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The impact of logistics performance on organization

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TheImpactofLogisticsPerformanceon
OrganizationalPerformanceinaSupplyChain
Context
ArticleinSupplyChainManagement·June2008
DOI:10.1108/13598540810882206

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Research paper

The impact of logistics performance on
organizational performance in a supply chain
context
Kenneth W. Green Jr
College of Business Administration, Department of Management and Marketing, Sam Houston State University, Huntsville, Texas, USA

Dwayne Whitten
Texas A&M University, Mays School of Business, Information and Operations Management Department, College Station, Texas, USA,
and

R. Anthony Inman
College of Administration and Business, Louisiana Tech University, Ruston, Louisiana, USA
Abstract
Purpose – The paper’s aim is to theorize and assess a logistics performance model incorporating logistics performance as the focal construct with
supply chain management strategy as antecedent and organizational performance, both marketing and financial, as consequences.
Design/methodology/approach – Data from a national sample of 142 plant and operations managers are analyzed using a structural equation
modeling methodology.


Findings – The results indicate that logistics performance is positively impacted by supply chain management strategy and that both logistics
performance and supply chain management strategy positively impact marketing performance, which in turn positively impacts financial performance.
Neither supply chain management strategy nor logistics performance was found to directly impact financial performance.
Research limitations/implications – To compete at the supply chain level, manufacturers must adopt a supply chain management strategy. Such a
strategy requires integration and coordination of key external processes such as purchasing, selling, and logistics with supply chain partners. In this
study the focus is limited to the impact of logistics performance on organizational performance within a supply chain context.
Practical implications – As manufacturers work to improve the logistics processes, they support their organization’s supply chain strategy, resulting
in improved performance for the overall supply chain and ultimately their manufacturing organizations.
Originality/value – Organizational managers are being asked to focus directly on supply chain functions such as logistics to bolster the
competitiveness of the supply chains in which their organizations are integral partners. Does such a supply chain focus ultimately result in improved
organizational performance? This study provides evidence that a supply chain focus will enhance logistics performance, which will ultimately result in
improved organizational performance.
Keywords Supply chain management, Organizational performance, Mathematical modelling
Paper type Research paper

chain strategies focus on how both internal and external
business processes can be integrated and coordinated
throughout the supply chain to better serve ultimate
customers and consumers while enhancing the performance
of the individual supply chain members (Cohen and Roussel,
2005). Examples of business processes that must be
integrated include manufacturing, purchasing, selling,
logistics, and the delivery of real-time, seamless information
to all supply chain partners. Managing at the supply chain
level requires a new focus and new ways of managing
(Lambert et al., 1998). Manufacturing managers must learn
to communicate, coordinate, and cooperate with supply chain
partners (t strategy
(SCMS)
Logistics performance (LP)
Financial performance (FP)
Marketing performance (MP)

4.91
5.42
4.63
4.55

B. Correlation matrix (n 5 142)
SCMS
LP
FP
MP

SCMS LP
FP
MP
1.000
*
0.230 * 1.000
*
* 1.000
*
0.193 * 0.243
*
* 0.706
*
* * 1.000
0.248 * 0.225

1.18
.93
1.22
1.30

Note: * *Correlation is significant at the 0.01 level (two-tailed)

A structural assessment of the full measurement model
indicates that the measurement model fits the data moderately
well with a relative chi-square (x2/degrees of freedom) of 2.02,
a RMSEA of 0.08, a GFI of 0.83, an NFI of 0.91, and a CFI
of 0.94. The full measurement model is displayed in Figure 2.
The individual measurement scales are considered sufficiently
unidimensional, reliable and valid and the fit of the
323


Impact of logistics performance on organizational performance

Supply Chain Management: An International Journal

Kenneth W. Green Jr, Dwayne Whitten and R. Anthony Inman

Volume 13 · Number 4 · 2008 · 317 –327

measurement model is considered sufficient to support
further assessment of the structural model.

