability, shorter lead times and thus quicker response to
demand, hence better customer response performance and higher customer satisfaction
(Wilson & Collier, 2000). We therefore hypothesise that process improvement performance
is positively related to customer-focused performance.
H3. Process improvement performance is positively related to customer-focused performance
Total Quality Management 3
On one hand, Lean is aimed to reduce variability and waste as much as possible by means of
standardisation, while on the other hand it is aimed to maximise customer value by means
of customisation. i.e. delivering the requested variability according to customer require-
ments. Lean is therefore ambidextrous in nature (Adler, Goldoftas, & Levine, 1999). It is
about variability reduction (standardisation) and variability adaptation (delivering customer
value). For most organisations, this means that the implementation and use of Lean means
finding a balance between these contradictions in accordance with the specific organis-
ational context. Indeed, organisations try to adapt practices to make them meaningful
and suitable within their specific organisational contexts (Strang & Macy, 2001) creating
a dynamic fit between practices and the perceived context by the adopter (Ansari, Fiss,
& Zajac, 2010). This phenomenon can be explained by both contingency theory (Sousa
& Voss, 2008) and the theory of rational accounts (Strang & Macy, 2001), i.e. organisations
tailor practices as they focus on the presumed economic benefits that result from the adap-
tation of a practice. Initially, an organisation adopts and (try to) implements ‘standard’Lean
practices based on observed behaviours on early adopters (Ansari et al., 2010) or based on
the advice and help of a consultant (McAdam & Evans, 2004). Then, with more accurate
information about a specific practice, the organisation decides to adjust the practice to fit
the perceived context consistent with their value expectation regarding that practice. This
means that in time, such practice will be reframed to match the perceived organisational
context, leading to better results. Consequently, the performance benefits of practices
depend on the perceived organisational context (Marodin & Saurin, 2013). For instance,
if an organisation deems efficiency and standardisation to be important in the market, it
will adapt and use Lean practices to standardise and improve processes accordingly. In con-
trast, the more important it is in the market to quickly and precisely meet customer demand
and needs, the more the organisation will adapt and use Lean for that objective (Shah &
Ward, 2007). Organisations select and tailor practices to suit their strategic choices
within a given environment (Ansari et al, 2010). Lander and Liker (2007) for instance
acknowledge that Lean is initially used to produce standardised products as efficiently as
possible in a stable context, but they also show that Lean can be successfully adapted to
make highly customised and creative products the Toyota way if the organisation is sin-
cerely willing to become customer centric and empower the workforce to continuously
improve products and processes from a customer perspective. Organisations will standar-
dise, improve and optimise their processes with Lean (i.e. the reduction of variation and
complexity and the elimination of waste) if they consider (process) standardisation impor-
tant in the organisational environment. In contrast, organisations that deem customer effec-
tiveness more important in the market, will mainly adapt and apply Lean to improve
customer-focused performance. However, placing too much emphasis on delivering
unique customer value, because the market deems customer effectiveness important, may
lead to a lower internal focus on efficiency and thus to a lower degree of process improve-
ment performance, while an overemphasis of standardisation, efficiency and low cost leads
to less customisation that dangers customer performance. Radnor & Johnston (2013) for
instance found that many public service organisations used Lean primarily to improve
internal operations due to the efficiency agenda in the public domain (i.e. the market)
leading to a process focus, rather than a market driven approach focusing on the the delivery
of customer value, which may hamper the improvement of customer-focused performance
(Hallgren & Olhager, 2009). We therefore hypothesise that there is a positive interaction
between the perceived importance attached to process standardisation in the market and
Lean, such that the higher the perceived importance attached to process standardisation
in the market, the stronger the positive effect of Lean on process improvement performance
4M.F. Van Assen
and the lower the effect of Lean on customer-focused performance. Similarly, we hypoth-
esise that there is a positive interaction between the perceived importance attached to cus-
tomer effectiveness in the market and Lean, such that the higher the perceived importance
attached to customer effectiveness in the market, the stronger the positive effect of Lean on
customer-focused performance and the lower the effect of Lean on process standardisation.
H4. The relationship between Lean and process improvement performance is a) positively
moderated by the perceived importance attached to process standardisation in the market,
and b) negatively moderated by the perceived importance attached to customer effectiveness
in the market
H5. The relationship between Lean and customer-focused performance is a) positively moder-
ated by the perceived importance attached to customer effectiveness in the market, and b)
negatively moderated by the perceived importance attached to process standardisation in
the market
The five hypotheses are summarised in Figure 1, which presents our research model.
3. Methodology
3.1. Data collection
To test the hypothesised research model we collected data from business school participants
in the period 2012/2013.Participants, predominantly middle managers, were asked to fill
out a questionnaire before they attended an Operational Excellence / Lean related course.
