EFFECT OF KNOWLEDGE SHARING AND SUPPLY CHAIN MANAGEMENT (SCM)
ON ORGANIZATIONAL PERFORMANCE
Knowledge and supply chain management`s (SCM) contribution to organizations has
been increasing while organizations are trying to increase competitive positioning.
A recent study has found that companies lose between 9% and 20% of their value over a
six-month period due to supply chain problems and there is strong evidence that SCM glitches
have negative impact on organizational performance (Hendricks and Singhal 2005). By making
the rules and conventions explicit, we can guarantee: the correctness of the transactions, no
misunderstandings among the participants, exceptions are handled. (Huhns et al., 2002, p; 1).
The benefit of supply chain integration can be attained through efficient linkage among
various supply chain activities, and the linkage should be subject to the effective construction
and utilization of various supply chain practices for an integrated supply chain (Kim, 2006) that
supply chain is hence today a very different field of knowledge and routines, even despite
it still incorporating logistics and distribution (Toivo 2008). Also SCM strongly depends on
external and internal information flow (Dimitriadis and Koh 2005) and effective, real-time
decision-making, customers and suppliers must share mission-critical information on a timely
basis (Nagai et al., 2004, p 723). The most important fact in the KM is reciprocal knowledge
interaction which is also critical in the SCM as well even Christopher (1998) argues that the
word “chain” should be replaced by “network”.
Purchasing/procurement, inventory management, transportation, order processing,
customer service, production scheduling, relations with vendors are Logistics Decision Areas
whereas internet applications used therefore knowledge sharing takes place. So we can say that
SCM is critical for organizational performance and information is critical for SCM. From that
point of view there must be a correlation between the knowledge management, SCM and
organizational performance in terms of SCM performance.
Key words: Supply Chain management, Knowledge Sharing, Performance
1
Literature Review
The Supply Chain Management
Supply chain management is defined as: a set of approaches utilized to efficiently
integrate suppliers, manufacturers, warehouses, and stores, so that merchandise is produced and
distributed at the right quantities, to the right locations, and at the right time, in order to minimize
system wide costs while satisfying service level requirements.
Supply chain management came into being as a field of its own as the realization
grow that real Performance improvements could be obtained by systemic modifications of
the traditional disciplines of (1) operations management, (2) logistics, and (3) purchasing.
Conceptually, such an approach had been widely understood for many years, but the
evolution of distributed, inexpensive information technology resources has made it possible
to share information at unprecedented levels so information sharing started to play critical role
in today’s supply chain management. (Hershauer et all, 2005, p 383)
The supply chain (also known as the logistics network) is made up by “suppliers,
manufacturing centers, warehouses, distribution centers, and retail outlets, as well as raw
materials, work-in-progress inventory, and finished products that flow between the
facilities (Toivo, 2008, p 30). The supply chain encompasses organizations and flows of goods
and information between organizations from raw materials to end-users (Halldorsson et al,
2007). There are thousands of related references but Supply chains can simply be viewed as
communication Systems among all the stakeholders in the System (Hershauer et all, 2005, p
390).
SCM helps to optimize customer service, operational overheads and inventory shelf-life.
so good customer service can lead to high customer satisfaction and through advanced forecating
and planning enabled by the system reputations of the organizations can improve (Wang, 2012)
The chain structure arises from the connected, chain-like facilities that work together to
supply these products (or services). In a supply chain, what make possible the functions of
procurement, processing (or manufacturing), storage and distribution is the flow of materials and
information (Beamon and Chen, 2001, p 3195)
2
Information Sharing and Supply Chain Processes
In general terms knowledge and information is different aspects. Literally knowledge has
more broad meaning than information because knowledge includes using, creating, evaluating
etc. of information but in this study the aim is to see the effects of information or knowledge as a
catalyst to SCM and organizational performance so they are used interchangeably.
Information sharing refers to the extent which critical and proprietary information is
communicated to one’s SC partner (Chantrasa, 2005, p 18). SCM aims to integrate all the
business processes, from final customers to original suppliers, which provide products, services
and information that add value for the customers (Li, 2005, p 5). Many researches consider IT a
great enabler for SCM practices because today firms’ competitive advantage derived from
network of relationships and unleashing the true potential of the SCM sharing long-range
information such as market trends, new products introductions and future plans needed
(Malhotra, 2000, p 7, 22) but also mutual trust, openness and management support is necessary
for collaborative information sharing (Arun, 2008, pp 113-117, Yalciner, 2004, p 59).