Generally, the results support the proposition that the
adoption of a supply chain management strategy leads to
improved supply chain performance, as measured by logistics
performance, which in turn leads to improved organizational
performance. It is very difficult to measure overall supply
chain performance directly. The logistics function, however, is
an externally focused supply chain function that has global, as
well as local, implications for managers in the manufacturing
sector.
While the performance of manufacturing managers
continues to be evaluated based on organization-level
metrics related to the sales, market share, and profitability
of the organization, the results of this study support the
contention that manufacturing managers make decisions that
directly support supply chain performance which will, in turn,
enhance organizational performance. This expectation that
local managers first be concerned with and make decisions
that strengthen the supply chain is relatively new and may be
difficult for local managers to embrace. In this supply chain
era, however, success of the organization depends upon the
success of the supply chain or chains in which the
organization operates as a partner. These results support the
propositions that organizations now compete globally at the
supply chain level, that organizational performance depends
directly on supply chain performance, and that local
manufacturing managers focus on and make decisions that
enhance supply chain performance. In short, local
optimization now depends on global optimization. This is a
relatively new mindset but, as the results indicate, an
important one for manufacturing managers.

Structural equation modeling 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 II. All correlation coefficients are positive
and significant at the 0.01 level.
Figure 3 illustrates the model with the structural equation
modeling results specified in the LISREL 8.8 output. The
relative x2 (x2/degrees of freedom) value of 2.02 is less than
the 3.00 maximum recommended by Kline (1998). The root
mean square error of approximation (0.08) equals the
recommended maximum of 0.08 (Schumacker and Lomax,
2004). While NNFI (0.93) is above the recommended 0.90
level (Byrne, 1998), the GFI (0.83) is not. These indices,
however, are more heavily impacted by a relatively small
sample size, and, as Byrne (1998) points out, the comparative
fit index (CFI) and incremental fit index (IFI) are more
appropriate when the sample size is small. The CFI (0.94)
and IFI (0.94) both exceed the recommended 0.90 level
(Byrne, 1998).
Four of the study hypotheses are supported by the
standardized estimates and associated t-values. The
relationship between SCMS and logistics performance (H1)
is significant at the 0.05 level with an estimate of 0.23 and tvalue of 2.52. The estimate of 0.21 for the relationship
between supply chain management strategy and marketing
performance (H2) is significant at the 0.05 level with a t-value
of 2.34. The relationship between supply chain management
strategy and financial performance (H3) is not significant with
an estimate of 0.00 and t-value of .04. The relationship
between logistics performance and marketing performance
(H4) is significant at the 0.05 level with a standardized
estimate of 0.18 and an associated t-value of 2.02. The
relationship between logistics performance and financial
performance (H5) is not significant with a standardized
estimate of 0.09 and t-value of 1.35. The relationship between
marketing performance and financial performance is
significant at the 0.01 level with a standardized estimate of
0.69 and a t-value of 7.67.

Conclusions
The theorized logistics performance model fits the data
moderately well providing support for four of the six study
hypotheses. As the focal construct, logistics performance is
positively impacted by supply chain management strategy and
directly impacts marketing performance which, in turn,
impacts financial performance. These results support the
positive relationship between logistics performance and
organizational performance within the manufacturing sector.

Figure 3 Theorized logistics performance structural model with standardized coefficients. t-Values are shown in parentheses (relative x2 ¼ 2:02,
GFI ¼ 0:83, CFI ¼ 0:94, RMSEA ¼ 0:08)

324


Impact of logistics performance on organizational performance

Supply Chain Management: An International Journal

Kenneth W. Green Jr, Dwayne Whitten and R. Anthony Inman

Volume 13 · Number 4 · 2008 · 317 –327

References

The success of the individual supply chain partners may
now depends upon the overall success of the supply chain(s)
in which the partners participate. Manufacturing managers
should now consider the implications for the overall supply
chain when making decisions related to their organization’s
manufacturing, purchasing, selling, and logistics processes.
Those processes are integrated and coordinated throughout
the supply chain to better serve the ultimate customers. It has
become critically important to measure the performance at
the supply chain level as well as organizational performance.
The theoretical proposition is that success at the supply chain
level will result in success at the organizational level. The
problem for both practitioners and researchers is that supply
chain performance is relatively difficult to measure. This
study incorporates an established measure of logistics
performance as a surrogate for supply chain performance.
Logistics is clearly a supply chain function in that it links
manufacturers and customers although those customers may
not be the ultimate customers in the supply chain.
The results of this study support the broad contention that
manufacturers should focus on strengthening the supply
chain(s) in which they operate. Successful adoption of a
supply chain management strategy requires a supply chain
focus and efforts by managers to strengthen linkages with
both suppliers and customers. These stronger relationships
result in improved performance of supply chain related
functions such as logistics, purchasing and selling. In this
particular case, a supply chain focus resulted in improved
logistics performance, which in turn led to improved
organizational performance. While organizational managers
will likely still be evaluated on organization-level performance
metrics, the route to enhancing organizational performance
may well be through supply chain performance in the future.
In short, global optimization trumps local optimization.
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 utilizing 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
independent 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 strengthened the study.
The study results have important implications from
manufacturing managers. The sustained, long-term success
of a manufacturing organization now depends upon
developing competitive advantage as a member of one or
more supply chains. While manufacturing managers have
embraced supply chain management as a strategic initiative,
they continue to search for appropriate tactical approaches to
implement the strategy. The logistics processes linking
manufacturer and customers play an important role in
supporting a supply chain management strategy. As
manufactures work to improve the logistics processes, they
support their organization’s supply chain strategy resulting in
improved performance for the overall supply chain and
ultimately their manufacturing organizations.