We explicitly remarked that we would use the results anonymously as a type of OpX-
scan during the course and for research. 80% of the participants filled out the questionnaire
resulting in 205 questionnaires, of which 198 were useful for research. There were no sig-
nificant differences between the respondents of the subsequent courses in time. In addition,
the respondents averaged 8.5 years’work experience with their current organisation: see
Table 1.
Figure 1. Hypothesised research model.
Total Quality Management 5
Table 1. Profile of survey respondents.
NAICS
codes Type of industry Percentage Function Percentage
Years of employment at this
organization Percentage
22 Energy 5 Non-management 23,6 <1 year 5
23 Construction 2 Middle-
management
66,3 1–3 years 12
31–33 Industry 17 Higher-
management
10,1 3–5 years 23
43 Wholesale Trade 6 5–10 years 15
48–49 Transportation and warehousing 3 10–15 years 1
52 Finance and Insurance 9 15–20 years 1
53 Real estate and rental and leasing 2 >20 years 8
54 Professional, scientific and technical
services
12
56 Water supply and waste management 1
61 Educational services 5
62 Health care and social assistance 18
81 Other services (except public
administration)
3
92 Public services 10
Missing 7 35
Total 100 100 100
6M.F. Van Assen
3.2. Measures, scale development and purification
To increase the generalisability and applicability of our research, we adapted the fam-
iliar operationalisation of Shah and Ward (2007) as a measure of Lean for both manu-
facturing and services industries; we excluded maintenance practices, JIT-delivery and
developing suppliers as these practices are less common in service environments
(Bowen & Youngdahl, 1998). The final scale includes set-up reduction (Cronbach α
= .85), controlled processes (α= .74), pull control (α= .87), flow (α= .68), involved
employees (α= .70), involved customers (α= .64), and supplier feedback (α= .64).
Items were estimated through respondents’perceptual evaluation on a five-point
Likert scale. The response categories for each item were anchored by 1 (strongly dis-
agree) and 5 (strongly agree).
Customer-focused performance (α= .75) was measured using items developed by
Patel et al. (2013). Respondents were required to indicate what their performance was
compared with competitors in their industry with respect to delivery reliability (CFP1),
quick response to customer inquiries (CFP2) and customer satisfaction (CFP3). In a
similar way, we developed a scale for process improvement performance (α= .83)
where respondents were required to indicate what their performance was compared
with competitors in their industry with respect to reduction of complexity in processes
(PIP1), reduction of waste in processes (PIP2), rate of improvement of processes
(PIP3), reduction of waiting time in processes (PIP4) and reduction of dysfunctional varia-
bility in processes (PIP5). The items were measured using 5-point Likert scales anchored
with ‘much worse than competition’and ‘much better than competition’. To investigate
the moderating influence of the environment in the relationship between Lean and
process improvement performance, we also asked respondents to rate the importance
attached to process standardisation in the market (ISM: Cronbach alpha = .84) and the
importance attached to customer effectiveness in the Market (ICEM: Cronbach alpha
= .80) for engaging in competition.
We evaluated the unidimensionality, reliability and convergent validity of the scales
using confirmatory factor analysis in the software package AMOS 23. For satisfactory con-
vergent validity, the estimated parameters between the latent variables and their indicators
should be at least 0.50 (Hair, Andreson, Tatham, & Black, 1998) and the average variances
extracted (AVE) should also be at least 0.50. Some items have therefore been removed from
the final scales. The full measurement model with all items and constructs fits the data well
given x2= 707.596 df. = 505, p< .001, CFI = .918, IFI = .921, NNFI/TLI = .903, RMSEA
= .045; see Table 7 in the appendix. In addition, the correlation matrix for all constructs with
Cronbach’s alpha values on the diagonal, is presented in Table 2.
To test for discriminant validity, we performed chi-square difference tests on the result
of CFA’s for an unconstrained model versus a constrained model for each pair of constructs
of the scales for Lean and management behaviour, where the covariance parameter of the
pair of constructs was constrained at 1 in the constrained model and set to be free in the
unconstrained model. For satisfactory discriminant validity, the x2-difference values
should be greater than 3.84 (Bagozzi, 1981; Bagozzi & Phillips, 1982; Kim, Kumar, &
Kumar, 2012; Ng, Rungtusanatham, Zhao, & Lee, 2015). The x2-difference values
ranged from 23.9 to 161.3 indicating satisfactory discriminant validity.
Cronbach’s alpha coefficients exceed.70 for all main constructs, which indicates satis-
factory reliability (Cronbach, 1951). In addition, all Cronbach alpha values are greater than
the correlations, which also indicates satisfactory discriminant validity; see e.g. Kaynak
(2003).
Total Quality Management 7
Table 2. Descriptive statistics and correlation matrix with Cronbach’s alpha on the diagonal.
