SUPPLY CHAIN MANAGEMENT AND PERFORMANCE: AN
EMPIRICAL STUDY IN MALAYSIAN MANUFACTURING
Arawati Agus and Zulridah Mohd Noor
Faculty of Economics and Business, Universiti Kebangsaan Malaysia,
43600, Bangi, Selangor Malaysia.
This paper examines the relationship between supply chain management programs
and performances such as supply chain flexibility and supply chain integration
variables as well as profitability and return on sales in manufacturing companies in
Malaysia. The study measures senior quality managers’ or production manager’s
perception of SCM practices and level of performances in the industry. At this
preliminary stage, this study examines relationships between supply chain
management programs and Supply Chain management practices, performance
improvements and associations are analyzed through non-parametric methods such
as Spearman’s correlations, Friedman’s Rank Test, Mann-Whitney test and Kruskal
Wallis test. The findings suggest that SCM programs and implementations have
significant correlations with supply chain performance (supply chain flexibility,
supply chain integration), profitability and return on sales (ROS). Specifically,
Supply chain performances namely supply chain flexibility and supply chain
integration have high correlations with SCM practices like ‘Strategic Supplier
Partnership’, ‘Quality Information Exchange’ and ‘Technology and Innovation’.
On the other hand bottom line outcomes exhibit strong associations with
‘Technology and Innovation’, ‘Lean System’, ‘Information Sharing’ and ‘Strategic
Supplier Partnership’. In addition, volume flexibility, responsiveness flexibility,
launch/new product flexibility, distribution flexibility and product flexibility have
significant correlations with profitability and return on sales. Meanwhile, purchasing
integration, production integration, logistics integration and inventory integration
also have strong correlations with profitability and return on sales. The result also
indicates that ‘high profit-generated companies’ emphasized more on SCM programs
such as ‘Customer Relations Practices’, ‘Technology and Innovation’, ‘Lean
System’, ‘Quality Information Exchange’ and ‘Postponement Concept’. They also
have better volume flexibility followed by responsiveness/market flexibility and
launch/new product flexibility compared to ‘low profit-generated companies’. This
cluster also has higher production integration, purchasing integration, inventory
integration and logistics integration.
Keywords: Supply Chain Management, Supply Chain Flexibility, Supply Chain
Integration Profitability, Manufacturing Companies, Spearman’s Correlation,
Friedman Test, Mann-Whitney Test and Kruskal Wallis Test.
According to Lambert et al. (1998), “supply chain management is the integration of
key business processes from end user through original suppliers that provides
products, service, and information that add value for customers and other
stakeholders.” Many manufacturing companies have fought the global pressures of
competition by becoming increasingly technologically advanced, moving up-market
to more value-added products, and upgrading the skills of their domestic work force.
To compete successfully in today challenging business environment manufacturing
companies should be able to effectively integrating the internal functions within a
company and effectively linking them with the external operations of suppliers and
supply chain members. As global competition increases, businesses should be more
involved in how their suppliers and customers do business. They need to focus on
process that has an impact on enhancing supply chain management performance such
as where materials come from, how their suppliers’ products are designed and
assembled, how products are transported and stored and what consumers really
wants. The process of making and distributing products and services to customers is
becoming the most effective and efficient way for businesses to stay successful and
is central to the practice of supply chain management.
Manufacturing industry has played important role in the development of consumers’
products and contributed major portions of national export. In 2005, percentage
export from manufacturing industry such as electric and electronic industry was
about three quarter of total manufacturing export at 65.8 per cent (Ministry of
Finance, 2004). Under the cluster-based development approach adopted in the
Second Industrial Master Plan (IMP2; 1996–2000), six strategic directions were
identified to propel the manufacturing sector towards higher value-added activities
such as R&D, product design, fabrication, marketing, sales, and distribution. One of
the six strategic directions was the deepening of the supply chain and one of the
three strategies was to strengthen the supply chain vertically and horizontally. The
government initiated the development of key components and products and existing
“missing links” within the manufacturing cluster. Domestic capability in the design
and fabrication machinery and equipment was encouraged to reduce dependence on
imports, and critical supporting industries were promoted. For example, efforts were
undertaken to developed design houses capable of designing wafers, thereby adding
much higher value to the semiconductor industry. However, the emergence of
AFTA, NAFTA, and European Union (EU) in tandem with trade liberalization has
an impact on Malaysian trade in terms of stiffer competition with other countries in
the world. Increasing global competition, the demands of customers for higher
product quality, greater product selection, and better customer service, the desire of
firms to shrink their supply bases while striving to contain costs, and the rising costs
of natural resources today have led many Malaysian manufacturing companies to
adopt cooperative, mutually partnership strategies with suppliers, distributors,
retailers, and other firms within their supply chains to maintain or improve
profitability and overall firm performance.