Ahire, S.L., Golhar, D.Y. and Waller, M.A. (1996),
“Development and validation of TQM implementation
constructs”, Decision Sciences, Vol. 27 No. 1, pp. 23-56.
Anderson, E.W., Fornell, C. and Lehmann, D.R. (1994),
“Customer satisfaction, market share, and profitability:
findings from Sweden”, Journal of Marketing, Vol. 58 No. 3,
pp. 53-66.
Armstrong, J.S. and Overton, T.S. (1977), “Estimating
nonresponse bias in mail surveys”, Journal of Marketing
Research, Vol. 14 No. 3, pp. 396-402.
Armistead, C.G. and Mapes, J. (1993), “The impact of
supply chain integration on operating performance”,
Logistics Information Management, Vol. 6 No. 4, pp. 9-14.
Bowersox, D.J., Closs, D.J., Stank, T.P. and Keller, S.B.
(2000), “How supply chain competency leads to business
success”, Supply Chain Management Review, Vol. 4 No. 4,
pp. 70-8.
Byrne, B.M. (1998), Structural Equation Modeling with
LISREL, PRELIS, and SIMPLIS, Lawrence Erlbaum
Associates, Mahwah, NJ.
Carter, J.R. and Narasimhan, R. (1996), “Purchasing and
supply management: future directions and trends”,
International Journal of Purchasing & Materials
Management, Vol. 32 No. 4, pp. 2-12.
Chen, I.J. and Paulraj, A. (2004), “Towards a theory of
supply chain management: the constructs and
measurements”, Journal of Operations Management, Vol. 22
No. 2, pp. 119-50.
Chopra, S. and Meindl, P. (2004), Supply Chain Management:
Strategy, Planning, and Operation, 2nd ed., Pearson
Prentice-Hall, Upper Saddle River, NJ.
Claycomb, C., Germain, R. and Dro¨ge, C. (1999), “Total
system JIT outcomes: inventory, organization and financial
effects”, International Journal of Physical Distribution and
Logistics, Vol. 29 No. 10, pp. 612-30.
Cohen, S. and Roussel, J. (2005), Strategic Supply Chain
Management: The Five Disciplines for Top Performance,
McGraw-Hill, New York, NY.
Cooper, M.C., Lambert, D.M. and Pagh, J.D. (1997),
“Supply chain management: more than a name for
logistics”, The International Journal of Logistics
Management, Vol. 8 No. 1, pp. 1-14.
Council of Supply Chain Management Professionals (2007),
“Supply chain management and logistics management
definitions”, available at: www.cscmp.org/Website/
AboutCSCMP/Definitions/Definitions.asp.
de Kluyver, C.A. and Pearce, J.A. II (2006), Strategy: A View
from the Top, 2nd ed., Pearson Prentice-Hall, Upper Saddle
River, NJ.
Dunn, S.C., Seaker, R.F. and Waller, M.A. (1994), “Latent
variables in business logistics research: scale development
and validation”, Journal of Business Logistics, Vol. 15 No. 2,
pp. 145-72.
Gammelgaard, B. and Larson, P.D. (2001), “Logistics skills
and competencies for supply chain management”, Journal
of Business Logistics, Vol. 22 No. 2, pp. 27-50.
Garver, M.S. and Mentzer, J.T. (1999), “Logistics research
methods: employing structural equation modeling to test
for construct validity”, Journal of Business Logistics, Vol. 20
No. 1, pp. 33-57.
325


