A STRUCTURAL EQUATION MODEL ASSESSMENT OF LEAN
MANUFACTURING PERFORMANCE
Tipparat Laohavichien
Department of Operations Management, Faculty of Business Administration
Kasetsart University, Thailand
Sawat Wanarat
Department of Operations Management, Faculty of Business Administration
Kasetsart University, Thailand
ABSTRACT
The purpose of this paper is to empirically test a framework which identifies the
relationships between lean practices, organizational performance and innovation
performance of Thai manufacturing firms. Specifically, this study examines the direct
effects of lean practices on organizational performance and whether innovation
performance mediates the relationship between lean practices and organizational
performance. A structural equation model (SEM) is estimated using data provided by
119 Thai manufacturing firms. The results show that lean practices have a direct and
significant impact on organizational and innovation performance of Thai firms.
Innovation improvement caused by lean practices also results in better organizational
performance. The results of this paper show the importance of lean practices and how
they directly influence organizational and innovative performance. This result will be
encouraging to firm in other developing countries.
Keyword: SEM, Lean practices, Innovative performance, Organizational performance
INTRODUCTION
The successful implementation of lean practices has become accepted by Toyota
as source of competitive advantage (Doolen and Hacker, 2005; Womack et al. 1990).
There are several studies that have examined the effects of lean on performance. The
results showed that lean practices might not be universally valid in all organizational
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contexts (Boyle et al., 2011, Cooney, 2002). Many researchers confirmed that the
relationship of lean on financial performance is mixed (York and Miree ,2004; Boyd
et al., 2006; Wayhan and Balderson, 2007). The study of Furlan et al. (2011) indicated
that not all the plants implement lean manufacturing bundles show the improvement
on operational performance.
This paper investigates the relationship of lean practices on organizational
performance and innovation performance, and the relationship of innovation
performance on organizational performance of manufacturers in Thailand using a
structural equation model (SEM). This allows us to evaluate whether the lean
practices that are effective in advanced economies like Japan are also effective in a
developing country like Thailand. The next sections of the paper review existing
literature, explain the research methodology and the data analysis. The final section
examines the results and provides conclusions and suggestions for future research.
LITERATURE REVIEW
The research model of this study is shown in Figure 1. The model proposed that
lean practices implemented by Thai manufacturers improve their organizational and
innovation performance. Also the improvement of innovation performance will
improve the organizational performance. The lean practices, organizational
performance and innovation performance are discussed in the next subsection.
Figure 1 Research Model.
Lean
Practices
Organizational
Performance
Innovation
Performance
H 1
H 2 H 3
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Lean Practices
Lean practices are designed to as one of inventory management system. With
lean practices, manufacturer can reduce lead times through lower level of inventory
(Bayou and de Korvin, 2008). The dominant principle of lean practices is waste
elimination. Ohno (1988) classified wastes into 7 types as follows: defects,
over-production, waiting for the next step, unnecessary transport or materials,
unnecessary movement of workers, inappropriate processing, and excess inventory.
Toyota in Japan claimed that the company significant improvements in cost and
quality by lean implementation (Womack et al. 1990). Literatures show that there are
a number of tools that are important for lean implementation. In this study, lean
practices were measured in three bundles including setup time reduction, cellular
manufacturing, and quality improvement (Fullerton and Wempe, 2009).
Setup time reduction measures the extent to which the manufacturer does the
following activities: (1) redesigns equipment to shorten setup time, (2) uses special
tools to shorten setup time, (3) trains employees to reduce setup time, and (4)
redesigns jigs or fixtures to shorten setup time. Cellular manufacturing measures the
extent to which the manufacturer does the following activities: (1) groups equipment
into product families, (2) groups equipment into families’ products that have similar
processing requirements, (3) groups equipment into families’ products that have
similar routing requirements, and (4) groups equipment into families’ products that
have similar designs. Quality improvement measures the extent to which your firm
does the following activities: (1) conducts process capability studies, (2) uses
designs of experiments, and (3) uses statistical process control (SPC) charts.
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Organizational Performance
Many researches showed that lean implementation effect organizational
performance. Motwani (2003) mentioned that lean practices eliminate wastes and
improve process. Krafcik (1998) stressed that lean practices improve quality,
productivity, and customer responsiveness. Rahman et al. (2010) stated that lean
practices can reduced lead times in production and increase velocity and flow in the
supply chain. In addition, lean practices can reduce human effort, tool investment,
product development time, and manufacturing space (Zayko et al., 1997). In this
study, organizational performance adopted the same items from Chong et al. (2011).
Six organizational performance measures in this study are lead time, inventory
turnover, product rejection/return, sales level, cost reduction, and meeting customers’
requirement.