Mean S.D. Lean PIP CFP ISM ICEM Size Tenure Pos 1 Pos 2
Lean 2.67 0.70 .82
Process improvement performance (PIP) 3.16 0.68 .36** .83
Customer-focused performance (CFP) 3.71 0.70 .34** .35** .75
Importance of standardisation in the market (ISM) 3.60 0.72 .11 .05 .00 .84
Importance of customer effectiveness in the market (ICEM) 4.21 0.65 .08 −.07 .02 .25** .80
Size 2.99 0.88 .07 −.05 −.04 .07 .04 -
Tenure 3.74 3.08 .01 −.01 .09 −.06 −.02 −.21** -
Pos 1 (dummy for non-management position) - - −.16* −.09 −.10 .02 .04 −.01 −.08 -
Pos 2 (dummy for middle management position) - - .04 .07 −.04 −.01 −.08 .02 −.03 −.78** -
Pos 3 (dummy for higher management position) - - .16* .01 .20** −.01 .06 −.01 .15* −.18** −.47**
**p< .01 level (2-tailed).
*p< .05 level (2-tailed).
8M.F. Van Assen
3.3. Control variables and common method bias
We used size, tenure and hierarchical position (for which we created dummy variables) as
control variables. Size, for instance, is considered a control variable since smaller organis-
ations typically have fewer resources for process improvement practices like Lean (Cao &
Zhang, 2011). Size of the organisation was measured by the number of employees (loga-
rithmised). There are interdependencies among control variables. As expected there is a cor-
relation tenure and higher management position (.15) and tenure and firm size (−.21).
Furthermore, a non-management position correlates negatively with Lean. However,
since these correlations are below.3 we conclude that the control variables do not structu-
rally associate with any of the main variables.
Procedural methods were applied to minimise the potential for common method bias
since both the independent and dependent measures were obtained from the same source
(Podsakoff & Organ, 1986). Our sample included predominantly mid to senior level man-
agers with significant levels of relevant knowledge, which tends to mitigate single source
bias (Mitchell, 1985). Common method bias was also reduced by separating the dependent
and independent variable items over the length of the survey instrument and by assuring
participants that their individual responses would be kept anonymous (Podsakoff,
MacKenzie, Lee, & Podsakoff, 2003). We also applied Harman’s one-factor test to
assess whether common method bias exists (Podsakoff et al., 2003). All variables were
entered into an unrotated exploratory factor analysis to test whether the majority of the var-
iance can be explained by a single factor, but this was not the case (explained variance by
one factor is 18%). Finally, we applied a common latent factor analysis in AMOS 23 to
assess whether common method bias exists (Podsakoff et al., 2003). Common latent
factor analysis with respect to the full measurement model with all variables resulted in a
common variance of 7% and all changes in factor loadings of the items are smaller than
0.2. We can therefore conclude that the tests of reliability, validity, overall model fit and
common method bias provide adequate support for the appropriateness of the model
constructs.
4. Results
4.1. The impact of Lean on process improvement performance & moderation
analysis
To estimate the effect of Lean on process improvement performance and whether this
relationship is moderated by ISM and ICEM, we tested a hierarchical regression model
using SPSS after mean-centring the variables; see Table 3 for the results including VIF
values suggesting that multicollinearity was not a problem. The adjusted R
2
changes signifi-
cantly from model M1 to model M2: ΔF= 28.79, adjusted R
2
= .12, p< .001) and from
model M2 to model M3: ΔF= 3.46, adjusted R
2
= .14, p< .05). Both the coefficients for
Lean (b= .20, p< .001) and the interaction term Lean × ISM (b= .09, p< .01) were positive
and significant in M3, while the coefficients of the interaction term Lean × ICEM (b=−.07,
p= .076) and the control variables were not significant. Hence, we conclude that ISM posi-
tively moderates the influence of Lean on process improvement performance.
To evaluate the effect of ISM as a moderator in the relationship between Lean and
process improvement performance (PIP), we plotted the effect (see Figure 2) by testing
the simple slopes for respondents with higher levels (i.e. one standard deviation above
the mean), average levels, and lower levels of ISM to determine the nature of the ISM ×
Lean interaction. Lean was significantly related to process improvement performance for
Total Quality Management 9
lower levels of ISM (b= .27, p< .01) for average levels of ISM (b= .45, p<.001) and for
higher levels of ISM (b= .63, p< .001).
Note that Figure 2 suggests that respondents with low to average levels of Lean, have
lower PIP levels if they perceive higher levels of ISM. However, to analyse the moderating
effect of ISM in more detail we used the Johnson-Neyman technique with bootstrapping as
recommended by (Preacher, Rucker, & Hayes, 2007) employing 1000 bootstrap replica-
tions. The estimates of the indirect effect and (bias corrected) confidence bands are
plotted in Figure 3. Given mean-centred values of ISM, the significance region for the inter-
action is above the threshold value for ISM of −.84 SD from the mean, where Lean is just
significantly related to process improvement performance (b= .23, p= .05). Of interest in
Figure 2. Interaction of ISM and Lean on process improvement.
Table 3. Hierarchical regression model for PIP to test the moderators.