Information sharing in SCM impacts supply chain processes in many ways, especially the
buyer-supplier relationship, the available evidence suggests managers’ information-processing
activities are tied to performance (Hult et al., 2004, 241–253) but also reverse is true: if the
retailer does not share promotion related information with the manufacturer, increase fluctuation
in demand will decrease the manufacturer’s profit (Zhao, 2002, p 16). Effective SCM aims to
synchronize supply, production, and delivery. For this to happen, firms needs to leverage the
connectivity of the Internet to create an inter-firm digital platform, enabling real-time
information sharing, and improving coordination of allocated resources across the supply chain
(Dong et al., 2009, pp. 18–32). Today many manufacturing technologies are driven by
information systems where such systems can electronically transmit information among supply
chain partners, mutual trust, and upper management support. Therefore, knowledge sharing is
critical in managing today’s e-supply chain and enable good supply chain processes. (Honggeng,
2003, pp 43-47, Kim and Narasimhan, 2002)
IT can create value in supply chain contexts. The value is generated through developing
digitally enabled integration capability, and manifested at the process level. Managers should
3
bear in mind that establishing information-linked strategic alliances with business partners is
critical (Dong et al., 2009, pp. 18–32) because integrated information system allow users obtain
information directly from the repository and eliminated the possibility of bias, delays, and
distortions from indirect knowledge transfer, thus guarantee knowledge quality dimensions of
high reliability, completeness, and timeliness (Li, 2007, pp 86-87; Li, 2002, p 77). Here IT and
information sharing have a role of fitting peaces together. So information sharing can remove
misunderstandings, exeptions can be handled as we discussed earlier.
Of course every decision has pros and cons, knowledge sharing is critical in SCM but
also has some disadvantages starting from high IT adaptation costs, lost of privacy, industrial
spying and so on. (Chantrasa, 2005, pp. 17-27)
Information sharing and quality can reduce cycle times, fulfill customer order more
quickly, cut out excessive inventory cost, delivery shorter new product development time, higher
dependability and shorter delivery time which are giving a competitive advantage with
competitors are significantly positively related to all measures of overall organizational
performance. (Li, 2002, pp 77-83)
Business Performance
Many different supply chain performance measures have been used in previous studies
for measuring performance. In general terms performance metrics have been divided into
financial and non-financial categories. A good performance measurement system should
emphasize the balance among performance outcomes, performance drivers, objective measures,
subjective measures, short-term measures, and long-term measures (Zhou, 2003). Lockamy et al.
(2000) described the performance goals of 3M’s supply chain management as customer
satisfaction, improved speed, and lower costs. McCormack (1998) measured days of supply,
cash-to-cash cycle, delivery performance versus commitment date, and delivery performance
versus quoted order lead-time. Ramdas and Spekman (2000) measured inventory cost, inventory
turns, product development time, time to market, order fulfillment, quality, customer focus, and
customer satisfaction. Sahin (2009, pp 190-191) investigated five dimensions of performance:
financial, innovation, functional, organizational prestige and customer relations management.
4
The
Performance
Measurement
Groups
(http://www.pmgbenchmarking.com)
benchmarks supply chain performance along the following nine dimensions: (1) delivery
performance to request, (2) upside production flexibility, (3) total supply-chain management
cost, (4) cash-to-cash cycle time, (5) order fulfillment lead-time, (6) order fill rate, (7) total
inventory days of supply, (8) value-added productivity per employee, and (9) net asset turns.
Capabilities of core interorganizational processes, such as customer relationship
management, supply chain management, and contract manufacturing, are suggested as critical
to firm performance (Rai et al., 2006) modern measurement systems should support innovative
strategies like teamwork and that non-financial measures (Hoek, 1998).
The Supply Chain Council developed the following measures for supply chain
performance: (1) on time delivery to schedule, (2) warranty cost of % of revenue, (3) inventory
days of supply, (4) asset returns, and (5) cash-to-cash cycle. Performance measures include
inventory turnover and percentage of late deliveries. Waterson et al. (1997) measured quality,
cost, and customer responsiveness. Logistics performance was dividing into four major
categories: time, quality, cost, and other/supporting. Then Supply Chain Council helped for an
integrated supply chain metric framework, which later became part of the SCOR model. It
includes five dimensions: (1) delivery, (2) cost, (3) flexibility, (4) responsiveness, and (5)
financial performance. (Zhou, 2003, p 53). We can add the metrics and measures in the
context of the following supply chain activities/processes: (1) plan, (2) source, (3)
make/assemble, and (4) delivery/customer (Gunasekaran, 2004, p 336). So with the plan
metrics added to SCOR model our model is shaped.