Impact of logistics performance on organizational performance

Supply Chain Management: An International Journal

Kenneth W. Green Jr, Dwayne Whitten and R. Anthony Inman

Volume 13 · Number 4 · 2008 · 317 –327

Gerbing, D.W. and Anderson, J.C. (1988), “An updated
paradigm
for
scale development incorporating
unidimensionality and its assessment”, Journal of
Marketing Research, Vol. 25 No. 2, pp. 186-92.
Green, K.W. Jr and Inman, R.A. (2005), “Using a just-intime selling strategy to strengthen supply chain linkages”,
International Journal of Production Research, Vol. 43 No. 16,
pp. 3437-53.
Green, K.W. Jr, McGaughey, R. and Casey, K.M. (2006),
“Does supply chain management strategy mediate the
association between market orientation and organizational
performance?”, Supply Chain Management: An International
Journal, Vol. 11 No. 5, pp. 407-14.
Green, K.W. Jr, Medlin, B. and Whitten, D. (2004),
“Developing optimism to improve performance: an
approach for the manufacturing sector”, Industrial
Management & Data Systems, Vol. 104 No. 2, pp. 106-14.
Hair, J.F. Jr, Black, W.C., Babin, B.J., Anderson, R.E. and
Tatham, R.L. (2006), Multivariate Data Analysis, 6th ed.,
Pearson Prentice-Hall, Upper Saddle River, NJ.
Harmon, H.A., Brown, G., Widing, R.E. II and Hammond,
K.L. (2002), “Exploring the sales manager’s feedback to a
failed sales effort”, Journal of Business & Industrial
Marketing, Vol. 17 No. 1, pp. 43-55.
Ho, D.C.K., Au, K.F. and Newton, E. (2002), “Empirical
research on supply chain management: a critical review and
recommendations”, International Journal of Production
Research, Vol. 40 No. 17, pp. 4415-30.
Klassen, R.D. and Jacobs, J. (2001), “Experimental
comparison of web, electronic and mail survey
technologies in operations management”, Journal of
Operations Management, Vol. 19, pp. 713-28.
Kline, R.B. (1998), Principles and Practice of Structural
Equation Modeling, Guilford Press, New York, NY.
Lai, K. and Cheng, T.C.E. (2003), “Supply chain
performance in transport logistics: an assessment by
service providers”, International Journal of Logistics:
Research and Applications, Vol. 6 No. 3, pp. 152-64.
Lambert, D.M., Cooper, M.C. and Pagh, J.D. (1998),
“Supply chain management: implementation issues and
research opportunities”, The International Journal of Logistics
Management, Vol. 9 No. 2, pp. 1-19.
Lambert, D.M. and Harrington, T.C. (1990), “Measuring
nonresponse bias in customer service mail surveys”, Journal
of Business Logistics, Vol. 11 No. 2, pp. 5-25.
Larson, P.D. (2005), “A note on mail surveys and response
rates in logistics research”, Journal of Business Logistics,
Vol. 26 No. 2, pp. 211-22.
Larson, P.D. and Halldorsson, A. (2004), “Logistics versus
supply chain management: an international survey”,
International Journal of Logistics: Research and Applications,
Vol. 7 No. 1, pp. 17-31.
Lin, C. (2006), “Influencing factors on the innovation in
logistics technologies for logistics service providers in
Taiwan”, The Journal of American Academy of Business,
Vol. 9 No. 2, pp. 257-63.
Mentzer, J.T., DeWitt, W., Keebler, J.S., Min, S., Nix, N.W.,
Smith, C.D. and Zacharia, Z.G. (2001), “Defining supply
chain management”, Journal of Business Logistics, Vol. 22
No. 2, pp. 1-25.
Meredith, J.R. and Shafer, S.M. (2002), Operations
Management for MBAs, 2nd ed., Wiley, New York, NY.