N= 198 M1 M2 M3
Variables b t b t b t VIF
Tenure −.01 −.41 .00 −.37 .00 −.28 1.08
Size −.03 −.83 −.05 −1.23 −.05 −1.18 1.05
Pos 2: Middle management .12 1.28 .05 .62 .07 .76 1.32
Pos 3: Higher management .12 .80 −.04 −.26 −.01 −.05 1.40
Lean .20*** 5.37 .20*** 5.43 1.06
Lean × ICEM −.07 −1.84 1.18
Lean × ISM .09** 2.44 1.19
Adjusted R
2
−.01 .12 .14
R
2
.01 .14 .17
ΔF.59 p= .67 28.79 p= .00 3.46 p= .03
Notes: N= 198, ***p< .001 level (2-tailed), **p< .01 level (2-tailed), *p< .05 level (2-tailed). Unstandardised
coefficients are reported.
10 M.F. Van Assen
this figure is the insight that the strength of the indirect effect of ISM via Lean on process
improvement performance increases with the level of ISM. Below the threshold, Lean has
no significant effect on process improvement performance. For respondents that indicated
that standardisation is not important in their markets, Lean has no effect on process
improvement performance. From this threshold value, the more important process standard-
isation is in the market, the greater the impact of Lean on process improvement performance
is. We therefore conclude that the test supported hypothesis 4a.
4.2. The impact of Lean on customer-focused performance (CFP) & moderation
analysis
To estimate i) the relationship between Lean and customer-focused performance (CFP) and
ii) whether this relationship is moderated by ISM and ICEM, we tested a second hierarch-
ical regression model using SPSS; see Table 4 for the results. The adjusted R
2
changes sig-
nificantly from model M4 to model M5: ΔF= 18.87, adjusted R
2
= .18, p< .001) and from
model M5 to model M6: ΔF= 3.73, adjusted R
2
= .20, p< .05). Both the coefficients for
Lean (b= .27, p< .001), process improvement performance (PIP) (b= .29, p< .001) and
the interaction term Lean × ICEM (b= .10, p< .01) were positive and significant in the
third step (i.e. model M6), while the coefficients of the interaction term Lean × ISM (b=
−.02) and the control variables were not significant except for higher management, indicat-
ing that respondents with a higher management position significantly rate customer-focused
performance higher. In all, we conclude that ICEM positively moderates the influence of
Lean on customer-focused performance.
To analyse the interaction effect of Lean × ICEM we also tested the simple slopes for
respondents with higher levels of ICEM (one standard deviation above the mean), with
respondents with average levels of ICEM and respondents with lower levels of ICEM
Figure 3. Interaction of ISM and Lean on process improvement.
Total Quality Management 11
(one standard deviation below the mean) to determine the nature of the ICEM × Lean inter-
action on customer-focused performance; see Figure 4. Lean was significantly related to cus-
tomer-focused performance for average levels of ICEM (b= .29, p< .01) and for higher
levels of ICEM (b= .48, p< .01), but not for lower levels of ICEM (b= .10, p= .311).
We analysed the Johnson-Neyman significant region for ICEM too; see Figure 5. Given
mean-centred values of perceived importance attached to customer effectiveness in the
market, the significance region for the interaction is above the threshold value for ICEM
of −.55 SD from the mean, where Lean is just significantly related to customer-focused per-
formance (b= .22, p= .05). Only 13.1% of the respondents have a value of this moderator
less than −.55. Lean has no effect on customer-focused performance for these respondents
Figure 4. Interaction of ICEM and Lean on customer-focused performance.
Table 4. Hierarchical regression model for CFP to test the moderators.
N= 198 M4 M5 M6
Variables b t b t b t VIF
Tenure .01 .71 .01 .87 .01 .87 1.08
Size −.02 −.43 −.02 −.43 −.02 −.43 1.06
Pos 2: Middle management .08 .88 .01 .11 .01 .11 1.33
Pos 3: Higher management .40** 2.73 .28* 1.98 .29* 2.08 1.40
Lean .27** 3.20 .27*** 3.28 1.20
PIP .27*** 3.74 .29*** 3.98 1.21
Lean × ICEM .10** 2.64 1.20
Lean × ISM −.02 −.42 1.23
Adjusted R
2
.03 .18 .20
R
2
.05 .20 .23
ΔF2.36 p= .06 18.87 p= .00 3.73 p= .03
Notes: N= 198, ***p< .001 level (2-tailed), **p< .01 level (2-tailed), *p< .05 level (2-tailed). Unstandardised
coefficients are reported.
12 M.F. Van Assen
who perceive customer effectiveness as unimportant in their market. From this threshold,
the more ICEM the more impact Lean has on customer-focused performance. In all, we
conclude that the test supported hypothesis 5a.
4.3. Mediation analysis
To investigate to whether process improvement performance (PIP) is a mediator in the
relationship between Lean and customer-focused performance (CFP), the direct effects
model (M6) is compared with a total effect model; see Table 5. The total effect of Lean
Figure 5. Interaction of ICEM and Lean on customer-focused performance.