In this study, lead time is defined as the time between the customer orders is
made and the customer orders are completely satisfied. Inventory turnover measures
the speed of goods move through and replenished by the system. Product
rejection/return measures by comparing the manufacturers’ current product rejection
or return rate with the industrial standard. Sales level is measured by evaluating
whether the manufactures’ sales level is equal, above, or below the standard of the
industry they are. Cost reduction is measured by evaluating whether the
manufacturers’ cost is higher, equal, or lower than their industrial competitors. In
addition, manufacturers were asked to respond whether they are lagging, below
averaged, average, above, or the leader in the industry in terms of meeting customers’
requirement.
Innovation Performance
Many studies suggest that lean practices are the wide-ranging encompassing
product development, collaboration with customers and pipelining a process from
suppliers to customers (Bhasin, 2011). Through lean practices, manufacturers need to
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share information internally (e.g. engineers, product designers, and marketing
employees) and externally (e.g. customers, suppliers, and distributors). Therefore, the
organization that implements lean practices should evidence the better innovation
performance than the one without lean implementation. Danneels (2002) mentioned
that innovation happened when organizations have competences relating to customers
and technologies. In this study, innovation performance adopted the same items from
Chong et al. (2011). Two innovation performance measures in this study are process
innovation and product innovation.
In this study, process innovation is defined as the changes in product delivery
and/or development processes as defined by method, functionality, administration, or
other features. There are four items to measure process innovation including: (1) we
are fast in adopting process with the latest technological innovations; (2) we use
up-to-date/new technology in the process; (3) we use the latest technology for new
product development; and (4) the process, techniques and technology change rapidly
in our company. Product innovation is defined as the changes in the products or
products features. There are five items to measure product innovation including: (1)
we have enough new products introduced to the market; (2) we have new products
which are first in market; (3) the speed of new product development is fax
enough/competitive; (4) we are technologically competitive; and (5) we are able to
produce products with novelty features.
Based on a review of the literature, the research model in the level of variables is
shown in Figure 2. The hypotheses of this study are based on Figure 2 as following:
H 1 Implementation of lean practices has a positive influence on organizational
performance
H 2 Implementation of lean practices has a positive influence on innovation
performance
H 3 Innovation performance has a positive effect on organizational performance
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Figure 2 Research Model in the Level of Variables.
RESEARCH METHODOLOGY
Sample and Data Collection
A survey instrument was developed in order to test the research model. The
items and questions in the proposed questionnaire were adopted existing studies.
The questionnaire was pre-tested with several senior executives from a manufacturing
firm to ensure that the wording and format of the questions were appropriate. Data for
this study were collected using a self-administered questionnaire that was distributed
to 550 Thai manufacturing firms. The sample was selected randomly from the
Thailand Manufacturers Directory. The data collections took nine months and were
collected from April 2012 to December 2012. The survey was completed by senior
officer in the firms. Out of the 550 surveys sent out, 119 were returned, yielding a
response rate of 21.63 per cent.
Lean Practices
- Setup time reduction
- Cellular manufacturing
- Quality improvement
Organizational Performance
- Lead time
- Inventory turnover
- Product rejection/return
- Sales level
- Cost reduction
- Meeting customers’ requirement
Innovation Performance
- Process innovation
- Product and service innovation
H 1
H 2
H 3
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Variable Measurement
The scale of lean practices (LP), which included 11 items, was adapted from
Fullerton and Wempe (2009). For the innovation performance (IP), 9 questions were
used to measure process innovation that adapted from Chong et al. (2011). The scale
of organizational performance (OP), three was designed to measure that adapted from
Chong et al. (2011). The survey used a five-point Likert-type scale (1= strongly
disagree, 5 = strongly agree) for measuring lean practices and innovation
performance. Table 1 specifies the items used in each variable measurement.
Validation of Measures
Before testing conceptual model, several reliability and validity issues need to
be addressed. First, the reliability of scales was measured by Cronbach’s alpha. In this
study, all values of Cronbach’s alpha ranged from 0.78 to 0.88 (see Table 1). Usually
Cronbach’s alpha of 0.7 or above was considered to be criteria for internal consistency
of the established scales (Bagozzi and Yi, 1998). Second, the confirmatory factor
analysis was used to assess the convergent and discriminate validity of measures with
structural equation modeling. The measurement model fit the data (x2/df = 2.174 GFI
0.961, AGFI = 0.926, RMSEA = 0.067, TLI = 0.966, CFI = 0.978) and all factor
loadings were highly significant (p < 0.001), which indicated the unidimensionality of
the measures (Anderson and Gerbing, 1998).
