Tài liệu The impact of timely information on organisational performance in a supply chain

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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

Online publication date: 22 October 2010
To cite this Article Green Jr, K. W. , Whitten, D. and Inman, R. A.(2007) 'The impact of timely information on
organisational performance in a supply chain', Production Planning & Control, 18: 4, 274 — 282
To link to this Article: DOI: 10.1080/09537280701243926
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Production Planning & Control,
Vol. 18, No. 4, June 2007, 274–282
The impact of timely information on organisational
performance in a supply chain
K. W. GREEN Jr*y, D. WHITTENz and R. A. INMANx
ySchool of Business, Henderson State University, Box 7762, Arkadelphia, AR 71999
zInformation and Operations Management Department, Texas A&M University,
Mays School of Business, Mailstop 4217, College Station, TX 77843
xCollege of Administration and Business, Louisiana Tech University,
PO Box 10318, Ruston, LA 71272
Information produced by ERP systems is termed JIT-information, since it is provided at the
right time in the right place with a minimum of waste. The JIT-information construct is
defined and described and a measurement scale is developed. A JIT-information performance
model is proposed and assessed using a structural equation modelling methodology. The
results indicate that the model fits the data well: (1) supply chain management strategy
positively impacts JIT-information, (2) JIT-information directly impacts both logistics and
organisational performance, and (3) logistics performance directly impacts organisational
performance.

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.

Using a traditional two-wave mailing methodology,
data were collected from 142 manufacturers who
primarily work as plant and operations managers and
used to assess the proposed model.
A review of the literature and discussion of the study
hypotheses follow in the next section. A discussion of
the methodology employed in the study is then
presented followed by a description of the results of
the scale assessment and the structural equation model-
ling results. Finally, a conclusions section, which
*Corresponding author. Email:
Production Planning and Control
ISSN 0953–7287 print/ISSN 1366–5871 online ß 2007 Taylor & Francis
/>DOI: 10.1080/09537280701243926
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incorporates discussions of the contributions of the
study, limitations of the study, suggestions for future
related research, and implications for practising
managers.
2. Literature review and hypotheses
According to Vokurka and Lummus (2000), low cost,
high quality, and improved responsiveness are three
strategic imperatives that have evolved over the last
century. Vokurka and Lummus (2000) further describe
how adoption of the JIT philosophy and associated
practices can balance these strategies within supply
chains. Wisner et al. (2005, p. 208) describe JIT as a
philosophy ‘encompassing continuous problem solving
to eliminate waste’. Davy et al. (1992, p. 655) expand the
definition to include ‘the full utilisation of people,

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-

ment strategies requires that organisations within supply
chains mutually and openly share information with both
suppliers and customers (Morash and Clinton 1997,
Vokurka and Lummus 2000, Mentzer et al. 2001).
Well designed and successfully implemented ERP
systems supply operational, tactical, and strategic
information to all supply ch ain members (Morash and
Clinton 1997, Siau and Tian 2004). Rajagopal (2002)
aptly describes the value of ERP systems as providing
‘one single information’ that is available to all supply
chain members. This ‘one single information’ is accessed
seamlessly (Siau and Tian 2004) in real-time (Gefen and
Ragowskyrik 2005). Competition at the supply chain
level requires integration of all chain partners.
Operational, tactical, and strategic information accessed
seamlessly and in real-time enables this desired
end-to-end connectivity (Rajagopal 2002).
The seamless, real-time characteristics of third gen-
eration ERP systems support the provision of quality
information to supply chain partners in the right form ,
in the right place, and at the right time. Customer
demand for information is no longer requir ed to work
its way from the customer sequentially through multiple
information systems to retailers, to wholesalers, to
manufacturers, to suppliers, resulting in time delays
and distortion (Cigolini et al. 2004). Today, customer
information is entered directly into the supply chain
database and is accessible by all members of the supply
chain.
The JIT philosophy requires that waste be eradicated

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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manufacturing firm. Firms operating within high
performing supply chains exhibit high levels of
logistics performance (Bowersox et al. 2000). Logistics
performance incorporates customer service, quality, and
productivity related to the delivery of goods to
customers (Bowersox et al. 2000).
Organisational performance encompasses both finan-
cial and marketing performance at the firm level (Green
and Inman 2005). Financial performance focuses on
a firm’s return on investment, return on sales,
and profitability as compared to its competition. The
marketing performance component compares the firm’s
sales volume, sales growth, and market share as
compared to its competition.
2.2 Hypotheses
The top managers of US manufacturing organisations
believe that supply chain management is critical to the
success of their individual organisations (Patterson et al.
2004). Successful supply chain management requires
significant integration of all supply chain partners (Ho
et al. 2002, Siau and Tian 2004), and this integration is
enabled with information supplied on a JIT-basis
(Vokurka and Lummus 2000, Rajagopal 2002).
Patterson et al. (2004, p. 6) go so far as to describe
information technology as the ‘crux of modern supply
chain management’. Firms that adopt a supply chain
management strategy must, therefore, necessarily
develop enabling information systems.
H1: A supply chain management strategy is
positively associated with the development of