This paper explores the possibility of adopting SCM as the basis for enhancing
performance in manufacturing companies in Malaysia (producing non food based
products with medium to high emphasis in technology). First, this paper proceeds
with a brief explanation on the SCM principles and literature review; Second, it
discusses the methodology adopted, the objectives of the study and the test
conducted to obtain the reliable measures of SCM variables. Third, it determines the
correlations between SCM and performances; Fourth, it highlights the results of
Spearman’s correlation, Friedman test, Mann-Whitney test and Kruskal Wallis test.
Finally, the results are then discussed and implications highlighted.
2. SUPPLY CHAIN MANAGEMENT (LITERATURE REVIEW)
According to Ganeshan and Harrison (1999), a supply chain is a network of facilities
and distribution options that performs the functions of procurement of materials,
transformation of these materials into intermediate and finished products, and the
distribution of these finished products to customers. Supply Chain Management
(SCM) is “the management of upstream and downstream relationships with suppliers
and customers to deliver superior customer value at less cost to the supply chain as a
whole” (Christopher, 1998). SCM involves integration, co-ordination and
collaboration across organizations and throughout the supply chain. SCM comprises
functions like distribution planning, demand forecasting, purchasing, requirement
planning, production planning, warehousing, material handling, inventory,
packaging, order processing, and transportation etc. All these functions are
considered as building blocks of SCM in today's business environment.
Supply Chain Management seeks to enhance performance by closely integrating the
internal functions within a company and effectively linking them with the external
operations of suppliers and chain members. Supply Chain management requires
coordination with customers and suppliers, but sometimes the dynamics of the
market make this difficult. Firms must achieve a relatively high degree of integration
before implementing SCM. SCM involves integration, coordination and
collaboration across organizations and throughout the supply chain.
Supply Chain management has the potential to assist the organization in achieving
both cost and a value advantage (Christopher, 1998). To gain competitive advantage,
organizations have to adopt Supply Chain Management (SCM) approach and
consider the supply chain as a whole. Many researchers claim that Supply Chain
Management can result in better supply chain performance (Christopher, 1998 and
Christiansee & Kumar, 2000), but very few empirical studies have been carried to
investigate the impact of SCM on supply chain performance, profitability and return
3. INDEPENDENT CONSTRUCT MEASUREMENT: VALIDITY AND
Validity and reliability tests were used to select and assess the final items of the
independent constructs that would be used for statistical testing. Content validity
represents the sufficiency with which a specific domain of content (construct) was
sampled (Nunnally, 1978). Content validity is subjective and judgmental but is often
based on two standards put forward by Nunnally: does the instrument contain a
representative set of measures, and were sensible methods of scale construction used
(Flynn et al, 1990,1995). The critical variables of supply chain management in this
study had content validity because an extensive review of the literature was
conducted in selecting the measurement items and the critical factors, and all the
items and factors were evaluated and validated by professionals in operation
management areas. The SCM variables in this study were adopted from prominent
studies or sources (Gunasekaran et al, 2003, Kuei et al., 2001, Li et. al, 2002, Hill,
2003, and Vickery, 1999). In this study, SCM was operationalized based upon seven
different kinds of activities that manufacturers commonly used to integrate their
operations with suppliers and customers namely Strategic Supplier Partnership,
Customer Relations Practices, Information Sharing, Quality Information Exchange,
Lean System, Postponement Concept and Technology & Innovation. As the initial
data analysis, the seven SCM variables constructs were subjected to validity and
reliability tests before a single score can be calculated to represent each construct.
Multi item scales were developed for each construct in the study. Before creating the
final scales, the data were checked for normality and outliers.