Table 5. Mediator regression model.
N= 198 M7
Total effect model
Variables b t VIF
Tenure .01 .76 1.08
Size −.03 −.75 1.06
Pos 2: Middle management .03 .11 1.33
Pos 3: Higher management .28* 1.99 1.40
Lean .39*** 4.90 1.06
Lean × ICEM .08** 2.06 1.18
Lean × ISM .01 .27 1.20
Adjusted R
2
.14
R
2
.17
ΔF2.77 p= .07
Notes: N= 198, ***p< .001 level (2-tailed), **p< .01 level (2-tailed), *p< .05 level (2-tailed). Unstandardised
coefficients are reported.
Total Quality Management 13
on customer-focused performance (b= .39, p< .001) is much higher than the direct effect of
Lean on customer-focused performance (b= .27, p< .001) though the latter is still signifi-
cant, which means that process improvement performance is only a partial mediator in the
relation between Lean and customer-focused performance. In other words, process
improvement performance lessens the effect of Lean on customer-focused performance.
This means that there is a direct path between Lean and customer-focused performance,
but that this relationship is partially mediated by process improvement performance. The
effect size (.11) of this mediator is significant with κ
2
= .11, Z = 2.32, p=.02.
5. Discussion
5.1. Findings
Lean is broadly classified under the umbrella of process improvement and world class oper-
ations, which also include other approaches like business process re-engineering and the
theory of constraints (Shah, Chandrasekaran, & Linderman, 2008). This study shows that
Lean directly impact process improvement performance (H1) and customer-focused per-
formance (H2), which concurs with the findings of Mackelprang and Nair (2010).
However, this study also shows that these relationships are moderated by the perceived
organisational context. The impact of Lean on process improvement performance is
enhanced in a context in which standardisation is perceived to be important (H4a). This
research also shows that the impact of Lean on customer-focused performance is enhanced
in a context where customer effectiveness is considered to be important (H5a); see Table 6
for an overview of the hypotheses testing results.o
Based on our findings, we conclude that organisations use and adapt Lean practices
according to the perceived requirements for standardisation in the market to improve pro-
cesses (i.e. the reduction of waste, complexity and variability) and simultaneously use and
adapt Lean practices according to the perceived requirements for meeting customer expec-
tations in the market to improve customer-focused performance processes (i.e. variability
adaptation). This concurs with the findings of Adler et al. (1999) that a Lean organisation
is an ambidextrous organisation capable to balance the simultaneous demand for variation
reduction and adaptation. Our results show that Lean is both useful in commodity
Table 6. Hypotheses testing results.
Hypothesis Path btSupported? Model
H1 Lean →process improvement
performance (PIP)
.20 5.43 Yes;
p<.001
M3, Table 3
H2 Lean →customer-focused performance
(CFP)
.27 3.28 Yes;
p<.001
M6, Table 4
H3 PIP →customer-focused performance
(CFP)
.29 3.98 Yes;
p<.001
M6, Table 4
H4a Lean × ISM →PIP .09 2.44 Yes;
p<.01
M3, Table 3
H4b Lean × ICEM →PIP −.07 −1.84 No;
p>.1
M3, Table 3
H5a Lean × ICEM →CFP .10 2.64 Yes;
p< .01
M6, Table 4
H5b Lean × ISM →CFP −.02 −.42 No;
p>.1
M6, Table 4
14 M.F. Van Assen
environments with stable and repetitive demand (Hopp & Spearman, 2004) and in capa-
bility environments in which organisations use and adapt Lean to meet customer require-
ments and increase customer-focused performance. In fact, Lean affects customer-
focused performance in at least two ways. Lean impacts customer-focused performance
directly as a result of better knowledge of customer value and customer requirements
and the adaptation of customer related variability, and indirectly through improved pro-
cesses. As a result, a Lean organisation is able to deliver customer value more efficiently
and effectively.
5.2. Implications
In this study, we make a distinction between process improvement performance and custo-
mer-focused performance and show that the perceived organisational context impact these
performance variables differently. If in the perception of the organisation the importance
attached to process standardisation in the market is high, for example in a commodity
market with strong competition on price, then the organisation will apply and adapt Lean
practices to standardise as much as possible to reduce costs. This research, however, also
shows that if customer effectiveness is deemed to be important in the market, organisations
also use Lean. After all, the objective of Lean is to deliver the right customer value at the
lowest cost. Lean can be applied to improve business processes and to manage variability
and complexity. The key question is which variability is functional and what is dysfunc-
tional. As this is determined by both the customer (i.e. the voice-of-the-customer) and
the organisation (the voice-of-the-business) it requires Lean to balance effectiveness (varia-
bility adaptation) and efficiency (variability reduction): delivering the right product or
service at the lowest cost. Hence, Lean may be geared towards the delivery of a commodity
product at the lowest possible costs if that yields optimal customer value, but Lean may also
be geared towards a customised product at the lowest possible costs.