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TABLE 1: MEASURED IN THE RESEARCH
Factors Standardized
Coefficients
(Loadings)
Cronbach
Alpha
Lean practices
Setup time reduction 0.78
ST1: Redesigns equipment to shorten setup time 0.864
ST2: Uses special tools to shorten setup time 0.895
ST3: Trains employees to reduce setup time 0.884
ST4: Redesigns jigs or fixtures to shorten setup time 0.855
Cellular manufacturing 0.867
CM1: Groups equipment in product families
CM2: Similar processing requirements 0.723
CM3: Similar routing requirements 0.865
CM4: Similar designs 0.746
Quality improvement 0.754
QI1: Conducts process capability 0.835
QI2: Uses designs of experiments 0.956
QI3: Uses statistical process control (SPC) chart 0.854
Innovation performance 0.88
IP1: We are fast in adopting process with the latest
technological innovations
0.846
IP2: We use up to date/new technology in the process 0.875
IP3: We use the latest technology for new product
development
0.835
IP4: The process, techniques and technology
change rapidly in our company
0.843
IP5: We have enough new products introduced to
the market
0.776
IP6: We have new products which are first in market 0.946
IP7: The speed of new product development is fax
enough/competitive
0.953
IP8: We are technologically competitive 0.835
IP9: We are able to produce products with novelty
features
0.877
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TABLE 1 (CONTINUE): MEASURED IN THE RESEARCH
Factors Standardized
Coefficients
(Loadings)
Cronbach
Alpha
Organizational performance: 0.82
OP1: Cost reduction 0.765
OP2: Lead time minimization 0.744
OP3: Level of sales 0.767
OP4: Inventory turnover 0.774
OP5: Effectiveness in meeting customers’
requirement
0.787
OP6: Avoidance of product reject/return 0.764
Model fit: x2/df = 2.174 GFI 0.961, AGFI = 0.926, RMSEA = 0.067, TLI = 0.966, CFI
= 0.978
Data Analysis
To test the research hypotheses, structural equation modeling was performed
using AMOS 16 software. Compared with conventional analytical techniques in the
literature on lean practices, organizational performance and innovation performance
such as correlation analysis, structural equation modeling (SEM) has the following
advantages (Anderson and Gerbing, 1988). First, it can estimate relationships among
latent constructs indicated by observed variables. Second, it can measure recursive
relationship between constructs. Third, it can allow for correlations among
measurement errors.
SEM used several goodness-of-fit indices, including Chi-Square statistics
divided by the degree of freedom (x2/df) was recommended to be less than 3,
Goodness-of –fit (GFI), Adjusted goodness-of –fit (AGFI, Comparative Fit Index
(CFI), Tucker-Lewis (TLI) were recommended to be greater than 0.90; and Root
Mean Square Error of Approximation (RMSEA) was recommended to be 0.05 up and
acceptable up to 0.08.
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RESULTS
Overall, the model had a very good fit with the data (x2/df = 2.174 GFI 0.961,
AGFI = 0.926, RMSEA = 0.067, TLI = 0.966, CFI = 0.978) and all of the paths were
significant at the level of 0.001. Figure 3 was drawn on the basis of the results of
structural equation modeling by AMOS 16.0.
Figure 3 showed that lean practices had a significant positive influence on
organizational performance (its standard coefficient was 0.601with significance level
of 0.01), which supported H1. At the same time, lean practices had positive effect on
innovation performance (its standard coefficient was 0.680 with significance level of
0.01), which supported H2. Innovation performance also had positive effect on
organizational performance (its standard coefficient was 0.215 with significance level
of 0.05), which supported H3.
Figure 3: The Results of SEM
Notes: **p = 0.01, *p = 0.05
0.680**
0.215*
0.601** Lean Practices
Innovation
Performance
Organizational
Performance
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Table 2 shows the total effects, direct effects and indirect effects
corresponding to Figure 3. As shown in Table 2, lean practices had a direct positive
influence on organizational performance, while lean practices had indirect positive
influence on organizational performance
TABLE 2 SEM RESULT: THE TOTAL EFFECTS, DIRECT EFFECTS AND
INDIRECT EFFECTS
Construct Direct
Effect
Indirect
Effect
Total
Effect
Lean practices Organizational Performance 0.601** 0.146** 0.747**
Lean practices Innovation Performance 0.680** - -
Innovation Performance Organizational
Performance
0.215* - -
Notes: n = 119. Measurement models are estimated using ML. Bootstrapping is
required in AMOS to determine the statistical significance of direct and indirect. **p
= 0.01, *p = 0.05
CONCLUSION
This study has provided empirical justification for the proposed research
model which investigates the relations between lean practice, organizational
performance and innovation performance among Thai manufacturing firms. Previous
studies have suggested that lean practices had significant positive effect on
organizational performance (Rosemary 2008; Motwani 2003; Krafcik 1988; Rahmai
et al. 2010). Extending, this study has empirically examined how lean practices
influenced organizational performance by introducing an important mediator
Innovation performance.
In addition, this study showed that lean practices are applicable to developing
countries like Thailand. This study suggests the international managers that lean
practices are universal tools to complete in today manufacturing. Moreover,
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international managers should be aware of mediating effect of innovation
performance to organization performance. More effort in research and development
could be improve the organization performance.
There are some limitations of this study. There was only one respondent per
company, so there is the possibility of common method variance (Ketokivi and
Schroeder, 2004). And this study used self-reported lean practices, organizational
performance and innovation performance, which may allow common method bias.
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