Confirmatory factor analysis (CFA) or a measurement model using AMOS 4 was
employed for examining construct validity of each scale by assessing how well the
individual item measured the scale (Ahire, Golhar and Walter 1996). Specifically,
confirmatory factor analysis was used to detect the unidimensionality of each
construct. Unidimensionality is evidence that a single trait or construct underlie a set
of measures (Hair et al. 1988). The measurement model for each construct was
treated as a single factor congeneric model with error variances and estimated
regression weights. According to Motwani et al. (1997), to establish the construct
validity of the measure, it is crucial to determine (1) the extent to which the measure
correlates with other measures designed to measure the same thing and (2) whether
the measure behaves as expected. The goodness of fit indices (GDI) of the eight
constructs exceeded the 0.90 criterion suggested by Hair et al. (1998), hence,
establishing the construct validity. CFA showed all the items were loaded highly on
their corresponding constructs, which supported the independence of the constructs
and provided strong empirical evidence of their validity. Divergent or discriminant
validity was tested by analyzing bivariate correlations between each of the SCM
scales and other variables such as demographic variables and company size etc.
There were no significant correlations between the SCM variables and these
variables, and thus the scales were not measuring other unintended constructs. Since
data for this study was generated using scaled responses, it was deemed necessary to
test for reliability (Frohlich & Westbrook, 2001).
The reliability analysis was conducted by calculating the Cronbach’s alpha for each
construct. Items that did not significantly contribute to the reliability were eliminated
for parsimony purpose. The result shows that the Cronbach’s alpha measures for the
seven constructs exceeds the threshold point of 0.70 suggested by Nunnally (1978).
Alpha coefficients for SCM scales range between 0.801 and 0.918 after the alpha
maximization process were carried out (Table 1). As a result, 41 items were retained
for the seven constructs.
Descriptive Statistics Of Critical Variables Of SCM Programs.
Variable Original Final Mean Std. Dev. Reliability
Strategic Supplier Partnership 8 8 5.247 0.871 0.801
Customer Relations Practices 7 7 5.704 0.836 0.826
Information Sharing 4 4 4.888 1.215 0.911
Quality Information 4 4 5.250 0.925 0.908
Lean System 6 6 5.329 0.905 0.808
Postponement Concept 6 6 5.346 0.824 0.822
Technology and Innovation 6 6 5.230 1.088 0.918
4. DEPENDENT CONSTRUCT MEASUREMENT
Several studies have identified performance improvement constructs that are
commonly associated with SCM (Voss, 1988, Gunasekaran et al, 2003, Kuei et al.,
2001 and Cox, 1999). Voss (1988) classified performance measures into three
groups: market place competitive advantage, productivity increases, and non-
productivity benefits. Marketplace success involved longer-term competitive gains
including increased market share and grater profitability. Productivity gains came
from decreased labor costs and increased throughput. Non-productivity benefits
included quality improvement and lead-time reductions. In order to capture the
multi-dimensional nature of supply chain management performance measures, this
study divided the performances into three types: 1) Supply Chain Flexibility 2)
Supply Chain Integration 3) Profitability and 4) Return on Sales.
Supply Chain Flexibility is vital to the success of the supply chain since the supply
chain exists in an uncertain environment. It can measure the degree to which the
supply chain can respond to random fluctuations in the demand and supply changes.
Flexibility may be defined as the ability to change or react with little penalty in time,
effort, cost or performance (Upton, 1994). Flexibility can improve the company's
competitiveness, particularly for the decision-making process of implementing
technologies (Jaikumar, 1986; Alvarez Gil, 1994). To this regard, some scholars
(Brill and Mandelbaum, 1989; Gerwin, 1993) think that a flexible operations system
requires the management and control of different flexibility dimensions, by
analyzing the total system flexibility. Enhancing a flexibility dimension does not
necessarily lead to a flexible operations system (Gupta and Somers, 1996). Because
flexibility is viewed as a reaction to environmental uncertainty (Riley and
Lockwood, 1997), in a global scenario, not only manufacturing, but also supply
chain logistics and management can be an important source of competitive
advantage, since material flows strongly affect business performance.