Morash, E.A. and Clinton, S.R. (1997), “The role of
transportation capabilities in international supply chain
management”, Transportation Journal, Vol. 36 No. 3,
pp. 5-17.
Morash, E.A. and Clinton, S.R. (1998), “Supply chain
integration: customer value through collaborative closeness
versus operational excellence”, Journal of Marketing: Theory
and Practice, Vol. 6 No. 4, pp. 104-20.
Nahm, A.Y., Vonderembse, M.A. and Koufteros, X.A.
(2004), “The impact of organizational culture on timebased manufacturing and performance”, Decision Sciences,
Vol. 35 No. 4, pp. 579-607.
Novack, R.A., Rinehart, L.M. and Wells, M.V. (1992),
“Rethinking concept foundations in logistics management”,
Journal of Business Logistics, Vol. 13 No. 2, pp. 233-67.
Oliver, N. and Delbridge, R. (2002), “The characteristics of
high performing supply chains”, International Journal of
Technology Management, Vol. 23 Nos 1-3, pp. 60-73.
Podsakoff, P.M. and Organ, D.W. (1986), “Self-reports in
organizational research: problems and prospects”, Journal
of Management, Vol. 12 No. 4, pp. 531-44.
Rabinovich, E. and Knemeyer, A.M. (2006), “Logistics
service providers in Internet supply chains”, California
Management Review, Vol. 48 No. 4, pp. 84-108.
Raykov, T. and Marcoulides, G.A. (2000), A First Course in
Structural Equation Modeling, Lawrence Erlbaum
Associates, Mahwah, NJ.
Rodrigues, A.M., Bowersox, D.J. and Calantone, R.J. (2005),
“Estimation of global and national logistics expenditures:
2002 data update”, Journal of Business Logistics, Vol. 26
No. 2, pp. 1-15.
Schramm-Klein, H. and Morschett, D. (2006), “The
relationship between marketing performance, logistics
performance and company performance for retail
companies”, International Review of Retail, Distribution and
Consumer Research, Vol. 16 No. 2, pp. 277-96.
Schumacker, R.E. and Lomax, R.G. (2004), A Beginner’s
Guide to Structural Equation Modeling, Lawrence Erlbaum
Associates, Mahwah, NJ.
Shao, X. and Ji, J. (2006), “Reconfiguration of
pharmaceutical logistics operations in China: an empirical
study”, Transportation Journal, Vol. 45 No. 4, pp. 52-66.
Sheen, G. and Tai, C. (2006), “A study on decision factors
and third party selection criterion of logistics outsourcing:
an exploratory study of direct selling industry”, The Journal
of American Academy of Business, Cambridge, Vol. 9 No. 2,
pp. 331-7.
Srivastava, S.K. (2006), “Logistics and supply chain practices
in India”, VISION – The Journal of Business Perspective,
Vol. 10 No. 3, pp. 69-79.
Stank, T.P., Davis, B.R. and Fugate, B.S. (2005), “A strategic
framework for supply chain oriented logistics”, Journal of
Business Logistics, Vol. 26 No. 2, pp. 27-45.
Stank, T.P., Keller, S.B. and Closs, D.J. (2002),
“Performance benefits of supply chain logistical
integration”, Transportation Journal, Vol. 41 Nos 2/3,
pp. 32-46.
Tan, K.C. (2002), “Supply chain management: practices,
concerns, and performance issues”, Journal of Supply Chain
Management, Vol. 38 No. 1, pp. 42-53.
Tan, K.C., Lyman, S.B. and Wisner, J.D. (2002), “Supply
chain management: a strategic perspective”, International
326


Impact of logistics performance on organizational performance

Supply Chain Management: An International Journal

Kenneth W. Green Jr, Dwayne Whitten and R. Anthony Inman

Volume 13 · Number 4 · 2008 · 317 –327

Journal of Operations and Production Management, Vol. 22
No. 6, pp. 614-31.
Vaidyanathan, G. (2005), “A framework for evaluating thirdparty logistics”, Communications of the ACM, Vol. 48 No. 1,
pp. 89-94.
Vickery, S., Clanatone, R. and Dro¨ge, C. (1999), “Supply
chain flexibility: an empirical study”, Journal of Supply
Chain Management: A Global View of Purchasing and Supply,
Vol. 35 No. 3, pp. 16-23.
Vokurka, R.J. and Lummus, R.R. (2000), “The role of just-intime in supply chain management”, The International
Journal of Logistics Management, Vol. 11 No. 1, pp. 89-98.

Wisner, J.D. (2003), “A structural equation model of supply
chain management strategies and firm performance”,
Journal of Business Logistics, Vol. 24 No. 1, pp. 1-26.

Corresponding author
Dwayne Whitten can be contacted at: contacted at: dwhitten
@mays.tamu.edu

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