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/>The impact of timely information on organisational performance in a
supply chain
K. W. Green Jr
a
; D. Whitten
b
; R. A. Inman
c
a
School of Business, Henderson State University, Arkadelphia
b
Information and Operations
Management Department, Texas A&M University, Mays School of Business, TX 77843
c
College of
Administration and Business, Louisiana Tech University, Ruston, LA 71272

Keywords: JIT systems; Information systems; Supply chain management; Structural equation
modelling
1. Introduction
Organisations that adopt a supply chain management
strategy (SCMS) are implementing enterprise resourc e
planning (ERP) information systems as a part of the
supply chain infrastructure. When successfully imple-
mented, ERP systems provide the necessary operational,
tactical, and strategic information to supply chain
partners on a just-in-time basis. For the purposes of
this study, the seamless, real-time information provided
by ERP systems is termed JIT-information (JIT-I),
because quality information is made available to users in
the right quantities at the right place, at the right time,
and because ERP systems are designed to remove waste
from the information generation process.
The purpose of this study is to investigate the impact
of SCMS on JIT-I and JIT-I on logistics performance
and organisational performance. Does the seamless,
real-time information (JIT-I) emanating from ERP
systems improve logistics performance and organisa-
tional performance as expected? We theorise a JIT-I
performance model that incorporates:
1. SCMS as an antecedent to JIT-I.
2. JIT-I as directly impacting supply chain
performance.
3. Logistics performance as directly impacting orga-
nisational performance.
4. JIT-I as directly impacting organisational
performance.

equipment, materials and parts’.
JIT strategies, therefore, focus on the elimination of
waste and the full utilisation of resources. Although
JIT was originally focused on the production function
within manufacturing plants, it has expanded to include
the production, purchasing, and sales functions as well
(Claycomb et al. 1999b, Green and Inman 2005).
Olhager (2002) and Vokurka and Lummus (2000)
emphasise that this external extension of the JIT
philosophy to include suppliers and customers requires
that information be openly shared among channel
members. Claycomb et al. (1999b) go so far as to state
that, ‘JIT integrates the entire supply chain’s market ing,
distribution, customer service, purchasing, and produc-
tion functions into one controlled process’.
Siau and Tian (2004) describe three generations of
ERP systems. The first generation focused on single-
company, single-site implementations. The second
extended the system to include multiple sites of a
single organisation. Third generation ERP systems
incorporate multiple sites and multiple companies.
With the third generation, the focus has shifted from
internal efficiencies to the integration and coordination
of mult iple organisations within a supply chain (Siau
and Tian 2004). Third generation ERP systems serve as
a prim ary enabler of successful supply chain manage-
ment (Vokurka and Lummus 2000, Siau and Tian 2004,)
by providing the infrastructure necessary for the
required sharing of information across the entire
supply chain. Implementation of supply chain manage-

from all supply chain processes (Vokurka and Lummus
2000). Third generation ERP systems were developed
and designed to eliminate the time delays and distortion
pointed out by Cigolini et al. (2004). It stands to reason
then that information supplied by ERP systems may be
labelled as JIT-information. The systems drive waste
from the information generating processes within the
supply chain and provide quality information on a JIT
basis (right-form, right-place, right-time).
2.1 Construct definitions
Wisner (2003, p. 7) described a supply chain manage-
ment strategy as ‘ideally a linkage of internally-focused,
mature, and successful supplier/customer-oriented cap-
abilities throughout the supply chain’s members’. The
objectives of such a strategy are to provide the supply
chain’s final customers with the quantity and quality
of goods and services at the precise time desired by the
customers.
ERP systems are implemented with the primary aim
of generating JIT-information for supply chain partners.
JIT-information is, therefore, defined as information
generated by ERP systems that is seamlessly shared
among manufacturers, suppliers, and customers on a
real-time basis throughout the full extension of the
supply chain (Vokurka and Lummus 2000, Olhager
2002, Rajagopal 2002, Wisner 2003).
Logistics performance captures a measure of
performance external (manufacturer/supplier) to the
The impact of timely information on organisational performance in a supply chain 275
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JIT-information.
The empirical work by Claycomb et al. (1999b)
alludes to a link between implementation of a total
JIT system with logistics performance. They found that
firms implementing JIT-purchasing, JIT-production,
and JIT-selling as an integrated strategy reduced
out-bound (logistics-related) inventory levels. JIT-
information as described facilitates this necessary
collaboration and integration resulting in improved
logistics performance. Hypothesis 2 follows from the
theoretical justification and empirical evidence.
H2: JIT-information is positively associated with
logistics performance.
Organisational strategies that support supply chain
strategies should strengthen the competitive position of
the supply chain which, in turn, enhances performance
of each of the individual supply chain partners.
Although no empirically tested measure of supply
chain performance was found, logistics performance
focuses outside the manufacturing function on the
manufacturer/customer relationshi p, and, as Bowersox
et al. (2000) describe it, logistics performance is a
reflection of supp ly chain superiority. Based upon the
theoretical justification, hypothesis 3 is stated as follows:
H3: Logistics performance is positively associated
with organisational performance.
ERP systems produce integrated information that is
seamlessly available in real-time to all supply chain
participants. This seamless, integrated, real-time infor-
mation supports decision making at the operational,