In this study, Supply Chain Flexibility variables were based on five types of
flexibility namely Product Flexibility, Volume flexibility, Launch/ New Product
flexibility, Distribution/ Access flexibility and Responsiveness/ Market flexibility:
a) Product flexibility – the ability to customize product or service to meet customer
specification. Vickery et al. (1997) define product flexibility in a supply chain
framework as the ability to handle difficult, non-standard orders, to meet special
customer specifications, and to produce products characterized by numerous
features, options, sizes, and colours.
b) Volume flexibility – the ability to adjust capacity to meet changes in customer
demand quantities. Volume flexibility is defined as the ability to effectively
increase or decrease aggregate production in response to customer demand
(Cleveland et al., 1989). Volume flexibility may require close coordination
between a manufacturer and its suppliers, especially in the face of increasing
c) Launch/New product flexibility – the ability to launch new or revised product.
The ability to rapidly introduce many new products and product varieties is a
strategically important flexibility that requires the integration of numerous value
activities across the entire supply chain. As product life cycles decrease,
increasing strategic emphasis is being placed on bringing many new products to
market as quickly as possible (Lieberman and Montgomery, 1988; Robinson et
d) Distribution flexibility/ access flexibility– the ability to provide widespread or
intensive distribution coverage. This flexibility is facilitated by the close
coordination of downstream activities in the supply chain whether performed
internally or externally to the firm (Vickery 1999, Sanchez & Perez, 2005).
e) Responsiveness flexibility/ market flexibility – the ability to respond to target
market needs. This flexibility captures the overall ability of the firm to respond
to the needs of its target markets (McDonald, 1993). Responsibility for this
flexibility is spread throughout the supply chain; effective performance on this
dimension hinges on a firm's ability to leverage the capabilities of its supply
chain to meet or exceed customer requirements (Sanchez & Perez, 2005).
The second performance variable in this paper is supply chain integration. Over the
past decade there has been a growing consensus concerning the strategic importance
of integrating suppliers, manufacturers, and customers (Morris and Calantone, 1991;
Cammish and Keough, 1991; Eloranta and Hameri, 1991; Burt and Doyle, 1992;
Clinton and Closs, 1997). Ragatz et al. (1997) noted that the “effective integration of
supplier into product value/supply chains will be a key factor for some
manufacturers in achieving the improvements necessary to remain competitive”. The
goal of Supply Chain integration is to create and coordinate manufacturing processes
across the supply chain in a manner that most competitors cannot easily match
(Anderson and Katz, 1998, Lumus et al., 1998). Several researchers have pointed out
the importance of integrating suppliers and customers into supply chains for
developing new products and processes. Growing evidence suggests that the higher
the level of integration with suppliers and customers in the supply the greater the
potential beneﬁts (Lee et al., 1997; Metters, 1997; Narasimhanand Jayaram, 1998;
Lummus et al., 1998; Anderson and Katz, 1998). Handﬁeld and Nichols (1999)
argued that now manufacturers must not only manage their own organizations but
also be involved in the management of the network of up- stream and downstream
ﬁrms. Hale (1999) similarly pointed out that those ﬁrms “who have traditionally
been structured as independent businesses will increasingly have to conﬁgure
operations on a shared basis”. By extension, manufacturers with high emphasis on
supply integration should have the highest levels of performance improvements. In
this study, SCM integration comprises within and across firm boundaries which
includes logistics, purchasing, production integration and inventory integration.
Lastly, the third and performance variables, profitability and return on sales; are
determined from single measurements.
In order to obtain consistent and reliable measures of supply chain flexibility, supply
chain integration and profitability as well as return on sales, a reliability test using
SPSS reliability procedure was conducted to determine the item analysis and internal
consistency and stability of the measurements (Saraph et al. 1989, Flynn et al. 1995,
Churchill, 1979). The reliability analysis was conducted by calculating the
Cronbach’s alpha for each scale. The result shows that the Cronbach’s alpha measure
for performances scales also exceed the threshold point of 0.70 suggested by
Nunnally (1978). The alpha coefficient for Supply Chain Flexibility scales is 0.941
and the alpha coefficient for Supply Chain Integration scales is 0.953 (Table 1).
Having met the requirement of reliability, the composite measure of each construct
can be measured by calculating its mean values (Hair et al. 1995). The results are
presented in Table 2.