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,

tactical, and strategic levels. ERP systems are designed
to eliminate waste associ ated with the local development
and sequential movement of information through a
supply chain from organ isation to organisation.
In essence, ERP systems provide infor mation on a JIT
basis. While JIT-I has not been specifically studied, JIT
strategies, such as JIT-manufacturing, JIT-purchasing
and JIT-selling, have been found to improve organisa-
tional performance (Inman and Mehra 1993, Germain
and Dro
¨
ge 1997, Germain and Dro
¨
ge 1998, Claycomb
et al. 1999a, b, Brox and Fader 2002, Kinney and
Wempe 2002, Green and Inman 2005).
Considering that waste is eliminated from the
information generat ing processes within the supply
chain, Stratman and Roth (2002) hypothesise that
ERP competence is an antecedent to improved business
performance. They further identify integration with
suppliers and customers, enabled by the availability of
JIT-I, as measures of improved business performance.
Other benefits of ERP implementation have been found
to include reduced direct operating costs, lower inven-
tory levels and improved cash flow management
(Mabert et al. 2003), enhanced cross-functional coordi-
nation (Rajagopal 2002), better managed inventories
resulting from integration, coordination, and colla-
boration fostered by the availability of information

(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

represented 33 different states.
The response rate is not atypical of that obtained in
industrial research (Harmon et al . 2002). Other report ed
response rates under similar circumstances are: 7.5%
(Nahm et al. 2003, Nahm et al. 2004), 9.6% (Mabert
et al. 2003), 10.8% (Harmon et al. 2002), and 6.7% (Tan
et al. 2002). While manufacturing managers are the
prime source for supply chain management related data,
they are often under severe time and resource
constraints.
Non-response bias was assessed using a common
approach described by Lambert and Harrington (1990)
in which the responses of early and late respondents are
compared. Fifty-four percent (77) of the study respon-
dents were categorised as early respondents and 46%
(65) were categorised as late respondents. A comparison
of the means of the descriptive variables and the scale
items for the two groups was conducted using one-way
ANOVA. With one exception, the comparisons resulted
in statistically non-significant differences. The exception
was for an item in the logistics performance scale that
was ultimately eliminated during the assessment for
unidimensionality. Because non-respondents have been
found to descriptively resemble late respondents
(Armstrong and Overton 1977), this finding of general
equality between early and late respondents supports the
conclusion that non-response bias is not a major
concern.
When data for the independent and dependent
variables are collected from single informants,

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

supply chain efforts. Logistics performance was mea-
sured using a 13-item scale developed by Bowersox et al.
(2000). Respondents were asked to rate their organis a-
tion’s performance compared to that of their competi-
tors on the performance metrics relat ed to custom er
service, cost management, quality, productivity, and
asset management performance metrics. A previously
used two-factor, seven-item organisational performance
scale (Green and Inman 2005) assessed both the
financial and marketing performance of the
organisation.
Quality measurement scales must exhibit content
validity, unidimensionality, reliability, discriminant
validity, convergent validity, and predictive validity.
Since the SCMS, supply chain performance, and
organisational performance scales were taken directly
from prior research (Bowersox et al. 2000, Wisner 2003,
Green and Inman 2005), content validity is assumed.
Items for the JIT-I scale were gleaned from a careful
review of the literature to ensure content validity.
Unidimensionality was assessed using confirmatory
factor analysis as recommended by Gerbing and
Anderson (1988). Re-specification of the JIT-I, supply
chain strategy, and logistics performance scales was
necessary to achieve sufficient dimensionality. JIT-I was
assessed as a two factor scale and subsequently reduced
to nine items, the supp ly chain strategy scale was reduced
from 13 to seven items, and the logistics performance
scale from 13 to six items. The organisational
The impact of timely information on organisational performance in a supply chain 277

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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.

5. The information shared by participants (suppliers, manufacturers and customers) in our supply chain is available on a real-time
basis.
6. Our customers make inventory and sales information visible to us on a real-time basis.
7. Visibility of customer inventory and sales information has allowed us to quickly replenish customer’ inventories with precise
quantities at precise locations at precise times.
8. Information distortion is minimized throughout our supply chain through quick, frequent and accurate information transfer
among supply chain members.
9. As a part of our supply chain management efforts, we have worked to develop an information system that is compatible with the
systems of our suppliers and customers.
Supply chain management strategy
Please indicate the importance of each of the following issues/concerns to your organisation’s supply chain management efforts (1 ¼ low
importance, 7 ¼ high importance
1. Reducing response times across the supply chain.
2. Searching for new ways to integrate SCM activities.
3. Creating a greater level of trust throughout the supply chain.
4. Identifying and participating in additional supply chains.
5. Establishing more frequent contact with supply chain members.
6. Involving all supply chain members in your firm’s product/service marketing plans.
7. Communicating your firm’s future strategic needs to suppliers.
Organisational performance
Please rate your organisation’s performance in each of the following areas as compared to the industry average (1 ¼ well below industry
average, 2 ¼ well above industry average)
1. Average return on investment over the past three years.
2. Average profit over the past three years.
3. Profit growth over the past three years.
4. Average return on sales over the past three years.
5. Average market share growth over the past three years.
6. Average sales volume growth over the past three years.
7. Average sales (in dollars) growth over the past three years.
Logistics performance