Relationship between Supply Chain Management, Information Sharing and Business
Performance
In general, firms pursue different competition capabilities within the generic strategies of
competing on cost, quality, time, flexibility, or product differentiation. So frequently cited
metrics for measuring firm performance can be growth in earnings, change in market share,
return on assets, reduction in operating costs and shareholder value (Martin, 2002, p 40) to
increase performance and decrease structural and operational uncertainty at supply chain level.
5
Final aim of SCM is to compete with other supply chains (Unuvar, 2007). But some of these
metrics cannot be directly connected with SCM outputs.
SCM is a new strategic business model and network aiming to integrate firms’ different
competencies and critical business processes in which information sharing and IT capabilities are
critically important. Even though information sharing is the driver of SCM it has no direct effect
on business performance (Yusuf et al., 2004, p 389; Zhou, 2003, p 172). But information sharing
needs trust and strategic cooperation which can lead to supplier’s strategic commitment to a
buyer, have a greater impact on performance than hard, more quantifiable criteria such as
supplier capability (Kannan and Tan, 2002, p 11). Information flows are critical collaborations
and their improvement is a major incentive in supply chain integration. Such flows creates closer
collaboration between the supply chain members, have positive impacts on customer
satisfaction, and can lead to the creation of new products and services, new marketing
approaches, and advanced operations (Wang et al., 2007, p 46).
Business performance was measured with five factors - Availability, Variety of
Product/Service Offerings, Timeliness, Profitability, and Growth (Min and Mentzer, 2004, p 78)
or by product value, customer loyalty, market performance, and financial performance
(Tracey et al., 2005) or by marketing performance (trust and customer satisfaction) and financial
performance (return on investment and return on sales) (Sin et al., 2005, p 1278).
The effect of SCM on performance has been researched in many studies and results vary.
Some researchers have found that SCM and knowledge or IT sharing have no impact on the
performance of the organization (Vereecke et al., 2006, pp. 1176-1198; Iyer, 2001, p 105, Li,
2002, p v, Ciravoğlu, 2006, p 135, Ozciftci (2009, p 149) or partial effect on business
performance (Zhou, 2003, p 132) But this performance has not been evaluated by the terms of
SCM.
At the same time, some researchers indicate that supply chain management capabilities
are an important competitive advantage and is an important determinant of a firm’s business
performance. (Tracey et al., 2005, 179–191; Yalciner, 2004; Li, 2006; Thatte, 2007 pp. 63-64; Li
et al., 2006; Kim, 2006, Stadtler and Kilger, 2005, p 282, Yusuf et al., 2004)
6
Generally in researchers, organizational performance hasn`t been measured within the
terms of SCM. In this study the empirical model designed to use a business performance system
that is primarily developed based on the performance measurements of SCM: (1) delivery, (2)
cost, (3) flexibility, (4) responsiveness, and (5) financial performance. (Honggeng, 2003, p 53)
In general, firms pursue different competition capabilities within the generic strategies of
competing on cost, quality, time, flexibility, or product differentiation.
The study showed that sharing information between supplier and customers can lead to
significant economic values (Zhou, 2003, p22) and inrease performance in SCM (Yalciner, 2004,
p 48).
The Research Model
We are concerned with a firm’s aggregate performance relative to its competitors.
Organizational performance is assessed by the terms of demand/supply predictability,
firm growth, operational excellence connected to SCM, consumer relations/satisfaction,
economical revenue, market share, use of IT structure (Rai et al., 2006)
Effective supply chain processes have positive influence on business performance. The
literature in this section has led to the research question of whether supply chain processes have
positive influence on business performance. The formal hypothesis is submitted as follows:
Hypothesis 1: Effective supply chain process improves business performance.
Hypothesis 2: Effective knowledge sharing has a positive effect on Supply chain process
Hypothesis 3: Effective knowledge sharing improves business performance.
Population and sample
For this study firms from Gaziantep`s-city in TURKIYE- Organized Industrial Zones are
chosen. These zones composed of manufacturing companies that left as a target sample.
Gaziantep has five zones containing 830 firms. But for the geographical closeness zones I
(138 firms), II (265 firms) are chosen (Total 403) (http://www.gaosb.org/kurumsal.php?id=5, Feb,
2013) for the research and from that zones only 84 companies answered surveys.