Descriptive Statistics Of Critical Variables Of Performance
Supply Chain Flexibility Mean Std. Dev. Reliability
Product Flexibility 4.8750 1.30458 0.941
Volume Flexibility 5.1500 1.29199
Launch / New Product Flexibility 5.0250 1.27073
Distribution Flexibility 5.0000 1.13228
Responsiveness Flexibility 5.1250 1.36227
Supply Chain Integration Mean Std. Dev. Reliability
Logistics integration 5.2000 1.19649 0.953
Purchasing integration 5.5000 1.05131
Production integration 5.6000 0.94032
Inventory integration 5.4000 1.09545
Profitability and return on sales Mean Std. Dev. Reliability
Profitability 5.1250 1.04237 Single measurement
Return on Sales 5.0000 1.14812 Single measurement
5. RESEARCH METHODOLOGY
The instrument used in this study was a structured survey questionnaire, which was
designed to assess the companies in term of the described dimensions. The
instrument developed in this study consists of two major parts. The first part
comprises several constructs measuring SCM practices, and the second part
comprises several performance measurements. To enable respondents to indicate
their answers, seven–point interval scales were use for the questionnaire. A total of
seven constructs of SCM, which have been widely referred, were extracted.
Similarly, the dependent variables namely supply chain flexibility, supply chain
integration, profitability and return on sales also used a seven-point interval scale,
representing a range of agreement on statement whether over the past three years
these performances are high relative to competitors after implementing SCM
Sample companies were randomly chosen from manufacturing companies (non-food
based manufacturing companies with medium to high technology) in Klang Valley,
Malaysia. Companies in Klang Valley were chosen because majority of these
companies were situated in Klang Valley (mostly in Kuala Lumpur and Selangor).
The reasons for focusing on this sector are twofold. First, manufacturing companies
have emerged as leading sectors in Malaysia in terms of adopting new manufacturing
and SCM programs and these practices are driven primarily by competitive rather
than regulatory forces. Second, the industry is heterogeneous in terms of sub-sectors
and product/process complexity. As an exploratory study, forty-five useable
responses were received and were analyzed using the SPSS package. The primary
purpose of the research was to measure senior quality managers’ or production
manager’s perception of SCM variables and to gain insight into the benefits of
implementing SCM in the manufacturing industry. The goal is to understand and
determine determinants of SCM that can enhanced SCM performances (supply chain
flexibility and supply chain integration) and bottom line result (profitability and
return on sales). Face to face interviews with SCM managers or production managers
were carried out for checking the information accuracy, validating the outcome of
analysis and developing an understanding of practical aspects of SCM principles
adoption. Given the scarcity of OR research in Malaysia that examines associations
between SCM and performance, the purpose of this paper is to enhance managerial
understandings of SCM and performance by addressing the following questions:
a) What factors that correlates with SCM variables?
b) Which SCM variables have significant impact on performance?
With regards to these questions, the main objectives of this paper are:
1) To empirically explore correlates among SCM variables.
2) To empirically investigate correlates between SCM and performance.
3) To empirically assess the importance of each SCM indicator on performance.
6. STUDY FINDINGS
Discussion on the empirical findings will be based on non-parametric analyses. The
non-parametric section will include (a) Spearman correlation analysis among SCM
variables, (b) Spearman correlation analyses between SCM variables and
performances, (c) cluster analysis and Friedman test, and (d) Kruskal Wallis and
Table 3 exhibits the result of correlation analysis among SCM variables in the study.
All SCM variables are strongly correlated with each other, indicating that
organizations in this industry implement these SCM programs in a holistic manner.
SCM variables indicate positive associations with each other (p ≤ 0.01). First and
foremost, Strategic Supplier Partnership is highly correlated with Customer
Relations Practices (r = 0.751), Information Sharing (r = 0.690), Quality Information
Exchange (r = 0.607), Lean System (r = 0.580), Postponement Concept (r = 0.457)
and Technology and Innovation (r = 0.373). Thus, on the basis of the preceding
findings, we can conclude that most of the SCM variables are significantly correlated
with one another suggesting that these variables complemented each other.