Unfortunately, many organisations have tried to implement programmes like TQM, JIT
and Lean as universal one-size-fits-all off-the-shelf method (see e.g. Sousa & Voss, 2001)
while in fact organisations must adapt and tailor these methods to their context over time
(see e.g. Ansari et al., 2010). In addition, scholars have mainly researched a fixed oper-
ational definition of Lean without evaluating the interplay between different practices
and perceived organisational context; see for instance Bortolotti, Danese, and Romano
(2013) and Bevilacqua, Ciarapica, and De Sanctis (2017).
5.3. Limitations and future research
As in other empirical studies, the findings and implications in this study should be inter-
preted with caution, given the methodological limitations of the research, which presents
additional future research opportunities. Though we acknowledge that Lean practices are
adapted over time, we used a cross-sectional research design in this paper. which limits
the extent to which cause–effect relationships can be inferred. This limitation can be
addressed in future research through a longitudinal research design and the collection
of longitudinal data. Second, since perceptual data is used to measure the (performance)
constructs of this study, the use of multiple informants to verify perceptions would be a
logical extension, especially since the environment was proposed as a moderating vari-
able using participants’perception of the importance attached to process standardisation
in the market and the importance attached to customer effectiveness in the market. Future
Total Quality Management 15
research is also required into the mechanisms and methods how organisations adapt Lean
practices.
Disclosure statement
No potential conflict of interest was reported by the author.
Supplemental data
Supplemental data for this article can be accessed 10.1080/14783363.2018.1530591.
References
Adler, P. S., Goldoftas, B., & Levine, D. I. (1999). Flexibility versus efficiency? A case study of
model changeovers in the toyota production system. Organization Science,10(1), 43–68.
Ansari, S. M., Fiss, P. C., & Zajac, E. J. (2010). Made to fit: How practices vary as they diffuse. The
Academy of Management Review,35(1), 67–92.
Azadegan, A., Patel, P. C., Zangoueinezhad, A., & Linderman, K. (2013). The effect of environmental
complexity and environmental dynamism on lean practices. Journal of Operations
Management,31(4), 193–212. doi:10.1016/j.jom.2013.03.002
Bagozzi, R. P. (1981). Attitudes, intentions, and behavior: A test of some key hypotheses. Journal of
Personality and Social Psychology,41(4), 607–627.
Bagozzi, R. P., & Phillips, L. W. (1982). Representing and testing organizational theories: A holistic
construal. Administrative Science Quarterly,27, 459–489.
Bevilacqua, M. F., Ciarapica, F. E., & De Sanctis, I. (2017). Lean practices implementation and their
relationships with operational responsiveness and company performance: An Italian study.
International Journal of Production Research,55(3), 769–794. doi:10.1080/00207543.2016.
1211346
Bortolotti, T., Danese, P., & Romano, P. (2013). Assessing the impact of just-in-time on operational
performance at varying degrees of repetitiveness. International Journal of Production
Research,51(4), 1117–1130. doi:10.1080/00207543.2012.678403
Bowen, D. E., & Youngdahl, W. E. (1998). “Lean”service: In defense of a production-line approach.
International Journal of Service Industry Management,9(3), 207–225. doi:10.1108/
09564239810223510
Cagliano, R., Caniato, F., & Spina, G. (2006). The linkage between supply chain integration and man-
ufacturing improvement programmes. International Journal of Operations and Production
Management,26(3), 282–299. doi:10.1108/01443570610646201
Cao, M., & Zhang, Q. (2011). Supply chain collaboration: Impact on collaborative advantage and firm
performance. Journal of Operations Management,29(3), 163–180.
Chavez, R., Yu, W., Jacobs, M., Fynes, B., Wiengarten, F., & Lecuna, A. (2015). Internal lean prac-
tices and performance: The role of technological turbulence. International Journal of
Production Economics,160, 157–171. doi:10.1016/j.ijpe.2014.10.005
Choi, T. Y., & Eboch, K. (1998). The TQM paradox: Relations among TQM practices, plant perform-
ance, and customer satisfaction. Journal of Operations Management,17(1), 59–75. doi:10.
1016/S0272-6963(98)00031-X
Claycomb, C., Germain, R., & Dröge, C. (1999). Total system JIT outcomes: Inventory, organization
and financial effects. International Journal of Physical Distribution & Logistics Management,
29(10), 612–630.
Cronbach, L. J. (1951). Coefficient alpha and the internal structure of tests. Psychometrika,16(3),
297–334.
Cua, K. O., McKone, K. E., & Schroeder, R. G. (2001). Relationships between implementation of
TQM, JIT, and TPM and manufacturing performance. Journal of Operations Management,
19(6), 675–694. doi:10.1016/S0272-6963(01)00066-3
Davenport, T. H. (2005). The coming commoditization of processes. Harvard Business Review,83
(6), 100–108.