7
Survey Construction
The questionnaire has three main parts: Knowledge sharing questions, SCM and
organizational performance. As we discussed earlier organizational performance is evaluated in
the terms of SCM dimensions.
SCM questions derived from SCOR model: Plan, Source, Make, Delivery, and Return.
(Zhou, 2003).
Organizational (business performance) is derived from different sources: main frame and
metrics form Zhou (2003) and from Kim and Narasimhan (2002). The forecast accuracy, The
delivery on time, The inventory turns from Stadtler and Kilger (2005); Reliability quality, Mix
flexibility, Changeover flexibility, Volume flexibility subcategories of Cost, Flexibility, Time
and Quality (Wang et al., 2007, p 149).
Total 35 questions asked. All of the items were measured by a 5 point Likert-type scale.
Totally 200 surveys printed but only got 84 responders. In most applications, a sample
size of n=30 is adequate. However, if the population distribution is highly skewed or contains
outliers, most statisticians would recommend increasing the sample size to 50 or more so 84
firms are adequate for the survey results. (Anderson et al., 2011, p 320)
Descriptive Statistics
Descriptive Statistics
Mean
Std. Deviation
N
Performance
4.1915
.49424
84
SCM practices
3.8920
.46364
84
Information Sharing
4.1481
.49219
84
There are 84 firms that answered the survey no missing values so all the surveys are
accepted. From standard deviation, we can say that SCM and information sharing are being
practiced.
8
Reliability and validity
Items with lower item-total correlations do not fit into this scale as well, sychometrically.
If the item's total correlation is negative or too low (less than .30), it is wise to examine the item
for wording problems and conceptual fit. You may want to modify or delete such items. (Leech,
et al., 2005) So last two questions of the questionnaire are deleted (also other researchers found
that financial performance is not influenced by SCM (Martin, 2002, p 66; Bradley, 2004, p 174).
Also it is an expected result because last 2 questions are about the profit of the company which is
not directly affected from SCM and Knowledge Sharing (Zhou, 2003, p 45) (Table 1). Note that
the alpha increases a little if Items are deleted.
Table 1: Item-Total Statistics
Knowledge Sharing
Knowledge Sharing
Knowledge Sharing
Knowledge Sharing
Knowledge Sharing
Knowledge Sharing
Knowledge Sharing
Knowledge Sharing
Knowledge Sharing
SCM Practices
SCM Practices
SCM Practices
SCM Practices
SCM Practices
SCM Practices
SCM Practices
SCM Practices
SCM Practices
SCM Practices
SCM Practices
SCM Practices
SCM Practices
Performance
Performance
Performance
Performance
Performance
Performance
Performance
Performance
Performance
Performance
Performance
Performance
Performance
Performance
Performance
Scale Mean if
Item Deleted
144.25
144.21
144.46
144.31
144.60
144.70
144.83
145.01
144.61
144.81
144.74
144.82
144.82
144.87
144.50
144.56
144.73
144.93
145.08
144.70
144.94
144.89
144.95
144.85
145.50
144.81
144.95
144.75
144.21
144.07
143.93
143.94
144.15
144.62
144.35
145.23
145.60
Scale Variance if
Item Deleted
208.142
210.821
210.324
211.349
208.485
207.850
203.249
205.217
206.796
208.734
205.352
204.920
204.486
208.115
209.699
209.117
208.587
205.971
202.294
205.079
207.021
211.012
207.299
202.783
196.976
203.385
200.022
207.636
210.917
210.910
213.176
212.418
210.012
203.877
205.578
220.105
220.653
9
Corrected ItemTotal Correlation
.439
.405
.374
.340
.366
.405
.511
.433
.436
.416
.495
.540
.580
.403
.320
.390
.390
.455
.538
.478
.348
.233
.482
.564
.542
.609
.646
.457
.428
.424
.356
.401
.424
.597
.651
-.077
-.097
Squared Multiple Cronbach's Alpha
Correlation
if Item Deleted
.
.897
.
.897
.
.898
.
.898
.
.898
.
.897
.
.895
.
.897
.
.897
.
.897
.
.896
.
.895
.
.894
.
.897
.
.898
.
.897
.
.897
.
.896
.
.895
.
.896
.
.898
.
.900
.
.896
.
.894
.
.895
.
.894
.
.893
.
.896
.
.897
.
.897
.
.898
.
.898
.
.897
.
.894
.
.894
.