(a) Spearman’s Correlations among SCM Variables
Spearmans’ Correlations Among SCM Scales
SCM 1 2 3 4 5 6 7
1 Strategic Supplier 1.00
2 Customer Relations .751
3 Information Sharing .690 .611
4 Quality Information .607 .479 .739
Exchange (**) (**) (**)
5 Lean System .580 .469 .502 .399
(**) (**) (**) (**)
6 Postponement .457 .383 .331 .487 .374
Concept (**) (**) (**) (**) (**)
7 Technology and .373 .333 .420 .437 .378 .431
Innovation (*) (*) (**) (**) (**) (**)
*P≤0.05, **P≤0.01 2. All t-tests are one-tailed
(b) Spearman Correlation analyses between SCM variables and performances
Further, through Spearman correlations (Table 4, Table 5 and Table 6) relationships
between SCM, supply chain flexibility, supply chain integration, profitability and
return on sales were investigated and described. This result indeed confirms close
associations between SCM programs and supply chain flexibility, supply chain
integration, profitability and return on sales. Supply chain flexibility and supply
chain integration have significant correlations with all SCM programs. Profitability
and return on sales (ROS) have strong correlations with ‘Technology and
Innovation’, ‘Lean System’ and ‘Information Sharing’. On the other hand,
profitability has positive correlations with responsiveness flexibility (r = 0.609), new
product flexibility (r = 0.569), distribution flexibility (r = 0.595), volume flexibility
(r = 0.478) and product flexibility (r = 0.399). Profitability also has strong
correlations with production integration (r = 0.569), purchasing integration (r =
0.586) and distribution/logistics integration (r = 0.507) and inventory integration (r =
0.528). Return on sales (ROS) has high and positive association with new product
flexibility (0.690), volume flexibility (r = 0.654) and responsiveness flexibility (r =
0.520). In addition, “return on sales” also exhibit strong correlation with logistic
integration (r = 0.624) and purchasing integration (r = 0.658). These findings are
consistent with several previous studies that proclaimed better organizational
transformations as a result of SCM initiatives (Lee et al., 1997; Metters, 1997;
Narasimhanand Jayaram, 1998; Lummus et al., 1998; Anderson and Katz, 1998).
Fundamentally, to improve supply chain flexibility, supply chain integration,
profitability and return on sales (ROS), a manufacturing company should implement
Spearman’s Correlations Between Supply Chain Management Programs And
Supply Chain Supply Chain Supply Profitability ROS
management programs Flexibility Chain (Return on
1 Strategic Supplier
.681(**) .637(**) .408(**) .466(**)
2 Customer Relations
.423(**) .415(**) .426(**) .328(*)
3 Information Sharing .557(**) .439(**) .490(**) .485(**)
4 Quality Information
.648(**) .631(**) .394(**) .514(**)
5 Lean System .539(**) .598(**) .515(**) .420(**)
.418(**) .384(**) .235 .341(*)
7 Technology and
.627(**) .629(**) .530(**) .638(**)
*P≤0.05, **P≤0.01 2. All t-tests are one-tailed
Spearman’s Correlations Between Supply Chain Flexibility And Performances
Supply chain flexibility Profitabiliy ROS
(Return on Sales)
1 Product Flexibility .399(**) .462(**)
2 Volume Flexibility .478(**) .654(**)
3 New Product Flexibility .560(**) .690(**)
4 Distribution Flexibility .595(**) .471(**)
5 Responsiveness Flexibility .609(**) .520(**)
*P≤0.05, **P≤0.01 2. All t-tests are one-tailed
Spearman’s Correlations Between Supply ChainIntegration, Profitability And
Return On Sales
Supply chain Integration Profitability ROS
(Return on Sales)
1 Distribution/ logistics integration .507(**) .624(**)
3 Production integration .569(**) .530(**)
4 Inventory integration .528(**) .517(**)
*P≤0.05, **P≤0.01 2. All t-tests are one-tailed
(c) Kruskal Wallis and Mann-Whitney Tests
Kruskal Wallis tests were used to further explore differentiation of SCM, supply
chain flexibility, supply chain integration, profitability and return on sales according
to types of industry. Kruskal Wallis test is essentially concerned with the test of
differentiation between means of the ranks. The chi square-value allows us to accept
or reject a null hypothesis that all group means are equal. This test is appropriate
because we are testing simultaneously for differences in means of the different
groups into which these manufacturing companies have been classified. In this study,
respondents were asked whether they classified their companies into small, medium
or large scaled industries. The results presented in Table 7 indicate that “large-scaled
industry” has the highest means for almost all the variables. Statistically, however,
the result only suggests significant difference in the means of profitability according
to the types of industries.