(Vokurka and Lummus 2000), quick response to
changes in customer demand facilitated by resulting
accurate and timely information (Cigolini et al. 2004),
and internal cost savings in functional areas such as
warehousing, manufacturing, and accounting via the
adoption of information technologies (Patterson et al.
2004). This empirical evidence theoretically justifies
hypothesis 4.
H4: JIT-information is positively associated with
organisational performance.
3. Methodology
Plant and operations managers working for large US
manufacturers were surveyed using a traditional initial
276 K. W. Green Jr et al.
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and follow-up mailing procedure. Plant and operations
managers were targeted because of their particular
knowledge related to manufacturing, purchasing, sell-
ing, and information related processes within their
organisations. A mailing of 1600 packets resulted in
18 returned due to bad addresses. Further, 121
‘non-participating’ forms were returned. One hundred
and forty-two manufacturers responded with completed
instruments for a response rate of 9.7%. All of the
respondents indicated that they worked for manufactur-
ing organisations. Sixty-two percent of the respondents
identified themselves specifically as plant or ope rations
managers. An additional 15% held purchasing and
inventory management positions. Nineteen specific
manufacturing SIC codes were identified. Respondents

common method bias may lead to inflated estimates of
the relationshi ps between the variables (Podsakoff and
Organ 1986). Harman’s one-factor test was used post
hoc to examine the extent of the potential bias.
Substantial common method variance is signalled by
the emergence of either a single factor or one ‘general’
factor that explains a majority of the total variance
(Podsakoff and Organ 1986). Results of the factor
analysis revealed six factors, whi ch combined to account
for 73% of the total variance. While the first factor
accounted for 33% of the total variance, it did not
account for a majority of the variance. Based upon these
results, problems associated with common method bias
are not considered significant.
4. Results
4.1 Measurement of constructs
Because JIT-I has not been previously measured, it was
necessary to develop a new two-factor, multi-item scale.
Seventeen items were developed from a careful analysis
of the related literature. The first eight items focus on
the seamless, real-time characteristics of JIT-I and were
primarily developed from descriptions provided by
Vokurka and Lummus (2000). The last nine items
focus on the integration characteristic of JIT-I and were
derived from the works of Wisner (2003), Olhager
(2002), Freeland (1991) and Rajagopal (2002). A
12-item scale developed by Wisner (2003) was used to
measure supply chain management strategy.
Respondents were asked to indicate the importance of
the listed issues and concerns to their organisation’s

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performance scale was assessed as a two factor scale
(Green and Inman 2005). Generally, items with
standardised coefficients less than 0.70 and items that
contributed to standardised residuals with values greater
than 3.00 or less than À3.00 were deleted (Raykov
and Marcoulides 2000). The scales and factors, as
re-specified, yielded Goodness-of-fit index (GFI)
values greater than 0.90 (Ahire et al. 1996),
non-normed-fit index (NNFI) and comparative-fit
index values great er than 0.90 (Garver and Mentzer
1999), and root mean square error of approximation
(RMSEA) values between 0.05 and 0.08 (Garver and
Mentzer 1999), indicating sufficient unidimensionality.
Scale items remaining after re-specification are identified
in table 1.
Alpha and construct-reliability values greater than or
equal to 0.70 and a variance-extracted measure of 0.50
or greater indicate sufficient scale or factor reliability
(Garver and Mentzer 1999). The alpha, constr uct-
reliability, and variance-extracted values for each of
the re-specified scales and factors exceeded the recom-
mended values indicating sufficient reliability.
Table 1. Measurement scales.
JIT-information
Please indicate the extent to which agree or disagree with each statement (1 ¼ strongly disagree, 7 ¼ strongly agree).
1. We are able to more quickly respond to customer needs by sharing information with our suppliers.
2. Information flows seamlessly between the suppliers, manufacturers and customers in our supply chain.
3. We openly share information with our suppliers and customers.
4. Our suppliers and customers openly share information with us.