.904
.
.905
As with other reliability coefficients, alpha should be above .70; (Leech, et al., 2005)
(Table 2)
Table 2: Reliability Statistics
Cronbach's Alpha
Cronbach's Alpha
N of Items
Based on
Standardized
Items
.899
.903
37
Regression
Multicollinearity (or collinearity) in low degree expected in this study because as we
discussed earlier SCM itself depending on information sharing between suppliers, customers and
organization. But Multicollinearity occurs when there are high intercorrelations among some set
of the predictor variables for this reason, it is important to test for multicollinearity when doing
regression.
Table 3: Correlations
Organizational
Performance
1.000
Knowledge
Sharing Mean
.570
Knowledge Sharing Mean
.570
1.000
.653
SCM Practices
.739
.653
1.000
.
.000
.000
Knowledge Sharing Mean
.000
.
.000
SCM Practices
.000
.000
.
Organizational Performance
84
84
84
Knowledge Sharing Mean
84
84
84
SCM Practices
84
84
84
Organizational Performance
Pearson Correlation
Organizational Performance
Sig. (1-tailed)
N
SCM Practices
After eliminate variables` questions that are highly correlated, correlation matrix:
10
.739
Table 4: Correlations
Organizational
Knowledge
Performance
Sharing
Organizational Performance
Pearson Correlation
1.000
.576
.731
Knowledge Sharing
.576
1.000
.614
SCM Practices
.731
.614
1.000
.
.000
.000
Knowledge Sharing
.000
.
.000
SCM Practices
.000
.000
.
Organizational Performance
84
84
84
Knowledge Sharing
84
84
84
SCM Practices
84
84
84
Organizational Performance
Sig. (1-tailed)
N
SCM Practices
As we can see table above there still is a collinatory between the SCM practices and
Knowledge sharing. It is natural consequence of SCM under very circumstances because SCM
practices depend on using IT structure and information flow between organization and suppliers
and customers. But even though information sharing contains sharing practices and IT structure
it is more than that like trust, strategically thinking and planning collaborate and sharing other
important intellectual capital like interorganizational process rather than only product
information. (Malhotra, 2000) But we will see from Coefficients table below that in this
example, we do not need to worry about multicollinearity.
Table 5: Coefficientsa
Unstandardized Coefficients
Model
B
1
Standardized
Coefficients
Std. Error
(Constant)
.943
.330
Information Sharing
.197
.090
SCM Practices
.612
.094
t
Sig.
Beta
Collinearity Statistics
Tolerance
VIF
2.861
.005
.204
2.185
.032
.623
1.604
.605
6.485
.000
.623
1.604
a. Dependent Variable: Organizational Performance
Tolerance and VIF give the same information. (Tolerance = 1 /VIF) They tell us if there
is multicollinearity. If the Tolerance value is low (< 1-R2), then there is probably a problem with
multicollinearity (Leech et al., 2005, p 90). In this case, since adjusted R2 is .56, and 1- R2 is
11
about .44, then tolerances are high for Information sharing and SCM practices indicating that
there isn`t too much multicollinearity (overlap between predictors) exists.
Table 6: Model Summary
Model
R
R Square
.748a
1
Adjusted R
Std. Error of the
Square
Estimate
.560
.549
.32711
a. Predictors: (Constant), SCM Practices, Knowledge Sharing
Model summary, indicates that 56% of the variance can be predicted from the
independent variables.
Table 7: ANOVAa
Model
Sum of Squares
Regression
1
df
Mean Square
11.633
2
5.817
8.641
81
.107
Residual
F
54.522
Sig.
.000b
Total
20.275
83
a. Dependent Variable: Performance Mean
b. Predictors: (Constant), Knowledge Sharing Mean, SCM practices mean
Our model significantly predicts organizational performance. ANOVA table indicates
that the combination of these variables significantly (p < .001) predicts the dependent variable.
So our model significantly predicts organizational performance. Now we can accept H1.
H3 rejected due to the coefficients table. As we can see information sharing is not
significant on organizational performance (sig .032). Same results can be seen in the other
studies as well (Ozciftci, 2009, p 149).
Hierarchical Multiple Linear Regression
We will use the hierarchical approach, which enters variables in a series of blocks or
groups, enabling the researcher to see if each new group of variables adds anything to the
prediction produced by the previous blocks of variables.
12
Table 8: Variables Entered/Removeda
Model
Variables Entered
Variables
Method
Removed
1
2
SCM Practicesb
. Enter
Knowledge
. Enter
Sharingb
a. Dependent Variable: Organizational Performance
b. All requested variables entered.