16 M.F. Van Assen
Done, A., Voss, C., & Rytter, N. G. (2011). Best practice interventions: Short-term impact and long-
term outcomes. Journal of Operations Management,29(5), 500–513. doi:10.1016/j.jom.2010.
11.007
Eroglu, C., & Hofer, C. (2011). Lean, leaner, too lean? The inventory-performance link revisited.
Journal of Operations Management,29(4), 356–369. doi:10.1016/j.jom.2010.05.002
Fullerton, R. R., & McWatters, C. S. (2001). The production performance benefits from JIT
implementation. Journal of Operations Management,19(1), 81–96.
Fullerton, R. R., McWatters, C. S., & Fawson, C. (2003). An examination of the relationships between
JIT and financial performance. Journal of Operations Management,21(4), 383–404. doi:10.
1016/s0272-6963(03)00002-0
Fullerton, R. R., & Wempe, W. F. (2009). Lean manufacturing, non-financial performance measures,
and financial performance. International Journal of Operations & Production Management,29
(3), 214–240. doi:10.1108/01443570910938970
Hair, J. F., Anderson, R. E., Tatham, R. L., & Black, W. C. (1998). Multivariate data analysis (5th
ed). New Jersey: Prentice-Hall Inc.
Hallgren, M, & Olhager, J. (2009). Lean and agile manufacturing: external and internal drivers and
performance outcomes. International Journal of Operations & Production Management,29
(10), 976–999.
Hines, P., Holweg, M., & Rich, N. (2004). Learning to evolve. International Journal of Operations
and Production Management,24(10), 994–1011. doi:10.1108/01443570410558049
Holmemo, M. D. Q., & Ingvaldsen, J. A. (2015). Bypassing the dinosaurs? –How middle managers
become the missing link in lean implementation. Total Quality Management & Business
Excellence,1–14. doi:10.1080/14783363.2015.1075876
Hopp, W. J., & Spearman, M. L. (2004). To pull or not to pull: What is the question? Manufacturing
and Service Operations Management,6(2), 133–148. doi:10.1287/msom.1030.0028
Jasti, N. V. K., & Kodali, R. (2015). Lean production: Literature review and trends. International
Journal of Production Research,53(3), 867–885. doi:10.1080/00207543.2014.937508
Jayaram, J., Vickery, S., & Droge, C. (2008). Relationship building, lean strategy and firm perform-
ance: An exploratory study in the automotive supplier industry. International Journal of
Production Research,46(20), 5633–5649. doi:10.1080/00207540701429942
Kaynak, H. (2003). The relationship between total quality management practices and their effects on
firm performance. Journal of Operations Management,21(4), 405–435. doi:10.1016/s0272-
6963(03)00004-4
Kim, D. -Y., Kumar, V., & Kumar, U. (2012). Relationship between quality management practices
and innovation. Journal of Operations Management,30(4), 295–315. doi:10.1016/j.jom.
2012.02.003
Krafcik, J. F. (1988). Triumph of the lean production system. MIT Sloan Management Review,30(1),
41–52.
Lander, E., & Liker, J. K. (2007). The Toyota Production System and art: Making highly customized
and creative products the Toyota way. International Journal of Production Research,45(16),
3681–3698. doi:10.1080/00207540701223519
Laureani, A., & Antony, J. (2017). Leadership and Lean Six Sigma: A systematic literature review.
Total Quality Management & Business Excellence,1–29. doi:10.1080/14783363.2017.
1288565
Lewis, M. A. (2000). Lean production and sustainable competitive advantage. International Journal
of Operations & Production Management,20(8), 959–978.
Liker, J. K. (2004). Toyota way: 14 management principles from the world’s greatest manufacturer.
New York: McGraw-Hill Education.
Lin, S., Yang, C., Chan, Y., & Sheu, C. (2010). Refining Kano’s‘quality attributes–satisfaction’
model: A moderated regression approach. International Journal of Production Economics,
126(2), 255–263.
Mackelprang, A. W., & Nair, A. (2010). Relationship between just-in-time manufacturing practices
and performance: A meta-analytic investigation. Journal of Operations Management,28(4),
283–302. doi:10.1016/j.jom.2009.10.002
Marodin, G. A., & Saurin, T. A. (2013). Implementing lean production systems: research areas and
opportunities for future studies. International Journal of Production Research,51(22),
6663–6680.
Total Quality Management 17
Marodin, G. A., & Saurin, T. A. (2015). Managing barriers to lean production implementation:
Context matters. International Journal of Production Research,53(13), 3947–3962. doi:10.
1080/00207543.2014.980454
McAdam, R., & Evans, A. (2004). The organisational contextual factors affecting the implementation
of Six-sigma in a high technology mass-manufacturing environment. International Journal of
Six Sigma and Competitive Advantage,1(1), 29–43.
Mitchell, T. R. (1985). An evaluation of the validity of correlational research conducted in organiz-
ations. Academy of Management Review,10(2), 192–205.