Kruskal Wallis Test And Summary Of Statistics By Types Of Industry
SCM Group Mean Chi-Square Sig.
° Rank Value
Mean Supply Chain 1 10.60 4.047 0.132 (ns)
Management programs 2 20.53
Mean Supply Chain 1 15.20 2.435 0.296 (ns)
Flexibility 2 18.10
Mean Supply Chain 1 15.30 3.613 0.164 (ns)
Integration 2 17.13
1 14.20 7.591 0.022 (*)
Profitability 2 15.83
ROS 1 17.13 4.455 0.108 (*)
(Return on Sales) 2 20.15
Notes: °1=Small scaled industry; 2 =Medium scaled Industry; 3 = Large-scaled Industry
**significant at p=0.001, * significant at p=0.05, ns = not significant
To explore further on the effect of ISO accreditation on SCM variables, supply chain
flexibility, supply chain integration, profitability and return on sales, Mann-Whitney
tests were conducted. The result presented in Table 8 did not support general
assumptions regarding the effect of ISO accreditation on SCM variables and
performance variables. These results show that:
1) Companies with ISO accreditation exhibit relatively higher level of
2) However, there are no significant differences between the two groups (‘ISO
accreditation’ and ‘no ISO accreditation’) for supply chain management
programs, supply chain flexibility, supply chain integration, profitability and
‘Return on Sales’.
Mann-Whitney Test and Summary of Statistics by ISO Accreditation
SCM Group° Mean Mann Sig.
Mean Supply Chain 1 20.82 72.000 0.293 (ns)
Management programs 2 15.50
Mean Supply Chain 1 20.76 74.000 0.329 (ns)
Flexibility 2 15.83
Mean Supply Chain 1 21.11 62.50 0.154 (ns)
Integration 2 13.92
Profitability 1 21.20 59.50 0.101 (ns)
ROS (Return on Sales) 1 23.06 124.00 0.529 (ns)
Notes: °1=Yes; 2 = No “ISO accreditation”
**significant at p=0.001, * significant at p=0.05, ns = not significant
Therefore, we can state that even though all performance measurements and SCM
scores are higher for companies with ISO accreditation, the Mann Whitney tests fail
to show significant statistical evidences to support the assumption that companies
with ISO accreditation have higher means for supply chain management, supply
chain flexibility, supply chain integration, profitability and ‘Return on Sales’.
(d) Cluster Analysis and Friedman’s Test
To further explore on the segmentation of manufacturing companies in this study, a
cluster analysis was carried out. Since profitability is a very importance bottom-line
outcome, therefore the classification is based on profitability clustering. The result
from cluster analysis statistically segmented the manufacturing companies into two
clusters based on profitability namely “High profit-generated companies” and “Low
profit-generated companies”. Tables 9 and 10 highlight further information about
the two clusters. The first cluster (“High profit-generated companies”) comprises of
large-scaled companies with average employees of more than 1,200 and average
approximated sales turnover between RM 4 million to RM 550 million. Mean while,
the second cluster (“Low profit-generated companies”) comprises of smaller
companies with average employees of about 330 and average approximated sales
turnover between RM 3 million to RM 25 million. From the result we can infer that
the higher level of SCM implementations are more realized in “High profit-
generated companies” than “Low profit-generated companies”. “High profit-
generated companies” put high priorities to customer relations practices, technology
and innovation, lean system, postponement concept, followed by quality information
exchange, strategic supplier partnership and lastly information sharing. This first
cluster achieved high supply chain flexibility especially volume flexibility,
responsiveness flexibility and new product flexibility followed by distribution
flexibility and product flexibility. On the other hand, the second cluster (“Low
profit-generated companies”) has volume flexibility, product flexibility and new
product flexibility. In addition, Table 11 exhibits the overall rankings of the SCM
integration for the two clusters based on the Friedman’s rank test and in case of a tie;
the variables were ranked according to means and standard deviations.