In the first column of this table there are two models (1 and 2). This indicates that first
we tested a model with SCM as a predictor, and then we added the other predictor (Knowledge
sharing) and tested that model (Model 2).
Table 9: Model Summary
Model
R
R Square
Adjusted R
Std. Error of
Square
the Estimate
Change Statistics
R Square
F Change
df1
df2
Sig. F
Change
.731a
1
.534
.528
Change
.33456
.534
93.926
1
82
.000
2
.560
.549
.32711
a. Predictors: (Constant), SCM Practices
b. Predictors: (Constant), SCM Practices, Knowledge Sharing
.026
4.775
1
81
.032
.748b
The Model Summary (Table 9) output shows there were two models run: Model 1 (in the
first row) and Model 2 (in the second row). It also shows that the addition of Information sharing
did not improve on the prediction by SCM practices alone, explaining only .026% additional
variance.
We can see from the ANOVA table that when SCM is entered by itself, it is a significant
predictor of performance, F (l, 82) = 93.9, p < .001; however, the model with the addition of the
other predictor variable is a better model for predicting organizational performance F (4, 68) =
54.5, p < .001. That Model 2 is better than Model 1 can also be seen in the Model Summary table
by the increase in the adjusted R2 value from R2 = .528 to an R2= .549.
Effect of Information Sharing on SCM (H2)
The correlation between IS and SCM has already been checked (Table 4) and high
correlation was found. Now we should see the regression between each factor:
13
Table 10: ANOVAa
Model
Sum of Squares
Regression
1
Residual
df
Mean Square
7.249
1
7.249
11.998
82
.146
Total
19.247
a. Dependent Variable: SCM Practices
b. Predictors: (Constant), Knowledge Sharing
F
Sig.
.000b
49.545
83
There is a significant relation of information sharing on SCM practices (Table 10).
(p < .001). So information sharing increasing the effectiveness of SCM practices.
Table 11 : Model Summary
Model
R
.614a
1
R Square
Adjusted R
Square
.377
Std. Error of the
Estimate
.369
.38251
a. Predictors: (Constant), Knowledge Sharing
Table 11, indicates that 36% of the variance on dependent variable (SCM Pracatices) can
be predicted from the independent variable-information sharing.
Table 12: Coefficientsa
Model
Unstandardized
Coefficients
B
Std. Error
(Constant)
1
Knowledge
Sharing
1.460
.350
.586
.083
Standardized
Coefficients
Beta
.614
t
Sig.
Collinearity Statistics
Tolerance
4.170
.000
7.039
.000
1.000
VIF
1.000
a. Dependent Variable: SCM Practices
In this example, we do not need to worry about multicollinearity because the Tolerance
value is close to 1.
Discussion
Organizations should increase their performances at least keep the momentum to practice
SCM practices. But effective SCM practices need an effective instrument: information sharing.
We have already discussed the positive effect of SCM on business performance and our
study shows that SCM has positive correlation on performance. That means better SCM
performance better organizational performance but to do that we also should find more effective
ways and dimensions of information sharing because information sharing is a very complex
14
process which depends on not only IT structure but people, organization, environment, partners,
culture, secrecy, leadership and other dependent/independent variables and all these dimensions
can be subject for future research.
Although Min and Mentzer (2004) and Sin et al. (2005) took the information sharing
(knowledge management), cooperation and long term relationship as a part of SCM they didn’t
searched for correlation between SCM and overall business performance. According to Zhou
(2003) when supply chain dynamism increases, effective information sharing becomes more
important. It is found that there is no positive correlation between information sharing and
organizational performance. This is interesting finding of this research because if not directly,
information sharing indirectly could have increased the organizational performance but it isn’t.
That means as Mentzer (Mentzer et al., 2000, p 550) mentioned before we should consider SCM
as a whole and information sharing is beneficial for the entire SCM (Zhao, 2002, p 17).
According to that we should asses SCM from broader organizational perspective.
Also other constraint is defining the metrics of organizational performance in terms of
information sharing. Information sharing is an instrument which involves nearly all processes of
the organization so it is very hard to separate information sharing and define the metrics of
performance on that.
Succinctly we see that SCM has an important benefactor of organizational performance
and information sharing is critical catalyst for the SCM.
15
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Internet Links
http://www.gaosb.org/kurumsal.php?id=5, Feb, 2013
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