Please rate your company’s performance in each of the following areas as compared to the performance of your competitors (1 ¼ much
worse than competition, 7 ¼ much better than competition)
1. Customer satisfaction.
2. Delivery speed.
3. Delivery dependability.
4. Responsiveness.
5. Delivery flexibility.
6. Order fill capacity.
278 K. W. Green Jr et al.
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Convergent validity was assessed using the normed-fit
index coefficient as recommended by Ahire et al. (1996)
with values greater than 0.9 indicating strong validity.
The NFI for each of the scales exceeds the 0.90 level
indicating sufficient convergent validity. Discriminant
validity was using a chi-square difference test for each
pair of scales under consideration, with a statistically
significant difference in chi-squares indicating validity
(Ahire et al. 1996, Gerbing and Anderson 1988, Garver
and Mentzer 1999). All possible pairs of the study scales
were subjected to chi-square difference tests with each
pairing producing a statistically significant difference
indicating sufficient discriminant validity. Predictive
validity was assessed by determining whether the scales
of interest correlate as expected wi th other
measures (Ahire et al. 1996, Garver and Mentzer
1999). A review of the correlation matrix (table 2) for
the study values supports claims of predictive validity
for each study variable. The study variables
are positively correlated with the coefficients significant

between JIT-I and organisational performance is sig-
nificant at the 0.01 level with a standardised estimate
of 0.26 and an associated t-value of 3.10.
As theorised, a supply chain management strategy
is antecedent to the provision of JIT-information to
all supply chain partners. Further, the provision of
JIT-information leads to improved logistics
Table 2. Descriptive statistics and correlations.
Mean Standard deviation Skewness Kurtosis
A. Descriptive statistics (n ¼ 142)
Supply chain management strategy (SCMS) 5.03 1.08 À0.542 0.724
JIT-information (JIT-I) 3.84 1.20 0.128 À0.550
Logistics performance (LP) 5.42 0.88 À0.915 1.250
Organisational performance (OP) 4.60 1.15 À0.234 À0.041
B. Correlation matrix (n ¼ 142)
SCMS JIT-I LP OP
SCMS 1.000
JIT-I 0.495** 1.000
LP 0.276** 0.381** 1.000
OP 0.242** 0.331** 0.281** 1.000
**Correlation is significant at the 0.01 level (two-tailed).
Logistics
performance
Financial/marketing
performance
Just-in-time
information
0.38 (4.90**)
0.18 (2.14*)
0.26 (3.10**)

noted, a more direct assessment of the potential bias
utilising data from a third wave and an intensive follow-
up on non-respondents would have strengthened the
study. Because responses related to both the dependent
and independen t variables were collected from the same
individual, the potential for common method bias was a
concern. While subsequent testing for the bias relieved
the concern, collection of the strategy and performance
data from separate sources would also have strength-
ened the study.
Of the scales used, only the organisational perfor-
mance scale s had bee n previously subjected to a
thorough assessment of unidimensionality, reliability
and validity. The JIT-information scale was newly
developed, and the supply chain management strategy
and logistics performance scales were necessarily
re-specified to achieve unidimensional ity leaving these
scales with somewhat fewer items that originally
specified (Bowersox et al. 2000, Wisner 2003). Such
re-specification may result in the loss of items important
to the definition of the original construct. It was
determined, however, that the importance of using
uni-dimensional scales overrode this concern.
As Mabe rt et al. (2003) found, small, medium, and
large manufacturers have adopted ERP systems capable
of meeting the information needs of supply chain
partners. They found that firm size significantly
impacted why and how firms implemented ERP systems
and in the benefits that firms accrued following the
implementation. This study focused only on relatively

managers that the adoption of a JIT-information
strategy leads to improvements in organisational
performance.
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Kenneth W. Green Jr is Associate Professor of Management at Henderson State University. He has
published papers in International Journal of Production Research, International Journal of Human
Resource Management, Journal of Business and Industrial Marketing, Supply Chain Management: An
International Journal, Industrial Management and Data Systems and Journal of Computer Information
Systems.
Dwayne Whitten is an Assistant Clinical Professor of Information Systems in the Mays School of
Business at Texas A&M University. His main research interests include IT outsourcing, IT security,
and supply chain efficiency. He has published in several business and information systems related
journals including the Harvard Business Review, European Journal of Information Systems, Decision
Sciences Journal, Journal of Strategic Information Systems, Communications of the AIS, Journal of