Rankings Of Supply Chain Management Programs Based On High And Low
Profit-Generated Companies Using Friedman’s Test
High profit-generated companies Low profit-generated companies
Supply Chain (n=29, chi-square = 19.247, (n=16, chi-square = 18.319,
Management significant=0.004) significant=0.005)
programs Friedman’ Rank Mean Std Friedman’s Rank Mean Std
s Test Dev Test Dev
3.52 5.363 0.905 3.78 4.648 .8982
Partnership 6 5
Relations 5.21 1 5.828 0.779 5.28 1 5.152 .9483
Information 3.03 5.023 1.282 2.69 3.812 1.510
Sharing 7 7
Information 3.78 5 5.388 .9463 4.31 2 4.609 1.076
Lean System 3
3.97 5.448 0.919 4.13 4.729 .8902
3.93 5.423 0.837 3.84 5.083 .6526
Technology and 2
4.57 5.606 0.934 2.97 4.206 .9641
Rankings of Supply Chain Flexibility based on High and Low Profit-Generated
Companies using Friedman’s Test
High profit-generated companies Low profit-generated companies
Supply Chain (n=29, chi-sq = 6.861, sig=0.143) (n=16, chi-sq = 1.584, sig=0.812)
Flexibility Friedman’ Rank Mean Std Friedman’ Rank Mean Std Dev
s Test Dev s Test
Product 5 2
2.67 5.172 1.3111 3.09 4.1875 0.98107
Volume 1 1
3.33 5.482 1.2136 3.25 4.2500 1.12546
New Product 3 3
2.93 5.414 1.1186 2.94 4.1250 1.08780
Distribution 4 5
2.81 5.310 .00370 2.81 4.0625 0.99791
Responsiveness 2 4
3.26 5.552 1.1522 2.91 4.0626 1.18145
The result highlights the importance of production, purchasing, inventory and
logistics integration in SCM implementations in enhancing profitability. The
findings also suggest that manufacturing companies in Malaysia give less emphasis
on ‘strategic supplier partnership’ and ‘information sharing’ compared to their
counterparts in developed countries.
Rankings Of Supply Chain Integration Based On High And Low Profit-
Generated Companies Using Friedman’s Test
High profit-generated companies Low profit-generated companies
Supply Chain (n =29, chi-sq = 0.895, sig =0.827) (n =16, chi-sq = 4.713, sig =0.194)
Integration Friedman’ Rank Mean Std Friedman’ Rank Mean Std
s Test Dev s Test Dev
2.40 5.310 1.1983 2.50 4.375 .8851
integration 4 3
2.55 5.414 1.1807 2.16 4.187 .9106
g integration 2 4
2.59 5.379 1.1469 2.84 4.562 .8921
Inventory Integration 1.1734
2.47 5.345 2.50 4.375 .7188
7. CONCLUSION AND IMPLICATIONS
The purpose of this paper is to empirically test the impact of supply chain
management practices on performances so as to determine to what degree SCM
issues influence with supply chain performance (supply chain flexibility, supply
chain integration), profitability and return on sales in manufacturing companies in
Malaysia. In summary, the findings of the empirical study are clear, and suggest
several things. Firstly, there is significant impact of SCM practices on performances
of the Malaysian manufacturing companies. The findings suggest that supply chain
management programs have significant correlations with supply chain flexibility,
supply chain integration, profitability and return on sales. “High profit-generated
companies” gives high emphasis on customer relations practices, technology and
innovation, lean system, followed by quality information exchange, postponement
concept, strategic supplier partnership and lastly information sharing. In addition,
supply chain flexibility and supply chain integration also have strong correlations
with profitability and return on sales. The result also indicates that ‘high profit-
generated companies’ have higher level of volume flexibility, responsiveness
flexibility and new product flexibility followed by distribution flexibility and
product flexibility. These companies also show high achievement in production
integration and purchasing integration. The results of this study suggest that superior
adoption in SCM does have an impact on performances. The findings show that
SCM is positively related to supply chain flexibility, supply chain integration and
profitability, which reinforces several empirical studies in the supply chain (Vickery
et al. 1999, Lee et al., 1997, Frohlich & Westbrook, 2001 Gunasekaran et al, 2003,
Kuei et al., 2001; and Cox, 1999).
Since this paper is still at the exploratory stage, no generalization is being put
forward. However at this stage, the evidence of the importance of SCM programs is
clear. Nonetheless, more samples will need be collected to test hypotheses,
assumptions and also propositions and ultimately to make generalizations. Therefore,
rather than being conclusive, this paper opens new avenue for extended and future
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