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

at the 0.01 level.
4.2 Structural equation modelling results
Summary values for the study variables were computed
by averaging across the items in the scales.
Descriptive statistics and the correlation matrix for the
summary variables are presented in table 2. All
correlation coefficients are positive and significant at
the 0.01 level.
Figure 1 illustrates the model with the structural
equation modelling results specified in the LISREL 8.7
output. The relative chi-square (chi-square/degrees of
freedom) value of 1.25 is less than the 3.00 maximum
recommended by Kline (1998). The root mean square
error of approximation (0.04) is below the recommended
maximum of 0.08 (Schumacker and Lomax 1996) and
values for NFI (0.98), GFI (0.99), and adjusted-GFI
(0.96) all exceed the recommended 0.90 level indicating
good fit (Schumacker and Lomax 1996).
In addition to an overall good fit for the model, all
study hypotheses are supported by the standardised
estimates and associated t-values. The relationship
between SCMS and JIT-I (hypothesis 1) is significant
at the 0.01 level with an estimate of 0.50 and t-value of
6.28. The estimate of 0.38 for the relationship between
JIT-I and logistics performance (hypothesis 2) is
significant at the 0.01 level with a t-value of 4.90. The
relationship between logistics perfor mance and organi-
sational performance (hypothesis 3) is significant at the
0.05 level with an estimate of 0.18 and t-val ue of 2.14
indicating significance at the 0.05 level. The relationship

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**)

0.50 (6.28**)
Supply chain
management
strategy
Figure 1. Theorized JIT-information performance model with
standardised estimates and (t-values). Relative chi-
square ¼ 1.25; chi-square P -value ¼ 0.29; GFI ¼ 0.99;
RMSEA ¼ 0.04. **Significant at 0.01 level; *Significant at
0.05 level.
The impact of timely information on organisational performance in a supply chain 279
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performance and organisational performance, and
logistics performance is also shown to impact organisa-
tional performance.
5. Conclusions
The JIT-information structural model achieved ‘good-
fit’ status and support was found for all study
hypotheses. Adoption of a supply chain management
strategy necessitates development of an information
systems infrastructure capable of providing JIT-infor-
mation to all supply chain partners. The availability
of such seaml ess, real-time information positively
impacts organisational performance both directly and
indirectly through logistics performance.
While the objectives of the study were successfully
accomplished, limitations of the study should be noted.
A survey methodology was used that resulted in
a relatively low response rate raising concerns of
potential non- response bias. Although the two waves
of responses were compared and no evidence of bias was

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

large US manufacturers. Noting the differences based
on firm size found by Mabert et al. (2003), generalising
the findings of this study to small- and medium-sized
manufacturing firms should be done with caution.
The narrow focus on relative ly large manufacturers
points to the need to survey both small- and medium-
sized manufacturing firms. Further, since the da ta
analysed were collected from manufacturers, the results
support implementation of the JIT-information perfor-
mance model in a manufacturing context. Supply chain
management is a strategic initiative that has application
in the service and governmental sectors as well as the
manufacturing sector. All sectors have the need for
seamless, real-time information provided on a JIT basis.
Because of the fundamental differences in the sectors
specifically in terms of how production processes are
designed and how performance is measured, it is not
possible, based upon the reported results, to generalise
the efficacy of a JIT-information strategy to these other
sectors. Future research in the service and governmental
sectors is recommended.
JIT-information is made available through the
successful implementation and operation of enterprise
resource systems. Such ERP systems are very expensive
to design, implement, and maintain and the benefits are
difficult to identify precisely. Before expending millions
of dollars and thousands of man-hours to implement an
ERP system, managers want to know that the benefits
will significantly exceed the costs. The results presented
here serve to provide some assurance to manufacturing

managers that the adoption of a JIT-information
strategy leads to improvements in organisational
performance.
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The impact of timely information on organisational performance in a supply chain 281
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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

Organizational and End User Computing, Journal of Computer Information Systems, Industrial
Management and Data Systems, Journal of International Technology and Information Management,
International Journal of Mobile Communications, International Journal of Electronic Healthcare and
International Journal of Human Resources Management.
R. Anthony Inman is Ruston Building and Loan Professor of Management at Louisiana Tech
University. He has published papers in Decision Sciences, Interfaces, International Journal of
Production Research, International Journal of Operations and Production Management, Production
and Inventory Management Journal, International Journal of Service Industry Management,
Production Planning and Control and International Journal of Quality and Reliability Management.
282 K. W. Green Jr et al.
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