Narasimhan, R., Swink, M., & Kim, S. W. (2006). Disentangling leanness and agility: An empirical
investigation. Journal of Operations Management,24(5), 440–457. doi:10.1016/j.jom.2005.
11.011
Naylor, J. B., Naim, M. M., & Berry, D. (1999). Leagility: Integrating the lean and agile manufactur-
ing paradigms in the total supply chain. International Journal of Production Economics,62(1–
2), 107–118. doi:10.1016/S0925-5273(98)00223-0
Negrão, L. L. L., Filho, M. G., & Marodin, G. (2017). Lean practices and their effect on performance:
A literature review. Production Planning and Control,28(1), 33–56. doi:10.1080/09537287.
2016.1231853
Ng, S. C. H., Rungtusanatham, J. M., Zhao, X., & Lee, T. S. (2015). Examining process management
via the lens of exploitation and exploration: Reconceptualization and scale development.
International Journal of Production Economics,163,1–15. doi:10.1016/j.ijpe.2015.01.021
Ohno, T. (1988). Toyota production system: Beyond large-scale production. Portland, OR:
Productivity Press.
Oliver, N., Delbridge, R., Jones, D., & Lowe, J. (1994). World class manufacturing: Further evidence
in the lean production Debate1. British Journal of Management,5, S53–S63. doi:10.1111/j.
1467-8551.1994.tb00130.x
Patel, P. C., Azadegan, A., & Ellram, L. M. (2013). The effects of strategic and structural supply chain
orientation on operational and customer-focused performance. Decision Sciences,44(4), 713–
753.
Podsakoff, P. M., MacKenzie, S. B., Lee, J. Y., & Podsakoff, N. P. (2003). Common method biases in
behavioral research: A critical review of the literature and recommended remedies. Journal of
Applied Psychology,88(5), 879–903. doi:10.1037/0021-9010.88.5.879
Podsakoff, P. M., & Organ, D. W. (1986). Self-reports in organizational research: Problems and pro-
spects. Journal of Management,12(4), 531–544. doi:10.1177/014920638601200408
Preacher, K. J., Rucker, D. D., & Hayes, A. F. (2007). Addressing moderated mediation hypotheses:
Theory, methods, and prescriptions. Multivariate Behavioral Research,42(1), 185–227.
doi:10.1080/00273170701341316
Radnor, Z, & Johnston, R. (2013). Lean in UK Government: internal efficiency or customer service?
Production Planning & Control,24, 903–915.
Sakakibara, S., Flynn, B. B., Schroeder, R. G., & Morris, W. T. (1997). The impact of just-in-time
manufacturing and its infrastructure on manufacturing performance. Management Science,
43(9), 1246–1257.
Schonberger, R. J. (2007). Japanese production management: An evolution—with mixed success.
Journal of Operations Management,25(2), 403–419. doi:10.1016/j.jom.2006.04.003
Shah, R., Chandrasekaran, A., & Linderman, K. (2008). In pursuit of implementation patterns: The
context of Lean and Six Sigma. International Journal of Production Research,46(23),
6679–6699. doi:10.1080/00207540802230504
Shah, R., & Ward, P. T. (2003). Lean manufacturing: Context, practice bundles, and performance.
Journal of Operations Management,21(2), 129–149. doi:10.1016/S0272-6963(02)00108-0
Shah, R., & Ward, P. T. (2007). Defining and developing measures of lean production. Journal of
Operations Management,25(4), 785–805. doi:10.1016/j.jom.2007.01.019
Sousa, R., & Voss, C. A. (2001). Quality management: Universal or context dependent? Production
and Operations Management,10(4), 383–404.
Sousa, R., & Voss, C. A. (2008). Contingency research in operations management practices. Journal
of Operations Management,26(6), 697–713. doi:10.1016/j.jom.2008.06.001
Spear, S. J., & Bowen, H. K. (1999). Decoding the DNA of the Toyota production system. Harvard
Business Review,77,96–108.
Strang, D., & Macy, M. W. (2001). In search of excellence: Fads, success stories, and adaptive emu-
lation. American Journal of Sociology,107, 147–182.
18 M.F. Van Assen
Tu, Q., Vonderembse, M. A., & Ragu-Nathan, T. S. (2001). The impact of time-based manufacturing
practices on mass customization and value to customer. Journal of Operations Management,
19(2), 201–217.
Wilson, D. D., & Collier, D. A. (2000). An empirical investigation of the Malcolm Baldrige National
Quality award causal model. Decision Sciences,31(2), 361–383. doi:10.1111/j.1540-5915.
2000.tb01627.x
Womack, J. P., Jones, D. T., & Roos, D. (1990). The machine that changed the world. New York:
Simon and Schuster.
Zhang, D., Linderman, J., & Schroeder, R. G. (2012). The moderating role of contextual factors on
quality management practices. Journal of Operations Management,30(1–2), 12–23. doi:10.
1016/j.jom.2011.05.001
Total Quality Management 19